Publikationer

Peer-reviewed publikationer ved QGG

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), Artikel 31. https://doi.org/10.1186/s12711-020-00550-w

Esfandyari, H., Fè, D., Tessema, B. B., Janss, L. L. & Jensen, J. (2020). Effects of different strategies for exploiting genomic selection in perennial ryegrass breeding programs. G3: Genes, Genomes, Genetics, 10(10), 3783-3795. https://doi.org/10.1534/g3.120.401382

Davis, R. B., Norberg, E. & Fogh, A. (2020). Estimation of genetic parameters for young stock survival in beef x dairy crossbred calves. Animal, 14(3), 445-451. Artikel 1751731119002386. https://doi.org/10.1017/S1751731119002386

Skovbjerg, C. K., Knudsen, J. N., Füchtbauer, W., Stougaard, J., Stoddard, F. L., Janss, L. & Andersen, S. U. (2020). Evaluation of yield, yield stability, and yield–protein relationship in 17 commercial faba bean cultivars. Legume Science, 2(3), Artikel e39. https://doi.org/10.1002/leg3.39

Dettmann, F., Warner, D., Buitenhuis, B., Kargo, M., Kjeldsen, A. M. H., Nielsen, N. H., Lefebvre, D. M. & Santschi, D. E. (2020). Fatty Acid Profiles from Routine Milk Recording as a Decision Tool for Body Weight Change of Dairy Cows after Calving. Animals, 10(11), 1-14. Artikel 1958. https://doi.org/10.3390/ani10111958

Forte, F. P., Schmid, J., Dijkwel, P. P., Nagy, I., Hume, D. E., Johnson, R. D., Simpson, W. R., Monk, S. M., Zhang, N., Sehrish, T. & Asp, T. (2020). Fungal Endophyte Colonization Patterns Alter Over Time in the Novel Association Between Lolium perenne and Epichloë Endophyte AR37. Frontiers in Plant Science, 11, Artikel 570026. https://doi.org/10.3389/fpls.2020.570026

Zaalberg, R. M., Buitenhuis, A. J., Sundekilde, U. K., Poulsen, N. A. & Bovenhuis, H. (2020). Genetic analysis of orotic acid predicted with Fourier transform infrared milk spectra. Journal of Dairy Science, 103(4), 3334-3348. https://doi.org/10.3168/jds.2018-16057

Chu, T. T., Madsen, P., Norberg, E., Wang, L., Marois, D., Henshall, J. & Jensen, J. (2020). Genetic analysis on body weight at different ages in broiler chicken raised in commercial environment. Journal of Animal Breeding and Genetics (Online), 137(2), 245-259. https://doi.org/10.1111/jbg.12448

Zaalberg, R. M., Bovenhuis, H., Poulsen, N. A., Larsen, L. B., Sehested, J. & Buitenhuis, A. J. (2020). Genetic analysis on minerals predicted with Fourier transform infrared milk spectra for two Danish dairy cattle breeds. Abstract fra 71st Annual Meeting of European Federation of Animal Science. https://www.wageningenacademic.com/doi/book/10.3920/978-90-8686-900-8

Poulsen, B. G., Nielsen, B., Ostersen, T. & Christensen, O. F. (2020). Genetic associations between stayability and longevity in commercial crossbred sows, and stayability in multiplier sows. Journal of Animal Science, 98(6), Artikel skaa183. https://doi.org/10.1093/jas/skaa183

Bjarup Hansen, P. (2020). Genetic Dissection and Prediction of Complex Traits in Barley and Festulolium Grasses. Århus Universitet.

Eydivandi, S., Sahana, G., Momen, M., Moradi, M. H. & Schönherz, A. A. (2020). Genetic diversity in Iranian indigenous sheep vis-à-vis selected exogenous sheep breeds and wild mouflon. Animal Genetics, 51(5), 772-787. https://doi.org/10.1111/age.12985

Christensen, O. F., Börner, V., Varona, L. & Legarra, A. (2020). Genetic evaluation including an intermediate omics trait. Abstract fra 71st Annual Meeting of European Federation of Animal Science. https://www.wageningenacademic.com/doi/book/10.3920/978-90-8686-900-8

