Frontiers in plant science · 2026
Genomic insights into sheath blight resistance: leveraging natural variation in the Bengal-Assam-Aus rice panel for multi-season association mapping.
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Naveenkumar R, Panda Siddharth, Reddy Challa Vijay Kumar, Prabhukarthikeyan S R, Sangeetha G, Anandan Annamalai, Kumar Acharya Licon, Ali Jauhar
Аннотация
INTRODUCTION: Sheath blight ranks among rice's most damaging diseases, cutting yield by up to half in severe outbreaks. No source of complete, durable resistance exists, so identifying the genetic basis of partial or quantitative resistance is a priority for breeding.
METHODS: We performed GWAS on 130 genotypes from the Bengal-Assam-Aus Panel (BAAP), phenotyped over three seasons viz., Wet 2018, Wet 2019, and Dry 2018-19, scoring disease severity by per cent disease index (PDI) and area under the disease progress curve (AUDPC).
RESULTS: Trait distributions were near-normal with substantial variation across genotypes, pointing to polygenic control of resistance. A strong genotype-by-environment interaction meant combined analysis wasn't appropriate, so we ran GWAS separately per season. This turned up 27 associated loci, three of which on chromosomes 1, 9, and 10 were consistent and high-confidence. The candidate genes underlying these peaks were LOC_Os01g03360 (BBTI4, a Bowman-Birk protease inhibitor), LOC_Os09g11790 (DEFL14, a defensin-like peptide), and LOC_Os10g04860 (AO2, an aldehyde oxidase).
DISCUSSION: The predicted functions include protease inhibition, antifungal activity, and hormone regulation. Instead of relying on a single-gene mechanism, it's advisable to suggest a layered defense response. Collectively, these findings enhance our understanding of the genetic and biochemical aspects of sheath blight tolerance, providing breeders with specific targets to focus on in their efforts.
METHODS: We performed GWAS on 130 genotypes from the Bengal-Assam-Aus Panel (BAAP), phenotyped over three seasons viz., Wet 2018, Wet 2019, and Dry 2018-19, scoring disease severity by per cent disease index (PDI) and area under the disease progress curve (AUDPC).
RESULTS: Trait distributions were near-normal with substantial variation across genotypes, pointing to polygenic control of resistance. A strong genotype-by-environment interaction meant combined analysis wasn't appropriate, so we ran GWAS separately per season. This turned up 27 associated loci, three of which on chromosomes 1, 9, and 10 were consistent and high-confidence. The candidate genes underlying these peaks were LOC_Os01g03360 (BBTI4, a Bowman-Birk protease inhibitor), LOC_Os09g11790 (DEFL14, a defensin-like peptide), and LOC_Os10g04860 (AO2, an aldehyde oxidase).
DISCUSSION: The predicted functions include protease inhibition, antifungal activity, and hormone regulation. Instead of relying on a single-gene mechanism, it's advisable to suggest a layered defense response. Collectively, these findings enhance our understanding of the genetic and biochemical aspects of sheath blight tolerance, providing breeders with specific targets to focus on in their efforts.