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A Genome-Wide Association Study Identifies SNP Markers for Virulence in Magnaporthe oryzae Isolates from Sub-Saharan Africa
A Genome-Wide Association Study Identifies SNP Markers for Virulence in Magnaporthe oryzae Isolates from Sub-Saharan Africa
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A Genome-Wide Association Study Identifies SNP Markers for Virulence in Magnaporthe oryzae Isolates from Sub-Saharan Africa
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A Genome-Wide Association Study Identifies SNP Markers for Virulence in Magnaporthe oryzae Isolates from Sub-Saharan Africa
A Genome-Wide Association Study Identifies SNP Markers for Virulence in Magnaporthe oryzae Isolates from Sub-Saharan Africa

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A Genome-Wide Association Study Identifies SNP Markers for Virulence in Magnaporthe oryzae Isolates from Sub-Saharan Africa
A Genome-Wide Association Study Identifies SNP Markers for Virulence in Magnaporthe oryzae Isolates from Sub-Saharan Africa
Paper

A Genome-Wide Association Study Identifies SNP Markers for Virulence in Magnaporthe oryzae Isolates from Sub-Saharan Africa

2018
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Overview
ABSTRACT The fungal phytopathogen Magnaporthe oryzae causes blast disease in cereals such as rice and finger millet worldwide. In this study, we assessed genetic diversity of 160 isolates from nine sub-Saharan Africa (SSA) and other principal rice producing countries and conducted a genome-wide association study (GWAS) to identify the genomic regions associated with virulence of M. oryzae. GBS of isolates provided a large and high-quality 617K single nucleotide polymorphism (SNP) dataset. Disease ratings for each isolate was obtained by inoculating them onto differential lines and locally-adapted rice cultivars. Genome-wide association studies were conducted using the GBS dataset and sixteen disease rating datasets. Principal Component Analysis (PCA) was used an alternative to population structure analysis for studying population stratification from genotypic data. A significant association between disease phenotype and 528 SNPs was observed in six GWA analyses. Homology of sequences encompassing the significant SNPs was determined to predict gene identities and functions. Seventeen genes recurred in six GWA analyses, suggesting a strong association with virulence. Here, the putative genes/genomic regions associated with the significant SNPs are presented.