Guo, X., Sarup, P. M., Jensen, J. D., Jihad, O., Kristensen, N. H., Mulder, F. A. A., Jahoor, A. & Jensen, J. (2020). Genetic Variance of Metabolomic Features and Their Relationship With Malting Quality Traits in Spring Barley. Frontiers in Plant Science, 11, Artikel 575467. https://doi.org/10.3389/fpls.2020.575467

Mao, X., Sahana, G., Johansson, A. M., Liu, A., Ismael, A., Løvendahl, P., De Koning, D.-J. & Guldbrandtsen, B. (2020). Genome-wide association mapping for dominance effects in female fertility using real and simulated data from Danish Holstein cattle. Scientific Reports, 10(1), Artikel 2953. https://doi.org/10.1038/s41598-020-59788-5

Gan, Q. F., Li, Y. R., Liu, Q. H., Lund, M., Su, G. S. & Liang, X. W. (2020). Genome-wide association studies for the concentrations of insulin, triiodothyronine, and thyroxine in Chinese Holstein cattle. Tropical Animal Health and Production, 52(4), 1655-1660. https://doi.org/10.1007/s11250-019-02170-z

Manzanilla Pech, C. I. V., Mansan Gordo, D. G., Løvendahl, P. & Lassen, J. (2020). Genome wide association study of methane traits in Danish Holstein. Abstract fra 6th International Conference of Quantitative Genetics, Brisbane, Australien. https://icqg6.org/wp-content/uploads/2020/11/ICQG6_2020_Abstract_Book.pdf

Zaalberg, R. M., Janss, L. & Buitenhuis, A. J. (2020). Genome-wide association study on Fourier transform infrared milk spectra for two Danish dairy cattle breeds. BMC Genetics, 21(1), Artikel 9. https://doi.org/10.1186/s12863-020-0810-4

Guldbrandtsen, B., Nielsen, V. H. & Schönherz, A. A. (2020). Genomic assessment of suitability of pigs for inclusion in the Pied Danish Pig conservation program – A case study. Acta Agriculturae Scandinavica, Section A - Animal Science, 69(1-2), 95-100. https://doi.org/10.1080/09064702.2020.1732455

Cao, L., Liu, H., Mulder, H. A., Henryon, M., Thomasen, J. R., Kargo, M. & Sørensen, A. C. (2020). Genomic Breeding Programs Realize Larger Benefits by Cooperation in the Presence of Genotype × Environment Interaction Than Conventional Breeding Programs. Frontiers in Genetics, 11, Artikel 251. https://doi.org/10.3389/fgene.2020.00251

Cai, Z., Sarup, P., Ostersen, T., Nielsen, B., Fredholm, M., Karlskov-Mortensen, P., Sørensen, P., Jensen, J., Guldbrandtsen, B., Lund, M. S., Christensen, O. F. & Sahana, G. (2020). Genomic diversity revealed by whole-genome sequencing in three Danish commercial pig breeds. Journal of Animal Science, 98(7), Artikel 229. https://doi.org/10.1093/jas/skaa229

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), Artikel 3347. https://doi.org/10.1038/s41598-020-60203-2

Eiriksson, J. H., Karaman, E., Su, G. & Christensen, O. F. (2020). Genomic prediction for crossbred cows by combining marker effects estimated in purebreds. Abstract fra 71st Annual Meeting of European Federation of Animal Science. https://www.wageningenacademic.com/doi/book/10.3920/978-90-8686-900-8

Guo, X., Svane, S. F., Füchtbauer, W. S., Andersen, J. R., Jensen, J. & Thorup-Kristensen, K. (2020). Genomic prediction of yield and root development in wheat under changing water availability. Plant Methods, 16, Artikel 90. https://doi.org/10.1186/s13007-020-00634-0

Karaman, E., Su, G., Croue, I. & Lund, M. S. (2020). Genomic prediction using a multi-breed reference data of purebred and admixed populations. Abstract fra 6th International Conference of Quantitative Genetics, Brisbane, Australien.

Karaman, E., Su, G., Croue, I. & Lund, M. S. (2020). Genomic prediction using data from multiple pure breeds and crossbreds. Abstract fra 71st Annual Meeting of European Federation of Animal Science.

