Publications

Peer-reviewed publications at QGG

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Hjortø, L., Andersen, T., Kargo, M. & Sørensen, A. C. (2022). Breeding schemes with optimum-contribution selection or truncation selection for beef cattle destined for use on dairy females. Journal of Dairy Science, 105(5), 4314-4323. https://doi.org/10.3168/jds.2021-21258

Slagboom, M., Milkevych, V., Liu, H., Thomasen, J. R., Kargo, M. & Schmidtmann, C. (2022). Conservation of local Red cattle breeds by collaboration with a mainstream Red dairy cattle breed. Livestock Science, 260, [104936]. https://doi.org/10.1016/j.livsci.2022.104936

Løvendahl, P. & Buitenhuis, A. J. (2022). Genetic and phenotypic variation and consistency in cow preference and circadian use of robotic milking units. Journal of Dairy Science, 105(6), 5283-5295. https://doi.org/10.3168/jds.2021-21593

Manzanilla Pech, C. I. V., Difford, G., Sahana, G., Rome, H. J. S., Løvendahl, P. & Lassen, J. (2022). Genome-wide association study for methane emission traits in Danish Holstein cattle. Journal of Dairy Science, 105(2), 1357-1368. https://doi.org/10.3168/jds.2021-20410

Mesbah-Uddin, M., Guldbrandtsen, B., Capitan, A., Lund, M. S., Boichard, D. & Sahana, G. (2022). Genome-wide association study with imputed whole-genome sequence variants including large deletions for female fertility in 3 Nordic dairy cattle breeds. Journal of Dairy Science, 105(2), 1298-1313. https://doi.org/10.3168/jds.2021-20655

Guillenea, A., Su, G., Lund, M. S. & Karaman, E. (2022). Genomic prediction in Nordic Red dairy cattle considering breed origin of alleles. Journal of Dairy Science, 105(3), 2426-2438. https://doi.org/10.3168/jds.2021-21173

Bordbar, F., Mohammadabadi, M., Jensen, J., Xu, L., Li, J. & Zhang, L. (2022). Identification of Candidate Genes Regulating Carcass Depth and Hind Leg Circumference in Simmental Beef Cattle Using Illumina Bovine Beadchip and Next-Generation Sequencing Analyses. Animals, 12(9), [1103]. https://doi.org/10.3390/ani12091103

Raffo, M. A., Sarup, P., Guo, X., Liu, H., Andersen, J. R., Orabi, J., Jahoor, A. & Jensen, J. (2022). Improvement of genomic prediction in advanced wheat breeding lines by including additive-by-additive epistasis. Theoretical and Applied Genetics, 135(3), 965-978. https://doi.org/10.1007/s00122-021-04009-4

Liu, T., Luo, C., Ma, J., Wang, Y., Shu, D., Qu, H. & Su, G. (2022). Including dominance effects in the prediction model through locus-specific weights on heterozygous genotypes can greatly improve genomic predictive abilities. Heredity, 128(3), 154-158. https://doi.org/10.1038/s41437-022-00504-6

Cai, Z., Christensen, O. F., Lund, M. S., Ostersen, T. & Sahana, G. (2022). Large-scale association study on daily weight gain in pigs reveals overlap of genetic factors for growth in humans. BMC Genomics, 23, [133]. https://doi.org/10.1186/s12864-022-08373-3

Moeskjær, S., Skovbjerg, C. K., Tausen, M., Wind, R., Roulund, N., Janss, L. & Andersen, S. U. (2022). Major effect loci for plant size before onset of nitrogen fixation allow accurate prediction of yield in white clover. Theoretical and Applied Genetics, 135(1), 125-143. https://doi.org/10.1007/s00122-021-03955-3

Bengtsson, C., Stålhammar, H., Thomasen, J. R., Eriksson, S., Fikse, W. F. & Strandberg, E. (2022). Mating allocations in Nordic Red Dairy Cattle using genomic information. Journal of Dairy Science, 105(2), 1281-1297. https://doi.org/10.3168/jds.2021-20849

