DOI: 10.5061/dryad.6t1g1jx3m
title: Data from: implications of methodologies for integrating empirical kinships into ex situ population management using PMx: a case study of Baer’s Pochard (Aythya baeri) in North America

description: In this study, we aimed to understand the implications of integrating
 empirical kinships into the genetic management of an ex situ population of
 the endangered waterfowl, Baer’s pochard (Aythya baeri), in North America.
 Single nucleotide polymorphism data were generated for 141 Baer’s pochard
 using double digest restriction site-associated DNA sequencing and
 empirical kinships were derived and integrated into the population
 management software PMx. We compared three different scenarios for appying
 empirical kinships within PMx: 1) no empirical kinships applied, 2)
 empirical kinships applied for pedigree terminals, 3) empirical kinships
 applied for the entire populations of pedigree terminals and descendants.
 We determined that most genetic summary statistics were impacted through
 the calculation of the population’s mean kinship, which increased
 signficantly after empirical kinships were integrated into our
 analyses. Our results also revealed the importance of understanding how
 molecular kinships derived from a particular estimator are scaled, if the
 scale differs significantly from pedigree-based kinships. We describe the
 theory behind the genetic metrics impacted and provide general guidance on
 incorporating empirical kinships into ex situ population management as
 well as provide suggestions for sampling strategies to minimize the biases
 inherent in merging two types of kinship estimators.
description: DNA extracted from whole blood from each of the 141 sampled
 individuals were sent to the Genomic and Bioinformatics Service, Texas
 A&M AgriLife Research laboratory for ddRAD library preparation and
 sequencing. A total of 500 ng of DNA from each individual were provided.
 Paired-end sequences approximately 150-bp in length were produced on a
 single lane of the Illumina NovaSeq 6000 S2 X platform. Demultiplexed
 sequence data was obtained in the form of compressed fastq files
 (fastq.gz), representing raw paired-end sequencing reads. Data filtering
 and SNP discovery were performed in STACKS v2.41 (Catchen et al. 2013,
 Rochette et al. 2019). Initially, sequence data was cleaned using the
 program <em>process_radtags</em> by removing reads with an
 uncalled base or low quality score (raw phred score &lt;10). A custom
 bioinformatics pipeline (available at https://github.com/apwilder/StacksParameterSelection) then was used to select optimal parameters (m, M, n) for STACKS based on the guidelines of Paris et al. (2017). The pipeline ran iterations of the STACKS de novo program, varying one parameter at a time (m, M, or n) while holding the other two parameters constant at default settings (m=3, M=2, n=1). Parameter values tested for the maximum distance allowed between stacks (-M) ranged from 2 and 5, and the minimum depth of coverage required to create a stack (-m) ranged from 1 and 5. A catalog was assembled from consensus loci with the number of mismatches allowed between sample loci when building the catalog (-n) tested from 1 and 5. Parameter values that maximized the number of total loci, polymorphic loci, and SNPs genotyped in at least 80% of individuals (r= 0.80) were then used for downstream analyses. Filtered reads were aligned into identical sequences or ‘stacks’ and putative loci were then identified de novo by comparing stacks. Putative loci (sets of stacks) were then matched against the catalog. Reads were aligned from each sample one locus at a time to identify SNPs across the entire sample set for each locus, genotyping each individual at each SNP. Finally, SNPs were further filtered for a minor allele frequency (MAF) cut-off of 0.02 to remove potential SNPs that might have been generated due to genotyping error, and loci shared by at least 90% of the population retained for further analyses (r=0.90). A higher r-value than that used for parameter selection ultimately was chosen for the final dataset because the number of available SNPs supported identifying a more consistent pool of loci across individuals for downstream analyses. The KING algorithm in PLINK v2.00a was used to calculate pairwise KING-robust kinships between individuals in the dataset.
