GWASeq: targeted re-sequencing follow up to GWAS.

Matthew P Salomon,Daniel D Buchanan,Mark A Jenkins,Loïc Le Marchand,Christopher K Edlund,John Morrison,Aung Ko Win,Wai Lok Sibon Li,Graham Casey,David V Conti,John L Hopper,Paul Marjoram,David Duggan,Barbara K Fortini,Steven Gallinger,Duncan C Thomas,Polly A Newcomb

doi:10.1186/s12864-016-2459-y

Abstract

BackgroundFor the last decade the conceptual framework of the Genome-Wide Association Study (GWAS) has dominated the investigation of human disease and other complex traits. While GWAS have been successful in identifying a large number of variants associated with various phenotypes, the overall amount of heritability explained by these variants remains small. This raises the question of how best to follow up on a GWAS, localize causal variants accounting for GWAS hits, and as a consequence explain more of the so-called “missing” heritability. Advances in high throughput sequencing technologies now allow for the efficient and cost-effective collection of vast amounts of fine-scale genomic data to complement GWAS.ResultsWe investigate these issues using a colon cancer dataset. After QC, our data consisted of 1993 cases, 899 controls. Using marginal tests of associations, we identify 10 variants distributed among six targeted regions that are significantly associated with colorectal cancer, with eight of the variants being novel to this study. Additionally, we perform so-called ‘SNP-set’ tests of association and identify two sets of variants that implicate both common and rare variants in the etiology of colorectal cancer.ConclusionsHere we present a large-scale targeted re-sequencing resource focusing on genomic regions implicated in colorectal cancer susceptibility previously identified in several GWAS, which aims to 1) provide fine-scale targeted sequencing data for fine-mapping and 2) provide data resources to address methodological questions regarding the design of sequencing-based follow-up studies to GWAS. Additionally, we show that this strategy successfully identifies novel variants associated with colorectal cancer susceptibility and can implicate both common and rare variants.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2459-y) contains supplementary material, which is available to authorized users.

Highlights

For the last decade the conceptual framework of the Genome-Wide Association Study (GWAS) has dominated the investigation of human disease and other complex traits
We live in the era of the Genome-wide Association Study [GWAS]
In this paper we focus on the first of those hypotheses: the discovery of nearby, and possibly rare variants that drive GWAS signals

Summary

Introduction

For the last decade the conceptual framework of the Genome-Wide Association Study (GWAS) has dominated the investigation of human disease and other complex traits. In the context of human disease, the design of such studies and, in particular, the so-called SNP-chip technology that underpins them, has aimed to exploit the common disease, common variant hypothesis (e.g.), [1, 2]. This assumes that common diseases will frequently be associated with common (>1–5 % frequency) variants. There is a long history of GWAS studies, and large numbers of variants have been found to be associated with disease [3] Such studies do not come without financial cost, and there has been a lively discussions regarding whether such a track record should be regarded as a success or failure [4, 5]. Our purpose here is not to add to that discussion, but rather to focus on what will often be a frequent ‘ step’ in such studies

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Discussion

Conclusion