The fitness effects of de novo structural variants

从头结构变异的适应度效应

基本信息

批准号：
10733508
负责人：
PingHsun Hsieh
金额：
$ 24.71万
依托单位：
UNIVERSITY OF MINNESOTA
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-02-09 至 2026-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10733508
关键词：
Advisory Committees Affect Area Award Base Pairing Benchmarking Categories Communities Complex Copy Number Polymorphism DNA DNA Sequence Data Demography Development Diploidy Disease Etiology Evolution Frequencies Future Genes Genetic Genetic Diseases Genetic Drift Genetic Models Genetic Polymorphism Genome Genomics Genotype Goals Human Human Genome Individual Knowledge Laboratories Learning Skill Machine Learning Medical Medical Genetics Mentors Methods Modeling Modernization Mutation Natural Selections Nature Organism Outcome Parents Pathogenicity Pathway interactions Phase Phylogenetic Analysis Population Population Genetics Primates Public Health Quantitative Trait Loci Recurrence Relaxation Research Research Personnel Resource Development Resources Sample Size Sampling Scientist Shapes Signal Transduction Single Nucleotide Polymorphism Supervision Technology Testing Training Training Programs Uncertainty United States National Institutes of Health Universities Variant Washington Work autism spectrum disorder biological systems biomedical resource career cohort disease-causing mutation expectation fitness genetic variant genome sciences genome sequencing genome wide association study genomic locus genomic variation high throughput technology human population genetics improved machine learning method model organism nonhuman primate novel pressure simulation skills trait

项目摘要

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.

项目概要/摘要 NIH 独立之路奖 (K99/R00) 的提案重点关注 PingHsun 博士的培训谢博士成为大规模基因组学和人类群体遗传学的独立研究者。谢家华是一位受过训练的群体遗传学家，拟议的研究将把他的训练提升为长篇阅读—— 基于测序技术和新颖的机器学习方法来研究健康后果人类和非人类灵长类动物的新突变，重点是结构变异（SV）。最重要的部分是开发最有可能出现的新型 SV 类型的资源致病性，因此最值得医学研究人员进一步努力。将使其他研究人员能够对疾病病因学中的 SV 进行更多无假设分析。具体来说，训练计划将集中研究新SV的健身效果分布人类和非人类灵长类动物使用高质量的 SV 调用和基因型从几个大规模的长期和短读测序项目将在初级的监督下进行。导师 Evan Eichler 博士和共同导师 Sharon Browning 博士均来自华盛顿大学 (UW)。导师和共同导师都是使用基因组变异表征的知名专家高通量技术和大规模遗传随机建模方法的发展谢博士还将分别从正式的咨询委员会以及通过该委员会获得建议。基因组科学系（GS）安排的活动，是受指导的最佳场所培训为候选人提供接触模型遗传学等领域杰出科学家的机会生物体、疾病、群体遗传学以及高通量基因组技术的发展。虽然在自然界中存在，但考虑到其大小，SV 通常被认为是有害的，但 SV 也可能是有益的，并且因此，新 SV 的适应度效应 (DFE) 分布（即有益的、中性的和有害的 SV）仍然难以捉摸。在拟议的研究中，我们将推断新 SV 和其他变体的 DFE。评估它们在自然界中的相对重要性，这反过来又有助于优先考虑变体（例如，SV 与单具体来说，在 K99/R00 阶段，我们将 (1) 推断 DFE。使用约 100 个长读长和约 4,000 个短读长的多样化面板进行新的 SV 和 SNV 高覆盖率人类和非人类灵长类动物基因组；（2）使用当代和古代 DNA 基因组；(3) 研究适应性效应和选择性限制超过 20,000 个基因组的大型队列中不同突变类别的疾病在此学到的技能。提案处于前沿，并为候选人量身定制，以积累大量的知识基因组学的新领域，将适用于许多生物体和疾病，并对人类健康至关重要候选人未来的独立实验室。