大规模多态信息的细胞溯祖理论和统计分析方法

Mutations occur primarily during cells replicate but rate of change may vary at different stages of development. Next generation sequencing has gradually become a standard mean to reveal polymorphism between individuals and within individuals. This project aims at developing coalescent-based population genetics theory, simulation algorithm and statistical methods for studying evolution in cell populations and exploring the polymorphism in human germline lineage in a sample of more than 10 healthy males of different ages and their parents generated by high-coverage whole exome sequencing to gain knowledge of the mutational pattern during individual development. Implementation of this project will not only achieve a great progress on cell population genetics, but also help in eclucidating the mutation rules and the factors affecting the mutations during the development progress of human germline. The development of methodology is of importance in investigating genectic disease-causative mutations during human development.

下代DNA测序技术不仅已经广泛应用于生物学、医学和人类健康研究领域，同时更是研究微进化的重要手段。然而, 如何有效利用大规模测序数据来回答重要的生物学问题则是个巨大的挑战，其离不开必要的理论和方法学上的支持。本项目是上一个重大计划资助的培育项目，即果蝇种系突变规律研究的延续，将通过理论和实验相结合，建立和阐明人类个体发育过程细胞谱系变异的基本理论和法则。 其中理论研究部分包括建立和发展细胞溯祖理论、计算机算法以及用于估计突变率和检验的统计学分析方法；而实验部分包括了多个不同年龄个体内不同组织样本的大规模外显子深度测序和分析。项目不仅会在细胞群体遗传学的理论和方法学上获得重要进展, 而且能够阐明人类种系谱系发育过程中的突变规律和影响因素。后者对研究人类发育过程的突变及其导致的遗传疾病有重要的借鉴作用。

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