MARKER ASSISTED SELECTION FOR RESISTANCE TO RICE YELLOW MOTTLE VIRUS IN FARMERS’PREFERRED RICE VARIETIES IN BURKINA FASO By TRAORE Valentin Stanislas Edgar (10293981) THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF GHANA, LEGON IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR THE AWARD OF DOCTOR OF PHILOSOPHY DEGREE IN PLANT BREEDING WEST AFRICA CENTRE FOR CROP IMPROVEMENT SCHOOL OF AGRICULTURE COLLEGE OF AGRICULTURE AND CONSUMER SCIENCES UNIVERSITY OF GHANA LEGON December, 2013 University of Ghana http://ugspace.ug.edu.gh i DECLARATION I hereby declare that except for references to works of other researchers, which have been duly cited, this work is my original research and that neither part nor whole has been presented elsewhere for the award of a degree. .................................................. TRAORE Valentin Stanislas Edgar (Student) .................................................. Professor Samuel Kwame OFFEI (Supervisor) .................................................. Professor Vernon Edward GRACEN (Supervisor) .................................................. Research Professor Oumar TRAORE (Supervisor) University of Ghana http://ugspace.ug.edu.gh ii ABSTRACT Rice yellow mottle disease (RYMD), caused by Rice yellow mottle virus (RYMV), is a very damaging disease of rice in Sub-Saharan Africa. A participatory rural appraisal was conducted in Burkina Faso to assess farmers' awareness of rice production constraints with emphasis on rice yellow mottle disease (RYMD) and its management. RYMD was mentioned by farmers as the most important rice disease. Management practices included replacement of rice varieties and spray of pesticides. Farmers' choice for rice varieties was based on grain yield and taste as major criteria. Thirty four (34) farmers' rice varieties and 91 varieties from agricultural research institutions in Burkina Faso and Ghana were screened for resistance to RYMV. Partial resistance was found in 29.6% of the varieties, while all other varieieties were susceptible to the virus apart from the high resistance control. Well characterized non-resistance breaking (nRB) isolates of the virus was critical in identifying resistance sources. RYMV1 high resistance gene in Gigante and Bekarosaka (bearing rymv1-2 allele) was introgressed into both susceptible and partial resistant farmers' preferred varieties. Interspecific crosses involving Oryza glaberrima cultivar Tog5681 (bearing rymv1-3 allele of RYMV1 resistance gene) were successful but introgression of the resistance gene to RYMV failed. Recombinant lines were readily genotyped for the presence of the resistance gene at both homozygous and heterozygote states using SNP-markers. Genotypic characterization of recombinant lines was confirmed by assessment of their phenotypes through virus inoculation. Field evaluation of recombinant lines revealed high (77.29%) broad sense heritability estimates for grain yield. Path coefficient analysis indicated that grain yield was highly and positively correlated with plant panicle number (r=0.80), tiller number (r=0.76) and 1000-grain weight (r=0.61) but negatively to above-ground total biomass (r=-0.28). Per plant panicle number had the highest direct and positive effect on grain yield University of Ghana http://ugspace.ug.edu.gh iii (0.94). Major indirect effects on grain yields were exerted by tiller number (0.76), number of days for first flowering (0.72) and above- ground total biomass (0.58). Most recombinant lines performed better than their parents with up to 27.5% highest increase compared to mid-parents. Best performing recombinant lines resulted from crosses involving high resistance donor Gigante or partial resistance donor Digang. From these recombinant lines, several high yielding lines are likely to be developed for release in the near future. By taking into account farmers' preferences, adequate varietal screening process and marker-assisted selection, it can be expected that the new rice varieties to be developed will make great impact in rice production in West Africa. Keywords: rice, recombinant lines, rice yellow mottle virus, resistance, marker-assisted selection, farmers’ preferred varieties. University of Ghana http://ugspace.ug.edu.gh iv DEDICATION To Almighty God, To Neila & Grace my daughters and Yollande my lovely spouse, for their patience; To the Grand Family TRAORE and related; To my late mother and my old father who kept praying for the success of this stud.May God give him longer life to benefit from this study. University of Ghana http://ugspace.ug.edu.gh v ACKNOWLEDGEMENTS To God alone is the all glory! I gratefully acknowledge Alliance for a Green Revolution in Africa (AGRA) who financially supported this five years PhD course and research at West Africa Centre for Crop Improvement (WACCI). My sincere gratitude to, Dr Joe DeVries, Dr I. KAPRAN, and to Dr A. TOURE for their support and their critical advice throughout this study; My heart goes all out with gratefulness to Dr. Rufaro Madakedze for her kind attention and her commitment to ensure that this study will be successfully completed on time (thank you Prof); I am sincerely grateful toWACCI and the University of Ghana for getting this fund from AGRA for accepting my admission and for hosting me to attempt this 5 year PhD course; I am also very indebted to the Faculty staff and WACCI management staff, special mention to Professor E.Y. Danquah for making everything in his power for the successes of this PhD programme; my appreciation and thanks to Enyonam, Vicencia, Mr Miah,Audrey, Rita, Everlove, Nancy, Jennifer, Osei Tutu, Eddie, Kwessi, and Ebeneszer; I also gratefully acknowledge all the lecturers and particularly my supervisory committee, Professor Samuel Kwame OFFEI, Professor Vernon Edward GRACEN and Professor Oumar TRAORE for the precious academic support and the sharp guidance throughout this study, (Profs, I have learnt a lot from your experiences); I am particularly grateful to my in-country supervisor Professor Oumar TRAORE for the critical and so constructive review of the present thesis, to Professor Tongona P. and Professor Derera J. from the University of Kwazulu Natal, for their precious assistance throughout the thesis write up, I am thankful to the Minister of Scientific Research and Innovation (MRSI) of Burkina Faso, Professor KONATE G., former Director of Environmental and Agricultural Research Institute (INERA), and to the present Director Professor LOMPO F. for granting me a study leave in order to pursue this course and providing me full research facilities; University of Ghana http://ugspace.ug.edu.gh vi My sincere gratitude to, Professor BARRO N., Vice-President of the University of Ouagadougou, Professor DABIRE C. B., Director of the INERA/CREAF Entomology- Laboratory, Dr JB-TIGNEGRE, PhD in plant breeding (ACCI) and Dr SOME K., PhD in plant breeding (WACCI), who basically contributed to make possible my application to this PhD programme. Many other people have contributed at different levels to the success of this study, they may not see their names here but I wish to thank all of you, from Kamboinse research station, from Virology and Biotechnology Laboratory, my colleagues Dr Neya B.J., Dr Sereme D.,, Dr Tiendrebeogo F., Mr Moustapha K., Mr Serge O. R., particularly my technical staff including Abdoulaye Zongo, Aristide Zongo, Adissa Ouedraogo, Konate Anatou, Lucien Kabore (master student), Coulibaly Aboubacar (master student), all collaborative rice farmers from Mogtedo and Banzon end, particularly Rasmane Sawadogo (rice farmer) and its son Dieudonne. All my colleagues in the WACCI First, Third and Second Cohort including: Dao (Burkina Faso), Allen, Ruth and Vivian (Ghana), Coulibaly (Niger), Goita and Sako (Mali) Beatrice and Usman (Nigeria), through to the Sixth Cohort, were sources of powerful network and warm collaboration in the frame of this PhD programme. Finally, my prayer goes to late Dr Charles THE who was part of my supervisor team from the beginning; at the early stage he contributed significantly to clear the pathway of this study; may his soul rests in peace eternally in heaven, Amen! University of Ghana http://ugspace.ug.edu.gh vii TABLE OF CONTENTS DECLARATION ......................................................................................................................................... I ABSTRACT ................................................................................................................................................ II DEDICATION ........................................................................................................................................... IV ACKNOWLEDGEMENTS ........................................................................................................................ V TABLE OF CONTENTS ........................................................................................................................ VII LIST OF FIGURES ................................................................................................................................. XII LIST OF TABLES .................................................................................................................................. XIV LIST OF ABBREVIATIONS ................................................................................................................ XVI CHAPTER 1 ............................................................................................................................................... 1 1. GENERAL INTRODUCTION ............................................................................................................. 1 CHAPTER 2 ............................................................................................................................................... 7 2. LITTERATURE REVIEW ................................................................................................................... 7 2.1. Rice origin and domestication............................................................................................... 7 2.2. Rice genetic diversity ............................................................................................................. 9 2.3. Rice yellow mottle disease ................................................................................................... 11 2.3.1. Symptoms and geographical distribution............................................................................ 11 2.3.2. Rice yellow mottle virus ..................................................................................................... 14 2.3.2.1. Taxonomy and genome organization ............................................................................... 14 2.3.2.2. Biochemical properties, transmission and susceptible hosts ........................................... 15 University of Ghana http://ugspace.ug.edu.gh viii 2.3.2.3. Serological and molecular diversity................................................................................. 16 2.4. Virus host interactions ......................................................................................................... 17 2.4.1. Rice genes involved in resistance to RYMV ...................................................................... 17 2.4.2. RYMV genes involved is resistance-breaking in rice......................................................... 21 2.5. Control of rice yellow mottle disease .................................................................................. 23 2.6. Breeding for rice improvement ........................................................................................... 25 2.6.1. Major objectives in rice breeding ....................................................................................... 25 2.6.2. Conventional rice breeding ................................................................................................. 27 2.6.3. Biotechnological and molecular approach in rice breeding ................................................ 28 CHAPTER 3 ............................................................................................................................................. 30 3. IMPACT OF RICE YELLOW MOTTLE DISEASE ON FARMERS’ PREFERRED RICE VARIETIES IN BURKINA FASO ......................................................................................................... 30 3.1. Introduction .......................................................................................................................... 30 3.2. Materials and methods ........................................................................................................ 32 3.2.1. Survey areas ........................................................................................................................ 32 3.2.2. Sampling procedures and data collection ........................................................................... 32 3.2.3. Yield loss and disease incidence assessment in farmers’ field ........................................... 33 3.2.4. Data analysis ....................................................................................................................... 33 3.3. Results ................................................................................................................................... 34 3.3.1. Features of rice production ................................................................................................. 34 3.3.2. Rice varieties grown and farmers' preferred varieties......................................................... 34 3.3.3. Major constraints to rice production ................................................................................... 37 3.3.4. Rice yellow mottle disease and its management ................................................................. 38 University of Ghana http://ugspace.ug.edu.gh ix 3.3.5. Yield loss assessment and disease incidence ...................................................................... 40 3.4. Discussion.............................................................................................................................. 41 CHAPTER 4 ............................................................................................................................................. 45 4. SCREENING OF RICE ACCESSIONS FOR RESISTANCE TO RICE YELLOW MOTTLE VIRUS IN BURKINA FASO .................................................................................................................. 45 4.1. Introduction .......................................................................................................................... 45 4.2. Material and methods .......................................................................................................... 48 4.2.1. Study area............................................................................................................................ 48 4.2.2. Germplasm collection ......................................................................................................... 48 4.2.3. Sources of inoculum ........................................................................................................... 49 4.2.4. Inoculation .......................................................................................................................... 49 4.2.4.1. Virus propagation............................................................................................................. 49 4.2.4.2. Screening of rice accessions ............................................................................................ 51 4.2.5. Data analysis ....................................................................................................................... 52 4.3. Results ................................................................................................................................... 52 4.3.1. Germplasm collection ......................................................................................................... 52 4.3.2. Reactions of rice accessions to mixtures of RYMV isolates .............................................. 53 4.3.3. Virus accumulation in inoculated plants ............................................................................. 59 4.3.4. Reactions of rice accessions to field isolates ...................................................................... 62 4.4. Discussion.............................................................................................................................. 64 CHAPTER 5 ............................................................................................................................................. 67 5. MARKER ASSISTED INTROGRESSION OF RYMV1 RESISTANCE GENE INTO FARMERS’ PREFERRED RICE VARIETIES .......................................................................................................... 67 University of Ghana http://ugspace.ug.edu.gh x 5.1. Introduction .......................................................................................................................... 67 5.2. Materials and methods ........................................................................................................ 69 5.2.1. Research time frame and study areas .................................................................................. 69 5.2.2. Parental lines ....................................................................................................................... 69 5.2.4. Rice emasculation and cross-pollination for F1 seeds production...................................... 71 5.2.5. Development of recombinant inbred populations ............................................................... 71 5.2.6. Marker assisted foreground selection for RYMV1 resistance gene ................................... 73 5.2.6.1. Extraction of total RNA from rice leaves ........................................................................ 73 5.2.6.2. Reverse Transcription PCR.............................................................................................. 73 5.2.7. Phenotyping RIPs for resistance to RYMV ........................................................................ 75 5.2.8. Data analysis ....................................................................................................................... 76 5.3. Results ................................................................................................................................... 77 5.3.1. Recombinant inbred populations ........................................................................................ 77 5.3.2. Molecular screening for RYMV1 gene identification ........................................................ 78 5.3.3. Reactions of rice recombinant inbred populations (RIPs) to RYMV inoculation .............. 83 5.3.3.1. Latency period ................................................................................................................. 83 5.3.3.2. Disease incidence ............................................................................................................. 89 5.4. Discussion.............................................................................................................................. 93 CHAPTER 6 ............................................................................................................................................. 97 6. EVALUATION OF RICE RECOMBINANT INBRED LINES FOR YIELD AND YIELD COMPONENTS IN THREE ENVIRONMENTS ................................................................................. 97 6.1. Introduction .......................................................................................................................... 97 6.2. Materials and methods ........................................................................................................ 99 University of Ghana http://ugspace.ug.edu.gh xi 6.2.1. Plant materials and field experiments ................................................................................. 99 6.2.2. Data collection .................................................................................................................. 100 6.2.3 Data analysis ...................................................................................................................... 101 6.2.3.1. Computation of variance components and estimation of genotypic and phenotypic variances ..................................................................................................................................... 101 6.2.3.2. Estimation of Path coefficients ...................................................................................... 103 6.3. Results ................................................................................................................................. 106 6.3.1. Analysis of variance and heritability ................................................................................ 106 6.3.2. Correlation among characters ........................................................................................... 111 6.3.3. Phenotypic and genotypic path coefficient analysis ......................................................... 111 6.4. Discussion............................................................................................................................ 114 7. GENERAL DISCUSSION, CONCLUSION AND RECOMMENDATIONS ............................... 117 7.1. General discussion ............................................................................................................. 117 7.1.1. Farmers' preferences in the breeding strategy ................................................................... 117 7.1.2. Screening of rice germplasm for resistance to rice yellow mottle virus disease .............. 118 7.1.3. Development of high yielding quality rice with resistance to RYMV ............................. 119 7.2. General Conclusion ............................................................................................................ 121 7.3. Recommendations .............................................................................................................. 122 BIBLIOGRAPHY ................................................................................................................................. 123 University of Ghana http://ugspace.ug.edu.gh xii LIST OF FIGURES Figure 2.1. Pathways of the domestication of the two cultivated rice (Khush, 1997) ................... 8 Figure 2.2. Typical symptoms of rice yellow mottle disease on susceptible rice variety BG90-2 and its healthy control (right) ........................................................................................................ 12 Figure 2. 3. Severe infestation of rice field by rice yellow mottle disease (Photo: Traore Oumar) ....................................................................................................................................................... 13 Figure 2. 4. Organization of Rice yellow mottle virus genome; five open reading frames (ORF) are mapped on the ∼4450 bases RNA genome. ........................................................................... 15 Figure 2. 5. Three-dimensional model of the central domain of RYMV1 gene (Albar et al., 2006) ....................................................................................................................................................... 19 Figure 2. 6. Model showing RYMV-RYMV1 gene interaction through the viral protein genome- linked (VPg) and the translation initiation factor eIF(iso)4G (Hebrard et al., 2008) ................... 22 Figure 3.1. Interaction with farmers during interviews and informal discussions ....................... 32 Figure 3.2. Single plant yield comparison: (A) Healthy and diseased plant tagged with white and black sachet respectively; panicles harvested from healthy (B) and from diseased (C) plants. ... 33 Figure 3.3. Farmers' grown and f preferred rice varieties in Banzon (A) and Mogtedo (B). ...... 35 Figure 3. 4. Farmers’ preferential criteria for rice varieties in Banzon and Mogtedo ................. 36 Figure 3. 5. Main constraints to rice production mentioned by farmers at Banzon and Mogtedo37 Figure 3. 6. Farmers’ awareness of rice diseases in Banzon and Mogtedo; (A) a farmer in Mogtedo able to identify rice yellow mottle disease symptoms on rice leaves ............................ 38 Figure 3.7. Rice yellow mottle control methods used by farmers in Banzon and Mogtedo; (A) a farmer spraying pesticide on rice field in Mogtedo ...................................................................... 39 University of Ghana http://ugspace.ug.edu.gh xiii Figure 4. 1. Map of Burkina Faso and Ghana showing rice accessions collection sites .............. 53 Figure 4. 2. Proportions of susceptible, partially resistant and highly resistant rice accessions identified after inoculation of RYMV isolates mixture 1 (A) and mixture 2 (B) ......................... 60 Figure 4. 3. Mean of virus titres in leaves of rice accessions inoculated with mixture 1 (A) and mixture 2 (B) of RYMV isolates (see material and methods). ..................................................... 61 Figure 5. 1. Device used for rice emasculation. ........................................................................... 72 Figure 5. 2. Breeding scheme for the development of recombinant inbred line populations ...... 72 Figure 5. 3. PCR-based RYMV1 allele specific amplification strategy using SNP markers. ..... 75 Figure 5. 4. Electrophoregrams showing RT-PCR amplification profiles using rymv1-2- and rymv1-3- allele specific primers. ................................................................................................... 79 Figure 5. 5. Reaction of RIPs to non-resistance breaking (A) and resistance breaking (B) RYMV isolates........................................................................................................................................... 90 Figure 5. 6. Reaction of RIPs to non-resistance breaking (A) and resistance breaking (B) RYMV isolates........................................................................................................................................... 92 Figure 5. 7. Reaction of RIPs to non-resistance breaking (Inoculum 1) and resistance breaking (Inoculum 2) RYMV isolates. ....................................................................................................... 93 University of Ghana http://ugspace.ug.edu.gh xiv LIST OF TABLES Table 2. 1 Genomic classification and distribution of Oryza species (Adapted from Khush, 1997) ....................................................................................................................................................... 10 Table 2. 2. Alignment of the 301-325 region of RYMV1 gene product from susceptible and resistant cultivated Oryza species (adapted from Thiemele et al., 2010) ..................................... 20 Table 2.3. Alignment of the (41-52) region out of the 79 amino acids RYMV VPg (Traore et al., 2010) ............................................................................................................................................. 22 Table 2. 4. Some important genes characterized in rice (Adapted from Delseny et al., 2013) ... 26 Table 3.1. Effect of rice yellow mottle disease on grain yield in three rice varieties ................. 40 .Table 4. 