Karaman, E., Su, G., Croue, I. & Lund, M. S. (2020). Genomic prediction using purebred and crossbred individuals. GenTORE Newsletter, (4), 13-16. https://www.gentore.eu/uploads/1/0/7/4/107437499/gentore_newsletter.pdf

Ankamah-Yeboah, T., Janss, L. L., Jensen, J. D., Hjortshøj, R. L. & Rasmussen, S. K. (2020). Genomic Selection Using Pedigree and Marker-by-Environment Interaction for Barley Seed Quality Traits From Two Commercial Breeding Programs. Frontiers in Plant Science, 11, Artikel 539. https://doi.org/10.3389/fpls.2020.00539

Thomasen, J. R., Liu, H. & Sørensen, A. C. (2020). Genotyping more cows increases genetic gain and reduces rate of true inbreeding in a dairy cattle breeding scheme using female reproductive technologies. Journal of Dairy Science, 103(1), 597-606. https://doi.org/10.3168/jds.2019-16974

Tausen, M., Clausen, M. M., Moeskjær, S., Shihavuddin, ASM., Dahl, A. B., Janss, L. & Andersen, S. U. (2020). Greenotyper: Image-based plant phenotyping using distributed computing and deep learning. Frontiers in Plant Science, 11, Artikel 1181. https://doi.org/10.3389/fpls.2020.01181

Liu, T., Luo, C., Ma, J., Wang, Y., Shu, D., Su, G. & Qu, H. (2020). High-Throughput Sequencing With the Preselection of Markers Is a Good Alternative to SNP Chips for Genomic Prediction in Broilers. Frontiers in Genetics, 11, Artikel 108. https://doi.org/10.3389/fgene.2020.00108

Calabrese, V., Scuto, M., Salinaro, A. T., Dionisio, G., Modafferi, S., Ontario, M. L., Greco, V., Sciuto, S., Schmitt, C. P., Calabrese, E. J. & Peters, V. (2020). Hydrogen sulfide and carnosine: Modulation of oxidative stress and inflammation in kidney and brain axis. Antioxidants, 9(12), 1-35. Artikel 1303. https://doi.org/10.3390/antiox9121303

Bordbar, F., Jensen, J., Du, M., Abied, A., Guo, W., Xu, L., Gao, H., Zhang, L. & Li, J. (2020). Identification and validation of a novel candidate gene regulating net meat weight in Simmental beef cattle based on imputed next-generation sequencing. Cell Proliferation, 53(9), Artikel e12870. https://doi.org/10.1111/cpr.12870

Su, G., Sørensen, A. C., Chu, T. T., Meier, K., Nielsen, T. & Lund, M. S. (2020). Impact of phenotypic information and composition of reference population on genomic prediction in fish under the presence of genotype by environment interaction. Aquaculture, 526, Artikel 735358. https://doi.org/10.1016/j.aquaculture.2020.735358

Li, J., Gao, H., Madsen, P., Li, R., Liu, W., Bao, P., Xue, G., Gao, Y., Di, X. & Su, G. (2020). Impact of the Order of Legendre Polynomials in Random Regression Model on Genetic Evaluation for Milk Yield in Dairy Cattle Population. Frontiers in Genetics, 11, Artikel 586155. https://doi.org/10.3389/fgene.2020.586155

Raffo, M. A., Sarup, P. M., Guo, X., Liu, H. & Jensen, J. (2020). Improvement of Genomic Prediction by Including Additive-by-Additive Epistasis. A Case of Study in Advanced Wheat-Breeding Lines. Abstract fra The 6th International Conference of Quantitative Genetics.

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

Liu, A., Lund, M. S., Boichard, D., Mao, X., Karaman, E., Fritz, S., Aamand, G. P., Wang, Y. & Su, G. (2020). Imputation for sequencing variants preselected to a customized low-density chip. Scientific Reports, 10, Artikel 9524. https://doi.org/10.1038/s41598-020-66523-7

Zhang, Q., Cai, Z., Lhomme, M., Sahana, G., Lesnik, P., Guerin, M., Fredholm, M. & Karlskov-Mortensen, P. (2020). Inclusion of endophenotypes in a standard GWAS facilitate a detailed mechanistic understanding of genetic elements that control blood lipid levels. Scientific Reports, 10(1), Artikel 18434. https://doi.org/10.1038/s41598-020-75612-6

Gautason, E. (2020). Incorporation of GWAS data on genomic prediction accuracies assessed in the small, unadmixed, unstructured population of Icelandic dairy cattle. Poster-session præsenteret på 6th International Conference of Quantitative Genetics, Brisbane, Australien.

