Yang Da

Prakapenka, D.; Liang, Z.; Jiang, J.; Ma, L.; Da, Y. A large-scale genome-wide association study of epistasis effects of production traits and daughter pregnancy rate in U.S. Holstein cattle. Genes 2021, 12, 1089.
URL: https://www.mdpi.com/2073-4425/12/7/1089

Liang, Z., C. Tan, D. Prakapenka, L. Ma, and Y. Da. 2020. Haplotype Analysis of Genomic Prediction Using Structural and Functional Genomic Information for Seven Human Phenotypes. Frontiers in Genetics 11(1461).
URL: https://www.frontiersin.org/articles/10.3389/fgene.2020.588907/full

Prakapenka, D., C. Wang, Z. Liang, C. Bian, C. Tan, and Y. Da. 2020. GVCHAP: A computing pipeline for genomic prediction and variance component estimation using haplotypes and SNP Markers. Frontiers in Genetics 11(282).
URL: https://www.frontiersin.org/articles/10.3389/fgene.2020.00282/full 

Sallam, A. H., E. Conley, D. Prakapenka, Y. Da, and J. A. Anderson. 2020. Improving prediction accuracy using multi-allelic haplotype prediction and training population optimization in wheat. G3: Genes, Genomes, Genetics 10(7):2265-2273.
URL: https://www.g3journal.org/content/10/7/2265                     

Zhang, H., Q. Liang, N. Wang, Q. Wang, L. Leng, J. Mao, Y. Wang, S. Wang, J. Zhang, H. Liang, X. Zhiu, Y. Li, Z. Cao, P. Luan, Z. Wang, H. Yauan, Z. Wang, X. Zhou, S. J. Lamount, Y. Da, R. Li, S. Tian, Z. Du, and H. Li. 2020. Microevolutionary dynamics of chicken genomes under divergent selection for adiposity. iScience:101193.
URL: https://www.sciencedirect.com/science/article/pii/S2589004220303783

Jiang, J., L. Ma, D. Prakapenka, P. M. VanRaden, J. B. Cole, and Y. Da. 2019. A large-scale genome-wide association study in U.S. Holstein cattle. Frontiers in Genetics 10(412).
URL: https://www.frontiersin.org/articles/10.3389/fgene.2019.00412/full

Ma, L., T. S. Sonstegard, J. B. Cole, C. P. VanTassell, G. R. Wiggans, B. A. Crooker, C. Tan, D. Prakapenka, G. E. Liu, and Y. Da. 2019. Genome changes due to artificial selection in U.S. Holstein cattle. BMC genomics 20(1):128.
URL: https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-019-5459-x

Jiang, J., J. B. Cole, E. Freebern, Y. Da, P. M. VanRaden, and L. Ma. 2019. Functional annotation and Bayesian fine-mapping reveals candidate genes for important agronomic traits in Holstein bulls. Communications Biology 2(1):212.
URL: https://www.nature.com/articles/s42003-019-0454-y

Ma, L., J. Cole, Y. Da, and P. VanRaden. 2018. Symposium review: Genetics, genome-wide association study, and genetic improvement of dairy fertility traits. Journal of Dairy Science. 101:1-9. 
URL: https://www.journalofdairyscience.org/article/S0022-0302(18)30906-8/fulltext

Tan,C., Z. Wu, J. Ren, Z. Huang, D. Liu, X. He, D. Prakapenka, R. Zhang, N. Li, Y. Da, and X. Hu. 2017. Genome-wide association study and accuracy of genomic prediction for teat number in Duroc pigs using genotyping-by-sequencing. Genetics Selection Evolution 49:35.
URL: https://gsejournal.biomedcentral.com/articles/10.1186/s12711-017-0311-8

Garbe, J.R., D. Prakapenka, C. Tan, and Y. Da. 2016. Genomic inbreeding and relatedness in wild panda populations. PLoS ONE 11(8): e0160496. doi:10.1371/journal.pone.0160496.
URL: http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0160496

Yang, J., F. Shen, R. Hou, and Y. Da. 2016. Genetic composition of captive panda population. BMC Genetics: 17(1):1-9. doi: 10.1186/s12863-016-0441-y.
URL: https://bmcgenet.biomedcentral.com/articles/10.1186/s12863-016-0441-y

Da, Y. 2015. Multi-allelic haplotype model based on genetic partition for genomic prediction and variance component estimation using SNP markers. BMC Genetics 2015, 16:144. DOI: 10.1186/s12863-015-0301-1.
URL: http://bmcgenet.biomedcentral.com/articles/10.1186/s12863-015-0301-1

Ma, L., J.R. O'Connell, P.M. VanRaden, B. Shen, A. Padhi, C. Sun, D.M. Bickhart, J.B. Cole, D.J. Null, G.E. Liu, Y. Da, and G.R. Wiggans. 2015. Cattle sex-specific recombination and genetic control from a large pedigree analysis. PLoS Genetics 11(11): e1005387. doi:10.1371/journal.pgen.1005387
URL: http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1005387

Da, Y., C. Wang, S. Wang, and G. Hu. 2014. Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers. PLoS ONE 2014, 9(1): e87666. doi:10.1371/journal.pone.0087666. 
URL: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0087666

