Cross-sex genetic correlations and the evolution of sex-specific local adaptation: Insights from classical trait clines in Drosophila melanogaster.

Natural selection varies widely among locations of a species' range, favoring population divergence and adaptation to local environmental conditions. Selection also differs between females and males, favoring the evolution of sexual dimorphism. Both forms of within-species evolutionary diversification are widely studied, though largely in isolation, and it remains unclear whether environmental variability typically generates similar or distinct patterns of selection on each sex. Studies of sex-specific local adaptation are also challenging because they must account for genetic correlations between female and male traits, which may lead to correlated patterns of trait divergence between sexes, whether or not local selection patterns are aligned or differ between the sexes. We quantified sex-specific divergence in five clinally variable traits in Drosophila melanogaster that individually vary in their magnitude of cross-sex genetic correlation (i.e., from moderate to strongly positive). In all five traits, we observed parallel male and female clines, regardless of the magnitude of their genetic correlation. These patterns imply that parallel spatial divergence of female and male traits is a reflection of sexually concordant directional selection imposed by local environmental conditions. In such contexts, genetic correlations between the sexes promote, rather than constrain, local adaptation to a spatially variable environment.

Genomic Trajectories to Desiccation Resistance: Convergence and Divergence Among Replicate Selected Drosophila Lines.

Adaptation to environmental stress is critical for long-term species persistence. With climate change and other anthropogenic stressors compounding natural selective pressures, understanding the nature of adaptation is as important as ever in evolutionary biology. In particular, the number of alternative molecular trajectories available for an organism to reach the same adaptive phenotype remains poorly understood. Here, we investigate this issue in a set of replicated Drosophila melanogaster lines selected for increased desiccation resistance-a classical physiological trait that has been closely linked to Drosophila species distributions. We used pooled whole-genome sequencing (Pool-Seq) to compare the genetic basis of their selection responses, using a matching set of replicated control lines for characterizing laboratory (lab-)adaptation, as well as the original base population. The ratio of effective population size to census size was high over the 21 generations of the experiment at 0.52-0.88 for all selected and control lines. While selected SNPs in replicates of the same treatment (desiccation-selection or lab-adaptation) tended to change frequency in the same direction, suggesting some commonality in the selection response, candidate SNP and gene lists often differed among replicates. Three of the five desiccation-selection replicates showed significant overlap at the gene and network level. All five replicates showed enrichment for ovary-expressed genes, suggesting maternal effects on the selected trait. Divergence between pairs of replicate lines for desiccation-candidate SNPs was greater than between pairs of control lines. This difference also far exceeded the divergence between pairs of replicate lines for neutral SNPs. Overall, while there was overlap in the direction of allele frequency changes and the network and functional categories affected by desiccation selection, replicates showed unique responses at all levels, likely reflecting hitchhiking effects, and highlighting the challenges in identifying candidate genes from these types of experiments when traits are likely to be polygenic.

Best practice data life cycle approaches for the life sciences.

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a 'life cycle' view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on 'omics' datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

A collection of Australian Drosophila datasets on climate adaptation and species distributions.

The Australian Drosophila Ecology and Evolution Resource (ADEER) collates Australian datasets on drosophilid flies, which are aimed at investigating questions around climate adaptation, species distribution limits and population genetics. Australian drosophilid species are diverse in climatic tolerance, geographic distribution and behaviour. Many species are restricted to the tropics, a few are temperate specialists, and some have broad distributions across climatic regions. Whereas some species show adaptability to climate changes through genetic and plastic changes, other species have limited adaptive capacity. This knowledge has been used to identify traits and genetic polymorphisms involved in climate change adaptation and build predictive models of responses to climate change. ADEER brings together 103 datasets from 39 studies published between 1982-2013 in a single online resource. All datasets can be downloaded freely in full, along with maps and other visualisations. These historical datasets are preserved for future studies, which will be especially useful for assessing climate-related changes over time.

Genetic isolation by environment or distance: which pattern of gene flow is most common?

Gene flow among populations can enhance local adaptation if it introduces new genetic variants available for selection, but strong gene flow can also stall adaptation by swamping locally beneficial genes. These outcomes can depend on population size, genetic variation, and the environmental context. Gene flow patterns may align with geographic distance (IBD--isolation by distance), whereby immigration rates are inversely proportional to the distance between populations. Alternatively gene flow may follow patterns of isolation by environment (IBE), whereby gene flow rates are higher among similar environments. Finally, gene flow may be highest among dissimilar environments (counter-gradient gene flow), the classic "gene-swamping" scenario. Here we survey relevant studies to determine the prevalence of each pattern across environmental gradients. Of 70 studies, we found evidence of IBD in 20.0%, IBE in 37.1%, and both patterns in 37.1%. In addition, 10.0% of studies exhibited counter-gradient gene flow. In total, 74.3% showed significant IBE patterns. This predominant IBE pattern of gene flow may have arisen directly through natural selection or reflect other adaptive and nonadaptive processes leading to nonrandom gene flow. It also precludes gene swamping as a widespread phenomenon. Implications for evolutionary processes and management under rapidly changing environments (e.g., climate change) are discussed.