Publications

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Morgante, F., Sorensen, D. A., Sørensen, P., Maltecca, C. & Mackay, T. F. C. (2014). Genetic Analysis of Micro-environmental Plasticity in Drosophila melanogaster. Paper presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada. https://event.crowdcompass.com/wcgalp2014/activity/PabaGIO0N3

Morgante, F., Sorensen, D. A., Sørensen, P., Maltecca, C. & Mackay, T. F. C. (2014). Genetic Analysis of Micro-environmental Plasticity in Drosophila melanogaster. Poster session presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada. https://event.crowdcompass.com/wcgalp2014/activity/PabaGIO0N3

Rohde, P. D., Edwards, S. M., Sarup, P. M. & Sørensen, P. (2014). Gene-based Association Approach Identify Genes Across Stress Traits in Fruit Flies. Paper presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada. https://asas.org/docs/default-source/wcgalp-posters/673_paper_9223_manuscript_493_0.pdf

Rohde, P. D., Edwards, S. M., Sarup, P. M. & Sørensen, P. (2014). Gene-based Association Approach Identify Genes Across Stress Traits in Fruit Flies. Poster session presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada. https://event.crowdcompass.com/wcgalp2014/activity/ztj3NIVR9W

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

Gebreyesus, G., Lund, M. S., Janss, L., Bovenhuis, H. & Buitenhuis, A. J. (2016). Fine mapping and genomic prediction for detailed milk protein composition. Poster session presented at 5th International Conference on Quantitative Genetics , Madison, United States.

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

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

Janss, L. (2015). Experiences in Bioinformatics. Abstract from ADSA-ASAS Joint Annual Meeting 2015, Orlando, Florida, United States. http://www.jtmtg.org/JAM/2015/index.asp

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

Zhang, Q., Calus, M. P. L., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2015). Estimation of inbreeding using pedigree, 50k SNP chip genotypes and full sequence data in three cattle breeds. BMC Genetics, 16(88), 1-16. https://doi.org/10.1186/s12863-015-0227-7

Lopes, M. S., Bastiaansen, J. W. M., Janss, L., Knol, E. F. & Bovenhuis, H. (2015). Estimation of Additive, Dominance, and Imprinting Genetic Variance Using Genomic Data. G3: Genes, Genomes, Genetics (Bethesda), 5(12), 2629-2637. https://doi.org/10.1534/g3.115.019513

Ashraf, B. H., Byrne, S., Fé, D., Czaban, A., Asp, T., Pedersen, M. G., Lenk, I., Roulund, N., Didion, T., Jensen, C. S., Jensen, J. & Janss, L. L. (2016). Estimating genomic heritabilities at the level of family-pool samples of perennial ryegrass using genotyping-by-sequencing. Theoretical and Applied Genetics, 129(1), 45-52. https://doi.org/10.1007/s00122-015-2607-9

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

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

Gianola, D., de los Campos, G., Toro, M. A., Naya, H., Schön, C.-C. & Sorensen, D. (2015). Do Molecular Markers Inform About Pleiotropy? Genetics, 201(1), 23-29. https://doi.org/10.1534/genetics.115.179978

Marete, A. G., Lund, M. S. & Boichard, D. A. (2016). Dissecting dairy complex traits beyond additive effects using genetic markers. Abstract from 19 thSéminaire des thésards du Département de Génétique Animale, Toulouse, France.

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

Janss, L. (2014). Disentangling Pleiotropy along the Genome using Sparse Latent Variable Models. Paper presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada. https://event.crowdcompass.com/wcgalp2014#/activity/2NusKyePpB

Ehsani, A., Janss, L., Pomp, D. & Sørensen, P. (2016). Decomposing genomic variances in a mouse F2 population using information from GWA, GWE and eQTL analyses. Animal Genetics, 47(2), 165-173. https://doi.org/10.1111/age.12396

Rohde, P. D., Demontis, D., Castro Dias Cuyabano, B., Børglum, A. & Sørensen, P. (2016). Covariance Association Test (CVAT) Identifies Genetic Markers Associated with Schizophrenia in Functionally Associated Biological Processes. Genetics (Print), 203(4), 1901-1913. https://doi.org/10.1534/genetics.116.189498

