Soybean is a major legume crop cultivated globally due to the high quality and quantity of its seed protein and oil. However, drought stress is the most significant factor that decreases soybean yield, and more than 90% of US soybean acreage is dependent on rainfall. Water use efficiency (WUE) is positively correlated with the carbon isotopic ratio (13)C/(12)C (C13 ratio) and selecting soybean varieties for high C13 ratio may enhance WUE and help improve tolerance to drought. Our study objective was to identify genetic loci associated with C13 ratio using a diverse set of 205 soybean maturity group IV accessions, and to examine the genomic prediction accuracy of C13 ratio across a range of environments. An accession panel was grown and assessed across seven distinct combinations of site, year and treatment, with five site-years under irrigation and two site-years under drought stress. Genome-wide association mapping (GWAM) analysis identified 103 significant single nucleotide polymorphisms (SNPs) representing 93 loci associated with alterations to C13 ratio. Out of these 93 loci, 62 loci coincided with previous studies, and 31 were novel. Regions tagged by 96 significant SNPs overlapped with 550 candidate genes involved in plant stress responses. These confirmed genomic loci could serve as a valuable resource for marker-assisted selection to enhance WUE and drought tolerance in soybean. This study also demonstrated that genomic prediction can accurately predict C13 ratio across different genotypes and environments and by examining only significant SNPs identified by GWAM analysis, higher prediction accuracies (P ⤠0.05; 0.51 ⤠r ⤠0.65) were observed. We generated genomic estimated breeding values for each genotype in the entire USDA-GRIN germplasm collection for which there was marker data. This information was used to identify the top ten extreme genotypes for each soybean maturity group, which could serve as valuable genetic and physiological resources for future breeding and physiological studies.
Association mapping for water use efficiency in soybean identifies previously reported and novel loci and permits genomic prediction.
大豆水分利用效率关联作图可识别先前报道的和新的基因位点,并允许进行基因组预测
阅读:4
作者:Chamarthi Siva K, Purcell Larry C, Fritschi Felix B, Ray Jeffery D, Smith James R, Kaler Avjinder S, King C Andy, Gillman Jason D
| 期刊: | Frontiers in Plant Science | 影响因子: | 4.800 |
| 时间: | 2024 | 起止号: | 2024 Nov 28; 15:1486736 |
| doi: | 10.3389/fpls.2024.1486736 | ||
特别声明
1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。
2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。
3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。
4、投稿及合作请联系:info@biocloudy.com。
