Interpreting noncoding genetic variation in complex traits and human disease.

Nat Biotechnol
Authors
Keywords
Abstract

Association studies provide genome-wide information about the genetic basis of complex disease, but medical research has focused primarily on protein-coding variants, owing to the difficulty of interpreting noncoding mutations. This picture has changed with advances in the systematic annotation of functional noncoding elements. Evolutionary conservation, functional genomics, chromatin state, sequence motifs and molecular quantitative trait loci all provide complementary information about the function of noncoding sequences. These functional maps can help with prioritizing variants on risk haplotypes, filtering mutations encountered in the clinic and performing systems-level analyses to reveal processes underlying disease associations. Advances in predictive modeling can enable data-set integration to reveal pathways shared across loci and alleles, and richer regulatory models can guide the search for epistatic interactions. Lastly, new massively parallel reporter experiments can systematically validate regulatory predictions. Ultimately, advances in regulatory and systems genomics can help unleash the value of whole-genome sequencing for personalized genomic risk assessment, diagnosis and treatment.

Year of Publication
2012
Journal
Nat Biotechnol
Volume
30
Issue
11
Pages
1095-106
Date Published
2012 Nov
ISSN
1546-1696
URL
DOI
10.1038/nbt.2422
PubMed ID
23138309
PubMed Central ID
PMC3703467
Links
Grant list
R01 HG004037 / HG / NHGRI NIH HHS / United States
RC1 HG005334 / HG / NHGRI NIH HHS / United States
R01HG004037 / HG / NHGRI NIH HHS / United States
RC1HG005334 / HG / NHGRI NIH HHS / United States