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通过全基因组关联研究(GWAS)挖掘与面包小麦气孔性状相关的基因组区域及其候选基因。

Mining genomic regions associated with stomatal traits and their candidate genes in bread wheat through genome-wide association study (GWAS).

作者信息

Liu Dezheng, Lu Shan, Tian Renmei, Zhang Xubin, Dong Qingfeng, Ren Hao, Chen Liang, Hu Yin-Gang

机构信息

State Key Laboratory of Crop Stress Resistance and High-Efficiency Production and College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China.

Institute of Water Saving Agriculture in Arid Regions of China, Northwest A&F University, Yangling, Shaanxi, China.

出版信息

Theor Appl Genet. 2025 Jan 7;138(1):20. doi: 10.1007/s00122-024-04814-7.

Abstract

112 candidate quantitative trait loci (QTLs) and 53 key candidate genes have been identified as associated with stomatal traits in wheat. These include bHLH, MADS-box transcription factors, and mitogen-activated protein kinases (MAPKs). Stomata is a common feature of the leaf surface of plants and serve as vital conduits for the exchange of gases (primarily CO₂ and water vapor) between plants and the external environment. In this study, a comprehensive genome analysis was conducted by integrating genome-wide association study (GWAS) and genome prediction to identify the genomic regions and candidate genes of stomatal traits associated with drought resistance and water-saving properties in a panel of 184 diverse bread wheat genotypes. There were significant variations on stomatal traits in the wheat panel across different environmental conditions. GWAS was conducted with the genotypic data from the wheat 660 K single-nucleotide polymorphism (SNP) chip, and the stomatal traits conducted across three environments during two growing seasons. The final GWAS identified 112 candidate QTLs that exhibited at least two significant marker-trait associations. Subsequent analysis identified 53 key candidate genes, including 13 bHLH transcription factor, 2 MADS-box transcription factors, and 4 mitogen-activated protein kinase genes, which may be strongly associated with stomatal traits. The application of Bayesian ridge regression for genomic prediction yielded an accuracy rate exceeding 60% for all four stomatal traits in both SNP matrices, with stomatal width achieving a rate in excess of 70%. Additionally, three Kompetitive allele-specific PCR markers were developed and validated, representing a significant advancement in marker-assisted prediction. Overall, these results will contribute to a more comprehensive understanding of wheat stomatal traits and provide a valuable reference for germplasm screening and innovation in wheat germplasm with novel stomatal traits.

摘要

已鉴定出112个候选数量性状基因座(QTL)和53个关键候选基因与小麦气孔性状相关。这些基因包括bHLH、MADS-box转录因子和丝裂原活化蛋白激酶(MAPK)。气孔是植物叶片表面的共同特征,是植物与外部环境之间气体(主要是二氧化碳和水蒸气)交换的重要通道。在本研究中,通过整合全基因组关联研究(GWAS)和基因组预测进行了全面的基因组分析,以确定184个不同面包小麦基因型群体中与抗旱和节水特性相关的气孔性状的基因组区域和候选基因。在不同环境条件下,小麦群体的气孔性状存在显著差异。利用小麦660K单核苷酸多态性(SNP)芯片的基因型数据进行GWAS分析,并在两个生长季节的三个环境中测定气孔性状。最终的GWAS鉴定出112个候选QTL,这些QTL表现出至少两个显著的标记-性状关联。随后的分析确定了53个关键候选基因,包括13个bHLH转录因子、2个MADS-box转录因子和4个丝裂原活化蛋白激酶基因,这些基因可能与气孔性状密切相关。在两种SNP矩阵中,贝叶斯岭回归用于基因组预测,所有四个气孔性状的准确率均超过60%,气孔宽度的准确率超过70%。此外,开发并验证了三个竞争性等位基因特异性PCR标记,这代表了标记辅助预测的重大进展。总体而言,这些结果将有助于更全面地了解小麦气孔性状,并为具有新型气孔性状的小麦种质资源筛选和创新提供有价值的参考。

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