1. Some reactions of rice accessions to rice yellow mottle virus .................................. 47 Table 4. 2. RYMV isolates selected from INERA RYMV collection used for screening rice accessions ...................................................................................................................................... 50 Table 4. 3. Characteristics of rice varieties used as susceptible and resistant checks .................. 52 Table 4. 4. Reactions of rice accessions to inoculation of two mixtures of RYMV isolates ....... 55 Table 4. 5. Reactions of 20 rice accessions to inoculation with 10 RYMV isolatesa .................. 63 Table 5. 1. Rice genotypes used for the development of recombinant and backcross inbred lines ....................................................................................................................................................... 70 Table 5. 2. Primers used for detecting alleles of RYMV1 gene within RIPs............................... 74 Table 5. 3. Selected RYMV isolates used for screening rice accessions ..................................... 76 Table 5. 4. Development of recombinant inbred line populations for resistance to RYMV ....... 77 University of Ghana http://ugspace.ug.edu.gh xv Table 5. 5. Allelic pattern of recombinant subfamilies from crosses involving donors of rymv1-2 and rymv1-3 resistance alleles ...................................................................................................... 80 Table 5. 6. Reactions of rice accessions to inoculation of two mixtures of RYMV isolates ....... 84 Table 6. 1. Analysis of variance yield and its components of 79 RIPs and their parents evaluated in three locations and two replications in fixed genotypes, random environments and random blocks model ............................................................................................................................... 108 Table 6. 2. Mean squares, heritability (broad sense) and co-efficient of variability estimates for grain yield components in rice .................................................................................................... 109 Table 6. 3. Parents and offspring mean performance for grain yield ......................................... 110 Table 6. 4. Genotypic (lower diagonal) and phenotypic (upper diagonal) correlation of grain yield components ........................................................................................................................ 112 Table 6. 5. Genotypic direct (bold face shaded and diagonal) and indirect effects of various components on rice grain yield ................................................................................................... 113 University of Ghana http://ugspace.ug.edu.gh xvi LIST OF ABBREVIATIONS AfricaRice : Ex WARDA AGTB Above Ground Total Biomass ANOVA : Analyse of variance BC(n)F1 : nth Backcross generation between F1 and recurrent parent BC(n)F1S(n) : nth self of nth Backcross generation between F1 and recurrent parent cDNA : Complementary Deoxyribonucleic Acid CP : Coat Protein CRD : Complete Randomized Design CSIR-CRI : Consil for Scientific and Industrial Research-Crop Research Institute CV : Coefficient of variation cv. : cultivar ELISA : Enzyme-linked immunosorbent assays DAS : Double antibody sandwich DFF : Days To First Flowering DNA : Deoxyribonucleic Acid Dpg : Days post germination Dpi : Days post inoculation E : Glutamic acid residue eIF(iso)4G : Eukaryotic translation initiation factor (isoform) 4G EMS : Error mean square; F(n) : nth breeding generation F1 : First breeding generation FAO : Food and Agriculture Organization of United Nation FAOSTAT : Food and Agriculture Organization of United Nation, statistic department FKR : Fara Koba Rice FKR(n)N : FKR(number) NERICA FLL Flag Leaf Length GA : Genetic advance University of Ghana http://ugspace.ug.edu.gh xvii GCV : Genotypic coefficients of variation GMS : Genotypic mean square GW Thousand Grain Weight H2 or hb 2 : Broad sense heritability HIV : Human immunodeficiency virus HR : High Resistance IRRI : International Rice Research Institute IITA : International Institute Of Tropical Agriculture INERA : ‘Institut de l’Environnement et de Recherches Agricoles’ K : Lysine residue Kbr : Kamboinse riz LSD : Least significant difference m² : Metre square MAS : Marker Assisted Selection mm : Millimetre MMLV-RT : Moloney Murine Leukemia Virus-Retro transcriptase NERICA : New Rice for Africa NPK : Nitrogen – Phosphorous – Potassium nRB : Non resistance breaking NS : No symptom nt : Nucleotide ORF : Open Reading Frame PCV : Phenotypic coefficients of variation PH Plant Height PL Panicle Length PPPN Per-Plant-Panicle Number PPTN Per-Plant-Tiller Number PR : Partial Resistance PRA : Participatory Rural Appraisal QTL : Quantitative Trait Loci RB : Resistance breaking University of Ghana http://ugspace.ug.edu.gh xviii RFLP : Restriction fragment length polymorphisms RILs : Recombinant inbred Lines RIPs : Recombinant inbred line Populations RNA : Ribonucleic Acid rr : Recessive resistant homozygous alleles RR : Dominant susceptible homozygous alleles rR : Heterozygous alleles RT-PCR : Reverse Transcription-Polymerase Chain Reaction RYMV : Rice yellow mottle virus RYMV1 : Rice yellow mottle virus resistance gene 1 RYMV2 : Rice yellow mottle virus resistance gene 2 RYMD : Rice yellow mottle virus disease S : Susceptible SNDR : National Strategic plan for Rice Development SNP : Single Nucleotide polymorphism SPY Single Plant Grain Yield SSA : Sub-Saharan Africa SSD : Single Seed Decent SSR : Single Sequence Repeats T : Threonine residue t/ha : Ton per hectare Tob : Tropical oryza barthii Tog : Tropical oryza glaberrima VPg : Viral genome-linked protein WARDA : West African Rice Development Association University of Ghana http://ugspace.ug.edu.gh 1 CHAPTER 1 1. GENERAL INTRODUCTION Rice is one of the most important food crops in the world. It is the main staple food for more than half of the world’s population (Barker et al., 2007; Ray et al., 2013). Rice is mostly consumed directly as cooked meals but it is also processed into various industrial products (rice cakes, rice bran oil, and wine). Rice straw is used for livestock feed, bedding for livestock and straw for mushroom production. In the early times, rice straw was also used for thatching roofs in Asia, and to make ropes, mats, paper, baskets, and bags. Nowadays rice straw is mainly used for animal feed or as organic fertilizer (Janick, 2002). In 2011, the overall rice production was estimated at 718,345,380 tons (FAOSTAT, 2013). This makes rice the second most produced cereal in the world after maize (875,098,631 tons) and more than wheat (674,884,372 tons). Following the green revolution, rice production was boosted in several Asian countries (Conway, 2012) and Asia remains the continent where most rice is grown, accounting for about 90% of the whole rice production. The leading rice producing countries are China (204,285,000 tons) and India (152,600,000 tons), which together represent about 55% of the total Asian rice production (Wasim, 2002). In Sub-Saharan Africa, rice is also an important staple and strategic food crop for several reasons. Milled rice consumption per capita has risen steadily from 14 kg in 1970 to 22 kg in 1980 and more than 39 kg in 2009 (Diagne, 2011). This rapid increase has been attributed mainly to changes in food preferences in favour of rice in both rural and urban areas, high population growth rates and rapid urbanization. The relative rate of growth in demand for rice in Africa and University of Ghana http://ugspace.ug.edu.gh 2 particularly in Sub-Saharan Africa has been faster than in other regions of the world (Somado et al., 2008). Rice production in West Africa in 2012 was estimated at 11.94 million tons, which represented 45.8% of the whole African production. Nigeria, Guinea, Mali and Sierra Leone were the biggest producing countries with annual production of 4.8 million tons, 1.92 million tons, 1.91 million tons, and 1.15 million tons respectively. Yields varied between 1.2 and 2.8 t/ha in most countries. However, significantly higher yields (about 5 t/ha) were recorded in Mauritania and Senegal. Most African countries, especially in West Africa, have worked to boost rice production following the 2008 food crisis (Seck et al., 2012). As a result, rice production increased significantly by 36% from 18,375 million tons in 2007-2008 to 25,018 tons in 2011-2012. However, in most West African countries, this increment was insufficient to meet the rice demands. Rice imports for countries like Mali, Guinea and Sierra Leone ranged from 5 to10% of the local consumption. In Côte d’Ivoire, Senegal, Gambia and Niger, rice imports accounted for more than half of the local consumption. Up to date, West Africa imports about 35% of its local production to meet the demand. These imports represent large quantities of rice, as Nigeria alone imported more than 1.6 million tons which represents quarter of its local production (FAOSTAT, 2013). Rice is a major food crop in Burkina Faso, ranking fourth after sorghum, millet and maize among cereals. Like other countries in Africa, rice consumption in Burkina Faso is subject to rapid changes mainly in urban populations but also in rural areas. Per capita rice consumption estimated at 14.8 kg in 1992 and has increased to 21 kg in 2008 (SNDR, 2011). University of Ghana http://ugspace.ug.edu.gh 3 Rice is grown everywhere in Burkina Faso by smallholder farmers. The overall rice production in the country reached 300,000 t in 2012. Cropping systems include rainfed upland rice, lowland rice and irrigated rice. Lowland rice is the most widespread cropping system and covers almost half of the total rice cultivation area. Upland rice (17% of total rice area) has been promoted in different parts of the country, especially in the south-western cotton belt where rice is used as a rotation crop with maize. Irrigated rice (34%) was introduced in the 1960s (Illy, 1997; Wopereis et al., 1999; Segda et al., 2005; SNDR, 2011). Irrigated rice in Burkina Faso is the most productive cropping system due to better water management which allows growing two crops per year with averagely good yields of 3 to 7 t/ha compared to 1 to 2 t/ha for other systems. Total irrigated area under rice cultivation represents only 5% of the overall irrigable land estimated at 233,500 ha. Therefore, there is a great potential to increase rice production in the country and a strategic plan was adopted in 2011. Under the plan, the increase in rice production should result in substantial increases in both cultivated acreages and productivity (SNDR, 2011). High productivity depends primarily on quality seeds (Conway, 2012). More than 60 improved rice varieties have been released in the country but only a few of them are currently grown by farmers (Chapter 3; SNDR, 2011). Most varieties were developed without considering farmers and consumers’ preferences. The national rice research programme included that aspect in its breeding schemes through participatory varietal selection. Farmers’ expectations are being considered more and more in the development of new rice varieties (Kam, 2011). Efforts have also been made to collect rice landraces to be used as genetic sources of farmers’ preferred traits and other desirable traits. University of Ghana http://ugspace.ug.edu.gh 4 Because rice is widely adapted to different environments, its production on the African continent faces several problems due to abiotic and biotic stresses (Abo et al., 1998). Major abiotic constraints include iron toxicity, phosphorus and zinc deficiencies, acid or alkaline soils, drought, cold and poor soils (Balasubramenian et al. 2007). The main biotic stresses are weeds, nematodes, birds, stem borers, and diseases. The effect of each constraint usually varies depending on locations, years, seasons of the year, and varieties. The most common rice diseases in Africa are caused by Xanthomonas sp responsible for bacterial blight, rice blast fungal diseases caused by Magnaporthe grisea and rice yellow mottle disease caused by Rice yellow mottle virus (RYMV)(Mew, 1991). RYMV is an emergent and highly damaging rice pathogen which is confined to the African continent including Madagascar (Fargette et al., 2006). Attempts made to control rice yellow mottle disease have been directed mainly to breeding for resistance to RYMV. Several screening programmes were conducted to identify sources of resistance to the virus (Awoderu, 1991; Thottappilly and Rossel, 1993; Thiemele et al., 2010). A few resistant sources have been identified and are being used in different breeding programmes. These resistant sources have not been stable in the field and have succumbed to the virulent strains of the virus (Traore et al., 2006a). Rice is among the most promising food crops for feeding the rapid growing population of the world, particularly in Africa. It is projected that to meet the demand for food by 2050, the overall food crop production should double. Without changing the overall rice cropping system, rice production is expected to increase by only 42% (Tilman et al., 2011). Unless yields are boosted further, most rice producing countries in Sub-Saharan Africa will experience significant University of Ghana http://ugspace.ug.edu.gh 5 decreases in the per capita rice harvests (Ray et al., 2013). Despite the great potential of arable land available, a sustainable increase in rice production in the region should result from increasing yields, rather than clearing more land (Foley et al., 2011, Conway, 2012, Tscharntke et al., 2012). Substantial increase in rice yields through genetic control of RYMV can be achieved by a combination of several approaches. Firstly, additional resistance sources to the virus need to be identified within rice germplasm including landraces and wild rice species (Thiemele et al., 2010, Kam, 2011). Therafter there is a need to develop new rice varieties that are more resilient to climate change. Such varieties can benefit from useful genes coming from poorly exploited sources including African rice species Oryza glaberrima Steud (Sarla and Mallikarjuna, 2005). Secondly, the proper identification of suitable resistance genes to RYMV requires a good knowledge of virus-host interactions. Thirdly, molecular tools such as marker assisted selection have to play a major role in plant breeding along with conventional techniques. Lastly, to meet its ultimate goal of widespread utilization of improved varieties, plant breeding must take into account the preferences of end users, of which farmers are at the forefront. Failure to fulfill this requirement usually leads to poor adoption or even rejection of newly developed high yielding varieties due to the lack of some traits not considered in the breeding process (Larc, 1995; Linares, 2002). Participatory plant breeding is now being used to include preferences of farmers and other stakeholders (consumers, processors, extension agents, vendors, industry, etc.) at all major stages of the breeding and selection process (Sperling et al., 2001). This research is aimed at contributing to food security and improving livelihoods of small-scale rice farmers in Burkina Faso by generating improved higher yielding and farmer-preferred University of Ghana http://ugspace.ug.edu.gh 6 varieties that are more resistant to RYMV. To achieve the above goal, the specific objectives of the study were: - to appraise farmers’ awareness regarding constrains to rice cultivation with focus on Rice yellow mottle virus (RYMV) disease; - to assess farmers for their preference for rice varieties and evaluate impact of RYMV on their cultivated rice varieties; - to identify new sources of resistance to RYMV and confirm efficacy of the existing sources of resistance; - to implement marker assisted selection to introgress resistance genes to RYMV into farmers’ varieties; - to determine relationships between secondary traits and grain yield in recombinant lines. These specific objectives aim at providing responses to the following assumptions: - Farmers have preferences for rice varieties for various reasons and are aware of rice diseases, especially RYMV and its damage; - Farmers use indigenous methods to control rice diseases; - Resistant rice genotypes to RYMV are available within collected rice germplasm and can be identified by proper screening; - Molecular approach using DNA markers is effective in improving farmers’ preferred rice varieties for resistance to RYMV; - Breeding gain for yield and resistance to RYMV is achievable with recombinant inbred line population involving farmers’ preferred varieties. - Yield components have direct and indirect effects on grain yield University of Ghana http://ugspace.ug.edu.gh 7 CHAPTER 2 2. LITTERATURE REVIEW 2.1. Rice origin and domestication Rice is a grain crop which belongs to the family Poaceae (Gramineae) and the genus Oryza. The Oryza genus includes two cultivated (Oryza sativa L. and O. glaberrima Steud.) as well as several wild rice species. Wild rice also refers to a small group of aquatic grasses of the genus Zizania. Both Oryza and Zizania are members of the tribe Oryzeae (Lee, 2002) but they are not sexually compatible. However, successful introgressions of Zizania genes into O. sativa by repeated pollination have been achieved (Wang et al., 2005). Unlike species of the genus Oryza, Zizania species have very limited in geographical distribution and lower contribution as a food crop. In addition to the two cultivated rice species, the genus Oryza also includes 21 wild species (Aggarwal et al., 1997). The main differences in botanical morphology between O. sativa and O. glaberrima are the ligule size and the glume pubescence. Most of O. glaberrima varieties have fewer hairs, short ligules, and fewer or no branches. They also have red-hulled grains on a shattering panicle. Another distinctive criterion between the two cultivated rice species is that O. glaberrima is strictly annual, whereas O. sativa is potentially perennial (Sacks et al., 2003; Sarla & Mallikarjuna, 2005). According to Khush (1997), the genus Oryza probably originated from Gondwanaland about 130 million years ago, before the domestication of the two cultivated rice species (Figure 2.1). Oryza sativa is composed of two major varietal groups, namely O. sativa indica and O. sativa japonica, sometimes referred to as subspecies. Rice domestication has been long debated, especially that of University of Ghana http://ugspace.ug.edu.gh 8 O. sativa species with respect to questions on the right area from where cultivated rice originated, the types of O. rufipogon which served as direct progenitors and how indica and japonica types evolved (Huang et al., 2012). Figure 2.1. Pathways of the domestication of the two cultivated rice (Khush, 1997) Based on genomic data, it has been clearly shown that O. sativa was domesticated in South East Asia from its ancestor Oryza rufipogon (Huang et al., 2012). However, indica and japonica groups were domesticated independently from different gene pools within O. rufipogon. Recently, new insights in O. sativa domestication indicated that japonica rice was first domesticated from a specific population of O. rufipogon in the region of the Pearl River in southern China (Huang et al., 2012). Oryza sativa indica rice was subsequently developed from crosses between japonica rice and local wild rice. Oryza glaberrima was domesticated in the Niger River delta about 2,000–3,000 years ago University of Ghana http://ugspace.ug.edu.gh 9 (Porteres, 1950). Its ancestors were the wild perennial O. longistaminata and the annual wild ancestor Oryza barthii (formerly known as Oryza brevilugata). Due to its center of domestication, O. glaberrima is sometimes referred to as ‘African rice’ as opposed to O. sativa (Kush, 1997). The African rice is cultivated only in West Africa where it is mainly used for ritual practices and traditional medicine (Linares, 2002). By contrast, the Asian rice O. sativa is cultivated worldwide because of its high yield potential and better adaptation to rice intensification. Presently, O. glaberrima is being replaced by O. sativa species in West Africa, contributing to the progressive disappearance of cultivated O. glaberrima genotypes (Linares, 2002). 2.2. Rice genetic diversity The genomes of Oryza and Zizania, both members of the tribe Oryzeae, have been mapped. The basic number of chromosomes of the rice species of the genus Oryza is 12 while that of Zizania is 15. Comparison of Oryza and Zizania genomes indicated that 12 of the 15 Zizania chromosomes correspond to the 12 chromosomes of Oryza. The additional three chromosomes in Zizania are likely duplications of three Oryza chromosomes (Kennard et al., 1999). Oryza species have been grouped into nine types of diploid (2n =2x = 24) genomes and various combinations among them at the tetraploid level (2n =4x= 48) (Aggarwal et al., 1999; Ge et al., 1999). The two cultivated rice species and their wild ancestors are included into the type AA genome group (Table 2.1). Phylogenetic analysis of alcohol dehydrogenase genes (Adh1 and Adh2) in rice indicated that type AA genome species diverged recently and radiated rapidly within the rice genus (Ge et al., 1999). The middle domain of eukaryotic initiation factor 4G (eIF4G) is involved in the genetic differentiation of Oryza sativa and O. glaberrima. At position University of Ghana http://ugspace.ug.edu.gh 10 303 of the protein sequence, amino acid residues were Alanine (A) in O. sativa and Aspartic acid (D) in O. glaberrima (Albar et al., 2003; 2006). Other known diploid genomes are types BB, CC, EE, FF and GG. The tetraploid genomes are consisting of allotetraploid combinations of two distinct diploid genomes. Combinations found so far include BBCC, CCDD, HHJJ, and HHKK genome types. Among all species, only O. punctata contains both diploid and tetraploid genome types. Genomic organization of Oryza species confirmed, to some extent, the previous grouping of species members into four complexes based on morphological characters (Cheng et al., 2002). Table 2. 1 Genomic classification and distribution of Oryza species (Adapted from Khush, 1997) Species 2n Chromosomes Genome Oryza sativa complex Oryza sativa L. 24 AA O. nivara Sharma et Shastry 24 AA O. rufipogon Griff. 24 AA O. breviligulata A. Chev. et Roehr. 24 AA O. glaberrima Steud. 24 AA O. longistaminata A. Chev. et Roehr. 24 AA O. meridionalis Ng 24 AA O. glumaepatula Steud. 24 AA Oryza officinalis complex O. punctata Kotschy ex Steud. 24 BB O. punctata Kotschy ex Steud 48 BBCC O. minuta J. S. Pesl. ex C.B. Presl. 48 BBCC O. officinalis Wall ex Watt 24 CC O. rhizomatis Vaughan 24 CC University of Ghana http://ugspace.ug.edu.gh 11 O. eichingeri A. Peter 24 CC O. latifolia Desv. 48 CCDD O. alta Swallen 48 CCDD O. grandiglumis (Doell) Prod. 48 CCDD O. australiensis Domin. 24 EE O. brachyantha A. Chev. et Roehr. 24 FF O. meyeriana complex O. granulata Nees et Arn. ex Watt 24 GG O. meyeriana (Zoll. et Mor. ex Steud.) Baill. 24 GG Oryza ridleyi complex O. longiglumis Jansen 48 HHJJ O. ridleyi Hook. f. 48 HHJJ O. schlechteri Pilger 48 HHKK Thus, type AA genome contains cultivated rice species and their ancestors form the O. sativa complex. Oryza officinalis complex includes diploid genomes BB, CC, EE and FF and tetraploid genomes BBCC and CCDD. Oryza meyeriana complex contains the diploid genome GG only. Oryza ridleyi complex includes tetraploid genomes HHJJ and HHKK. Genome types HH, JJ and KK have not been reported in any Oryza species although they were involved in tetraploid types in the O. ridleyi complex. This suggests that diploid species with HH, JJ, or KK genomes are either extinct or are yet to be discovered (Ge et al., 1999). 2.3. Rice yellow mottle disease 2.3.1. Symptoms and geographical distribution Rice stripe necrosis and rice yellow mottle are the two major rice virus diseases reported in Africa. Rice stripe necrosis disease was first reported in Côte d’Ivoire (Fauquet and Thouvenel, 1983) and subsequently in Colombia (Morales et al., 1999) and Brazil (Maciel et al., 2006). Rice University of Ghana http://ugspace.ug.edu.gh 12 yellow mottle is the most widespread viral disease of rice in Africa, south of the Sahara (Abo et al., 1998). The disease has not been reported in any other continent. First symptoms were observed in 1966 in Kenya (Bakker, 1970; Bakker, 1974) and consisted of yellowing or mottling of the leaves of infected plants (Figure 2.2). Additional symptoms are stunting, partial emergence of panicles and sterility. Early infection of susceptible cultivars often leads to plant death. Rice yellow mottle symptoms in the field appear as yellow patches which often coalesce when conditions are favourable for disease spread (Figure 2.3). From the mid-1970s, several rice growing countries in West, Central and East Africa have been affected by the disease (Abo et al., 1998; Fauquet and Thouvenel, 1977; Fomba, 1988; John et al., 1984; John et al., 1985; Raymundo and Buddenhagen, 1976; Traore et al., 2001). Recently, the disease was reported in Rwanda, Central African Republic and Democratic Republic of Congo (Ndikumana et al., 2011; Longue-Sokpe et al., 2013). Figure 2.2. Typical symptoms of rice yellow mottle disease on susceptible rice variety BG90-2 and its healthy control (right) University of Ghana http://ugspace.ug.edu.gh 13 Figure 2. 3. Severe infestation of rice field by rice yellow mottle disease (Photo: Traore Oumar) To date, rice yellow mottle has been found in almost all major rice growing countries in Sub- Saharan Africa including Madagascar. It has been estimated that the disease emerged about 200 years ago in East Africa (Fargette et al., 2008). However, it started to be a serious problem for rice cropping after the introduction of exotic and highly susceptible O. sativa varieties from Asia (Abo et al., 1998; Reckhaus and Adamou, 1986). Also the increase in rice cultivation due to the availability of water for sequential plantings throughout the year favoured its increase (Bakker, 1974; Thresh, 1989). Rice yellow mottle is responsible for serious yield losses in all rice growing systems. However, irrigated rice is most affected because of more favourable conditions for disease spread (Traore et al., 2009). Yield losses vary from 25 to 100% depending on the rice cultivars grown and how University of Ghana http://ugspace.ug.edu.gh 14 early the infection sets in, and the rice cultivation system (Awoderu, 1991; Konate et al., 1997; Taylor et al., 1990). Nearly total yield losses have been reported in several rice cultivars infected at an early growth stage (Abo et al., 1998). 2.3.2. Rice yellow mottle virus 2.3.2.1. Taxonomy and genome organization Rice yellow mottle disease is caused by Rice yellow mottle virus (acronym: RYMV), member of the genus Sobemovirus (Hull and Fargette, 2005). It is an isometric virus measuring 28 ± 3 nm in diameter. RYMV has a single-stranded positive RNA genome of about 4450 nucleotides. The genome organisation of sobemoviruses has been recently updated with the identification of a new open reading frame (ORF) (Ling et al., 2013). Therefore, RYMV genome is organized into five open reading frames (Figure 2.4). ORF1, located at the 5’ end of the genome, encodes protein P1 involved in virus movement and gene silencing suppression or activation (Sire et al., 2008, Lacombe et al., 2010). ORF2a encodes a serine protease and a viral protein genome-linked (VPg). VPg is involved in virulence and determines the ability to overcome resistance genes (Hebrard et al., 2006; Pinel-Galzi et al., 2007). It is also involved in the adaptation of RYMV to Asian or African rice species (Thiemele et al., 2010). ORF2b, which is translated through a -1 ribosomal frame shift mechanism as a fusion protein, encodes the RNA-dependent-RNA polymerase. ORF3 is expressed through a subgenomic RNA and encodes the coat protein (CP) involved in virus spread within the plant (Brugidou et al., 1995). The 3’ end of the full viral RNA is deprived of the poly (A) tail found in most viral RNA genomes and the 5’ end is covalently linked to the VPg (Hull, 1988; Hull and Fargette, 2005). The functional role of ORFx is not fully known but it is suggested to control the establishment of systemic infection (Ling et al., 2013). University of Ghana http://ugspace.ug.edu.gh 15 5’ ORFx ORF1 ORF2a ORF2b ORF3 3’ Vpg Figure 2. 