Publikationer

Peer-reviewed publikationer ved QGG

Ramstein, G. P. & Buckler, E. S. (2022). Prediction of evolutionary constraint by genomic annotations improves functional prioritization of genomic variants in maize. Genome Biology, 23(1), Artikel 183. https://doi.org/10.1186/s13059-022-02747-2

Poulsen, B. G., Ostersen, T., Nielsen, B. & Christensen, O. F. (2022). Predictive performances of animal models using different multibreed relationship matrices in systems with rotational crossbreeding. Genetics, selection, evolution : GSE, 54, Artikel 25. https://doi.org/10.1186/s12711-022-00714-w

Thomasen, J. R., Nielsen, H. M., Kargo, M. & Slagboom, M. (2022). Purebred breeding goals optimized for crossbreeding improves crossbred performance. I Book of Abstracts of the 73rd Annual Meeting - EAAp (s. 598). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-937-4

Milkevych, V., Karaman, E., Sahana, G., Janss, L., Cai, Z. & Lund, M. S. (2022). Quantitative trait simulation using MeSCoT software. I WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/30_009.pdf

Malinowska, M., Ruud, A. K., Jensen, J., Svane, S. F., Smith, A. G., Bellucci, A., Lenk, I., Nagy, I., Fois, M., Didion, T., Thorup-Kristensen, K., Jensen, C. S. & Asp, T. (2022). Relative importance of genotype, gene expression, and DNA methylation on complex traits in perennial ryegrass. The Plant Genome, 15(4), Artikel e20253. https://doi.org/10.1002/tpg2.20253

Martinez Boggio, G., Christensen, O. F., Legarra, A., Allain, C., Meynadier, A. & Marie-Etancelin, C. (2022). Rumen bacteria do not provide improved genetic evaluation of dairy traits in sheep. I WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/05_009.pdf

Cai, Z. & Sahana, G. (2022). Segregation of the structural variant responds for mastitis resistance in re-sequencing Nordic Holstein animals. I WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/28_004.pdf

Manzanilla Pech, C. I. V., Stephansen, R. B., Difford, G., Løvendahl, P. & Lassen, J. (2022). Selecting for feed efficient cows will help to reduce methane gas emissions. Frontiers in Genetics, 13, Artikel 885932. https://doi.org/10.3389/fgene.2022.885932

Chu, T. T., Zaalberg, R. M., Jensen, J. & Villumsen, T. M. (2022). Selection for piglet mortality and litter size in outdoor organic pig production systems. I WCGALP 2022 Programme book Wageningen Academic Publishers. https://wcgalp.com/wp-content/uploads/2022/07/e-WCGALP22-programme-booklet.pdf

Bolormaa, S., MacLeod, I. M., Khansefid, M., Marret, L., Wales, B., Miglior, F., Baes, C. F., Schenkel, F. S., Connor, E. E., Manzanilla Pech, C. I. V., Coffey, M., Stothard, P., Herman, E., Nieuwhof, G. J., Goddard, M. E. & Pryce, J. (2022). Sharing of either phenotypes or genetic variants can increase the accuracy of genomic prediction of feed efficiency. Genetics Selection Evolution, 54(1), Artikel 60. https://doi.org/10.1186/s12711-022-00749-z

Schmidtmann, C., Slagboom, M., Sørensen, A. C., Hinrichs, D., Thaller, G. & Kargo, M. (2022). Short- and long-term consequences of collaboration between Northern European Red dairy and dual-purpose cattle. Journal of Animal Breeding and Genetics, 139(4), 447-461. https://doi.org/10.1111/jbg.12672

Kargo, M., Nielsen, H. M., Østergaard, S., Kring, R. D., Slagboom, M., Clasen, J. B. & Thomasen, J. R. (2022). Should we breed cows like pigs? A new organisation of dairy cattle breeding. I WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/45_007.pdf

Liu, H., Nielsen, H. M., Kargo, M., Thomasen, J. R., Berg, P., Slagboom, M., Sørensen, A. C. & Milkevych, V. (2022). Simulation of animal crossbreeding schemes using ADAM software. I WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/56_007.pdf