Kamal, N., Mun, T., Reid, D., Lin, J.-S., Akyol, T. Y., Sandal, N., Asp, T., Hirakawa, H., Stougaard, J., Mayer, K. F. X., Sato, S. & Andersen, S. U. (2020). Insights into the evolution of symbiosis gene copy number and distribution from a chromosome-scale Lotus japonicus Gifu genome sequence. D N A Research, 27(3), Artikel dsaa015. https://doi.org/10.1093/dnares/dsaa015

Morgante, F., Huang, W., Sørensen, P., Maltecca, C. & Mackay, T. F. C. (2020). Leveraging Multiple Layers of Data To Predict Drosophila Complex Traits. G3 (Bethesda, Md.), 10(12), 4599-4613. https://doi.org/10.1534/g3.120.401847

Poulsen, N. A., Szekeres, B. D., Kargo, M. & Larsen, L. B. (2020). Mineral and fatty acid composition of milk from native Jutland and Danish Red 1970 cattle breeds. Acta Agriculturae Scandinavica, Section A - Animal Science, 69(1-2), 131-135. https://doi.org/10.1080/09064702.2019.1674914

Rome, H. J. S., Marois, D., Huang, C.-H. & Jensen, J. (2020). Modeling maternal effects in later traits in broilers. Abstract fra 71st Annual Meeting of European Federation of Animal Science.

Ba, H., Qin, T., Cai, Z., Liu, W. & Li, C. (2020). Molecular evidence for adaptive evolution of olfactory-related genes in cervids. Genes and Genomics, 42(4), 355-360. https://doi.org/10.1007/s13258-019-00911-w

Manzanilla-Pech, C. I. V., Gordo, D., Difford, G. F., Løvendahl, P. & Lassen, J. (2020). Multitrait genomic prediction of methane emissions in Danish Holstein cattle. Journal of Dairy Science, 103(10), 9195-9206. https://doi.org/10.3168/jds.2019-17857

Karaman, E., Lund, M. S. & Su, G. (2020). Multi-trait single-step genomic prediction accounting for heterogeneous (co)variances over the genome. Heredity, 124(2), 274-287. https://doi.org/10.1038/s41437-019-0273-4

Schonherz, A. A., Bødker, J. S., Schmitz, A., Brøndum, R. F., Jakobsen, L. H., Roug, A. S., Severinsen, M. T., El-Galaly, T. C., Jensen, P., Johnsen, H. E., Bøgsted, M. & Dybkær, K. (2020). Normal myeloid progenitor cell subsetassociated gene signatures for acute myeloid leukaemia subtyping with prognostic impact. PLOS ONE, 15(4), Artikel e0229593. https://doi.org/10.1371/journal.pone.0229593

Gebreyesus, G., Sahana, G., Christian Sørensen, A., Lund, M. S. & Su, G. (2020). Novel approach to incorporate information about recessive lethal genes increases the accuracy of genomic prediction for mortality traits. Heredity, 125, 155-166. https://doi.org/10.1038/s41437-020-0329-5

Wu, X., Mesbah-Uddin, M., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2020). Novel haplotypes responsible for prenatal death in Nordic Red and Danish Jersey cattle. Journal of Dairy Science, 103(5), 4570-4578. https://doi.org/10.3168/jds.2019-17831

Hutchings, N., Lærke, P. E., Munkholm, L. J., Elsgaard, L., Kristensen, T., Rasmussen, J., Lund, P., Børsting, C. F., Løvendahl, P., Mikkelsen, M. H., Albrektsen, R., Gyldenkærne, S., Møller, H. B., Hansen, M. J., Feilberg, A. & Adamsen, A. P. S., (2020). Opdatering af effekter og potentialer af klimavirkemidler til anvendelse i landbrug, Nr. 2019-0035910, 23 s., mar. 02, 2020.