description: <strong>ddRAD</strong><strong> paired-end
 sequence data for 141 sampled Baer's
 pochard:</strong> 
 BAPO_Seq_1_20 BAPO_Seq_21_38
 BAPO_Seq_39_55 BAPO_Seq_56_72
 BAPO_Seq_73_89 BAPO_Seq_90_107
 BAPO_Seq_108_123
 BAPO_Seq_124_141 
 <strong>Stacks population map input
 file:</strong> 
 PopulationMap 
 <strong>Stacks output file (haplotype and
 SNPs):</strong> 
 populations.snps.vcf 
 <strong>Empirical kinship files imported into
 PMx:</strong> 
 KinshipMatrix_N56_Scenario2.txt
 KinshipMatrix_N141_Scenario3.txt
 KinshipMatrix_N141_OriginalWithNegativeValues.txt
 <strong>The PMx (scti.tools/pmx/) software is
 requried to open the PMx project files:</strong>
 BaersPochard_Scenario1.pmxproj 
 BaersPochard_Scenario2.pmxproj
 BaersPochard_Scenario3.pmxproj
description: This README file was generated on 2023-10-03 by Asako Chaille. GENERAL
 INFORMATION 1. Title of Dataset: Implications of methodologies for
 integrating empirical kinships into ex situ population management using
 PMx: A case study of Baer’s Pochard (Aythya baeri) in North America 2.
 Author Information First Author Contact Information Name: Asako Chaille
 San Diego Zoo Wildlife Alliance Address: San Diego, CA USA Email:
 achaille@sdzwa.org 3. Date of data collection (single date, range,
 approximate date): Birds were sampled for blood between 2017 and 2019.
 ddRAD data was generated and analyzed between 2019-2021 4. Geographic
 location of data collection: Birds were sampled across 21 participating
 North American facilities. The ddRAD library preparation and sequencing
 was done at the Genomic and bioinformatics Service, Texas A&M
 AgriLife Research laboratory. 5. Information about funding sources that
 supported the collection of the data: This work was funded by Akron Zoo,
 Buttonwood Park Zoo, Minnesota Zoo, Pinola Conservancy, and San Diego Zoo
 Wildlife Alliance. SHARING/ACCESS INFORMATION 1. Licenses/restrictions
 placed on the data: CC0 1.0 Universal (CC0 1.0) Public Domain 2. Links to
 publications that cite or use the data: Chaille, A. Y., Lacy, R. C.,
 Putnam, A. S., Toste, J. L., & Ivy, J. A. (2023). Implications of
 methodologies for integrating empirical kinships into ex situ population
 management using PMx: A case study of Baer’s Pochard (Aythya baeri) in
 North America. Journal of Heredity. 3. Links to other publicly accessible
 locations of the data: None 4. Links/relationships to ancillary data sets:
 None 5. Was data derived from another source? No A. If yes, list
 source(s): NA 6. Recommended citation for this dataset: Chaille, A. Y.,
 Lacy, R. C., Putnam, A. S., Toste, J. L., & Ivy, J. A. (2023).
 Data from: Implications of methodologies for integrating empirical
 kinships into ex situ population management using PMx: A case study of
 Baer’s Pochard (Aythya baeri) in North America. Dryad Digital Repository.
 https://doi.org/10.5061/dryad.6t1g1jx3m DATA & FILE OVERVIEW 1.
 File List: A) Individuals\_1\_20.zip B) Individuals\_21\_38.zip C)
 Individuals\_39\_55.zip D) Individuals\_56\_72.zip E)
 Individuals\_73\_89.zip F) Individuals\_90\_107.zip G)
 Individuals\_108\_123.zip H) Individuals\_124\_141.zip I)
 PopulationMap.txt J) populations.snps.vcf K)
 KinshipMatrix\_N56\_Scenario2.txt L) KinshipMatrix\_N141\_Scenario3.txt M)
 KinshipMatrix\_N141\_OriginalWithNegativeValues.txt N)
 BaersPochard\_Scenario1.pmxproj O) BaersPochard\_Scenario2.pmxproj P)
 BaersPochard\_Scenario3.pmxproj 2. Relationship between files, if
 important: Files A-H are raw ddRAD sequence data (paired-end) for 141
 sampled Baer's pochard. 3. Additional related data collected that was
 not included in the current data package: None 4. Are there multiple
 versions of the dataset? No A. If yes, name of file(s) that was updated:
 NA i. Why was the file updated? NA ii. When was the file updated? NA
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: Individuals\_21\_38.zip
 Individuals\_39\_55.zip Individuals\_56\_72.zip Individuals\_73\_89.zip
 Individuals\_90\_107.zip Individuals\_108\_123.zip
 Individuals\_124\_141.zip These files contain raw ddRAD sequence data
 (paired-end) for 141 sampled Baer's pochard in FASTQ format. Data are
 divided into multiple zipped folders by sample number 1-141, and not by
 individual ID.