Eydivandi, S., Roudbar, M. A., Ardestani, S. S., Momen, M. & Sahana, G. (2021). A selection signatures study among Middle Eastern and European sheep breeds. Journal of Animal Breeding and Genetics, 138(5), 574-588. https://doi.org/10.1111/jbg.12536

Rome, H. J. S., Chu, T. T., Marois, D., Huang, C-H., Madsen, P. & Jensen, J. (2021). Accounting for genetic architecture for body weight improves accuracy of predicting breeding values in a commercial line of broilers. Journal of Animal Breeding and Genetics, 138(5), [528-540]. https://doi.org/10.1111/jbg.12546

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

Schmidtmann, C., Schönherz, A., Guldbrandtsen, B., Marjanovic, J., Calus, M., Hinrichs, D. & Thaller, G. (2021). Assessing the genetic background and genomic relatedness of red cattle populations originating from Northern Europe. Genetics Selection Evolution, 53(1), [23]. https://doi.org/10.1186/s12711-021-00613-6

Olesen, J. E., Ingvartsen, K. L., Williams, M. H., Hertel, O., Jacobsen, C. S., Lund, M. S., Bach, H. & Halberg, N. (2021). Besparelser rammer grøn forskning på Aarhus Universitet: Er politikerne overhovedet klar over konsekvenserne? Altinget.dk. https://www.altinget.dk/forskning/artikel/forskere-nedskaeringer-i-forskningskapacitet-koster-paa-den-groenne-omstilling

Eiríksson, J. H., Karaman, E., Su, G. & Christensen, O. F. (2021). Breed of origin of alleles and genomic predictions for crossbred dairy cows. Genetics Selection Evolution, 53, [84]. https://doi.org/10.1186/s12711-021-00678-3

Manzanilla Pech, C. I. V., Løvendahl, P., Mansan Gordo, D. G., Difford, G., Pryce, J., Schenkel, F. S., Wegmann, S., Miglior, F., Chud, T. C. S., Moate, P. J., Williams, S. R. O., Richardson, C. M., Stothard, P. & Lassen, J. (2021). Breeding for reduced methane emission and feed-efficient Holstein cows: An international response. Journal of Dairy Science, 104(8), 8983-9001. https://doi.org/10.3168/jds.2020-19889

Johansen, K., Hein, L., Spleth, P., Vestergaard, M., Nielsen, H. M. & Kargo, M. (2021). Comparing growth and feed intake in pure- and crossbred heifers fed different energy concentrations. In E. Strandberg, L. Pinotti, S. Messori, D. Kenny, M. Lee, J. F. Hocquette, V. A. P. Cadavez, S. Millet, R. Evans, T. Veldkamp, M. Pastell & G. Pollott (Eds.), Book of Abstracts of the 72nd Annual Meeting of the European Federation of Animal Science (pp. 521). Wageningen Academic Publishers. EAAP Book of Abstracts Vol. 27 https://doi.org/10.3920/978-90-8686-918-3

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

Slagboom, M. (Producer), Bengtsson, C. (Producer), Thomasen, J. R. (Producer) & Kargo, M. (Producer). (2021). Consequences of genetic changes considering G by E and different production environments: GenTore WP5.4 Decision Support Tools. Pictures, Video and sound recordings (digital) https://www.youtube.com/watch?v=FOsG2Cw4YP8&feature=youtu.be

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 A: Animal Sciences, 70(1). https://doi.org/10.1080/09064702.2020.1867632

Laursen, S. F., Hansen, L. S., Bahrndorff, S., Nielsen, H. M., Noer, N. K., Renault, D., Sahana, G., Sørensen, J. G. & Kristensen, T. N. (2021). Contrasting Manual and Automated Assessment of Thermal Stress Responses and Larval Body Size in Black Soldier Flies and Houseflies. Insects, 12(5), [380]. https://doi.org/10.3390/insects12050380

Schmidtmann, C., Thaller, G., Kargo, M., Hinrichs, D. & Ettema, J. (2021). Derivation of economic values for German dairy breeds by means of a bio-economic model—with special emphasis on functional traits. Journal of Dairy Science, 104(3), 3144-3157. https://doi.org/10.3168/jds.2019-17635