Feng, C., Y. Gao, B. Dorshorst, C. Song, X. Gu, Q. Li, J. Li, T. Liu, C-J. Rubin, Y. Wang, J. Fei, H. Li, K. Chen, H. Qu, D. Shu, C. Ashwell, Y. Da, L. Andersson, X. Hu, and N. Li. 2014. A cis-regulatory mutation of PDSS2 causes silky-feather in chickens. PLoS Genet. 10(8): e1004576. doi:10.1371/journal.pgen.1004576.
URL:  http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1004576

Hu, G., C. Wang, and Y. Da. 2014. Genomic heritability estimation for the early life-history transition related to propensity to migrate in wild rainbow and steelhead trout populations. Ecology and Evolution. doi: 10.1002/ece3.1038.
URL: http://onlinelibrary.wiley.com/doi/10.1002/ece3.1038/full

Wang, C., and Y. Da. 2014. Quantitative genetics model as the unifying model for defining genomic relationship and inbreeding coefficient. PLoS ONE 9(12): e114484. doi:10.1371/journal.pone.0114484.
URL: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0114484

Wang, C., D. Prakapenka, S. Wang, S. Pulugurta, H.B. Runesha, and Y. Da. 2014. GVCBLUP: A computer package for genomic prediction and variance component estimation of additive and dominance effects. BMC Bioinformatics 15:270. DOI: 10.1186/1471-2105-15-270.
URL: http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-270

Kim, E-S., J.B. Cole, H. Huson, G.R. Wiggans, C.P. Van Tassell, B.A. Crooker, G. Liu, Y. Da, and T.S. Sonstegard. 2013. Effect of artificial selection on runs of homozygosity in U.S. Holstein cattle. PLoS ONE 2013, 8(11): e80813. doi:10.1371/journal.pone.0080813
URL: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0080813

Ma, L., G.R. Wiggans, S. Wang, T.S. Sonstegard, J. Yang, B.A. Crooker, J.B. Cole, C.P Van Tassell, T.J. Lawlor, and Y. Da. 2012. Effect of sample stratification on dairy GWAS results. BMC Genomics 2012, 13:536.
URL: http://www.biomedcentral.com/1471-2164/13/536

Wang, S., D. Dvorkin, and Y. Da. 2012. SNPEVG: A graphical tool for GWAS graphing with mouse clicks. BMC Bioinformatics 2012, 13:319.
URL: http://www.biomedcentral.com/1471-2105/13/319/

Xie, L., C. Luo, C. Zhang, R. Zhang, J. Tang, Q. Nie, L. Ma, X. Hu, N. Li, Y. Da, and X. Zhang. 2012. Genome-wide association study identified a narrow chromosome 1 region associated with chicken growth traits. PLoS ONE 2012, 7(2):e30910.
URL: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0030910

Zhang, H., S.Z. Wang, Z.P. Wang, Y. Da, N. Wang, X.X. Hu, Y.D. Zhang, Y.X. Wang, L. Leng, Z.Q. Tang, and H. Li. 2012. A genome-wide scan of selective sweeps in two broiler chicken lines divergently selected for abdominal fat content. BMC Genomics 2012, 13:704.
URL: http://www.biomedcentral.com/1471-2164/13/704

Zhang, H., X. Hu, Z. Wang, Y. Zhang, S. Wang, Y. Zhang, S. Wang, N. Wang, L. Ma, L. Leng, S. Wang, Q. Wang, Y. Wang, Z. Tang, N. Li, and Y. Da. 2012. Selection signature analysis implicates the PC1/PCSK1 region for chicken abdominal fat content. PLoS ONE 2012 7(7): e40736. doi:10.1371/journal.pone.0040736.
URL: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0040736

Cole, J.B., G.R. Wiggans, L. Ma, T.S. Sonstegard, T.J. Lawlor, B.A. Crooker, C.P. Van Tassell, J. Yang, S. Wang, L.K. Matukumalli, and Y. Da. 2011. Genome-wide association analysis of thirty one production, health, reproduction and body conformation traits in contemporary U.S. Holstein cows. BMC Genomics 2011, 12(1):408.
URL: http://www.biomedcentral.com/1471-2164/12/408

Gu, X., C. Feng, L. Ma, C. Song, Y. Wang, Y. Da, H. Li, K. Chen, S. Ye, and C. Ge. 2011. Genome-wide association study of body weight in chicken F2 resource population. PLoS ONE 2011, 6(7):e21872.
URL: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0021872

Ma, L., S. Han, J. Yang, and Y. Da. 2010. Multi-locus test conditional on confirmed effects leads to increased power in genome-wide association studies. PLoS ONE 2010, 5(11):e15006.
URL: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0015006

Ma, L., J. Yang, H.B. Runesha, T. Tanaka, L. Ferrucci, S. Bandinelli, and Y. Da. 2010. Genome-wide association analysis of total cholesterol and high-density lipoprotein cholesterol levels using the Framingham Heart Study data. BMC Medical Genetics 2010, 11(1):55.
URL: http://www.biomedcentral.com/1471-2350/11/55

