Elucidating the effects of structural variation on cis-regulation in stickleback

项目摘要 是什么产生了一个人独特的特征，如头发的颜色，心率，甚至发展疾病的概率？健康生物体的大多数特征是遗传因素与环境条件（如饮食或压力水平）相互作用的组合。当这些相互作用出错时，结果往往是人口中某些成员的疾病状态。通常，疾病的来源是有害的基因的分离变体，其可以破坏基因或基因组的正常调节或转录。单核苷酸多态性（SNPs）是遗传变异的一个重要类型。最近，随着更高通量基因组技术的出现，结构变异的普遍性-例如大DNA块的倒位、缺失或易位-已变得越来越受重视。重要的是，初步研究表明，这些结构变异可能与人类疾病有关，如血友病和亨特综合征等。结构变异可以通过产生基因拷贝数的变异和通过基因缺失暴露隐性等位基因来影响基因组和表型。然而，这种基因组水平的变异如何转化为生物性状的差异仍不清楚。一种假说是，结构变异可能会改变基因的调控，改变每个细胞中特定基因的产生时间、地点和数量。 在人类中研究结构和表型变异之间的机制关系是困难的，但可以在模型脊椎动物生物体中完成，如小鼠或在我们的情况下，小鱼的自然种群。该研究项目的主要目标是记录自然群体中结构变异的基因组分布，并检验基因组水平结构变异通过基因表达变化促进表型变异的假设。这项研究将主要集中在threespine刺鱼，一个新兴的模型解剖数量性状表型变异的遗传基础，并适合在自然种群和实验室中的操纵研究的屏幕。我们将使用几种全基因组分析和下一代测序技术的新合成来实现以下目标。首先，我们将确定祖先和衍生threespine棘鱼的种群内和种群之间的结构变异的分布，第二，我们将遗传图谱的结构变异对基因表达的影响，推断顺式调控变化，通过eQTL分析。为了使我们的分析技术广泛用于其他模式生物，我们将创建一组公共的，基于网络的计算资源，用于识别相关的结构变异与基因表达。

Project Summary What produces an individual's unique set of traits, such as hair color, heart rate, or even probability of developing a disease? Most traits of healthy organisms are a combination of inherited genetic factors interacting with environmental conditions such as diet or stress levels. When these interactions go awry, the outcome is often a disease state in certain members of the population. Often, the source of the disease is a segregating variant of a gene that is harmful and which can disrupt the normal regulation or transcription of a gene or set of genes. Single letter changes, so-called Single Nucleotide Polymorphisms (SNPs), have long been recognized as an important category of genetic variation. Recently, with the advent of more high throughput genomic techniques, the prevalence of structural variation - such as inversions, deletions, or translocations of large blocks of DNA - has become increasingly appreciated. Importantly, initial studies have indicated that these structural variants can be associated with human diseases such as hemophilia and Hunter syndrome among many others. Structural variation can affect genomes and phenotypes by creating variation in gene copy number, and by exposing recessive alleles through gene deletions. However, the way that this genomic level variation can translate to differences in organismal traits is still unclear. A hypothesis is that structural variants may alter the regulation of genes, changing when, where and how much of a particular gene is made in each cell. Studying the mechanistic relationship between structural and phenotypic variation is difficult in humans, but can be accomplished in model vertebrate organisms such as mice or in our case natural populations of small fish. The primary goal of this research project is to document the genomic distribution of structural variants in natural populations and to test the hypothesis that genome level structural variation contributes to phenotypic variation through changes in gene expression. The research will focus primarily on threespine stickleback, an emerging model for dissecting the genetic basis of phenotypic variation in quantitative traits, and is amenable to both screens in natural populations and manipulative studies in the laboratory. We will use a novel synthesis of several whole-genome analysis and next generation sequencing techniques to accomplish the following aims. First, we will identify the distribution of structural variants within and among populations of ancestral and derived threespine stickleback fish, and second, we will genetically map the effects of structural variation on gene expression to infer cis-regulatory changes through an eQTL analysis. To make our analysis techniques widely available for use in other model organisms, we will create a set of public, web-based computational resources for identifying associating structural variation with gene expression.