Publications

Peer-reviewed publications at QGG

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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. Article 528-540. https://doi.org/10.1111/jbg.12546

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, https://doi.org/10.1111/jbg.12536

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

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

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, Article 75. https://doi.org/10.1186/s12711-021-00669-4

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), Article skab231. https://doi.org/10.1093/jas/skab231

De, T., Goncalves, A., Speed, D., Froguel, P., NFBC consortium, Gaffney, D. J., Johnson, M. R., Jarvelin, M.-R. & Coin, L. J. (2021). Signatures of TSPAN8 variants associated with human metabolic regulation and diseases. iScience, 24(8), Article 102893. https://doi.org/10.1016/j.isci.2021.102893

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. https://doi.org/10.3920/978-90-8686-918-3

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), Article skab234. https://doi.org/10.1093/jas/skab234

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

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. https://doi.org/10.3920/978-90-8686-918-3

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. https://doi.org/10.3920/978-90-8686-918-3

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. https://doi.org/10.3920/978-90-8686-918-3

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, Article 667300. https://doi.org/10.3389/fgene.2021.667300

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), Article skab188. https://doi.org/10.1093/jas/skab188

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

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

Cuyabano, B. C. D., Rovere, G., Lim, D., Kim, T. H., Lee, H. K., Lee, S. H. & Gondro, C. (2021). GPS coordinates for modelling correlated herd effects in genomic prediction models applied to Hanwoo beef cattle. Animals, 11(7), Article 2050. https://doi.org/10.3390/ani11072050

Jørgensen, U., Kristensen, T., Jørgensen, J. R., Kongsted, A. G., De Notaris, C., Nielsen, C., Mortensen, E. Ø., Ambye-Jensen, M., Jensen, S. K., Stødkilde-Jørgensen, L., Dalsgaard, T. K., Møller, A. H., Grøn Sørensen, C., Asp, T., Lehmann Olsen, F. & Gylling, M. (2021). Green biorefining of grassland biomass. DCA - Nationalt Center for Fødevarer og Jordbrug. DCA rapport No. 193 https://dcapub.au.dk/djfpublikation/index.asp?action=show&id=1480

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), Article jkab133. https://doi.org/10.1093/g3journal/jkab133

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), Article skab139. https://doi.org/10.1093/jas/skab139

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.

Fois, M. (2021). Genetic dissection of crown rust (Puccinia coronata f.sp. lolii) resistance in perennial ryegrass (Lolium perenne L.). Århus Universitet.

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, https://doi.org/10.1111/age.13058

Fois, M., Malinowska, M., Schubiger, F. X. & Asp, T. (2021). Genomic Prediction and Genotype-by-Environment Interaction Analysis of Crown and Stem Rust in Ryegrasses in European Multi-Site Trials. Agronomy, 11(6), Article 1119. https://doi.org/10.3390/agronomy11061119

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

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). Data on: contrasting manual and automated assessment of larval body size and thermal stress responses in black soldier flies and houseflies. Dataset, Dryad Digital Repository. https://doi.org/10.5061/dryad.cjsxksn5p

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), Article 380. https://doi.org/10.3390/insects12050380

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(1), Article 46. https://doi.org/10.1186/s12711-021-00637-y

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

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

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, Article 636223. https://doi.org/10.3389/fmicb.2021.636223

Fu, Y., Thomas, A., Gasior, D., Harper, J., Gay, A., Jones, C., Hegarty, M., Asp, T., Fradera-Sola, A., Armstead, I. & Fernandez-Fuentes, N. (2021). A comparison of shared patterns of differential gene expression and gene ontologies in response to water-stress in roots and leaves of four diverse genotypes of Lolium and Festuca spp. temperate pasture grasses. PLOS ONE, 16(4), Article e0249636. https://doi.org/10.1371/journal.pone.0249636

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), Article 33. https://doi.org/10.1186/s12711-021-00624-3

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

Luo, H., Li, X., Hu, L., Xu, W., Chu, Q., Liu, A., Guo, G., Liu, L., Brito, L. F. & Wang, Y. (2021). Genomic analyses and biological validation of candidate genes for rectal temperature as an indicator of heat stress in Holstein cattle. Journal of Dairy Science, 104(4), 4441-4451. https://doi.org/10.3168/jds.2020-18725

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, Article 628205. https://doi.org/10.3389/fgene.2021.628205

Ramstein, G. (2021). High-resolution genome-wide association study pinpoints metal transporter and chelator genes involved in the genetic control of element levels in maize grain. G3: Genes, Genomes, Genetics, 11(4).

