Genotyping Error Detection and Customised Filtration for SNP Datasets.
Equus hemionus
SNP filtering
genotype recapture
genotyping error
non‐invasive genetics
triplicates
Journal
Molecular ecology resources
ISSN: 1755-0998
Titre abrégé: Mol Ecol Resour
Pays: England
ID NLM: 101465604
Informations de publication
Date de publication:
22 Oct 2024
22 Oct 2024
Historique:
revised:
23
08
2024
received:
07
11
2023
accepted:
02
09
2024
medline:
22
10
2024
pubmed:
22
10
2024
entrez:
22
10
2024
Statut:
aheadofprint
Résumé
A major challenge in analysing single-nucleotide polymorphism (SNP) genotype datasets is detecting and filtering errors that bias analyses and misinterpret ecological and evolutionary processes. Here, we present a comprehensive method to estimate and minimise genotyping error rates (deviations from the 'true' genotype) in any SNP datasets using triplicates (three repeats of the same sample) in a four-step filtration pipeline. The approach involves: (1) SNP filtering by missing data; (2) SNP filtering by error rates; (3) sample filtering by missing data and (4) detection of recaptured individuals by using estimated SNP error rates. The modular pipeline is provided in an R script that allows customised adjustments. We demonstrate the applicability of the method using non-invasive sampling from the Asiatic wild ass (Equus hemionus) population in Israel. We genotyped 756 samples using 625 SNPs, of which 255 were triplicates of 85 samples. The average SNP error rate, calculated based on the number of mismatching genotypes across triplicates before filtration, was 0.0034 and was reduced to 0.00174 following filtration. Evaluating genetic distance (GD) and relatedness (r) between triplicates before and after filtration (expected to be at the minimum and maximum respectively) showed a significant reduction in the average GD, from 58.1 to 25.3 (p = 0.0002) and a significant increase in relatedness, from r = 0.98 to r = 0.991 (p = 0.00587). We demonstrate how error rate estimation enhances recapture detection and improves genotype quality.
Identifiants
pubmed: 39435526
doi: 10.1111/1755-0998.14033
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e14033Subventions
Organisme : United States-Israel Binational Science Foundation
ID : 2011384
Informations de copyright
© 2024 John Wiley & Sons Ltd.
Références
AgriPlex Genomics. 2023. “PlexSeq™: Bridging the Genotyping Gap Between Single‐Plex Screening and High‐Density Arrays.” https://pag.confex.com/pag/xxvi/recordingredirect.cgi/oid/Recording2865/paper32115_1.pdf.
Aird, D., M. G. Ross, W. S. Chen, et al. 2011. “Analyzing and Minimizing PCR Amplification Bias in Illumina Sequencing Libraries.” Genome Biology 12, no. 2: R18. https://doi.org/10.1186/gb‐2011‐12‐2‐r18.
Andrews, K. R., J. M. Good, M. R. Miller, G. Luikart, and P. A. Hohenlohe. 2016. “Harnessing the Power of RADseq for Ecological and Evolutionary Genomics.” Nature Reviews. Genetics 17, no. 2: 81–92. https://doi.org/10.1038/nrg.2015.28.
Andrews, K. R., and G. Luikart. 2014. “Recent Novel Approaches for Population Genomics Data Analysis.” Molecular Ecology 23: 1661–1667. https://doi.org/10.1111/mec.12686.
Andrews, S. 2010. “FastQC: A Quality Control Tool for High Throughput Sequence Data.” http://www.bioinformatics.babraham.ac.uk/projects/fastqc.
Benjamini, Y., and T. P. Speed. 2012. “Summarizing and Correcting the GC Content Bias in High‐Throughput Sequencing.” Nucleic Acids Research 40, no. 10: e72. https://doi.org/10.1093/nar/gks001.