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

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

Su, G., Christensen, O. F., Janss, L. & Lund, M. S. (2014). Comparison of genomic predictions using genomic relationship matrices built with different weighting factors to account for locus-specific variances. Journal of Dairy Science, 97(10), 6547-6559. https://doi.org/10.3168/jds.2014-8210

Zhang, Q., Guldbrandtsen, B., Calus, M. P. L., Lund, M. S. & Sahana, G. (2016). Comparison of gene-based rare variant association mapping methods for quantitative traits in a bovine population with complex familial relationships. Genetics Selection Evolution, 48(1), Article 60. https://doi.org/10.1186/s12711-016-0238-5

van den Berg, I., Boichard, D. & Lund, M. S. (2016). Comparing power and precision of within-breed and multibreed genome-wide association studies of production traits using whole-genome sequence data for 5 French and Danish dairy cattle breeds. Journal of Dairy Science, 99(11), 8932-8945. https://doi.org/10.3168/jds.2016-11073

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

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.

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

Castro Dias Cuyabano, B., Su, G., Rosa, G. J. M., Lund, M. S. & Gianola, D. (2015). Bootstrap study of genome-enabled prediction reliabilities using haplotype blocks across Nordic Red cattle breeds. Journal of Dairy Science, 98(10), 7351-63. https://doi.org/10.3168/jds.2015-9360

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

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

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

Meier, K., Lund, M. S. & Sørensen, A. C. (2015). A simulation study of a future infrastructure supporting genomic selection in mink. In Proceedings of NJF fur animal seminar 485 (pp. 221-230)

Michot, P., Chahory, S., Marete, A. G., Grohs, C., Dagios, D., Donzel, E., Aboukadiri, A., Deloche, M.-C., Allais-Bonnet, A., Chambrial, M., Barbey, S., Genestout, L., Boussaha, M., Danchin-Burge, C., Fritz, S., Boichard, D. & Capitan, A. (2016). A reverse genetic approach identifies an ancestral frameshift mutation in RP1 causing recessive progressive retinal degeneration in European cattle breeds. Genetics Selection Evolution, 48. https://doi.org/10.1186/s12711-016-0232-y

Rohde, P. D., Krag, K., Loeschcke, V., Overgaard, J., Sørensen, P. & Kristensen, T. N. (2016). A Quantitative Genomic Approach for Analysis of Fitness and Stress Related Traits in a Drosophila melanogaster Model Population. International Journal of Genomics, 2016, 1-11. Article 2157494. https://doi.org/10.1155/2016/2157494

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

Henryon, M., Berg, P. & Sørensen, A. C. (2014). Animal-breeding schemes using genomic information need breeding plans designed to maximise long-term genetic gains. Livestock Science, 166, 38-47. https://doi.org/10.1016/j.livsci.2014.06.016

Legarra, A., Christensen, O. F., Vitezica, Z. G., Aguilar, I. & Misztal, I. (2015). Ancestral Relationships Using Metafounders: Finite Ancestral Populations and Across Population Relationships. Genetics (Print), 200(2), 455-468. https://doi.org/10.1534/genetics.115.177014

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

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

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

van den Berg, I., Guldbrandtsen, B., Hozé, C., Brøndum, R. F., Boichard, D. A. & Lund, M. S. (2014). Across Breed QTL Detection and Genomic Prediction in French and Danish Dairy Cattle Breeds. Paper presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada. https://event.crowdcompass.com/wcgalp2014/activity/DtbvU7eMTN

van den Berg, I., Guldbrandtsen, B., Hozé, C., Brøndum, R. F., Boichard, D. A. & Lund, M. S. (2014). Across Breed QTL Detection and Genomic Prediction in French and Danish Dairy Cattle Breeds. Poster session presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada. https://event.crowdcompass.com/wcgalp2014/activity/DtbvU7eMTN

Sahana, G., Iso-Touru, T., Wu, X., Nielsen, U., de Koning, D.-J., Lund, M. S., Vilkki, J. & Guldbrandtsen, B. (2016). A 0.5-Mbp deletion on bovine chromosome 23 is a strong candidate for stillbirth in Nordic Red cattle. Genetics Selection Evolution, 48(1), Article 35. https://doi.org/10.1186/s12711-016-0215-z

Displaying results 101 to 145 out of 145

Revised 19.03.2025

Jette Odgaard Villemoes

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2018

2017