4. Organization of Rice yellow mottle virus genome; five open reading frames (ORF) are mapped on the ∼4450 bases RNA genome. ORFs and corresponding proteins are as follows: ORF1 (P1), ORFx, ORF2a (Protease and VPg), ORF2b (RdRp) and ORF3 (coat protein) ( Ling et al., 2013) 2.3.2.2. Biochemical properties, transmission and susceptible hosts RYMV is a highly infectious and stable virus with the thermal inactivation point of 70°C, the dilution end-point of more than 10-6 and the longevity in vitro of 100 days at 20°C (Bakker, 1975; Fauquet and Thouvenel, 1977). RYMV was found infectious in infected dry leaves after one year of storage over CaCl2 (Bakker, 1974). RYMV is easily transmitted by mechanical inoculation in the laboratory. Vectors involved in its transmission in the field include mainly beetles and also mammals such as cows (Bos spp.), rats (Arvicanthis niloticus, and donkeys (Asinus spp.) (Sarra and Peters, 2003). RYMV has been transmitted through abiotic factors including wind (Sarra et al., 2004), and contact between plants (Traore et al., 2008b). During some cultural practices, the virus was transmitted through contaminated hands and transplantation of rice seedlings into contaminated soil (Traore et al., 2008b). Transplanting contaminated seedlings from nurseries into the field contributed to a rapid spread of the virus (Traore et al., 2006b). RYMV is not seed-transmitted in rice or its wild hosts (Fauquet and Thouvenel, 1977; Konate et al., 2001; Abo et al., 2004; Allarangaye et al., 2006). Non-seed transmission of RYMV, despite clear detection in all seed parts, including the embryo, has been attributed to virus inactivation during seed maturation and desiccation. Such virus University of Ghana http://ugspace.ug.edu.gh 16 inactivation has been found in cow dung frequently used as manure in rice fields, indicating that this organic fertilizer is not a source for virus infection in the field (Sarra, 1998). RYMV is transmitted to a narrow host range limited to members of the family Poaceae. Apart from rice, natural hosts include wild rice O. longistaminata, O. barthii, Ischaemum rugosum Salisb., Echinocloa colona (L.) Link, Echinochloa crus-pavonis (Kunth) Schult., Eragrostis atrovirens (Desf.) Trin. ex Steud and Panicum repens L. (Awoderu, 1991; Konate et al., 1997). Several graminaceous species members of the tribes Chloridae and Eragrostidae were identified as experimental hosts (Awoderu, 1991; Allarangaye et al., 2007). 2.3.2.3. Serological and molecular diversity Yellow mottle symptoms induced by RYMV are most of the time typical, but they can be confounded with other disorders such as those caused by iron deficiency or mite feeding damage. Moreover, symptomless infections by RYMV have been found in some host species (Bakker, 1974). Serological tools have long been used to ascertain RYMV infections, as the virus is highly immunogenic and does not have serological relationships with any other plant virus (Calvert et al., 2003; Traore et al., 2008a). Additionally, RT-PCR has gained high popularity in the virus diagnosis due to its sensitivity, possibility for downstream tests on amplification products and increasing affordability of the technique all over the world. Both serological and molecular techniques have been used to assess RYMV diversity. The virus serological variation was first demonstrated by cross reactivity studies with polyclonal antibodies in double diffusion gel assays (Fauquet and Thouvenel, 1987; Mansoor and Baillis, 1994; Sere et al. 2005). More accurate data were obtained later, when monoclonal antibodies and sequences of virus genes became available (Traore et al., 2009). Five serotypes were distinguished and named University of Ghana http://ugspace.ug.edu.gh 17 Ser1 to Ser5. Sequence analyses of the coat protein gene confirmed the grouping of virufs isolates into serotypes. Accordingly, virus strains identified using this molecular tool was referred to as S1 to S5 (Fargette et al., 2002). However, this molecular typing was found more accurate than serological typing, as it allowed the identification of an additional strain S6 that was serologically indistinguishable from strain S5 (Traore et al., 2005). RYMV diversity was found to be dependent of the ecology and geographical area from where isolates were collected (Konate et al., 1997, Traore et al, 2009). A close relationship was found between pairwise geographic and genetic distances calculated on the full virus genome or on individual genes (Fargette et al., 2004, 2006). The emergence, diversification and dispersion of RYMV were studied thanks to the availability of full or partial virus genome sequences at continental level (Abubakar et al., 2003; Fargette et al., 2004; Traore et al., 2005). The highest number of virus strains, including the most divergent ones, was found in the eastern region of Tanzania, suggesting that this region is the centre of origin of RYMV (Traore et al., 2005; Fargette et al., 2006). Although the route of dispersal remains unravelled, the RYMV is thought to have spread in other regions of the continent from an ancestor which first emerged and diversified in East Tanzania. A second centre of diversification was identified in the inner delta of the Niger in the north of Mali. 2.4. Virus host interactions 2.4.1. Rice genes involved in resistance to RYMV Most rice varieties grown worldwide including Africa are of O. sativa species, of which, the vast majority are highly susceptible to RYMV. In such varieties, virus infection is systemic (Bakker, 1974) and virions multiply in all organs including roots, stems, leaves, flowers and University of Ghana http://ugspace.ug.edu.gh 18 seeds. However, virus concentrations may vary depending on the plant parts. Higher concentrations were found in xylem parenchyma cells and sieve elements (Opalka et al., 1998). A lot of research work was carried out in order to identify sources of resistance to RYMV and to understand the genetic mechanisms that govern such resistance (Attere and Fatokun, 1983; Okioma and Sarkarung, 1983; John et al., 1985; Fomba, 1988; Thottappilly and Rossel, 1993; Paul et al., 1995; Albar et al., 1998; Coulibaly et al., 1999; Ioannidou et al., 2000; Thiemele et al., 2010). Hundreds of rice accessions have been assessed and results indicated the occurrence of two types of resistance which are partial resistance and high resistance. Partial resistance, associated with low virus titres at early stages of infection and delay in symptom expression, were predominantly found in upland O. sativa japonica cultivars such as FKR33, Lac23, Moroberekan and Azucena. By contrast, temperate O. sativa japonica and most O. sativa indica cultivars were susceptible. Partial resistance was found to be polygenic and markers targeting eight regions of the rice genome were used to map QTLs (Albar et al., 1998). A major QTL was identified on chromosome 12 acting in epistasis with other QTLs on chromosome 7 (Ahmadi et al., 2001; Pressoir et al., 1998). The high resistance was found only in a few African rice Oryza glaberrima cultivars (Thottappilly and Rossel, 1993) and only two O. sativa cultivars, namely Gigante and Bekarosaka (Ndjiondjop et al., 1999; Rakotomalala et al., 2008). This high resistance is under the control of the RYMV1 gene (Albar et al., 2006). RYMV1 gene encodes an eukaryotic translation initiation factor eIF(iso)4G. Two important amino-acid positions (E309 and E321) involved in resistance to RYMV are shown on the three-dimensional model of the gene (Figure 2.5). They both represent substitutions of a glutamic acid residue (E) by a lysine residue (K) at University of Ghana http://ugspace.ug.edu.gh 19 position 309 (E309K) and 321 (E321K), respectively. The two mutations were found in highly resistant varieties, the wild type residue E being found in susceptible varieties. At least four alleles of RYMV1 gene have been identified in resistant rice accessions: rymv1-2, rymv1-3, rymv1-4 and rymv1-5 in Gigante or Bekarosaka, Tog5681, Tog5672, and Tog5674, respectively (Table 2.2). Allele rymv1-1 was found in susceptible rice varieties of the two cultivated Oryza species. Rymv1-2 identified only in O. sativa indica varieties whereas all other alleles were found in O. glaberrima varieties. The molecular bases of resistance alleles, rymv1-2 and rymv1-4 were found to be single mutations E309K and E321K, respectively. Allele rymv1-3 was characterized by a tripeptide deletion at positions 322-324 while allele rymv1-5 was based on the mutation K312N associated with a tripeptide deletion at positions 313-315. C terminal domain E309 E321 N terminal domain Figure 2. 5. Three-dimensional model of the central domain of RYMV1 gene (Albar et al., 2006) University of Ghana http://ugspace.ug.edu.gh 20 Table 2. 2. Alignment of the 301-325 region of RYMV1 gene product from susceptible and resistant cultivated Oryza species (adapted from Thiemele et al., 2010) Alleles Rice speciesa Amino Acid residue position 3 0 1 3 0 2 3 0 3 3 0 4 3 0 5 3 0 6 3 0 7 3 0 8 3 0 9 3 1 0 3 1 1 3 1 2 3 1 3 3 1 4 3 1 5 3 1 6 3 1 7 3 1 8 3 1 9 3 2 0 3 2 1 3 2 2 3 2 3 3 2 4 3 2 5 rymv1-1 O. s (S) E G A E S L R A E I A K L T G P D Q E M E R R D K rymv1-2 O. s (R) E G A E S L R A K I A K L T G P D Q E M E R R D K rymv1-1 O. g (S) E G D E S L R A E I A K L T G P D Q E M E R R D K rymv1-3 O. g (R) E G D E S L R A E I A K L T G P D Q E M E * * * K rymv1-4 O. g (R) E G D E S L R A E I A K L T G P D Q E M K R R D K rymv1-5 O. g (R) E G D E S L R A E I A N * * * P D Q E M K R R D K a Oryza species are O. sativa (O.s) and O. glaberrima (O.g) with susceptible (S) and resistant (R) phenotypes. Polymorphic sites involved in alleles differentiation, are shaded. Recently, a second major recessive resistance gene to Rice yellow mottle virus (RYMV2) has been reported in the African cultivated rice species Tog7291 (Thiemele et al., 2010). A single mutation affecting the CPR5 gene was associated with RYMV2 resistance. This mutation was characterized by a 1-base deletion leading to a truncated and probably non-functional protein (Orjuela et al., 2013). CPR5 gene is involved in pathogen defence responses in Arabidopsis thaliana (Yoshida et al., 2002). Partial and high resistances to RYMV were found associated with failure in cell-to-cell movement (Ndjiondjop et al., 2001). The virus was able to multiply equally in protoplasts of susceptible rice cultivars as well as in those of partially or highly resistant ones. Rice cultivar discrepancies in susceptibility to the virus were evident in planta where virus movement was blocked or not. University of Ghana http://ugspace.ug.edu.gh 21 2.4.2. RYMV genes involved is resistance-breaking in rice RYMV pathogenic diversity has been assessed mainly on the aspects of isolates capabilities to break down resistances in rice. Biological and molecular characterization of RYMV isolates of different origins led to the identification of resistance breaking strains. In West and Central Africa, such stains represented about 40% of the virus isolates and were able to overcome high resistance in Gigante (allele rymv1-2) and Tog5681 (allele rymv1-3) (Traore et al., 2006a). Of course, partial resistance in rice cultivars was also overcome (Fargette et al., 2002). Studies on interactions between RYMV and other resistance alleles are in progress. To date, RYMV diversity is such that all known resistances against the virus conferred by RYMV1 and RYMV2 genes are overcome by some isolates (Koala, 2012). The molecular basis of breaking resistance conferred by RYMV1 gene has been studied in detail for the alleles, rymv1-2 and rymv1-3 (Galzi-Pinel et al., 2007; Traore et al., 2010; Poulicard et al., 2012). The VPg coded by ORF2a is the protein interacting with the host factors to determine the RYMV ability to overcome resistances (Hebrard et al, 2006; 2010). Interaction between VPg and eIf(iso)4G is illustrated in Figure 2.6. Several mutations occurring at codon 48 of the Vpg have been attributed to the ability for the virus to overcome resistance conferred by allele rymv1- 2 (Table 2.3). Break down of allele rymv1-3 was associated mainly with mutations that occur at codon 41 and 52. University of Ghana http://ugspace.ug.edu.gh 22 Middle domain eIF(iso)4G R48 E309 E321 H52 VPg Figure 2. 6. Model showing RYMV-RYMV1 gene interaction through the viral protein genome- linked (VPg) and the translation initiation factor eIF(iso)4G (Hebrard et al., 2008) Table 2.3. Alignment of the (41-52) region out of the 79 amino acids RYMV VPg (Traore et al., 2010) Isolate phenotypea VPg codon position 41 42 43 44 45 46 47 48 49 50 51 52 nRB S N T W V R E R E R Y H rymv1-2 RB S N T W V R E E E R Y H rymv1-2 RB S N T W V R E G E R Y H rymv1-2 RB S N T W V R E I E R Y H rymv1-2 RB S N T W V R E V E R Y H rymv1-2 RB S N T W V R E R E R Y Y rymv1-3 RB A N T W V R E R T R Y Y (rymv1-2 + rymv1-3) RB P N T W V R E R T R Y Y (rymv1-2 + rymv1-3) RB S N T W V R E W T R Y H a phenotype include non-resistance breaking (nRB), allele 2 resistance breaking (rymv1-2 RB), allele 3 resistance breaking (rymv1-3 RB) and both alleles 2 and 3 resistance breaking (rymv1-2+rymv1-3) RB University of Ghana http://ugspace.ug.edu.gh 23 It was found that the emergence of resistance breaking isolates depended on the identity of the amino acid residue at codon 49 (Poulicard et al., 2012). Codon 49 is a polymorphic position with either a glutamic acid (E) residue or a threonine (T) residue. On the one hand, when codon 49 has glutamic acid, resistance breaking isolates could emerge on O. saliva. On the other hand, virus isolates with a threonine residue were most adapted to O. glaberrima background. A subset of “threonine isolates” were able to adapt to O. sativa, leading to double allele resistance breaking ability. Altogether, host-virus interaction suggested that prior knowledge of the structure of the viral populations in a given region (resistance-breaking types, adaptation to O. sativa or O. glaberrima) is necessary for any judicious deployment of resistant rice varieties (Traore et al., 2009). 2.5. Control of rice yellow mottle disease Two major control strategies were envisaged soon after the first outbreaks of rice yellow mottle disease. Firstly, phytosanitary measures were advised mostly on the basis of what was applied to other similar plant virus diseases (Abo et al., 1998; Fauquet and Thouvenel, 1987). They include protection of seedbeds using nets, disinfections of the tools used at replanting and weeding, destruction of reservoir host and rice ratoons and other residues. Substantial progress has been made to understand the RYMV epidemiology but most of them did not result in recommendations for disease control at the farmer’s level. Rice seedlings infection at the nursery level and further transplantation into the field served as the main primary sources of infection (Traore et al., 2006b). Several sources previously thought to be involved in the spread of the virus including seeds and straw from infected rice or dung from cows fed on University of Ghana http://ugspace.ug.edu.gh 24 infected rice were ruled out of the process (Sarra, 2005; Allarangaye et al., 2006; Traore, 2012; Traore et al., 2009). Genetic control of rice yellow mottle disease was considered as the most effective way to combat the disease (Leung et al., 2003). Partially resistant rice varieties were recommended in replacement of susceptible ones (Abo et al., 1998; Sy and Sere, 2001). After the identification of highly resistant sources bearing RYMV1 gene, new rice varieties have been developed by ingression of rymv1-2 allele (Jaw et al., 2012). The occurrence of resistance breaking isolates of RYMV undermined the sole usage of genetic control against rice yellow mottle disease. Attempts were made to develop transgenic lines that could be useful for rice yellow mottle disease control. They were all based on the concept of ‘’pathogen-derived’’ resistance which was successfully used in some pathosystems (Tai et al., 1999; Mathew et al., 2002). Transgenic plants expressing RNA-dependent RNA polymerase of RYMV were produced (Pinto et al., 1999). However, the level of the resistance in the transgenic plants was similar to that of partial natural resistance. Like natural resistance, it could also be overcome by some isolates (Sorho et al., 2005). Transgenic rice plants expressing RYMV coat protein were also produced (Kouassi et al., 2006). In this case, most of transgenic plants accumulated more virus than non-transgenic controls while only partial resistance was found in other transgenic plants. These results indicated that coat protein gene was not suitable for genetic engineering of rice for resistance to RYMV. No single management means could be used solely to control RYMV efficiently. Chemical control of the vectors was not considered as economically feasible and not even envisaged in most areas to avoid pollution of water resources concomitantly used for livestock and farmers’ University of Ghana http://ugspace.ug.edu.gh 25 domestic needs. New strategies involved judicious combinations of prophylactic measures and genetic control have been put forward in an integrated management approach for RYMV. Such approach is being advocated strongly in the frame of sustainable agriculture under the double green revolution concept (Conway, 2012). 2.6. Breeding for rice improvement 2.6.1. Major objectives in rice breeding The rice green revolution has been one of most important milestones for rice genetic improvement. The major objectives were to develop high yielding varieties that could be grown in several countries where rice was the main staple food crop. Thus, the semi-dwarf rice IR8 was developed to efficiently use nitrogen without easily lodging (Guimares, 2009). A great number of traits were targeted afterwards. More than 600 genes have been identified from the 12 chromosomes (Jiang et al., 2012). Some important genes are presented in Table 2.4. Only a few genes controlling traits such as aroma, fertility, grain weight, nitrogen use efficiency and seed shattering were reported. By contrast, several genes were found for traits related to yield (plant architecture, flowering date and panicle size), and biotic and abiotic stresses. The great number of genes that control biotic and abiotic stresses indicated that these constraints are of major concern (Jiang et al., 2012). The perfect condition of varietal development is breeding to meet the diverse needs of overall rice production for high yield, superior quality, multiple resistances and high nutrient-use efficiency. Such design should follow five different steps: (1) the population structure that can make maximum use of the solar energy in given ecological conditions; (2) the plant architecture to realize the population structure; (3) the traits to make up the plant architecture and to achieve University of Ghana http://ugspace.ug.edu.gh 26 high quality, resistances to multiple biotic and abiotic stresses, and high nutrient use efficiency; (4) the genes to produce the traits; and (5) the breeding strategy to assemble the genes. The rice genome is being actively screened to elucidate the functions of the genes and identify new useful genes for better varietal improvement (Zhang et al., 2008; Delseny et al., 2013) Table 2. 4. Some important genes characterized in rice (Adapted from Delseny et al., 2013) Controlled traits Names of the genes Architecture MOC1, DWARF10, DWARF27, D3, OsTB1, HTD1, OsSPL14 Flowering date OsG1, Hd1, Hd3a, RFT1, RCN1, Ehd1, Ehd2, SE5, PHYB, ETR2, Hd6, Ghd7, OsMADS50, OsMADS51, RFL, OsMADS56, OsMADS14, OsLFL1 Panicle size RCN1, RCN2, LAX1, Gn1a, Ghd7, APO1, LOG, RFL, LRK1, EP3, Ghd8, SPA, FZP, ASP1 Grain weight GS3, GW2, GW5, GIF1, RISBZ1, RPBF Shattering Sh4, qSH1 Fertility S5, SaM, SaF, S1 Aroma BADH2 Biotic Stresses : Resistance to pyricularia, Xanthomonas, brownleafhopper, RYMV Pib, Pi-ta, Pi-k, Pi9, Pi21, Pi36, Pi37, Pikm, Pi5-1, Pi5-2, Pid3, Pb1, Pi-d2 Xa1, Xa3, xa5, xa13, Xa21, Xa27 OsH1- LOX, OsLox1, Bph14, Rymv1 Abiotic Stresses : drought salinity, cold, submergence OsSKIPa, DSM1, DSM2, OsCIPK12, OsGH3.13 SKC1, OsNAC6, OsKAT1, OsCIPK15 SNAC1, OsbZIP23, DST, AP59, OsSIK1, OsNAC10 OsCIPK03, qLTG3-1, Ctb1 OsMYB3R-2, MYBS3 Sub1A, SNORKEL1, SNORKEL2 Nitrogen use efficiency GS1.1, GS1.2, GlnA, GOGAT, OsAAT1, OsAAT2 University of Ghana http://ugspace.ug.edu.gh 27 2.6.2. Conventional rice breeding Conventional breeding of rice through Mendelian genetics took advantage of the identification of genes for major diseases and insects, agronomic traits and abiotic stresses. The major breakthroughs in conventional breeding of rice have been the development of high-yielding, semi-dwarf genotypes from different sources mainly from China and Japan (Rutger and Mackill, 2001). Another major achievement was the development of high-yielding varieties with broad adaptation for irrigated areas due to the insensitivity to photoperiod. Several photoperiod- associated genes were identified, some of which were used to improve semi-dwarf and photosensitive varieties. The first major farmers and industry-oriented traits used in rice selection have been the glabrous-hull characteristic controlled by the gl-gene (Delseny et al., 2013). The gene also confers the glabrous characteristic to the leaves, hence making hand harvesting and threshing easier. Another farmer- oriented trait was the purple leaf conferred by the pl gene. Purple leaf rice varieties have been adopted by farmers in some areas to facilitate the removal of green weeds, particularly in direct-seeded systems (Kinoshita and Maekawa, 1986). In order to exploit full potential of rice varieties, compatible genotypes were used to develop hybrid rice. Hybrid rice produced 15-22% higher yield than the best available inbred cultivars (Nanda and Virmani, 2000); this increase has gone to over 55% yield increase with newer hybrids (Akram et al., 2007; Chen et al., 2007; Xangsayasane et al., 2010; Berger et al., 2012). Grain quality was also a major focus in conventional rice breeding for instance waxy gene (wx) is expressed in varieties that have low amylose content in endosperm starch. As a result, waxy rice varieties are preferred for pastries and ceremonial foods (Kobayashi and Nishimura, 2007). As part of the improvement of grain quality, aromatic rice varieties have been developed mainly University of Ghana http://ugspace.ug.edu.gh 28 in USA and Asian countries (Kibria et al., 2008). Recently, some breeding programmes in West Africa showed interest in such varieties (Asante, 2009). Conventional breeding of rice for resistance to pest and diseases contributed a lot to reduction of in yield. Breeding for resistance to diseases and insects in rice has been considered as one of the most successful examples of the use of major genes in crops species (Rutger and Mackill, 2001). Rice varieties resistant to rice blast caused by Magnaporthe grisea and bacterial blight caused by Xanthomonas campestris have been produced (Ogawa and Khush, 1989). In some cases, gene pyramiding has been performed to achieve more durable and broader resistance (Huang et al., 1997). Two major virus diseases (rice tungro and rice yellow mottle diseases) have attracted much attention from breeders. Several near-isogenic lines carrying resistance genes from diverse donors including traditional varieties and wild rice (O. rufipogon) have been produced (Azzam et al. 2002). In the case of rice yellow mottle disease, development of resistance varieties mainly targeted the high resistance and recessive RYMV1-gene. Allele rymv1-2 from Gigante was introduced in susceptible rice IR64 and other varieties do develop resistant near isogenic lines (Jaw et al., 2012). Introgression of allele rymv1-3 from resistant O. glaberrima sources into high yielding O. sativa backgrounds by conventional breeding usually failed because of genetic barriers (Jones et al., 1997b). 