Stephansen, R. B., Lassen, J., Ettema, J. F., Sørensen, L. P. & Kargo, M. (2021). Economic value of residual feed intake in dairy cattle breeding goals. Livestock Science, 253, [104696]. https://doi.org/10.1016/j.livsci.2021.104696

Houlahan, K., Schenkel, F. S., Hailemariam, D., Lassen, J., Kargo, M., Cole, J. B., Connor, E. E., Wegmann, S., Oliveira, G. A., Miglior, F., Fleming, A., Chud, T. C. S. & Baes, C. F. (2021). Effects of incorporating dry matter intake and residual feed intake into a selection index for dairy cattle using deterministic modeling. Animals, 11(4), [1157]. https://doi.org/10.3390/ani11041157

Olijhoek, D., Hellwing, A. L. F., Lund, P., Weisbjerg, M. R., Løvendahl, P. & Børsting, C. F. (2021). Enteric methane emission of Holstein and Jersey dairy cows at high dietary concentrate proportions. Poster session presented at Meeting in iClimate.

Gautason, E., Sahana, G., Su, G., Benjamínsson, B. H., Jóhannesson, G. & Guldbrandtsen, B. (2021). Erratum to: Short communication: investigation of the feasibility of genomic selection in Icelandic Cattle. Journal of Animal Science, 99(8), [skab234]. https://doi.org/10.1093/jas/skab234

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

Zhang, H., Liu, A., Wang, Y., Luo, H., Yan, X., Guo, X., Li, X., Liu, L. & Su, G. (2021). Genetic Parameters and Genome-Wide Association Studies of Eight Longevity Traits Representing Either Full or Partial Lifespan in Chinese Holsteins. Frontiers in Genetics, 12, [634986]. https://doi.org/10.3389/fgene.2021.634986/full

Zaalberg, R. M., Poulsen, N. A., Bovenhuis, H., Sehested, J., Larsen, L. B. & Buitenhuis, A. J. (2021). Genetic analysis on infrared-predicted milk minerals for Danish dairy cattle. Journal of Dairy Science, 104(8), 8947-8958. https://doi.org/10.3168/jds.2020-19638

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

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

Gao, H., Su, G., Jensen, J., Madsen, P., Christensen, O. F., Ask, B., Poulsen, B. G., Ostersen, T. & Nielsen, B. (2021). Genetic parameters and genomic prediction for feed intake recorded at the group and individual level in different production systems for growing pigs. Genetics Selection Evolution, 53(1), [33]. https://doi.org/10.1186/s12711-021-00624-3

Zaalberg, R. M., Chu, T. T., Villumsen, T. M. & Jensen, J. (2021). Genetic parameters for birth weight and litter size in Danish organic pigs. In Book of Abstracts of the 72nd Annual Meeting of the European Federation of Animal Science (Vol. 27). Wageningen Academic Publicers. EAAP Book of Abstracts https://doi.org/10.3920/978-90-8686-918-3

Manzanilla Pech, C. I. V., Stephansen, R. B. & Lassen, J. (2021). Genetic parameters for feed efficiency using 3D cameras in jersey cows in commercial Danish farms. In Proceedings of the Association for the Advancement of Animal Breeding and Genetics (pp. 226-229). Association for the Advancement of Animal Breeding and Genetics. http://www.aaabg.org/aaabghome/AAABG24papers/57Pech24226.pdf

Villumsen, T. M., Chu, T. T., Zaalberg, R. M. & Jensen, J. (2021). Genetic parameters for growth rate in Danish organic pigs. In Book of Abstracts of the 72nd Annual Meeting of the European Federation of Animal Science (Vol. 27). Wageningen Academic Publicers. EAAP Book of Abstracts https://doi.org/10.3920/978-90-8686-918-3

Handegård, K. W., Madsen, P., Storengen, L. M. & Lingaas, F. (2021). Genetic parameters for noise reactivity in standard poodles. Journal of Veterinary Behavior, 45, 33-36. https://doi.org/10.1016/j.jveb.2021.06.005

Luo, H., Brito, L. F., Li, X., Su, G., Dou, J., Xu, W., Yan, X., Zhang, H., Guo, G., Liu, L. & Wang, Y. (2021). Genetic parameters for rectal temperature, respiration rate, and drooling score in Holstein cattle and their relationships with various fertility, production, body conformation, and health traits. Journal of Dairy Science, 104(4), 4390-4403. https://doi.org/10.3168/jds.2020-19192

