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Center for Quantitative Genetics and Genomics

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Cao, L., Mulder, H. A., Liu, H., Nielsen, H. M. & S⊘rensen, A. C. (2021). Competitive gene flow does not necessarily maximize the genetic gain of genomic breeding programs in the presence of genotype-by-environment interaction. Journal of Dairy Science, 104(7), 8122-8134. https://doi.org/10.3168/jds.2020-19823

Milkevych, V., Madsen, P., Gao, H. & Jensen, J. (2021). The relative effect of genomic information on efficiency of Bayesian analysis of the mixed linear model with unknown variance. Journal of Animal Breeding and Genetics (Online), 138(1), 14-22. https://doi.org/10.1111/jbg.12497, https://doi.org/10.1111/jbg.12497

Madsen, M. D., Villumsen, T. M., Hansen, B. K., Møller, S. H., Jensen, J. & Shirali, M. (2020). Combined analysis of group recorded feed intake and individually recorded body weight and litter size in mink. Animal : an international journal of animal bioscience, 14(9), 1793-1801. https://doi.org/10.1017/S1751731120000762

Wang, L., Janss, L. L., Madsen, P., Henshall, J., Huang, C.-H., Marois, D., Alemu, S., Sørensen, A. C. & Jensen, J. (2020). Effect of genomic selection and genotyping strategy on estimation of variance components in animal models using different relationship matrices. Genetics, selection, evolution : GSE, 52(1), Article 31. https://doi.org/10.1186/s12711-020-00550-w

Tsai, H.-Y., Janss, L. L., Andersen, J. R., Orabi, J., Jensen, J. D., Jahoor, A. & Jensen, J. (2020). Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat. Scientific Reports, 10(1), Article 3347. https://doi.org/10.1038/s41598-020-60203-2

Liu, A., Lund, M. S., Boichard, D. A., Karaman, E., Fritz, S., Aamand, G. P., Nielsen, U. S., Wang, Y. & Su, G. (2020). Improvement of genomic prediction by integrating additional single nucleotide polymorphisms selected from imputed whole genome sequencing data. Heredity, 124(1), 37-49. https://doi.org/10.1038/s41437-019-0246-7

Tessema, B. B., Liu, H., Sørensen, A. C., Andersen, J. R. & Jensen, J. (2020). Strategies Using Genomic Selection to Increase Genetic Gain in Breeding Programs for Wheat. Frontiers in Genetics, 11, Article 578123. https://doi.org/10.3389/fgene.2020.578123

Mesbah-Uddin, M., Hoze, C., Michot, P., Barbat, A., Lefebvre, R., Boussaha, M., Sahana, G., Fritz, S., Boichard, D. & Capitan, A. (2019). A missense mutation (p.Tyr452Cys) in the CAD gene compromises reproductive success in French Normande cattle. Journal of Dairy Science, 102(7), 6340-6356. https://doi.org/10.3168/jds.2018-16100

Gebreyesus, G., Buitenhuis, A. J., Poulsen, N. A., Visker, M. H. P. W., Zhang, Q., van Valenberg, H. J. F., Sun, D. & Bovenhuis, H. (2019). Combining multi-population datasets for joint genome-wide association and meta-analyses: The case of bovine milk fat composition traits. Journal of Dairy Science, 102(12), 11124-11141. https://doi.org/10.3168/jds.2019-16676

Cai, Z., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2019). Dissecting closely linked association signals in combination with the mammalian phenotype database can identify candidate genes in dairy cattle. BMC Genetics, 20, Article 15. https://doi.org/10.1186/s12863-019-0717-0

Kristensen, P. S., Jensen, J., Andersen, J. R., Guzmán, C., Jihad, O. & Jahoor, A. (2019). Genomic Prediction and Genome-Wide Association Studies of Flour Yield and Alveograph Quality Traits Using Advanced Winter Wheat Breeding Material. Genes, 10(9), Article 669. https://doi.org/10.3390/genes10090669

Mesbah-Uddin, M., Guldbrandtsen, B., Lund, M. S., Boichard, D. & Sahana, G. (2019). Joint imputation of whole-genome sequence variants and large chromosomal deletions in cattle. Journal of Dairy Science, 102(12), 11193-11206. https://doi.org/10.3168/jds.2019-16946

Gebreyesus, G., Buitenhuis, A. J., Poulsen, N. A., Visker, M. H. P. W., Zhang, Q., van Valenberg, H. J. F., Sun, D. & Bovenhuis, H. (2019). Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition. BMC Genomics, 20, Article 178. https://doi.org/10.1186/s12864-019-5573-9