2.6.3. Biotechnological and molecular approach in rice breeding Despite the barriers, natural gene flows among O. glaberrima, O. sativa and O. longistaminata have been reported, indicating the possible use of these species for rice improvement. Incompatibility barriers are now being overcome through different techniques such as embryo rescue and double haploid breeding. These techniques were successfully used to develop the so- University of Ghana http://ugspace.ug.edu.gh 29 called Nerica (New rice for Africa) varieties (Jones et al., 1997b; Li et al., 1997; Sie et al., 2010). Advances in biotechnology, genomic research, and molecular marker applications and their integration with conventional plant breeding have revolutionized crop improvement practices. For example, marker assisted backcrossing can halve the number of backcrosses necessary to incorporate a gene of interest into a preferred genetic background (reviewed by Dudley, 1993). Marker assisted backcrossing is especially attractive for recessive genes, such as RYMV1. There is no need to identify heterozygous individuals in the backcross generations by traditional methods using several selfing steps. The heterozygous individuals carry the gene of interest are needed for the production of the next backcross. The traditional genotyping procedure is time consuming and involves the detection of segregation in progeny produced by selfing individuals from each backcross generation. Marker assisted selection was used for rice improvement in relation to resistance to RYMV. RFLP and microsatellites markers were used to test efficiency of introgression of partial resistance into O. sativa cultivars (Ahmadi et al., 2001). Recently, markers specific to the different alleles of the RYMV1 gene were developed for marker-assisted selection (Thiemele et al., 2010). They are located inside RYMV1 gene and differed from previously used markers such as RM241, RM273 and RM252 which were outside the gene (Albar et al., 2003; Sow, 2012). University of Ghana http://ugspace.ug.edu.gh 30 CHAPTER 3 3. IMPACT OF RICE YELLOW MOTTLE DISEASE ON FARMERS’ PREFERRED RICE VARIETIES IN BURKINA FASO 3.1. Introduction Rice (Oryza sativa L. and O. glaberrima Steud.), as a major food crop in Sub-Saharan Africa (SSA), plays a key role for food security in this region. The overall paddy rice production in the region was estimated at 18.5 million tons (FAOSTAT 2011), which covers only half of the consumption needs. Rice demand has more than tripled from 1.9 to 5.8 million tons over the past two decades in SSA countries (Ogunbayo et al., 2005; 2007). Following the recent food crisis (Seck et al. 2012), several West African countries adopted strategies for increasing rice production. These included large scale use of improved seeds, better technical assistance to rice farmers and increase of rice cultivation. Since the early 1990s, rice production has been severely affected by rice yellow mottle disease caused by Rice yellow mottle virus (RYMV) (Kouassi et al. 2005). The disease is widespread in most rice growing countries in Africa including Madagascar. RYMV is non-seed transmissible in rice and wild host species (Konate et al. 2001; Allarangaye et al. 2006). However, it is known as a highly infectious and very stable virus transmitted by several means including wind, insects, mammals and man (Bakker 1970; Sarra et al. 2004; Traore et al. 2005). Significant yield losses, induced by RYMV (25-100%), have been reported, although most studies were done under experimental conditions (Rechkaus and Adamou 1986; Fomba 1988; Taylor et al., 1990; Konate et al. 1997; Kouassi et al. 2005). Rice genotype and age of plants during infection have been shown to be major factors influencing yield reduction. University of Ghana http://ugspace.ug.edu.gh 31 Most cultivated rice varieties belong to O. sativa species and have been reported to be highly susceptible (Rakotomalala et al. 2008). Attempts to control rice yellow mottle disease have been mainly directed to breeding for resistance to RYMV (Thiemele et al. 2010). A few sources of resistance to be used in breeding programs have been identified (Thottappilly and Rossel 1993; Ndjiondjop et al. 1999; Rokotomala et al. 2008; Thiemele et al. 2010). However, the durability of such resistance has been questioned, as resistance-breaking isolates of the virus have been shown to occur frequently (Sorho et al. 2005; Traore et al. 2006a). Consequently, Traore et al. (2009) concluded that integrated management strategies should be adopted for durable control of the disease. The use of insecticides was found to effectively control populations of some insect vectors (Abo et al. 1998). However, chemical control of rice yellow mottle is economically unfeasible and difficult to effectively use due to the large number vector species (Calvert et al. 2003). Consequently, sustainable management of the disease should rely mainly on genetic control combined with effective phytosanitary and good cropping measures. Farmers' involvement in the process of disease control can be of great importance in the success of management practices as exemplified by the wide application of farmers' field schools in recent years (Roling et al. 1994). The development of integrated pest management technologies for rice farmers in Asia has been relatively successful (Adesina et al. 1994). This success was attributed to extensive creation of farm-level awareness of pest and diseases and management strategies. By contrast, only a few similar studies have been conducted in Africa and this has probably limited the success of IPM implementation for sustainable rice production. In a previous study focused on traditional rice varieties, farmers’ perception of rice yellow mottle disease was appraised in a limited area of South West region of Burkina Faso (Kam, 2011). The present study was conducted in other rice growing areas of the country to assess farmers' University of Ghana http://ugspace.ug.edu.gh 32 awareness, perception and management practices of rice yellow mottle disease and the impact of RYMV on their preferred varieties. 3.2. Materials and methods 3.2.1. Survey areas In this study, surveys were conducted in two locations including Banzon (11°19'0.00"N; 4°47'60.00"W) and Mogtedo (12°17'03.84"N; 0°50'14.00"W), representative of the wet and the dry savannah zones, respectively. In both locations, rice is grown under irrigation and rice yellow mottle disease occurs endemically. Banzon has a full irrigation system for growing rice all year round using water from a permanent river. At Mogtedo, irrigation water is mostly from reservoirs fed by rainwater and located up stream. Availability of water for irrigation is therefore dependent on rainfall and there is more lowland and rainfed rice than in Banzon. 3.2.2. Sampling procedures and data collection Surveys were conducted using two complementary approaches: (i) informal discussions with farmers in the field and (ii) questionnaires (Figure 3.1). All interactions with farmers were done in local languages to ensure effective understanding. Over 200 farmers (100 per locality) were interviewed (appendice 1). Farmers were randomly selected regardless the gender around their cultivation perimeters. Data were collected on farmers' awareness, perception and control of rice yellow mottle disease. Data on farmer's criteria for preference of rice varieties were also collected. Figure 3.1. Interaction with farmers during interviews and informal discussions University of Ghana http://ugspace.ug.edu.gh 33 3.2.3. Yield loss and disease incidence assessment in farmers’ field Yield losses due to the virus were assessed in three rice varieties in Banzon locality during 2010 and 2011 main rice growing seasons spanning from June to October. This activity was conducted from 100% flowering to grain filling stage. For each rice variety, a total of 50 diseased plants and 50 symptomless plants were randomly selected in five distinct 500 m²-blocs which were at least 50 meters apart. All plants were tagged with two different color labels (Figure 3.2). At maturity, rice panicles from individual plants were harvested and dry seeds (11% humidity) weighed. Yield losses were computed by comparing yield means from healthy and diseased plants. Figure 3.2. Single plant yield comparison: (A) Healthy and diseased plant tagged with white and black sachet respectively; panicles harvested from healthy (B) and from diseased (C) plants. Disease incidence was assessed in the whole perimeter regardless of rice varieties in five blocs which were 100 meters apart. In each bloc, 1000 plants were randomly examined and diseased plants were counted. 3.2.4. Data analysis Data on farmer’s interviews were analyzed using SPHINX-PLUS© software version 4.5. Significance of differences in mean yield losses between rice varieties were tested by analysis of University of Ghana http://ugspace.ug.edu.gh 34 variance (ANOVA) using STATISTICA software. Data on disease incidence were also analyzed by ANOVA after angular transformation (Zar 1999). 3.3. Results 3.3.1. Features of rice production Rice production in both Banzon and Mogtedo was dominated by male farmers (87.2%). There were more female farmers in Mogtedo (22.3%) than in Banzon (3.0%). Most farmers appeared to have long experience in rice cultivation since 87.2% had been producing rice for more than five years. Rice production was largely dominated by smallholders in both locations. About 98.5% of farmers cultivated fields ranged from 0.5 ha to less than 5 ha. Larger field sizes (5 to more than 10 ha) were held by only a few farmers. Most farmers (58% and 94% at Banzon and Mogtedo, respectively) experienced low yields of 1-2 t/ha. Accordingly, 42% of Banzon farmers and only 6% of Mogtedo farmers recorded higher yields of 3-5 t/ha. All farmers were also involved in the production of other crops including cereals, dry legumes and vegetables. 3.3.2. Rice varieties grown and farmers' preferred varieties A total of 13 rice varieties were inventoried in the two study areas which shared only six varieties (Figure 3.3). Most farmers indicated simultaneous cultivation of several varieties. The proportion of farmers using one, two or three varieties were 17.7%, 31% and 51.3%, respectively. Varieties common to the two localities included FKR14, FKR19, FKR28 and three interspecific O. sativa x O. glaberrima derived NERICA varieties (FKR56N, FKR60N and FKR62N) (Sie et al. 2007). The majority of farmers in Banzon (70.8%) cited four varieties including FKR18, FKR19, FKR60N and FKR62N as the common varieties grown, FKR18 being the most common (20.4%). However, FKR62N was quoted as the best yielding among NERICA varieties. At Mogtedo, FKR19, FKR56N, FKR60N and FKR62N were the most frequently University of Ghana http://ugspace.ug.edu.gh 35 grown varieties (83.5% of farmers). However, FKR19 clearly was favoured over the NERICA varieties as indicated by 42% of farmers. Figure 3.3. Farmers' grown and f preferred rice varieties in Banzon (A) and Mogtedo (B). Farmers' preferred rice varieties in Banzon somewhat matched the top grown varieties except for FKR19. The three NERICA varieties were part of the most preferred varieties, as 43% of farmers preferred them. Yet, most farmers (38%) preferred FKR18, indicating a clear-cut choice for this variety. In Mogtedo, FKR19 was by far the most preferred variety chosen by 65% of farmers. University of Ghana http://ugspace.ug.edu.gh 36 NERICA varieties were also among Mogtedo farmers' top choices but to a lesser extent compared to Banzon. Hence, the proportion of farmers who preferred these varieties as a whole was only 24.3%. Altogether, farmer's choice for rice varieties strongly depended on varieties they usually grew. This was apparent in both Banzon and Mogtedo (P<0.001). Definitely the five top farmers’ preferred rice varieties in both study areas included FKR18, FKR19, FKR56N, FKR60N and FKR62N followed by TS2, FKR28, FKR16, FKR14, FKR34 and C2. The underlying criteria driving farmers' preference for rice varieties varied in the different the localities surveyed. In Banzon and Mogtedo, high yielding and high market value varieties were among the important criteria considered (Figure 3.4). Taste was the first criterion mentioned by farmers at Banzon. Other characteristics were disease resistance and availability of good seeds. Figure 3. 4. Farmers’ preferential criteria for rice varieties in Banzon and Mogtedo Grain quality, resistance to pests and plant height and length of the growing period were considered to be of secondary importance. By contrast, farmers in Mogtedo stated yield as their foremost criterion. Although high market value varieties were among their primary criteria, University of Ghana http://ugspace.ug.edu.gh 37 length of the growing period and plant height were also important. All other factors including pest and disease resistance were minor. 3.3.3. Major constraints to rice production Prominent constraints to rice production mentioned by farmers at Banzon and Mogtedo were water shortaage and diseases (Figure 3.5). Lack of access to fertilizers and their high cost were considered as moderate constraints, particularly at Banzon. Other constraints including availability of quality seeds, lack of technical assistance and damage by insect pests, weeds, birds, and grazing mammals were referred to as less important. Water shortage and diseases were the most important constraints in Mogtedo. Moreover, constraints in this locality were of greater importance than in Banzon. Figure 3. 5. Main constraints to rice production mentioned by farmers at Banzon and Mogtedo (A) Rice stem borer in rice stalk, showed by a farmer at Banzon and (B) dead panicle caused by rice stem borer B A University of Ghana http://ugspace.ug.edu.gh 38 Rice yellow mottle disease was the most important disease cited by farmers at both Banzon and Mogtedo (Figure 3.6). Secondary diseases and pests included African gall midge (Orseolia oryzivora Harris & Gagne [Diptera: Cecidomyiidae]) and rice blast. Iron toxicity was also mentioned, particularly at Banzon, even though it is an abiotic stress. Some of the farmers were unaware of the occurrence of diseases. They recognized symptoms but attributed them to different factors such as soil infertility, soil degradation or by ash coming from burned rice residues when cleaning the fields. 3.3.4. Rice yellow mottle disease and its management Farmers used expressive terms to refer to most important diseases they observed. Hence, rice yellow mottle was referred to as "rice HIV" because like Human immunodeficiency virus, once a rice plant was infected, it remained so until death or harvest (Figure 3.5). Figure 3. 6. Farmers’ awareness of rice diseases in Banzon and Mogtedo; (A) a farmer in Mogtedo able to identify rice yellow mottle disease symptoms on rice leaves A University of Ghana http://ugspace.ug.edu.gh 39 In several instances, farmers did not give any particular name, but stated symptoms which might have been caused by RYMV. Such symptoms included "yellowing of the leaves", "plant stunting" "panicle sterility", cited alone or in combinations. Gall midge was referred to as "dead heart" or "antenna" to describe the characteristic onion shoots galls. Up to 85% of farmers stated that they adopted at least one control measure against rice yellow mottle disease. Replacement of rice varieties and use of pesticides were some of the common control measures. Farmers indicated that no recommendations were given to them for the use of pesticides, yet they systematically adopted this measure blindly as a first solution. Shifting varieties was more widespread at Banzon where farmers benefited more from technical assistance while pesticides application in rice fields was practiced more at Mogtedo (Figure 3.6). Indigenous control methods included cropping practices, spray of of pesticides and abandon of the fields for one or two years. Cropping practices comprised disease avoidance through delay of sowing and transplanting dates, weeding rice fields as well as clearing levees and ditches around fields. Figure 3.7. Rice yellow mottle control methods used by farmers in Banzon and Mogtedo; (A) a farmer spraying pesticide on rice field in Mogtedo A University of Ghana http://ugspace.ug.edu.gh 40 Most farmers indicated that varietal shifts and other cultural practices were recommended by extension agents although these recommendations were not usually effective because they continued to experience yield losses due to diseases. 3.3.5. Yield loss assessment and disease incidence Yield loss due to rice yellow mottle disease was assessed for three rice varieties including FKR56N, FKR62N and TS2 (Table 1). Rice yellow mottle disease had a high impact on grain yield reduction. Average yield losses of approximately 75%, 79% and 84% were recorded in rice varieties TS2, FKR62N and FKR56N, respectively. Consequently, the overall yield loss induced by rice yellow mottle disease was estimated at 79.33% in average. Analysis of variance of per plant grain yield indicated significant effects of disease (F=1832.1; df=1, 600; P<0.0001) and rice variety (F=25.95; df=2, 600; P<0.0001). There were also disease- variety (F=12.61; df=2, 600; P<0.001) and disease-year (F=6.35; df=1, 600; P=0.012) interactions, indicating that the effect of disease on yield depended on varieties and year of production. In the first year, diseased plants of rice varieties TS2 and FKR62 yielded twice as much as those of FKR56N. By contrast, higher yields were found in TS2 only during the second year. Table 3.1. Effect of rice yellow mottle disease on grain yield in three rice varieties Variety Year 1 Year 2 Healthy Diseased Yield loss (%) Healthy Diseased Yield loss (%) FKR56N 38.94aa 4.40a 88.70a 35.83a 7.30a 79.63a FKR62N 47.33b 10.10b 78.66a 47.23b 7.43ab 80.14a TS2 38.18a 8.03b 78.97a 35.59a 10.50c 70.50a aFigures in the table represent means of per plant paddy rice yields in grams (n=50). Means within the same column followed by the same letter(s) are not significantly different (P=0.05), according to Fisher's LSD. University of Ghana http://ugspace.ug.edu.gh 41 The levels of rice yellow mottle disease infections in Banzon were moderate. Disease incidence was evaluated at 29.54% in 2010 and 26.98% in 2011. The difference in disease incidence was not significant (F= 0.19; df=1; P=0.67), indicating consistent epidemic levels over the two years. Taking into account the average yield loss assessed earlier, observed disease incidences would give extrapolated yield loss of 22.33% per year in Banzon perimeter. 3.4. Discussion The two study areas had contrasting ecologies and rice growing systems. Rice cultivation in both areas was at subsistence levels. Most farmers held small fields, and also most (76%) had low yields of 1-2 t/ha, which is consistent with the results reported for the whole West Africa (Saito et al. 2012). Almost all farmers practiced mixed cropping. The strategy of growing several crops has been considered as a way to improve resilience (Lin 2011). However it may prevent farmers from focusing sufficiently on adequate production of one particular crop, which could benefit rice intensification. Altogether, features of rice cultivation observed here reflected a more general situation common to SSA which also applies to other major crops like maize, sorghum, and cassava (Fermont et al., 2009). For rice in particular, Adesina et al. (1994) reported that rice farming in the Ivory Coast was dominated by small scale farmers with minimal external fertilizer input and very little technical assistance from extension agents. Similar characteristics were found in the present study, as the vast majority of farmers (98.5%) held small plots of less than 5 ha and technical assistance was stated as a constraint, particularly at Mogtedo. However, efforts are being made to provide more support to farmers by providing them with improved quality rice seeds and fertilizers along with closer technical assistance. At both Banzon and Mogtedo, several rice varieties were grown by farmers on a regular basis, irrespective of recommendations from extension agents. By growing several varieties, farmers University of Ghana http://ugspace.ug.edu.gh 42 adopted the same resilience strategy for rice as for other crops. As such, based on their own empirical knowledge, one particular farmer would grow at least two rice varieties, one early maturing though usually low yielding and one late maturing. This strategy was clearly exemplified by the choice of FKR18 and FKR19 as top varieties by farmers at Banzon and Motgedo,. FKR18 was considered by farmers as high yielding with good taste at Banzon but needed more water than FKR19. As for Mogtedo farmers, whose main concern was water availability, FKR19 was their top variety because of its better resistance to drought as well as its capability to be grown under irrigated and rainfed conditions. NERICA varieties were among top farmers' preferred rice varieties. Indeed, successful promotion strategies were put in place by AfricaRice through participatory variety selection work involving female and male farmers after the development of these varieties (Seck et al. 2012). The national research team also provided strong advertising locally. In the present study, women only represented a small proportion of farmers despite the promotion of several women farmers' organizations in Mogtedo. However, they may have played a significant role in the adoption of varieties through the appreciation of post-harvest processing properties. Possibly, the utmost reason for choosing NERICA varieties was their good yields as indicated by farmers who experienced 3-5 t/ha. These data are consistent with the potential yields of 5 to 7 t/ha (Sie et al., 2007) as on-farm yields were usually found to be lower than potential yields (Becker et al., 2003). Results on yield loss assessment (Table 1) confirmed the higher yield of FKR62N as quoted by farmers during the survey. Although NERICA varieties were highly preferred by farmers, they were not the top preferred, neither at Banzon nor at Mogtedo. According to farmers, FKR18, the top preferred variety at Banzon was one of the recommended rice varieties about 30 years ago. Later on, technical assistance dissuaded farmers from growing it because of University of Ghana http://ugspace.ug.edu.gh 43 its high susceptibility to rice blast despite the high yield potential of 5-6 t/ha. NERICA varieties which exhibited moderate resistance to this disease (Sie et al., 2007) were deployed but farmers kept growing FKR18 primarily for its good taste. A similar behaviour was observed in 2002 in Mali where rice variety BG90-2 was grown by some farmers for their own consumption because of its good taste while varieties recommended for rice yellow mottle disease management purpose were grown for market (Traore O., unpublished data). The choice of FKR 19 as top preferred variety at Mogtedo did not follow the same rationale. The water shortage constraint and need for getting good yields made FKR19 the best choice in that locality. Rice diseases were reported by farmers as very important constraints. The opposite opinion was reported eighteen years ago in Ivory Coast where only a small proportion of farmers (9%) mentioned diseases among major constraints in rice (Adesina et al. 1994). Farmers' unawareness of diseases was one of the main reasons for the low level of importance they attached to such constraints. Hence, farmers usually mistook diseases for soil infertility symptoms. Recently, farmers and extension agents have been involved in routine trainings with the goal of improving rice production. These trainings allowed several farmers to become familiar with diseases and pests including rice yellow mottle, rice blast, African gall midge, particularly at Banzon and other main irrigated rice areas. This confirmed results obtained in other rice cultivation areas in Burkina Faso (Kam, 2011). Sow (2012) also reported that farmers in Niger mentioned rice yellow mottle disease and bacterial leaf blight as major diseases in irrigated rice systems. Lack of knowledge on rice diseases was perceivable especially at Mogtedo, which may have lowered the proportion of farmers considering diseases as constraints. Farmers recognized RYMD as the most important rice disease but control measures applied were not effective. Due the complexity of disease epidemiology, Traore et al. (2009) argue that an University of Ghana http://ugspace.ug.edu.gh 44 integrated disease management approach combining the deployment of resistant cultivars with prophylactic measures should be implemented. Although economically unfeasible (Calvert et al. 2003) and environmentally-unfriendly, the use of pesticides by farmers possibly had some effect on insect vectors. Effectiveness of varietal shift would have been significant if farmers' varieties were resistant to the disease. Unfortunately, all rice varieties, including NERICA varieties were severely affected by the disease, indicating their susceptibility. Yield loss assessment due to RYMD on three rice varieties indicated the high yield reduction of the disease whatever the variety. Average per plant yield was estimated at 79.33% with an extrapolated overall yield loss of 22.3% based on disease incidence in the fields. Such moderate levels of yield loss were less than losses ranging from 58-82% reported during severe epidemics (Reckhaus and Adamou 1986; Taylor et al. 1990). This was consistent with relatively low disease incidence observed in the fields and indicated that the survey was done in low epidemic years. University of Ghana http://ugspace.ug.edu.gh 45 CHAPTER 4 4. SCREENING OF RICE ACCESSIONS FOR RESISTANCE TO RICE YELLOW MOTTLE VIRUS IN BURKINA FASO 4.1. Introduction The necessity for disease management in rice has come to the foreground of crop production since the green revolution. Several damaging outbreaks occurred with all the main virus diseases of rice including rice yellow mottle, hoja blanca, rice grassy stunt and rice ragged stunt (Thresh 1989). Rice yellow mottle disease is endemic to Africa where it is confined. It is induced by Rice yellow mottle virus (RYMV) which is considered as the most damaging rice pathogen on the continent. Yield losses often vary from 25 to 100% (Abo et al., 1998). RYMV is easily transmitted mechanically but field dissemination is done by a number of vectors among which beetles are likely the most important. The main control methods of rice yellow mottle disease include the use of resistant genotypes and application of insecticides to control the vector of RYMV. The use of pesticides in modern agriculture has contributed to improved world food supply through the achievement of better plant growth and yield. However, pesticides and particularly insecticides are often hazardous and their indiscriminate use for controlling pests in crops has been associated with several drawbacks such as resurgence of resistant insect populations, poisoning of farmers and environmental pollution (Hashmi and Khan, 2011). Pesticides, therefore, need to be used in a more responsible manner in order to preserve the environment (Conway, 2012). Host plant resistance to biotic stresses can play a pivotal role in crop protection (Bonman et al., 1992; Leung et al., 2003). Use of resistant varieties has been considered as an attractive and effective means to control diseases. It requires no additional cost other than that of seeds of University of Ghana http://ugspace.ug.edu.gh 46 resistant genotypes and it is environmentally safe (Mew, 1991). Moreover, unlike other disease management technologies, resistant varieties can easily be adopted by farmers and widely disseminated. These considerations are particularly applicable to the context of rice growing systems in Africa where almost all farmers are smallholders. Sources of resistance to pests and diseases need to be identified and evaluated for their efficiency. A lot of research on rice has been devoted to screening rice germplasm and wild rice species for resistance to biotic and abiotic constraints. Many reports by international institute of tropical agriculture (IITA) and by AfricaRice (formerly West African Rice Development Association, WARDA) have identified sources of resistance to RYMV within rice germplasm. Many accessions including O. sativa, O. glaberrima and wild species O. longistaminata and O. barthii were screened at IITA and at AfricaRice using either mechanical inoculation of the virus or direct field exposure (Thottappilly and Rossel, 1993; Ng et al., 1988; Attere and Fatokun, 1983; Awoderu, 1991; Raymundo and Konteh, 1980; Okioma and Sarkarung, 1983). Several national research institutions have also screened local accessions for resistance to RYMV (Fomba, 1988; Coulibaly et al., 1999; Zouzou et al., 2008; Rakotomalala et al., 2008; Moga et al., 2012; Sow, 2012, Kam, 2011; Jaw, 2010). Resistance to RYMV has been found in several accessions (Table 4.1). Consistency in varietal reaction between authors has been observed in a few cases such as the high resistance in Gigante, Bekarosaka, Tog5672, Tog5674, Tog5681 and Tog7291. By contrast, conflicting reactions were observed in several cases. For instance, accessions such as rice cultivars Moroberekan and OS6 were found highly resistant or even immune in some studies (Awoderu, 1991, Zouzou et al., 2008) but only partially resistant in others (Thottappilly and Rossel, 1993). Coulibaly et al. (1999) reported OS6 as a susceptible accession. More strikingly, the rice cultivar Moroberekan University of Ghana http://ugspace.ug.edu.gh 47 showed different reactions when it was grown under irrigated versus rainfed conditions (Zouzou et al., 2008). .Table 4. 