Kempe, R. M., Mehtiö, T., Leino, A.-M., Koivula, M., Pitkänen, T. J., Stephansen, R. B., Mäntysaari, P., Negussie, E., Pösö, J., Nielsen, U. S., Fikse, W. F., Aamand, G. P. & Lidauer, M. H. (2022). Single-step genomic prediction for metabolic body weight of Nordic Red dairy cattle. I WCGALP 2022: Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/14_005.pdf

Speed, D., Kaphle, A. & Balding, D. J. (2022). SNP-based heritability and selection analyses: Improved models and new results. BioEssays, 44(5), e2100170. Artikel 2100170. https://doi.org/10.1002/bies.202100170

Kotlarz, K., Kosinska-Selbi, B., Cai, Z., Sahana, G. & Szyda, J. (2022). The application of mixed linear models for the estimation of functional effects on bovine stature based on SNP summary. I WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/11_004.pdf

Zaalberg, R. M., Nielsen, H. M., Sorensen, A. C., Chu, T. T., Jensen, J. & Villumsen, T. M. (2022). The Effect of Using Organic or Conventional Sires on Genetic Gain in Organic Pigs: A Simulation Study. Animals, 12(4), Artikel 455. https://doi.org/10.3390/ani12040455

Sterenborg, R. B. T. M., Galesloot, T. E., Teumer, A., Netea-Maier, R. T., Speed, D., Meima, M. E., Visser, W. E., Smit, J. W. A., Peeters, R. P. & Medici, M. (2022). The effects of common genetic variation in 96 genes involved in thyroid hormone regulation on TSH and FT4 concentrations. The Journal of Clinical Endocrinology & Metabolism, 107(6), e2276-e2283. https://doi.org/10.1210/clinem/dgac136

Sargent, C., Kosmadopoulos, A., Zhou, X. & Roach, G. D. (2022). Timing of Sleep in the Break Between Two Consecutive Night-Shifts: The Effect of Different Strategies on Daytime Sleep and Night-Time Neurobehavioural Function. Nature and Science of Sleep, 14, 231-242. https://doi.org/10.2147/NSS.S336795

Hansen, L. S., Laursen, S. F., Bahrndorff, S., Kargo, M., Kristensen, T. N., Sahana, G., Sørensen, J. G. & Nielsen, H. M. (2022). Towards selective breeding in insects – estimating genetic parameters with individual-level phenotypes and pedigree. I WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/53_010.pdf

Jensen, J. (2022). Word of thanks to professor Ignacy Misztal. Journal of Animal Breeding and Genetics, 139(4), 369-369. https://doi.org/10.1111/jbg.12725

Chen, C. J., Garrick, D., Fernando, R., Karaman, E., Stricker, C., Keehan, M. & Cheng, H. (2022). XSim Version 2: Simulation of Modern Breeding Programs. G3: Genes, Genomes, Genetics, 12(4), Artikel jkac032. https://doi.org/10.1093/g3journal/jkac032

Econogene Consortium, Ajmone-Marsan, P., Bradley, D. G., Colli, L., Drögemüller, C., Lei, C., Mannen, H., Pompanon, F., Tosser-Klopp, G. & Jiang, Y. (2022). Y-chromosomal haplogroups from wild and domestic goats reveal ancient migrations and recent introgressions. I R. F. Veerkamp & Y. de Haas (red.), Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP): Technical and species orientated innovations in animal breeding, and contribution of genetics to solving societal challenges (s. 886-889). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-940-4_208

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

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), Artikel e0249636. https://doi.org/10.1371/journal.pone.0249636

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

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), Artikel 100101. https://doi.org/10.1016/j.animal.2020.100101

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

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

Jefsen, O. H., Speed, M., Speed, D. & Østergaard, S. D. (2021). Bipolar disorder and cannabis use: A bidirectional two-sample Mendelian randomization study. Addiction Biology, 26(6), Artikel 13030. https://doi.org/10.1111/adb.13030

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

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(1), Artikel 84. https://doi.org/10.1186/s12711-021-00678-3

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. I 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 (red.), Book of Abstracts of the 72nd Annual Meeting of the European Federation of Animal Science (s. 521). Wageningen Academic Publishers. 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., 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. Billeder, Video- og Lydoptagelser (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, Section A - Animal Science, 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), Artikel 380. https://doi.org/10.3390/insects12050380