Ma, L., H.B. Runesha, D. Dvorkin, J.R. Garbe, and Y. Da. 2008. Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies. BMC Bioinformatics 2008, 9(1):315.
URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2503991/

Ma, L., D. Dvorkin, J.R. Garbe, and Y. Da. 2007. Genome-wide analysis of single-locus and epistasis single-nucleotide polymorphism effects on anti-cyclic citrullinated peptide as a measure of rheumatoid arthritis. BMC Proceedings 2007, 1(Suppl 1):S127
URL: http://www.biomedcentral.com/1753-6561/1/S1/S127

Mao, Y., N.R. London, L. Ma, D. Dvorkin, and Y. Da. 2006.  Detection of SNP epistasis effects of quantitative traits using an extended Kempthorne model. Physiological Genomics 2006, 28(1):46-52.
URL: http://physiolgenomics.physiology.org/content/28/1/46.full

Mao, Y., and Y. Da. 2005. Statistical power for detecting epistasis QTL effects under the F-2 design. Genetics Selection Evolution 2005, 37(2):129-150.
URL: http://www.biomedcentral.com/content/pdf/1297-9686-37-3-129.pdf

Da, Y. 2003. Statistical analysis and experimental design for mapping genes of complex traits in domestic animals. Acta Genetica Sinica 2003, 30(12):1183-1192.

Garbe, J., and Y. Da. 2003. A software tool for the graphical visualization of large and complex populations. Acta Genetica Sinica 2003, 30(12):2293-2295.

London, N.R., J.R. Garbe, S.M. Schmutz, M.S. Abrahamsen, and Y. Da. 2003. Linkage analysis for mapping genes of sex-influenced traits. Mammalian Genome 2003, 14(4):261-267.

Da, Y., J. Garbe, N. London, and J. Xu. 2002. Linkage analysis using direct and indirect counting and relative efficiencies for codominant and dominant loci. J. Animal Sci. 2002, 80(10):2528.

Da, Y., P.M. VanRaden, and L.B. Schook. 2000. Detection and parameter estimation for quantitative trait loci using regression models and multiple markers. Genetics Selection Evolution 2000, 32:357-381.

Yang Da. Genomic discovery and prediction for quantitative traits with complex genetic mechanisms, 5-minute talk, The 2023 NSF/NIH EDGE Awardee Meeting, National Science Foundation, October 10-11, 2023, Alexandria, Virginia.

Yang Da, Zuoxiang Liang, Dzianis Prakapenka. Sharply negative recessive alleles of reproduction traits in Holstein cows, Poster presentation, The 2023 NSF/NIH EDGE Awardee Meeting, National Science Foundation, October 10-11, 2023, Alexandria, Virginia.

Yang Da, Paul VanRaden, Li Ma, John Garbe, Christian Maltecca, Peter Hansen. 2021. Genetic Mechanism of Reproductive Heterosis in Dairy Cattle. Virtual poster presentation. The 2021 Animal Reproduction Project Director’s Meeting. December 14-15, 2021, St. Louis.

Da Y, Liang Z, Prakapenka D. Multifactorial methods integrating haplotype and epistasis effects for genomic estimation and prediction.

Bian, C., D. Prakapenka, C. Tan, R. Yang, D. Zhu, X. Guo, D. Liu, G. Cai, Y. Li, Z. Liang, Z. Wu, Yang Da, X. Hu. 2020. Haplotype genomic prediction based on chromosome distance and gene boundaries using low-coverage sequencing in Duroc pigs.

Prakapenka, D., C. Wang, Z. Liang, C. Bian, C. Tan and Y. Da. GVCHAP: A computing pipeline for genomic prediction and variance component estimation using haplotypes and SNP markers. 

Sallam, A., D. Prakapenka, E. Conley, Y. Da, J. Anderson. Improving prediction accuracy using multi-allelic haplotype prediction and training population optimization in wheat.

Jiang, J., L. Ma, D. Prakapenka, P. M. VanRaden, J. B. Cole, and Y. Da. 2019. A large-scale genome-wide association study in U.S. Holstein cattle. Frontiers in Genetics 10(412). Impact factor: 3.517 

Ma, L., T. S. Sonstegard, J. B. Cole, C. P. VanTassell, G. R. Wiggans, B. A. Crooker, C. Tan, D. Prakapenka, G. E. Liu, and Y. Da. 2019. Genome changes due to artificial selection in U.S. Holstein cattle. BMC genomics 20(1):128. Impact factor: 3.730 

Jiang, J., J. B. Cole, E. Freebern, Y. Da, P. M. VanRaden, and L. Ma. 2019. Functional annotation and Bayesian fine-mapping reveals candidate genes for important agronomic traits in Holstein bulls. Communications Biology 2(1):212. Impact factor: new journal 

Jiang, J., D. Prakapenka, L. Ma, J. B. Cole, P. M. VanRaden, and Y. Da. 2018. Extreme antagonistic pleiotropy effects of DGAT1 on fat, milk and protein yields. Proceedings of the World Congress on Genetics Applied to Livestock Production, 11.142.