1. Some reactions of rice accessions to rice yellow mottle virus Resistance level Accession Reference Immune ExDoko, Tob5689, Tob5701, Tob7382, Tog5379, Tog5674, Tog5681, Tog7235, Tog7291 Tol12, Tol268 Thottappilly et al., 1993 TOG 5672 Coulibaly et al., 1999 High resistance ITA235, ITA257, IDSA6, FAROX299, IAC164, Itame Nembeika,Azi, Toubabou, Gnonkonsoka, Moroberekan, 0S6 Awoderu, 1991; Zouzou et al., 2008 IRAT156, ITA 315, IR50, IR56, IRAT170, ITA128, IRAT161, IRAT104, ITA305, ITA303, BPT1235, W1263, GEB24, PY2, Kalinga2, Kannagi, IR9830-26-3-3 Awoderu, 1991 Gigante, Bekarosaka, Tog5681, Tog7235, Tog7291, Tog5675, Tog5674, Tog7226, Tog7238, VL6, VL123 Coulibaly et al., 1999; Ndjiondjop et al., 1999 ; Rakotomalala et al., 2008 Thiemele et al., 2010, Partial resistance MRC603-303. Ratna, Tnau175, TKM9, MTU15, KAU I675. Kaohsiung-Senyu, IR29, IR46, PVRI, UPR254-21-1,IR9802-31-2,IITA, FR77068-2, IR 19473-461-2-3-3-2 Awoderu, 1991 OS-6, Moroberekan, LAC23, CT19, IRAT110. ITA-235, ITA257, ITA303, ITA305, ITA307, ITA313, ITA315 Thottappilly et al., 1993 IRAT104, Moroberekan, FKR33 Coulibaly et al., 1999 University of Ghana http://ugspace.ug.edu.gh 48 Inconsistancies in reactions to RYMV across accessions likely reflect the fact that RYMV isolates differed. Therefore, accessions reported as resistant in a given area were susceptible elsewhere. RYMV isolates are known to display a high diversity according to their geographical and ecological origins (Traore et al. 2005; Traore et al. 2006a; Nguessan et al., 2000). In West Africa alone, three major RYMV strains, S1, S2 and Sa, were found based on the coat protein variability. Another layer of complexity is that each strain exhibits different pathogenic features. The occurrence of resistance-breaking isolates that are able to overcome all known resistant genes (Koala, 2012) is a serious threat for the durability of resistances in fields. Crosses between a few O. glaberrima accessions have indicated the existence of additional potential resistance genes (Ahmadi N. and Singh B., 1995; Paul et al., 2003). The objective of this study was to evaluate the reaction of rice accessions collected from Burkina Faso and Ghana to all the major RYMV strains occurring in West Africa. 4.2. Material and methods 4.2.1. Study area This study was conducted at Kamboinse research station of the Institute of Environment and Agricultural Research (INERA, Burkina Faso), at 12˚28'N latitude, 1˚32'W longitude. Local weather conditions were characterized by 600-900 mm annual rainfall, 75-90% relative humidity, and temperature between 25-33°C. 4.2.2. Germplasm collection Rice varieties were collected from national research systems including INERA (Burkina Faso) and CSIR-crops research institute of Kumasi/Ghana. Farmer’s landraces were also collected mainly from lowland rice cultivation areas in different localities of the western region of Burkina Faso and from the Volta region of Ghana. Germplasm collected from INERA included a subset of ten top farmers’ University of Ghana http://ugspace.ug.edu.gh 49 preferred rice varieties identified from a participatory rural appraisal study in Banzon and Mogtedo rice growing areas.(Chapter 3) The rice accessions were stored in a cold room at 10-15°C. 4.2.3. Sources of inoculum All virus isolates used in the experiments originated from West African countries. They were part of INERA plant virus collection maintained at the Laboratory of Plant Virology and Biotechnology. In a first experiment, a viral mixture (Virus mixture-1) was made of all non- resistance breaking isolates (nRB) presented in Table 4.2. Leaf samples infected by corresponding isolates were mixed at equal weights. Of the 11 nRB isolates, six were of strain S1 and the remaining isolates belonged to strain S2. In a second experiment, another mixture (Virus mixture-2) made of nine resistance breaking (RB) isolates of RYMV strains S1 (4 isolates), S2 (4 isolates) and Sa (1 isolate). A third experiment involved 20 RYMV field isolates collected from main rice cultivation areas in Burkina Faso, distinct from those used in the two previous experiments. These isolates were all used singly to screen 23 rice accessions including resistant check varieties. 4.2.4. Inoculation 4.2.4.1. Virus propagation All selected virus isolates (Table 4.2) were first multiplied in susceptible rice cultivar BG90-2 using mechanical inoculation. Inoculations were done in an insect-proof greenhouse. Infected leaf samples were ground with sterile pestles and mortars in inoculation buffer (0.05 M potassium phosphate buffer, pH 7.0). To ease the grinding process, 1 g of leaf sample was homogenized in 10 ml of buffer containing a pinch of acid-washed sterile sand. Then, carborundum (600 mesh) was added to the extracts which were subsequently rubbed onto the leaves of 21 days post-germination rice seedlings. Leaves from plants infected with each isolate University of Ghana http://ugspace.ug.edu.gh 50 that showed clear visible symptoms were harvested two weeks post-inoculation and used as source of inoculum. Susceptible variety BG90-2 and other rice varieties with known resistance phenotypes were used as controls (Table 4.3). All rice accessions were screened in the greenhouse by mechanically inoculating the virus to five plants of each accession. Virus inoculation was done 21 days post germination (dpg). Symptoms development was monitored for up to 45 days post-inoculation (dpi). Table 4. 2. RYMV isolates selected from INERA RYMV collection used for screening rice accessions RYMV Origin Straina Pathogenicityb isolates Gigante Tog5681 Pathotype 854-1 Burkina Faso S1 - + RB-rymv1-3 854-2 Burkina Faso S1 + - RB-rymv1-2 854-3 Burkina Faso S1 - - nRB 854-4 Burkina Faso S2 - - nRB 854-5 Burkina Faso S2 + + RB-rymv1-1/rymv1-3 466-1 Mali S1 - - nRB 466-2 Mali S1 - - nRB 466-3 Mali S2 - + RB-rymv1-3 466-4 Mali S2 - - nRB 466-5 Mali Sa + - RB-rymv1-2 University of Ghana http://ugspace.ug.edu.gh 51 562-1 Niger S1 + + RB-rymv1-2/rymv1-3 562-2 Niger S1 - - nRB 562-3 Niger S1 + - RB-rymv1-2 562-4 Niger S1 - - nRB 562-5 Niger S1 - - nRB 288-1 Ghana S2 - - nRB 288-2 Ghana S2 - - nRB 288-3 Ghana S2 - - nRB 288-4 Ghana S2 + - RB-rymv1-2 288-5 Ghana S2 + - RB-rymv1-2 aVirus strains were determined based on the variability of the coat protein gene (Traore et al., 2010). bVirus isolates were assigned to pathotypes depending on their ability to overcome (+)allele rymv1-2 in Gigante (RB-rymv1-2) or Tog5681 (RB-rymv1-3) or simultaneously both alleles (RB-rymv1-2/ rymv1- 3). Isolates not able to overcome (-) any RYMV1 resistance allele as well as RYMV2 gene were included in pathotype nRB. 4.2.4.2. Screening of rice accessions Leaves of inoculated plants were collected at 14 dpi for leaf virus content assessment. Leaf virus content was assessed in leaf extracts by double antibody sandwich Enzyme-linked immunosorbent assays (DAS-ELISA) using a broad spectrum polyclonal antibody (Traore et al., 2008a). All leaf extracts were tested in triplicate. University of Ghana http://ugspace.ug.edu.gh 52 Table 4. 3. Characteristics of rice varieties used as susceptible and resistant checks Rice varieties Species Gene Allele Phenotype BG90-2 O. sativa RYMV1 rymv1 Susceptible Azucena O. sativa japonica RYMV1 rymv1 Partial resistance Gigante O. sativa indica RYMV1 rymv2 High resistance Bekarosaka O. sativa indica RYMV1 rymv2 High resistance Tog5681 O. glaberrima RYMV1 rymv3 High resistance Tog5672 O. glaberrima RYMV1, RYMV2 rymv4 High resistance Tog5674 O. glaberrima RYMV1 rymv5 High resistance Tog7291 O. glaberrima RYMV2 - High resistance 4.2.5. Data analysis Data was analyzed using Statistica software ver.6 (StatSoft France, 2001). One-way analysis of variance (ANOVA) was used to test differences in the mean number of days for symptom appearance between accessions. Data from each accession was compared to the control BG90-2 using Dunnett’s test (cf article from Sayes et al., 2006). ANOVA was also used to test for significant differences between leaf virus contents in rice accessions. 4.3. Results 4.3.1. Germplasm collection In total, 125 rice accessions were collected from 16 locations in Burkina Faso and Ghana (Figure 4.1). Accessions were predominantly from research institutes (46 accessions from INERA including the eight checks and 45 accessions from CSIR-CRI). Most of these accessions were released after varietal improvement which did not consider rice mottle disease management. Thus, apart from varieties used as checks, the accessions had never been screened for resistance University of Ghana http://ugspace.ug.edu.gh 53 to the RYMV disease. Out of 34 accessions collected from farmers in both countries, 21 were landraces that belonged to O. glaberrima species and 13 were of O. sativa species. 4.3.2. Reactions of rice accessions to mixtures of RYMV isolates The reactions of rice accessions to the RYMV isolates are summarized in Table 4.4. Days to symptom appearance varied among the accessions inoculated with virus mixture-1. Symptoms on the leaves of the susceptible control BG90-2 were observed as early as 10 dpi and all inoculated plants showed symptoms at 13 dpi. Partially resistant control Azucena showed symptoms between 15 and 17 dpi. No symptoms were observed in highly resistant rice accessions until 45 dpi when the experiment was terminated. Ouagoudougou Kaya Manni Mogtedo Nouna Goni Dano Bapla Loto Bamako Banzo Bama Tita Fumesua Lolobi Ashiaman GHANA TOGO BENIN NIGER MALI COTE D’IVOIRE 100 km Figure 4. 1. Map of Burkina Faso and Ghana showing rice accessions collection sites University of Ghana http://ugspace.ug.edu.gh 54 Analysis of variance of the number of days for symptom appearance indicated a significant rice accession effect (F=45.38; P<0.001, df=118), which confirmed differences in reactions among the rice accessions. Post-hoc analysis using Dunnett's test and taking BG90-2 as control group indicated that, apart from accessions used as checks, all accessions could be grouped in two categories. Accessions which did not differ significantly from BG90-2 were susceptible to RYMV. They represented the largest group (65.8%). They were assigned to the susceptible (S) group. Varieties preferred by most farmers’ belonged to this group. The second group (29.6%) included accessions which showed symptoms significantly later than BG90-2. Accessions in this category belonged to the partially resistant (PR) phenotype. Only two farmers' preferred varieties (TS2 and FKR28) exhibited the PR phenotype. Reactions of rice accessions after inoculation with RYMV mixture-2 resulted in the expression of symptoms in BG90-2 earlier than with mixture-1. Symptoms appeared in some plants after 7 dpi and all plants were symptomatic at 10 dpi. By contrast, inoculated plants of the partially resistant accession Azucena showed symptoms between 14 and 18 dpi. Inoculated plants of all highly resistant checks, apart from Tog5672, were symptomatic at 17 dpi. Symptoms were visible on plants of highly resistant accessions Bekarosaka, Gigante and Tog5681 between 13 and 17 dpi. By contrast, in Tog5674 and Tog7291, inoculated plants showed symptoms between 8 and 9 dpi. Differences in reactions of rice accessions following inoculation with RYMV isolates mixture 2 were found significant in one-way ANOVA (F=42.03; P<0.001; df=123). As with virus mixture 1, Dunnett's post-hoc test resulted in three distinct groupings of accessions. Susceptible accessions formed the largest group (81.6%) while partially resistant accessions and highly resistant ones represented only 17.6% and 0.8%, respectively. University of Ghana http://ugspace.ug.edu.gh 55 Table 4. 4. Reactions of rice accessions to inoculation of two mixtures of RYMV isolates N° Rice accessiona Number of days for symptom appearanceb Virus mixture-1 Virus mixture-2 1 TS2 17.6 ± 1.5 (PR) 17.2 ± 4.1 (PR) 2 FKR2 7.8 ± 1.1 (S) 8.2 ± 1.6 (S) 3 FKR14 9 ± 0 (S) 7.2 ± 0.4 (S) 4 FKR16 9 ± 0 (S) 6.6 ± 0.5 (S) 5 FKR18 9 ± 0 (S) 7 ± 0 (S) 6 FKR19 11.6 ± 0.5 (S) 7.4 ± 0.9 (S) 7 FKR28 17.2 ± 2.9 (PR) 10.4 ± 0.5 (S) 8 FKR62N 9 ± 0 (S) 7 ± 0 (S) 9 FKR56N 9 ± 0 (S) 7 ± 0 (S) 10 FKR60N 10 ± 0 (S) 7.4 ± 0.9 (S) 11 Adaisi 9 ± 0 (S) 10.2 ± 1.8 (S) 12 Alcame-Femelle 9 ± 0 (S) 7 ± 0 (S) 13 Alcame-Male 9 ± 0 (S) 7.8 ± 1.1 (S) 14 Aromatic 15.2 ± 0.8 (PR) 15.8 ± 1.1 (PR) 15 Aromatic-short 16 ± 1 (PR) 18.2 ± 3.5 (PR) 16 Azucena 16 ± 1 (PR) 16.6 ± 1.7 (PR) 17 Basmati370 9.2 ± 0.4 (S) 8.2 ± 1.6 (S) 18 Beauty 18 ± 3 (PR) 19.6 ± 0.5 (PR) 19 Bekarosaka NS (HR) 14.2 ± 1.1 (PR) 20 BG90-2 11.6 ± 1.3 (S) 8.2 ± 1.6 (S) 21 Boning kari 9 ± 0 (S) 8.6 ± 0.5 (S) 22 Bouake189 9.8 ± 0.8 (S) 7.6 ± 0.5 (S) 23 CG14 16.4 ± 1.3 (PR) 12.6 ± 4.3 (PR) 24 Chinoire maalo 10.2 ± 1.3 (S) 6 ± 0 (S) 25 Chinois 10.2 ± 1.3 (S) 8.4 ± 0.9 (S) 26 CRI38 NERICA 5 17.8 ± 2.7 (PR) 7.2 ± 0.4 (S) 27 Digang 16 ± 2.5 (PR) 17 ± 1.7 (PR) University of Ghana http://ugspace.ug.edu.gh 56 28 Dissi 16.2 ± 1.3 (PR) 6.4 ± 0.9 (S) 29 Djineve 10.2 ± 1.1 (S) 9.4 ± 2.2 (S) 30 ”Fao” 8.6 ± 0.5 (S) 8.2 ± 1.1 (S) 31 FKR1 15.2 ± 1.8 (PR) 7 ± 0 (S) 32 FKR21 17.2 ± 1.6 (PR) 17.4 ± 2.2 (PR) 33 FKR29 21.2 ± 2.5 (PR) 16 ± 1.4 (PR) 34 FKR33 14.4 ± 0.9 (PR) 18.4 ± 0.9 (PR) 35 FKR35 10.2 ± 1.1 (S) 9.4 ± 2.2 (S) 36 FKR37 15.2 ± 1.3 (PR) 9.4 ± 0.5 (S) 37 FKR39 10 ± 0 (S) 9.4 ± 1.3 (S) 38 FKR41 14.4 ± 3.6 (PR) 15 ± 0 (PR) 39 FKR42 9 ± 0 (S) 7.4 ± 0.5 (S) 40 FKR43 21.4 ± 5 (PR) 15 ± 0 (PR) 41 FKR45N 9.8 ± 1.8 (S) 8.6 ± 0.5 (S) 42 FKR47N 21.8 ± 1.8 (PR) 10.6 ± 1.3 (S) 43 FKR48 9 ± 0 (S) 7.2 ± 0.4 (S) 44 FKR49 19 ± 0 (PR) 10.4 ± 0.5 (S) 45 FKR50 10 ± 0 (S) 7.4 ± 0.5 (S) 46 FKR58N 13 ± 0.7 (S) 8.8 ± 0.4 (S) 47 GH 4008 9 ± 0 (S) 9.2 ± 0.8 (S) 48 GH1520 21 ± 5 (PR) 21.4 ± 3.6 (PR) 49 GH1571 8.8 ± 0.4 (S) 7.4 ± 0.5 (S) 50 GH1577 19 ± 0 (PR) 16.4 ± 0.5 (PR) 51 GH1584 7.2 ± 0.4 (S) 8 ± 0 (S) 52 GH1584 bis 9 ± 0 (S) 8.2 ± 0.4 (S) 53 GH1585 7.6 ± 0.5 (S) 8.4 ± 0.5 (S) 54 GH1589 7 ± 0 (S) 6.2 ± 0.4 (S) 55 GH1796 9 ± 0 (S) 8 ± 0 (S) 56 GH1801 10.2 ± 1.3 (S) 8 ± 0 (S) 57 GH1835 8.4 ± 0.5 (S) 8.8 ± 0.4 (S) University of Ghana http://ugspace.ug.edu.gh 57 58 GH4008 10 ± 0 (S) 9.4 ± 0.5 (S) 59 Gigante NS (HR) 15.2 ± 1.8 (PR) 60 GR18 8.4 ± 1.3 (S) 7.2 ± 0.4 (S) 61 IDSA85 15.2 ± 1.1 (PR) 16.6 ± 2.6 (PR) 62 IET6279 9.8 ± 0.4 (S) 8.8 ± 1.6 (S) 63 IR5 9 ± 0 (S) 7.2 ± 1.1 (S) 64 IR64 8.6 ± 0.5 (S) 6.6 ± 0.5 (S) 65 IR67908-5-1 9.8 ± 0.4 (S) 9.4 ± 1.3 (S) 66 IR70445-146-3-3 8.8 ± 1.1 (S) 9.4 ± 1.3 (S) 67 IR70445-229-4-1 9 ± 0 (S) 10.6 ± 0.9 (S) 68 IR71137-184-3-2-3-3 11 ± 1.2 (S) 10 ± 0 (S) 69 IR71138-49-2-2-1-2 14.6 ± 1.3 (PR) 10.2 ± 0.4 (S) 70 IR72870-120-1-2-2 9.2 ± 0.4 (S) 8.2 ± 1.6 (S) 71 ITA320 9.8 ± 0.4 (S) 10.6 ± 0.5 (S) 72 ITA324 9 ± 0 (S) 10.4 ± 0.5 (S) 73 Jasmine85 9.8 ± 0.4 (S) 10 ± 0 (S) 74 KRC-Baika 10.2 ± 0.4 (S) 9.4 ± 1.3 (S) 75 Kumazuce 16.4 ± 0.5 (PR) 7.8 ± 1.1 (S) 76 Maalobo 11.2 ± 0.8 (S) 6.4 ± 0.5 (S) 77 Maalo-gwai 21.8 ± 4 (PR) 6 ± 0 (S) 78 Maaloteliman 17.2 ± 2 (PR) 7.6 ± 0.9 (S) 79 Maalowouleen 9.6 ± 0.5 (S) 6.4 ± 0.9 (S) 80 Malina 9 ± 0 (S) 8.2 ± 1.1 (S) 81 Maloba 9 ± 0 (S) 6.8 ± 1.1 (S) 82 Maloboo 9 ± 0 (S) 6.8 ± 1.1 (S) 83 Marobou 10.4 ± 1.9 (S) 7.6 ± 0.9 (S) 84 Marshall 9.2 ± 0.4 (S) 7 ± 0 (S) 85 Moobou 9.8 ± 0.8 (S) 7.6 ± 0.9 (S) 86 Moui 9 ± 0 (S) 6 ± 0 (S) 87 Mouikwin1 9 ± 0 (S) 7.6 ± 0.9 (S) University of Ghana http://ugspace.ug.edu.gh 58 88 Mouikwin2 9 ± 0 (S) 7.6 ± 0.9 (S) 89 Mouikwin3 8.4 ± 0.5 (S) 7.6 ± 0.9 (S) 90 Mouikwin4 17.6 ± 1.7 (PR) 7.2 ± 1.1 (S) 91 Mouikwin5 9 ± 0 (S) 7.6 ± 0.9 (S) 92 Mouiplaa 9 ± 0 (S) 7.2 ± 1.1 (S) 93 N28K 19.6 ± 0.5 (PR) 10.8 ± 0.4 (S) 94 Napone 8.4 ± 0.5 (S) 8 ± 0 (S) 95 NERICA1 16 ± 1.7 (PR) 10 ± 0 (S) 96 Nerica16 9 ± 0 (S) 8.8 ± 1.1 (S) 97 NERICA2 12.8 ± 1.6 (S) 9 ± 0 (S) 98 Nerica23 19.8 ± 0.4 (PR) 9.2 ± 0.4 (S) 99 Nerica24 19 ± 2.2 (PR) 13.8 ± 1.6 (PR) 100 Nerica28 16.8 ± 2.2 (PR) 7.4 ± 0.5 (S) 101 NERICA3 12 ± 0 (S) 7.2 ± 0.4 (S) 102 NERICA4 16 ± 0 (PR) 8.4 ± 0.5 (S) 103 Nerica54 9 ± 0 (S) 9 ± 0 (S) 104 Nerica7 15.4 ± 0.5 (PR) 16.6 ± 3.1 (PR) 105 Nerica9 19 ± 1.2 (PR) 14.8 ± 0.4 (PR) 106 Nerica-pluvial 14.6 ± 0.5 (PR) 13.8 ± 1.6 (PR) 107 Orodara 9.2 ± 0.4 (S) 6 ± 0 (S) 108 P38 13.2 ± 1.5 (S) 8.4 ± 0.9 (S) 109 Paroyente 8 ± 0 (S) 8 ± 0 (S) 110 Perfum-rice 10.2 ± 0.8 (S) 8 ± 0 (S) 111 Rox-cv 9.2 ± 0.4 (S) 9 ± 1.4 (S) 112 Sikamoo 9 ± 0 (S) 8.6 ± 2.2 (S) 113 Soomalo 10.2 ± 1.1 (S) 6.4 ± 0.9 (S) 114 TanghinI 9 ± 0 (S) 7 ± 0 (S) 115 TanghinII 9 ± 0 (S) 7.8 ± 0.4 (S) 116 Tiefagamalo 9 ± 0 (S) 7.2 ± 0.8 (S) 117 Tog5672 NS (HR) NS (HR) University of Ghana http://ugspace.ug.edu.gh 59 118 Tog5674 NS (HR) 8.6 ± 0.5 (S) 119 Tog5681 NS (HR) 16.6 ± 0.5 (PR) 120 Tog7291 NS (HR) 8 ± 0 (S) 121 Tox728-1 9.2 ± 0.4 (S) 8.6 ± 1.2 (S) 122 Viwonor short 19 ± 2 (PR) 10.2 ± 1.8 (S) 123 Viwonor tall 13.8 ± 0.8 (S) 7.6 ± 1.3 (S) 124 Wita7 9.8 ± 0.4 (S) 7.6 ± 1.3 (S) 125 Woussou 9 ± 0 (S) 7 ± 0 (S) aFarmer's ten top preferred rice accessions are in boldface bmean number of DSA (days for symptom appearance) post inoculation ± standard deviation (n=5) with virus mixture 1 and mixture 2 (see Material and methods); no symptom (NS) was observed in some cases; c Reaction phenotypes (indicated in parentheses) were attributed to accessions after one-way ANOVA of the number of days for symptom appearance followed by Dunnett's test (P < 0.05), taking BG90-2 as control group: S, susceptible; PR, partially resistant; HR, highly resistant. As shown in Figure 4.2, the proportion of resistant accessions identified after inoculation with virus mixture-1 was significantly less (² =7.43; P=0.006) when mixture 2 was used. Up to 14.4% of accessions identified as partially resistant following inoculation with virus mixture-1 were susceptible after inoculation with mixture-2. 4.3.3. Virus accumulation in inoculated plants Assessment of the levels of virus multiplication in plants, expressed as absorbances, indicated that rice accessions could be grouped based on the leaf virus content. Following inoculation with virus mixture 1, three groups of accessions were distinguished (Figure 4.3A). The first group consisted of all accessions identified as highly resistant (HR) when assessing the time for symptom appearance. No virus could be detected in these accessions because they reacted as the healthy control leaf extract giving a background reaction only. A second group included the susceptible check BG90-2 and accessions of the S phenotype. As indicated by the high absorbance values, accessions of the second group supported high virus multiplication. The third University of Ghana http://ugspace.ug.edu.gh 60 group included accessions of the PR-phenotype and Azucena. In this group, ELISA reactions indicated relatively low virus titres. There was a large variation in reactions of PR pathotypes as indicated by the high standard deviation value. Assessment of virus titre in leaf extracts infected by virus mixture-2 resulted in a different pattern (Figure 4.3B). High virus titre was found in Tog5672 as well as in another group of accessions including BG90-2, Tog7291, Tog5674 and all S-phenotype accessions. Lower virus titre was obtained from PR-phenotype accessions as well as Tog5681, Gigante, Bekarosaka and Azucena. A B Susceptible Partially resistant Highly resistant Figure 4. 2. Proportions of susceptible, partially resistant and highly resistant rice accessions identified after inoculation of RYMV isolates mixture 1 (A) and mixture 2 (B) University of Ghana http://ugspace.ug.edu.gh 61 0 0,5 1 1,5 2 BG90-2 S PR Azucena Bekarosaka Gigante Tog5681 Tog5672 Tog5674 Tog7291 Heathy control Absorbance at 405 nm R i c e a c c e s s i o n s 0 0,5 1 1,5 2 BG90-2 S PR Azucena Bekarosaka Gigante Tog5681 Tog5672 Tog5674 Tog7291 Heathy control Absorbance at 405 nm R i c e a c c e s s i o n s a a a a a a a b b c c a a b b b b c d cd cd cd A B Figure 4. 3. Mean of virus titres in leaves of rice accessions inoculated with mixture 1 (A) and mixture 2 (B) of RYMV isolates (see material and methods). Data from susceptible (S) and partially resistant (PR) accessions were pooled, respectively. Means associated with the same letter(s) did not differ significantly according to Fisher's LSD test at P=0.05. Error bars indicate standard deviation of the mean. University of Ghana http://ugspace.ug.edu.gh 62 4.3.4. Reactions of rice accessions to field isolates Following inoculation with individual field RYMV isolates that had not been characterized, the susceptible check BG90-2 developed symptoms with all virus isolates (Table 4.5). Partially resistant check Azucena displayed PR-phenotype with almost all virus isolates.Only isolate VII was able to overcome its partial resistance. Similarly, two accessions (Gh1577 and FKR33) showed the PR phenotype with almost all isolates but were susceptible to isolate III. The highly resistant check Gigante remained symptomless after inoculation with six of the 10 virus isolates, therefore displaying a high resistant (HR) phenotype. However, it developed symptoms similarly to BG90-2 to four isolates, indicating a S phenotype. Consequently, the six isolates which could not overcome resistance in Gigante were non-resistance breaking isolates. Alternatively, the four other isolates which induced symptoms on Gigante were resistant breaking isolates. Half of the 20 rice accessions tested showed the PR phenotype, regardless of the isolate used. The remaining accessions displayed the S phenotype in most cases, particularly with virus isolates that were able to overcome resistance in Gigante. With non-resistance breaking isolates, all accessions except CG14 showed resistance (PR phenotype). University of Ghana http://ugspace.ug.edu.gh 63 Table 4. 5. Reactions of 20 rice accessions to inoculation with 10 RYMV isolatesa Rice accessions RYMV isolates I II III IV V VI VII VIII IX X Digang PR PR PR PR PR PR PR PR PR PR TS2 . . . . . . . . . . CG14 . S S S . S S S . S GH1577 . . S . . . . . . . FKR21 . . . . . . . . . . Aromatic short . . . . . . . . . . FKR28 . . S S . . . . . . FKR29 . . . . . . . . . . Beauty . . . . . . . . . . Dissi . S S S . . . . . . FKR49 . . S S . . . . . . FKR33 . . S . . . . . . . FKR43 . . S S . . . . . . FKR47N . . . . . . . . . . IDSA 85 . . . . . . . . . . Maalo-teliman . . S S . . . . . . Moui kwin4 . S S S . . . . . . Viwonor short . . S S . . S . . . NERICA 1 . . . . . . . . . . CRI38 NERICA 5 . . . . . . . . . . BG90-2 S S S S S S S S S S Azucena . . . . . . S . . . Gigante HR S S S HR HR S HR HR HR aFor each RYMV isolate, reaction phenotypes were attributed to rice accessions after one-way ANOVA of the number of days for symptom appearance followed by Dunnett's test (P <0.05), taking susceptible (S) variety BG90-2 as control group. Azucena and Gigante were used as partially resistant (PR) and highly resistant (HR) checks. Dots represent the PR phenotype expressed by Digang. University of Ghana http://ugspace.ug.edu.gh 64 4.4. Discussion Part of the rice germplasm (16.8%) collected during the surveys consisted of accessions of the African rice O. glaberrima held by farmers. This indicates that some farmers continue to grow O. glaberrima varieties despite the fact that most rice varieties grown in West Africa belong to O. sativa species. The African rice has a low yield potential compared to its Asian counterpart, but it is used by some communities for food, rituals and herbal medicine (Linares, 2002; Van Andel, 2010). Cultivation of O. glaberrima by smallholder farmers may also be due its better adaptation to stresses caused by pests, diseases and abiotic constraints (Jones et al., 1997a). Although rice accessions in this study were collected in locations distinct from previous collection surveys (Sie, 1998; Kam, 2011), duplications likely occured. The use of molecular markers for germplasm diversity studies may provide useful information for cleaning up the duplicated rice accessions from the collection (Wong et al., 2009; Some, 2012) Screening of the collected rice accessions for resistance to RYMV indicated that virus-host interactions strongly depended on the virus isolates. Up to 45.9% of rice accessions expressed the PR phenotype with virus mixture 1. They were found to be susceptible when mixture 2 was used. Consequently, virus mixture 1, composed of non-resistance breaking isolates, was more effective in the identification of resistance in rice accessions. Virus mixture 2 was able to overcome resistance in highly resistant accessions used as controls. However, some of these accessions displayed partial resistance even though the high resistance was no longer effective. These results suggest that the mechanisms for overcoming partial and high resistance are distinct. Previous studies clearly indicated that high resistance and partial resistance have different genetic bases (Ndjiondjop et al., 1999; Ahmadi et al., 2001). Therefore, the ability of virus mixture 2 to overcome the partial resistance in some of the accessions PR to mixture 1 was not University of Ghana http://ugspace.ug.edu.gh 65 unexpected. Possibly, mixture 2 also included virulent isolates distinct from those which overcame the high resistance conferred by the RYMV1 gene. This was apparent in the breakdown of resistance conferred by RYMV2 gene in Tog7291. Altogether, screening rice accessions for resistance to RYMV indicated that most rice accessions were susceptible to RYMV, which is consistent with previous studies (Calvert et al., 2003;Coulibaly et al., 1999; Calvert et al., 2003; Zouzou et al., 2008; Sow, 2012). No new highly resistance source was identified in collected rice accessions including O. glaberrima species from which such resistance are more frequent. Additional high resistance genes are yet to be searched in rice, particularly the African rice (Ahmadi N. and Singh B., 1995; Paul et al., 2003). Therefore, screening rice germplasm for resistance to disease, particularly RYMV, needs to be continued in order to identify suitable resistance sources. Efforts are continuously to collect and preserve rice germplasm at both national and international levels. More than 200,000 rice accessions are reported in 40 national and international rice gene banks (Chen et al., 2007; Berger et al., 2012). Most accessions in these collections have not been screened for disease resistance. The present study contributed to the characterization of national rice collections to identify partial resistant accessions which can be used in breeding programmes for rice yellow mottle disease management. Conflicting results attributed to the effect of environment have been frequently reported in screening experiments conducted for the identification of resistance sources to RYMV (Kouassi et al., 2005; Zouzou et al., 2008). Indeed, the environmental conditions may have some effects on the virus-host interactions but our results suggest that most screening experiments failed to take into account the virus dimension adequately. The use of virus mixture 1 and mixture 2 composed of nRB and RB isolates, respectively, led to inconsistent identification of PR- University of Ghana http://ugspace.ug.edu.gh 66 phenotype rice accessions. This result was confirmed when field isolates of the virus were used for screening. Moreover, isolates which did not overcome RYMV1 resistance gene in Gigante gave inconsistent virus-host interactions in CG14 (Table 4.5). Overall, screening for resistance to RYMV should be based on a good knowledge of the virus diversity. The identification of sources of resistance to the virus requires the use of well characterized nRB isolates. Although virus mixture 1 and individual nRB isolates led to similar results in the identification of PR-phenotype accessions, inoculum consisting of a mixture of virus isolates may drive to synergic effects in overcoming some potential sources of partial resistance to RYMV. Indeed the biological effects of interactions between RYMV isolates are poorly known. In mixed infections of rice plants, S2 isolates dominated over S1 isolates for virus accumulation but there was no evidence of interaction in the virus accumulation between either types of isolates and S4 isolates (N'Guessan et al., 2001). University of Ghana http://ugspace.ug.edu.gh 67 CHAPTER 5 5. MARKER ASSISTED INTROGRESSION OF RYMV1 RESISTANCE GENE INTO FARMERS’ PREFERRED RICE VARIETIES 5.1. Introduction Rice plays an important role as a staple food crop in Africa, especially in West Africa (Diagne, 2011). Several authors indicated that rice is one of the four top