Blåhed, I. M., G. Ericsson, and G. Spong. 2019. “Noninvasive Population Assessment of Moose (Alces alces) by SNP Genotyping of Fecal Pellets.” European Journal of Wildlife Research 65, no. 6: 1–11. https://doi.org/10.1007/s10344‐019‐1337‐8.
Bronner, I. F., M. A. Quail, D. J. Turner, and H. Swerdlow. 2013. “Improved Protocols for Illumina Sequencing.” Current Protocols in Human Genetics 79, no. 1: 18.2.1‐42. https://doi.org/10.1002/0471142905.hg1802s62.
Browne, P. D., T. K. Nielsen, W. Kot, et al. 2020. “GC Bias Affects Genomic and Metagenomic Reconstructions, Underrepresenting GC‐Poor Organisms.” GigaScience 9, no. 2: giaa008. https://doi.org/10.1093/gigascience/giaa008.
Carroll, E. L., M. W. Bruford, J. A. DeWoody, et al. 2018. “Genetic and Genomic Monitoring With Minimally Invasive Sampling Methods.” Evolutionary Applications 11, no. 7: 1094–1119. https://doi.org/10.1111/eva.12600.
Catchen, J. M., P. A. Hohenlohe, S. Bassham, A. Amores, and W. A. Cresko. 2013. “Stacks: An Analysis Tool Set for Population Genomics.” Molecular Ecology 22: 3124–3140. https://doi.org/10.1111/mec.12354.
Chen, Y. C., T. Liu, C. H. Yu, T. Y. Chiang, and C. C. Hwang. 2013. “Effects of GC Bias in Next‐Generation‐Sequencing Data on De Novo Genome Assembly.” PLoS One 8, no. 4: e62856. https://doi.org/10.1371/journal.pone.0062856.
Cheng, C., Z. Fei, and P. Xiao. 2023. “Methods to Improve the Accuracy of Next‐Generation Sequencing.” Frontiers in Bioengineering and Biotechnology 11: 982111. https://doi.org/10.3389/fbioe.2023.982111.
Cruz, M., J. D. Arbelaez, K. Loaiza, J. Cuasquer, J. Rosas, and E. Graterol. 2021. “Genetic and Phenotypic Characterization of Rice Grain Quality Traits to Define Research Strategies for Improving Rice Milling, Appearance, and Cooking Qualities in Latin America and the Caribbean.” Plant Genome 14, no. 3: e20134. https://doi.org/10.1002/tpg2.20134.
Danecek, P., J. K. Bonfield, J. Liddle, et al. 2021. “Twelve Years of SAMtools and BCFtools.” GigaScience 10, no. 2: giab008. https://doi.org/10.1093/gigascience/giab008.
Danecek, P., A. Auton, G. Abecasis, et al. 2011. “The Variant Call Format and VCFtools.” Bioinformatics 27, no. 15: 2156–2158. https://doi.org/10.1093/bioinformatics/btr330.
Delahaye, C., and J. Nicolas. 2021. “Sequencing DNA With Nanopores: Troubles and Biases.” PLoS One 16, no. 10: e0257521. https://doi.org/10.1371/journal.pone.0257521.
Díaz‐Arce, N., and N. Rodríguez‐Ezpeleta. 2019. “Selecting RAD‐Seq Data Analysis Parameters for Population Genetics: The More the Better?” Frontiers in Genetics 10: 533. https://doi.org/10.3389/fgene.2019.00533.
Ekblom, R., M. Aronsson, F. Elsner‐Gearing, M. Johansson, T. Fountain, and J. Persson. 2021. “Sample Identification and Pedigree Reconstruction in Wolverine (Gulo gulo) Using SNP Genotyping of Non‐Invasive Samples.” Conservation Genetics Resources 13: 261–274. https://doi.org/10.1007/s12686‐021‐01208‐5.
Eriksson, C. E., J. Ruprecht, and T. Levi. 2019. “More Affordable and Effective Noninvasive SNP Genotyping Using High‐Throughput Amplicon Sequencing.” bioRxiv, 776492. https://doi.org/10.1101/776492.