Da, Y. 2017. Selection limits in dairy cattle. 19th Conf. on Animal Breeding and Genetics, Nanjing, China. Oct. 14-16. Invited Talk.

Ma, L., Y. Da, J. Durr, P. Vanraden, and J. Cole. 2017. Analytics of the large U.S. dairy cattle genomics and phenotype database. Livestock High-Throughput Phenotyping and Big Data Analytics, Beltsville, MD. Nov. 13-14. Oral Presentation.

Ma, L., J. Jiang, D. Prakapenka, M.E. Tooker, P.M. VanRaden, J.B. Cole, and Y. Da. 2017. Large-scale GWAS reveals reason for the DGAT1 significance and identifies new SNP effects in Holstein cattle. Livestock High-Throughput Phenotyping and Big Data Analytics, Beltsville, MD. Nov. 13-14. Poster Presentation.

Prakapenka, D., L. Ma, and Y. Da. 2017. Chromosome-specific genomic relationships using haplotypes for genomic prediction and variance component estimation. Plant and Animal Genome XXV, San Diego, CA. Jan. 13-18. Poster Presentation.

Tan, C., D. Prakapenka, L. Ma, Z. Wu, X. Hu, and Y. Da. 2017. JBLUP: The joint best linear unbiased prediction using BLUP and GBLUP solutions. Plant and Animal Genome XXV, San Diego, CA. Jan. 13-18. Poster Presentation.

Da, Y., C. Wang, C. Tan, D. Prakapenka, M. Shigematsu, J. Garbe, and L. Ma. 2015. Multi-allelic haplotype model to integrate functional genomic information with genomic prediction and variance component estimation. Poster Presentation. Plant and Animal Genome Conf., San Diego, CA. Jan. 11.

Sonstegard, T., L. Ma, E-S. Kim, C. Van Tassell, G. Wiggans, B. Crooker, J. Cole, G. Liu, S. Fahrenkrug, A. Ponce de León, and Y. Da. 2015. Genome changes due to forty years of artificial selection associated with divergent dairy production and reproduction. Invited Presentation. Cattle/Sheep/Goat Workshop 2. 2015 Plant and Animal Genome Conf., San Diego, CA. Jan. 11.

Gu, X., J.R. Garbe, C. Luo, Z. Sheng, H. Qu, X. Zhang, D. Shu, N. Li, Y. Da, and X. Hu. 2014. Linkage analysis to improve the chicken genome assembly. 34th Internatl. Soc. for Anim. Genetics Conf. Poster presentation.

Hu, Z-L., J.R. Garbe, J.M. Reecy, M.F. Rothschild, Y. Da, and J.C.M. Dekkers. 2014. Linkage analysis to improve the swine genome assembly. 34th Internatl. Soc. for Anim. Genetics Conf. Poster presentation.

Wang, C., D. Prakapenka, H.B. Runesha, and Y. Da. 2014. Parallel computing for mixed model implementation of genomic prediction and variance component estimation of additive and dominance effects. 10th World Congr. of Genetics Applied to Livestock Prod., Vancouver, Canada. Aug. 17-22. Oral and poster presentations.
URL: https://www.asas.org/docs/default-source/wcgalp-proceedings-oral/158_paper_8748_manuscript_1615_0.pdf?sfvrsn=2

Da, Y. 2011. Quantitative genetics: A bridge between theory, practice and technology. Contributed paper to the Symposium on Animal Breeding and Genetics in Honor of Professor Wu Zongxian's 100th Birthday, China Agricultural University, May 2011.

Cole, J.B., G.R. Wiggans, L. Ma, T.A. Sonstegard, B.A. Crooker, C.P. Van Tassell, J. Yang, L.K. Matukumalli, and Y. Da. 2010. High resolution QTL maps of 31 traits in contemporary U.S. Holstein cows. Proc. 9th World Congr. Genet. Appl. Livest. Prod., Leipzig, Germany, Aug. 1–6. Comm. 464, 4 p.

Sonstegard, T.S., L. Ma, C.P. Van Tassell, E-S. Kim, J.B. Cole, G.R. Wiggans, B.A. Crooker, B.D. Mariani, L.K. Matukumalli, J.R. Garbe, S.C. Fahrenkrug, G. Liu, and Y. Da. 2010. Forty years of artificial selection in U.S. Holstein cattle had genome-wide signatures. Poster presentation at 9th World Congr. Genet. Appl. Livest. Prod., Leipzig, Germany, Aug. 1-6. Comm. 464, 4 pp.

Da, Y. 2009. Genome changes due to 40 years of artificial selection and genome-wide association study in U.S. Holstein cattle. Workshop on Holstein Management and Breeding, Hohhot, Inner Mongolia, China. Aug. 14-15.

Da, Y. 2009. Genome-wide association analysis. Animal Science Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China. Aug. 11.

Ma, L., D. Dvorkin, J.R. Garbe, and Y. Da. 2007. Genome-wide analysis of single-locus and epistasis SNP effects on anti-cyclic citrullinated peptide as a measure of rheumatoid arthritis. BMC Proceedings:1(Suppl. 1):S127.

