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Chinook salmon (Oncorhynchus tshawytscha) are migratory fish that are highly valued for subsistence, sport, and commercial fisheries throughout their native range. Populations of Chinook salmon in western Alaska have exhibited long-term declines, leading to restrictions on harvests. Management priorities require greater resolution for genetic stock identification (GSI) than is available with current methods. We leveraged RADseq, TaqMan, and GT-seq data originating from multiple sources, collected through time, to develop a set of GT-seq panels containing 1092 single nucleotide polymorphisms (SNPs) that improved GSI resolution in western Alaska for at-sea and in-river sampling. We generated a dense linkage map to ensure that markers selected for panels spanned the entire genome. In addition, we identified multiple RADseq markers that were associated with sex; these aligned to a 5-centimorgan (cM) region on the sex chromosome. Finally, we developed a bioinformatic pipeline to streamline analysis of GT-seq data that is capable of genotyping microhaplotypes and paralogs, both of which can improve GSI resolution over traditional single-SNP data. Our panels and pipeline provide tools for management agencies to rapidly and easily analyze large-scale genotyping projects.

Many studies exclude loci that exhibit linkage disequilibrium (LD); however, high LD can signal reduced recombination around genomic features such as chromosome inversions or sex-determining regions. Chromosome inversions and sex-determining regions are often involved in adaptation, allowing for the inheritance of co-adapted gene complexes and for the resolution of sexually antagonistic selection through sex-specific partitioning of genetic variants. Genomic features such as these can escape detection when loci with LD are removed; in addition, failing to account for these features can introduce bias to analyses. We examined patterns of LD using network analysis to identify an overlapping chromosome inversion and sex-determining region in chum salmon. The signal of the inversion was strong enough to show up as false population substructure when the entire dataset was analyzed, while the effect of the sex-determining region on population structure was only obvious after restricting analysis to the sex chromosome. Understanding the extent and geographic distribution of inversions is now a critically important part of genetic analyses of natural populations. Our results highlight the importance of analyzing and understanding patterns of LD in genomic dataset and the perils of excluding or ignoring loci exhibiting LD. Blindly excluding loci in LD would have prevented detection of the sex-determining region and chromosome inversion while failing to understand the genomic features leading to high-LD could have resulted in false interpretations of population structure.

Many studies exclude loci exhibiting linkage disequilibrium (LD); however, high LD can signal reduced recombination around genomic features such as chromosome inversions or sex-determining regions. Chromosome inversions and sex-determining regions are often involved in adaptation, allowing for the inheritance of co-adapted gene complexes and for the resolution of sexually antagonistic selection through sex-specific partitioning of genetic variants. Genomic features such as these can escape detection when loci with LD are removed; in addition, failing to account for these features can introduce bias to analyses. We examined patterns of LD using network analysis to identify an overlapping chromosome inversion and sex-determining region in chum salmon. The signal of the inversion was strong enough to show up as false population substructure when the entire dataset was analyzed, while the signal of the sex-determining region was only obvious after restricting genetic analysis to the sex chromosome. Understanding the extent and geographic distribution of inversions is now a critically important part of genetic analyses of natural populations. The results of this study highlight the importance of analyzing and understanding patterns of LD in genomic dataset and the perils of ignoring or excluding loci exhibiting LD.

We examined genetic diversity patterns among 55 collections of Chum Salmon from the northeastern Pacific Ocean using 89 single nucleotide polymorphisms (SNPs). The distribution of Chum Salmon samples extended from the Nass River along the coast of British Columbia and along the coast of Washington as far south as the Columbia River. Chum Salmon represented three previously defined run-groups: fall (primarily), summer, and winter. Genetic variation at SNP loci, as measured by FST, ranged from 0.002 to 0.279 over all collections and averaged 0.062 over all loci. Similar to the genetic patterns detected with microsatellites and allozymes, genetic variation followed a regional structure along geographic distance, with genetic diversity being highest in the north and decreasing southward, then increasing in and near the Columbia River. Within Puget Sound, Washington, genetic variation was structured further according to run timing (fall, summer, and winter) and shared ancestry. Simulations indicated th...

