Chen Yongming, Wang Wenxi, Yang Zhengzhao, Peng Huiru, Ni Zhongfu, Sun Qixin, Guo Weilong
Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China.
aBIOTECH. 2024 Feb 7;5(1):52-70. doi: 10.1007/s42994-023-00131-7. eCollection 2024 Mar.
Bread wheat () is an important crop and serves as a significant source of protein and calories for humans, worldwide. Nevertheless, its large and allopolyploid genome poses constraints on genetic improvement. The complex reticulate evolutionary history and the intricacy of genomic resources make the deciphering of the functional genome considerably more challenging. Recently, we have developed a comprehensive list of versatile computational tools with the integration of statistical models for dissecting the polyploid wheat genome. Here, we summarize the methodological innovations and applications of these tools and databases. A series of step-by-step examples illustrates how these tools can be utilized for dissecting wheat germplasm resources and unveiling functional genes associated with important agronomic traits. Furthermore, we outline future perspectives on new advanced tools and databases, taking into consideration the unique features of bread wheat, to accelerate genomic-assisted wheat breeding.
普通小麦()是一种重要作物,在全球范围内是人类蛋白质和热量的重要来源。然而,其庞大的异源多倍体基因组对遗传改良构成了限制。复杂的网状进化历史和基因组资源的复杂性使得功能基因组的破译更具挑战性。最近,我们通过整合统计模型开发了一系列用于剖析多倍体小麦基因组的通用计算工具。在此,我们总结了这些工具和数据库的方法创新及应用。一系列逐步示例说明了如何利用这些工具剖析小麦种质资源并揭示与重要农艺性状相关的功能基因。此外,考虑到普通小麦的独特特征,我们概述了关于新的先进工具和数据库的未来展望,以加速基因组辅助小麦育种。