期刊
WILEY INTERDISCIPLINARY REVIEWS-DEVELOPMENTAL BIOLOGY
卷 7, 期 1, 页码 -出版社
WILEY
DOI: 10.1002/wdev.289
关键词
-
资金
- NATIONAL INSTITUTE ON AGING [R01AG043490] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE ON ALCOHOL ABUSE AND ALCOHOLISM [R01AA016560] Funding Source: NIH RePORTER
- NIAAA NIH HHS [R01 AA016560] Funding Source: Medline
- NIA NIH HHS [R01 AG043490] Funding Source: Medline
Understanding the genetic architecture (causal molecular variants, their effects, and frequencies) of quantitative traits is important for precision agriculture and medicine and predicting adaptive evolution, but is challenging in most species. The Drosophila melanogaster Genetic Reference Panel (DGRP) is a collection of 205 inbred strains with whole genome sequences derived from a single wild population in Raleigh, NC, USA. The large amount of quantitative genetic variation, lack of population structure, and rapid local decay of linkage disequilibrium in the DGRP and outbred populations derived from DGRP lines present a favorable scenario for performing genome-wide association (GWA) mapping analyses to identify candidate causal genes, polymorphisms, and pathways affecting quantitative traits. The many GWA studies utilizing the DGRP have revealed substantial natural genetic variation for all reported traits, little evidence for variants with large effects but enrichment for variants with low P-values, and a tendency for lower frequency variants to have larger effects than more common variants. The variants detected in the GWA analyses rarely overlap those discovered using mutagenesis, and often are the first functional annotations of computationally predicted genes. Variants implicated in GWA analyses typically have sex-specific and genetic background-specific (epistatic) effects, as well as pleiotropic effects on other quantitative traits. Studies in the DGRP reveal substantial genetic control of environmental variation. Taking account of genetic architecture can greatly improve genomic prediction in the DGRP. These features of the genetic architecture of quantitative traits are likely to apply to other species, including humans. (C) 2017 Wiley Periodicals, Inc.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据