|Salmonid Population Genetics|
Jeff Guyon, Chris Kondzela, and Chuck Guthrie
Kondzela, C. M., Guthrie III, C. M., Marvin, C. T., Nguyen, H. T., Ramsower, C., Whittle, J. A., Guyon, J. R. 2016. Stock Composition Analysis of Juvenile Chum and Chinook Salmon Captured on the 2012 and 2013 Bering Sea and Chukchi Sea Surface Trawl Surveys. US Dept. of the Interior, Bureau of Ocean Energy Management, Alaska OCS Region. OCS Study BOEM 2011-AK-11-08 a/b. 41 pp. – DRAFT REPORT
Juvenile chum (Oncorhynchus keta) and Chinook salmon (O. tshawytscha) were collected in the Bering and Chukchi seas as part of the 2012 U.S. BASIS/Arctic Ecosystem Integrated Survey (Arctic EIS) cruises. Juvenile chum salmon were more commonly encountered on the survey and 1,222 juveniles were genotyped for 11 microsatellite markers to determine their stock of origin. The most northern sample set was relatively small; juvenile chum salmon collected in the Chukchi Sea were predominantly from the Kotzebue Sound stock group. Juvenile chum salmon collected in the northern Bering Sea near Norton Sound were predominantly of Norton Sound origin. Yukon River chum salmon were present in both survey areas of the Bering Sea, but were more prevalent between lat. 60-63°N. Juvenile Chinook salmon were not encountered in the Chukchi Sea, but a small sample of 81 juveniles from the Bering Sea was genotyped for 43 single nucleotide polymorphism (SNP) markers. Most of the Chinook salmon were from the Upper Yukon, Coastal Western Alaska, and Middle Yukon stock groups. This study determined the freshwater origin of juvenile chum and Chinook salmon from the northern Bering and Chukchi seas during late-summer/fall based on genetic data and may be used to help guide future surveys of juvenile salmon abundance in western Alaska.
Juvenile chum salmon (Oncorhynchus keta) were collected during late-summer/fall in the northern Bering and southeastern Chukchi seas as part of the 2013 U.S. BASIS/Arctic Ecosystem Integrated Survey (Arctic Eis) cruises. A small number of genetic samples were collected, most from the Chukchi Sea, and genotyped for 11 microsatellite markers to determine freshwater origin. All of the juvenile chum salmon samples were from western Alaska populations: about half from the Yukon River, one-quarter from Kotzebue Sound, and the remainder from Norton Sound and Kuskokwim/northeastern Bristol Bay. About two-thirds of the fish that originated from the Yukon River were from fall-run populations in the middle and upper reaches of the river. This study adds to a growing body of information about the early marine distribution of juvenile chum salmon from western Alaska.
|Arctic Cod and Capelin Population Genetics|
Jeff Guyon and Sharon Wildes
Wildes, S.L., J. Whittle, H. Nguyen, and J. Guyon. 2016. Boreogadus saida genetics in the Alaskan Arctic. US Dept. of the Interior, Bureau of Ocean Energy Management, Alaska OCS Region. OCS Study BOEM 2011-AK-11-08 a/b. 67 pp. – DRAFT REPORT
Population structure of Boreogadus saida (B. saida) (Arctic cod) was examined with nuclear and mitochondrial DNA (mtDNA) loci. Non-spawning B. saida were collected from the Chukchi Sea and Arctic Ocean adjacent to Alaska, in 2012 and 2013. Genetic data was obtained (n=1493) from 15 microsatellite markers, including two loci developed for this study. Newly developed microsatellite locus Sai25 clearly distinguishes morphologically similar B. saida from juvenile Gadus chalcogrammus (pollock). Two microsatellite loci, Sai13 and Bsa60, departed significantly from Hardy- Weinberg equilibrium (HWE) expectations in nearly every collection, P > 0.0001, likely indicating the presence of null alleles. Sequence information of the mtDNA cytochrome oxidase I gene from a subset of these samples (n=351), resulted in one main haplotype and 4 smaller clades. Data from 13 nuclear loci in HWE suggest B. saida is a single panmictic population in the Chukchi Sea and Arctic Ocean adjacent to Alaska. While the suite of genetic markers in this study did not detect population structure in this species with low genetic diversity, it does not preclude that structure may exist.
Wildes, S.L., Hv. Nguyen, and J. Guyon. 2016. Capelin (Mallotus villosus) genetics in the Alaskan Arctic. US Dept. of the Interior, Bureau of Ocean Energy Management, Alaska OCS Region. OCS Study BOEM 2011-AK-11-08 a/b. 55 pp. – DRAFT REPORT
The conclusions of this study are based on a survey of microsatellite markers and mtDNA sequences of capelin in northern Alaskan waters. Non-spawning adult capelin were collected from the northeastern Bering Sea, Chukchi Sea, and Arctic Ocean near Barrow, Alaska in 2012 and 2013 (N=1600). Data from 192 Gulf of Alaska capelin from a previous study were added for comparison. Data were obtained from 16 microsatellite markers, and a subset of individuals was sequenced at the cytochrome b region of the mtDNA (N=300). Genetic differentiation was not detected geographically or temporally among the collections of Arctic samples, however, significant departure from Hardy-Weinberg proportions was observed at 7 of the 16 microsatellite loci after correction for multiple tests in the Arctic population as a whole. Further, a log likelihood of data partitioned into two theoretical groups by STRUCTURE, indicated that the tails of the distribution, half of the samples, had a high (75-95%) individual assignment to one of the two partitioned populations. Distribution of allele frequencies were not a smooth or unimodal distribution in half of the loci examined. These indices suggest weak structure among capelin in the Arctic, or remnants of past structure, which may now be introgressing. Comparison with Gulf of Alaska (GOA) samples confirms a previously described historic divergence of mtDNA between the GOA and the Arctic, and examination of nuclear loci from this study indicate the divergence is contemporary.
