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.

农艺性状的遗传解析对于作物改良和全球粮食安全非常重要。雄穗分支数（TBN）的表型变异是一个主要的育种目标，由许多数量性状基因座（QTL）控制。大规模QTL克隆方法的缺乏限制了TBN的系统解析，从而阻碍了现代玉米育种。在这里，我们设计了 QTG-Miner，一种基于多组学数据的技术，用于大规模、快速克隆玉米数量性状基因 (QTG)。使用 QTG-Miner，我们克隆并验证了 7 个 TBN QTL 背后的 7 个基因。与传统方法相比，QTG-Miner 在主效应和次效应 TBN QTL 方面均表现良好。选择分析表明，在玉米改良过程中，大量基因和网络模块受到了选择。选择特征在雌性杂种优势群体和雄性杂种优势群体之间的多种生物学途径中显着丰富。总之，QTG-Miner 提供了一种在作物中快速克隆 QTG 的大规模方法，并剖析了 TBN 的遗传基础，以用于进一步的玉米育种。