Data from: Connecting thermal performance curve variation to the genotype: a multivariate QTL approach

Thermal performance curves (TPCs) are continuous reaction norms that describe the relationship between organismal performance and temperature and are useful for understanding trade-offs involved in thermal adaptation. While thermal trade-offs such as those between generalists and specialists or between hot- and cold-adapted phenotypes are known to be genetically variable and evolve during thermal adaptation, little is known of the genetic basis to TPCs – specifically, the loci involved and the directionality of their effects across different temperatures. To address this, we took a multivariate approach, mapping QTL for locomotor activity TPCs in the fly, Drosophila serrata using a panel of 76 recombinant inbred lines. The distribution of additive genetic (co)variance in the mapping population was remarkably similar to the distribution of mutational (co)variance for these traits. We detected 11 TPC-QTLs in females and 4 in males. Multivariate QTL effects were closely aligned with the major axes genetic (co)variation between temperatures; most QTL effects corresponded to variation for either overall increases or decreases in activity with a smaller number indicating possible trade-offs between activity at high and low temperatures. QTLs representing changes in curve shape such as the 'generalist-specialist' trade-off, thought key to thermal adaptation, were poorly represented in the data. We discuss these results in light of genetic constraints on thermal adaptation.Locomotor activity for D. serrata RILs across 6 temperatures and the 49 QTL markers.Parental flies originally collected from the field and inbred in the lab. TriKinetic's Drosophilla Activity Monitors (DAMs) used to record fly activity. The 49 markers consist of microsatelites, dCAPS, and EST derived SNPs. See the Readme file for more information.Ril_data.xl