新疆维吾尔族遗传负荷分析及其进化和医学意义

Harmful, or deleterious mutations decrease the fitness of the carriers in the population but are maintained on a low level due to natural selection, especially in those populations experienced a long time isolation and have adapted to the environment where they have been residing. However, deleterious mutations could significantly increase in a recent admixed population resulted from inter-marriages between previously mutually isolated populations when they come into contact through colonization and migration. Consequently, genetic load of the admixed population is expected to fluctuate significantly, most likely increase, which has great impact on both evolutionary and medical studies. In this proposed project, we focus on the genetic load analysis of the Uyghur population in Xinjiang, a typical admixed population with both East Eurasian and West Eurasian ancestries, as we have previously revealed. Next-generation sequencing technology will be used for generating whole-genome data in 50 individuals and genetic variation will be analyzed to estimate and evaluate the genetic load of the Uyghurs. Genes or genomic regions with genetic load significantly increased or decreased in the Uyghurs can be identified with comparisons to the data of the European and East Asian populations which are public available such as the 1000 Genomes Project. The mechanism of the genetic load fluctuation driven by gene flow between populations will be explored and the contribution of genes with high genetic load to high incidence diseases such as type II diabetes will be further estimated and evaluated. The ambition of this project is to establish a integrative paradigm for both the evolutionary genetics and medical genetics, so that not only the long-term microevolution of genetic load in an admixed population such as the Uyghur, but also the short-term risk impact of genomic variations in the Uyghur can be elucidated.

人群经历长期分化和适应世居地环境，基因组中有害突变一般维持在一个较低水平。而彼此隔离分化的人群在近期大规模基因交流产生的混合人群，遗传负荷(genetic load)可能发生显著波动，这对人群的微观进化和疾病风险研究有重要影响。本项目选择我国典型的混合人群——新疆维吾尔族，采用新一代测序技术考察全基因组遗传变异，在群体和个体水平定量估计维吾尔族的遗传负荷；并与欧洲和东亚人群进行比较分析，确定维吾尔族中遗传负荷显著增加和降低的基因或基因组区域；进一步探讨基因交流对人群遗传负荷的作用机制，同时评估高遗传负荷基因变异在维族高发疾病如II-型糖尿病中的可能贡献；力图把维吾尔族进化遗传研究和医学遗传研究纳入到统一框架。本项目不仅从长期尺度上探讨维吾尔族遗传负荷形成和演化的机制，而且在近期尺度上揭示维吾尔族遗传负荷与其罹患高发性疾病的内在联系，因此在进化和生物医学研究中都具有重要科学价值和现实意义。

本项目围绕新疆维吾尔族遗传负荷分析及其进化和医学意义研究，经过四年的实施，达成既定目标，主要包括以下四个方面:. 【方法研究】发展了一系列遗传混合分析新方法(iMAAPs，CAMer，AdmixInfer，MultiWaver1.0 &2.0，ArchaicSeeker)，解析了新疆维吾尔族的遗传背景和祖源构成。. 【科学发现】基于深度全基因组测序数据揭示了维吾尔族人群由于遗传混合引入的大量稀有变异会对维吾尔族人群疾病或者表型的遗传结构产生影响，包括头面部特征、肤色、代谢、免疫，和嗅觉等。代表性工作于2021年9月11日发表在National Science Review发表，题为《Genomic diversity and post-admixture adaptation in the Uyghurs》。. 【机制研究】研究了新疆维吾尔族等群体中宿主-肠道微生物遗传多样性模式与微观共进化机制。例如，调节肠道免疫水平的Bacteroides ovatus与宿主遗传变异rs12899811存在共同作用并影响人类特定表型。代表性工作于2021年11月20日发表于Journal of Genetics and Genomics。. 【资源建设】建立了多个大型人类群体基因组数据资源库，包括已建成并公开发布的人群多样性 数据库(PGG.population)、突变库(PGG.SNV)，入选F1000、 中国生物信息学十大科学进展、中国生物信息学十大数据库等。. 本项目共发表论文39篇，专著(书籍章节)1篇，均已标注基金号: 31771388。其中SCI收录期刊(Genome Biol., NAR, NSR, MBE, Nat.Genet., Nat.Communi.等)论文39篇；项负责人为通讯(或共同通讯)作者论文29篇；其中5-year IF>10的期刊论文14篇，单篇最高被引131次。. . 项目执行期间，培养博士生7名，硕士生2名，其中1人获得中科院院长奖 、1人上海市优秀毕业生；2名青年人才入选中科院青年促进会，1名青年人才晋升高级职称并获得上海市青年科技英才——“扬帆计划”，1名在读博士研究生获得国家奖学金。2名在站博士后分别入选上海市“超博计划”和复旦大学“超博计划”。项目负责人入选万人计划领军人才。