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Whole-genome resequencing (WGR) is a powerful method for addressing fundamental evolutionary biology questions that have not been fully resolved using traditional methods. WGR includes four approaches: the sequencing of individuals to a high depth of coverage with either unresolved or resolved haplotypes, the sequencing of population genomes to a high depth by mixing equimolar amounts of unlabelled-individual DNA (Pool-seq) and the sequencing of multiple individuals from a population to a low depth (lcWGR). These techniques require the availability of a reference genome. This, along with the still high cost of shotgun sequencing and the large demand for computing resources and storage, has limited their implementation in nonmodel species with scarce genomic resources and in fields such as conservation biology. Our goal here is to describe the various WGR methods, their pros and cons and potential applications in conservation biology. WGR offers an unprecedented marker density and surveys a wide diversity of genetic variations not limited to single nucleotide polymorphisms (e.g., structural variants and mutations in regulatory elements), increasing their power for the detection of signatures of selection and local adaptation as well as for the identification of the genetic basis of phenotypic traits and diseases. Currently, though, no single WGR approach fulfils all requirements of conservation genetics, and each method has its own limitations and sources of potential bias. We discuss proposed ways to minimize such biases. We envision a not distant future where the analysis of whole genomes becomes a routine task in many nonmodel species and fields including conservation biology., (© 2017 John Wiley & Sons Ltd.)

Understanding how marine organisms adapt to local environments is crucial for predicting how populations will respond to global climate change. The genomic basis, environmental factors and evolutionary processes involved in local adaptation are however not well understood. Here we use Atlantic herring, an abundant, migratory and widely distributed marine fish with substantial genomic resources, as a model organism to evaluate local adaptation. We examined genomic variation and its correlation with environmental variables across a broad environmental gradient, for 15 spawning aggregations in Atlantic Canada and the United States. We then compared our results with available genomic data of northeast Atlantic populations. We confirmed that population structure lies in a fraction of the genome including likely adaptive genetic variants of functional importance. We discovered 10 highly differentiated genomic regions distributed across four chromosomes. Nine regions show strong association with seasonal reproduction. One region, corresponding to a known inversion on chromosome 12, underlies a latitudinal pattern discriminating populations north and south of a biogeographic transition zone on the Scotian Shelf. Genome–environment associations indicate that winter seawater temperature best correlates with the latitudinal pattern of this inversion. The variation at two so‐called 'islands of divergence' related to seasonal reproduction appear to be private to the northwest Atlantic. Populations in the northwest and northeast Atlantic share variation at four of these divergent regions, simultaneously displaying significant diversity in haplotype composition at another four regions, which includes an undescribed structural variant approximately 7.7 Mb long on chromosome 8. Our results suggest that the timing and geographic location of spawning and early development may be under diverse selective pressures related to allelic fitness across environments. Our study highlights the role of genomic architecture, ancestral haplotypes and selection in maintaining adaptive divergence in species with large population sizes and presumably high gene flow. [ABSTRACT FROM AUTHOR]

Understanding how populations adapt to their environment is increasingly important to prevent biodiversity loss due to overexploitation and climate change. Here we studied the population structure and genetic basis of local adaptation of Atlantic horse mackerel, a commercially and ecologically important marine fish that has one of the widest distributions in the eastern Atlantic. We analyzed whole‐genome sequencing and environmental data of samples collected from the North Sea to North Africa and the western Mediterranean Sea. Our genomic approach indicated low population structure with a major split between the Mediterranean Sea and the Atlantic Ocean and between locations north and south of mid‐Portugal. Populations from the North Sea are the most genetically distinct in the Atlantic. We discovered that most population structure patterns are driven by a few highly differentiated putatively adaptive loci. Seven loci discriminate the North Sea, two the Mediterranean Sea, and a large putative inversion (9.9 Mb) on chromosome 21 underlines the north–south divide and distinguishes North Africa. A genome–environment association analysis indicates that mean seawater temperature and temperature range, or factors correlated to them, are likely the main environmental drivers of local adaptation. Our genomic data broadly support the current stock divisions, but highlight areas of potential mixing, which require further investigation. Moreover, we demonstrate that as few as 17 highly informative SNPs can genetically discriminate the North Sea and North African samples from neighboring populations. Our study highlights the importance of both, life history and climate‐related selective pressures in shaping population structure patterns in marine fish. It also supports that chromosomal rearrangements play a key role in local adaptation with gene flow. This study provides the basis for more accurate delineation of the horse mackerel stocks and paves the way for improving stock assessments. [ABSTRACT FROM AUTHOR]

We developed and validated a mixed-stock analysis (MSA) method with 59 single-nucleotide polymorphisms selected from genome-wide data to assign individuals to populations in mixed-stock samples of Atlantic herring from the North and Baltic seas. We analysed 3734 herring from spawning locations and scientific catches of mixed feeding stocks to demonstrate a "one-fits-all" tool with unprecedented accuracy for monitoring spatio-temporal dynamics throughout a large geographical range with complex stock mixing. We re-analysed time-series data (2002–2021) and compared inferences about stock composition with estimates from morphological data. We show that contributions from the western Baltic spring-spawning stock complex, which is under management concern, have likely been overestimated. We also show that a genetically distinctive population of western Baltic autumn spawners, ascribed low fisheries importance, contributes non-negligible and potentially temporally increasing proportions to mixed-stock aggregations, calling for a re-evaluation of stock definitions. MSA data can be implemented in stock assessment and in a variety of applications, including marine ecosystem description, impact assessment of specific fleets, and stock-rebuilding plans. [ABSTRACT FROM AUTHOR]