Chu, T. T., Zaalberg, R. M., Villumsen, T. M. & Jensen, J. (2021). Genetic parameters of piglet mortality in Danish organic pigs. In Book of Abstracts of the 72nd Annual Meeting of the European Federation of Animal Science (Vol. 27). Wageningen Academic Publicers. EAAP Book of Abstracts https://doi.org/10.3920/978-90-8686-918-3

Gebreyesus, G., Lund, M. S., Kupisiewicz, K. & Su, G. (2021). Genetic parameters of semen quality traits and genetic correlations with service sire nonreturn rate in Nordic Holstein bulls. Journal of Dairy Science, 104(9), 10010-10019. https://doi.org/10.3168/jds.2021-20403

Shi, S., Li, X., Fang, L., Liu, A., Su, G., Zhang, Y., Luobu, B., Ding, X. & Zhang, S. (2021). Genomic Prediction Using Bayesian Regression Models With Global-Local Prior. Frontiers in Genetics, 12, [628205]. https://doi.org/10.3389/fgene.2021.628205

Gautason, E., Schönherz, A. A., Sahana, G. & Guldbrandtsen, B. (2021). Genomic inbreeding and selection signatures in the local dairy breed Icelandic Cattle. Animal Genetics, 52(3), 251-262. https://doi.org/10.1111/age.13058

Karaman, E., Su, G., Croue, I. & Lund, M. S. (2021). Genomic prediction using a reference population of multiple pure breeds and admixed individuals. Genetics Selection Evolution, 53, [46]. https://doi.org/10.1186/s12711-021-00637-y

Eiríksson, J. H., Byskov, K., Thomassen, J. R., Su, G. & Christensen, O. F. (2021). Genomic predictions of crossbred dairy cows based on breed of origin of alleles. 520-520. Abstract from 72nd Annual Meeting of the European Federation of Animal Science, Davos, Switzerland.

Eydivandi, S., Roudbar, M. A., Karimi, M. O. & Sahana, G. (2021). Genomic scans for selective sweeps through haplotype homozygosity and allelic fixation in 14 indigenous sheep breeds from Middle East and South Asia. Scientific Reports, 11, [2834]. https://doi.org/10.1038/s41598-021-82625-2

Villumsen, T. M., Su, G., Guldbrandtsen, B., Asp, T. & Lund, M. S. (2021). Genomic selection in American mink (Neovison vison) using a single-step genomic best linear unbiased prediction model for size and quality traits graded on live mink. Journal of Animal Science, 99(1), [skab003]. https://doi.org/10.1093/jas/skab003

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

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

Kargo, M., Clasen, J. B., Nielsen, H. M., Byskov, K. & Norberg, E. (2021). Heterosis and breed effects for milk production and udder health traits in crosses between Danish Holstein, Danish Red, and Danish Jersey. Journal of Dairy Science, 104(1), 678-682. https://doi.org/10.3168/jds.2019-17866

Mei, Q., Fu, C., Sahana, G., Chen, Y., Yin, L., Miao, Y., Zhao, S. & Xiang, T. (2021). Identification of new semen trait-related candidate genes in Duroc boars through genome-wide association and weighted gene co-expression network analyses. Journal of Animal Science, 99(7), [skab188]. https://doi.org/10.1093/jas/skab188

Slagboom, M., Sørensen, A. C., Thomasen, J. R., Liu, H., Kargo, M. & Hjortø, L. (2021). Ignoring genotype by environment interaction in the genetic evaluation of dairy cattle reduces accuracy but may increase selection intensity. Journal of Dairy Science, 104(12), 12756-12764. https://doi.org/10.3168/jds.2021-20876

Mohammadabadi, M., Bordbar, F., Jensen, J., Du, M. & Guo, W. (2021). Key genes regulating skeletal muscle development and growth in farm animals. Animals, 11(3), [835]. https://doi.org/10.3390/ani11030835

Christensen, O. F., Höglund, J. & Chu, T. T. (2021). Lavere halebidsfrekvens gennem kvantitativ avl.