Whole-genome duplications have occurred in the recent ancestors of many plants, fish and amphibians. Signals of these whole-genome duplications still exist in the form of paralogous loci. Recent advances have allowed reliable identification of paralogs in genotyping-by-sequencing (GBS) data such as that generated from restriction-site-associated DNA sequencing (RADSeq); however, excluding paralogs from analyses is still routine due to difficulties in genotyping. This exclusion of paralogs may filter a large fraction of loci, including loci that may be adaptively important or informative for population genetic analyses. We present a maximum-likelihood method for inferring allele dosage in paralogs and assess its accuracy using simulated GBS, empirical RADSeq and amplicon sequencing data from Chinook salmon. We accurately infer allele dosage for some paralogs from a RADSeq data set and show how accuracy is dependent upon both read depth and allele frequency. The amplicon sequencing data set, using RADSeq-derived markers, achieved sufficient depth to infer allele dosage for all paralogs. This study demonstrates that RADSeq locus discovery combined with amplicon sequencing of targeted loci is an effective method for incorporating paralogs into population genetic analyses.

Members of the genus Salvelinus often occur sympatrically, exhibit a high degree of phenotypic plasticity, and commonly hybridize. These factors often complicate species identification and hybrid detection based solely on morphology. Many species and populations of Salvelinus are threatened or endangered and accurate species identification and hybrid detection are important for conservation. Single nucleotide polymorphism (SNP) markers offer several advantages over other classes of genetic markers for species identification. We used DNA sequences from six species of Salvelinus to identify 16 SNPs that exhibited fixed differences among species and 16 additional SNPs that were variable within different species. These markers were used for species identification of putative Bull Trout Salvelinus confluentus that were misidentified as Lake Trout S. namaycush in a recreational fishery in Lake Pend Oreille, Idaho. The markers developed in this study will be useful for Salvelinus species identification a...

We establish a TaqMan-based assay panel for genotyping single-nucleotide polymorphisms in rainbow trout and steelhead (Oncorhynchus mykiss). We develop 22 novel single-nucleotide polymorphism markers based on new steelhead sequence data and on assays from sister taxa. Additionally, we adapt 154 previously developed markers to the TaqMan platform. At the beginning of this study, 59 SNPs with TaqMan assays were available to the scientific community. By adding 176 additional TaqMan assays to this number, we greatly expand the biological applications of TaqMan genotyping within both population genetics and quantitative genetics.

Incorporating historical tissues into the study of ecological, conservation and management questions can broaden the scope of population genetic research by enhancing our understanding of evolutionary processes and anthropogenic influences on natural populations. Genotyping historical and low-quality samples has been plagued by challenges associated with low amounts of template DNA and the potential for pre-existing DNA contamination among samples. We describe a two-step process designed to (i) accurately genotype large numbers of historical low-quality scale samples in a high-throughput format and (ii) screen samples for pre-existing DNA contamination. First, we describe how an efficient multiplex preamplification PCR of 45 single nucleotide polymorphisms (SNPs) can generate highly accurate genotypes with low failure and error rates in subsequent SNP genotyping reactions of individual historical scales from sockeye salmon (Oncorhynchus nerka). Second, we demonstrate how the method can be modified for the amplification of microsatellite loci to detect pre-existing DNA contamination. A total of 760 individual historical scale and 182 contemporary fin clip samples were genotyped and screened for contamination. Genotyping failure and error rates were exceedingly low and similar for both historical and contemporary samples. Pre-existing contamination in 21% of the historical samples was successfully identified by screening the amplified microsatellite loci. The advantages of automation, low failure and error rates, and ability to multiplex both the preamplification and subsequent genotyping reactions combine to make the protocol ideally suited for efficiently genotyping large numbers of potentially contaminated low-quality sources of DNA.

We describe the use of high-resolution melting (HRM), a recent enhancement to traditional DNA melting analyses for the characterization of polymerase chain reaction products, in the identification of 11 novel single-nucleotide polymorphisms (SNPs) for distinguishing between rainbow trout Oncorhynchus mykiss and cutthroat trout O. clarkii. Single-nucleotide polymorphisms provide an important tool for species identification in studies of hybridization and introgression between these two species, but until now the time-consuming and costly nature of DNA sequencing has limited identification of new markers. The ability of HRM to accurately discern nucleotide changes in a DNA sequence make it a cost- and time-effective alternative to traditional sequencing for the detection of novel SNPs.

