Gene expression clines reveal local adaptation and associated trade-offs at a continental scale

Abstract

Local adaptation, where fitness in one environment comes at a cost in another, should lead to spatial variation in trade-offs between life history traits and may be critical for population persistence. Recent studies have sought genomic signals of local adaptation, but often have been limited to laboratory populations representing two environmentally different locations of a species’ distribution. We measured gene expression, as a proxy for fitness, in males of Drosophila subobscura, occupying a 20° latitudinal and 11 °C thermal range. Uniquely, we sampled six populations and studied both common garden and semi-natural responses to identify signals of local adaptation. We found contrasting patterns of investment: transcripts with expression positively correlated to latitude were enriched for metabolic processes, expressed across all tissues whereas negatively correlated transcripts were enriched for reproductive processes, expressed primarily in testes. When using only the end populations, to compare our results to previous studies, we found that locally adaptive patterns were obscured. While phenotypic trade-offs between metabolic and reproductive functions across widespread species are well-known, our results identify underlying genetic and tissue responses at a continental scale that may be responsible for this. This may contribute to understanding population persistence under environmental change.

A simple genetic basis of adaptation to a novel thermal environment results in complex metabolic rewiring in Drosophila

“…Reanalyzing clinal population genetic data (Sedghifar, Saelao, Begun 2016), SNF4Aγ is among the 603 most differentiated genes shared by North American and Australian D. simulans populations. Gene expression of SNF4Aγ is clinal in European D. subobscura populations, with southern populations having lower expression levels (Porcelli et al 2016), which parallels the response observed in our experimental evolution populations. Because the selected haplotype may be partially maintained in other populations, we tested the diagnostic SNPs for clinal variation.…”

“…Temperature is a major factor modulating the expression of numerous genes in ectotherms and is particularly well studied in Drosophila (Zhao et al 2015; Chen, Nolte, Schlötterer 2015; Porcelli et al 2016). Our experimental populations, which evolved in a novel hot thermal environment displayed highly significant differences in gene expression involving many genes of well-defined pathways.…”

“…Temperature is a major abiotic factor known to affect a broad range of phenotypes and provides a good study system to investigate the genetic architecture of phenotypic evolution, in particular of quantitative traits. Most insight into thermal adaptation comes from contrasting natural populations that have evolved in different thermal habitats (Fabian et al 2012; Bergland et al 2014; Zhao et al 2015; Machado et al 2016; Sedghifar, Saelao, Begun 2016; Porcelli et al 2016). Apart from complications intrinsic to natural populations, such as confounding signals of demography (Bergland et al 2016) and the complexity of natural environments, the underlying evolutionary time scales are too long to be informative about rapid adaptation required to counter the current rate of climate change (Franks, Hoffmann 2012).…”

Local adaptation of reproductive performance during thermal stress

“…We have previously found, across six D. subobscura populations from a 20°latitudinal cline in Europe (of which the Valencia and Uppsala populations represent the southern-and northernmost population, respectively), a gradient in gene expression in which adult males from southern populations have higher expression of spermatogenesis genes than males from northern populations, under benign (18°C) conditions (Porcelli et al, 2016). Given that females are monandrous, sperm competition cannot explain increased investment in spermatogenesis in lower latitude populations.…”

Dynamic turnover of centromeres drives karyotype evolution in Drosophila

“…To characterize gene expression in D. athabasca we analyzed EB RNA--seq data from whole larva and pooled larval heads (above , Table S1). For D. subobscura we analyzed RNA--seq data generated from two pools of whole individuals (Uppsalapool and Valenciapool; Porcelli et al 2016). For each species, all reads were aligned to their respective reference genomes using HiSat2 (Kim et al 2015) and StringTie (Pertea et al 2015) was used to estimate gene expression (FPKM).…”