London, N. and Y. Da. 2006. Statistical power and sample size requirement for QTL detection. Proc. 8th World Congress on Genetics Applied to Livestock Production, edited by B.D. Valente, O. Rossi de Morais, and R.V. Ventura. Belo Horizonte, Brazil: Instituto Prociência. Vol. 22: Article #18.

Ma, L., D. Dvorkin, and Y. Da. 2006. Genome-wide analysis of single-locus and epistasis SNP effects on anti-cyclic citrullinated peptide. In: Participant Contributions, Genetic Analysis Workshop 15, pp. 13-54 ~ 13-56. St. Petersburg Beach, FL. Nov. 12-15.

Mao, Y. and Y. Da. 2006. Statistical power and sample size for QTL detection using flanking markers under the f-2 design. Proc.  8th World Congress on Genetics Applied to Livestock Production, edited by B.D. Valente, O. Rossi de Morais, and R.V. Ventura. Belo Horizonte, Brazil: Instituto Prociência. Vol. 23: Article #19.

Da, Y., N. London, and J. Xu. 2002. Partition of genotypic variance for two linked loci under the F-2 design for QTL mapping. Proc. 7th World Cong. Genet. Appl. Livest. Prod., Montpellier, France 32: 737-740.

London, N., J. Xu, J. Garbe, and Y. Da. 2002. Linkage analysis for the hypothesized interaction between the polled and scurred traits in cattle. Proc. 7th World Cong. Genet. Appl. Livest. Prod., Montpellier, France 29: 485-488.

Xu, J., N. London, J. Garbe, and Y. Da. 2002. Bias in linkage analysis due to ignoring epistasis effects. Proc. 7th World Cong. Genet. Appl. Livest. Prod., Montpellier, France 32: 633-636.

Da, Y. 2001. Partitioning of genotypic value and variance for two quantitative trait loci with linkage. Symposium on Animal Breeding and Genetics in Honor of Professor Wu Zongxian's 90th Birthday, pp. 59-67, China Agricultural University, May 11-12.

Da, Y., T. Sonstegard, B. Crooker, L. Hansen, H. Chester-Jones, M. Fahning, B. Seguin, G. Marx, G.C. Lamb, and F.A. Ponce de León. 2000. Designs of resource populations for dairy QTL mapping. W.E. Petersen Lecture. Dairy Genomics: Trends and Opportunities. University of Minnesota, St. Paul, MN. Dec. 11-12.

Da, Y., M. Ron, A. Yanai, M. Band, R.E. Everts, D.W. Heyen, J.I. Weller, G.R. Wiggans, and H.A. Lewin. 1994. The dairy bull DNA repository: A resource for mapping quantitative trait loci. 5th Congress of Genetics Applied to Livestock Production. 21:229-232.

Da. Y. 2019. Mixed model methods for genetic analysis. Classnotes for AnSc 8141. Department of Animal Science, University of Minnesota. https://animalgene.umn.edu/sites/animalgene.umn.edu/files/ansc8141_2019.pdf 

Prakapenka, D., C. Wang, Z. Liang, C. Bian, C. Tan and Y. Da. GVCHAP User Manual Version 2.1. 

Da, Y. 2012. Mixed Model Methods for Genetic Analysis. AnSc 8141 supplementary classnotes, 2 credits, 75 pages plus instructor's computer programs and in-class derivations. Department of Animal Science, University of Minnesota.

Wang, S., L. Ma, and Y. Da. 2012. AGDP: A software tool for the analysis of genome differences between populations. User manual version 21.1, 18 pages. Department of Animal Science, University of Minnesota.

Wang, S., D. Dvorkin, and Y. Da. 2012. SNPEVG: a graphical tool for SNP effect viewing and graphing. User manual version 3.1, 41 pages. Department of Animal Science, University of Minnesota. URL: http://animalgene.umn.edu

Ma, L., J. Garbe, H.B. Runesha, and Y. Da. 2011. epiSNP: a computer package of parallel and serial computing programs for single-locus and epistasis testing in genome-wide association studies. User manual version 4.2, 22 pages. Department of Animal Science, University of Minnesota.

Da, Y. 2007. Statistical Genetics and Genomics. Department of Animal Science, University of Minnesota.

Ma, L., D. Dvorkin, and Y. Da. 2006. EpiSNP User Manual Version 1.0w. Department of Animal Science, University of Minnesota. URL: http://animalgene.umn.edu.

Garbe, J.R. and Y. Da. 2005. Pedigraph user manual Version 2.2. Department of Animal Science, University of Minnesota. URL: http://animalgene.umn.edu

Prakapenka, D., C. Wang, Z. Liang, C. Bian, C. Tan and Y. Da. GVCHAP User Manual Version 2.1.

Garbe, J.R. and Y. Da. 2004. MiniInbred, a computer program to minimize inbreeding in breeding plans. URL: http://animalgene.umn.edu

Garbe, J.R. and Y. Da. 2004. Pedigraph 2.0, a computer program for pedigree/genealogy visualization of large, complex pedigrees. URL: http://animalgene.umn.edu

Liang, Z., D. Prakapenka, and Y. Da. 2021a. EPIHAP: a computing tool for genomic estimation and prediction using global epistasis effects and haplotype effects. Abstract P167, page 223 of ADSA2021 Abstracts, ADSA 2021 Virtual Annual Meeting. URL: https://www.adsa.org/Portals/0/SiteContent/Docs/Meetings/2021ADSA/ADSA2021_Abstracts.pdf.