Czech, B., Guldbrandtsen, B. & Szyda, J. (2020). Patterns of DNA variation between the autosomes, the X chromosome and the Y chromosome in Bos taurus genome. Scientific Reports, 10(1), Artikel 13641. https://doi.org/10.1038/s41598-020-70380-9

Chu, T. T., Sørensen, A. C., Lund, M. S., Meier, K., Nielsen, T. & Su, G. (2020). Phenotypically Selective Genotyping Realizes More Genetic Gains in a Rainbow Trout Breeding Program in the Presence of Genotype-by-Environment Interactions. Frontiers in Genetics, 11, Artikel 866. https://doi.org/10.3389/fgene.2020.00866

Schonherz, A. A., Szekeres, B. D., Nielsen, V. H. & Guldbrandtsen, B. (2020). Population structure and genetic characterization of two native Danish sheep breeds. Acta Agriculturae Scandinavica, Section A - Animal Science, 69(1-2), 53-67. https://doi.org/10.1080/09064702.2019.1639804

Slagboom, M., Hjortø, L., Sørensen, A. C., Mulder, H. A., Thomasen, J. R. & Kargo, M. (2020). Possibilities for a specific breeding program for organic dairy production. Journal of Dairy Science, 103(7), 6332-6345. https://doi.org/10.3168/jds.2019-16900

Su, G., Höglund, J., Christensen, O. F. & Lund, M. S. (2020). Possibilities for genetic improvement of pig survival until slaughter. DCA - Nationalt Center for Fødevarer og Jordbrug.

Holmqvist, V., Roos, L. K. S., Kjartansdottir, K. R., Dunø, M., Petersen, M. R., Hnida, C., Pedersen, I. S., Ernst, A., Toft, C. L. F., Diemer, T., Ingerslev, H. J., Pinborg, A. & Løssl, K. (2020). Præimplantationsgenetisk testning for aneuploidi. Ugeskrift for Læger, 181(4), Artikel V12180849.

Poulsen, B. G., Ask, B., Nielsen, H. M., Ostersen, T. & Christensen, O. F. (2020). Prediction of genetic merit for growth rate in pigs using animal models with indirect genetic effects and genomic information. Genetics, selection, evolution : GSE, 52(1), Artikel 58. https://doi.org/10.1186/s12711-020-00578-y

Gebreyesus, G., Difford, G. F., Buitenhuis, B., Lassen, J., Noel, S. J., Højberg, O., Plichta, D. R., Zhu, Z., Poulsen, N. A., Sundekilde, U. K., Løvendahl, P. & Sahana, G. (2020). Predictive ability of host genetics and rumen microbiome for subclinical ketosis. Journal of Dairy Science, 103(5), 4557-4569. https://doi.org/10.3168/jds.2019-17824

Larsen, F., Guldbrandtsen, B., Christensen, D., Pitcovski, J., Kjærup, R. B. & Dalgaard, T. S. (2020). Pustulan activates chicken bone marrow-derived dendritic cells in vitro and promotes ex vivo CD4⁺ T cell recall response to infectious bronchitis virus. Vaccines, 8(2), Artikel 226. https://doi.org/10.3390/vaccines8020226

Rohde, P. D., Fourie Sørensen, I. & Sørensen, P. (2020). qgg: an R package for large-scale quantitative genetic analyses. Bioinformatics (Oxford, England), 36(8), 2614-2615. https://doi.org/10.1093/bioinformatics/btz955

Poulsen, N. A., Hein, L., Kargo, M. & Buitenhuis, A. J. (2020). Realization of breeding values for milk fatty acids in relation to seasonal variation in organic milk. Journal of Dairy Science, 103(3), 2434-2441. https://doi.org/10.3168/jds.2019-17065

Gautason, E., Schonherz, A. A., Sahana, G. & Guldbrandtsen, B. (2020). Relationship of Icelandic cattle with Northern and Western European cattle breeds, admixture and population structure. Acta Agriculturae Scandinavica, Section A - Animal Science, 69(1-2), 25-38. https://doi.org/10.1080/09064702.2019.1699951

Hozé, C., Escouflaire, C., Mesbah-Uddin, M., Barbat, A., Boussaha, M., Deloche, M.-C., Boichard, D., Fritz, S. & Capitan, A. (2020). Short communication: A splice site mutation in CENPU is associated with recessive embryonic lethality in Holstein cattle. Journal of Dairy Science, 103(1), 607-612. https://doi.org/10.3168/jds.2019-17056

