Systems genetics of complex traits in Drosophila melanogaster

Abstract

SUMMARY Determining the genetic architecture of complex traits is challenging because phenotypic variation arises from interactions between multiple, environmentally sensitive alleles. We quantified genome-wide transcript abundance and phenotypes for six ecologically relevant traits in D. melanogaster wild-derived inbred lines. We observed 10,096 genetically variable transcripts and high heritabilities for all organismal phenotypes. The transcriptome is highly genetically inter-correlated, forming 241 transcriptional modules. Modules are enriched for transcripts in common pathways, gene ontology categories, tissue-specific expression, and transcription factor binding sites. The high transcriptional connectivity allows us to infer genetic networks and the function of predicted genes based on annotations of other genes in the network. Regressions of organismal phenotypes on transcript abundance implicate several hundred candidate genes that form modules of biologically meaningful correlated transcripts affecting each phenotype. Overlapping transcripts in modules associated with different traits provides insight into the molecular basis of pleiotropy between complex traits.

Effects of larval crowding on quantitative variation for development time and viability in Drosophila melanogaster

“…The DGRP strains are characterized by high genetic (Mackay et al., 2012; Massouras et al., 2012) and phenotypic variation (Ayroles et al., 2009; Durham, Magwire, Stone, & Leips, 2014; Ellis et al., 2014; Harbison, McCoy, & Mackay, 2013; Mackay et al., 2012; Unckless, Rottschaefer, & Lazzaro, 2015). Fly stocks were ordered from the Bloomington Stock Center and are kept in standard molasses/soy‐corn flour/agar media‐containing vials.…”

Scoring the collective effects of SNPs: association of minor alleles with complex traits in model organisms

“…Great variations in MAC (~0.2 to ~0.7) were observed for C. elegans RILs from either the Kruglyak or the Kammenga laboratory ( Figure 1A and B) [19,20], a yeast segregants panel analogous to a RIL panel in animals ( Figure 1C) [21,22], and the BXD mouse RIL panel ( Figure 1F) [24,25]. Relative to these RILs, D. melanogaster inbred panel derived from the wild showed lower MAC and smaller variation range ( Figure 1D) [23]. RILs that were only partially inbred such as the collaborative cross (CC) G2F7 mouse panel that has been inbred for only seven generations also showed small variation range in MAC ( Figure 1E) [26].…”

“…The deleterious effect of higher MAC on reproductive traits was confirmed in three other RIL panels in mouse and rat, BXD, CC (G2F6), and BXHHXB (Table 4). In addition, higher MAC was linked with lower life span in C. elegans and mouse (Table 4), less startle response (the ability to respond rapidly to harmful changes in the environment) in D. melanogaster (for males, Spearman r=0.23, P=0.004) [23], and more chill coma response in D. melanogaster (for females, Spearman r=0.22, P=0.007) [23].…”

What can whole genome expression data tell us about the ecology and evolution of personality?

“…single nucleotide polymorphisms; SNPs) in the gene's regulatory or control region, or both. Whole genome expression data, combined with other approaches such as linkage mapping or association studies, help us to identify the specific genetic variants that influence variation in gene expression and ultimately in the organismic phenotype such as behaviour (Schadt et al 2003;Emilsson et al 2008;Ayroles et al 2009), reviewed in Gilad et al (2008). The advantage of measuring gene expression over behaviour is that the genes that are associated with variation in behaviour gives us direct information about the molecular mechanisms, networks and pathways involved.…”