Stay-green(SG)in wheat is a beneficial trait that increases yield and stress tolerance.However,conventional phenotyping techniques limited the understanding of its genetic basis.Spectral indices(SIs)as non-destructive...Stay-green(SG)in wheat is a beneficial trait that increases yield and stress tolerance.However,conventional phenotyping techniques limited the understanding of its genetic basis.Spectral indices(SIs)as non-destructive tools to evaluate crop temporal senescence provide an alternative strategy.Here,we applied Sls to monitor the senescence dynamics of 565 diverse wheat accessions from anthesis to maturation stages over 2 field seasons.Four Sis(normalized difference vegetation index,green normalized difference vegetation index,normalized difference red edge index,and optimized soil-adjusted vegetation index)were normalized to develop relative stay-green scores(RSGS)as the SG indicators.An RSGS-based genome-wide association study identified 47 high-confidence quantitative trait loci(QTL)harboring 3,079 single-nucleotide polymorphisms associated with SG and 1,085 corresponding candidate genes.Among them,15 QTL overlapped or were adjacent to known SG-related QTL/genes,while the remaining QTL were novel.Notably,a set of favorable haplotypes of SG-related candidate genes such as TraesCS2A03G1081100,TracesCS6B03G0356400,and TracesCS2B03G1299500 are increasing following the Green Revolution,further validating the feasibility of the pipeline.This study provided a valuable reference for further quantitative SG and genetic research in diverse wheat panels.展开更多
基金supported by the National Key R&D Program of China(no.2022YFE0116200)the Key R&D Program of Qinghai Province(2022-NK-125)the Key R&D Program of Yangling Seed Industry Innovation Center(grant no.Ylzy-xm-01).
文摘Stay-green(SG)in wheat is a beneficial trait that increases yield and stress tolerance.However,conventional phenotyping techniques limited the understanding of its genetic basis.Spectral indices(SIs)as non-destructive tools to evaluate crop temporal senescence provide an alternative strategy.Here,we applied Sls to monitor the senescence dynamics of 565 diverse wheat accessions from anthesis to maturation stages over 2 field seasons.Four Sis(normalized difference vegetation index,green normalized difference vegetation index,normalized difference red edge index,and optimized soil-adjusted vegetation index)were normalized to develop relative stay-green scores(RSGS)as the SG indicators.An RSGS-based genome-wide association study identified 47 high-confidence quantitative trait loci(QTL)harboring 3,079 single-nucleotide polymorphisms associated with SG and 1,085 corresponding candidate genes.Among them,15 QTL overlapped or were adjacent to known SG-related QTL/genes,while the remaining QTL were novel.Notably,a set of favorable haplotypes of SG-related candidate genes such as TraesCS2A03G1081100,TracesCS6B03G0356400,and TracesCS2B03G1299500 are increasing following the Green Revolution,further validating the feasibility of the pipeline.This study provided a valuable reference for further quantitative SG and genetic research in diverse wheat panels.
