Identification of Genomic Regions Associated with Agronomic and Disease Resistance Traits in a Large Set of Multiple DH Populations
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Abstract
Breeding maize lines with the improved level of desired agronomic traits under optimum
and drought conditions as well as increased levels of resistance to several diseases such as maize
lethal necrosis (MLN) is one of the most sustainable approaches for the sub-Saharan African region.
In this study, 879 doubled haploid (DH) lines derived from 26 biparental populations were evaluated
under artificial inoculation of MLN, as well as under well-watered (WW) and water-stressed (WS)
conditions for grain yield and other agronomic traits. All DH lines were used for analyses of genotypic
variability, association studies, and genomic predictions for the grain yield and other yield-related
traits. Genome-wide association study (GWAS) using a mixed linear FarmCPU model identified
SNPs associated with the studied traits i.e., about seven and eight SNPs for the grain yield; 16 and
12 for anthesis date; seven and eight for anthesis silking interval; 14 and 5 for both ear and plant
height; and 15 and 5 for moisture under both WW and WS environments, respectively. Similarly,
about 13 and 11 SNPs associated with gray leaf spot and turcicum leaf blight were identified. Eleven
SNPs associated with senescence under WS management that had depicted drought-stress-tolerant
QTLs were identified. Under MLN artificial inoculation, a total of 12 and 10 SNPs associated with
MLN disease severity and AUDPC traits, respectively, were identified. Genomic prediction under
WW, WS, and MLN disease artificial inoculation revealed moderate-to-high prediction accuracy. The
findings of this study provide useful information on understanding the genetic basis for the MLN
resistance, grain yield, and other agronomic traits under MLN artificial inoculation, WW, and WS
conditions. Therefore, the obtained information can be used for further validation and developing
functional molecular markers for marker-assisted selection and for implementing genomic prediction
to develop superior elite lines.
Description
Research Article
Keywords
genome-wide association study, genomic prediction, water stress, well-watered, maize lethal necrosis, genotyping by sequencing, well-watered, water stress