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. Datasæt, Dryad Digital Repository. https://doi.org/10.5061/dryad.cjsxksn5p

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

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. Artikel 234. https://doi.org/10.3390/pr9020234

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, Artikel 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), Artikel 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 præsenteret på 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), Artikel skab234. https://doi.org/10.1093/jas/skab234

Madsen, M. D., van der Werf, J., Börner, V., Mulder, H. A. & Clark, S. (2021). Estimation of macro- and micro-genetic environmental sensitivity in unbalanced datasets. Animal, 15(12), Artikel 100411. https://doi.org/10.1016/j.animal.2021.100411

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

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), Artikel iyab130. https://doi.org/10.1093/genetics/iyab130

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

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), Artikel 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. I Book of Abstracts of the 72nd Annual Meeting of the European Federation of Animal Science (Bind 27). Wageningen Academic Publicers. 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. I Proceedings of the Association for the Advancement of Animal Breeding and Genetics (s. 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. I Book of Abstracts of the 72nd Annual Meeting of the European Federation of Animal Science (Bind 27). Wageningen Academic Publicers. 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. I Book of Abstracts of the 72nd Annual Meeting of the European Federation of Animal Science (Bind 27). Wageningen Academic Publicers. 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

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

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), Artikel 1119. https://doi.org/10.3390/agronomy11061119

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. I Interbull Bulletin: Proceedings of the 2021 Interbull Meeting (Bind 56 (2021), s. 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 fra 72nd Annual Meeting of the European Federation of Animal Science, Davos, Schweiz.

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), Artikel 46. https://doi.org/10.1186/s12711-021-00637-y

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

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, Artikel 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), Artikel 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

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), Artikel 193. https://doi.org/10.1186/s12864-021-07496-3

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), Artikel 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 Nr. 193 https://dcapub.au.dk/djfpublikation/index.asp?action=show&id=1480

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

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

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), Artikel 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

Zhang, Q., Privé, F., Vilhjálmsson, B. & Speed, D. (2021). Improved genetic prediction of complex traits from individual-level data or summary statistics. Nature Communications, 12(1), Artikel 4192. https://doi.org/10.1038/s41467-021-24485-y

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

Poulsen, N. A., Sundekilde, U. K., Lindahl, E. I., Buitenhuis, A. J. & Larsen, L. B. (2021). Milk Genomics: Variation in milk composition in major Danish dairy breeds and exploitation in dairy products. DCA - Nationalt Center for Fødevarer og Jordbrug. DCA Report Nr. 194 https://dcapub.au.dk/djfpublikation/index.asp?action=show&id=1479

Rohde, P. D., Nyegaard, M., Kjolby, M. & Sørensen, P. (2021). Multi-Trait Genomic Risk Stratification for Type 2 Diabetes. Frontiers in Medicine, 8, Artikel 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), Artikel 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), Artikel 5848. https://doi.org/10.1038/s41467-021-26153-7

Washburn, J. D., Cimen, E., Ramstein, G., Reeves, T., O’Briant, P., McLean, G., Cooper, M., Hammer, G. & Buckler, E. S. (2021). Predicting phenotypes from genetic, environment, management, and historical data using CNNs. Theoretical and Applied Genetics, 134(12), 3997-4011. https://doi.org/10.1007/s00122-021-03943-7

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

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

Kramer, L. M., Wolc, A., Esfandyari, H., Thekkoot, D. M., Zhang, C., Kemp, R. A., Plastow, G. & Dekkers, J. C. M. (2021). Purebred-crossbred genetic parameters for reproductive traits in swine. Journal of Animal Science, 99(10), Artikel skab270. https://doi.org/10.1093/jas/skab270

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), Artikel 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, Artikel 667300. https://doi.org/10.3389/fgene.2021.667300

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), Artikel 806. https://doi.org/10.3390/ani11030806

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 , 2(1), 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(1), Artikel 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), Artikel skab139. https://doi.org/10.1093/jas/skab139

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), Artikel 102893. https://doi.org/10.1016/j.isci.2021.102893

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), Artikel skab231. 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. Artikel 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, Artikel 636223. https://doi.org/10.3389/fmicb.2021.636223

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