Arctic cod and capelin are abundant in the Chukchi Sea and important for a wide variety of critical prey species. Samples from both species will be collected during 2012 and a genetic analysis will be undertaken to examine whether these species exist as large metapopulations or genetically distinct subpopulations.
In 2011, a library was constructed for discovering Arctic cod microsatellite markers and 100 of the clones were DNA sequenced. Additional Arctic cod DNA clones will be sequenced in 2012 and our collaboration with other researchers will help identify a set of up to 10 microsatellite markers for genotyping Arctic cod samples collected in the 2012 Chukchi survey. Currently a group of capelin microsatellite markers are being optimized in the laboratory.
Approach – During 2012 surveys, Arctic cod will be collected systematically so that samples are representative of the fish in the area. In large catches, all individuals will be counted and every 10th fish will be genetically sampled. Capelin schools are patchier and so all capelin caught will be collected and frozen for laboratory analysis. DNA will be isolated from tissue, amplified via polymerase chain reaction and individual genotypes obtained by DNA sequencing. The geographical structure of the sampled populations will be assessed using principal component analysis, neighbor-joining tree, Bayesian clustering and other state-of-the-art genetic analysis methods. For capelin, allele frequencies will be compared between and among both (1) the 3 groups of samples collected in the 2012 Chukchi Sea bottom trawl survey and (2) capelin sample sets collected previously from the Arctic Ocean, Bering Sea, and Gulf of Alaska. Preliminary analysis using a subset of genetic markers suggests differences between capelin populations between the Bering Sea and Gulf of Alaska suggesting the potential for localized stock structure. We will use our results from this analysis to determine the extent of heterogeneity within and among each collection. For Arctic cod, allele frequencies will be compared between and among the 3 groups of samples collected in the 2012 Chukchi survey.
Products – Written reports will be prepared describing whether unique capelin and Arctic cod stocks were identified within the collections and the reports will be considered for future publication in a peer-reviewed journal.
|Saffron Cod Population Genetics and Structure|
Tony Gharrett and Noel Sme
Objectives- (1) Develop genetic markers for saffron cod, (2) determine geographic scale of genetic divergence, which will include evaluation of reference collections distal to the Arctic and Bering Sea collections, (3) describe the genetic population structure and seascape genetics of saffron cod in the Pacific sector of the subarctic and Arctic oceans, with a particular focus on the Chukchi Sea, and (4) ensure that saffron cod in the Alaskan Arctic does not also include the congener navaga (E. navaga).
The saffron cod is abundant in Alaskan Arctic waters and an important component of the Arctic ecosystem (Wolotira 1985). However, the species is little studied, especially in North American waters. It is a commercially valuable species in Asia and its potential commercial value (NPFMC 2009) and importance as prey for several marine mammals (Bluhm and Gradinger 2008) dictate a need to learn more about the species. The geographic structure of populations, or, for continuously distributed species, the scale of a species’ basis for production is important to both conservation and management and to understanding responses to anthropogenic disturbances. That geographical scale is often referred to as its intrinsic scale and is related to the scale of lifetime dispersal of a species. The extent of dispersal of a species determines the amount of genetic divergence that occurs over geographical distance. Consequently, the geographic elements of management should focus on intrinsic structure as determined by genetic divergence as well as by practical geographic features. Here we describe work that will provide information about the genetic structure of saffron cod and will enhance our understanding of the biology and life history of the species.
We will address three questions that relate to the fine-scale geographic distribution of adults from studies that use microsatellite loci: (1) At what geographic scale does genetic divergence or isolation by distance (IBD) become apparent? (2) Can we detect specific spatial discontinuities, gradients, or transitions in the genetic compositions of these species? and (3) If so, do discontinuities correspond with known geographic, oceanographic, or life history features? Finally because there are questions about the actual Arctic distributions of saffron cod and its sister species navaga (Wolotira 1985), we will also conduct mitochondrial DNA analyses of a portion of the samples to see if the geographic structure harbors distinct lineages as opposed to a continuum over which divergence occurs.
Although the focus of the project is the Alaskan Arctic and near Arctic, we plan to include samples of saffron cod and navaga distal from the geographic region of interest for contrast because divergence in marine species may be significant, but low, and because some gadid species have relatively little variation. In particular, we will seek samples from Prince William Sound, the Sea of Okhotsk, Kodiak Island, the northern Bering Sea, the Beaufort Sea, the Canadian Arctic, and the Russian Arctic.
We will conduct microsatellite analyses on the samples from all regions. Only two saffron cod-specific microsatellites are available (M. Canino NWFSC, NMFS Seattle), so in anticipation that loci available from other species (O’Reilly et al. 2000) will cross react poorly, we plan to contract the development of additional saffron cod-specific loci. We will look for divergent lineages within and among the geographically distinct collection by applying Eco-tilling, an efficient, low cost method for detecting variation in nucleotide sequences. Data will be analyzed by first using conventional software to obtain standard genetic characterizations (1) to assure data quality, and (2) to estimate the variation within and among collections. Next we will conduct isolation-by-distance analyses based on individuals (Rousset 2000). From these analyses and estimates of abundance, we can estimate global plausible ranges of dispersal distances (intrinsic scale) and effective neighborhood sizes across the range. We can also identify geographically and genetically distinct groups of samples. Recently, a variety of methods have been developed to inspect spatial data for discontinuities in gene flow (Guillot et al. 2009). These “seascape genetics” approaches will be used to look for oceanographic and geological influences on population structure.