Ferreira, C. M., H. Sabino‐Marques, S. Barbosa, et al. 2018. “Genetic Non‐Invasive Sampling (gNIS) as a Cost‐Effective Tool for Monitoring Elusive Small Mammals.” European Journal of Wildlife Research 64: 46. https://doi.org/10.1007/s10344‐018‐1188‐8.
Flanagan, S. P., and A. G. Jones. 2019. “The Future of Parentage Analysis: From Microsatellites to SNPs and Beyond.” Molecular Ecology 28, no. 3: 544–567. https://doi.org/10.1111/mec.14988.
Foroughirad, V., A. L. Levengood, J. Mann, and C. H. Frère. 2019. “Quality and Quantity of Genetic Relatedness Data Affect the Analysis of Social Structure.” Molecular Ecology Resources 19, no. 5: 1181–1194. https://doi.org/10.1111/1755‐0998.13028.
Freedman, A. H., M. Clamp, and T. B. Sackton. 2021. “Error, Noise, and Bias in De Novo Transcriptome Assemblies.” Molecular Ecology Resources 21, no. 1: 18–29. https://doi.org/10.1111/1755‐0998.13156.
Graham, N., E. Telfer, T. Frickey, et al. 2022. “Development and Validation of a 36K SNP Array for Radiata Pine (Pinus radiata D. Don).” Forests 13, no. 2: 176. https://doi.org/10.3390/f13020176.
Hasegawa, T., F. Sato, N. Ishida, Y. Fukushima, and H. Mukoyama. 2000. “Sex Determination by Simultaneous Amplification of Equine SRY and Amelogenin Genes.” Journal of Veterinary Medical Science 62: 1109–1111. https://doi.org/10.1292/jvms.62.1109.
Hu, T., N. Chitnis, D. Monos, and A. Dinh. 2021. “Next‐Generation Sequencing Technologies: An Overview.” Human Immunology 82, no. 11: 801–811. https://doi.org/10.1016/j.humimm.2021.02.012.
Huisman, J. 2017. “Pedigree Reconstruction From SNP Data: Parentage Assignment, Sibship Clustering and Beyond.” Molecular Ecology Resources 17, no. 5: 1009–1024. https://doi.org/10.1111/1755‐0998.12665.
Jamieson, I. G. 2010. “Founder Effects, Inbreeding, and Loss of Genetic Diversity in Four Avian Reintroduction Programs.” Conservation Biology 25, no. 1: 115–123. https://doi.org/10.1111/j.1523‐1739.2010.01574.x.
Kebschull, J. M., and A. M. Zador. 2015. “Sources of PCR‐Induced Distortions in High‐Throughput Sequencing Data Sets.” Nucleic Acids Research 43, no. 21: e143. https://doi.org/10.1093/nar/gkv717.
Kim, B. J., H. Lee, and S. D. Lee. 2009. “Species‐ and Sex‐Specific Multiple PCR Amplifications of Partial Cytochrome b Gene and Zfx/Zfy Introns Form Invasive and Non‐invasive Samples of Korean Ungulates.” Genes & Genomics 31: 369–375. https://doi.org/10.1007/BF03191255.
King, S. R. B., K. A. Schoenecker, J. A. Fike, and S. J. Oyler‐McCance. 2021. “Feral Horse Space Use and Genetic Characteristics From Fecal DNA.” Journal of Wildlife Management 85: 1074–1083. https://doi.org/10.1002/jwmg.21974.
Kleinman‐Ruiz, D., B. Martínez‐Cruz, L. Soriano, et al. 2017. “Novel Efficient Genome‐Wide SNP Panels for the Conservation of the Highly Endangered Iberian lynx.” BMC Genomics 18, no. 1: 556. https://doi.org/10.1186/s12864‐017‐3946‐5.
