Table_1_Genome-Wide Association Studies Detect Multiple QTLs for Productivity in Mesoamerican Diversity Panel of Common Bean Under Drought Stress.xlsx

Drought stress is an important abiotic factor limiting common bean yield, with great impact on the production worldwide. Understanding the genetic basis regulating beans’ yield and seed weight (SW) is a fundamental prerequisite for the development of superior cultivars. The main objectives of this work were to conduct genome-wide marker discovery by genotyping a Mesoamerican panel of common bean germplasm, containing cultivated and landrace accessions of broad origin, followed by the identification of genomic regions associated with productivity under two water regimes using different genome-wide association study (GWAS) approaches. A total of 11,870 markers were genotyped for the 339 genotypes, of which 3,213 were SilicoDArT and 8,657 SNPs derived from DArT and CaptureSeq. The estimated linkage disequilibrium extension, corrected for structure and relatedness (r2sv), was 98.63 and 124.18 kb for landraces and breeding lines, respectively. Germplasm was structured into landraces and lines/cultivars. We carried out GWASs for 100-SW and yield in field environments with and without water stress for 3 consecutive years, using single-, segment-, and gene-based models. Higher number of associations at high stringency was identified for the SW trait under irrigation, totaling ∼185 QTLs for both single- and segment-based, whereas gene-based GWASs showed ∼220 genomic regions containing ∼650 genes. For SW under drought, 18 QTLs were identified for single- and segment-based and 35 genes by gene-based GWASs. For yield, under irrigation, 25 associations were identified, whereas under drought the total was 10 using both approaches. In addition to the consistent associations detected across experiments, these GWAS approaches provided important complementary QTL information (∼221 QTLs; 650 genes; r2 from 0.01% to 32%). Several QTLs were mined within or near candidate genes playing significant role in productivity, providing better understanding of the genetic mechanisms underlying these traits and making available molecular tools to be used in marker-assisted breeding. The findings also allowed the identification of genetic material (germplasm) with better yield performance under drought, promising to a common bean breeding program. Finally, the availability of this highly diverse Mesoamerican panel is of great scientific value for the analysis of any relevant traits in common bean.

干旱胁迫是限制普通菜豆产量的重要非生物胁迫因子，对全球菜豆生产均具有显著影响。解析调控菜豆产量与种子重量（Seed Weight, SW）的遗传基础，是培育优良菜豆品种的核心前提。本研究的核心目标为：对涵盖广泛遗传背景的栽培与地方品种种质的中美洲普通菜豆种质群体开展基因分型以进行全基因组标记开发；随后采用多种全基因组关联分析（Genome-Wide Association Study, GWAS）方法，鉴定两种水分环境下与产量相关的基因组区域。本研究共对339份基因型材料完成基因分型，共获得11870个标记，其中3213个为SilicoDArT标记，8657个为源自DArT与捕获测序（CaptureSeq）的单核苷酸多态性（Single Nucleotide Polymorphism, SNPs）标记。经群体结构与亲缘关系校正后的连锁不平衡扩展长度（r2sv），在地方品种与育种系中分别为98.63 kb与124.18 kb。供试种质资源被划分为地方品种与育种系/栽培品种两类群体。我们针对百粒重与产量性状，在连续3年的灌溉与干旱胁迫田间试验环境中，分别采用单标记、片段以及基于基因的关联分析模型开展全基因组关联分析。在灌溉条件下的种子重量性状中，以高严格性阈值检测到的关联位点数量更多，单标记与片段关联分析共获得约185个数量性状位点（Quantitative Trait Locus, QTLs）；而基于基因的全基因组关联分析则鉴定到约220个基因组区域，涵盖约650个功能基因。在干旱胁迫下的种子重量性状中，单标记与片段关联分析共鉴定到18个QTLs，基于基因的全基因组关联分析则检测到35个相关基因。对于产量性状，灌溉条件下共鉴定到25个关联位点，而干旱胁迫下两种分析方法联合共获得10个关联位点。除了在不同试验中重复检测到的稳定关联位点外，本研究还获得了约221个QTLs、650个功能基因的互补关联信息，其表型变异解释率（r²）范围为0.01%至32%。多个QTLs被定位在与产量形成密切相关的候选基因内部或侧翼区域，这为解析上述性状的遗传机制提供了更深入的认知，并为标记辅助育种提供了可用的分子工具。本研究的发现还筛选出了在干旱胁迫下产量表现更优的遗传材料（种质资源），可为普通菜豆育种项目提供优异的育种素材。最后，该高度多样化的中美洲种质群体的构建，为解析普通菜豆其他相关性状的遗传机制提供了重要的科学研究平台。