B08_SOW_(1).docx

STATEMENT OF WORK

PACIFIC WALRUS GENETIC ANALYSIS

FOR GENETIC AND CLOSE-KIN MARK-RECAPTURE

GENERAL:

The US Fish and Wildlife Service (USFWS), Marine Mammal Office, AK, requires Genetic Analysis services.

INTRODUCTION

The U.S. Fish and Wildlife Service (USFWS) is tasked under the Marine Mammal Protection Act (MMPA) to evaluate Pacific walrus (Odobenus rosmarus divergens) status and trends across their range. Recent efforts to estimate walrus abundance and demographic parameters have generally yielded poor precision, which makes basing management decisions off those estimates difficult. Standing age structure data have proven valuable in improving precision of demographic parameters (Taylor et al. 2018), but similar improvements for estimating population size have been elusive.

Genetic mark-recapture (GMR) efforts have been shown to yield some improvements in precision (Beatty et al. in review). Close-kin mark-recapture (CKMR) is a recently developed approach for estimating abundance and demographic parameters that relies on the frequency of kinship relationships (identified through genotyping) among individuals sampled from a population (Bravington et al. 2016a, 2016b). While GMR techniques require self-recaptures, CKMR does not. Study designs can therefore rely on lethal sampling (e.g., through harvest), potentially reducing costs and logistical challenges markedly and increasing sample sizes to improve precision of estimates.

A crude estimate of the sample size (number of adults and juveniles) required to obtain a coefficient of variation (CV) of approximately 15% is given by , where N is the total population size. Given previously collected samples for walruses and our current understanding of the population size, a CV of <15% is likely with a CKMR effort and will improve quickly as additional samples are collected (e.g., through harvest) because each sample “marks” many individuals in the population. Such precision will be a substantial improvement over current estimates of walrus abundance (Taylor et al. 2018), as well as those likely to be obtained with current GMR modeling efforts (Beatty et al. in press). CKMR approaches can also leverage information gathered by identifying half sibling pairs (HSPs) and including such in models drastically improves precision. Identifying HSPs with negligible error—essentially required for computation—requires a panel of about 3000 single nucleotide polymorphisms (SNPs; Waples and Feutry 2021). For a polygynous species, such as Pacific walrus, mitochondrial DNA analysis is also required to determine if HSPs are maternal or paternal, due to differences in potential future reproductive output between sexes (Waples and Feutry 2021). Furthermore, precise age information is also required so that year at birth can be identified for sampled individuals (Waples and Feutry 2021).

We plan to implement close-kin mark-recapture to obtain precise estimates of walrus abundance and demographic parameters, which requires (1) a panel of 3000 SNPs, (2) a procedure to genotype samples based on that panel (3) a mitochondrial DNA assay to determine paternal/maternal relationships, (4) a reliable assay to sex samples, and (45) an epigenetic aging assay to precisely age samples. Further, we plan to also genotype samples based on the 116 SNPs used by Beatty et al (in press) so that we can apply their methods as well. The old 116 SNP assay and sex marker will be included in the 3000 SNP assay to be developed. The SNP panel will be used to identify kin relationships (i.e., half sibling and parent-offspring) with existing samples from walruses as well as all future samples, and the future samples will also be genotyped based on the 116 SNPs.

We are developing a large (~3000) panel of SNPs for Pacific walrus for use in an application of CKMR to improve estimates of walrus abundance. The panel is being developed and the preliminary set of samples are now analyzed by DArTseq and DArTcap - the only technologies proven for constructing large SNP panels for application of CKMR, as suggested by one of the lead developers of CKMR techniques (M. Bravington) and demonstrated by Hillary et al. (2018). These technologies are patented and implemented by the Diversity Arrays Technology Pty Ltd (DArT), Australia. The next steps required for CKMR implementation include processing of larger set of samples with this large SNP assay, mtDNA marker development and sample analysis for parental pair identification, sex marker development and sexing the samples, and finally carrying out epigenetic aging of the samples with pre-developed markers. All of these steps have to be carried out by the same laboratory to minimize the uncertainly rate associated with different equipment and procedures being used for various steps of the analysis and ensure consistent, high quality results essential for successful CKMR application.

The first step of these analysis (developing the panel of 3000 SNPs, which includes the current 116 SNPs, and genotyping a preliminary set of walrus samples) has been conducted by the DArT laboratory and continuation of the development and sample analysis is key to successful completion of the population assessment we are conducting. The epigenetic aging assay is being developed in collaboration with other partners. DArT has the capabilities to process all existing samples collected in 2013-2017 and future samples to be collected in the new field study to occur in 2023-2025 (or optional - 2027Following the new sample acquisition and processing they are to be sent to the laboratory for genotyping after each field collection season. Old samples are to be added to the new ones. Using the same vendor for all of these required analyses will be key to minimizing error in the genetic analysis to a level that is negligible, which is paramount for successfully implementing CKMR (Waples and Feutry 2021).

PERIOD OF PERFORMANCE:

Base Year: October 1, 2022 – September 30, 2023 Option Year 1: October 1, 2023 – September 30, 2024 Option Year 2: October 1, 2024 – September 30, 2025 Option Year 3: October 1, 2025 – September 30, 2026 Option Year 4: October 1, 2026 – September 30, 2027

DESCRIPTION OF DELIVERABLES

The work outlined here includes:

· DNA extraction for walrus samples provided by USFWS, if required

· Processing walrus samples based on panel of 3000 SNPs developed using DArTseq

· Developing mitochondrial DNA (mtDNA) assays to determine maternal/paternal relationships for all samples

· Aging sampled individuals based on pre-developed epigenetic aging assay and/or developing and applying new assays for aging

· Sexing sampled walruses based on existing markers and/or other identified markers

· Provide all data and results to USFWS as well as retain them for processing samples in the future

· Provide support as needed understanding and interpreting the genetic data and results

DESCRIPTION OF TASKS

The contractor shall perform the following deliverables and conduct all work in close collaboration with the FWS office of Marine Mammal Management. Up to four additional option years will be considered subject to availability of funds. There is one base year and 4 option years as specified below.

