Wang Xi, Han Linqian, Li Juan, Shang Xiaoyang, Liu Qian, Li Lin, Zhang Hongwei
National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China.
Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Cell Rep. 2023 Sep 26;42(9):113039. doi: 10.1016/j.celrep.2023.113039. Epub 2023 Aug 30.
Functional cloning and manipulation of genes controlling various agronomic traits are important for boosting crop production. Although bulked segregant analysis (BSA) is an efficient method for functional cloning, its low throughput cannot satisfy the current need for crop breeding and food security. Here, we review the rationale and development of conventional BSA and discuss its strengths and drawbacks. We then propose next-generation BSA (NG-BSA) integrating multiple cutting-edge technologies, including high-throughput phenotyping, biological big data, and the use of machine learning. NG-BSA increases the resolution of genetic mapping and throughput for cloning quantitative trait genes (QTGs) and optimizes candidate gene selection while providing a means to elucidate the interaction network of QTGs. The ability of NG-BSA to efficiently batch-clone QTGs makes it an important tool for dissecting molecular mechanisms underlying various traits, as well as for the improvement of Breeding 4.0 strategy, especially in targeted improvement and population improvement of crops.
克隆控制各种农艺性状的基因并对其进行操作，对于提高作物产量至关重要。尽管混合分组分析法（BSA）是功能克隆的一种有效方法，但其低通量无法满足当前作物育种和粮食安全的需求。在此，我们回顾了传统BSA的原理和发展，并讨论了其优缺点。然后，我们提出了整合多种前沿技术的下一代BSA（NG-BSA），包括高通量表型分析、生物大数据以及机器学习的应用。NG-BSA提高了遗传图谱绘制的分辨率和克隆数量性状基因（QTG）的通量，并优化了候选基因的选择，同时提供了阐明QTG相互作用网络的手段。NG-BSA高效批量克隆QTG的能力使其成为剖析各种性状潜在分子机制以及改进育种4.0策略的重要工具，特别是在作物的定向改良和群体改良方面。
