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Genomic tools for robust quantitative trait locus discovery and interpretation.

机译:用于强大的数量性状基因座发现和解释的基因组工具。

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摘要

Understanding the mechanisms of gene regulation is fundamental for both evolution and disease research. The rise of genomics has made it possible to collect a huge amount of data for the study of human polymorphisms and gene regulation. With these data it is common to look for quantitative trait loci (QTLs), polymorphisms in the genome with genotypes that are correlated with a regulatory measurement, most commonly mRNA levels. However, to understand the effects of genetic variation we must look beyond QTLs for mRNA levels in a single tissue. Gene regulation may vary across tissues and polymorphisms may take effect at many stages including chromatin, transcription, translation, or degradation levels. However, studying all of these can introduce challenges as these experiments are often expensive and samples hard to acquire. Moreover, to fully understand gene regulation variation we must look for patterns in local sequence context to explain why some polymorphism are QTLs and why others are not. I will present WASP, a set of tools designed to (i) remove experimental artefacts from QTL studies, (ii) account for the many sources of variation in sequencing data, and (iii) maximize power to detect QTLs in small sample sizes. I will then describe how I extended WASP to look for consistent effects across polymorphisms with similar contexts. I will demonstrate how I applied WASP to discover QTLs for four different histone modifications in the human genome. These modifications are important markers of function and chromatin state and were measured in 10 unrelated human lymphoblastoid cell lines. Even with this limited sample size, I was able to identify hundreds of QTLs using WASP. I found that polymorphisms interrupting transcription factor binding sites consistently alter local histone modifications. Finally, I found that variants impacting chromatin at distal regulatory sites frequently also direct changes in chromatin and gene expression at associated promoters.
机译:了解基因调控的机制是进化和疾病研究的基础。基因组学的兴起使得收集大量数据用于人类多态性和基因调控的研究成为可能。利用这些数据,通常需要寻找基因组中的数量性状位点(QTL),即多态性,其基因型与调节测量相关,最常见的是mRNA水平。但是,要了解遗传变异的影响,我们必须超越QTL来检测单个组织中的mRNA水平。基因调节可能在组织之间有所不同,多态性可能在许多阶段生效,包括染色质,转录,翻译或降解水平。但是,对所有这些进行研究可能会带来挑战,因为这些实验通常很昂贵,而且很难获得样品。此外,要完全理解基因调控变异,我们必须在局部序列环境中寻找模式,以解释为什么某些多态性是QTL,而为什么其他不是。我将介绍WASP,这套工具旨在(i)从QTL研究中去除实验假象,(ii)解决测序数据变异的多种来源,以及(iii)最大化检测小样本QTL的能力。然后,我将描述如何扩展WASP以在具有相似上下文的多态性中寻找一致的效果。我将演示如何应用WASP发现人类基因组中四种不同组蛋白修饰的QTL。这些修饰是功能和染色质状态的重要标志,并在10个无关的人淋巴母细胞系中进行了测定。即使样本数量有限,我仍然可以使用WASP识别数百个QTL。我发现中断转录因子结合位点的多态性不断改变局部组蛋白的修饰。最后,我发现影响远端调节位点染色质的变异体也经常指导染色质和相关启动子上基因表达的变化。

著录项

  • 作者

    van de Geijn, Bryce Myers.;

  • 作者单位

    The University of Chicago.;

  • 授予单位 The University of Chicago.;
  • 学科 Genetics.;Bioinformatics.;Statistics.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 110 p.
  • 总页数 110
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 宗教;
  • 关键词

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