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Unravelling the Genetic Architecture of Rust Resistance in the Common Bean (Phaseolus vulgaris L.) by Combining QTL-Seq and GWAS Analysis.

Xinyi Wu | Baogen Wang | Yan Xin | Ying Wang | Shuo Tian | Jian Wang | Xiaohua Wu | Zhongfu Lu | Xinjiang Qi | Liming Xu | Guojing Li
Plants (Basel, Switzerland) | 2022

The common bean (Phaseolus vulgaris L.) is the most important legume crop directly used for human consumption worldwide. Bean rust, caused by Uromyces appendiculatus, is a devastating disease and usually causes severe loss of seed yield and pod quality. Deployment of resistant cultivars is the best strategy to combat this disease. However, despite being the largest snap bean-producing country, the genetic basis research of rust resistance has largely lagged in China. In this study, an RIL population and a diversity panel were evaluated for rust resistance against a purified rust isolate Cua-LS using a detached leaf assay. Deploying a QTL-Seq analysis in the RIL population, a 1.81 Mb interval on chromosome 4, a 2.73 Mb interval on chromosome 5 and a 1.26 Mb interval on chromosome 6 were identified as major QTLs for rust resistance, designated as Qur-1, Qur-2 and Qur-3, respectively. Through a GWAS diversity panel, 64 significant SNPs associated with rust resistance were detected, distributed in all 11 chromosomes and explaining 19-49% of the phenotypic variation. Synteny analysis showed that Qur-2 was validated in GWAS, but the rust QTL/SNPs detected in our study were different from the known genes, except Ur-11. A total of 114 candidate genes, including the typical NBS-LRR genes, protein kinase superfamily proteins and ABC transporter family proteins, were identified and proposed as the likely candidates. The identified 17 resistant accessions will enrich the resistant germplasm resources, and the detected QTLs/SNPs will facilitate the molecular breeding of rust resistance in the common bean.

Pubmed ID: 35406934

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BWA (tool)

RRID:SCR_010910

Software for aligning sequencing reads against large reference genome. Consists of three algorithms: BWA-backtrack, BWA-SW and BWA-MEM. First for sequence reads up to 100bp, and other two for longer sequences ranged from 70bp to 1Mbp.

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ANNOVAR (tool)

RRID:SCR_012821

An efficient software tool to utilize update-to-date information to functionally annotate genetic variants detected from diverse genomes (including human genome hg18, hg19, as well as mouse, worm, fly, yeast and many others). Given a list of variants with chromosome, start position, end position, reference nucleotide and observed nucleotides, ANNOVAR can perform: 1. gene-based annotation. 2. region-based annotation. 3. filter-based annotation. 4. other functionalities. (entry from Genetic Analysis Software)

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