Valdisser Paula Arielle Mendes Ribeiro, Müller Bárbara S F, de Almeida Filho Janeo Eustáquio, Morais Júnior Odilon Peixoto, Guimarães Cléber Morais, Borba Tereza C O, de Souza Isabela Pavanelli, Zucchi Maria Imaculada, Neves Leandro G, Coelho Alexandre S G, Brondani Claudio, Vianello Rosana Pereira
Biotechnology Laboratory, EMBRAPA Arroz e Feijão, Santo Antônio de Goiás, Brazil.
Genetics and Molecular Biology Graduate Program, Institute of Biology, UNICAMP, Campinas, Brazil.
Front Plant Sci. 2020 Nov 12;11:574674. doi: 10.3389/fpls.2020.574674. eCollection 2020.
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 ( ), 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; 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因素,对全球菜豆生产影响巨大。了解调控菜豆产量和种子重量(SW)的遗传基础是培育优良品种的基本前提。本研究的主要目标是通过对一个中美洲普通菜豆种质资源群体进行基因分型来进行全基因组标记发现,该群体包含广泛来源的栽培种和地方品种,随后使用不同的全基因组关联研究(GWAS)方法鉴定在两种水分条件下与生产力相关的基因组区域。对339个基因型共进行了11,870个标记的基因分型,其中3,213个是硅基DArT标记,8,657个单核苷酸多态性(SNP)标记来自DArT和CaptureSeq。经结构和亲缘关系校正后的连锁不平衡延伸估计值,地方品种和育种系分别为98.63 kb和124.18 kb。种质被分为地方品种和品系/栽培品种。我们连续3年在有水分胁迫和无水分胁迫的田间环境中,使用单标记、区段标记和基因标记模型对100粒种子重量(100-SW)和产量进行了GWAS分析。在灌溉条件下,SW性状在高严格度下鉴定出更多的关联,单标记和区段标记共鉴定出约185个数量性状位点(QTL),而基于基因的GWAS分析显示约220个基因组区域包含约650个基因。对于干旱条件下的SW,单标记和区段标记鉴定出18个QTL,基于基因的GWAS分析鉴定出35个基因。对于产量,在灌溉条件下鉴定出25个关联,而在干旱条件下两种方法共鉴定出10个关联。除了在各实验中检测到的一致关联外,这些GWAS方法还提供了重要的互补QTL信息(约221个QTL;650个基因;贡献率从0.01%到32%)。在对生产力起重要作用的候选基因内部或附近挖掘到了几个QTL,这有助于更好地理解这些性状的遗传机制,并为标记辅助育种提供了可用的分子工具。这些发现还使得能够鉴定出在干旱条件下具有更好产量表现的遗传材料(种质),这对普通菜豆育种计划很有意义。最后,这个高度多样化的中美洲群体的可用性对于分析普通菜豆的任何相关性状具有重要的科学价值。