Liang, Z., D. Prakapenka, and Y. Da. 2021b. Genomic heritability and prediction accuracy of epistasis effects for production and fertility traits in U.S. Holstein cattle. Abstract P170, page 224 of ADSA2021 Abstracts, ADSA 2021 Virtual Annual Meeting. URL: https://www.adsa.org/Portals/0/SiteContent/Docs/Meetings/2021ADSA/ADSA2021_Abstracts.pdf.

Liang, Z., D. Prakapenka, P. M. VanRaden, and Y. Da. 2021c. Genomic heritability and prediction accuracy of additive and nonadditive effects for daughter pregnancy rate in crossbred dairy cows. Abstract P168, page 224 of ADSA2021 Abstracts, ADSA 2021 Virtual Annual Meeting. URL: https://www.adsa.org/Portals/0/SiteContent/Docs/Meetings/2021ADSA/ADSA2021_Abstracts.pdf.

Prakapenka, D., Z. Liang, J. Jiang, L. Ma, and Y. Da. 2021a. Genome-wide association study of epistasis effects associated with production and fertility traits in U.S. Holstein cattle. Abstract P171, page 224 of ADSA2021 Abstracts, ADSA 2021 Virtual Annual Meeting. URL: https://www.adsa.org/Portals/0/SiteContent/Docs/Meetings/2021ADSA/ADSA2021_Abstracts.pdf.

Prakapenka, D., Z. Liang, P. M. VanRaden, J. Jiang, L. Ma, J. R. Garbe, C. Melticca, P. J. Hansen, and Y. Da. 2021b. Genetic mechanisms of reproductive heterosis in crossbred dairy cows involve genome-wide additive and nonadditive effects. Abstract P169, page 224 of ADSA2021 Abstracts, ADSA 2021 Virtual Annual Meeting. URL: https://www.adsa.org/Portals/0/SiteContent/Docs/Meetings/2021ADSA/ADSA2021_Abstracts.pdf.

Ma, L., J. Jiang, D. Prakapenka, J. B. Cole and Y. Da. 2019. Approximate generalized least squares method for large-scale genome-wide association study. Poster presentation. ADSA Annual Meeting, Cincinnati. 

Prakapenka, D. and Y. Da. 2019. Computing pipeline for genomic prediction and estimation using haplotypes and SNP markers. Poster presentation. ADSA Annual Meeting, Cincinnati. 

Jiang, J., D. Prakapenka, L. Ma, J. B. Cole, P. M. VanRaden, and Y. Da. 2018. Extreme antagonistic pleiotropy effects of DGAT1 on fat, milk and protein yields. Proceedings of the World Congress on Genetics Applied to Livestock Production, 11.142.

Sallam, A., D. Prakapenka, E. Conley, Y. Da, J. Anderson. 2018. Genomic prediction in wheat using fixed-length haplotypes. Poster presentation at Plant Breeding Symposium at the University of Minnesota.

Da, Y., C. Tan, and D. Prakapenka. 2016. Integrated SNP-haplotype genomic selection based on the invariance property of GBLUP and GREML to duplicate SNPs. 2016 Joint Annual Mtg. ASAS-ADSA-CSAS-WSASAS, Salt Lake City, UT. July 19-23.

Garbe, J.R., D. Prakapenka, J. Yang, C. Tan, C. Wang, and Y. Da. 2016. Genomic inbreeding and relationships in wild panda populations. Plant and Animal Genome XXIV Conf., San Diego, CA. Jan. 9-13. Abstr. P0694.

Tan, C., Y. Da, Z. Wu, D. Liu, N. Li, and X. Hu. 2016. Genome-wide association study and accuracy of genomic prediction for teat number in Duroc pigs using genotyping by sequencing. 2016 Joint Annual Mtg. ASAS-ADSA-CSAS-WSASAS, Salt Lake City, UT. July 19-23.

Tan, C., Y. Da, Z. Wu, D. Liu, N. Li, and X. Hu. 2016. Genotyping-by-sequencing for genomic evaluation in pigs. Plant and Animal Genome XXIV Conf., San Diego, CA. Jan. 9-13. Abstr. P0365.

