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Publication Detail

Title: GWASeq: targeted re-sequencing follow up to GWAS.

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

Published In BMC Genomics, (2016 Mar 03)

Abstract: 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. 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.We 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.Here 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.

PubMed ID: 26940994 Exiting the NIEHS site

MeSH Terms: Chromosome Mapping; Colonic Neoplasms/genetics; Computational Biology; Genetic Variation; Genome-Wide Association Study*; High-Throughput Nucleotide Sequencing/methods*; Humans; Sequence Analysis, DNA/methods*

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