Temperature-dependent gene regulatory divergence underlies local adaptation with gene flow in the Atlantic silverside.

Gene regulatory divergence is thought to play an important role in adaptation, yet its extent and underlying mechanisms remain largely elusive for local adaptation with gene flow. Local adaptation is widespread in marine species despite generally high connectivity and is often associated with tightly linked genomic architectures, such as chromosomal inversions. To investigate gene regulatory evolution under gene flow and the role of inversions associated with local adaptation to a steep thermal gradient, we generated RNA-seq data from Atlantic silversides (Menidia menidia) from two locally adapted populations and their F1 hybrids, reared under two temperatures. We found substantial divergence in gene expression and thermal plasticity between populations, with up to 31% of genes being differentially expressed. Reduced thermal plasticity, temperature-dependent gene misexpression, and the disruption of coexpression networks in hybrids point toward a role of regulatory incompatibilities in local adaptation, particularly under colder temperatures. Chromosomal inversions show an accumulation of regulatory incompatibilities but are not consistently enriched for differentially expressed genes. Together, these results suggest that gene regulation can diverge substantially among populations despite gene flow, partly due to the accumulation of temperature-dependent regulatory incompatibilities within inversions.

Comparative linkage mapping uncovers recombination suppression across massive chromosomal inversions associated with local adaptation in Atlantic silversides.

The role of recombination in genome evolution has long been studied in theory, but until recently empirical investigations had been limited to a small number of model species. Here, we compare the recombination landscape and genome collinearity between two populations of the Atlantic silverside (Menidia menidia), a small fish distributed across the steep latitudinal climate gradient of the North American Atlantic coast. We constructed separate linkage maps for locally adapted populations from New York and Georgia and their interpopulation laboratory cross. First, we used one of the linkage maps to improve the current silverside genome assembly by anchoring three large unplaced scaffolds to two chromosomes. Second, we estimated sex-specific recombination rates, finding 2.3-fold higher recombination rates in females than males-one of the most extreme examples of heterochiasmy in a fish. While recombination occurs relatively evenly across female chromosomes, it is restricted to only the terminal ends of male chromosomes. Furthermore, comparisons of female linkage maps revealed suppressed recombination along several massive chromosomal inversions spanning nearly 16% of the genome. These inversions segregate between locally adapted populations and coincide near perfectly with blocks of highly elevated genomic differentiation between wild populations. Finally, we discerned significantly higher recombination rates across chromosomes in the northern population compared to the southern. In addition to providing valuable resources for ongoing evolutionary and comparative genomic studies, our findings represent a striking example of structural variation that impacts recombination between adaptively divergent populations, providing empirical support for theorized genomic mechanisms facilitating adaptation despite gene flow.

The Effects of Quantitative Trait Architecture on Detection Power in Short-Term Artificial Selection Experiments.

Evolve and resequence (E&R) experiments, in which artificial selection is imposed on organisms in a controlled environment, are becoming an increasingly accessible tool for studying the genetic basis of adaptation. Previous work has assessed how different experimental design parameters affect the power to detect the quantitative trait loci (QTL) that underlie adaptive responses in such experiments, but so far there has been little exploration of how this power varies with the genetic architecture of the evolving traits. In this study, we use forward simulation to build a more realistic model of an E&R experiment in which a quantitative polygenic trait experiences a short, but strong, episode of truncation selection. We study the expected power for QTL detection in such an experiment and how this power is influenced by different aspects of trait architecture, including the number of QTL affecting the trait, their starting frequencies, effect sizes, clustering along a chromosome, dominance, and epistasis patterns. We show that all of these parameters can affect allele frequency dynamics at the QTL and linked loci in complex and often unintuitive ways, and thus influence our power to detect them. One consequence of this is that existing detection methods based on models of independent selective sweeps at individual QTL often have lower detection power than a simple measurement of allele frequency differences before and after selection. Our findings highlight the importance of taking trait architecture into account when designing and interpreting studies of molecular adaptation with temporal data. We provide a customizable modeling framework that will enable researchers to easily simulate E&R experiments with different trait architectures and parameters tuned to their specific study system, allowing for assessment of expected detection power and optimization of experimental design.

Novel signals of adaptive genetic variation in northwestern Atlantic cod revealed by whole-genome sequencing.