Koch, I. J., and S. R. Narum. 2021. “An Evaluation of the Potential Factors Affecting Lifetime Reproductive Success in Salmonids.” Evolutionary Applications 14, no. 8: 1929–1957. https://doi.org/10.1111/eva.13263.
Kongrit, C., and C. Siripunkaw. 2017. “Determination of Age and Construction of Population Age Structure of Wild Asian Elephants Based on Dung Bolus Circumference.” Thai Journal of Veterinary Medicine 47, no. 2: 145–153. https://doi.org/10.56808/2985‐1130.2818.
Kozarewa, I., and D. J. Turner. 2011. “Amplification‐Free Library Preparation for Paired‐End Illumina Sequencing.” Methods in Molecular Biology 733: 257–266. https://doi.org/10.1007/978‐1‐61779‐089‐8_18.
Kraus, R. H., B. vonHoldt, B. Cocchiararo, et al. 2015. “A Single‐Nucleotide Polymorphism‐Based Approach for Rapid and Cost‐Effective Genetic Wolf Monitoring in Europe Based on Noninvasively Collected Samples.” Molecular Ecology Resources 15, no. 2: 295–305. https://doi.org/10.1111/1755‐0998.12307.
Krueger, F. 2021. “Trimgalore.” Github Depository. https://github.com/FelixKrueger/TrimGalore.
Larroque, J., E. Kennedy‐Overton, J. M. Vandel, S. Ruette, and S. Devillard. 2023. “Using Pedigree Relations to Inform Capture‐Recapture Data for the Estimation of Census Population Size.” Journal of Wildlife Management 87, no. 8: e22481. https://doi.org/10.1002/jwmg.22481.
Li, C. C., D. E. Weeks, and A. Chakravarti. 1993. “Similarity of DNA Fingerprints Due to Chance and Relatedness.” Human Heredity 43, no. 1: 45–52. https://doi.org/10.1159/000154113.
Li, H. 2013. “Aligning Sequence Reads, Clone Sequences and Assembly Contigs with BWA‐MEM.” arXiv preprint arXiv:1303.3997. https://doi.org/10.48550/arXiv.1303.3997.
Li, H. 2014. “Toward a Better Understanding of Artifacts in Variant Calling From High‐Coverage Samples.” Bioinformatics 30, no. 20: 2843–2851. https://doi.org/10.1093/bioinformatics/btu356.
Lynch, M., and K. Ritland. 1999. “Estimation of Pairwise Relatedness With Molecular Markers.” Genetics 152, no. 4: 1753–1766. https://doi.org/10.1093/genetics/152.4.1753.
Margaryan, K., G. Melyan, F. Röckel, R. Töpfer, and E. Maul. 2021. “Genetic Diversity of Armenian Grapevine (Vitis vinifera L.) Germplasm: Molecular Characterization and Parentage Analysis.” Biology 10, no. 12: 1279. https://doi.org/10.3390/biology10121279.
McFarlane, S., M. Manseau, A. Flasko, et al. 2018. “Genetic Influences on Male and Female Variance in Reproductive Success and Implications for the Recovery of Severely Endangered Mountain Caribou.” Global Ecology and Conservation 16: e00451. https://doi.org/10.1016/j.gecco.2018.e00451.
Nazareno, A. G., and L. L. Knowles. 2021. “There Is no 'rule of thumb': Genomic Filter Settings for a Small Plant Population to Obtain Unbiased Gene Flow Estimates.” Frontiers in Plant Science 12: 677009. https://doi.org/10.3389/fpls.2021.677009.
Nielsen, R., T. Korneliussen, A. Albrechtsen, Y. Li, and J. Wang. 2012. “SNP Calling, Genotype Calling, and Sample Allele Frequency Estimation From New‐Generation Sequencing Data.” PLoS One 7, no. 7: e37558. https://doi.org/10.1371/journal.pone.0037558.