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. https://www.altinget.dk/forskning/artikel/forskere-nedskaeringer-i-forskningskapacitet-koster-paa-den-groenne-omstilling

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

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), Article 835. https://doi.org/10.3390/ani11030835

Li, Y., Pu, L., Shi, L., Gao, H., Zhang, P., Wang, L. & Zhao, F. (2021). Revealing New Candidate Genes for Teat Number Relevant Traits in Duroc Pigs Using Genome-Wide Association Studies. Animals, 11(3), Article 806. https://doi.org/10.3390/ani11030806

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, Article 634986. https://doi.org/10.3389/fgene.2021.634986/full

Ruud, A. K., Malinowska, M. & Asp, T. (2021, Feb 4). Hestebønners rodudvikling er undersøgt i rodrør. SEGES. https://www.landbrugsinfo.dk/public/b/2/e/afgroder_hestebonners_rodudvikling_er_undersogt_i_rodror

Martin, P., Ducrocq, V., Gordo, D. G. M. & Friggens, N. C. (2021). A new method to estimate residual feed intake in dairy cattle using time series data. Animal, 15(2), Article 100101. https://doi.org/10.1016/j.animal.2020.100101

Johannsen, I., Kilsgaard, B., Milkevych, V. & Moore, D. (2021). Design, modelling, and experimental validation of a scalable continuous-flow hydrothermal liquefaction pilot plant. Processes, 9(2), 1-18. Article 234. https://doi.org/10.3390/pr9020234

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

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, Article 2834. https://doi.org/10.1038/s41598-021-82625-2

Cao, L. (2021). Optimizing dairy cattle breeding programs in the presence of genotype-by-environment interaction. Århus Universitet.

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), Article 15. https://doi.org/10.1186/s12711-021-00609-2

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

Slagboom, M., Bengtsson, C., Thomasen, J. R. & Kargo, M. (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

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), Article skab003. https://doi.org/10.1093/jas/skab003

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

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

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

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

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), Article 23. https://doi.org/10.1186/s12711-021-00613-6

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

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), Article 1157. https://doi.org/10.3390/ani11041157

Stephansen, R. B., Lidauer, M., Nielsen, U. S., Pösö, J., Fikse, F., Manzanilla Pech, C. I. V. & Aamand, G. P. (2021). Genomic prediction of residual feed intake in the Nordic breeds using data from research herds and 3D cameras in commercial herds. In Interbull Bulletin: Proceedings of the 2021 Interbull Meeting (Vol. 56 (2021), pp. 162-166) https://journal.interbull.org/index.php/ib/article/view/66

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.

Shi, R., Brito, L. F., Liu, A., Luo, H., Chen, Z., Liu, L., Guo, G., Mulder, H., Ducro, B., van der Linden, A. & Wang, Y. (2021). Genotype-by-environment interaction in Holstein heifer fertility traits using single-step genomic reaction norm models. BMC Genomics, 22(1), Article 193. https://doi.org/10.1186/s12864-021-07496-3

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

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

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), Article 187. https://doi.org/10.1038/s41597-020-0537-0

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), Article 2953. https://doi.org/10.1038/s41598-020-59788-5

Karaman, E., Su, G., Croue, I. & Lund, M. S. (2020). Genomic prediction using data from multiple pure breeds and crossbreds. Abstract from 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

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. Article 1303. https://doi.org/10.3390/antiox9121303

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, Article 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), Article 18434. https://doi.org/10.1038/s41598-020-75612-6

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

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), Article 13641. https://doi.org/10.1038/s41598-020-70380-9

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.

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

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, Article 586155. https://doi.org/10.3389/fgene.2020.586155

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

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

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. Article e20049. https://doi.org/10.1002/tpg2.20049

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, Article 575467. https://doi.org/10.3389/fpls.2020.575467

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), Article 58. https://doi.org/10.1186/s12711-020-00578-y

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

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. Article 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, Article 570026. https://doi.org/10.3389/fpls.2020.570026

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

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

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), Article e39. https://doi.org/10.1002/leg3.39

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, Article 735358. https://doi.org/10.1016/j.aquaculture.2020.735358

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

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, Article 866. https://doi.org/10.3389/fgene.2020.00866

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, Article 1181. https://doi.org/10.3389/fpls.2020.01181

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

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

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

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), Article 229. https://doi.org/10.1093/jas/skaa229

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, Article 90. https://doi.org/10.1186/s13007-020-00634-0

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Jette Odgaard Villemoes