Tracing the evolution of the human mutation rate

DESCRIPTION（由申请人提供）：所有的遗传变异都是由突变，由DNA损伤或DNA复制过程中的复制错误引起的变化产生的。突变非常频繁，平均而言，一个孩子的30亿个碱基对基因组中包含74个新的基因变异，而这些变异在父母的基因组中都不存在。这种新的突变比旧的突变具有更高的疾病风险，因为它们没有通过父母和后代几代人的生存测试。我们的目标是查明当人类离开非洲并适应全球不同的新环境时，人类突变率是如何进化的。我的初步研究表明，欧洲人在与非洲人和亚洲人分化后，经历了突变率的变化。这种变化的主要证据是，欧洲基因组比非洲或亚洲基因组的TCC→TTC突变型负担更高，其中三核苷酸“TCC”在其中心位点经历了从“C”到“T”的突变。我们希望通过观察混血拉丁裔和非裔美国人的罕见变异来研究这种突变率变化的遗传基础。特别是，我们将分离出可能在过去10-15代内通过突变产生的年轻基因变异，在基因从欧洲进入美洲已经开始之后。我们将推断每个新突变产生的遗传背景（欧洲人、非洲人或美洲原住民），并寻找欧洲人种与过量的TCC→TTC突变密切相关的基因组区域。这些地区最有可能存在改变欧洲人突变积累过程的因果等位基因。这项工作有可能对黑色素瘤产生有价值的见解，黑色素瘤是一种主要影响欧洲血统个体的癌症，其体细胞突变特征由TCC→TTC主导。第二个具体目标是寻找在人类物种中，或者更广泛地说，在类人猿中发生的突变率变化的其他特征。我们将使用一种称为潜在狄利克雷分配（LDA）的自然语言处理技术来识别突变率似乎在共同遗传控制下的突变类型集合。除了TCC→TTC外，少数突变类型显示出种群间速率分化的微弱信号，我们将尝试推断需要多少单独的突变率变化事件来解释这些信号。来自Specific Aim I的混合作图技术也可以用于询问近期可能发生的其他突变率变化的遗传基础。这些努力将提高我们对人类突变率的遗传结构的理解，以及突变率在不同人群之间的差异。

DESCRIPTION (provided by applicant): All genetic variation is created by mutations, changes that arise due to DNA damage or copying mistakes during DNA replication. Mutations are frequent enough that, on average, a child's 3-billion base pair genome contains 74 new genetic variants that are not present in the genome of either parent. Such new mutations confer a higher disease risk than older mutations because they have not passed the test of surviving through several generations of parents and offspring. We aim to pinpoint how the human mutation rate has evolved as humans left Africa and adapted to diverse new environments across the globe. One specific aim will follow up on my preliminary research which showed that Europeans experienced a mutation rate change after diverging from Africans and Asians. The primary evidence for this change is that European genomes have a higher burden than African or Asian genomes of the mutation type TCC→TTC, where the trinucleotide "TCC" has experienced a mutation from "C" to "T" at its central site. We wish to and the genetic basis of this mutation rate change by looking at rare variants in mixed- ancestry Latino and African-American individuals. Specially, we will isolate young genetic variants that probably arose via mutation within the past 10-15 generations, after gene ow from Europe into the Americas had already begun. We will infer the genetic background (European, African, or Native American) upon which each new mutation arose and look for genomic regions where European ances- try correlates strongly with an excess of TCC→TTC mutations. These will be the regions most likely to harbor a causal allele that changed the process of mutation accumulation in Europeans. This work has the potential to yield valuable insights into melanoma, a cancer that predominantly affects individuals of European ancestry and whose somatic mutational signature is dominated by TCC→TTC. A second specific aim is to look for other signatures of mutation rate change that have occurred within the human species or, more broadly, within the great apes. We will use a natural language processing technique called Latent Dirichlet Allocation (LDA) to identify collections of mutation types whose rates appear to be under common genetic control. A few mutation types besides TCC→TTC show weak signals of rate differentiation between populations, and we will attempt to infer how many separate mutation rate change events are necessary to explain these signals. The admixture mapping technique from Specific Aim I can also be adapted to interrogate the genetic basis of other mutation rate changes that might have occurred in the recent past. These efforts should improve our understanding of the human mutation rate's genetic architecture and how mutation rates differ between populations.