Tracing the evolution of the human mutation rate

描述(由申请人提供)：所有基因变异都是由突变造成的，即由于DNA损伤或复制错误而产生的变化。突变非常频繁，平均而言，一个孩子30亿个碱基对的基因组中包含74个新的遗传变异，这些变异在父母双方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存活测试。我们的目标是查明随着人类离开非洲并适应全球不同的新环境，人类突变率是如何演变的。我的初步研究表明，欧洲人在与非洲人和亚洲人分道扬镳后，经历了突变率的变化，这将是一个具体的目标。这一变化的主要证据是，欧洲基因组比非洲或亚洲突变型Tcc→Ttc的基因组负担更重，在这些突变型基因组中，三核苷酸“tcc”在其中心位置经历了从“C”到“T”的突变。我们希望通过观察拉丁裔和非裔美国人混合血统的罕见变异来改变这种突变率的遗传基础。特别是，我们将分离年轻的基因变异，这些变异可能是在过去10-15代内通过突变产生的，之后基因已经开始从欧洲进入美洲。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)，并寻找欧洲人尝试与tcc→ttc突变过多密切相关的基因组区域。这些区域将是最有可能含有改变欧洲人突变积累过程的因果等位基因的区域。这项工作有可能为黑色素瘤提供有价值的见解，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人类物种内，或者更广泛地说，在类人猿体内发生的突变率变化的其他特征。我们将使用一种名为潜在狄利克雷分配(LDA)的自然语言处理技术来识别其突变类型的集合，这些突变类型的频率似乎受到共同的基因控制。除了Tcc→Ttc外，还有几种突变类型显示出种群间的速率分化信号，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。来自特定目标I的混合作图技术也可以用于询问最近可能发生的其他突变率变化的遗传基础。这些努力应该会提高我们对人类突变率的遗传结构以及不同种群之间突变率差异的理解。

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.