DNA analysis of the origins of chum salmon bycatch in Alaskan trawl fisheries. A.J. Gharrett and M. Garvin. Dr. Vladimir Brykov

Transcription

1 DNA analysis of the origins of chum salmon bycatch in Alaskan trawl fisheries A.J. Gharrett and M. Garvin Fisheries Division School of Fisheries and Ocean Sciences University of Alaska Fairbanks in collaboration with Dr. Vladimir Brykov Institute of Marine Biology Russian Academy of Sciences

2 The problem: Chum salmon are important to rural Alaskan livelihood and culture (Federal Subsistence Board); a subject of international allocation (the Pacific Salmon Treaty); Chum salmon are taken as bycatch in fisheries including Bering Sea trawl fisheries.

3 Thousands of chum BSAI chum bycatch CVOA chum bycatch CVOA limit Year

4 In recent years chum salmon abundance declined sharply. Are the declines a result of Interceptions? Ecological changes -- either interannual or global environmental?

5 In recent years chum salmon abundance declined sharply. Are the declines a result of Interceptions? Ecological changes -- either interannual or global environmental? Regardless, we must be able to determine the origins/destinations of fish in order to address these questions

6 In recent years chum salmon abundance declined sharply. Are the declines a result of Interceptions? Ecological changes -- either interannual or global environmental? Regardless, we must be able to determine the origins/destinations of fish in order to address these questions Some of the pertinent questions include: What is the marine distribution of a particular stock? To what extent does the distribution change during the year? To what extent does the distribution differ between years? What environmental factors are related to distributional changes?

7 What are their origins? 50 N 55 N 60 N 120 E 140 E 160 E W 140 W 120 W 60 N 55 N 50 N? 45 N 40 N 35 N

8 Our approach focuses on DNA-based variation Single Nucleotide Polymorphisms (SNPs) We detect both nuclear and mtdna variation and Microsatellites (supported by BSFA)

9 What is a SNP? SNP = Single nucleotide polymorphism Fish #1... aggagcttct cctgctagat... Fish #2... aggagcttct cctgctagat... Fish #3... aggagctcct cctgctagat... Fish #4... aggagcttct cctgctagat Fish #n... aggagcttct cctgctagat...

10 We have developed a new method to identify SNPs. Our method reduces biases (ascertainment bias) by substantially increasing the numbers surveyed in preliminary screening. It has been accepted for publication

11 We have developed a new method to identify SNPs. Our method reduces biases (ascertainment bias) by substantially increasing the numbers surveyed in preliminary screening. It has been submitted for publication We are also applying an alternative assay method. The method reduces reagent costs about 85%.

12 We have developed a new method to identify SNPs. Our method reduces biases (ascertainment bias) by substantially increasing the numbers surveyed in preliminary screening. It has been submitted for publication We are also applying an alternative assay method. The method reduces reagent costs about 85%. Consequently, we increased our scope of work. We surpassed our proposed scope, but will develop more SNP loci and assay additional populations.

13 Previously presented results of screening for sequence variation Asia Western AK BBay SCAk SE Alaska BC/PNW Heilong Katagishi Tym Hairsova Ossoro Kobuk Eldorado Achilinguk Sheenjek Kanektok Goodnews Fishing Br Frosty Cree Big Creek Kiznyiak Olsen Cr Alsek Herman Cr Taku Greens Old Tom Tasu Neekas John's Locus Clock site site Insulin site site POMC Somatolactin site site Vitellogenin Receptor site site site 3* site 4* Vitellogenin Lysozyme Transferrin Calcium Receptor exon Calcium Receptor exon Isotocin I site site site 3* site 4* site 5* Stannocalcin site Vasotocin I site site site converted to SNP assay promising

14 New results of screening for sequence variation Asia Western AK BBay SCAk SE Alaska BC/PNW Locus Heilong Katagishi Tym Hairsova Ossoro Kobuk Eldorado Achilinguk Sheenjek Kanektok Goodnews Fishing Br Frosty Cr Big Creek Kiznyiak Olsen Cr Alsek Herman Cr Taku Greens Old Tom Tasu Neekas John's MHC IIB site site site ER site ERPRM site site site SW2 Opsin site RH1 Opsin site GRPRM site site site site ISOIIPRM site site site PRLPRM site Vitellogenin 3' UTR site site Lysozyme 2 site VTI Promoter site site converted to SNP assay promising to be evaluated