crops that will be feeding the world population by 2050 and efforts must be made to increase its productivity (Seck et al., 2012; Alexandratos et al., 2012; Ray et al., 2013). This goal can be achieved by breeding rice to develop new high yielding and adapted rice varieties. Rice breeders have been interested in developing high yielding varieties which also combine desirable agronomic traits such as earliness and grain quality. Constraints such as pests and diseases have not been systematically taken into account in most breeding strategies. Rice yellow mottle disease is one of the most damaging rice diseases in Africa. It is caused by Rice yellow mottle virus (RYMV) which causes yield losses of 25-100% (Abo et al., 1998; Kouassi et al., 2005). In order to develop resistant rice varieties against RYMV, sources of resistance were identified by screening rice germplasm (Thottappilly and Rossel, 1993; Awoderu, 1991; Coulibaly et al., 1999). Screening rice germplasm for resistance to RYMV has been an ongoing process (See Chapter 4) (Thiemélé et al., 2010, Kam, 2011; Mogga et al., 2012). Partially resistant varieties were identified and recommended to farmers, during severe disease epidemics (Coulibaly et al., 2001). Highly resistant sources were later identified in Oryza sativa cv. Gigante (Ndjiondjop et al., 1999) and Bekarosaka (Rakotomalala et al., 2008). High resistance was also found in a few O. glaberrima varieties among which cv. Tog5681 is the most University of Ghana http://ugspace.ug.edu.gh 68 studied (Thottappilly and Rossel, 1993; Konaté et al., 1997; Ndjiondjop et al., 1999; Thiemele et al., 2010). The identified sources of high resistance were poor yielding or poorly adapted, so they have only been used in breeding for resistance to RYMV (Ndjiondjop et al., 1999). Studies were conducted to ascertain genetic basis of resistance to the virus. Partial resistance was found to be polygenic (Albar et al., 1998; Ioannidou et al., 2000) and high resistance was monogenic and recessive, and involved two genes, namely RYMV1 and RYMV 2 (Ndjiondjop et al., 1999; Thiemele et al., 2010). Further studies on RYMV1 gene led to the identification of five alleles (Albar et al., 2006). Several breeding programmes are currently developing or testing RYMV1-mediated resistant rice varieties (Seck et al., 2012). Marker-assisted selection (MAS) is being used as a more efficient breeding strategy. Recently, microsatellite markers were used to develop near-isogenic resistant lines (Kam, 2011; Jaw et al., 2012). PCR-based single nucleotide polymorphism markers have been also used to tag specific resistance alleles (Thiemele et al., 2010; Sow, 2012). The stability of RYMV resistance has been questioned since several resistance-breaking isolates of the virus were found in most rice growing areas (Traore et al., 2006a; Amoncho et al., 2009; Ochola and Tusiime, 2011; Issaka et al., 2012). Some authors suggest that genetic control should be included in a broader disease management strategy, taking into account prophylactic measures (Traore et al., 2009). In such a strategy, partial resistance may be used to efficiently control the disease. Moreover, as reported in other viral pathosystems, combining partial and high resistance to the virus may result in more resistance stability (Palloix et al., 2009). In this chapter, recombinant inbred line populations were developed using different hybridization schemes involving partial resistance and RYMV1-mediated high resistance donors and University of Ghana http://ugspace.ug.edu.gh 69 susceptible farmers' rice varieties. RYMV1-mediated resistance alleles were tagged using specific SNP markers and inbred lines were assessed for resistance to RYMV. 5.2. Materials and methods 5.2.1. Research time frame and study areas The development of recombinant inbred line populations (RIPs) was carried out from March 2011 to October 2012. Thereafter, genotyping and phenotyping of recombinant inbred lines (RILs) and backcrossed inbred lines (BILs) for resistance to RYMV were performed from October 2012 to December 2012. All experiments were carried out in greenhouse and laboratory facilities of INERA Kamboinse research station (12˚28'N latitude, 1˚32'W longitude). Local weather conditions were characterized by 600-900 mm annual rainfall, 75-90% relative humidity and temperature between 25-39°C. 5.2.2. Parental lines In total, 14 rice varieties were used as parental lines (Table 5.1). Half of them were farmers' varieties while the rest consisted of RYMV resistant genotypes possessing resistance alleles, rymv1-2 (Gigante and Bekarosaka) and rymv1-3 (Tog5681). Most farmers' varieties were among the top preferred ones (Chapter 3) and were also shown to be susceptible to RYMV (see Chapter 4). Kumazuce was included in the experiment because it was preferred by farmers in some areas of Ghana. Partial resistance donors included varieties CG14, GH1520, Nerica28, Digang and Azucena which showed partial resistance consistently with virus mixture 1 and mixture 2 (chapter 4). All parental lines were chosen based on a prior assessment of crossing compatibility. 5.2.3. Breeding nursery establishment Parental seeds were sown in a nursery three times at intervals of 14 days to ensure synchronization of flowering times. Over 100 seeds from each parental line were cleaned using University of Ghana http://ugspace.ug.edu.gh 70 0.08% sodium hypochlorite and pre-germinated into ‘’Petri dishes’’ using sterile water containing 0.01 % of fungicide (ThiramTM: dithiocarbamate). Table 5. 1. Rice genotypes used for the development of recombinant and backcross inbred lines Genotypes Source Speciesa Phenotypeb Farmers' rice varieties FKR16 INERA/BURKINA FASO Oryza sativa Susceptible FKR19 INERA/BURKINA FASO O. sativa Susceptible FKR56N INERA/BURKINA FASO Interspecific Susceptible FKR60N INERA/BURKINA FASO Interspecific Susceptible FKR62N INERA/BURKINA FASO Interspecific Susceptible Nerica28 INERA/BURKINA FASO O. sativa PR Kumazuce SRI-CRI/GHANA O. sativa PR Resistance donors CG14 SRI-CRI/GHANA O. glaberrima PR Gh1520 SRI-CRI/GHANA O. glaberrima PR Digang SRI-CRI/GHANA O. sativa PR Azucena INERA/BURKINA FASO O. sativa PR Gigante INERA/BURKINA FASO O. sativa HR (rymv1-2) Bekarosaka INERA/BURKINA FASO O. sativa HR(rymv1-2) Tog5681 INERA/BURKINA FASO O. glaberrima HR(rymv1-3 aInterspecific lines resulted for O. sativa x O. glaberrima crosses. bRice line phenotypes are related to their reactions to RYMV as determined in Chapter 4. PR and HR indicate partial and high resistance, respectively. Pre-germinated seeds were planted in nurseries (average density of 1000 seeds/m2) for 3 weeks. Subsequently, plantlets were transplanted singly into 20 litre buckets filled with clay soil. Fertilizer was applied at a rate of 200 kg of NPK (15:15:15) per hectare. Nitrogen fertilizer (urea: 46% N) was applied in two dressings, at maximum tillering and at panicle initiation, stages. University of Ghana http://ugspace.ug.edu.gh 71 5.2.4. Rice emasculation and cross-pollination for F1 seeds production An electric vacuum emasculator was adapted from that of Cornell University (Figure 5.1). This device was used to remove anthers from rice flowers. Selected partially emerged (50-60%) panicles on female plants were first disinfected using 0.5% chlorometric sodium hypochlorite prior to emasculation. Panicle leaf sheaths were folded down and upper and the lower florets were cut off with scissors. Tips of florets were clipped off and anthers were removed by suction using the vacuum emasculator. Emasculated panicles were covered with paper bags and tagged to prevent undesired pollination. Pollen was collected from male plants and poured into emasculated florets within 24 hours after emasculation. Pollinated panicles were immediately enveloped in paper bags to prevent out crosses and provide protection against bad weather, pests and contaminations by pathogens. Progeny seeds were harvested when they lost their green colour, usually about 25 to 30 days after pollination. All crosses were reciprocal, donor parent and recurrent parent representes male and female respectively. 5.2.5. Development of recombinant inbred populations Pre-germinated F1 seeds were planted in plastic buckets and fertilizers were applied as indicated above. RIPs were developed as indicated in Figure 5.2. At flowering stage, emerging panicles from F1 plants where bagged in order to produce F2 seeds by selfing. To develop BC1F1 seeds, F1 plants were crossed to recurrent parents. Backcrosses were performed in both directions whereby F1 plants were used alternatively as female or male parents (Figure 5.3). Harvested F2 and BC1F1seeds were planted and selfed to yield F3 and BC1F2 seeds respectively while BC1F1 plants were backcrossed to generate BC2F1 seeds. Finally, F3, BC1F2 and BC2F1 seeds were planted and selfed to generate targeted recombinant inbred line populations (RIPs) including F4, BC1F3 and BC2F2 seeds, respectively. University of Ghana http://ugspace.ug.edu.gh 72 Figure 5. 1. Device used for rice emasculation. A= Electric house cleaning vacuum with pressure selector; B= pipe; C: anther sucking tip; D: pollen collection tube. Figure 5. 2. Breeding scheme for the development of recombinant inbred line populations A B D C University of Ghana http://ugspace.ug.edu.gh 73 5.2.6. Marker assisted foreground selection for RYMV1 resistance gene 5.2.6.1. Extraction of total RNA from rice leaves Total RNA was extracted using Qiagen® Rneasy kit (Qiagen, France) as recommended by the manufacturer. Briefly, 100 mg of finely ground leaves were mixed with 450 µl of lysis buffer (RLT buffer) containing 2% (v/v) β-mercaptoethanol. After filtration, total RNA was precipitated by addition of 225 µl absolute ethanol. RNA extract was washed once with 700 µl of RW1 buffer and twice with 500 µl of RPE buffer. Clean total RNA was eluted from spin column by addition of 30 µl of nuclease free H2O and centrifugation at 10,000 rpm for 1 min. Eluted RNA was used immediately in RT-PCR reactions or stored at -70°C for further use 5.2.6.2. Reverse Transcription PCR Reverse transcription (RT) PCR were done in two steps using oligonucleotide primers P2 and R4 (Table 5.2) specific to rymv1-2 and rymv1-3 alleles respectively (Figure 5.3). RT reactions were done in total volumes of 25 µl containing 9 µl RNA, 1µl of 100 µM reverse primer, 2 µl of 5 mM dNTPs, 200 U of RNase inhibitor, 5 µl of (5x) RT buffer and 1 µl of MMLV-RT. cDNA synthesis was performed in a PTC100 thermocycler at 42°C for 60 min. PCR reactions were done in 20 µl reaction volumes using AccuPower PCR Premix kit from Bioneer®. A reaction mix containing 2.5 µl of cDNA template, 17.5 µl of nuclease-free water and 4 picomoles of each primer (forward and reverse) was added to the lyophilised PCR premix tube. Primer combinations for PCR reactions are indicated in figure 5.3 (Thiemele et al., 2010).The set of primers P1, P2, Pi and Pg (Table 5.2) was used to detect rymv1-2 allele in RIPs (Figure 5.3A). Combination of primers P2 and Pg specifically detects rymv1-2 resistance allele with an expected PCR product of 127 nucleotides (nt). P1-Pi combination yields an expected product of 187 nt specific to the susceptible allele. P1-P2 combination (269 nt) detects the entire central region of the resistance gene and was used as internal PCR control. The set of primers F1, F5, R1 University of Ghana http://ugspace.ug.edu.gh 74 and R4 (Table 5.2) was used to detect rymv1-3 allele (Figure 5.3B). Specifically, R4-F5 primer combination amplifies a fragment of 540 nt in rymv-3 mediated resistant lines. Primers F1-R1 amplifies a 725 nt fragment used as internal PCR control. Cycling conditions for primers set P1, P2, Pi and Pg were as follows: 94°C, 3 min; 30 cycles of 94°C, 30 sec; 61°C, 30 sec; 72°C, 1 min; and 72°C, 10 min. For the set of primers F1, F5, R1 and R4, cycling conditions were: 94°C, 3 min; 30 cycles of 94°C, 30 sec; 58°C, 45 sec; 72°C, 1 min; and 72°C, 10 min. PCR products were electrophoresed in 2% agarose gels containing 0.05% ethidium bromide and visualized under UV trans-illumination. Table 5. 2. Primers used for detecting alleles of RYMV1 gene within RIPs Primer Sequence (5' 3') P1 GAGCCCACCTTCTGTCCGATG P2 AGTAGCTCACCAATTAGACGGA Pi CAGGGCCAGTCAATTTTGCTATTTC Pg GTGCTGAGAGCCTAAGGGCTA F1 CACGTCGGCGGCGCATCCAAG R1 CGAACACGCTCGCGCACCTCA F5 CCCTGACCAAGAGATGGAGAAAG R4 CCTCGGTACAACCAAGAGAC University of Ghana http://ugspace.ug.edu.gh 75 Figure 5. 3. PCR-based RYMV1 allele specific amplification strategy using SNP markers. Primers, polymorphic sites and sizes of PCR products are indicated for rymv1-2 (A) and rymv1-3 (B) alleles (Albar et al., 2006; Thiemele et al., 2010). 5.2.7. Phenotyping RIPs for resistance to RYMV RIPs included progenies from F3, F4, BC1F2, BC1F3 and BC2F2 families. Parental varieties and different rice cultivars were used as checks. A total of 93 recombinant inbred populations were planted in buckets arranged in a complete randomized design (CRD). For each population, 20 pre-germinated seeds were directly sown into 20 litre plastic buckets in three replications. Plants were inoculated as indicated in chapter 4, using virus inoculums 1 and 2 composed of non-resistance-breaking (nRB) and resistance-breaking (RB) isolates, respectively (Table 5.3). University of Ghana http://ugspace.ug.edu.gh 76 5.2.8. Data analysis Data were analyzed using Statistica software ver.6 (StatSoft France, 2001). One-way analysis of variance was used to test differences in the mean number of days for symptom appearance between rice genotypes. Data from each genotype was compared to the control BG90-2 using Dunnett’s test (Sayes et al., 2006). Table 5. 3. Selected RYMV isolates used for screening rice accessions RYMV Origin Strainsa Pathogenicityb isolates BG90-2 Gigante Tog5681 Pathotype Virus inoculum 1 854-3 Burkina Faso S1 + - - nRB 466-4 Mali S2 + - - nRB 562-2 Niger S1 + - - nRB 288-1 Ghana S2 + - - nRB Virus inoculum 2 288-4 Ghana S2 + + - RB-rymv1-2 466-5 Mali Sa + + - RB-rymv1-2 854-5 Burkina Faso S2 + + + RB-rymv1-2/rymv1-3 562-1 Niger S1 + + + RB-rymv1-2/rymv1-3 aVirus strains were determined based on the variability of the coat protein gene (Traore et al., 2010); bVirus isolates were assigned to pathotypes depending on their ability to overcome (+) singly allele rymv1-2 or simultaneously both alleles (RB-rymv1-2/ rymv1-3). Isolates not able to overcome (-) any RYMV1 resistance allele as well as RYMV2 gene were included in pathotype nRB. University of Ghana http://ugspace.ug.edu.gh 77 5.3. Results 5.3.1. Recombinant inbred populations To develop recombinant inbred line populations, parental lines were used to make 16 crosses (Table 5.3). The number of pollinated florets for each cross ranged between 30 and 255. Intraspecific O. sativa x O. sativa crosses were most successful (23-56.6%). However, such intraspecific cross between Azucena and Bekarosaka gave a very low success rate (2%) in spite of the higher number of pollinated florets. Low rates of successful crosses were also found between O. sativa x NERICA crosses (4.45% in average) as well as all interspecific O. sativa x O. glaberrima crosses (1.72% in average). All crosses were advanced to form six breeding families composed of 79 recombinant inbred line populations labelled from KBR1 to KBR79. Table 5. 4. Development of recombinant inbred line populations for resistance to RYMV Crosses Cross typea Pollinated florets F1 seedsb RIPs composition Gigante x FKR16 indica x indica 30 17 (56.7) BC1F1, BC1F3 Gigante x FKR19 indica x indica 30 15 (50.0) BC1F1 Gigante x Digang indica x indica 30 16 (53.3) BC1F2, BC1F3 Azucena x Gigante japonica x indica 30 7 (23.3) F3 Azucena x Bekarosaka japonica x indica 150 3 (2.0) F3 FKR19 x Digang indica x indica 30 12 (40.0) F3 Kumazuce x Digang indica x indica 30 17 (56.7) F3 FKR56N x Gigante nerica x sativa 180 8 (4.4) F3 FKR60N x Gigante nerica x sativa 180 7 (3.9) F3 Gigante x FKR62N sativa x nerica 180 12 (6.7) BC1F3, BC2F1 Digang x Nerica28 sativa x nerica 180 5 (2.8) F3 University of Ghana http://ugspace.ug.edu.gh 78 FKR56N xTog5681 nerica x glaberrima 255 4 (1.6) BC1F3 Gigante x Tog5681 sativa x glaberrima 225 3 (1.3) F3 GH1520 x Gigante glaberrima x sativa 180 4 (2.2) BC2F1, BC2F2 CG14 x Digang glaberrima x sativa 150 3 (2.0) BC1F1, BC1F2 CG14 x Gigante glaberrima x sativa 135 2 (1.5) F1 aRice genotype belonged to Oryza glaberrima and O. sativa species, the latter being subdived into indica and japonica subspecies bNumber of F1 seeds indicating successful crosses which percentages are indicated in parentheses. 5.3.2. Molecular screening for RYMV1 gene identification Crosses involving rymv1-2 allele bearing genotypes (Gigante and Bekarosaka) were screened using primers P1, P2, P1 and Pg. Combinations of the three expected RT-PCR amplification fragments (127 bp, 187 bp and 269 bp) determined three allelic patterns (Figure 5.4A). Resistant genotypes Gigante and Bekarosaka showed an allelic pattern (rr) involving the presence of 127 bp and 269 bp fragments. Allelic pattern (RR) resulting from simultaneous amplifications of 187 bp and 269 bp fragments was found in the susceptible genotype FKR16. Recombinant lines from crosses between Gigante or Bekarosaka and other parental genotypes showed both allelic patterns rr and RR. A third allelic pattern (rR) determined by the presence of all three amplification fragments was also found in some recombinant lines. Primers R1, F1, R4, and F5 were used to screen recombinant populations resulting from crosses which involved Tog5681 as donor of rymv1-3 resistance allele. The expected amplification fragment of 725 bp was found in Tog5681 as well as FKR16, CG14 and all recombinant lines. In contrast, the second expected fragment (540 bp) was found only in Tog5681. This result indicated that allele rymv1-3 was detected only in resistance donor Tog5681. University of Ghana http://ugspace.ug.edu.gh 79 A 725bp 540bp 500bp 600bp 800bp 700bp B M Tog5681 FKR16 CG14 KBR27 KBR28 KBR59 KBR60 KBR61 KBR62 KBR63 KBR60 KBR61 KBR62 KBR63 300bp 100bp 269bp 127bp 200bp 500bp M Gigante Bekarosaka FKR16 KBR8 KBR9 KBR21 KBR47 KBR25 KBR18 KBR58 RR rR rrrrrrRRrRrrrr rr 187bp Figure 5. 4. Electrophoregrams showing RT-PCR amplification profiles using rymv1-2- and rymv1-3- allele specific primers. (A) Amplification profiles in Gigante, Bekarosaka, FKR16 and their progenies. Allelic patterns (rr, RR, rR) corresponding to amplification profiles are indicated. (B) Amplification profiles in Tog5681, susceptible genotypes FKR16 and CG14 and progenies from crosses involving Tog5681. Sizes of marker (M) fragments are indicated in base pairs (bp). Results of the molecular screening of all 79 Kbr recombinant subfamilies are summarized in Table 5.4. Only nine subfamilies were derived from crosses involving Tog5681. The absence of rymv1-3 allele in these lines indicated their genotype predicted susceptibility to RYMV. However, two of these subfamilies (Kbr21 and Kbr22) which were derived from a cross between Tog5681 and Gigante were homozygous for resistant allele rymv1-2. Consequently, these subfamilies were predicted as resistant to RYMV. In addition to Kbr21 and Kbr22, 72 subfamilies were derived from crosses involving rymv1-2 allele from Gigante or Bekarosaka. Rymv1-2 allelic pattern rr (homozygous genotype with predicted resistance to RYMV) was found in more than half (58.3%) of the subfamilies. Notably, rr allelic pattern was found in all University of Ghana http://ugspace.ug.edu.gh 80 subfamilies derived from the following crosses: Gigante x FKR16, Gigante x Digang, Gigante x Azucena and Bekarosaka x Azucena. Table 5. 5. Allelic pattern of recombinant subfamilies from crosses involving donors of rymv1-2 and rymv1-3 resistance alleles Genotypes Parents / Crosses Breeding Allelic patterna Predicted families rymv1-3 rymv1-2 phenotype FKR16 Susceptible control Line nt RR Susceptible Bekarosaka rymv1-2 donor Line nt rr Resistant Gigante rymv1-2 donor Line nt rr Resistant Tog5681 rymv1-3 donor Line + nt Resistant Kbr1 Gigante x FKR16 BC1F1 nt rr Resistant Kbr2 Gigante x FKR16 BC1F1 nt rr Resistant Kbr3 Gigante x FKR16 BC1F1 nt rr Resistant Kbr4 Gigante x FKR16 BC1F1 nt rr Resistant Kbr5 Gigante x FKR16 BC1F1 nt rr Resistant Kbr6 Gigante x FKR16 BC1F1 nt rr Resistant Kbr55 Gigante x FKR16 BC1F3 nt rr Resistant Kbr56 Gigante x FKR16 BC1F3 nt rr Resistant Kbr57 Gigante x FKR16 BC1F3 nt rr Resistant Kbr58 Gigante x FKR16 BC1F3 nt rr Resistant Kbr7 Gigante x FKR62N BC1S2 nt rr Resistant Kbr8 Gigante x FKR62N BC1S2 nt rR Susceptible Kbr9 Gigante x FKR62N BC2F1 nt RR Susceptible Kbr47 Gigante x FKR62N BC1F3 nt rr Resistant Kbr48 Gigante x FKR62N BC1F3 nt rr Resistant Kbr49 Gigante x FKR62N BC1F3 nt rr Resistant University of Ghana http://ugspace.ug.edu.gh 81 Kbr50 Gigante x FKR62N BC1F3 nt rr Resistant Kbr51 Gigante x FKR62N BC1F3 nt rr Resistant Kbr52 Gigante x FKR62N BC1F3 nt rr Resistant Kbr10 Gigante x FKR19 BC1F1 nt rR Susceptible Kbr11 Gigante x FKR19 BC1F1 nt rr Resistant Kbr12 Gigante x Digang BC1F3 nt rr Resistant Kbr13 Gigante x Digang BC1F3 nt rr Resistant Kbr14 Gigante x Digang BC1F2 nt rr Resistant Kbr40 Gigante x Digang BC1F3 nt rr Resistant Kbr41 Gigante x Digang BC1F3 nt rr Resistant Kbr42 Gigante x Digang BC1F3 nt rr Resistant Kbr43 Gigante x Digang BC1F3 nt rr Resistant Kbr44 Gigante x Digang BC1F3 nt rr Resistant Kbr45 Gigante x Digang BC1F3 nt rr Resistant Kbr46 Gigante x Digang BC1F3 nt rr Resistant Kbr25 FKR56N x Gigante F2:3 nt rR Susceptible Kbr26 FKR56N x Gigante F2:3 nt rR Susceptible Kbr66 FKR56N x Gigante F2:3 nt rR Susceptible Kbr67 FKR56N x Gigante F2:3 nt RR Susceptible Kbr68 FKR56N x Gigante F2:3 nt rR Susceptible Kbr69 FKR56N x Gigante F2:3 nt RR Susceptible Kbr70 FKR56N x Gigante F2:3 nt RR Susceptible Kbr71 FKR56N x Gigante F2:3 nt rR Susceptible Kbr72 FKR56N x Gigante F2:3 nt RR Susceptible Kbr73 FKR56N x Gigante F2:3 nt RR Susceptible Kbr15 GH1520 x Gigante BC2F1 nt rr Resistant Kbr16 GH1520 x Gigante BC2F1 nt rr Resistant University of Ghana http://ugspace.ug.edu.gh 82 Kbr17 GH1520 x Gigante BC2F1 nt rR Susceptible Kbr18 GH1520 x Gigante BC2F1 nt rr Resistant Kbr19 GH1520 x Gigante BC2F1 nt rr Resistant Kbr20 GH1520 x Gigante BC2F1 nt rr Resistant Kbr53 GH1520 x Gigante BC2F2 nt rr Resistant Kbr54 GH1520 x Gigante BC2F2 nt rr Resistant Kbr29 FKR60N x Gigante F2:3 nt rR Susceptible Kbr30 FKR60N x Gigante F2:3 nt rR Susceptible Kbr64 FKR60N x Gigante F2:3 nt RR Susceptible Kbr27 FKR56N x Tog5681 BC1F3 (-) nt Susceptible Kbr28 FKR56N x Tog5681 BC1F3 (-) nt Susceptible Kbr59 FKR56N x Tog5681 BC1F3 (-) nt Susceptible Kbr60 FKR56N x Tog5681 BC1F3 (-) nt Susceptible Kbr61 FKR56N x Tog5681 BC1F3 (-) nt Susceptible Kbr62 FKR56N x Tog5681 BC1F3 (-) nt Susceptible Kbr63 FKR56N x Tog5681 BC1F3 (-) nt Susceptible Kbr23 Azucena x Gigante F2:3 nt rr Resistant Kbr24 Azucena x Gigante F2:3 nt rr Resistant Kbr31 Azucena x Bekarosaka F2:3 nt rr Resistant Kbr32 Azucena x Bekarosaka F2:3 nt rr Resistant Kbr76 Azucena x Bekarosaka F2:4 nt rr Resistant Kbr21 Gigante x Tog5681 F2:3 (-) rr Resistant Kbr22 Gigante x Tog5681 F2:3 (-) rr Resistant a Rice genotypes were screened for the presence (+) or absence (-) of rymv1-3 resistance allele; nt= not tested; detection of rymv1-2 allele in rice genotypes determined allelic patterns RR (susceptible homozygote), rr (resistant homozygote) and rR (susceptible heterozygote). University of Ghana http://ugspace.ug.edu.gh 83 Heterozygous rR pattern was found in 13.9% of the recombinant subfamilies which were predicted as susceptible. Susceptibility phenotype was also expected from the remaining 27.8% of the recombinant subfamilies belonging to the RR allelic pattern. 5.3.3. Reactions of rice recombinant inbred populations (RIPs) to RYMV inoculation 5.3.3.1. Latency period From the Kbr recombinant subfamilies, 79 recombinant inbred line populations (RIPs) were generated and were exposed to both non-RB isolates in virus inoculum 1 and RB isolates in inoculum 2. A wide range of variation in the time required for disease symptom appearance were recorded (Table 5.5). The average time for symptom development in plants of the susceptible control BG90-2 was 11.7 days post-inoculation (dpi). First symptoms in RIPs were observed as early as 7 dpi, particularly in RIPs from cross between FKR56N and Tog5681. By contrast, several RIPs developed symptoms after 20 dpi. A highly significant genotype effect was found (F=390.2, df=50; P<0.001) in one-way ANOVA when inoculum 1 was used. Dunnett's test using BG90-2 as control group indicated that 21.52% (17/79) of RIPs reacted similarly to the susceptible control and were assigned the S-phenotype. More than half of the RIPs (45/79) did not develop any symptom up to 45 dpi when the experiments ended. Such RIPs were derived from crosses involving Gigante or Bekarosaka. They were classified as highly resistant (HR- phenotype) as their reactions were similar to those of the resistant progenitors. All other RIPs (17/79) which showed symptoms later than BG90-2 were referred to as partially resistant (PR- phenotype). When inoculum 2 was used, symptoms were observed in individual genotypes within all HR- phenotype RIPs previously identified with inoculum 1. However, in all of the RIPs, symptoms appeared 15 to 27 dpi, which was significantly longer than in the control group BG90-2 (F= University of Ghana http://ugspace.ug.edu.gh 84 421.5, df=98; P<0.001). Consequently, they were attributed to the PR-phenotype. Altogether, 79.7% of the RIPs were partially resistant and 20.3% were susceptible. RIPs were subdivided into two major groups according to their phenotypes in the first group composed of 53 (out of the 79 RIPs) all recombinant lines within the same population exhibited the same phenotype (either S or PR or HR). In this group, proportions of phenotypes S, PR and HR were 24.5%, 17% and 58.5%, respectively with inoculum1. Using inoculum 2, only PR (71.7%) and S (28.3%) phenotypes were found. The second group (26/79) consisted of populations in which recombinant lines belonged to different phenotypes (Table 5.5). Table 5. 