Clasen, J. B., Kargo, M., Fikse, W. F., Strandberg, E., Wallenbeck, A., Østergaard, S. & Rydhmer, L. (2021). Conservation of a native dairy cattle breed through terminal crossbreeding with commercial dairy breeds. Acta Agriculturae Scandinavica, Section A - Animal Science, 70(1). https://doi.org/10.1080/09064702.2020.1867632

Clasen, J. B., Kargo, M., Østergaard, S., Fikse, W. F., Rydhmer, L. & Strandberg, E. (2021). Genetic consequences of terminal crossbreeding, genomic test, sexed semen, and beef semen in dairy herds. Journal of Dairy Science, 104(7), 8062-8075. https://doi.org/10.3168/jds.2020-20028

Chu, T. T., Henryon, M., Jensen, J., Ask, B. & Christensen, O. F. (2021). Statistical model and testing designs to increase response to selection with constrained inbreeding in genomic breeding programs for pigs affected by social genetic effects. Genetics Selection Evolution, 53(1), Artikel 1. https://doi.org/10.1186/s12711-020-00598-8

Christensen, B., Zachariae, E. D., Poulsen, N. A., Buitenhuis, A. J., Larsen, L. B. & Sørensen, E. S. (2021). Factors influencing milk osteopontin concentration based on measurements from Danish Holstein cows. Journal of Dairy Research, 88(1), 89 - 94. https://doi.org/10.1017/S0022029921000054

Christensen, O. F., Börner, V., Varona, L. & Legarra, A. (2021). Genetic evaluation including intermediate omics features. Genetics, 219(2), Artikel iyab130. https://doi.org/10.1093/genetics/iyab130

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

Bellamy, K. K. L., Lingaas, F. & Madsen, P. (2021). Heritability of distichiasis in Havanese dogs in Norway. Canine medicine and genetics, 8(1), Artikel 11. https://doi.org/10.1186/s40575-021-00110-5

Bauer, M., Glenn, T., Achtyes, E. D., Alda, M., Agaoglu, E., Altınbaş, K., Andreassen, O. A., Angelopoulos, E., Ardau, R., Vares, E. A., Aydin, M., Ayhan, Y., Baethge, C., Bauer, R., Baune, B. T., Balaban, C., Becerra-Palars, C., Behere, A. P., Behere, P. B. ... Whybrow, P. C. (2021). Variations in seasonal solar insolation are associated with a history of suicide attempts in bipolar I disorder. International Journal of Bipolar Disorders, 9(1), Artikel 26. https://doi.org/10.1186/s40345-021-00231-7

Atrian-Afiani, F., Gao, H., Joezy-Shekalgorabi, S., Madsen, P., Aminafshar, M., Ali, S. & Jensen, J. (2021). Genotype by climate zone interactions for fertility, somatic cell score, and production in Iranian Holsteins. Journal of Dairy Science, 104(12), 12994-13007. https://doi.org/10.3168/jds.2020-20084, https://doi.org/10.3168/jds.2020-20084

Ask, B., Pedersen, L. V., Christensen, O. F., Nielsen, H. M., Turner, S. P. & Nielsen, B. (2021). Selection for social genetic effects in purebreds increases growth in crossbreds. Genetics, selection, evolution : GSE, 53(1), Artikel 15. https://doi.org/10.1186/s12711-021-00609-2

Ahmad, S., Drag, M. H., Salleh, S. M., Cai, Z. & Nielsen, M. O. (2021). Transcriptomics analysis of differentially expressed genes in subcutaneous and perirenal adipose tissue of sheep as affected by their pre- and early postnatal malnutrition histories. BMC Genomics, 22(1), Artikel 338. https://doi.org/10.1186/s12864-021-07672-5

Afiani, F. A., Joezy-Shekalgorabi, S., Amin-Afshar, M., Sadeghi, A.-A. & Jensen, J. (2021). Additive genetic and permanent environmental correlation between different parts of lactation in moderate and cold regions. Czech Journal of Animal Science, 66(4), 112-121. https://doi.org/10.17221/254/2020-CJAS

Karaman, E., Lund, M. S. & Su, G. (2020). Correction: Multi-trait single-step genomic prediction accounting for heterogeneous (co)variances over the genome . Heredity, 124(4), 618. https://doi.org/10.1038/s41437-020-0299-7

Christensen, O. F., Nielsen, B., Su, G., Xiang, T., Madsen, P., Ostersen, T., Velander, I. & Strathe, A. B. (2020). Correction to: A bivariate genomic model with additive, dominance and inbreeding depression effects for sire line and three-way crossbred pigs. Genetics, selection, evolution : GSE, 52(1), Artikel 23. https://doi.org/10.1186/s12711-020-00541-x

Jensen, J. (2020). Carrying the torch of the Journal of Animal Breeding and Genetics forward. Journal of Animal Breeding and Genetics, 137(1), 1-2. https://doi.org/10.1111/jbg.12462