Zhao, Q., Liu, H., Qadri, Q. R., Wang, Q., Pan, Y. & Su, G. (2021). Long-term impact of conventional and optimal contribution conservation methods on genetic diversity and genetic gain in local pig breeds. Heredity, 127(6), 546-553. https://doi.org/10.1038/s41437-021-00484-z

Milkevych, V., Karaman, E., Sahana, G., Janss, L., Cai, Z. & Lund, M. S. (2021). MeSCoT: The tool for quantitative trait simulation through the mechanistic modeling of genes' regulatory interactions. G3 (Bethesda, Md.), 11(7), [jkab133]. https://doi.org/10.1093/g3journal/jkab133

Rohde, P. D., Nyegaard, M., Kjolby, M. & Sørensen, P. (2021). Multi-Trait Genomic Risk Stratification for Type 2 Diabetes. Frontiers in Medicine, 8, [711208]. https://doi.org/10.3389/fmed.2021.711208

Hao, D., Bai, J., Du, J., Wu, X., Thomsen, B., Gao, H., Su, G. & Wang, X. (2021). Overview of metabolomic analysis and the integration with multi-omics for economic traits in cattle. Metabolites, 11(11), [753]. https://doi.org/10.3390/metabo11110753

Pan, Z., Yao, Y., Yin, H., Cai, Z., Wang, Y., Bai, L., Kern, C., Halstead, M., Chanthavixay, G., Trakooljul, N., Wimmers, K., Sahana, G., Su, G., Lund, M. S., Fredholm, M., Karlskov-Mortensen, P., Ernst, C. W., Ross, P., Tuggle, C. K. ... Zhou, H. (2021). Pig genome functional annotation enhances the biological interpretation of complex traits and human disease. Nature Communications, 12(1), [5848]. https://doi.org/10.1038/s41467-021-26153-7

Hjortø, L., Henryon, M., Liu, H., Berg, P., Thomasen, J. R. & Sørensen, A. C. (2021). Pre-selection against a lethal recessive allele in breeding schemes with optimum-contribution selection or truncation selection. Genetics Selection Evolution, 53, [75]. https://doi.org/10.1186/s12711-021-00669-4

Ma, X., Christensen, O. F., Gao, H., Huang, R., Nielsen, B., Madsen, P., Jensen, J., Ostersen, T., Li, P., Shirali, M. & Su, G. (2021). Prediction of breeding values for group-recorded traits including genomic information and an individually recorded correlated trait. Heredity, 126(1), 206-217. https://doi.org/10.1038/s41437-020-0339-3

Rohde, P. D., Kristensen, T. N., Sarup, P., Muñoz, J. & Malmendal, A. (2021). Prediction of complex phenotypes using the Drosophila melanogaster metabolome. Heredity, 126(5), 717-732. https://doi.org/10.1038/s41437-021-00404-1

Salimiyekta, Y., Vaez‐torshizi, R., Abbasi, M. A., Emmamjome‐kashan, N., Amin‐afshar, M., Guo, X. & Jensen, J. (2021). Random regression model for genetic evaluation and early selection in the iranian holstein population. Animals, 11(12), [3492]. https://doi.org/10.3390/ani11123492

Gebreyesus, G., Lund, M. S., Sahana, G. & Su, G. (2021). Reliabilities of Genomic Prediction for Young Stock Survival Traits Using 54K SNP Chip Augmented With Additional Single-Nucleotide Polymorphisms Selected From Imputed Whole-Genome Sequencing Data. Frontiers in Genetics, 12, [667300]. https://doi.org/10.3389/fgene.2021.667300

Macedo, F. L., Christensen, O. F. & Legarra, A. (2021). Selection and drift reduce genetic variation for milk yield in Manech Tête Rousse dairy sheep. JDS Communications , 31-34. https://doi.org/10.3168/jdsc.2020-0010

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, [15]. https://doi.org/10.1186/s12711-021-00609-2

Gautason, E., Sahana, G., Su, G., Benjamínsson, B. H., Jóhannesson, G. & Guldbrandtsen, B. (2021). Short Communication: Investigation of the feasibility of genomic selection in Icelandic Cattle. Journal of Animal Science, 99(7), [skab139]. https://doi.org/10.1093/jas/skab139

