Association analysis for resistance to Striga hermonthica in diverse tropical maize inbred lines
Striga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe Striga infestation, yield losses can range from 60 to 100% resulting in abandonment of farmers’ lands. Diverse methods have been proposed for S...
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Published in | Scientific reports Vol. 11; no. 1; p. 24193 |
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Main Authors | , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
17.12.2021
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
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Summary: | Striga hermonthica
is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe
Striga
infestation, yield losses can range from 60 to 100% resulting in abandonment of farmers’ lands. Diverse methods have been proposed for
Striga
management; however, host plant resistance is considered the most effective and affordable to small-scale famers. Thus, conducting a genome-wide association study to identify quantitative trait nucleotides controlling
S. hermonthica
resistance and mining of relevant candidate genes will expedite the improvement of
Striga
resistance breeding through marker-assisted breeding. For this study, 150 diverse maize inbred lines were evaluated under
Striga
infested and non-infested conditions for two years and genotyped using the genotyping-by-sequencing platform. Heritability estimates of
Striga
damage ratings, emerged
Striga
plants and grain yield, hereafter referred to as
Striga
resistance-related traits, were high under
Striga
infested condition. The mixed linear model (MLM) identified thirty SNPs associated with the three
Striga
resistance-related traits based on the multi-locus approaches (mrMLM, FASTmrMLM, FASTmrEMMA and pLARmEB). These SNPs explained up to 14% of the total phenotypic variation. Under non-infested condition, four SNPs were associated with grain yield, and these SNPs explained up to 17% of the total phenotypic variation. Gene annotation of significant SNPs identified candidate genes (Leucine-rich repeats, putative disease resistance protein and VQ proteins) with functions related to plant growth, development, and defense mechanisms. The marker-effect prediction was able to identify alleles responsible for predicting high yield and low
Striga
damage rating in the breeding panel. This study provides valuable insight for marker validation and deployment for
Striga
resistance breeding in maize. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-021-03566-4 |