Gebreyesus, G., Bovenhuis, H., Lund, M. S., Poulsen, N. A., Sun, D. & Buitenhuis, B. (2019). Reliability of genomic prediction for milk fatty acid composition by using a multi-population reference and incorporating GWAS results. Genetics Selection Evolution, 51(1), Article 16. https://doi.org/10.1186/s12711-019-0460-z

Ørsted, M., Hoffmann, A. A., Rohde, P. D., Sørensen, P. & Kristensen, T. N. (2019). Strong impact of thermal environment on the quantitative genetic basis of a key stress tolerance trait. Heredity, 122(3), 315-325. https://doi.org/10.1038/s41437-018-0117-7

Marete, A. G., Guldbrandtsen, B., Lund, M. S., Fritz, S., Sahana, G. & Boichard, D. (2018). A Meta-Analysis Including Pre-selected Sequence Variants Associated With Seven Traits in Three French Dairy Cattle Populations. Frontiers in Genetics, 9, Article 522. https://doi.org/10.3389/fgene.2018.00522

Jardim, J. G., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2018). Association analysis for udder index and milking speed with imputed whole-genome sequence variants in Nordic Holstein cattle. Journal of Dairy Science, 101(3), 2199-2212. https://doi.org/10.3168/jds.2017-12982

Marete, A. G., Lund, M. S., Boichard, D. A. & Ramayo-Caldas, Y. (2018). A system-based analysis of the genetic determinism of udder conformation and health phenotypes across three French dairy cattle breeds. PLoS One, 13(7), Article e0199931. https://doi.org/10.1371/journal.pone.0199931

Esfandyari, H., Berg, P. & Sørensen, A. C. (2018). Balanced selection on purebred and crossbred performance increases gain in crossbreds. Genetics Selection Evolution, 50(1), Article 8. https://doi.org/10.1186/s12711-018-0379-9

Ørsted, M., Rohde, P. D., Hoffmann, A. A., Sørensen, P. & Kristensen, T. N. (2018). Environmental variation partitioned into separate heritable components. Evolution, 72(1), 136-152. https://doi.org/10.1111/evo.13391

Boichard, D. A., Boussaha, M., Capitan, A., Rocha, D., Hoze, C., Sanchez, M.-P., Tribout, T., Letaief, R., Croiseau, P., Grohs, C., Li, W., Harland, C., Charlier, C., Lund, M. S., Sahana, G., Georges, M., Barbier, S., Coppieters, W., Fritz, S. & Guldbrandtsen, B. (2018). Experience from large scale use of the EuroGenomics custom SNP chip in cattle. In Proceedings of the World Congress on Genetics Applied to Livestock Production: Volume Molecular Genetics 4 (Vol. 11). Article 11.675 http://www.wcgalp.org/proceedings/2018/experience-large-scale-use-eurogenomics-custom-snp-chip-cattle

Marete, A. G., Janss, L., Guldbrandtsen, B., Hoze, C., Sahana, G., Boichard, D. A. & Lund, M. S. (2018). Exploring non-additive variance using genome-wide dense SNP in four French and Nordic dairy cattle breeds. In Proceedings of the World Congress on Genetics Applied to Livestock Production Article 70

Rohde, P. D., Østergaard, S., Kristensen, T. N., Sørensen, P., Loeschcke, V., F C Mackay, T. & Sarup, P. M. (2018). Functional validation of candidate genes detected by genomic feature models. G3: Genes, Genomes, Genetics (Bethesda), 8(5), 1659-1668. https://doi.org/10.1534/g3.118.200082

Marete, A. G., Sahana, G., Fritz, S., Lefebvre, R., Barbat, A., Lund, M. S., Guldbrandtsen, B. & Boichard, D. (2018). Genome-wide association study for milking speed in French Holstein cows. Journal of Dairy Science, 101(7), 6205-6219. https://doi.org/10.3168/jds.2017-14067

Gebreyesus, G., Buitenhuis, A. J., Poulsen, N. A., Visker, M. H. P. W., Zhang, Q., van Valenberg, H. J. F., Sun, D. & Bovenhuis, H. (2018). Genome-wide association study of the de novo synthesized milk fatty acids based on Dutch, Danish and Chinese Holstein Friesians. 141. Abstract from The 11th World Congress on Genetics Applied to Livestock Production , Auckland, New Zealand.

