Genetic and Functional Studies of Non-coding Variants in Human Disease
Contributors: Altshuler, David; Mootha, Vamsi; Lander, Eric; McCarroll, Steven; Raychaudhuri, Soumya; Kellis, Manolis
Published: 2012
Language: eng
Description: Genome-wide association studies (GWAS) of common diseases have identified hundreds of genomic regions harboring disease-associated variants. Translating these findings into an improved understanding of human disease requires identifying the causal variants(s) and gene(s) in the implicated regions which, to date, has only been accomplished for a small number of associations. Several factors complicate the identification of mutations playing a causal role in disease. First, GWAS arrays survey only a subset of known variation. The true causal mutation may not have been directly assayed in the GWAS and may be an unknown, novel variant. Moreover, the regions identified by GWAS may contain several genes and many tightly linked variants with equivalent association signals, making it difficult to decipher causal variants from association data alone. Finally, in many cases the variants with strongest association signals map to non-coding regions that we do not yet know how to interpret and where it remains challenging to predict a variants likely phenotypic impact.
Notes: Keywords: fine-mapping, GWAS, high-throughput screening, non-coding.

Thesis Ph.D. Harvard University 2012