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Studying the effect of similar environments on diverse genetic backgrounds has long been a goal of evolutionary biologists with studies typically relying on experimental approaches. Pink salmon, a highly abundant and widely ranging salmonid, provide a naturally occurring opportunity to study the effects of similar environments on divergent genetic backgrounds due to a strict two-year semelparous life history. The species is composed of two reproductively isolated lineages with overlapping ranges that share the same spawning and rearing environments in alternate years. We used restriction-site-associated DNA ( RAD) sequencing to discover and genotype approximately 8000 SNP loci in three population pairs of even- and odd-year pink salmon along a latitudinal gradient in North America. We found greater differentiation within the odd-year than within the even-year lineage and greater differentiation in the southern pair from Puget Sound than in the northern Alaskan population pairs. We identified 15 SNPs reflecting signatures of parallel selection using both a differentiation-based method ( BAYESCAN) and an environmental correlation method ( BAYENV). These SNPs represent genomic regions that may be particularly informative in understanding adaptive evolution in pink salmon and exploring how differing genetic backgrounds within a species respond to selection from the same natural environment. [ABSTRACT FROM AUTHOR]

Studies of the oceanic and near-shore distributions of Pacific salmon, whose migrations typically span thousands of kilometres, have become increasingly valuable in the presence of climate change, increasing hatchery production and potentially high rates of bycatch in offshore fisheries. Genetics data offer considerable insights into both the migratory routes as well as the evolutionary histories of the species. However, these types of studies require extensive data sets from spawning populations originating from across the species' range. Single nucleotide polymorphisms (SNPs) have been particularly amenable for multinational applications because they are easily shared, require little interlaboratory standardization and can be assayed through increasingly efficient technologies. Here, we discuss the development of a data set for 114 populations of chum salmon through a collaboration among North American and Asian researchers, termed PacSNP. PacSNP is focused on developing the database and applying it to problems of international interest. A data set spanning the entire range of species provides a unique opportunity to examine patterns of variability, and we review issues associated with SNP development. We found evidence of ascertainment bias within the data set, variable linkage relationships between SNPs associated with ancestral groupings and outlier loci with alleles associated with latitude., (© 2011 Blackwell Publishing Ltd.)

Single nucleotide polymorphisms (SNPs) are appealing genetic markers due to several beneficial attributes, but uncertainty remains about how many of these bi-allelic markers are necessary to have sufficient power to differentiate populations, a task now generally accomplished with highly polymorphic microsatellite markers. In this study, we tested the utility of 37 SNPs and 13 microsatellites for differentiating 29 broadly distributed populations of Chinook salmon (n = 2783). Information content of all loci was determined by In and G'(ST), and the top 12 markers ranked by In were microsatellites, but the 6 highest, and 7 of the top 10 G'(ST) ranked markers, were SNPs. The mean ratio of random SNPs to random microsatellites ranged from 3.9 to 4.1, but this ratio was consistently reduced when only the most informative loci were included. Individual assignment test accuracy was higher for microsatellites (73.1%) than SNPs (66.6%), and pooling all 50 markers provided the highest accuracy (83.2%). When marker types were combined, as few as 15 of the top ranked loci provided higher assignment accuracy than either microsatellites or SNPs alone. Neighbour-joining dendrograms revealed similar clustering patterns and pairwise tests of population differentiation had nearly identical results with each suite of markers. Statistical tests and simulations indicated that closely related populations were better differentiated by microsatellites than SNPs. Our results indicate that both types of markers are likely to be useful in population genetics studies and that, in some cases, a combination of SNPs and microsatellites may be the most effective suite of loci.