Mesbah-Uddin, M., Guldbrandtsen, B., Iso-Touru, T., Vilkki, J., De Koning, D.-J., Boichard, D., Lund, M. S. & Sahana, G. (2018). Genome-wide mapping of large deletions and their population-genetic properties in dairy cattle. D N A Research, 25(1), 49-59. https://doi.org/10.1093/dnares/dsx037

Rohde, P. D., Sørensen, I. F. & Sørensen, P. (2018). Genomic Feature Prediction Models - Improved Prediction Accuracy by Joint Marker Estimation. Poster session presented at ESHG 2018: European Society of Human Genetics, Milano, Italy.

Xiang, T., Christensen, O. F., Vitezica, Z. G. & Legarra, A. (2018). Genomic model with correlation between additive and dominance effects. Genetics, 209(3), 711-723. https://doi.org/10.1534/genetics.118.301015

Guo, X., Cericola, F., Fè, D., Pedersen, M. G., Lenk, I., Jensen, C. S., Jensen, J. & Janss, L. L. (2018). Genomic prediction in tetraploid ryegrass using allele frequencies based on genotyping by sequencing. Frontiers in Plant Science, 9, Article 1165. https://doi.org/10.3389/fpls.2018.01165

Villumsen, T. M., Su, G., Cai, Z., Guldbrandtsen, B., Asp, T., Sahana, G. & Lund, M. S. (2018). Genomic selection in mink yield higher accuracies with a Bayesian approach allowing for heterogeneous variance than a GBLUP model. In Proceedings of the World Congress on Genetics Applied to Livestock Production, 2018: Volume Methods and Tools - Prediction 2 Article 11.618 http://www.wcgalp.org/proceedings/2018/genomic-selection-mink-yield-higher-accuracies-bayesian-approach-allowing

Guldbrandtsen, B., Cai, Z., Sahana, G., Villumsen, T. M., Asp, T., Thomsen, B. & Lund, M. S. (2018). Genomics using the Assembly of the Mink Genome. In Proceedings of the World Congress on Genetics Applied to Livestock Production, 2018: Volume Electronic Poster Session - Molecular Genetics 1 Article 539 http://www.wcgalp.org/proceedings/2018/genomics-using-assembly-mink-genome

Mesbah-Uddin, M., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2018). Genotype call for chromosomal deletions using read-depth from whole genome sequence variants in cattle. Poster session presented at The 11th World Congress on Genetics Applied to Livestock Production , Auckland, New Zealand.

Madsen, M. D., Madsen, P., Nielsen, B., Kristensen, T. N., Jensen, J. & Shirali, M. (2018). Macro-environmental sensitivity for growth rate in Danish Duroc pigs is under genetic control. Journal of Animal Science, 96(12), 4967-4977. https://doi.org/10.1093/jas/sky376

Bouwman, A. C., Daetwyler, H. D., Chamberlain, A. J., Ponce, C. H., Sargolzaei, M., Schenkel, F. S., Sahana, G., Govignon-Gion, A., Boitard, S., Dolezal, M., Pausch, H., Brøndum, R. F., Bowman, P. J., Thomsen, B., Guldbrandtsen, B., Lund, M. S., Servin, B., Garrick, D. J., Reecy, J. ... Hayes, B. J. (2018). Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals. Nature Genetics, 50(3), 362-372. https://doi.org/10.1038/s41588-018-0056-5

Fang, L., Sørensen, P., Sahana, G., Panitz, F., Su, G., Zhang, S., Yu, Y., Li, B., Ma, L., Liu, G., Lund, M. S. & Thomsen, B. (2018). MicroRNA-guided prioritization of genome-wide association signals reveals the importance of microRNA-target gene networks for complex traits in cattle. Scientific Reports, 8(1), Article 9345. https://doi.org/10.1038/s41598-018-27729-y

Sverrisdóttir, E., Sundmark, E. H. R., Johnsen, H. Ø., Kirk, H. G., Asp, T., Janss, L., Bryan, G. & Nielsen, K. L. (2018). The value of expanding the training population to improve genomic selection models in tetraploid potato. Frontiers in Plant Science, 9, Article 1118. https://doi.org/10.3389/fpls.2018.01118

Liu, A., Lund, M. S., Boichard, D., Fritz, S., Karaman, E., Wang, Y. & Su, G. (2018). Using additional single nucleotide polymorphisms selected from whole genome sequence data for genomic prediction in Danish Jersey. In Proceedings of the World Congress on Genetics Applied to Livestock Production, 2018 Article 586 http://www.wcgalp.org/system/files/proceedings/2018/using-additional-single-nucleotide-polymorphisms-selected-whole-genome-sequence-data-genomic.pdf

