Species-wide survey of the phenotypic impact of genomic structural variation in yeast

酵母基因组结构变异对表型影响的物种范围调查

基本信息

批准号：
10686133
负责人：
Maitreya J Dunham
金额：
$ 26.01万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-01 至 2026-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10686133
关键词：
Affect Agar Aneuploidy Bar Codes Beer Beverages Biology Caenorhabditis elegans Chromosome Structures Chromosomes Collaborations Collection Complement Complex Copy Number Polymorphism DNA Resequencing Data Data Analyses Dissection Engineering Environment Eukaryota Fermentation Food Frequencies Gene Expression Genetic Genetic Variation Genome Genomics Genotype Growth Heritability Human Human Development Human body Hybrids Individual Industrialization Insecta Knowledge Laboratories Libraries Literature Measures Messenger RNA Methods Modeling Molecular Mutation Phenotype Plants Population Process Proteins Resources Role Saccharomyces cerevisiae Saccharomycetales Sampling Series Soil Source Structure Surveys Technology Testing Universities Variant Washington Wine Work Yeast Model System Yeasts base design dosage experimental study fitness fitness test gene environment interaction genetic architecture genetic linkage genetic variant genome wide association study genome-wide human disease model organism molecular phenotype nanopore novel strategies pleiotropism rare variant trait vector whole genome

项目摘要

ABSTRACT Elucidating the underlying genetic causes of the awesome phenotypic diversity observed in natural populations is a major challenge in biology. Despite the importance of understanding the genetic basis of complex traits, we currently lack complete knowledge of the relevant genetic components. Genetic variation affecting the structure and copy number of chromosomal segments is an underappreciated component of the genetic architecture. In this proposal, we seek to obtain a species-wide view of structural variation (SV) and copy number variation (CNV) and how these contribute to the phenotypic landscape of natural populations. In order to accomplish this, we will take advantage of the genetic workhorse Saccharomyces cerevisiae, for which we have recently completed whole genome resequencing of 1,011 natural isolates, plus accompanying large scale phenotyping efforts. CNVs are frequent in our strain collection and have outsize phenotypic affects in the association tests we have so far completed. We propose to: Aim 1. Apply long read sequencing to better characterize the structural variation present in these strains and generate high quality de novo assemblies. In Aim 2, we will collect quantitative strain phenotypes over a large panel of environmental conditions, with a particular emphasis on conditions that we and others have found to be particularly sensitive to CNVs. We will also include molecular traits such as mRNA and protein abundance. We will then perform association testing with the variants discovered in Aim 1 in order to determine over an entire species the degree to which SVs and CNVs contribute to trait variation. Since association methods perform poorly for rare genetic variants, we will in Aim 3 use a diallel panel where controlled crosses allow us to better survey all variation present. Finally, in Aim 4 we will complement our work on naturally occurring variation by building libraries of engineered variants. We will create large dosage series pools of segmental amplifications and deletions to better understand their consequences across multiple genetic backgrounds. Our work will result in a more complete understanding of the complexities of the genotype-phenotype connection with respect to this important but understudied class of genetic variants.

抽象的阐明自然中观察到的令人敬畏的表型多样性的潜在遗传原因种群数量是生物学的一个重大挑战。尽管了解遗传基础很重要由于性状复杂，我们目前缺乏相关遗传成分的完整知识。遗传变异影响染色体片段的结构和拷贝数是染色体的一个未被充分认识的组成部分遗传结构。在本提案中，我们寻求获得结构变异（SV）和拷贝数变异（CNV）以及它们如何影响自然种群的表型景观。在为了实现这一目标，我们将利用遗传主力酿酒酵母，为此我们最近完成了 1,011 个天然分离株的全基因组重测序，以及伴随的大规模化表型分析工作。 CNV 在我们的菌株收集中很常见，并且在菌株中具有巨大的表型影响到目前为止我们已经完成了关联测试。我们建议：目标 1. 应用长读长测序更好地表征这些菌株中存在的结构变异并生成高质量的从头组装。在目标 2，我们将收集大量环境条件下的定量菌株表型，特别强调我们和其他人发现对 CNV 特别敏感的条件。我们将还包括分子特征，例如 mRNA 和蛋白质丰度。然后我们将进行关联测试结合目标 1 中发现的变体，以确定整个物种中 SV 和 CNV 有助于性状变异。由于关联方法对于罕见的遗传变异表现不佳，我们将在目标 3 中，使用双列组面板，其中受控的交叉使我们能够更好地调查存在的所有变异。最后，在目标 4 我们将通过构建工程基因库来补充我们在自然发生变异方面的工作变种。我们将创建分段扩增和删除的大剂量系列池，以更好地了解其在多种遗传背景下的后果。我们的工作将带来更加完整的结果了解基因型-表型联系的复杂性，这一点很重要，但正在研究的一类遗传变异。