Da, Y., C. Wang, C. Tan, D. Prakapenka, M. Shigematsu, J.R. Garbe, and L. Ma. 2015. Multi-allelic haplotype model to integrate functional genomic information with genomic prediction and estimation. Plant and Anim. Genome XXIII, San Diego, CA. Jan. 10-14. Abstr. P1176.
URL: https://pag.confex.com/pag/xxiii/webprogram/Paper14435.html

Ma, L., T.S. Sonstegard, C.P. VanTassell, J.B. Cole, G.R. Wiggans, B.A. Crooker, F.A. Ponce de, and Y. Da. 2015. Selection signature analysis in Holstein cattle identified genes known to affect reproduction. ADSA/ASAS 2015, Orlando, FL, July 12-16. Abstr. T102.
URL: http://m.jtmtg.org/abs/t/64127

Tan, C., D. Prakapenka, C. Wang, L. Ma, J.R. Garbe, and Y. Da. 2015. Integration of haplotype analysis of functional genomic information with single SNP analysis improved accuracy of genomic prediction. ADSA/ASAS 2015, Orlando, FL, July 12-16. Abstr. M84.
URL:  http://m.jtmtg.org/abs/t/65063

Tan, C., J. Ren, Z. Huang, Y. Zhao, Y. D., X. Hu. 2015. An improved approach for swine SNP genotyping using Genotyping-by-Sequencing. ADSA/ASAS 2015, Orlando, FL, July 12-16. Abstract M78. http://m.jtmtg.org/abs/t/65275

Cole, J.B., T.S. Sonstegard, L. Ma, G. R. Wiggans, B.A. Crooker, C.P. Van Tassell, J. Yang, L.K. Matukumalli, and Y. Da. 2010. High resolution QTL map of net merit component traits and calving traits from genome-wide association analysis in contemporary U.S. Holstein cows. Abstract and Poster #P565 at Plant and Animal Genome XVIII, San Diego, CA. Jan. 9-13.

Ma, L., T.S. Sonstegard, J.B. Cole, G.R. Wiggans, B.A. Crooker, C.P. Van Tassell, J. Yang, L.K. Matukumalli, and Y. Da. 2010. X chromosome SNPs were heavily involved in epistasis effects of net merit component traits in contemporary U.S. Holstein cows. Abstract and Poster #P542 at Plant and Animal Genome XVIII, San Diego, CA. Jan. 9-13.

Wiggans, G.R., L. Ma , T.S. Sonstegard, J.B. Cole, B.A. Crooker, C.P. Van Tassell, J. Yang, L.K. Matukumalli, and Y. Da. 2010. High resolution QTL map of body conformation traits from genome-wide association analysis in contemporary U.S. Holstein cows. Abstract and Poster #P547 at Plant and Animal Genome XVIII, San Diego, CA. Jan. 9-13.

Ma, L., T.S. Sonstegard, J.B. Cole, G.R. Wiggans, B.A. Crooker, C.P. Van Tassell, and Y. Da. 2009. Preliminary results of genome-wide association analysis of nine traits in Holstein Cows. Poster Presentation at Symposium on Statistical Genetics of Livestock for the Post-Genomic Era, Madison, WI. May 4-6.

Sonstegard, T.S. L. Ma, J.B. Cole, G.R. Wiggans, B.A. Crooker, C.P. Van Tassell, B.D. Mariani, and Y. Da. 2009. Genome signature of artificial selection for milk yield in Holstein cattle. Abstract and Poster Presentation at Plant and Animal Genome XVII, San Diego, CA. Jan. 10-14.

Sonstegard, T.S., L. Ma, J.B. Cole, G.R. Wiggans, B.A. Crooker, C.P. Van Tassell, B.D. Mariani, P.M. Van Raden, M.V. da Silva, and Y. Da. 2008. Genomic signatures of artificial selection in U.S. Holstein cows. (Oral and Poster Presentation.) Conf. International Society of Animal Genetics, Amsterdam, The Netherlands. July 20-24.

Duan, Y., J. Garbe, N. London. L. Ma, and Y. Da. 2006. A computer program for detecting additive, dominance, imprinting, sex-influenced and the overall QTL effects. Abstract #32, Joint Ann. Mtg. of American Dairy Sci. Assoc. and American Animal Sci. Assoc., Minneapolis, MN.

Ma, L., D. Dvorkin, and Y. Da. 2006. Large scale SNP epistasis detection of complex traits using pairwise epistasis tests. IGES 15th Ann. Mtg., St. Pete Beach, FL. Nov. 16-17. p. 55.

Da, Y. and Y. Mao. 2005. Detection of epistasis effects of biallelic candidate genes of complex traits. Program and Abstract Book, p.55, Human Genome Meeting, Tokyo. April 18-21.

Garbe, J.R. and Y. Da. 2004. A computerized approach to minimize inbreeding of breeding plans. ADSA-ASAS-PSA Joint Annual Meeting, St. Louis, MO. July 25-29. p. 376.

Garbe, J.R. and Y. Da. 2004. Graphical visualization of two large complex populations using Pedigraph 2.0. ADSA-ASAS-PSA Joint Annual Meeting, St. Louis, MO. July 25-29. p. 377.

Garbe, J.R. and Y. Da. 2004. Pedigraph 2.0 - A software tool for the graphing and analysis of large complex pedigrees. ADSA-ASAS-PSA Joint Annual Meeting, St. Louis, MO. July 25-29. p. 242.

London, N.R. and Y. Da. 2004. Statistical methods to detect imprinted QTL with gender specific recombination frequencies. ADSA-ASAS-PSA Joint Annual Meeting, St. Louis, MO. July 25-29. p. 416.