Gebregiwergis, G. T., Meuwissen, T. H. E., Sørensen, A. C. & Henryon, M. (2017). Alternative genomic relationship matrices in genomic optimum optimun contribution selection. Abstract from 68th Annual Meeting of the European Federation of Animal Science , Tallinn, Estonia. http://www.dairycareaction.org/uploads/2/4/2/6/24266896/eaap2017_book_of_abstracts_-_preliminary_pages.pdf

Uddin, M. M., Guldbrandtsen, B., Iso-Touru, T., Vilkki, J., de Koning, D.-J., Boichard, D., Lund, M. S. & Sahana, G. (2017). A population scale discovery of large deletions in Holstein, Jersey and Nordic Red Cattle genome. Poster session presented at 36th International Society for Animal Genetics Conference, Dublin, Ireland. http://www.isag.us/Docs/Proceedings/ISAG2017_Proceedings.pdf?v3

Meier, K., Norberg, E., Thomsen, B. & Sorensen, A. C. (2017). Combining breeding practice and quantitative genetic theory: Examples from a fish breeding network in Denmark. Aquaculture, 472(Special Issue), 133.

Zhang, Q., Calus, M. P. L., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2017). Contribution of rare and low-frequency whole-genome sequence variants to complex traits variation in dairy cattle. Genetics Selection Evolution, 49(1), Article 60. https://doi.org/10.1186/s12711-017-0336-z

Fang, L., Sahana, G., Ma, P., Su, G., Yu, Y., Zhang, S., Lund, M. S. & Sørensen, P. (2017). Exploring the genetic architecture and improving genomic prediction accuracy for mastitis and milk production traits in dairy cattle by mapping variants to hepatic transcriptomic regions responsive to intra-mammary infection. Genetics Selection Evolution, 49, Article 44. https://doi.org/10.1186/s12711-017-0319-0

Thirstrup, J. P., Jensen, J. & Lund, M. S. (2017). Genetic parameters for fur quality graded on live animals and dried pelts of American mink (Neovison vison). Journal of Animal Breeding and Genetics (Online), 134(4), 322-331. https://doi.org/10.1111/jbg.12258

Liu, A., Wang, Y., Sahana, G., Zhang, Q., Liu, L., Lund, M. S. & Su, G. (2017). Genome-wide Association Studies for Female Fertility Traits in Chinese and Nordic Holsteins. Scientific Reports, 7(1), Article 8487. https://doi.org/10.1038/s41598-017-09170-9

Rohde, P. D., Gartner, B., Ward, K., Sørensen, P. & F C Mackay, T. (2017). Genomic Analysis of Genotype-by-Social Environment Interaction for Drosophila melanogaster Aggressive Behavior. Genetics (Print), 206(4), 1969-1984. https://doi.org/10.1534/genetics.117.200642

Gebreyesus, G., Lund, M. S., Janss, L., Bovenhuis, H., Poulsen, N. A. & Buitenhuis, A. J. (2017). Genomic prediction for detailed milk protein composition traits. Poster session presented at 5th Annual GenSAP Meeting, 15-16 November 2017, Billund, Denmark.

Sverrisdóttir, E., Byrne, S., Sundmark, E. H. R., Johnsen, H. Ø., Kirk, H. G., Asp, T., Janss, L. & Nielsen, K. L. (2017). Genomic prediction of starch content and chipping quality in tetraploid potato using genotyping-by-sequencing. Theoretical and Applied Genetics, 130(10), 2091-2108. https://doi.org/10.1007/s00122-017-2944-y

Fang, L., Sahana, G., Su, G., Yu, Y., Zhang, S., Lund, M. S. & Sørensen, P. (2017). Integrating Sequence-based GWAS and RNA-Seq Provides Novel Insights into the Genetic Basis of Mastitis and Milk Production in Dairy Cattle. Scientific Reports, 7, Article 45560. https://doi.org/10.1038/srep45560

Liu, H., Henryon, M. & Sørensen, A. C. (2017). Mating strategies with genomic information reduce rates of inbreeding in animal breeding schemes without compromising genetic gain. Animal, 11(4), 547-555. https://doi.org/10.1017/S1751731116001786

Gebreyesus, G., Lund, M. S., Buitenhuis, A. J., Bovenhuis, H., Poulsen, N. A. & Janss, L. (2017). Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits. Genetics Selection Evolution, 49(1), Article 89. https://doi.org/10.1186/s12711-017-0364-8

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Jette Odgaard Villemoes