The fitness effects of de novo structural variants

项目摘要/摘要 NIH独立之路奖(K99/R00)的这份提案侧重于对平勋博士的培训 谢长廷将成为大规模基因组学和人类种群遗传学的独立研究员。Dr。 谢家华是一名训练有素的种群遗传学家，拟议中的研究将使他的培训进入长期阅读的阶段- 基于测序技术和新的机器学习方法来研究 人类和非人类灵长类动物中的新突变，重点是结构变异(SVS)。另一个 关键部分将是开发最有可能基于哪些类型的新SVS的资源 致病，因此最值得医学研究人员进一步努力。在这项工作中开发的方法 将使其他研究人员能够在疾病病因学中对SVS进行更多的无假设分析。 具体地说，培训计划将集中研究新SVS的健身效果在 人类和非人类灵长类动物使用高质量的SV叫声和来自几个大规模的长和 短文测序项目。辅导工作将在小学生的监督下进行。 导师Evan Eichler博士和共同导师Sharon Browning博士都来自华盛顿大学(UW)。 导师和共同导师是在基因组变异表征方面久负盛名的专家 高通量技术与大规模遗传随机建模方法的发展 分别为数据。谢博士还将从一个正式的咨询委员会以及通过 由基因组科学部(GS)安排的活动，这是被辅导者的最佳地点 为候选人提供接触模型遗传学等领域杰出科学家的培训 生物体、疾病、种群遗传学和高通量基因组技术的发展。 虽然在自然界中被发现，但由于其大小通常被认为是有害的，SVS可能是有益的，并且 因此，新的SVS的适应度效应(DFE)的分布(即，有益、中性和 有害的SVS)仍然难以捉摸。在拟议的研究中，我们将推断新的SVS和其他变体的DFE 评估它们在自然界中的相对重要性，这反过来又有助于确定变体的优先顺序(例如，SVS与Single- 核苷酸变异[SNV])在医学遗传学中。具体地说，在K99/R00阶段，我们将(1)推断DFE 使用约100个长阅读和约4,000个短阅读高覆盖的多样化小组的新SVS和SNV 人类和非人灵长类基因组；(2)比较灵长类动物中新突变的DFE 现代和古代DNA基因组；以及(3)研究适应度效应和选择限制 在20,000个基因组的大队列中不同突变类别的疾病。在这一过程中学到的技能 提案是前沿的，是为候选人量身定做的，以积累大量的知识 基因组学的新领域，它将适用于许多生物体和疾病，并对 候选人未来的独立实验室。

PROJECT SUMMARY/ABSTRACT This proposal for the NIH Pathway to Independence Award (K99/R00) focuses on the training of Dr. PingHsun Hsieh to become an independent investigator of large-scale genomics and human population genetics. Dr. Hsieh is a population geneticist by training, and the proposed studies will advance his training into long-read- based sequencing technologies and novel machine-learning approaches to study the fitness consequences of new mutations, with a focus on structural variants (SVs), in humans and nonhuman primates. Another essential piece will be the development of resources on which types of new SVs are most likely to be pathogenic and hence most worth further effort by medical researchers. The methods developed in this work will enable other researchers to do more hypothesis-free analysis of SVs in disease etiology. Specifically, the training program will center on the study of the distribution of fitness effects of new SVs in human and nonhuman primates using high-quality SV calls and genotypes from several large-scale long- and short-read sequencing projects. The mentored work will take place under the supervision of the primary mentor, Dr. Evan Eichler, and the co-mentor, Dr. Sharon Browning, both at the University of Washington (UW). The mentor and co-mentor are well-established experts in the characterization of genomic variations using high-throughput technologies and the development of stochastic modeling methods for large-scale genetic data, respectively. Dr. Hsieh will also gain advice from a formal advisory committee as well as through activities arranged by the Department of Genome Sciences (GS), which is an optimal place for the mentored training providing the candidate with access to outstanding scientists in areas including genetics of model organisms, disease, population genetics, and the development of high-throughput genomic technologies. While found in nature and yet generally deemed to be deleterious given their size, SVs can be beneficial, and thus, the distribution of fitness effects (DFE) of new SVs (i.e., the relative frequencies of beneficial, neutral, and deleterious SVs) remains elusive. In the proposed studies, we will infer the DFE of new SVs and other variants to assess their relative importance in nature, which in turn helps prioritize variants (e.g., SVs vs. single- nucleotide variants [SNVs]) in medical genetics. Specifically, in the K99/R00 phases we will (1) infer the DFE of new SVs and SNVs using a diverse panel of ~100 long-read and ~4,000 short-read high-coverage human and nonhuman primate genomes; (2) compare the DFE of new mutations among primates using contemporary and ancient DNA genomes; and (3) study the fitness effects and selective constraints on diseases in different mutation categories in large cohorts of >20,000 genomes. The skills learned in this proposal are on the cutting-edge and are tailored for the candidate to amass a great amount of knowledge in new areas of genomics, which will be applicable to many organisms and diseases and critical to the candidate’s future independent laboratory.