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

Zhang, Q., Difford, G., Sahana, G., Løvendahl, P., Lassen, J., Lund, M. S., Guldbrandtsen, B. & Janss, L. (2020). Bayesian modeling reveals host genetics associated with rumen microbiota jointly influence methane emission in dairy cows. The ISME Journal, 14(8), 2019-2033. https://doi.org/10.1038/s41396-020-0663-x

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

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

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

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

Wang, X., Su, G., Hao, D., Lund, M. S. & Kadarmideen, H. N. (2020). Comparisons of improved genomic predictions generated by different imputation methods for genotyping by sequencing data in livestock populations. Journal of Animal Science and Biotechnology, 11(1), Artikel 3. https://doi.org/10.1186/s40104-019-0407-9

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

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

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

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

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

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

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

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

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

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

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

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, 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

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

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

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

Nielsen, H. M. & Kargo, M. (2020). An endangered horse breed can be conserved by using optimum contribution selection and preselection of stallions. Acta Agriculturae Scandinavica, Section A - Animal Science, 69(1-2), 127-130. https://doi.org/10.1080/09064702.2020.1728370

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

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

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

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

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

Macedo, F. L., Christensen, O. F., Astruc, J.-M., Aguilar, I., Masuda, Y. & Legarra, A. (2020). Bias and accuracy of dairy sheep evaluations using BLUP and SSGBLUP with metafounders and unknown parent groups. Genetics, selection, evolution : GSE, 52(1), Artikel 47. https://doi.org/10.1186/s12711-020-00567-1

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

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

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

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

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

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

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

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

Islam, M. S., Jensen, J., Løvendahl, P., Karlskov-Mortensen, P. & Shirali, M. (2020). Bayesian estimation of genetic variance and response to selection on linear or ratio traits of feed efficiency in dairy cattle. Journal of Dairy Science, 103(10), 9150-9166. https://doi.org/10.3168/jds.2019-17137

Huang, A., Zhi, D., Tang, H., Jiang, L., Luo, S. & Zhou, Y. (2020). Effect of Fe²⁺, Mn²⁺ catalysts on the performance of electro-Fenton degradation of antibiotic ciprofloxacin, and expanding the utilizing of acid mine drainage. Science of the Total Environment, 720, Artikel 137560. https://doi.org/10.1016/j.scitotenv.2020.137560

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

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.

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

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

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

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

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

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

Gebregiwergis, G. T., Sørensen, A. C., Henryon, M. & Meuwissen, T. (2020). Controlling Coancestry and Thereby Future Inbreeding by Optimum-Contribution Selection Using Alternative Genomic-Relationship Matrices. Frontiers in Genetics, 11, Artikel 345. https://doi.org/10.3389/fgene.2020.00345

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

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

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

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

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

Difford, G. F., Løvendahl, P., Veerkamp, R. F., Bovenhuis, H., Visker, M. H. P. W., Lassen, J. & de Haas, Y. (2020). Can greenhouse gases in breath be used to genetically improve feed efficiency of dairy cows? Journal of Dairy Science, 103(3), 2442-2459. https://doi.org/10.3168/jds.2019-16966

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

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

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

Cui, X., Zhang, S., Zhang, Q., Guo, X., Wu, C., Yao, M. & Sun, D. (2020). Comprehensive MicroRNA Expression Profile of the Mammary Gland in Lactating Dairy Cows With Extremely Different Milk Protein and Fat Percentages. Frontiers in Genetics, 11, Artikel 548268. https://doi.org/10.3389/fgene.2020.548268

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

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

Carmelo, V. A. O. & Kadarmideen, H. N. (2020). Genetic variations (eQTLs) in muscle transcriptome and mitochondrial genes, and trans-eQTL molecular pathways in feed efficiency from Danish breeding pigs. PLOS ONE, 15(9 September), Artikel e0239143. https://doi.org/10.1371/journal.pone.0239143

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., Dusza, M., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2020). Distinguishing pleiotropy from linked QTL between milk production traits and mastitis resistance in Nordic Holstein cattle. Genetics, selection, evolution : GSE, 52(1), Artikel 19. https://doi.org/10.1186/s12711-020-00538-6

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

Cagnano, G., Vázquez-De-Aldana, B. R., Asp, T., Roulund, N., Jensen, C. S. & Soto-Barajas, M. C. (2020). Determination of loline alkaloids and mycelial biomass in endophyte-infected schedonorus pratensis by near-infrared spectroscopy and chemometrics. Microorganisms, 8(5), Artikel 776. https://doi.org/10.3390/microorganisms8050776

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

Ba, H., Cai, Z., Gao, H., Qin, T., Liu, W., Xie, L., Zhang, Y., Jing, B., Wang, D. & Li, C. (2020). Chromosome-level genome assembly of Tarim red deer, Cervus elaphus yarkandensis. Scientific Data, 7(1), Artikel 187. https://doi.org/10.1038/s41597-020-0537-0

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