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.

抽象的阐明自然观察到的令人敬畏的表型多样性的潜在遗传原因人口是生物学的主要挑战。尽管重要的是了解复杂的特征，我们目前缺乏对相关遗传成分的完全了解。遗传变异影响染色体片段的结构和拷贝数是该组件的不足。遗传结构。在此提案中，我们试图获得整个结构变化（SV）和拷贝数变化（CNV）以及它们如何促进自然种群的表型景观。在为了实现此目的我们最近完成了整个基因组的1,011天然分离株，以及伴随的大型分离株比例表型努力。 CNV在我们的应变收集中很常见，并且具有超大的表型影响协会测试我们已经完成了。我们建议：AIM 1。将长阅读测序应用于更好表征这些菌株中存在的结构变化并产生高质量的从头组件。在 AIM 2，我们将在大量环境条件下收集定量应变表型，特别强调我们和其他人对CNV特别敏感的条件。我们将还包括分子性状，例如mRNA和蛋白质丰度。然后，我们将执行关联测试在AIM 1中发现的变体是为了确定整个物种的SV和 CNV有助于性状变化。由于关联方法对稀有遗传变异的效果较差，我们将在AIM 3中，使用拨号板面板，其中受控的十字架使我们能够更好地调查目前的所有变化。最后，在 AIM 4我们将通过建立工程的图书馆来补充我们关于自然发生变化的工作变体。我们将创建大型剂量系列的分段放大和删除池，以更好了解它们在多个遗传背景之间的后果。我们的工作将导致更完整了解有关这一重要但研究了一类遗传变异。