Detecting QTL system of root hydraulic stress tolerance index at seedling stage in soybean

• Published in: Zuo wu xue bao Vol. 47; no. 5; pp. 847 - 859
• Main Authors: WANG, Wu-Bin, TONG, Fei, KHAN, Mueen-Alam, ZHANG, Ya-Xuan, HE, Jian-Bo, HAO, Xiao-Shuai, XING, Guang-Nan, ZHAO, Tuan-Jie, GAI, Jun-Yi
• Format: Journal Article
• Language: English; Chinese
• Published: Beijing Chinese Academy of Agricultural Sciences (CAAS) 01.05.2021
• Subjects: Chromosomes; Crop yield; Drought resistance; Environmental effects; Environmental stress; Gene expression; Gene mapping; Genes; Genome-wide association studies; Genomes; Heritability; Inbreeding; Mapping; Phenotypic variations; Plant breeding; Proline; Protein metabolism; Protein sources; Protein turnover; Proteins; Quantitative trait loci; Seedlings; Soybeans; Transcription factors; Transcriptomes; Vegetable oils
• ISSN: 0496-3490
• DOI: 10.3724/SP.J.1006.2021.04176

Soybean is an important source of plant protein and vegetable oil in the world. Drought is one of the important environmental stress factors affecting soybean yield. To explore the genetic base of drought tolerance in soybean, a nested association mapping population composed of two sets of recombinant inbred lines with a common parent in a total of 429 lines was investigated for leaf proline content under PEG simulated drought stress. The genetic system of root hydraulic stress tolerance index(RHSTI) was analyzed using the RTM-GWAS(restrictive two-stage multilocus genome-wide association study). The results showed that there were significant differences in RHSTI among the three parents under two different environments in spring and summer, and among the nested association mapping population with the variation range of 0.11–2.94 and 0.03–1.93, respectively. The heritability values of Line and Line×Environment were 37.9% and 60.1%, respectively, indicating that the variation of RHSTI was greatly affected by the environment. Using the RHSTI data and 6137 SNPLDB markers, a total of 45 main effect QTLs were detected on 18 chromosomes, which could explain a total of 37.58% phenotypic variation, including 7 large contribution QTLs with R2 more than 1%. Among them, 34 QTLs with QTL×Environment effect explained 12.50% of the phenotypic variation. Combined with the transcriptome data under PEG stress, totally 38 differentially expressed genes were identified within a QTL ± 500 kb, which can be grouped into different biological categories, including ABA responders, stress responders, transcription factors, development factors, protein metabolism factors, unknown functions and others, with stress responses, transcription factors and development factors as the major parts. In summary, the results indicated that the drought tolerance of soybean was a complex quantitative trait, with the complex genetic basis controlling by multiple loci, multiple genes and interaction with the environment. The present results can lay the foundation of molecular breeding for drought tolerance in soybean.