Yuan Jin Hong, Li Jun Hua, Yuan Jiao Jiao, Jia Ke Li, Li Shu Fen, Deng Chuan Liang, Gao Wu Jun
College of Life Sciences, Henan Normal University, Xinxiang 453007, China.
Yi Chuan. 2017 Dec 20;39(12):1168-1177. doi: 10.16288/j.yczz.17-095.
Classical forward genetic analysis relies on construction of complicated progeny populations and development of many molecular markers for linkage analysis in genetic mapping, which is both time- and cost-consuming. The recently developed MutMap is a new forward genetic approach based on high-throughput next-generation sequencing technologies. It is more efficient and affordable than traditional methods. Moreover, new extended methods based on MutMap have been developed: MutMap+, which is based on self-crossing; MutMap-Gap, which is used to recognize the causative variations occurring in genome gap regions; QTL-seq, a method similar to MutMap for mapping quantitative trait loci. These methods are free from constructing complicated mapping population, genetic hybridization and linkage information. They have greatly accelerated the identification of genetic elements associated with interested phenotypic variation. Here, we review the basic principles of MutMap, and discuss their future applications in next generation sequencing-based forward genetic mapping and crop improvement.
经典的正向遗传学分析依赖于构建复杂的后代群体以及开发许多分子标记用于遗传图谱中的连锁分析，这既耗时又费钱。最近开发的MutMap是一种基于高通量下一代测序技术的新型正向遗传学方法。它比传统方法更高效且成本更低。此外，基于MutMap的新扩展方法也已被开发出来：MutMap+，基于自交；MutMap-Gap，用于识别基因组间隙区域中发生的致病变异；QTL-seq，一种类似于MutMap的用于定位数量性状位点的方法。这些方法无需构建复杂的作图群体、进行遗传杂交和连锁信息分析。它们极大地加速了与感兴趣的表型变异相关的遗传元件的鉴定。在此，我们综述了MutMap的基本原理，并讨论了它们在基于下一代测序的正向遗传图谱绘制和作物改良中的未来应用。