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.

Single nucleotide polymorphisms (SNPs) are valuable tools for ecological and evolutionary studies. In non-model species, the use of SNPs has been limited by the number of markers available. However, new technologies and decreasing technology costs have facilitated the discovery of a constantly increasing number of SNPs. With hundreds or thousands of SNPs potentially available, there is interest in comparing and developing methods for evaluating SNPs to create panels of high-throughput assays that are customized for performance, research questions, and resources. Here we use five different methods to rank 43 new SNPs and 71 previously published SNPs for sockeye salmon: F(ST), informativeness (I(n)), average contribution to principal components (LC), and the locus-ranking programs BELS and WHICHLOCI. We then tested the performance of these different ranking methods by creating 48- and 96-SNP panels of the top-ranked loci for each method and used empirical and simulated data to obtain the probability of assigning individuals to the correct population using each panel. All 96-SNP panels performed similarly and better than the 48-SNP panels except for the 96-SNP BELS panel. Among the 48-SNP panels, panels created from F(ST), I(n), and LC ranks performed better than panels formed using the top-ranked loci from the programs BELS and WHICHLOCI. The application of ranking methods to optimize panel performance will become more important as more high-throughput assays become available.

Incorporating historical tissues into the study of ecological, conservation and management questions can broaden the scope of population genetic research by enhancing our understanding of evolutionary processes and anthropogenic influences on natural populations. Genotyping historical and low-quality samples has been plagued by challenges associated with low amounts of template DNA and the potential for pre-existing DNA contamination among samples. We describe a two-step process designed to (i) accurately genotype large numbers of historical low-quality scale samples in a high-throughput format and (ii) screen samples for pre-existing DNA contamination. First, we describe how an efficient multiplex preamplification PCR of 45 single nucleotide polymorphisms (SNPs) can generate highly accurate genotypes with low failure and error rates in subsequent SNP genotyping reactions of individual historical scales from sockeye salmon (Oncorhynchus nerka). Second, we demonstrate how the method can be modified for the amplification of microsatellite loci to detect pre-existing DNA contamination. A total of 760 individual historical scale and 182 contemporary fin clip samples were genotyped and screened for contamination. Genotyping failure and error rates were exceedingly low and similar for both historical and contemporary samples. Pre-existing contamination in 21% of the historical samples was successfully identified by screening the amplified microsatellite loci. The advantages of automation, low failure and error rates, and ability to multiplex both the preamplification and subsequent genotyping reactions combine to make the protocol ideally suited for efficiently genotyping large numbers of potentially contaminated low-quality sources of DNA.

Population genetics studies play an increasingly important role in the management and conservation of nonmodel organisms. Unlike studies with model organisms, a typical population genetics study of a nonmodel organism may be conducted by analyzing thousands or hundreds of thousands of individuals for several dozen single nucleotide polymorphisms (SNPs). The use of robust, robotically mediated TaqMan reactions provides substantial advantages in these types of studies. We describe the methods and laboratory setup for analyzing a sustained high throughput of SNP assays in routine university or natural resource agency laboratories with a handful of thermal cyclers. Agencies sustain rates of nearly 150,000 assays per week using uniplex reactions with the Applied Biosystems 7900HT Fast Real-Time PCR System (AB 7900HT). We further describe the medium-density array run on the BioMark from Fluidigm, which increases this rate to over 500,000 assays per week by multiplexing 96 samples for 96 SNPs.

Population genetics studies play an increasingly important role in the management and conservation of nonmodel organisms. Unlike studies with model organisms, a typical population genetics study of a nonmodel organism may be conducted by analyzing thousands or hundreds of thousands of individuals for several dozen single nucleotide polymorphisms (SNPs). The use of robust, robotically mediated TaqMan reactions provides substantial advantages in these types of studies. We describe the methods and laboratory setup for analyzing a sustained high throughput of SNP assays in routine university or natural resource agency laboratories with a handful of thermal cyclers. Agencies sustain rates of nearly 150,000 assays per week using uniplex reactions with the Applied Biosystems 7900HT Fast Real-Time PCR System (AB 7900HT). We further describe the medium-density array run on the BioMark from Fluidigm, which increases this rate to over 500,000 assays per week by multiplexing 96 samples for 96 SNPs.