Nielsen, R., J. S. Paul, A. Albrechtsen, and Y. S. Song. 2011. “Genotype and SNP Calling From Next‐Generation Sequencing Data.” Nature Reviews Genetics 12, no. 6: 443–451. https://doi.org/10.1038/nrg2986.
O'Leary, S. J., J. B. Puritz, S. C. Willis, C. M. Hollenbeck, and D. S. Portnoy. 2018. “These Aren't the Loci You're Looking for: Principles of Effective SNP Filtering for Molecular Ecologists.” Molecular Ecology 27: 3193–3206. https://doi.org/10.1111/mec.14792.
Peakall, R., and P. E. Smouse. 2012. “GenAlEx 6.5: Genetic Analysis in Excel. Population Genetic Software for Teaching and Research—An Update.” Bioinformatics 28, no. 19: 2537–2539. https://doi.org/10.1093/bioinformatics/bts460.
Pečnerová, P., G. Garcia‐Erill, X. Liu, et al. 2021. “High Genetic Diversity and Low Differentiation Reflect the Ecological Versatility of the African Leopard.” Current Biology 31, no. 9: 1862–1871. https://doi.org/10.1016/j.cub.2021.01.064.
Peterson, B. K., J. N. Weber, E. H. Kay, H. S. Fisher, and H. E. Hoekstra. 2012. “Double Digest RADseq: An Inexpensive Method for De Novo SNP Discovery and Genotyping in Model and Non‐Model Species.” PLoS One 7, no. 5: e37135. https://doi.org/10.1371/journal.pone.0037135.
Peyrégne, S., and K. Prüfer. 2020. “Present‐Day DNA Contamination in Ancient DNA Datasets.” BioEssays 42, no. 9: 2000081. https://doi.org/10.1002/bies.202000081.
Pfeiffer, F., C. Gröber, M. Blank, et al. 2018. “Systematic Evaluation of Error Rates and Causes in Short Samples in Next‐Generation Sequencing.” Scientific Reports 8, no. 1: 10950. https://doi.org/10.1038/s41598‐018‐29325‐6.
Pompanon, F., A. Bonin, E. Bellemain, and P. Taberlet. 2005. “Genotyping Errors: Causes, Consequences, and Solutions.” Nature Reviews Genetics 6, no. 11: 847–859. https://doi.org/10.1038/nrg1707.
Puckett, E. E. 2017. “Variability in Total Project and Per Sample Genotyping Costs Under Varying Study Designs Including With Microsatellites or SNPs to Answer Conservation Genetic Questions.” Conservation Genetics Resources 9: 289–304. https://doi.org/10.1007/s12686‐016‐0643‐7.
Queller, D. C., and K. F. Goodnight. 1989. “Estimating Relatedness Using Genetic Markers.” Evolution 43, no. 2: 258–275. https://doi.org/10.1111/j.1558‐5646.1989.tb04226.x.
R Core Team. 2023. “R: A Language and Environment for Statistical Computing.” R Foundation for Statistical Computing, Vienna, Austria. https://www.R‐project.org/.
Ramón‐Laca, A., L. Soriano, D. M. Gleeson, and J. A. Godoy. 2015. “A Simple and Effective Method for Obtaining Mammal DNA From Feces.” Wildlife Biology 21: 195–203. https://doi.org/10.2981/wlb.00096.
Rang, F. J., W. P. Kloosterman, and J. de Ridder. 2018. “From Squiggle to Basepair: Computational Approaches for Improving Nanopore Sequencing Read Accuracy.” Genome Biology 19: 90. https://doi.org/10.1186/s13059‐018‐1462‐9.
Renan, S., E. Speyer, N. Shahar, T. Gueta, A. R. Templeton, and S. Bar‐David. 2012. “A Factorial Design Experiment as a Pilot Study for Noninvasive Genetic Sampling.” Molecular Ecology Resources 12, no. 6: 1040–1047. https://doi.org/10.1111/j.1755‐0998.2012.03170.x.