Mellergaard, M., Høgh, R. I., Lund, A., Aldana, B. I., Guérillot, R., Møller, S. H., Hayes, A. S., Panagiotopoulou, N., Frimand, Z., Jepsen, S. D., Hansen, C. H. F., Andresen, L., Larsen, A. R., Peleg, A. Y., Stinear, T. P., Howden, B. P., Waagepetersen, H. S., Frees, D. & Skov, S. (2020). Staphylococcus aureus induces cell-surface expression of immune stimulatory NKG2D ligands on human monocytes. The Journal of Biological Chemistry, 295(33), 11803-11821. https://doi.org/10.1074/jbc.RA120.012673

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, Artikel 578123. https://doi.org/10.3389/fgene.2020.578123

Mesbah-Uddin, M., Guldbrandtsen, B., Capitan, A., Lund, M. S., Boichard, D. & Sahana, G. (2020). Strategy to imputation of large genomic deletions and utilizing them in mapping and genomic prediction in cattle. Abstract fra 6th International Conference of Quantitative Genetics, Brisbane, Australien. https://icqg6.org/wp-content/uploads/2020/11/ICQG6_2020_Abstract_Book.pdf

Zhang, Y., Ran, Y., Nagy, I., Lenk, I., Qiu, J. L., Asp, T., Jensen, C. S. & Gao, C. (2020). Targeted mutagenesis in ryegrass (Lolium spp.) using the CRISPR/Cas9 system. Plant Biotechnology Journal, 18(9), 1854-1856. https://doi.org/10.1111/pbi.13359

Malinowska, M., Nagy, I., Wagemaker, C. A. M., Ruud, A. K., Svane, S. F., Thorup-Kristensen, K., Jensen, C. S., Eriksen, B., Krusell, L., Jahoor, A., Jensen, J., Eriksen, L. B. & Asp, T. (2020). The cytosine methylation landscape of spring barley revealed by a new reduced representation bisulfite sequencing pipeline, WellMeth. The Plant Genome, 13(3), e20049. Artikel e20049. https://doi.org/10.1002/tpg2.20049

Ask, B., Christensen, O. F., Heidaritabar, M., Madsen, P. & Nielsen, H. M. (2020). The predictive ability of indirect genetic models is reduced when culled animals are omitted from the data. Genetics, selection, evolution : GSE, 52(1), Artikel 8. https://doi.org/10.1186/s12711-020-0527-x

Tsai, H.-Y., Cericola, F., Edriss, V., Andersen, J. R., Orabi, J., Jensen, J. D., Jahoor, A., Janss, L. & Jensen, J. (2020). Use of multiple traits genomic prediction, genotype by environment interactions and spatial effect to improve prediction accuracy in yield data. PLOS ONE, 15(5), Artikel e0232665. https://doi.org/10.1371/journal.pone.0232665

Sarup, P., Guo, X., Nielsen, N., Jensen, J. D., Mulder, F., Jihad, O., Edriss, V., Jahoor, A. & Jensen, J. (2020). Using NMR metabolomics in breeding for malt quality in spring barley. Abstract fra International Symposium of the Society for Plant Breeding (GPZ), Tulln, Østrig. https://gpz2020.boku.ac.at/wp-content/uploads/2020/03/06_Sarup.pdf

Vestergaard, M., Spleth, P., Stephansen, R., Kargo, M., Ettema, J. F. & Fogh, A. (2020). Utilizing beef x dairy crossbreds for beef production – Danish experiences. I Book of Abstracts of the 71st Annual Meeting of the European Federation of Animal Science (Bind 26, s. 317). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-900-8

Liu, A., Lund, M. S., Boichard, D., Karaman, E., Guldbrandtsen, B., Fritz, S., Aamand, G. P., Nielsen, U. S., Sahana, G., Wang, Y. & Su, G. (2020). Weighted single-step genomic best linear unbiased prediction integrating variants selected from sequencing data by association and bioinformatics analyses. Genetics Selection Evolution, 52(1), Artikel 48. https://doi.org/10.1186/s12711-020-00568-0

