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, Article 133.
https://doi.org/10.1186/s12864-022-08373-3
Bouquet, A. E. R., Slagboom, M., Thomasen, J. R., Friggens, N.
, Kargo, M. & Puillet, L. (2022).
Coupling genetic and mechanistic models to benchmark selection strategies for feed efficiency in dairy cows: sensitivity analysis validating this novel approach.
Animal - Open Space,
1(1), Article 100017.
https://doi.org/10.1016/j.anopes.2022.100017
Bornhofen, E., Fè, D., Lenk, I., Greve, M., Didion, T., Jensen, C. S.
, Asp, T. & Janss, L. (2022).
Leveraging spatiotemporal genomic breeding value estimates of dry matter yield and herbage quality in ryegrass via random regression models.
The Plant Genome,
15(4), Article e20255.
https://doi.org/10.1002/tpg2.20255
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), Article 1103.
https://doi.org/10.3390/ani12091103
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), Article 60.
https://doi.org/10.1186/s12711-022-00749-z
Bengtsson, C.
, Thomasen, J. R., Kargo, M., Bouquet, A. & Slagboom, M. (2022).
Emphasis on resilience in dairy cattle breeding: Possibilities and consequences.
Journal of Dairy Science,
105(9), 7588-7599.
https://doi.org/10.3168/jds.2021-21049
Alemu, S. W., Bijma, P., Calus, M. P. L.
, Liu, H., Fernando, R. L. & Dekkers, J. C. M. (2022).
Comparison of linkage disequilibrium estimated from genotypes versus haplotypes for crossbred populations.
Genetics Selection Evolution,
54(1), Article 12.
https://doi.org/10.1186/s12711-022-00703-z
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
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
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.
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.
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
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
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
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
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
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), Article 753.
https://doi.org/10.3390/metabo11110753
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
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
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
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
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
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
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, Article 104696.
https://doi.org/10.1016/j.livsci.2021.104696
Song, Y., Wilson, A. J., Zhang, X. C., Thoms, D., Sohrabi, R., Song, S.
, Geissmann, Q., Liu, Y., Walgren, L., He, S. Y. & Haney, C. H. (2021).
FERONIA restricts Pseudomonas in the rhizosphere microbiome via regulation of reactive oxygen species.
Nature Plants,
7(5), 644-654.
https://doi.org/10.1038/s41477-021-00914-0
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
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
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
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
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
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), Article 3492.
https://doi.org/10.3390/ani11123492
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
Rabaglino, M. B., O’Doherty, A., Secher, J. B. M., Lonergan, P., Hyttel, P., Fair, T.
& Kadarmideen, H. N. (2021).
Application of multi-omics data integration and machine learning approaches to identify epigenetic and transcriptomic differences between in vitro and in vivo produced bovine embryos.
PLOS ONE,
16(5 May), Article e0252096.
https://doi.org/10.1371/journal.pone.0252096
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), Article 5848.
https://doi.org/10.1038/s41467-021-26153-7
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
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
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
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), Article 100411.
https://doi.org/10.1016/j.animal.2021.100411
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
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
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
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
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), Article skab270.
https://doi.org/10.1093/jas/skab270
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
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
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
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
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
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
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
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
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
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
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
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), Article 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
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
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), Article 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), Article 15.
https://doi.org/10.1186/s12711-021-00609-2