Ritland, K. 1996. “Estimators for Pairwise Relatedness and Individual Inbreeding Coefficients.” Genetical Research 67, no. 2: 175–185. https://doi.org/10.1017/s0016672300033620.
Robasky, K., N. E. Lewis, and G. M. Church. 2014. “The Role of Replicates for Error Mitigation in Next‐Generation Sequencing.” Nature Reviews Genetics 15, no. 1: 56–62. https://doi.org/10.1038/nrg3655.
Ross, M. G., C. Russ, M. Costello, et al. 2013. “Characterizing and Measuring Bias in Sequence Data.” Genome Biology 14: 1–20. https://doi.org/10.1186/gb‐2013‐14‐5‐r51.
Saltz, D., and D. I. Rubenstein. 1995. “Population Dynamics of a Reintroduced Asiatic Wild Ass (Equus hemionus) Herd.” Ecological Applications 5, no. 2: 327–335. https://doi.org/10.2307/1942025.
Schoenecker, K. A., S. R. King, L. S. Ekernas, and S. J. Oyler‐McCance. 2021. “Using Fecal DNA and Closed‐Capture Models to Estimate Feral Horse Population Size.” Journal of Wildlife Management 85, no. 6: 1150–1161. https://doi.org/10.1002/jwmg.22056.
Schultz, A. J., K. Strickland, R. H. Cristescu, J. Hanger, D. de Villiers, and C. H. Frère. 2021. “Testing the Effectiveness of Genetic Monitoring Using Genetic Non‐invasive Sampling.” Ecology and Evolution 12, no. 1: e8459. https://doi.org/10.1002/ece3.8459.
Sims, D., I. Sudbery, N. E. Ilott, A. Heger, and C. P. Ponting. 2014. “Sequencing Depth and Coverage: Key Considerations in Genomic Analyses.” Nature Reviews Genetics 15, no. 2: 121–132. https://doi.org/10.1038/nrg3642.
Smith, O., and J. Wang. 2014. “When Can Noninvasive Samples Provide Sufficient Information in Conservation Genetics Studies?” Molecular Ecology Resources 14, no. 5: 1011–1023. https://doi.org/10.1111/1755‐0998.12250.
Smouse, P. E., and R. O. D. Peakall. 1999. “Spatial Autocorrelation Analysis of Individual Multiallele and Multilocus Genetic Structure.” Heredity 82, no. 5: 561–573. https://doi.org/10.1038/sj.hdy.6885180.
Song, K., L. Li, and G. Zhang. 2016. “Coverage Recommendation for Genotyping Analysis of Highly Heterologous Species Using Next‐Generation Sequencing Technology.” Scientific Reports 6: 35736. https://doi.org/10.1038/srep35736.
Städele, V., and L. Vigilant. 2016. “Strategies for Determining Kinship in Wild Populations Using Genetic Data.” Ecology and Evolution 6, no. 17: 6107–6120. https://doi.org/10.1002/ece3.2346.
Taberlet, P., and G. Luikart. 1999. “Non‐Invasive Genetic Sampling and Individual Identification.” Biological Journal of the Linnean Society 68, no. 1–2: 41–55. https://doi.org/10.1006/bijl.1999.0329.
Treangen, T. J., and S. L. Salzberg. 2012. “Repetitive DNA and Next‐Generation Sequencing: Computational Challenges and Solutions.” Nature Reviews Genetics 13, no. 1: 36–46. https://doi.org/10.1038/nrg3117.