Harwood, S. L., Nielsen, N. S., Jensen, K. T., Nielsen, P. K., Thøgersen, I. B. & Enghild, J. J. (2020). α₂-macroglobulin-like protein 1 can conjugate and inhibit proteases through their hydroxyl groups, because of an enhanced reactivity of its thiol ester. Journal of Biological Chemistry, 295(49), 16732-16742. https://doi.org/10.1074/jbc.RA120.015694

Christensen, O. F., Nielsen, B., Su, G., Xiang, T., Madsen, P., Ostersen, T., Velander, I. & Strathe, A. B. (2019). A bivariate genomic model with additive, dominance and inbreeding depression effects for sire line and three-way crossbred pigs. Genetics Selection Evolution, 51(1), Artikel 45. https://doi.org/10.1186/s12711-019-0486-2

Nielsen, H. M. & Kargo, M. (2019). A conservation plan for the Danish Jutland horse. Abstract fra Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgien.

Liu, H., Tessema, B. B., Jensen, J., Cericola, F., Andersen, J. R. & Sørensen, A. C. (2019). ADAM-Plant: A Software for Stochastic Simulations of Plant Breeding From Molecular to Phenotypic Level and From Simple Selection to Complex Speed Breeding Programs. Frontiers in Plant Science, 9, 1926. Artikel 1926. https://doi.org/10.3389/fpls.2018.01926

Poulsen, N. A., Robinson, R. C., Barile, D., Larsen, L. B. & Buitenhuis, B. (2019). A genome-wide association study reveals specific transferases as candidate loci for bovine milk oligosaccharides synthesis. BMC Genomics, 20, Artikel 404. https://doi.org/10.1186/s12864-019-5786-y

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

Iso-Touru, T., Wurmser, C., Venhoranta, H., Hiltpold, M., Savolainen, T., Sironen, A., Fischer, K., Flisikowski, K., Fries, R., Vicente-Carrillo, A., Alvarez-Rodriguez, M., Nagy, S., Mutikainen, M., Peippo, J., Taponen, J., Sahana, G., Guldbrandtsen, B., Simonen, H., Rodriguez-Martinez, H. ... Pausch, H. (2019). A splice donor variant in CCDC189 is associated with asthenospermia in Nordic Red dairy cattle. BMC Genomics, 20(1), Artikel 286. https://doi.org/10.1186/s12864-019-5628-y

Bornhofen, E., Ramires, T. G., Bergonci, T., Nakamura, L. R. & Righetto, A. J. (2019). Associations between global indices of risk management and agricultural development. Agricultural Systems, 173, 281-288. https://doi.org/10.1016/j.agsy.2019.03.006

Fan, H., Hou, Y., Sahana, G., Gao, H., Zhu, C., Du, L., Zhao, F. & Wang, L. (2019). A Transcriptomic Study of the Tail Fat Deposition in Two Types of Hulun Buir Sheep According to Tail Size and Sex. Animals, 9(9), Artikel 655. https://doi.org/10.3390/ani9090655

Kargo, M. (2019). Avl. I T. Kristensen, J. O. Lehmann & L. Mogensen (red.), Fremtidens helhedsorienterede og balancerede kvægproduktion - visioner og udfordringer for malkekvægsbedriften frem mod år 2040 (Bind 146, s. 52-64).

Chu, T. T., Norberg, E., Henshall, J. & Jensen, J. (2019). Benefits of using genomic information for broiler breeding program in presence of GxE interactions. Abstract fra Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgien.

Gao, H., Madsen, P., Aamand, G. P., Thomasen, J. R., Sørensen, A. C. & Jensen, J. (2019). Bias in estimates of variance components in populations undergoing genomic selection: a simulation study. BMC Genomics, 20(1), Artikel 956. https://doi.org/10.1186/s12864-019-6323-8

Malik, P. L., Janss, L., Nielsen, L. K., Borum, F., Jørgensen, H., Eriksen, B., Schjoerring, J. K. & Rasmussen, S. K. (2019). Breeding for dual-purpose wheat varieties using marker–trait associations for biomass yield and quality traits. Theoretical and Applied Genetics, 132(12), 3375-3398. https://doi.org/10.1007/s00122-019-03431-z

