TWAS facilitates gene-scale trait genetic dissection through gene expression, structural variations, and alternative splicing in soybean

作者：Delin Li, Qi Wang, Yu Tian, Xiangguang Lyv, Hao Zhang, Huilong Hong, Huawei Gao, Yan-Fei Li, Yan-Fei Li, Chaosen Zhao, Jiajun Wang, Ruizhen Wang, Jinliang Yang, Bin Liu, Patrick S. Schnable, James C. Schnable, Ying-Hui Li, Ying-Hui Li, Li-Juan Qiu · 发表于：Plant Communications · 年份：2024 · DOI：10.1016/j.xplc.2024.101010 · 被引用次数：25 · 研究领域：Soybean genetics and cultivation、Genetic Mapping and Diversity in Plants and Animals、Plant pathogens and resistance mechanisms

A genome-wide association study (GWAS) identifies trait-associated loci, but identifying the causal genes can be a bottleneck, due in part to slow decay of linkage disequilibrium (LD). A transcriptome-wide association study (TWAS) addresses this issue by identifying gene expression-phenotype associations or integrating gene expression quantitative trait loci with GWAS results. Here, we used self-pollinated soybean (Glycine max [L.] Merr.) as a model to evaluate the application of TWAS to the genetic dissection of traits in plant species with slow LD decay. We generated RNA sequencing data for a soybean diversity panel and identified the genetic expression regulation of 29 286 soybean genes. Different TWAS solutions were less affected by LD and were robust to the source of expression, identifing known genes related to traits from different tissues and developmental stages. The novel pod-color gene L2 was identified via TWAS and functionally validated by genome editing. By introducing a new exon proportion feature, we significantly improved the detection of expression variations that resulted from structural variations and alternative splicing. As a result, the genes identified through our TWAS approach exhibited a diverse range of causal variations, including SNPs, insertions or deletions, gene fusion, copy number variations, and alternative splicing. Using this approach, we identified genes associated with flowering time, including both previously known genes and novel genes ...