6. Reactions of rice accessions to inoculation of two mixtures of RYMV isolates Rice accessions Parents/ Families Line/cross Duration for symptom appearance (days)a Virus inoculum 1 Virus inoculum 2 FKR16 Parent Line 10.65±0.67 (S) 9±0 (S) FKR19 Parent Line 7.89±0.32 (S) 7.74±0.45 (S) FKR56N Parent Line 9.5±0.51 (S) 9.75±0.44 (S) FKR60N Parent Line 9.65±0.61 (S) 8.71±0.46 (S) FKR62N Parent Line 8.5±0.76 (S) 7.74±0.45 (S) Kumazuce Parent Line 19±0 (PR) 17.6±0.51 (S) Digang Parent Line 20.3±2.03 (PR) 18.5±1.32 (PR) Nerica 28 Parent Line 17.92±2.75 (PR) 18.33±2.71 (PR) GH1520 Parent Line 17.3±1.66 (PR) 18.19±2.06 (PR) CG14 Parent Line 19.3±2.39 (PR) 13.9±0.31 (S) Azucena Parent Line 17.29±2.05 (PR) 16.95±2.03 (PR) University of Ghana http://ugspace.ug.edu.gh 85 Bekarosaka Parent Line NS (HR) 11.44±0.51 (S) Gigante Parent Line NS (HR) 13.77±0.43 (PR) Tog5681 Parent Line NS (HR) 0±0 (HR) BG90-2 Control Line 9.64±0.49 (S) 9.19±0.93 (S) Kbr1 BC1F2 Gigante x FKR16 NS (HR) 23.25±0.44 (PR) Kbr2 BC1F2 Gigante x FKR16 NS (HR) 21.7±0.47 (PR) Kbr3 BC1F2 Gigante x FKR16 NS (HR) 25±0 (PR)* Kbr4 BC1F2 Gigante x FKR16 NS (HR) 22.5±1 (PR)* Kbr5 BC1F2 Gigante x FKR16 NS (HR) 24.5±0.51 (PR) Kbr6 BC1F2 Gigante x FKR16 NS (HR) 23±0 (PR) Kbr55 BC1F4 Gigante x FKR16 NS (HR) 23.85±1.05 (PR) Kbr56 BC1F4 Gigante x FKR16 NS (HR) 23.54±0.51 (PR) Kbr57 BC1F4 Gigante x FKR16 NS (HR) 23.92±1.05 (PR) Kbr58 BC1F4 Gigante x FKR16 NS (HR) 22.54±0.51 (PR) Kbr7 BC1F4 Gigante x FKR62N NS (HR) 26.6±0.5 (PR) Kbr8 BC1F4 Gigante x FKR62N 21.08±1.97 (PR)* 29±0 (PR)* Kbr9 BC2F2 Gigante x FKR62N 8.27±0.7 (S) 9±0.94 (S) Kbr47 BC1F4 Gigante x FKR62N NS (HR) 23.77±0.86 (PR) Kbr48 BC1F4 Gigante x FKR62N NS (HR) 22.62±0.5 (PR) Kbr49 BC1F4 Gigante x FKR62N NS (HR) 22.65±0.49 (PR) Kbr50 BC1F4 Gigante x FKR62N NS (HR) 16.47±0.83 (PR) Kbr51 BC1F4 Gigante x FKR62N NS (HR) 22.3±1.43 (PR) Kbr52 BC1F4 Gigante x FKR62N NS (HR) 24.73±0.78 (PR) University of Ghana http://ugspace.ug.edu.gh 86 Kbr10 BC1F2 Gigante x FKR19 19.38±2.06 (PR)* 15.14±1.04 (PR) Kbr11 BC1F2 Gigante x FKR19 NS (HR) 22±0 (PR)* Kbr12 BC1F4 Gigante x Digang NS (HR) 23.41±0.5 (PR) Kbr13 BC1F4 Gigante x Digang NS (HR) 27.41±0.5 (PR) Kbr14 BC1F3 Gigante x Digang NS (HR) 23.4±1.47 (PR) Kbr40 BC1F4 Gigante x Digang NS (HR) 24.35±0.49 (PR) Kbr41 BC1F4 Gigante x Digang NS (HR) 25.69±0.47 (PR) Kbr42 BC1F4 Gigante x Digang NS (HR) 22.09±0.79 (PR) Kbr43 BC1F4 Gigante x Digang NS (HR) 23±0 (PR) Kbr44 BC1F4 Gigante x Digang NS (HR) 25.19±1.13 (PR) Kbr45 BC1F4 Gigante x Digang NS (HR) 27±0 (PR)* Kbr46 BC1F4 Gigante x Digang NS (HR) 22.42±0.5 (PR) Kbr25 F4 FKR56N x Gigante 10.64±0.76 (S)* 21.44±2.53 (PR)* Kbr26 F4 FKR56N x Gigante 9.3±0.66 (S)* 21.42±2.83 (PR)* Kbr66 F4 FKR56N x Gigante 21.77±0.99 (PR)* 22.35±0.49 (PR)* Kbr67 F4 FKR56N x Gigante 18±1.38 (PR)* 22.96±0.82 (PR)* Kbr68 F4 FKR56N x Gigante 19.56±1.47 (PR)* 22.85±0.73 (PR)* Kbr69 F4 FKR56N x Gigante 9.73±0.46 (S) 11±0 (S) Kbr70 F4 FKR56N x Gigante 11.33±0.97 (S) 9.67±0.48 (S) Kbr71 F4 FKR56N x Gigante 11±0.98 (S)* 11.25±0.85 (S)* Kbr72 F4 FKR56N x Gigante 11.43±0.51 (S) 10.43±0.9 (S) Kbr73 F4 FKR56N x Gigante 20.56±1.24 (PR) 16.06±0.93 (PR) Kbr15 BC2F2 GH1520 x Gigante NS (HR) 23.5±0.51 (PR) University of Ghana http://ugspace.ug.edu.gh 87 Kbr16 BC2F2 GH1520 x Gigante NS (HR) 24.19±1.36 (PR) Kbr17 BC2F2 GH1520 x Gigante 16.29±2.47 (PR)* 20.48±5.08 (PR) Kbr18 BC2F2 GH1520 x Gigante NS (HR) 26±0 (PR)* Kbr19 BC2F2 GH1520 x Gigante NS (HR) 27.58±0.5 (PR) Kbr20 BC2F2 GH1520 x Gigante NS (HR) 23±0 (PR)* Kbr53 BC2F3 GH1520 x Gigante NS (HR) 23.12±0.65 (PR) Kbr54 BC2F3 GH1520 x Gigante NS (HR) 23.96±1.22 (PR) Kbr29 F4 FKR60N x Gigante 20±0.73 (PR)* 24.23±1.37 (PR) Kbr30 F4 FKR60N x Gigante 12.5±0.98 (S)* 20.5±2.95 (PR) Kbr64 F4 FKR60N x Gigante 9±0 (S) 21.95±1.16 (PR) Kbr27 BC1F4 FKR56N x Tog5681 11.71±0.46 (S) 21.5±2.14 (PR) Kbr28 BC1F4 FKR56N x Tog5681 16.88±2.39 (PR) 22.85±0.83 (PR) Kbr59 BC1F4 FKR56N x Tog5681 10.77±0.43 (S) 10.6±0.5 (S) Kbr60 BC1F4 FKR56N x Tog5681 8.84±0.37 (S) 8.25±0.9 (S) Kbr61 BC1F4 FKR56N x Tog5681 8.7±0.63 (S) 8.57±0.51 (S) Kbr62 BC1F4 FKR56N x Tog5681 12.73±0.46 (S) 9.56±0.51 (S) Kbr63 BC1F4 FKR56N x Tog5681 9.88±0.33 (S) 13.6±0.5 (S) Kbr33 BC1F2 CG14 x Digang 20.96±1.15 (PR) 27±0 (PR)* Kbr34 BC1F2 CG14 x Digang 21.08±1.9 (PR) 24.69±0.74 (PR) Kbr35 BC1F2 CG14 x Digang 21.62±0.8 (PR) 22.54±0.51 (PR) Kbr36 BC1F2 CG14 x Digang 18.85±0.73 PR) 23±0 (PR) Kbr37 BC1F2 CG14 x Digang 20.08±0.84 (PR) 23.69±0.47 (PR) Kbr38 BC1F2 CG14 x Digang NS (HR) 23.67±0.49 (PR)* University of Ghana http://ugspace.ug.edu.gh 88 Kbr39 BC1F3 CG14 x Digang 9.6±0.5 (S) 23±0 (PR) Kbr80 F4 FKR19 x Digang 11.52±0.51 (S) 10.53±0.51 (S) Kbr81 F4 Kumazuce x Digang NS (HR) 9.47±0.51 (S) Kbr82 F4 Kumazuce x Digang NS (HR) 10.79±1.58 (S) Kbr83 F4 Kumazuce x Digang 21.42±0.5 (PR) 13±0.8 (S) Kbr84 F4 Digang x Nerica28 20.92±0.89 (PR) 13.3±1.69 (S) Kbr85 F4 Digang x Nerica28 17.96±0.8 (PR) 13.24±0.89 (S) Kbr23 F4 Azucena x Gigante NS (HR) 23.4±0.51 (PR)* Kbr24 F4 Azucena x Gigante NS (HR) 26±0 (PR)* Kbr31 F4 Azucena x Bekarosaka NS (HR) 23.43±0.53 (PR)* Kbr32 F4 Azucena x Bekarosaka NS (HR) 23±0 (PR)* Kbr76 F4 Azucena x Bekarosaka NS (HR) 23±0 (PR)* Kbr21 F4 Gigante x Tog5681 NS (HR) 27±0 (PR)* Kbr22 F4 Gigante x Tog5681 NS (HR) 27±0 (PR)* aMean number of days for symptom appearance after virus inoculation ± standard deviation (n=20) with virus inoculum 1 and inoculum 2 (see Material and methods); no symptom (NS) was observed in highly resistant (HR) genotypes; Reaction phenotypes (indicated in parentheses) were attributed to accessions after one-way ANOVA of the number of days for symptom appearance followed by Dunnett's test (P <0.05), taking BG90-2 as control group: S, susceptible; PR, partially resistant. Stars (*) indicate the presence of additional phenotypes. University of Ghana http://ugspace.ug.edu.gh 89 5.3.3.2. Disease incidence Kbr populations in which recombinant lines belonged to different phenotypes were studied in more detail. Proportions of recombinant lines (n=20) which showed disease symptoms within each of the 26 populations (disease incidence) were determined. Kbr populations derived from crosses between Gigante and susceptible recurrent parents FKR62N, FKR56N, FKR60N, FKR16 and FKR19 were more resistant to the virus (Figure 5.5A). Recombinant lines in eight populations (Kbr8, Kbr10, Kbr25, Kbr26, Kbr29, Kbr66, Kbr67 and Kbr68) showed only PR and HR phenotypes. Recombinant lines of the S phenotype were found in Kbr30 and Kbr71 populations derived from FKR60N x Gigante and FKR56N x Gigante crosses. Altogether, HR and PR phenotypes represented 94.1% and S-phenotype were only 5.8% of the recombinant lines when inoculum 1 was used as virus source. When virus inoculum 2 was used, the proportion of resistant recombinant lines dropped to 72.1% while that of S-phenotype lines increased to 27.9%. Interestingly, half of the resistant lines belonged to the HR phenotype despite the use of resistant breaking isolates in inoculum 2. Such lines were found in all crosses except FKR60N x Gigante. Crosses where HR phenotype lines were found at high rates (60-90%) were those involving FKR16, FKR19 and FKR62N. Crosses involving high resistance rymv1-2 donors (Gigante and Bekarosaka) and partially resistant genotypes yielded higher proportions of resistant progenies. Using inoculum 1, 100% of progenies in all populations except Kbr17 fell into the HR phenotype (Figure 5.6A). University of Ghana http://ugspace.ug.edu.gh 90 0 20 40 60 80 100 Kbr8 Kbr25 Kbr26 Kbr66 Kbr67 Kbr68 Kbr71 Kbr29 Kbr30 Kbr3 Kbr4 Kbr10 Kbr11 P h e n o t y p e p r o p o r t i o n ( % ) Rice genotypes 0 20 40 60 80 100 Kbr8 Kbr25 Kbr26 Kbr66 Kbr67 Kbr68 Kbr71 Kbr29 Kbr30 Kbr3 Kbr4 Kbr10 Kbr11 P h e n o t y p e p r o p o r t i o n ( % ) Rice genotypes A B S PR HR FKR56N x Gigante Gigante x FKR62N FKR60N x Gigante Gigante x FKR16 Gigante x FKR19 FKR56N x Gigante Gigante x FKR62N FKR60N x Gigante Gigante x FKR16 Gigante x FKR19 Figure 5. 5. Reaction of RIPs to non-resistance breaking (A) and resistance breaking (B) RYMV isolates. RIPs were developed from crosses between rymv1-2 resistance allele donor and five susceptible recurrent parents (FKR16, FKR19, FKR56N, FKR60N and FKR62N). RIPs were classified as susceptible (S), partially resistant (PR) and highly resistant (PR) according to their reaction to RYMV. University of Ghana http://ugspace.ug.edu.gh 91 Half of Kbr17 lines belonged to HR phenotype and the other half to PR phenotype. When progenies were screened with virus inoculum 2, all Kbr17 lines became partially resistant. In all other progenies, 15 to 58% of recombinant lines that were highly resistant to inoculum 1 were PR phenotype when exposed to inoculum 2 (Figure 5.6B). Crosses between partially resistant genotypes Digang and CG14 resulted in two populations (Kbr33 and Kbr38) in which two phenotypes were found. Surprisingly, HR phenotype was found in high proportions (over 70%) when recombinant lines were challenged with inoculum 1. HR phenotype was also found although to a lesser extent, when recombinant lines were screened with inoculum 2 (Figure 5.7A). Crosses involving both donors of high resistance alleles, rymv1-2 (Gigante) and rymv1-3 (Tog5681) resulted in progenies belonging to the HR phenotype when exposed to inoculum 1(Figure 5.7B). Only a small proportion (12-15%) of these progenies, were partially resistant when inoculum 2 was used. University of Ghana http://ugspace.ug.edu.gh 92 0 20 40 60 80 100 Kbr45 Kbr17 Kbr18 Kbr20 Kbr23 Kbr24 Kbr31 Kbr32 Kbr76 P h e n o t y p e p r o p o r t i o n ( % ) Rice genotypes 0 20 40 60 80 100 Kbr45 Kbr17 Kbr18 Kbr20 Kbr23 Kbr24 Kbr31 Kbr32 Kbr76 P h e n o t y p e p r o p o r t i o n ( % ) Rice genotypes GH1520 x Gigante Gigante x Digang Azucena x Gigante Azucena x Bekarosaka GH1520 x Gigante Gigante x Digang Azucena x Gigante Azucena x Bekarosaka A B PR HR Figure 5. 6. Reaction of RIPs to non-resistance breaking (A) and resistance breaking (B) RYMV isolates. RIPs were developed from crosses between rymv1-2 resistance allele donors (Gigante and Bekarosaka) and three partially resistant recurrent parents (Digang, GH1520, and Azucena). RIPs were classified as partially resistant (PR) and highly resistant (HR) according to their reaction to RYMV. University of Ghana http://ugspace.ug.edu.gh 93 0 20 40 60 80 100 Kbr33 Kbr38 Kbr33 Kbr38 P h e n o t y p e p r o p o r t i o n ( % ) Rice genotypes (CG14 x Digang) A BInoculum 2Inoculum 1 PR HR 0 20 40 60 80 100 Kbr21 Kbr22 Kbr21 Kbr22 P h e n o t y p e p r o p o r t i o n ( % ) Rice genotypes (Gigante x Tog5681) Inoculum 2Inoculum 1 Figure 5. 7. Reaction of RIPs to non-resistance breaking (Inoculum 1) and resistance breaking (Inoculum 2) RYMV isolates. RIPs were developed from crosses between partially resistant genotypes CG14 and Digang (A) and between highly resistant genotypes Gigante and Tog5681 (B). RIPs were classified as partially resistant (PR) and highly resistant (HR) according to their reaction to RYMV. 5.4. Discussion Recombinant inbred line populations were generated by crossing several farmers' rice varieties susceptible to RYMV with partial and high resistance donors. There were clear differences in the number of viable F1 seeds produced, which indicated that genotypes were not always fully cross compatible. Crosses were most successful (40-57%) when all parental genotypes belonged to O. sativa indica subspecies. Indica x japonica crosses were moderately successful in the Azucena x Gigante cross (23%) and worse in the Azucena x Bekarosaka cross (2%). Our results are consistent with previous studies on F1 hybrids sterility from both intrasubspecific indica x indica and intersubspecific indica x japonica crosses (Stebbins, 1958; Ikehashi, 1982; Oka, 1988; Harushima et al., 2003; Najeeb et al., 2013). Hybrid sterility in indica x japonica crosses has University of Ghana http://ugspace.ug.edu.gh 94 been attributed to the interaction of several genes which leads to varying degrees of fertility in F1 hybrids, from fully fertile to almost completely sterile (Liu et al., 1996; Zhang et al., 1997; Asante et al., 2006). Interspecific crosses O.sativa x O.glaberrima also yielded low proportions of F1 hybrid seeds. Most previous studies indicated that such crosses resulted in 100% spikelet sterility in F1 hybrids (Sano, 1990; Ghesquiere et al., 1997; Jones et al., 1997b; Huer and Miezan, 2003; Geravito et al., 2010). In this study, F1 hybrids were produced with four distinct, O.sativa x O.glaberrima crosses, indicating that they were not developed by chance. However, proportions of successful crosses were very low (1.3 to 2.2%). Possibly, interspecific crosses were successful because clipped florets were filled in with fresh pollen during the pollination procedure used in this study, or some selfing occurred although rare, O.sativa x O.glaberrima hybrids were found in the field (Barry et al., 2007). Semon et al. (2004) also indicated that many rice varieties grown in Africa were admixtures between O. sativa and O.glaberrima. Natural occurrence of O.sativa x O.glaberrima hybrids seemed to be favoured by the fact that farmers grew varieties of both rice species in neighbouring fields. Some farmers even intercropped the two rice species within the same field. Resistance alleles rymv1-2 and rymv1-3 were detected in recombinant inbred lines using PCR base SNP-markers. Allele identification was done unambiguously so that homozygous as well as heterozygous recombinant lines could be detected. SSR marker RM252 was most often used to tag RYMV1 resistance gene (Albar et al., 2003; Jaw et al., 2012; Sow, 2012). SNP markers used in this study are more than adequate for marker assisted selection (MAS) because they are located within the target gene and also allow the identification of specific alleles of the gene (Thiemele et al., 2010). Although recombinant lines were developed from interspecific O.sativa University of Ghana http://ugspace.ug.edu.gh 95 x O.glaberrima crosses, RYMV1 resistance from Tog5681 was not introgressed into sativa genetic background. This was determined only by using MAS. The purpose of using O. glaberrima in rice breeding is to transfer into O. sativa desirable traits such as resistance to pests and diseases and resilience to abiotic stresses (Jones et al., 1997a; Sarla and Mallikarjuna, 2005). Crosses aimed at introgressing rymv1-3 resistance allele into O. sativa background failed to do so (Ndjiondjop et al., 1999). The reasons for this failure remain unknown. Possibly, RYMV resistance gene may be tightly linked to sterility genes (Levings, 1990; Garavito et al., 2010; Ott et al., 2013). Latency period for disease symptom expression was used to determine RILs' phenotypes resulting from their reactions to RYMV inoculation (Albar et al. 1998; chapter 4). MAS- predicted phenotypes were confirmed by virus inoculation. All rr rice genotypes were found to be highly resistant when non- resistance breaking isolates were used. Although progenies from Gigante x Tog5681 crosses lacked the rymv1-3 allele, they were also found to be highly resistant because of the inheritance of rymv1-2 resistance allele from Gigante. They are likely to have inherited some partial resistance from their O.glaberrima (Tog5681) parent as well because resistance in most of them could not be broken even by RB isolates in inoculum 2 (Figure 5.7B). Molecular and biological screening of RILs confirmed successful introgression of resistance genes into farmers' preferred susceptible rice genotypes. Introgression of partial and high resistance was evidenced by the reaction of RILs in the screening tests. Although rymv1-3 resistance failed to be introgressed, resistant inbred lines were obtained by transferring rymv1-2 resistance allele from both Gigante and Bekarosaka. Interestingly, resistance that was not broken down by RB isolates in inoculum 2 was achieved in several RILs. In particular, the combination of high and partial resistance yielded several recombinant lines which can be used in short term University of Ghana http://ugspace.ug.edu.gh 96 breeding programmes for resistance to RYMV. Field testing of these recombinant lines for yield and stability of resistance is a step towards this goal. Progenies with superior resistance were even found in crosses involving only partial resistant parents, indicating additive effects of PR genes. These results fully agree with the view that pyramiding resistance genes to plant pathogens, especially viruses, is an effective way to ensure durable resistance (Parlevliet, 2002; Moullet et al., 2009; Shi et al., 2009). University of Ghana http://ugspace.ug.edu.gh 97 CHAPTER 6 6. EVALUATION OF RICE RECOMBINANT INBRED LINES FOR YIELD AND YIELD COMPONENTS IN THREE ENVIRONMENTS 6.1. Introduction Rice yellow mottle virus disease caused by Rice yellow mottle virus (RYMV) is considered as the most devastating rice disease in Sub-Saharan Africa (Kouassi et al., 2005). The disease occurs erratically and epidemics are not predictable even at field level. Therefore, plots with high disease incidence (sometimes referred to as 'disease hotspots') in one season may be free of disease during the next season and vice-versa. Typical of many plant viruses, breeding for resistance to RYMV has been considered by several authors as the most convenient means to control the disease (Mew, 1991; Leung et al., 2003). Rice recombinant inbred line populations (RIPs) were developed and screened for resistance (Chapter 5). These RIPs were evaluated in the field to determine their productivity. Agronomic value of a rice variety depends on many traits (Huang et al. 1991) and the most essential characteristics include high yielding ability, resistance to pests and diseases, tolerance to undesirable environmental factors and good grain quality. Increasing grain yield of rice, given the complexity of the environment, is one of the key objectives for breeding rice (Ashura, 1998; Swaminathan, 1999). The approaches for breeding high yielding rice varieties largely depend on the estimation of genetic variability, heritability, genetic advance and correlations between grain yield and yield components. Useful yield components to be used for yield improvements should be highly heritable traits. Heritability (h2) is one of the popular indexes, between the phenotypic and breeding value and direct effect on selection (Falconer, 1989). It indicates to what extent University of Ghana http://ugspace.ug.edu.gh 98 progenies resemble their parents. Broad sense heritability measures the fraction of total variation which is heritable (genotypic). Narrow sense heritability quantifies the portion of phenotypic variation that is additive by nature. Heritability of 45% and 31% was determined in rice for panicle number and for panicle weight, respectively (Gravois and McNew, 1993). Several studies reported high narrow-sense heritability for grain weight, moderate for per-panicle- spikelets number and low for per-plant-panicle number (Surek and Korkut, 1998; Surek and Beser, 2005). Highly realized heritability ranging from 63% to 90% was reported for grain weight in rice (Mustafa and Elsheikh, 2007). Kato (1997) estimated 16% of realized heritability for per-plant-panicle number in rice and 20 to 33% for per-panicle-spikelets number. Grain yield is a complex character which involves several components such as number of panicles per plant or unit area, plant height, number of fertile tillers, number of spikelets per panicle, panicle length, percentage of filled grains, grain filling period, weight of 1000 grains, and other factors (Halil and Necmi, 2005; Surek and Beser, 2005; Mustafa and Elsheikh, 2007; Ukaoma et al., 2013). Therefore, selecting directly for yield may be misleading (Mustafa and Elsheikh, 2007). Knowledge of inter-relationships of yield components among each other and their contribution to yield is useful in selecting high yielding varieties. Simple correlation analyses relating grain yield to each component may not provide complete understanding of the contribution of components to yield (Dewey and Lu, (1959). A statistical technique referred to as path coefficient analysis is more adequate for this purpose (Surek and Beser, 2003; Azarpour, 2013). It partitions the correlation coefficients into its direct and indirect effects, so that the contribution of each component to yield can be estimated. Many studies using path analysis have shown direct effects of various yield components including harvest index, biomass yield (Ibrahim et al., 1990; Kumar and Hunshal, 1998), and 1000 grain weight (Yagdi, 2009) on University of Ghana http://ugspace.ug.edu.gh 99 wheat grain yield. Recently, Sadeghi, (2011) reported high direct influence of productive tillers number on rice grain yield. Other yield components such as filled grains per panicle, panicles per plant, grains per panicle, plant height and days to flowering were also reported to have positive impact in rice grain yield (Mustafa and Elsheikh, 2007; Kole et al., 2008; Hairmansis et al., 2010; Akinwale et al., 2011). The present study was carried out to estimate heritability, genetic variation and direct and indirect contributions for grain yield of some yield components in RIPs evaluated for resistance to rice yellow mottle virus disease. 6.2. Materials and methods 6.2.1. Plant materials and field experiments Field experiments were carried out in three locations including Kamboinse (12˚28'N latitude, 1˚32'W longitude) and two different locations at Banzon (11°19'0.00"N; 4°47'60.00"W). The two locations in the Banzon irrigated rice scheme were 5 km apart from each other. Kamboinse is located in the dry savannah zone characterized by 600 to 900 mm annual rainfall. Banzon is located in the moist savannah zone characterized by annual rain falls ranging from 900 mm to 1100 mm. Experiments involved 100 rice genotypes comprising 13 parental lines and eight check varieties and 79 recombinant inbred line populations (RIPs). The 79 RIPs belonged to six advanced breeding families including F4 (26), BC1F2 (14), BC1F3 (2), BC1F4 (28), BC2F2 (7) and BC2F3 (2). The experimental design was an alpha lattice of 100 entries laidout in 10 x10 with 2 replications and in one location. Rice genotypes were first sown in nurseries and thereafter 21 days-old University of Ghana http://ugspace.ug.edu.gh 100 seedlings of each genotype were transplanted each 25 cm in rows separated by 30 cm. Fertilizer was applied at a rate of 200 kg of NPK (15:15:15) per hectare. Nitrogen fertilizer (urea: 46% N) was applied in two dressings, at maximum tillering and at panicle initiation stages. 6.2.2. Data collection Apart from data on days to first flowering (DFF), measurements were taken at rice physiological maturity stage. Measured parameters were number of days to first flowering, plant height (PH), per-plant-tiller number (PPTN), per-plant-panicle number (PPPN), panicle length (PL), flag leaf length (FLL), above ground total biomass (AGTB), single plant grain yield (SPY), and thousand grain weight (TGW). Measurements of parameters were done as follow (Sarker et al., 2013) : DFF: numbers of days required for the plant to show the first panicle emergence or blooming counted from the date of sowing. PH: measured (cm) from ground level to the tip of the tallest panicle. PPTN: total numbers of stalks of each single plant bearing panicle or not. PPPN: total numbers of productive panicles were counted from each single plant in each plot. PL: measured (cm) from the basal node to the tip of any single well developed panicle of each single plant in each plot. FLL: measured (cm) from the basal node to the tip of any single well developed flag leaf of each single plant in each plot. University of Ghana http://ugspace.ug.edu.gh 101 AGTB: each entire single plant including mature panicles in each plot was mown from the bottom, dried for 1 week and weighted (g). SPY: total grain weight (g) per plant was taken after cleaning. TGW: 100 garins were randomly counted out of the total seeds of each single plant and weighted (g); TGW was calculated from average weights of 100 seeds lots. 6.2.3 Data analysis Analysis of variance (ANOVA) was done following Singh and Chaudhary (1985) with the mean data of all the replications. To test the differences between genotypes, Duncan’s new Range Test (DMRT) was performed following the method of Steel and Torrie (1997). 6.2.3.1. Computation of variance components and estimation of genotypic and phenotypic variances Estimation of genotypic and phenotypic variances according to the formula given by Johnson et al., (1955): Genotypic variance (σ2g) = (GMS-EMS) / r Where: GMS = Genotypic mean square; EMS = Error mean square; and r = Number of replications. Phenotypic variance (σ2p) = σ 2 g + EMS Where: σ2g = Genotypic variance and EMS = Error mean square. Estimation of genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) (Burton, 1952; Singh and Chaudhary, 1985): University of Ghana http://ugspace.ug.edu.gh 102 Genotypic coefficients of variation (GCV) = Where: σ2g = Genotypic variance and x = Population mean. Phenotypic coefficients of variation (PCV) = Where: σ2p = Phenotypic variance and x = Population mean. Estimation of heritability in broad sense by the formula suggested by Johnson et al. (1955) and Hanson et al. (1960): Heritability (h2b) = (σ 2 g /σ 2 p) x 100 Where: σ2g = Genotypic variance and σ 2 p = Phenotypic variance. Estimation of genetic advance was done following formula given by Johnson et al. (1955) and Allard (1960). Genetic advance (GA) = h2b. K.σp Where k = 1.76 at 10% selection intensity. Genetic advance noted GA (%) was calculated by the formula of Comstock and Robinson (1952) as follows: Genetic advance in percentage of mean, GA (%) = Where GA= Genetic advance and x = Population mean. The genotypic and phenotypic correlation coefficients between yield and different yield contributing characters were estimated as: University of Ghana http://ugspace.ug.edu.gh 103 Genotypic correlation = rg(xy)= Where: Covg(xy) = Genotypic covariance between the variables X and Y; σ 2 (g)1 = Genotypic variance of the variable X1 and σ2 (g)2 = Genotypic variance of the variable X2. Similarly, phenotypic correlation rp(xy) = Where Cov ph(xy) = phenotypic covariance between the variables X and Y; σ 2 (ph)1 = phenotypic variance of the variable X1 and σ2 (ph)2 = phenotypic variance of the variable X2. 