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: PopulationMap.txt This is the population
 map input file used for the STACKS analysis. 1. Number of variables: 2 2.
 Number of cases/rows: 141 3. Variable List: * 1st column: studbook number
 (individual identifier) for all 141 birds sampled for the study * 2nd
 column: population assignment - all given 1 4. Missing data codes: None 5.
 Specialized formats or other abbreviations used: None
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: populations.snps.vcf Output of SNPs and
 haplotypes from STACKS containing 26,454 filtered SNPs for 141
 individuals. 1. Number of variables: 149 (16 variables and 141 birds
 sampled for the study) 2. Number of cases/rows: 26,454 polymorphic SNPs 3.
 Variable List: * CHROM: Catalog locus * POS: SNP location * ID: Locus
 number not applicable (.) * REF: Primary SNP allele * ALT: Alternative SNP
 allele * QUAL: Not applicable '.' * FILTER: Passed the filtering
 steps * INFO: NS = number of samples with data; AF = allele frequency *
 FORMAT: The format used in the VCF file to describe haplotypes for each
 individual (GT:DP:AD:GQ:GL) * COLUMNS '024'through
 to'285': 141 birds' studbook identifiers 4. Missing data
 codes: not applicable '.' 5. Specialized formats or other
 abbreviations used: Variant Call Format (VCF)
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: KinshipMatrix\_N56\_Scenario2.txt Empirical
 kinship text file for 56 pedigree terminals integrated into the PMx
 project for Scenario 2. The first 56 rows list the 56 pedigree terminals
 by studbook identifier. This is followed by a full matrix of the pairwise
 empirical kinships (KING-robust) between a pair of individuals in the
 order listed in the rows above. Missing data codes: '-1'
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: KinshipMatrix\_N141\_Scenario3.txt
 Empirical kinship text file for all 141 birds in the population integrated
 into the PMx project for Scenario 3. The first 141 rows list the 141
 pedigree terminals by studbook identifier. This is followed by a full
 matrix of the pairwise empirical kinships (KING-robust) between a pair of
 individuals in the order listed in the rows above. Missing data codes:
 '-1'
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR:
 KinshipMatrix\_N141\_OriginalWithNegativeValues.txt The original empirical
 kinship text file for all 141 birds in the population prior to truncating
 negative values to '0'. The first 141 rows list the 141 pedigree
 terminals by studbook identifier. This is followed by a full matrix of the
 pairwise empirical kinships (KING-robust) between a pair of individuals in
 the order listed in the rows above. Missing data codes: '-1'
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: BaersPochard\_Scenario1.pmxproj
 BaersPochard\_Scenario2.pmxproj BaersPochard\_Scenario3.pmxproj PMx
 project files for Scenario 1 in which no empirical kinships were applied,
 Scenario 2 in which empirical kinships are applied to pedigree terminals,
 and Scenario 3 in which empirical kinships are applied for the entire
 population. The PMx (scti.tools/pmx/) software is required to open the PMx
 project files. The files themselves are compressed (zipped) file that uses
 the standard file compression format. For the manuscript, PMx version
 1.6.20200804 was used to run those files.
 #########################################################################
 CODE/SOFTWARE A custom bioinformatics pipeline (available at
 https://github.com/apwilder/StacksParameterSelection) was used to select
 optimal parameters (m, M, n) for STACKS based on the guidelines of Paris
 et al. (2017).