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Introduced and invasive species make excellent natural experiments for investigating rapid evolution. Here, we describe the effects of genetic drift and rapid genetic adaptation in pink salmon (Oncorhynchus gorbuscha) that were accidentally introduced to the Great Lakes via a single introduction event 31 generations ago. Using whole‐genome resequencing for 134 fish spanning five sample groups across the native and introduced range, we estimate that the source population's effective population size was 146,886 at the time of introduction, whereas the founding population's effective population size was just 72—a 2040‐fold decrease. As expected with a severe founder event, we show reductions in genome‐wide measures of genetic diversity, specifically a 37.7% reduction in the number of SNPs and an 8.2% reduction in observed heterozygosity. Despite this decline in genetic diversity, we provide evidence for putative selection at 47 loci across multiple chromosomes in the introduced populations, including missense variants in genes associated with circadian rhythm, immunological response and maturation, which match expected or known phenotypic changes in the Great Lakes. For one of these genes, we use a species‐specific agent‐based model to rule out genetic drift and conclude our results support a strong response to selection occurring in a period gene (per2) that plays a predominant role in determining an organism's daily clock, matching large day length differences experienced by introduced salmon during important phenological periods. Together, these results inform how populations might evolve rapidly to new environments, even with a small pool of standing genetic variation.

 

From genes to communities, understanding how diversity is maintained remains a fundamental question in biology. One challenging to identify, yet potentially ubiquitous, mechanism for the maintenance of diversity is negative frequency dependent selection (NFDS), which occurs when entities (e.g., genotypes, life history strategies, species) experience a per capita reduction in fitness with increases in relative abundance. Because NFDS allows rare entities to increase in frequency while preventing abundant entities from excluding others, we posit that negative frequency dependent selection plays a central role in the maintenance of diversity. In this review, we relate NFDS to coexistence, identify mechanisms of NFDS (e.g., mutualism, predation, parasitism), review strategies for identifying NFDS, and distinguish NFDS from other mechanisms of coexistence (e.g., storage effects, fluctuating selection). We also emphasize that NFDS is a key place where ecology and evolution intersect. Specifically, there are many examples of frequency dependent processes in ecology, but fewer cases that link this process to selection. Similarly, there are many examples of selection in evolution, but fewer cases that link changes in trait values to negative frequency dependence. Bridging these two well‐developed fields of ecology and evolution will allow for mechanistic insights into the maintenance of diversity at multiple levels.

 

Genomic data are ubiquitous across disciplines, from agriculture to biodiversity, ecology, evolution and human health. However, these datasets often contain noise or errors and are missing information that can affect the accuracy and reliability of subsequent computational analyses and conclusions. A key step in genomic data analysis is filtering — removing sequencing bases, reads, genetic variants and/or individuals from a dataset — to improve data quality for downstream analyses. Researchers are confronted with a multitude of choices when filtering genomic data; they must choose which filters to apply and select appropriate thresholds. To help usher in the next generation of genomic data filtering, we review and suggest best practices to improve the implementation, reproducibility and reporting standards for filter types and thresholds commonly applied to genomic datasets. We focus mainly on filters for minor allele frequency, missing data per individual or per locus, linkage disequilibrium and Hardy–Weinberg deviations. Using simulated and empirical datasets, we illustrate the large effects of different filtering thresholds on common population genetics statistics, such as Tajima’s D value, population differentiation (FST), nucleotide diversity (π) and effective population size (Ne). 

Environmentally covarying local adaptation is a form of cryptic local adaptation in which the covariance of the genetic and environmental effects on a phenotype obscures the divergence between locally adapted genotypes. Here, we systematically document the magnitude and drivers of the genetic effect (V G ) for two forms of environmentally covarying local adaptation: counter- and cogradient variation. Using a hierarchical Bayesian meta-analysis, we calculated the overall effect size of V G as 1.05 and 2.13 for populations exhibiting countergradient or cogradient variation, respectively. These results indicate that the genetic contribution to phenotypic variation represents a 1.05 to 2.13 s.d. change in trait value between the most disparate populations depending on if populations are expressing counter- or cogradient variation. We also found that while there was substantial variance among abiotic and biotic covariates, the covariates with the largest mean effects were temperature (2.41) and gamete size (2.81). Our results demonstrate the pervasiveness and large genetic effects underlying environmentally covarying local adaptation in wild populations and highlight the importance of accounting for these effects in future studies. 

Abstract Freshwater pollution is a major global concern. Common methods for determining the effects of contaminants on freshwater organisms involve short-term laboratory experiments with otherwise healthy organisms. However, in natural systems, organisms are commonly exposed to parasites, which could alter their ability to survive exposure to aquatic contamination. We used a freshwater crustacean (Daphnia dentifera) to quantify the effects of parasite exposure on mortality from two common freshwater contaminants (elevated salinity [NaCl] and carbaryl). In our salinity trial, both parasite exposure and elevated salinity reduced survival in an additive manner. In our carbaryl trial, exposure to carbaryl reduced survival and we found a less-than-additive (i.e. antagonistic) interaction between carbaryl and the parasite; the parasite only reduced survival in the control (no carbaryl) treatments. Our results demonstrate that parasites and contaminants can jointly affect mortality in aquatic organisms in an additive or less-than-additive manner.