Esfandyari, H. & Jensen, J. (2021). Simultaneous Bayesian estimation of genetic parameters for curves of weight, feed intake, and residual feed intake in beef cattle. Journal of Animal Science, 99(9). https://doi.org/10.1093/jas/skab231

Fu, C., Ostersen, T., Christensen, O. F. & Xiang, T. (2021). Single-step genomic evaluation with metafounders for feed conversion ratio and average daily gain in Danish Landrace and Yorkshire pigs. Genetics Selection Evolution, 53(1), 79. [79]. https://doi.org/10.1186/s12711-021-00670-x

Zhu, Z., Difford, G., Noel, S. J., Lassen, J., Løvendahl, P. & Hojberg, O. (2021). Stability Assessment of the Rumen Bacterial and Archaeal Communities in Dairy Cows Within a Single Lactation and Its Association With Host Phenotype. Frontiers in Microbiology, 12, [636223]. https://doi.org/10.3389/fmicb.2021.636223

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), [1]. https://doi.org/10.1186/s12711-020-00598-8

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

Hartfield, M., Poulsen, N. A., Guldbrandtsen, B. & Bataillon, T. (2021). Using singleton densities to detect recent selection in Bos taurus. Evolution Letters, 5(6), 595-606. https://doi.org/10.1002/evl3.263

Gebreyesus, G., Poulsen, N. A., Larsen, M. K., Larsen, L. B., Sørensen, E. S., Würtz Heegaard, C. & Buitenhuis, A. J. (2021). Vitamin B12 and transcobalamin in bovine milk: Genetic variation and genome-wide association with loci along the genome. JDS Communications , 2(3), 127-131. https://doi.org/10.3168/jdsc.2020-0048

Kargo, M. & Nielsen, V. H., (2021). Vurdering af racespecifikke krav til Jysk Kvæg, No. 2021-0203800, 11 p., Jun 23, 2021. Rådgivningsnotat fra DCA – National Center for Fødevarer og Jordbrug

Jensen, J. (2021). Word of thanks to Professor Miguel-Pérez Enciso. Journal of Animal Breeding and Genetics, 138(3), 277-277. https://doi.org/10.1111/jbg.12548

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

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

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

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), [47]. https://doi.org/10.1186/s12711-020-00567-1

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

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

Munksgaard, L., Weisbjerg, M. R., Henriksen, J. C. S. & Løvendahl, P. (2020). Changes to steps, lying, and eating behavior during lactation in Jersey and Holstein cows and the relationship to feed intake, yield, and weight. Journal of Dairy Science, 103(5), 4643-4653. https://doi.org/10.3168/jds.2019-17565

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, 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), [3]. https://doi.org/10.1186/s40104-019-0407-9

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, [345]. https://doi.org/10.3389/fgene.2020.00345

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), [23]. https://doi.org/10.1186/s12711-020-00541-x

Mahmood, K., Orabi, J., Kristensen, P. S., Sarup, P., Jørgensen, L. N. & Jahoor, A. (2020). De novo transcriptome assembly, functional annotation, and expression profiling of rye (Secale cereale L.) hybrids inoculated with ergot (Claviceps purpurea). Scientific Reports, 10(1), [13475]. https://doi.org/10.1038/s41598-020-70406-2

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), [19]. https://doi.org/10.1186/s12711-020-00538-6

Clasen, J. B., Fikse, W. F., Kargo, M., Rydhmer, L., Strandberg, E. & Østergaard, S. (2020). Economic consequences of dairy crossbreeding in conventional and organic herds in Sweden. Journal of Dairy Science, 103(1), 514-528. https://doi.org/10.3168/jds.2019-16958

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), [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. [1751731119002386]. https://doi.org/10.1017/S1751731119002386

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), [1958]. https://doi.org/10.3390/ani10111958

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, [575467]. https://doi.org/10.3389/fpls.2020.575467

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 from 71st Annual Meeting of European Federation of Animal Science. https://www.wageningenacademic.com/doi/book/10.3920/978-90-8686-900-8

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Jette Odgaard Villemoes