Clasen, J. B., Lehmann, J. O., Thomasen, J. R., Østergaard, S. & Kargo, M. (2019). Combining extended lactation with sexed semen in a dairy cattle herd: Effect on genetic and total economic return. Livestock Science, 223, 176-183. https://doi.org/10.1016/j.livsci.2019.03.001

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

Garnsworthy, P. C., Difford, G. F., Bell, M. J., Bayat, A. R., Huhtanen, P., Kuhla, B., Lassen, J., Peiren, N., Pszczola, M., Sorg, D., Visker, M. H. P. W. & Yan, T. (2019). Comparison of methods to measure methane for use in genetic evaluation of dairy cattle. Animals, 9(10), Artikel 837. https://doi.org/10.3390/ani9100837

Clasen, J., Kargo, M., Østergaard, S., Fikse, W. F., Rydhmer, L. & Strandberg, E. (2019). Consequences of crossbreeding, genotyping, and use of sexed semen and beef semen on genetic merit and profitability in Swedish dairy herds. 292-293. Abstract fra ADSA Annual Meeting 2019, Cincinnati, Ohio, USA. https://www.adsa.org/Portals/0/SiteContent/Docs/Meetings/2019ADSA/2019ADSA_Abstract_Book.pdf?v20190715

Chu, T. T., Bastiaansen, J. W. M., Berg, P., Romé, H., Marois, D., Henshall, J. & Jensen, J. (2019). Correction to: Use of genomic information to exploit genotype-by-environment interactions for body weight of broiler chicken in bio-secure and production environments. Genetics Selection Evolution, 51(1), Artikel 68. https://doi.org/10.1186/s12711-019-0513-3

Wang, X., Gao, H., Gebremedhin, K. G., Bjerg, B. S., Van Os, J., Tucker, C. B. & Zhang, G. (2019). Corrigendum to “A predictive model of equivalent temperature index for dairy cattle (ETIC)” [J. Therm. Biol. (2018) 165–170]. Journal of Thermal Biology, 82, 252-253. https://doi.org/10.1016/j.jtherbio.2018.12.012

Schmidtmann, C., Kargo, M., Ettema, J. F., Hinrichs, D. & Thaller, G. (2019). Derivation of economic values for German dairy breeds. 609-609. Abstract fra 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgien.

Warner, D., Dettmann, F., Buitenhuis, A. J., Kargo, M., Hostrup Kjeldsen, A. M., Nielsen, N. H., Lefebvre, D. M. & Santschi, D. E. (2019). Development of a prediction equation for body weight change in early-lactating dairy cows by Fourier-transform infrared predicted fatty acid profiles in milk. Journal of Dairy Science, 102(Supplement 1), 109-110. Artikel 95. https://www.adsa.org/Portals/0/SiteContent/Docs/Meetings/2019ADSA/2019ADSA_Abstract_Book.pdf?v20190715

Clasen, J. B., Fogh, A. & Kargo, M. (2019). Differences between performance of F1 crossbreds and Holsteins at different production levels. Journal of Dairy Science, 102(1), 436-441. https://doi.org/10.3168/jds.2018-14975

Ruud, A. K., Malinowska, M., Bjarup Hansen, P., Svane, S. F., Eriksen, L. B., Fè, D., Jensen, C. S., Greve, M., Thorup-Kristensen, K., Nagy, I. & Asp, T. (2019). Differential gene expression and multi-omic analysis of drought stress in Lolium perenne. 287. Abstract fra EGF-EUCARPIA Symposium, Grassland Science in Europe, Zurich, Schweiz. https://www.europeangrassland.org/fileadmin/documents/Infos/Printed_Matter/Proceedings/EGF2019.pdf

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, Artikel 15. https://doi.org/10.1186/s12863-019-0717-0

Pedersen, M. L. M., Velander, I. H., Nielsen, M. B. F., Lundeheim, N. & Nielsen, B. (2019). Duroc boars have lower progeny mortality and lower fertility than Pietrain boars1. Translational Animal Science, 3(2), 885-892. https://doi.org/10.1093/tas/txz036

Clasen, J., Kargo, M., Østergaard, S., Fikse, W. F., Rydhmer, L. & Strandberg, E. (2019). Effect of crossbreeding and using new techniques on genetic merit and economy in Swedish dairy herds. 285-285. Abstract fra 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgien.

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