GWASeq: targeted re-sequencing follow up to GWAS

BMC Genomics

Research Article

Mark A. Jenkins¹  John L. Hopper¹  Aung Ko Win¹  Daniel D. Buchanan²  John Morrison³  David V. Conti³  Barbara K. Fortini³  Paul Marjoram³  Wai Lok Sibon Li³  Christopher K. Edlund³  Duncan C. Thomas³  Graham Casey³  Matthew P. Salomon⁴  Polly A. Newcomb⁵  Steven Gallinger⁶  David Duggan⁷  Loïc Le Marchand⁸ 

[1] Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Melbourne, VIC, Australia;Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Melbourne, VIC, Australia;Oncogenomics Group, Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, Melbourne, VIC, Australia;Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA;Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA;Department of Molecular Oncology, John Wayne Cancer Institute at Providence Saint John’s Health Center, Santa Monica, CA, USA;Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA;Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, ON, Canada;Translational Genomics Research Institute, Phoenix, AZ, USA;University of Hawaii Cancer Center, Honolulu, HI, USA;

关键词: Rare Variant;    Internal Ribosome Entry Site;    Internal Ribosome Entry Site Element;    Sequence Kernel Association Test;    GWAS Signal;   

DOI  :  10.1186/s12864-016-2459-y

 received in 2015-01-22, accepted in 2016-02-09,  发布年份 2016

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY   
© Salomon et al. 2016

【 图 表 】

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