Valiere, N., C. Bonenfant, C. Toïgo, G. Luikart, J. M. Gaillard, and F. Klein. 2007. “Importance of a Pilot Study for Non‐invasive Genetic Sampling: Genotyping Errors and Population Size Estimation in Red Deer.” Conservation Genetics 8: 69–78. https://doi.org/10.1007/s10592‐006‐9149‐2.
von Thaden, A., B. Cocchiararo, A. Jarausch, et al. 2017. “Assessing SNP Genotyping of Noninvasively Collected Wildlife Samples Using Microfluidic Arrays.” Scientific Reports 7, no. 1: 10768. https://doi.org/10.1038/s41598‐017‐10647‐w.
von Thaden, A., C. Nowak, A. Tiesmeyer, et al. 2020. “Applying Genomic Data in Wildlife Monitoring: Development Guidelines for Genotyping Degraded Samples With Reduced Single Nucleotide Polymorphism Panels.” Molecular Ecology Resources 20, no. 3: 662–680. https://doi.org/10.1111/1755‐0998.13136.
Waits, L. P., G. Luikart, and P. Taberlet. 2001. “Estimating the Probability of Identity Among Genotypes in Natural Populations: Cautions and Guidelines.” Molecular Ecology 10, no. 1: 249–256. https://doi.org/10.1046/j.1365‐294x.2001.01185.x.
Waits, L. P., and D. Paetkau. 2005. “Noninvasive Genetic Sampling Tools for Wildlife Biologists: A Review of Applications and Recommendations for Accurate Data Collection.” Journal of Wildlife Management 69, no. 4: 1419–1433. https://doi.org/10.2193/0022‐541X(2005)69[1419:NGSTFW]2.0.CO;2.
Wall, J. D., L. F. Tang, B. Zerbe, et al. 2014. “Estimating Genotype Error Rates From High‐Coverage Next‐Generation Sequence Data.” Genome Research 24, no. 11: 1734–1739. https://doi.org/10.1101/gr.168393.113.
Wang, J. 2010. “Effects of Genotyping Errors on Parentage Exclusion Analysis.” Molecular Ecology 19, no. 22: 5061–5078. https://doi.org/10.1111/j.1365‐294X.2010.04865.x.
Wang, J. 2011. “COANCESTRY: A Program for Simulating, Estimating, and Analyzing Relatedness and Inbreeding Coefficients.” Molecular Ecology Resources 11, no. 1: 141–145. https://doi.org/10.1111/j.1755‐0998.2010.02885.x.
Wang, J. 2016. “Individual Identification From Genetic Marker Data: Developments and Accuracy Comparisons of Methods.” Molecular Ecology Resources 16: 163–175. https://doi.org/10.1111/1755‐0998.12452.
Wang, J. 2017. “Estimating Pairwise Relatedness in a Small Sample of Individuals.” Heredity 119, no. 5: 302–313. https://doi.org/10.1038/hdy.2017.52.
Wang, J. 2019. “Pedigree Reconstruction From Poor Quality Genotype Data.” Heredity 122: 719–728. https://doi.org/10.1038/s41437‐018‐0178‐7.
Wang, C., H. Li, Y. Guo, et al. 2020. “Donkey Genomes Provide New Insights Into Domestication and Selection for Coat Color.” Nature Communications 11, no. 1: 6014. https://doi.org/10.1038/s41467‐020‐19813‐7.
Wang, J. 2002. “An Estimator for Pairwise Relatedness Using Molecular Markers.” Genetics 160, no. 3: 1203–1215. https://doi.org/10.1093/genetics/160.3.1203.
Wright, E. S., and K. H. Vetsigian. 2016. “Quality Filtering of Illumina Index Reads Mitigates Sample Cross‐Talk.” BMC Genomics 17, no. 1: 1–7. https://doi.org/10.1186/s12864‐016‐3217‐x.
Zecherle, L. J., H. J. Nichols, S. Bar‐David, et al. 2021. “Subspecies Hybridization as a Potential Conservation Tool in Species Reintroductions.” Evolutionary Applications 14, no. 5: 1216–1224. https://doi.org/10.1111/eva.13191.