Genetic basis of stress tolerance in natural populations of yeast

描述（由申请人提供）：复杂性状通过群体中分离的数量性状基因座的组合效应遗传。这些遗传决定因素可能有或大或小的影响，并可能以无数方式联合收割机。尽管通过全基因组关联研究和其他方法对复杂性状的遗传决定因素进行了十年的研究，但该领域尚未确定从基因型推断表型的最佳方法。我们建议使用酵母遗传学来学习一系列数量性状的潜在遗传结构。酵母系统拥有上级的实验工具、跨真核生物的保守生物学，以及可供借鉴的不断增长的多样化基因组序列集合。我们将首先关注强效应基因座，即“孟德尔”性状。这些通过等位基因交换实验容易地进行遗传作图和实验确认。我们的假设是，具有强效应等位基因的基因也将在整个群体中具有更多数量效应的等位基因。这个想法类似于“罕见变异”假说，其中低频率强效应等位基因导致高疾病风险。我们试图发现这些相同的基因是否也可能在整个人群中具有重要性，因为较低的效应等位基因可能更难以识别。我们将在三个具体目标下进行这个项目，每个目标都由一名专家调查员负责。在目标1中，我们将探索自然酵母菌群中的表型多样性。cerevisiae和S.矛盾的。这些物种有大量的表型和基因型多样性，我们可以利用。特别是，我们将观察到分离的生长能力，在面对环境压力，酵母菌可能经历了在其自然历史。第二个目的是确定那些分离为少数大效应位点的表型的遗传基础。为了定位致病基因座，我们将使用批量分离定位方法结合深度测序，然后进行等位基因交换实验以证明因果关系。第三个目标是测试这些相同的基因座是否对一大组菌株的表型变异很重要。我们将从数百个遗传多样性分离株中扩增等位基因，将其移植到等基因背景中，并通过基于池的定量竞争性测定来测定基因功能。将使用深度测序测量等位基因频率。这种方法的组合将使我们能够识别杂交，其中耐胁迫性状以遗传上简单的方式分离，绘制致病基因，并确定这些基因中其他变异体在整个种群中的重要性。我们的研究结果将为理解复杂性状的遗传基础提供信息。 公共卫生相关性：大多数人类疾病都有复杂的潜在遗传基础;然而，一个子集分离为简单的孟德尔特征。我们将利用模型真核生物芽殖酵母，以确定是否与遗传简单性状相关的基因的变异也在人群中具有数量变异。我们的研究结果可能会影响对人类这些特征的研究。

DESCRIPTION (provided by applicant): Complex traits are inherited via the combined effects of quantitative trait loci segregating in a population. These genetic determinants may have large or small effects, and may combine in a myriad of ways. Despite a decade of work on mapping the genetic determinants of complex traits via genome-wide association studies and other methods, the field has as yet not determined an optimal approach to inferring phenotype from genotype. We propose to use yeast genetics to learn the underlying genetic architecture of a series of quantitative traits. The yeast system has superior experimental tools, conserved biology across eukaryotes, and a growing collection of diverse genome sequences on which to draw. We will first focus on loci of strong effect, i.e. "Mendelian" traits. These lend themselves o easy genetic mapping and experimental confirmation via allele swap experiments. Our hypothesis is that genes with strong effect alleles will also harbor alleles of more quantitative effect across a population. This idea is akin to the "rare variant" hypothesis in which low frequency strong effect alleles contribute to high disease risk. We seek to discover whether these same genes may also be of importance across the population due to lower effect alleles that may be more difficult to identify. We will pursue this project in three specific aims, each le by an expert investigator. In Aim 1, we will explore the phenotypic diversity in natural yeast populations from the species S. cerevisiae and S. paradoxus. These species have a great deal of phenotypic and genotypic diversity that we can utilize. In particular, we will observe segregation of growth ability in the face of environmental stresses that yeasts may have experienced during their natural history. The second aim is to determine the genetic basis of those phenotypes that segregate as a small number of large effect loci. To map the causative loci, we will use a bulk segregant mapping method coupled with deep sequencing, followed by allele swap experiments to prove causation. The third aim is to test whether these same loci are important for phenotypic variation across a large panel of strains. We will amplify alleles from hundreds of genetically diverse isolates, transplant them into an isogenic background, and assay gene function via a pool-based, quantitative, competitive assay. Allele frequency will be measured using deep sequencing. This combination of methods will allow us to identify crosses in which stress tolerance traits segregate in a genetically simple manner, map the causative genes, and determine the importance of additional variants in these genes across a population. Our results will inform the understanding of the genetic basis of complex traits. PUBLIC HEALTH RELEVANCE: Most human diseases have a complex underlying genetic basis; however, a subset segregates as simple Mendelian traits. We will utilize the model eukaryote budding yeast to determine whether the genes whose variants are associated with genetically simple traits also harbor quantitative variation across populations. Our results could influence the study of such traits in humans.