15 PCCRC support made it possible to undertake a microsatellite project. (supported by Bering Sea Fishermen s Association) Our goal: parallel microsatellite and SNP baselines Survey the same individuals in the same populations. The data are compatible and can be used together in analyses. Microsatellite data presented here are from out lab: S. Fuller, S. Hall, & R. Riley

16 Microsatellite analysis microsatellite loci about every 10,000 bp PCR amplify millions of copies Sequencer image variable repeat numbers alleles CA CA CA CA CA CA CA CA CA CA CA CA CA electrophoresis

17 Chum salmon populations analyzed for SNP variation 50 N 55 N 60 N 120 E 140 E 160 E W 140 W 120 W 60 N 55 N 50 N 45 N 40 N 35 N

18 Chum salmon populations analyzed for microsatellite variation 50 N 55 N 60 N 120 E 140 E 160 E W 140 W 120 W 60 N 55 N 50 N 45 N 40 N 35 N

19 Principal components analysis (SNPs) Fall Yukon Summer Yukon NW Ak Kuskokwim/ Bering Sea B Bay/ Ak Penn N SE Ak SC Ak S SE Ak Wash B Col PC2 Russia Japan PC4 Fall Yukon NW Ak B Bay/ Ak Penn N SE Ak Summer Yukon 15 Kuskokwim/ Bering Sea Japan Russia SC Ak Wash S SE Ak B Col PC1

20 Principal components analysis (microsatellites) Alsek Karta/OldTom NSE Alaska Behm Canal QCI Brit Col SC Alaska Summer Yukon Pac NW BBay/ Ak Penn Kusk/ B Sea Fall Yukon PC2 NW Alaska Amur Magadan Kamchatka Sakalin Kurile Primore Honshu PC1

21 Resolving stock mixtures Contributions Estimates Potential contributing populations n-1 n Mixture Baseline data (all pops) Stock separation program (SPAM) n-1 n

22 Potential contributing populations Testing baseline (by simulation) Test one population at a time to evaluate misassignment Estimates Contributions 1 Baseline data 1 3% 1 (all pops) n-1 n 100% Mixture SPAM n-1 n e.g., for n = 10 95% 2% n-1 n 10% 10% 10% 10% 10% 10% good poor

23 100% simulations 100% 80% 12 microsatellites 60% 40% 20% 0% Asia Coast WAk U Yukon BBay SCAk SEAk/QC BC/PNW Key 100% 80% 19 SNPs (8 loci) 60% 40% 20% 0%

24 Japan W Okhotsk Kamchatka NW Alaska L Yukon U Yukon Kuskokwim BBay SCAk NSEAk Behm Canal SSEAk WashBC 100% simulations 12 microsatellites 19 SNPs (8 loci) 100% 80% 60% 40% 20% 0% 100% 80% 60% 40% 20% 0%

25 Japan W Okhotsk Kamchatka NW Alaska L Yukon U Yukon Kuskokwim BBay SCAk NSEAk Behm Canal SSEAk WashBC 100% simulations 100% 80% 12 microsatellites 60% 40% 20% 0% Key 100% 80% 19 SNPs (8 loci) 60% 40% 20% 0%

26 Estimates of bycatch sample collected 13 Aug 2005 at 55 o 25 N 167 o 01 W microsatellites SNPs cbayes SPAM cbayes SPAM Sim Boot Sim Boot Region mean SE mean SE mean SE mean SE Japan (Honshu)/Primore W Okhotsk Magadan/Kamchatka NW Alaska Summer Yukon Fall Yukon Kuskokwim/Bering Sea Bristol Bay/Ak Penn Southcentral Ak N Southeast Ak Behm Canal S Southeast Ak/Queen Charlotte Brtiish Col/Washington Maximum SE Asia Coastal western Alaska Fall Yukon BBay/NAkPen Southcentral Ak Southeast Ak Brtiish Col/Washington Maximum SE

27 What next? (no cost extension) We will: Continue developing new SNP loci Survey variation in additional baseline samples Include more Asian samples to parallel microsatellite baseline Conduct eco-tilling of MHC II genes Continue developing techniques to resolve linkage disequilibrium Evaluate a second bycatch sample with both baselines M. Garvin will complete M.S. and begin Ph.D.