文献类型: 外文期刊
作者: Xi Wang;Juan Li;Linqian Han;Chengyong Liang;Jiaxin Li;Xiaoyang Shang;Xinxin Miao;Zi Luo;Wanchao Zhu;Zhao Li;Tianhuan Li;Yongwen Qi;Huihui Li;Xiaoduo Lu;Lin Li
作者机构:
期刊名称: Nature Communications
ISSN: 2041-1723
年卷期: 2023 年 14 卷 1 期
页码:
收录情况: SCIE(2023版)
摘要: Genetic dissection of agronomic traits is important for crop improvement and global food security. Phenotypic variation of tassel branch number (TBN), a major breeding target, is controlled by many quantitative trait loci (QTLs). The lack of large-scale QTL cloning methodology constrains the systematic dissection of TBN, which hinders modern maize breeding. Here, we devise QTG-Miner, a multi-omics data-based technique for large-scale and rapid cloning of quantitative trait genes (QTGs) in maize. Using QTG-Miner, we clone and verify seven genes underlying seven TBN QTLs. Compared to conventional methods, QTG-Miner performs well for both major- and minor-effect TBN QTLs. Selection analysis indicates that a substantial number of genes and network modules have been subjected to selection during maize improvement. Selection signatures are significantly enriched in multiple biological pathways between female heterotic groups and male heterotic groups. In summary, QTG-Miner provides a large-scale approach for rapid cloning of QTGs in crops and dissects the genetic base of TBN for further maize breeding.
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