Year: 2012
Type: peer-review
Abstract: A major challenge of biology is understanding the relationship between molecular genetic variation and variation in quantitative traits, including fitness.This relationship determines our ability to predict phenotypes from genotypes and to understand how evolutionary forces shape variation within and between species.Previous efforts to dissect the genotype-phenotype map were based on incomplete genotypic information.Here, we describe the Drosophila melanogaster Genetic Reference Panel (DGRP), a community resource for analysis of population genomics and quantitative traits.The DGRP consists of fully sequenced inbred lines derived from a natural population.Population genomic analyses reveal reduced polymorphism in centromeric autosomal regions and the X chromosome, evidence for positive and negative selection, and rapid evolution of the X chromosome.Many variants in novel genes, most at low frequency, are associated with quantitative traits and explain a large fraction of the phenotypic variance.The DGRP facilitates genotype-phenotype mapping using the power of Drosophila genetics.Understanding how molecular variation maps to phenotypic variation for quantitative traits is central for understanding evolution, animal and plant breeding, and personalized medicine 1,2 .The principles of mapping quantitative trait loci (QTLs) by linkage to, or association with, marker loci are conceptually simple 1,2 .However, we have not yet achieved our goal of explaining genetic variation for quantitative traits in terms of the underlying genes; additive, epistatic, and pleiotropic effects as well as phenotypic plasticity of segregating alleles; and the molecular nature, population frequency and evolutionary Users may view, print, copy, download and text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com
Author: Daven Presgraves
Institution: University of Rochester
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W4230147537