Functional Analysis of Genome Wide Associations in Colorectal Cancer

描述（由申请人提供）：结直肠癌（CRC）的全基因组关联（GWA）研究已经确定了许多显著相关的命中，这些命中已经在其他人群中得到了强有力的复制。随着使用高密度SNP阵列的更大规模的结直肠癌GWA研究以及对现有GWA研究的荟萃或汇总分析的完成，关联的数量可能在未来几年内显著增长。迄今为止，很少有人强调确定与这些发现相关的因果变异，甚至很少有人致力于了解它们的生物学影响。如果不进行旨在描述通过GWA研究确定的因果变异的功能相关性的研究，就无法完全了解这些方法的生物学含义。本提案的目标是利用多学科方法为CRC GWA研究中产生的hit的功能分析制定综合战略。这不是一个微不足道的挑战，因为迄今为止通过GWA研究发现的大多数关联并不针对外显子中的非同义变异，而是涉及基因附近或基因贫乏区域内的变异，这需要综合分析方法。我们将通过开发这些区域的精细制图信息，寻求从已发表的CRC GWA研究中产生的有效命中。我们将结合最先进的条形码多重深度重测序，并利用来自ChIP-seq， RNA-seq和硅分析的信息来确定基因或调控区域的候选因果变异，这些变异将使用生化分析进行功能测试。我们的目标是确定通过GWA研究确定的因果基因，并描述因果变异的功能意义。通过这样做，我们的目标是充分利用全基因组关联研究的前景，并为通过全基因组关联（GWA）研究确定的关联的生物学含义提供一个全面理解的框架。我们的工作的动机是充分利用GWA研究的生物学意义的障碍越来越大，如果成功，我们的方法应该适用于正在进行的CRC和其他复杂遗传疾病的GWA研究中发现的新关联。

DESCRIPTION (provided by applicant): Genome-wide association (GWA) studies of colorectal cancer (CRC) have led to the identification of a number of significantly associated hits that have been robustly replicated in other populations. The number of associations is likely to grow considerably over the next few years as larger GWA studies of CRC using higher density SNP arrays as well as meta- or pooled analyses of existing GWA studies are completed. To date there has been little emphasis on identifying the causal variant associated with these findings and even less effort directed towards developing an understanding of their biological impact. Without conducting studies designed to characterize the functional relevance of causal variants identified through GWA studies a complete understanding of the biological implications of such approaches will not be achieved. The goal of this proposal is to develop comprehensive strategies for the functional analysis of hits arising from CRC GWA studies using a multidisciplinary approach. This is not an insignificant challenge as most of the associations identified to date through GWA studies do not target non-synonymous variants in exons but instead involve variants that lie near genes or within gene-poor regions that require comprehensive analytical approaches. We will pursue validated hits arising from published CRC GWA studies by developing fine mapping information across these regions. We will incorporate state-of-the-art barcoded multiplex deep re-sequencing, and leverage information from ChIP-seq, RNA-seq and in silico analyses to identify candidate causal variants in genic or regulatory regions that will be functionally tested using biochemical analyses. Our goal is to identify the causal gene(s) identified through GWA studies and to characterize the functional significance of the causal variants. By doing so we aim to fully exploit the promise of GWA studies and provide a framework for a comprehensive understanding of the biological implications of associations identified through genome wide association (GWA) studies. Our work is motivated by the growing roadblock to fully exploiting the biological significance of GWA studies and if successful our approaches should be applicable to novel associations identified in ongoing GWA studies of CRC but also other complex genetic diseases.