Mao, Y. and Y. Da. 2004. Statistical power for detecting epistasis QTL effects under the F-2 Design. ADSA-ASAS-PSA Joint Annual Meeting, St. Louis, MO. July 25-29. p. 414.

Xu, J., J.R. Garbe, N.R. London, Y. Mao, and Y. Da. 2004. Evaluation of three statistical methods for QTL analysis. ADSA-ASAS-PSA Joint Annual Meeting, St. Louis, MO. July 25-29. p. 243.

Garbe, J.R. and Y. Da. 2003. Genealogy graphing for large complex populations: the example of European royal genealogy data. Journal of American Human Genetics, Supplement to Vol. 73, p. 605, 53rd Annual Meeting of the American Society of Human Genetics.

Garbe, J. and Y. Da. 2003. Pedigraph, a software tool for the graphical visualization of large complex pedigrees. Final Abstracts Guide, p. 293. Plant and Animal Genome XI, San Diego, CA. Jan. 11-15.

Garbe, J., N. London, and Y. Da. 2003. Locusmap, a linkage map construction tool for loci with various inheritance modes. Final Abstracts Guide, p. 305. Plant and Animal Genome XI, San Diego, CA. Jan. 11 15.

London, N.R. and Y. Da. 2003. Optimum marker spacing for QTL detection. Journal of American Human Genetics, Supplement to Vol. 73, p. 615, 53rd Annual Meeting of the American Society of Human Genetics.

London N. and Y. Da. 2003. Statistical power for detecting additive and dominance QTL effects under the reciprocal backcross and F-2 designs. Final Abstracts Guide, p. 254. Plant and Animal Genome XI, San Diego, CA. Jan. 11-15.

Xu, J. and Y. Da. 2003. Genetic sampling and chiasm interference affect QTL mapping accuracy. J. of American Human Genetics, Supplement to Vol. 73, p. 617, 53rd Annual Meeting of the American Society of Human Genetics.

Chrystal, M.A., Y. Da, L.B. Hansen, and A.J. Seykora. 2001. Accuracy of marker assisted selection using a mixed model method. Abstract book, p. 191, International Animal Agriculture and Food Science Conference, Indianapolis, IN. July 24-28.

Da, Y. 2001. A rapid method for linkage analysis using direct and indirect counting. In: Final Abstracts Guide, p. 151. Plant and Animal Genome IX, San Diego, CA. Jan. 14-17.

Da, Y. 2001. Parameter estimation of epistasis effects using orthogonal marker contrasts. Abstract book, p. 191, International Animal Agriculture and Food Sci. Conf., Indianapolis, IN. July 24-28.

Xu, J. and Y. Da. 2001. A heterogeneity model for estimating the number of alleles of a quantitative trait locus. Abstract book, p. 340, International Animal Agriculture and Food Sci. Conf., Indianapolis, IN. July 24-28.

Xu, J. and Y. Da. 2001. Inversion-free method for variance component estimation under the animal model. Abstract book, p. 341, International Animal Agriculture and Food Science Conference, Indianapolis, IN. July 24-28.

Chrystal, M.A., Y. Da, L.B. Hansen, and A.J. Seykora. 2000. A mixed model method for QTL detection and marker assisted selection. In: Conference Abstract Book, p. 9, ISAG 2000, 27th International Conference on Animal Genetics, Minneapolis, MN. July 22-26.

Da, Y. 2000. Detection and parameter estimation for dominance effects of quantitative trait loci. In: Conference Abstract Book, p. 5, ISAG 2000, 27th International Conference on Animal Genetics, Minneapolis, MN. July 22-26.

London, N.R. 2004. Statistical theory and methods for mapping gender-affected genes and quantitative trait loci. Ph.D. Thesis. Department of Animal Science and Program in Molecular Veterinary Bioscience, University of Minnesota.

Xu, J. 2004. Statistical analysis for mapping linked quantitative trait loci. Ph.D. Thesis. Department of Animal Science, University of Minnesota.

Chrystal, M.A. 2003. Marker assisted selection in dairy cattle using a mixed model approach. Ph.D. Thesis. Department of Animal Science, University of Minnesota.

Prakapenka, D. and Y. Da. 2019. Computing pipeline for genomic prediction and estimation using haplotypes and SNP markers. Abstract #M65, American Dairy Science Association Annual Meeting. June 23-26, 2019. Cincinnati.  https://m.adsa.org/2019/abs/t/78856. [poster - PDF]

Ma, L., J. Jiang, D. Prakapenka, J. B. Cole, and Y. Da. 2019. Approximate generalized least squares method for large-scale genome-wide association study. Abstract #M64, American Dairy Science Association Annual Meeting. June 23-26, 2019. Cincinnati.  https://m.adsa.org/2019/abs/t/78854. [poster - PDF]

Garbe JR, Prakapenka D, Tan C, Da Y. 2019. Genomic Inbreeding and Relatedness in Wild Panda Populations. 2019 Showcase of Department of Animal Science, University of Minnesota. [poster - PDF]

Da, Y. 2017. Selection limits in dairy cattle. The 19th Animal Breeding and Genetic Conference. October 14-16, Nanjing, China. [slides - PDF]