Selection can create complex patterns of adaptive differentiation among populations in the wild that may be relevant to management. Atlantic cod in the Northwest Atlantic are at a fraction of their historical abundance and a lack of recovery within the Gulf of Maine has created concern regarding the misalignment of fisheries management structures with biological population structure. To address this and investigate genome-wide patterns of variation, we used low-coverage sequencing to perform a region-wide, whole-genome analysis of fine-scale population structure. We sequenced 306 individuals from 20 sampling locations in U.S. and Canadian waters, including the major spawning aggregations in the Gulf of Maine in addition to spawning aggregations from Georges Bank, southern New England, the eastern Scotian Shelf, and St. Pierre Bank. With genotype likelihoods estimated at almost 11 million loci, we found large differences in haplotype frequencies of previously described chromosomal inversions between Canadian and U.S. sampling locations and also among U.S. sampling locations. Our whole-genome resolution also revealed novel outlier peaks, some of which showed significant genetic differentiation among sampling locations. Comparisons between allochronic winter- and spring-spawning populations revealed highly elevated relative (FST ) and absolute (dxy ) genetic differentiation near genes involved in reproduction, particularly genes associated with the brain-pituitary-gonadal axis, which likely control timing of spawning, contributing to prezygotic isolation. We also found genetic differentiation associated with heat shock proteins and other genes of functional relevance, with complex patterns that may point to multifaceted selection pressures and local adaptation among spawning populations. We provide a high-resolution picture of U.S. Atlantic cod population structure, revealing greater complexity than is currently recognized in management. Our genome-scan approach likely underestimates the full suite of adaptive differentiation among sampling locations. Nevertheless, it should inform the revision of stock boundaries to preserve adaptive genetic diversity and evolutionary potential of cod populations.

Contrasting genomic shifts underlie parallel phenotypic evolution in response to fishing.

Humans cause widespread evolutionary change in nature, but we still know little about the genomic basis of rapid adaptation in the Anthropocene. We tracked genomic changes across all protein-coding genes in experimental fish populations that evolved pronounced shifts in growth rates due to size-selective harvest over only four generations. Comparisons of replicate lines show parallel allele frequency shifts that recapitulate responses to size-selection gradients in the wild across hundreds of unlinked variants concentrated in growth-related genes. However, a supercluster of genes also rose rapidly in frequency and dominated the evolutionary dynamic in one replicate line but not in others. Parallel phenotypic changes thus masked highly divergent genomic responses to selection, illustrating how contingent rapid adaptation can be in the face of strong human-induced selection.

Range-wide genomic data synthesis reveals transatlantic vicariance and secondary contact in Atlantic cod.

Recent advances in genetic and genomic analysis have greatly improved our understanding of spatial population structure in marine species. However, studies addressing phylogeographic patterns at oceanic spatial scales remain rare. In Atlantic cod (Gadus morhua), existing range-wide examinations suggest significant transatlantic divergence, although the fine-scale contemporary distribution of populations and potential for secondary contact are largely unresolved. Here, we explore transatlantic phylogeography in Atlantic cod using a data-synthesis approach, integrating multiple genome-wide single-nucleotide polymorphism (SNP) datasets representative of different regions to create a single range-wide dataset containing 1,494 individuals from 54 locations and genotyped at 796 common loci. Our analysis highlights significant transatlantic divergence and supports the hypothesis of westward post-glacial colonization of Greenland from the East Atlantic. Accordingly, our analysis suggests the presence of transatlantic secondary contact off eastern North America and supports existing perspectives on the phylogeographic history of Atlantic cod with an unprecedented combination of genetic and geographic resolution. Moreover, we demonstrate the utility of integrating distinct SNP databases of high comparability.

What genomic data can reveal about eco-evolutionary dynamics.

Recognition that evolution operates on the same timescale as ecological processes has motivated growing interest in eco-evolutionary dynamics. Nonetheless, generating sufficient data to test predictions about eco-evolutionary dynamics has proved challenging, particularly in natural contexts. Here we argue that genomic data can be integrated into the study of eco-evolutionary dynamics in ways that deepen our understanding of the interplay between ecology and evolution. Specifically, we outline five major questions in the study of eco-evolutionary dynamics for which genomic data may provide answers. Although genomic data alone will not be sufficient to resolve these challenges, integrating genomic data can provide a more mechanistic understanding of the causes of phenotypic change, help elucidate the mechanisms driving eco-evolutionary dynamics, and lead to more accurate evolutionary predictions of eco-evolutionary dynamics in nature.

Harnessing the Power of Genomics to Secure the Future of Seafood.

