Explaining additional genetic variation in complex traits

Robinson, Matthew R., Wray, Naomi R. and Visscher, Peter M. (2014) Explaining additional genetic variation in complex traits. Trends in Genetics, 30 4: 124-132. doi:10.1016/j.tig.2014.02.003

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Author Robinson, Matthew R.
Wray, Naomi R.
Visscher, Peter M.
Title Explaining additional genetic variation in complex traits
Journal name Trends in Genetics   Check publisher's open access policy
ISSN 0168-9525
1362-4555
Publication date 2014-04-01
Year available 2014
Sub-type Critical review of research, literature review, critical commentary
DOI 10.1016/j.tig.2014.02.003
Open Access Status File (Author Post-print)
Volume 30
Issue 4
Start page 124
End page 132
Total pages 9
Place of publication Kidlington, Oxford, United Kingdom
Publisher Elsevier Ltd
Language eng
Subject 1311 Genetics
Abstract Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of complex traits, discovering >6000 variants associated with >500 quantitative traits and common complex diseases in humans. The associations identified so far represent only a fraction of those that influence phenotype, because there are likely to be many variants across the entire frequency spectrum, each of which influences multiple traits, with only a small average contribution to the phenotypic variance. This presents a considerable challenge to further dissection of the remaining unexplained genetic variance within populations, which limits our ability to predict disease risk, identify new drug targets, improve and maintain food sources, and understand natural diversity. This challenge will be met within the current framework through larger sample size, better phenotyping, including recording of nongenetic risk factors, focused study designs, and an integration of multiple sources of phenotypic and genetic information. The current evidence supports the application of quantitative genetic approaches, and we argue that one should retain simpler theories until simplicity can be traded for greater explanatory power.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Critical review of research, literature review, critical commentary
Collections: Queensland Brain Institute Publications
Official 2015 Collection
UQ Diamantina Institute Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 52 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 54 times in Scopus Article | Citations
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