6.2.3.2. Estimation of Path coefficients Path coefficient analysis was done according to the procedure employed by Dewey and Lu (1959) also quoted in Singh and Chaudhary (1985), using phenotypic correlation coefficient values. In path analysis, correlation coefficients between yield and yield contributing characters were partitioned into direct and indirect effects of yield contributing characters on grain yield per hectare. In order to estimate direct and indirect effects of the correlated characters, i.e. 1, 2, 3…and 10 on yield y, a set of simultaneous equations is required to be formulated as shown below: r1.y = P1.y + r1.2 P2.y + r1.3 P3.y + r1.4 P4.y + r1.5 P5.y + r1.6 P6.y + r1.7 P7.y + r1.8 P8.y+ r1.9 P9.y + r1.10 P10.y r2.y = r1.2 P1.y + P2.y + r2.3 P3.y + r2.4 P4.y + r2.5 P5.y + r2.6 P6.y + r2.7 P7.y + r2.8 P8.y+ r2.9 P9.y + r2.10 P10.y r3.y = r1.3 P1.y + r2.3 P2.y + P3.y + r3.4 P4.y + r3.5 P5.y + r3.6 P6.y + r3.7 P7.y + r3.8 P8.y+ r3.9 P9.y + r3.10 P10.y r4.y = r1.4 P1.y + r2.4 P2.y + r3.4 P3.y + P4.y + r4.5 P5.y + r4.6 P6.y + r4.7 P7.y + r4.8 P8.y+ r4.9 P9.y + r4.10 P10.y r5.y = r1.5 P1.y + r2.5 P2.y + r3.5 P3.y + r4.5 P4.y + P5.y + r5.6 P6.y + r5.7 P7.y + r5.8 P8.y+ r5.9 P9.y + r5.10 P10.y r6.y = r1.6 P1.y + r2.6 P2.y + r3.6 P3.y + r4.6 P4.y + r5.6 P5.y + P6.y + r6.7 P7.y + r6.8 P8.y+ r6.9 P9.y + r6.10 P10.y r7.y = r1.7 P1.y+ r2.7 P2.y + r3.7 P3.y + r4.7 P4.y + r5.7 P5.y + r6.7 P6.y + P7.y + r7.8 P8.y+ r7.9 P9.y + r7.10 P10.y University of Ghana http://ugspace.ug.edu.gh 104 r8.y = r1.8 P1.y + r2.8 P2.y + r3.8 P3.y + r4.8 P4.y + r5.8 P5.y + r6.8 P6.y + r7.8 P7.y + P8.y+ r8.9 P9.y + r8.10 P10.y r9.y = r1.9P1.y + r2.9P2.y + r3.9P3.y + r4.9P4.y + r5.9P5.y + r6.9P6.y+ r7.9P7.y + r8.9P8.y + P9.y+ r9.10P10.y Where: r1y = Genotypic correlation coefficients between y and i h character (y = Grain yield = GY) Piy = Path coefficient due to i th character (i = 1, 2, 3… 10) 1 = Days to First Flowering (DFF) 6 = Flag Leaf Length (FLL) 2 = Plant height (PH) 7 = Upper Ground Total Biomass (AGTB) 3 = Per-Plant-Tillers-Number (PPTN) 8 = Single Plant Grain Yield (SPY) 4 = Per-Plant-Panicles-Number (PPPN) 9 = Thousand grains weight (TGW) 5 = Panicle Length (PL) Partitioning of total correlation is done as indicated below taking as example number days to first flowering (DFF) and grain yield (y = SPY) i.e., r1y: P1.y = Direct effect of DFF on SPY r1.2 P2.y = Indirect effect of DFF on SPY via PH r1.3 P3.y = Indirect effect of DFF on SPY via PPTN r1.4 P4.y = Indirect effect of DFF on SPY via PPPN r1.5 P5.y = Indirect effect of DFF on SPY via PL r1.6 P6.y = Indirect effect of DFF on SPY via FLL r1.7 P7.y = Indirect effect of DFF on SPY via AGTB r1.8 P8.y = Indirect effect of DFF on SPY via SPY r1.9 P9.y = Indirect effect of DFF on SPY via TGW Where: University of Ghana http://ugspace.ug.edu.gh 105 P1.y, P2.y, P3.y …P10.y = Path coefficient of the independent variables 1, 2, 3… 10 on the dependent variable y, respectively. r1.y, r2.y, r3.y… r10.y = Correlation coefficient of 1, 2, 3 …10 with y, respectively. After calculating the direct and indirect effect of the characters, residual effect (R) was calculated by using the formula given below (Singh and Chaudhary, 1985): P2RY = 1- (r1.yP1.y + r2.yP2.y +…. + r10.yP13.y) Where, P2RY = R 2 and hence residual effect, R = (P2RY) ½; P1.y = Direct effect of the i th character on yield y and r1.y = Correlation of the i th character with yield y. University of Ghana http://ugspace.ug.edu.gh 106 6.3. Results 6.3.1. Analysis of variance and heritability Significant differences among genotypes and locations (P=0.001) for all grain yield related characters (Table 6.1) were observed. On average, rice genotypes in RIPs showed first flowers at 93 days (DFF) after germination. In some families, DFF was as low as 60 days but reached 128 days in other families. Mean values for plant height, number of tillers per plants and total above ground biomass were 125 cm (90-180 cm), 17.5 (6-31 tillers) and 117.9 g (64.2-157.5), respectively. Per plant panicle number and single plant grain yield were 13.7 (5-27 panicles) and 29.4 g (14.5-48.5 g), respectively. Genotypic and phenotypic variances, coefficients of variation and broad sense heritability for characters, were calculated (Table 6.2). Genotypic coefficients of variation ranged from 13.50 to 85.95 and phenotypic coefficients of variation ranged from 18.1 to 90.95 among various parameters under consideration. Total number of tillers (PPTN) and number of fertile panicles (PPPN) showed the highest genotypic as well as phenotypic coefficients of variation. Both genotypic and phenotypic coefficients of variation were lowest for panicle length (PL) and 1000- grain weight (TGW). All characters showed high heritability estimates and ranged from 55.26 to 95.34%). Genetic advance in response to selection was highest for per plant panicle number and total tiller number. Most characters including DFF, PH, PL, FLL and AGTB showed low genetic advance estimates ranging from 0.36% to 0.76%. Genotype effect reflected the performance of recombinant lines for grain yield (Table 6.3). Grain yield was especially higher in four recombinant families compared to mid-parents. These families resulted from the following crosses: Gigante x FKR16 (27.5 % increase over mid- parents), Gigante x FKR62N (27.1% increase), Digang x Gigante (22.1%) and FKR19 x Digang University of Ghana http://ugspace.ug.edu.gh 107 (19.1%). Some crosses resulted in decrease in grain yield. The biggest decrease in yield was observed in Digang x CG14 cross (17% decrease over mid-parents) and in Gigante x Tog5681 cross (10.7% decrease). Most often, decrease in yield over mid-parents was due to the lower performance of recombinant lines over the male parents. University of Ghana http://ugspace.ug.edu.gh 108 Table 6. 1. Analysis of variance yield and its components of 79 RIPs and their parents evaluated in three locations and two replications in fixed genotypes, random environments and random blocks model Source Of Variation DF Mean Square a DFF PPPN PPTN PH PL FLL AGTB TGW SPY Means 93 13.65 17.53 125.57 25.91 33.94 117.98 26.34 29.4 Location 2 1548.71 1371.55*** 2636.77*** 103223.43*** 177.26*** 12256.28*** 177280.22*** 72.23*** 477.65 Replications (Locations) 3 3430.33*** 264.77*** 40.78 1475.18*** 39.63 1200.58*** 25764.53*** 35.1 1459.03*** Genotype 99 12918.06*** 629.13*** 1052.32*** 12873.43*** 58.14*** 424.22*** 15141.88*** 214.57*** 1872.91*** Locations*Genotypes 198 275.44 122.43*** 173.03*** 2291.78*** 40.84*** 303.66*** 10498.2*** 7.47 676.98*** Error 599 336.78 26.49 32.59 145.28 10.46 50.33 1625.01 7.27 190.75 R-Square 0.33 0.32 0.39 0.76 0.17 0.37 0.28 0.28 0.18 CV (%) 19.73 37.71 32.56 9.6 12.48 20.9 34.17 10.24 46.98 aDFF: days to first panicle flowering; PH: plant height; PPTN: number of tillers per plant; PPPN: number of panicles per plant; PL: panicle length; FLL: flag leaf length; AGTB: above ground total biomass; TGW: 1000 grain weight; SPY: single plant grain yield. ***: Significant effects at P=0.001. University of Ghana http://ugspace.ug.edu.gh 109 Table 6. 2. Mean squares, heritability (broad sense) and co-efficient of variability estimates for grain yield components in rice Characters MS CV% Mean σg 2 σp 2 σe 2 Coefficient of variation H2 (%) GA% Genotypic Phenotypic SPY 1172.82*** 43.12 29.4 506.07 666.74 160.67 76.52 87.83 77.29 2.67 PPPN 290.82*** 34.72 13.65 134.19 156.64 22.45 84.89 91.71 85.67 6.77 PPTN 481.34*** 29.74 17.53 227.07 254.26 27.19 85.95 90.95 89.3 5.45 DFF 4909.3*** 19.17 93 2295.8 2613.51 317.71 51.52 54.97 87.84 0.61 PH 4967.46*** 8.67 125.57 2424.46 2543 118.54 39.21 40.16 95.34 0.36 PL 34.02*** 12.08 25.91 12.11 21.91 9.8 13.43 18.07 55.26 0.45 FLL 213.81*** 19.85 33.94 84.22 129.6 45.38 27.04 33.54 64.98 0.76 AGTB 10530.73*** 30.65 117.98 4611.8 5918.92 1307.12 57.56 65.21 77.92 0.51 TGW 129.54*** 8.93 26.34 62 67.54 5.53 29.89 31.2 91.81 1.28 aDFF: days to first panicle flowering; PH: plant height; PPTN: number of tillers per plant; PPPN: number of panicles per plant; PL: panicle length; FLL: flag leaf length; AGTB: above ground total biomass; TGW: 1000 grain weight; SPY: single plant grain yield, GA: genetic advance; CV: coefficient of variation. ***: Significant effects at P=0.001. University of Ghana http://ugspace.ug.edu.gh 110 Table 6. 3. Parents and offspring mean performance for grain yield Families of RIPs Average yield per plant (g)a % increase or decrease over OF FP MP MiP FP MP MiP Gigante x FKR16 33.94±14.56 25.07±8.59 28.17±13.25 26.62±10.92 35.4 20.5 27.5 Gigante x FKR19 27.12±13.16 25.07±8.59 25.3±17.44 25.18±0.00 8.2 7.2 7.7 FKR56N x Gigante 29.04±12.88 29.97±10.83 25.07±8.59 27.52±9.71 -3.1 15.8 5.5 Gigante x FKR60N 24.23±10.18 25.07±8.59 24.9±9.09 24.98±0.00 -3.4 -2.7 -3 Gigante x FKR62N 30.42±16.11 25.07±8.59 22.8±11.11 23.93±9.85 21.3 33.4 27.1 Digang x Gigante 30.38±16.91 24.7±8.81 25.07±8.59 24.88±8.70 23.0 21.2 22.1 GH1520 x Gigante 32.76±12.96 38.97±15.44 25.07±8.59 32.02±12.02 -15.9 30.7 2.3 Azucena x Gigante 19.98±19.90 14.27±7.14 25.07±8.59 19.67±7.86 40.0 -20.3 1.6 Azucena x Bekarosaka 23.08±19.28 14.27±7.14 34.67±20.01 24.47±13.57 61.7 -33.4 -5.7 Gigante x Tog5681 29.28±14.34 25.07±8.59 40.53±16.76 32.8±12.67 16.8 -27.8 -10.7 FKR56N x Tog5681 31.8±15.75 29.97±10.83 40.53±16.76 32.8±12.67 6.1 -21.5 -3.0 Kumazuce x Digang 24.01±10.58 24.6±9.45 24.7±8.81 24.65±9.13 -2.4 -2.8 -2.6 FKR19 x Digang 29.77±14.39 25.3±17.44 24.7±8.81 25±13.13 17.7 20.5 19.1 Digang x CG14 30.4±12.53 24.7±8.81 48.53±21.1 36.62±14.95 23.1 -37.4 -17.0 aOF: offsprings; FP: female parent; MP: Male parent; MiP: Mid-parent University of Ghana http://ugspace.ug.edu.gh 111 6.3.2. Correlation among characters The genotypic and phenotypic coefficients of correlation among grain yield and its components are presented in Table 6.4. Four components (PPPN, PPTN, TGW, and AGTB) were highly correlated genotypically to grain yield (SPY). Although AGTB was highly correlated to SPY, the correlation coefficient was negative, indicating that the more biomass produced, the less grain yield is obtained. No significant correlation was found between SPY and other characters. PPPN was correlated to most characters, DFF and FLL being the only ones with which it was correlated. Few significant correlations were observed at the phenotypic level. Only PPPN showed significant correlation with grain yield. AGTB was highly correlated with three other components including PPPN, PPTN and DFF. No significant correlations were found between PH and any other character. At genotypic and phenotypic levels, only PPPN was correlated with grain yield. At both levels, PPTN was consistently correlated with PPPN and PL. In several cases, correlation coefficients were only significant either at genotypic or phenotypic levels. 6.3.3. Phenotypic and genotypic path coefficient analysis Path coefficients were computed for the estimation of the contribution of individual components (dependant variables) to grain yield (independent variable). Direct positive effects on grain yield were found with PPPN, DFF, PH, PL and TGW (Table 6.5). The highest direct effect resulted from the number of panicles per plant (+ 0.944), which alone exceeded the sum of all other direct effects. Negative direct effects resulted from per plant tiller number (-0.183), flag leaf length (-0.116) and above ground total biomass (-0.0007). Indirect genotypic effects on grain yield were low. The highest positive effect was due to 1000 grain weight and the number of fertile panicles (+0.137). University of Ghana http://ugspace.ug.edu.gh 112 Table 6. 4. Genotypic (lower diagonal) and phenotypic (upper diagonal) correlation of grain yield components Charactera SPY PPPN PPTN DFF PH PL FLL TGW AGTB SPY 0.2485** 0.18482 0.00304 -0.00306 -0.16262 -0.01737 0.28765 -0.01385 PPPN 0.8031*** 0.80308*** 0.76098*** 0.01677 -0.03978 -0.19655 -0.05107 0.61041*** PPTN 0.7610*** 0.9672*** 0.96719*** 0.02479 -0.3429*** -0.27409** -0.11212 0.56445*** DFF -0.0328 0.0286 0.0313 -0.00838 -0.34711*** -0.26487** -0.11034 0.54848*** PH -0.0398 -0.3429*** -0.3471*** -0.1304 0.01302 -0.12709 -0.0968 -0.11134 PL -0.1965 -0.2741** -0.2649** -0.1497 0.1855 0.18555 0.3539*** -0.143 FLL -0.0511 -0.1121 -0.1103 0.0443 0.3539*** 0.4449*** 0.44487*** -0.17779 TGW 0.6104*** 0.5645*** 0.5485*** 0.2096* -0.1430 -0.1778 0.1054 0.10543 AGTB -0.2751** -0.3793*** -0.4088*** -0.1123 0.2657** 0.2004* 0.0247 -0.3158*** aDFF: days to first panicle flowering; PH: plant height; PPTN: number of tillers per plant; PPPN: number of panicles per plant; PL: panicle length; FLL: flag leaf length; AGTB: above ground total biomass; TGW: 1000 grain weight; SPY: single plant grain yield. Significant effects at P=0.05 (*); P=0.01 (**) and P=0.001 (***) are indicated. University of Ghana http://ugspace.ug.edu.gh 113 Table 6. 5. Genotypic direct (bold face shaded and diagonal) and indirect effects of various components on rice grain yield Charactersa PPPN PPTN DFF PH PL FLL TGW AGTB PPPN 0.943572 0.757767 0.718042 0.015824 -0.037538 -0.185459 0.006962 0.575962 PPTN -0.177644 -0.183671 -0.177645 -0.004553 0.062981 0.050342 0.003171 -0.103674 DFF 0.000116 -0.000039 0.004677 -0.000039 -0.001623 -0.001239 0.000002 0.002565 PH -0.097861 -0.099064 0.003715 0.285393 0.003715 -0.036271 -0.000135 -0.031776 PL -0.015616 -0.01509 -0.007241 0.010571 0.056973 0.010571 0.000602 -0.008147 FLL 0.013049 0.012842 0.011266 -0.041188 -0.051776 -0.116385 0.006026 0.020692 TGW 0.137033 0.133154 -0.02703 -0.034716 -0.043161 0.025595 0.24277 0.025595 AGTB 0.000274 0.000295 -0.000048 -0.000192 -0.000145 -0.000018 0.000228 -0.000722 aDFF: days to first panicle flowering; PH: plant height; PPTN: number of tillers per plant; PPPN: number of panicles per plant; PL: panicle length; FLL: flag leaf length; AGTB: above ground total biomass; TGW: 1000 grain weight; SPY: single plant grain yield compared to genotypic ones. Such phenotypic effects were most evident in the number of fertile panicles per plant compared to three other components, number of tillers per plant (+0.758), the number of days for first flowering (+0.718) and the total biomass above ground (+0.576). University of Ghana http://ugspace.ug.edu.gh 114 The most important negative indirect effect on grain yield observed with the number of tillers per plant and the number of fertile panicles (-0.177). Phenotypic indirect effects were higher compared to genotypic ones. Such phenotypic effects were most evident in the number of fertile panicles per plant compared to three other components, number of tillers per plant (+0.758), the number of days for first flowering (+0.718) and the total biomass above ground (+0.576). 6.4. Discussion Recombinant inbred rice lines with resistance to rice yellow mottle virus disease were evaluated in the field for grain yield. The high level of differences observed in yield components considered in the study is consistent with the nature of rice genotypes evaluated. All genotypes belonged to segregating recombinant families. The extensive variability of rice genotypes for grain yield suggests that promising high yielding rice lines with resistance/tolerance to RYMV can be selected. The highest performances were recorded in progenies from crosses involving Gigante, which is a donor of high resistance gene to the disease. One parent of each set of progenies was farmers' preferred varieties. Therefore, future varieties developed from the progenies will likely be adopted by farmers. Estimates of broad sense heritability for grain yield (77.29%) were consistent with estimates from several previous studies. Khan et al. (2009) found an estimate of more than 50% heritability for yield in rice. Similarly, high heritability estimates of 76.18% and 99% for rice grain yield were also reported by Rahman et al. (2012) and Sathya and Jebara (2013), respectively. These heritability estimates are helpful in making selection for yield in rice on the basis of phenotypic performance. High genotypic correlations between grain yield and its components have been reported in rice (Rahman et al., 2012) and other cereal crops (Debebe et al., 2013). This was also confirmed in the present study. The high genotypic positive correlations between grain yield University of Ghana http://ugspace.ug.edu.gh 115 and three components (PPPN, PPTN and TGW) suggest that selection directed at any of these components may directly affect grain yield. Negative correlations between plant height and grain yield per plant at both genotypic and phenotypic levels are in agreement with the findings of Saif-ur-Rasheed et al. (2002). However, a positive correlation between the two factors was observed by Sharma and Reddy (1991). In this study, discrepancies between genotypic and phenotypic correlations were clearly found. Such discrepancies have been observed in other studies (Saif-ur-Rasheed et al., 2002; Debebe et al., 2013; Sarker et al., 2013). On the one hand, correlations found only at the genotypic level suggest possible environmental effects (Aktar et al., 2011) , however, correlations at the phenotypic level only may be misleading for breeders as selection based on such correlations could result in unstable performance. Direct and positive effect (0.943) of panicle number per plant appeared to be the most important component with the biggest influence on grain yield. This component was also reported elsewhere to have positive and direct effect on rice grain yield although at a lower magnitude (Karad et al., 2008; Mugemangango and Vinod, 2011; Haider et al., 2012). The positive effect of panicle number per plant and highly significant positive correlation at genotypic and phenotypic levels revealed by the present study indicates that PPPN is an important yield related trait that can be used for selection. Among other components that had positive and direct effects on grain yield, 1000- grain weight, per plant tiller number, plant height and panicle lenght were also reported by several authors (Khan et al., 2009; Aktar et al., 2011; Seyoum et al., 2012). The magnitude of the direct effects on grain yield found by these authors was quite low for all of the components under consideration, which is in agreement with the results obtained in the present study. Major indirect effects on grain yield were found in number of tillers, days to first flowering and the above ground biomass and most of these components had low positive or even negative direct effects. Therefore, such University of Ghana http://ugspace.ug.edu.gh 116 components should be used in combinations in order to achieved indirect selection for grain yield in rice. Path coefficient analysis provided an insight into the inter-relationship of various characters with grain yield. Considering grain yield as the artifact of all the causal characters PH, PPTN, PPPN, PL, FLL, TGW, DFF, AGTDM, the correlation coefficients of these causal factors with grain yield are partitioned into direct and indirect effects. As yield is influenced by many factors, selection based on correlation may be misleading because it measures only the mutual association between two variables, whereas path coefficient analysis specifically measures the relative importance of different yield components. To find out the direct and indirect effects and to measure the relative importance of causal factors, path coefficient analysis is useful, which permits critical examination of the specific forces acting to produce a given correlation plant for more reliable selection for high yielding genotypes. University of Ghana http://ugspace.ug.edu.gh 117 CHAPTER 7 7. GENERAL DISCUSSION, CONCLUSION AND RECOMMENDATIONS 7.1. General discussion 7.1.1. Farmers' preferences in the breeding strategy As a contribution to a better productivity of rice through the control of rice yellow virus disease (caused by Rice yellow mottle virus, RYMV), this thesis used an approach combining several aspects of field crop research. Attention was first focused on farmers as the main stakeholders in rice production. Most farmers in Burkina Faso were smallholder farmers and 98.5% of them held fields of less than 5 ha. This is consistent with reports from many other African countries (Nakano et al. 2011; GRiSP, 2013). Rice yellow mottle virus disease appears to be known by the majority of farmers but the success of disease management procedures is questionable. Replacement of varieties and insecticide applications used as the most common methods of control are likely to be ineffective in a sustainable production system. Farmers' varieties are susceptible or partially resistant to RYMV (Chapter 4). The indiscriminate use of insecticides is not desirable (Hashmi and Khan, 2011). Insecticides are hazardous and environmentally unfriendly. They may prevent disease spread to some extent but it is not known whether insects are the major factor for virus dissemination in the field (Calvert et al., 2003; Traore et al., 2009). Given that rice cultivation is dominated by smallholder farmers, rice yellow mottle disease management through genetic control is probably the best alternative for control (Bonman et al., 1992; Mew, 1991; Leung et al., 2003). The participatory rural appraisal approach used in this study identified farmers' indigenous knowledge and perceptions on RYMV and measures for control. This is important as a University of Ghana http://ugspace.ug.edu.gh 118 starting point for more effective farmers' capacity building from extensive farm-level awareness of pest and diseases and their management strategies. Farmers' involvement in the process of disease control through farmers' field schools and integrated pest management technologies has led to the adoption of successful management practices (Adesina et al. 1994; Roling et al. 1994). Moreover, farmers' preferences for rice varieties were also determined. If such varieties were to be improved for resistance to RYMV, it is expected that their wide adoption will not be a major problem (Debebe et al., 2005). 7.1.2. Screening of rice germplasm for resistance to rice yellow mottle virus disease Most screenings of rice germplasm for resistance to RYMV in the past did not consider the virus diversity as a critical factor. In this study, both non-resistance breaking (nRB) and resistance breaking (RB) isolates of the virus were used to screen rice varieties. The diversity in varietal reaction and inconsistency in results from nRB and RB isolates clearly demonstrated that screening experiments for resistance of rice to RYMV should be done with well characterized virus isolates. At least, the pathogenic properties (nRB or RB) of virus isolates should be well-known beforehand. Failure to use nRB isolates in the screening experiments could affect the identification of stable sources of resistance (at both partial and high level). Only two resistance genes (RYMV1 and RYMV2) have been reported for RYMV (Ndjiondjop et al., 1999; Thiemele et al., 2010). New resistance genes are likely to be found, especially in the African rice Oryza glaberrima (Paul et al., 2003). Concomitant use of nRB and RB isolates may help identify additional resistance genes that cannot be broken down by RB isolates. Screening rice germplasm for resistance in the greenhouse was more efficient than running the experiment in field conditions for two main reasons: University of Ghana http://ugspace.ug.edu.gh 119 (i) field virus isolates characteristics are unknown, which may lead to different conclusions if experiments are done in different environments (Awoderu, 1991; Thottappilly and Rossel, 1993; Coulibaly et al. (1999; Zouzou et al., 2008); (ii) due to the erratic nature of rice yellow mottle virus disease, inoculum pressure may be very low or greatly variable between locations. Locations sometimes referred to as 'disease hotpots' may not be equally affected by the disease from one season to another. Therefore, even if multi-location trials are conducted, this does not always guarantee adequate disease pressure necessary for the screening. Many breeders argue that greenhouse screening is inappropriate because of the higher virus contents in the inoculum compared to field transmission by vectors or other means. This should not be a major concern since resistant varieties found in the greenhouse will likely be resistant also in the field. What could be missed is field resistance in case of antibiosis to RYMV vectors. Antibiosis was reported in several rice varieties against the brown planthopper Nilaparvata lugens which vectors rice ragged stunt and rice grassy stunt viruses (Kenmore et al., 1984). Antibiosis against the green leafhopper (Nephotettix virescens), vector of rice tungro virus disease, was also reported (Park et al., 2013). Antibiosis against RYMV vectors has not been reported yet. 7.1.3. Development of high yielding quality rice with resistance to RYMV High resistance conditioned by RYMV1 in rice cultivars Gigante and Bekarosaka was transferred into farmers' preferred varieties. Both cultivars are homozygous for the rymv1-2 allele of the resistance gene (Albar et al., 2006; Rakotomalala et al., 2008). Of the 79 recombinant inbred populations developed from crosses of these varieties and farmer preferred varieties, 57% showed high resistance to RYMV. Most populations resulted from crosses between Gigante or Bekarosaka and partially resistant rice varieties. The high resistance was broken down by RB isolates but most inbred lines exhibited partial resistance University of Ghana http://ugspace.ug.edu.gh 120 characterized by a significant delay in symptom expression compared to the susceptible cultivar BG90-2. Therefore, combining both high and partial resistance resulted in a more stable disease resistance in the progenies even when they were challenged with RB virus isolates. Gene pyramiding for resistance to plant pathogens, especially viruses, has been reported to be an effective way to ensure durable resistance (Parlevliet, 2002; Moullet et al., 2009; Shi et al., 2007). Therefore, both high and partial resistance could be introgressed into susceptible farmers' preferred rice varieties. Partial resistance is controlled by several genes (polygenic) (Albar et al., 1998) therefore; resistance genes may not be completely the same in all partially resistant rice varieties. This was apparent in differential virus-host interactions in partially resistant cultivars Azucena (Ioannidou et al., 2000) and Digang (Chapter 4). Thus, bringing resistance from several partially resistant rice donors may be more beneficial in breeding for resistance to RYMV. Although crosses involving resistance donor Tog5681 bearing rymv1-3 allele were successful, no resistance was transferred to susceptible recurrent parents (Chapter 5). Progenies did show heterosis but only marker-assisted selection (MAS) was able to track the resistance gene. This exemplified the power of MAS as a key tool for modern plant breeding (Thiemele et al., 2010; Kam, 2011; Jaw et al., 2012). Efforts need to be made to identify suitable molecular markers for partial resistance in order to efficiently combine both high and partial resistance in rice. Field evaluation of recombinant inbred populations indicated tremendous variability for grain yield, suggesting the possibility for selecting high yielding rice varieties with resistance/tolerance to RYMV. Estimates of broad sense heritability for grain yield were high (77.29%) and consistent with estimates from several previous studies (Khan et al., 2009; Rahman et al., 2012; Sathya and Jebara, 2013). High genotypic correlations were found University of Ghana http://ugspace.ug.edu.gh 121 between yield and three of its components: number of panicles or tillers per plant and 1000- grain weight. These highly correlated yield related components will be useful for the next selection steps within recombinant inbred populations developed during this study. 7.2. General Conclusion Five farmers’ most preferred rice varieties were identified in both Banzon and Mogtedo. Results revealed that farmers grow rice varieties according to their preferences. Breeding efforts for rice improvement should therefore take into consideration farmers preferred attributes. Rice yellow mottle disease (RYMD) appeared to be reconized as a major constraint by most rice farmers but the success of disease management procedures remain uncertain. Inconsistency in rice genotype reactions to RYMV isolates suggested that well characterized virus isolates is crutial in screening for resistance to RYMV. At least, the pathogenic properties regarding the ability of virus isolates to overcome existing resistance genes should be defined. The genetic basis of resistance of newly identified sources of partial resistance seemed to be different from the control cv Azucena. High resistance conditioned by RYMV1 in rice cultivars Gigante and Bekarosaka was succssessfully transferred into some farmers' preferred rice varieties. This high resistance was lower and not active against resistant breaking (RB) isolates but most inbred lines exhibited partial resistance reaction characterized by a significant delay in symptom expression compared to the Partial Resistance control Azucena. Combining both high and partial resistance resulted in a more stable disease resistance in the progenies when they were challenged with RB virus isolates (Moullet et al., 2009; Shi et al., 2007). Progenies from crosses between PR genotypes were found to express high resistance University of Ghana http://ugspace.ug.edu.gh 122 phenotype. Ioannidou et al. (2000) indicated that combining resistance from several partial resistant rice donors may be more beneficial in breeding for durable resistance to RYMV. Field evaluation of recombinant inbred populations indicated high significant variability for grain yield, suggesting the possibility for selecting high yielding rice varieties with resistance/tolerance to RYMV. At least 600 randomly selected F2 seeds from all crosses were advanced by single seed decent (SSD) method. F5 seeds were generated from SSD to be used in future rice selection programmes for grain yield and resistance to RYMV. 7.3. Recommendations 1. Further characterization of viral populations’ structure in each rice cultivation area should be undertaken for an effective breeding strategy for resistance to RYMV. 2. 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