Consequences of mutation accumulation for growth performance are more likely to be resource-dependent at higher temperatures

Conditionally Deleterious Mutation Load Accumulates in Genomic Islands of Local Adaptation but Can Be Purged with Sufficient Genotypic Redundancy

AbstractLocal adaptation frequently evolves in patches or environments that are connected via migration. In these cases, genomic regions that are linked to a locally adapted locus experience reduced effective migration rates. Via individual-based simulations of a two-patch system, we show that this reduced effective migration results in the accumulation of conditionally deleterious mutations, but not universally deleterious mutations, adjacent to adaptive loci. When there is redundancy in the genetic basis of local adaptation (i.e., genotypic redundancy), turnover of locally adapted polymorphisms allows conditionally deleterious mutation load to be purged. The amount of mutational load that accumulates adjacent to locally adapted loci is dependent on redundancy, recombination rate, migration rate, population size, strength of selection, and the phenotypic effect size of adaptive alleles. Our results highlight the need to be cautious when interpreting patterns of local adaptation at the level of phenotype or fitness, as the genetic basis of local adaptation can be transient, and evolution may confer a degree of maladaptation to nonlocal environments.

The effects of mutations on gene expression and alternative splicing

Understanding the relationship between mutations and their genomic and phenotypic consequences has been a longstanding goal of evolutionary biology. However, few studies have investigated the impact of mutations on gene expression and alternative splicing on the genome-wide scale. In this study, we aim to bridge this knowledge gap by utilizing whole-genome sequencing data and RNA sequencing data from 16 obligately parthenogenetic Daphnia mutant lines to investigate the effects of ethyl methanesulfonate-induced mutations on gene expression and alternative splicing. Using rigorous analyses of mutations, expression changes and alternative splicing, we show that trans-effects are the major contributor to the variance in gene expression and alternative splicing between the wild-type and mutant lines, whereas cis mutations only affected a limited number of genes and do not always alter gene expression. Moreover, we show that there is a significant association between differentially expressed genes and exonic mutations, indicating that exonic mutations are an important driver of altered gene expression.

Genome-wide selection signatures reveal widespread synergistic effects of two different stressors in Drosophila melanogaster

Experimental evolution combined with whole-genome sequencing (evolve and resequence (E&R)) is a powerful approach to study the adaptive architecture of selected traits. Nevertheless, so far the focus has been on the selective response triggered by a single stressor. Building on the highly parallel selection response of founder populations with reduced variation, we evaluated how the presence of a second stressor affects the genomic selection response. After 20 generations of adaptation to laboratory conditions at either 18°C or 29°C, strong genome-wide selection signatures were observed. Only 38% of the selection signatures can be attributed to laboratory adaptation (no difference between temperature regimes). The remaining selection responses are either caused by temperature-specific effects, or reflect the joint effects of temperature and laboratory adaptation (same direction, but the magnitude differs between temperatures). The allele frequency changes resulting from the combined effects of temperature and laboratory adaptation were more extreme in the hot environment for 83% of the affected genomic regions-indicating widespread synergistic effects of the two stressors. We conclude that E&R with reduced genetic variation is a powerful approach to study genome-wide fitness consequences driven by the combined effects of multiple environmental factors.