Methods for high-resolution analysis of genetic effects on gene expression

高分辨率分析遗传对基因表达影响的方法

基本信息

  • 批准号:
    8915306
  • 负责人:
  • 金额:
    $ 14.2万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2013
  • 资助国家:
    美国
  • 起止时间:
    2013-08-01 至 2016-06-30
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Assessing the impact of genetic variants on cellular phenotypes like gene expression provide new opportunities for understanding the biology of genomes and disease. By identifying expression and splicing quantitative trait loci (eQTL or sQTL), we can elucidate new mechanisms underlying trait-associated variation and gain new insights into gene regulatory mechanisms and pathways. With the availability of novel technologies and new large datasets we are now in a position to perform high resolution analysis of transcriptomes and elucidate causal cellular mechanisms for phenotypic variability and disease. In the proposed project we aim to do the following: Specific Aim 1: We will undertake detailed transcriptome analysis of the GTEx data. We will improve the workflow of transcriptome analysis by deploying novel computational methods. First, we will tackle the problem of identifying transcripts and estimating their abundances. Second, we will deploy a Bayesian approach for comparing transcript distribution within and among populations and tissues to develop a robust catalog of differentially expressed genes. Specific Aim 2: We will develop improved statistical methods to discover regulatory variation. Over the past 3-4 years, our collaborative group has developed many tools for mapping genetic variants underlying expression differences among individuals. Here, we will apply these tools to the GTEx data to map eQTL using the high-quality transcriptome feature quantifications from Aim 1. The approaches we will deploy include: (i) haplotype-based methods for mapping of cis eQTL, (ii) improved methods for quantifying Allele Specific Expression (ASE), (iii) Bayesian mapping of trans eQTL using GRNs, and (iv) integrated multi-tissue and multi-population eQTL mapping. Specific Aim 3: We will map putatively causal variants that affect gene expression or transcript structure and assess their functional attributes. To understand the molecular bases of human gene regulation, we will create a comprehensive catalog of causal variants influencing expression and their associated genomic features. We will focus on: (i) the study of patterns of chromatin states to define rules for the location and effect of eQTL; and (ii) the interpretation o loss of function variant effects on transcriptomes and individuals. Specific Aim 4: We will build quantitative genetic and gene regulatory models of cellular transcript abundance. Our main efforts under this aim will be: (i) to assess patterns of epistasis/penetrance between protein-coding and regulatory variation; and (ii) reconstruct gene regulatory networks. These models will provide biological insights into the causes and consequences of eQTL.
描述(由申请人提供):评估遗传变异对细胞表型(如基因表达)的影响为理解基因组和疾病的生物学提供了新的机会。通过鉴定表达和剪接数量性状位点(eQTL或sQTL),我们可以阐明性状相关变异的新机制,并对基因调控机制和途径有新的认识。随着新技术和新的大型数据集的可用性,我们现在能够对转录组进行高分辨率分析,并阐明表型变异和疾病的因果细胞机制。具体目标1:我们将对GTEx数据进行详细的转录组分析。我们将通过部署新的计算方法来改进转录组分析的工作流程。首先,我们将解决识别转录本和估计其丰度的问题。其次,我们将部署一个贝叶斯方法比较转录本分布内和人群和组织之间,以开发一个强大的目录差异表达基因。具体目标2:我们将开发改进的统计方法来发现监管变异。在过去的3-4年里,我们的合作小组已经开发了许多工具,用于绘制个体之间表达差异的遗传变异。在这里,我们将这些工具应用于GTEx数据,使用Aim 1的高质量转录组特征定量来绘制eQTL。我们将部署的方法包括:(i)基于单倍型的cis eQTL定位方法,(ii)用于量化等位基因特异性表达(ASE)的改进方法,(iii)使用GRNs的transeQTL的贝叶斯定位,以及(iv)整合的多组织和多群体eQTL定位。具体目标3:我们将绘制影响基因表达或转录本结构的pupectin因果变体,并评估其功能属性。为了了解人类基因调控的分子基础,我们将创建一个影响表达的因果变异及其相关基因组特征的全面目录。我们将重点关注:(i)研究染色质状态的模式以定义eQTL的定位和效应的规则;和(ii)解释功能丧失变体对转录组和个体的效应。具体目标4:我们将建立细胞转录本丰度的定量遗传和基因调控模型。我们的主要工作是:(i)评估蛋白质编码和调控变异之间的上位性/非上位性模式;(ii)重建基因调控网络。这些模型将为eQTL的原因和后果提供生物学见解。

项目成果

期刊论文数量(0)
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Carlos Daniel Bustamante其他文献

Carlos Daniel Bustamante的其他文献

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{{ truncateString('Carlos Daniel Bustamante', 18)}}的其他基金

Biorepository of Human iPSCs for Studying Dilated and Hypertrophic Cardiomyopathy
用于研究扩张型和肥厚型心肌病的人类 iPSC 生物储存库
  • 批准号:
    9031800
  • 财政年份:
    2014
  • 资助金额:
    $ 14.2万
  • 项目类别:
Why We Can't Wait: Conference to Eliminate Health Disparities in Genomics
为什么我们不能等待:消除基因组学健康差异的会议
  • 批准号:
    8785928
  • 财政年份:
    2014
  • 资助金额:
    $ 14.2万
  • 项目类别:
Methods for high-resolution analysis of genetic effects on gene expression
高分辨率分析遗传对基因表达影响的方法
  • 批准号:
    8915307
  • 财政年份:
    2013
  • 资助金额:
    $ 14.2万
  • 项目类别:
Methods for high-resolution analysis of genetic effects on gene expression
高分辨率分析遗传对基因表达影响的方法
  • 批准号:
    9270646
  • 财政年份:
    2013
  • 资助金额:
    $ 14.2万
  • 项目类别:
Methods for high-resolution analysis of genetic effects on gene expression
高分辨率分析遗传对基因表达影响的方法
  • 批准号:
    8585947
  • 财政年份:
    2013
  • 资助金额:
    $ 14.2万
  • 项目类别:
Clinically Relevant Genome Variation Database
临床相关基因组变异数据库
  • 批准号:
    8738706
  • 财政年份:
    2013
  • 资助金额:
    $ 14.2万
  • 项目类别:
Why We Cant Wait: Conference to Eliminate Health Disparities in Genomics
为什么我们不能等待:消除基因组学健康差异的会议
  • 批准号:
    8529747
  • 财政年份:
    2013
  • 资助金额:
    $ 14.2万
  • 项目类别:
Methods for high-resolution analysis of genetic effects on gene expression
高分辨率分析遗传对基因表达影响的方法
  • 批准号:
    8894321
  • 财政年份:
    2013
  • 资助金额:
    $ 14.2万
  • 项目类别:
Methods for high-resolution analysis of genetic effects on gene expression
高分辨率分析遗传对基因表达影响的方法
  • 批准号:
    8711566
  • 财政年份:
    2013
  • 资助金额:
    $ 14.2万
  • 项目类别:
Clinically Relevant Genome Variation Database
临床相关基因组变异数据库
  • 批准号:
    9047616
  • 财政年份:
    2013
  • 资助金额:
    $ 14.2万
  • 项目类别:

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