TECHNICAL CAPABILITIES:

· Ability to perform comprehensive single nucleotide polymorphism (SNP) panel (>3000 SNPs) development for a new species with no or limited prior sequencing information using genomic complexity reduction approach coupled with next-generation sequencing;

· Ability to perform high throughput genotyping, with little to no limitations to the sample volume and marker density;

· Ability to perform genotyping with minimal error rates to ensure low uncertainty data for subsequent CKMR analysis and walrus abundance estimation with adequate precision;

· Availability of technologies to genotype materials with specific markers (pre-developed SNP assays including those derived from other platforms) with high throughput rate; ability to include a previously developed 160 SNP assay in the longer 3000 SNP panel;

· Ability to develop mitochondrial DNA-assays to determine maternal/paternal relationships of animals;

· Ability to sex and age individuals using pre-developed markers derived from other platforms and/or develop and apply new assays for sexing and aging

· Fast processing of samples – ability to deliver results within 2-3 months upon sample delivery and quality control completion;

· Proven record of top-quality performance, timely order delivery and high professional ethics working with clients on long-term complex projects.

BASE YEAR TASKS:

Project specific tasks:

1. Analyze the two plates of samples used to develop the SNP panel with DArTcap technology

2. Develop mtDNA assay(s) for determining paternal/maternal kinship

3. Analyze existing 9 plates of samples with the mtDNA assays

4. Analyze 9 plates of samples with sex marker(s)

5. Analyze 4 plates with pre-existing age marker(s)

Deliverables:

Approximately up to 9 plates analyzed with the mtDNA assays, sex and age markers; 2 plates analyzed with DArTcap technology

OPTION YEAR 1 TASKS:

Project specific tasks:

1. Extract DNA from up to 40 plates of samples;

2. Analyze up to 40 plates of samples with DArTcap technology;

3. Analyze up to 40 plates of samples with the mtDNA assays;

4. Analyze 40 plates of samples with sex marker(s);

5. Analyze 45 plates with epigenetic marker(s).

Deliverables:

Approximately up to 40 plates of walrus samples analyzed with DarTcap, mtDNA, and sex markers; up to 49 plates analyzed with age marker(s).

OPTION YEAR 2 TASKS:

Project specific tasks:

1. Extract DNA from up to 40 plates of samples;

2. Analyze up to 40 plates of samples with DArTcap technology;

3. Analyze up to 40 plates of samples with the mtDNA assays;

4. Analyze 40 plates of samples with sex marker(s);

5. Analyze 40 plates with epigenetic marker(s).

Deliverables:

Approximately up to 40 plates of walrus samples analyzed with DarTcap, mtDNA, age and sex markers.

OPTION YEAR 3 TASKS:

Project specific tasks:

1. Extract DNA from up to 40 plates of samples;

2. Analyze up to 40 plates of samples with DArTcap technology;

3. Analyze up to 40 plates of samples with the mtDNA assays;

4. Analyze 40 plates of samples with sex marker(s);

5. Analyze 40 plates with epigenetic marker(s).

Deliverables:

Approximately up to 40 plates of walrus samples analyzed with DarTcap, mtDNA, age and sex markers.

OPTION YEAR 4 TASKS:

Project specific tasks:

1. Extract DNA from up to 40 plates of samples;

2. Analyze up to 40 plates of samples with DArTcap technology;

3. Analyze up to 40 plates of samples with the mtDNA assays;

4. Analyze 40 plates of samples with sex marker(s);

5. Analyze 40 plates with epigenetic marker(s).

Deliverables:

Approximately up to 40 plates of walrus samples analyzed with DarTcap, mtDNA, age and sex markers.

REFERENES

Beatty, W.S., Lemons, P.R., Everett, J.P., Lewis, C.J., Taylor, R.L., Lynn, R.J., Sethi, S.A., Quakenbush, L., Citta, J.J., Kissling, M.L., Kryukova, N., and Wenburg, J.K. In press. Estimating Pacific walrus abundance and survival with multievent mark-recapture models. Marine Ecology Progress Series Bravington, M. V., Grewe, P. M., & Davies, C. R. (2016a). Absolute abundance of southern bluefin tuna estimated by close-kin mark-recapture. Nature Communications, 7, 1–8. https://doi.org/10.1038/ncomms13162 Bravington, M. V., Skaug, H. J., & Anderson, E. C. (2016b). Close-kin mark-recapture. Statistical Science, 31(2), 259–274. https://doi.org/10.1214/16-STS552 Hillary, R. M., Bravington, M. V, Patterson, T. A., Grewe, P., Bradford, R., & Feutry, P. (2018). Genetic relatedness reveals total population size of white sharks in eastern Australia and New Zealand. Scientific Reports, June 2017, 1–9. https://doi.org/10.1038/s41598-018-20593-w Taylor, R. L., Udevitz, M. S., Jay, C. V., Citta, J. J., Quakenbush, L. T., Lemons, P. R., & Snyder, J. A. (2018). Demography of the Pacific walrus (Odobenus rosmarus divergens) in a changing Arctic. Marine Mammal Science, 34(1), 54–86. https://doi.org/10.1111/mms.12434 Waples, R. S. & Feutry, P. (2021). Close-kin methods to estimate census size and effective population size. BioRxiv, 3254(January), 2021.01.19.427337. https://doi.org/10.1101/2021.01.19.427337