Best use of scientific knowledge is required to maintain the fundamental role of seafood in human nutrition. While it is acknowledged that genomic-based methods allow the collection of powerful data, their value to inform fisheries management, aquaculture, and biosecurity applications remains underestimated. We review genomic applications of relevance to the sustainable management of seafood resources, illustrate the benefits of, and identify barriers to their integration. We conclude that the value of genomic information towards securing the future of seafood does not need to be further demonstrated. Instead, we need immediate efforts to remove structural roadblocks and focus on ways that support integration of genomic-informed methods into management and production practices. We propose solutions to pave the way forward.

Evolutionary impact assessment: accounting for evolutionary consequences of fishing in an ecosystem approach to fisheries management.

Managing fisheries resources to maintain healthy ecosystems is one of the main goals of the ecosystem approach to fisheries (EAF). While a number of international treaties call for the implementation of EAF, there are still gaps in the underlying methodology. One aspect that has received substantial scientific attention recently is fisheries-induced evolution (FIE). Increasing evidence indicates that intensive fishing has the potential to exert strong directional selection on life-history traits, behaviour, physiology, and morphology of exploited fish. Of particular concern is that reversing evolutionary responses to fishing can be much more difficult than reversing demographic or phenotypically plastic responses. Furthermore, like climate change, multiple agents cause FIE, with effects accumulating over time. Consequently, FIE may alter the utility derived from fish stocks, which in turn can modify the monetary value living aquatic resources provide to society. Quantifying and predicting the evolutionary effects of fishing is therefore important for both ecological and economic reasons. An important reason this is not happening is the lack of an appropriate assessment framework. We therefore describe the evolutionary impact assessment (EvoIA) as a structured approach for assessing the evolutionary consequences of fishing and evaluating the predicted evolutionary outcomes of alternative management options. EvoIA can contribute to EAF by clarifying how evolution may alter stock properties and ecological relations, support the precautionary approach to fisheries management by addressing a previously overlooked source of uncertainty and risk, and thus contribute to sustainable fisheries.

Microevolution in time and space: SNP analysis of historical DNA reveals dynamic signatures of selection in Atlantic cod.

Little is known about how quickly natural populations adapt to changes in their environment and how temporal and spatial variation in selection pressures interact to shape patterns of genetic diversity. We here address these issues with a series of genome scans in four overfished populations of Atlantic cod (Gadus morhua) studied over an 80-year period. Screening of >1000 gene-associated single-nucleotide polymorphisms (SNPs) identified 77 loci that showed highly elevated levels of differentiation, likely as an effect of directional selection, in either time, space or both. Exploratory analysis suggested that temporal allele frequency shifts at certain loci may correlate with local temperature variation and with life history changes suggested to be fisheries induced. Interestingly, however, largely nonoverlapping sets of loci were temporal outliers in the different populations and outliers from the 1928 to 1960 period showed almost complete stability during later decades. The contrasting microevolutionary trajectories among populations resulted in sequential shifts in spatial outliers, with no locus maintaining elevated spatial differentiation throughout the study period. Simulations of migration coupled with observations of temporally stable spatial structure at neutral loci suggest that population replacement or gene flow alone could not explain all the observed allele frequency variation. Thus, the genetic changes are likely to at least partly be driven by highly dynamic temporally and spatially varying selection. These findings have important implications for our understanding of local adaptation and evolutionary potential in high gene flow organisms and underscore the need to carefully consider all dimensions of biocomplexity for evolutionarily sustainable management.

A genomic island linked to ecotype divergence in Atlantic cod.

The genomic architecture underlying ecological divergence and ecological speciation with gene flow is still largely unknown for most organisms. One central question is whether divergence is genome-wide or localized in 'genomic mosaics' during early stages when gene flow is still pronounced. Empirical work has so far been limited, and the relative impacts of gene flow and natural selection on genomic patterns have not been fully explored. Here, we use ecotypes of Atlantic cod to investigate genomic patterns of diversity and population differentiation in a natural system characterized by high gene flow and large effective population sizes, properties which theoretically could restrict divergence in local genomic regions. We identify a genomic region of strong population differentiation, extending over approximately 20 cM, between pairs of migratory and stationary ecotypes examined at two different localities. Furthermore, the region is characterized by markedly reduced levels of genetic diversity in migratory ecotype samples. The results highlight the genomic region, or 'genomic island', as potentially associated with ecological divergence and suggest the involvement of a selective sweep. Finally, we also confirm earlier findings of localized genomic differentiation in three other linkage groups associated with divergence among eastern Atlantic populations. Thus, although the underlying mechanisms are still unknown, the results suggest that 'genomic mosaics' of differentiation may even be found under high levels of gene flow and that marine fishes may provide insightful model systems for studying and identifying initial targets of selection during ecological divergence.