Publications

Peer-reviewed publications at QGG

Olijhoek, D., Hellwing, A. L. F., Grevsen, K., Haveman, L., Chowdhury, M. R., Løvendahl, P., Weisbjerg, M. R., Noel, S. J., Hojberg, O., Wiking, L. & Lund, P. (2019). Effect of dried oregano (Origanum vulgare L.) plant material in feed on methane production, rumen fermentation, nutrient digestibility, and milk fatty acid composition in dairy cows. Journal of Dairy Science, 102(11), 9902–9918. https://doi.org/10.3168/jds.2019-16329

Vargas-Beloo-Pérez, E., Dhakal, R., Kargo, M., Buitenhuis, A. J. & Poulsen, N. A. (2019). Effect of feeding managements on the milk concentrations of short- and medium-chain fatty acids. Abstract from 70th Annual Meeting of the European Federation of Animal Science (EAAP), Ghent, Belgium.

Steenfeldt, S., Sørensen, P. & Nielsen, B. L. (2019). Effects of choice feeding and lower ambient temperature on feed intake, growth, foot health, and panting of fast- and slow-growing broiler strains. Poultry Science, 98(2), 503-513. https://doi.org/10.3382/ps/pey323

Lee, A., Krawczel, P., Ternman, E. M., Schneider, L., Løvendahl, P. & Munksgaard, L. (2019). Effects of mean occupation rate on hourly automatic milking system use and total milk production in Holstein cows. Journal of Dairy Science, 102(Suppl. 1), 250-250. Article 262. https://www.adsa.org/Portals/0/SiteContent/Docs/Meetings/2019ADSA/2019ADSA_Abstract_Book.pdf?v20190715

Szalanski, M., Kristensen, T., Difford, G., Lassen, J., Buitenhuis, A. J., Pszczola, M. & Løvendahl, P. (2019). Enteric methane emission from Jersey cows during the spring transition from indoor feeding to grazing. Journal of Dairy Science, 102(7), 6319-6329. https://doi.org/10.3168/jds.2018-15984

Malinowska, M., Nagy, I., Ruud, A. K., Bjarup Hansen, P., Svane, S. F., Wagemaker, C. A. M., Krusell, L., Eriksen, B., Jahoor, A., Jensen, J. D., Fè, D., Lenk, I., Greve, M., Eriksen, L. B., Thorup-Kristensen, K., Jensen, C. S. & Asp, T. (2019). Epigenetics of drought responses in spring barley and perennial ryegrass. Abstract from The Plant and Animal Genome XXVII Conference (PAG) 2019, San Diego, United States.

Guo, X., Jensen, J. & Janss, L. (2019). Estimating epistasis in cereals for genomic prediction of unobserved crosses in a half diallel experiment. Abstract from The Plant and Animal Genome XXVII Conference (PAG) 2019, San Diego, United States. https://pag.confex.com/pag/xxvii/meetingapp.cgi/Paper/34819

Lee, A., Krawczel, P., Ternman, E. M., Schneider, L., Løvendahl, P. & Munksgaard, L. (2019). Evaluating the effects of mean occupation rate and milk production on two automatic milking systems. In R. C. Newberry & B. O. Braastad (Eds.), Proceedings of the 53rd Congress of the ISAE: Animal Lives Worth Living (pp. 302-302). Wageningen Academic Publishers. https://www.applied-ethology.org/ISAE_Meetings.html

Lee, A. R., Krawczel, P., Ternman, E. M., Schneider, L. G., Løvendahl, P. & Munksgaard, L. (2019). Evaluating the effects of mean stocking density on automatic milking system use and total milk production in Holstein cows. In Proceedings of the 2nd International Precision Dairy Farming Conference (pp. 71-72)

Olijhoek, D., Løvendahl, P., Hellwing, A. L. F., Weisbjerg, M. R. & Lund, P. (2019). Feed sorting of low and high concentrate diets by Holstein and Jersey dairy cows. 199. Abstract from British Society of Animal Science conference 2019, Edinburgh, United Kingdom.

Knorst, V., Yates, S., Byrne, S., Asp, T., Widmer, F., Studer, B. & Kölliker, R. (2019). First assembly of the gene-space of Lolium multiflorum and comparison to other Poaceae genomes. Grassland Science, 65(2), 125-134. https://doi.org/10.1111/grs.12225

Sahana, G. (2019). Genes for disease resistance in cattle – lessons learned from genome-wide association studies. 81-82. Abstract from XIV Agricultural Science Congress, New Delhi, India.

Zaalberg, R. M. (2019). Genetic analysis of Fourier transform infrared milk spectra in Danish dairy cattle. Århus Universitet.

Zaalberg, R. M., Shetty, N., Janss, L. & Buitenhuis, A. J. (2019). Genetic analysis of Fourier transform infrared milk spectra in Danish Holstein and Danish Jersey. Journal of Dairy Science, 102(1), 503-510. https://doi.org/10.3168/jds.2018-14464

Zhang, H., Liu, A., Li, X., Xu, W., Shi, R., Luo, H., Su, G., Dong, G., Guo, G. & Wang, Y. (2019). Genetic analysis of skinfold thickness and its association with body condition score and milk production traits in Chinese Holstein population. Journal of Dairy Science, 102(3), 2347-2352. https://doi.org/10.3168/jds.2018-15180

Guo, X. (2019). Genetic and Environmental Variation in Yield and Root Development in Winter Wheat Using a Semi-Field Phenotyping System. Abstract from Plant and Animal Genome Conference ASIA 2019, Shenzhen, China.

Lidauer, M., Leino, A.-M., Stephansen, R. B., Pösö, J., Fikse, F. & Aamand, G. P. (2019). Genetic Evaluation for Maintenance – Towards Genomic Breeding Values for Saved Feed in Nordic Dairy Cattle. In Interbull Bulletin: Proceedings of the 2019 Interbull Meeting (Vol. 55 (2019), pp. 21-25) https://journal.interbull.org/index.php/ib/article/view/177

Mebratie, W., Madsen, P., Hawken, R., Romé, H., Marois, D., Henshall, J., Bovenhuis, H. & Jensen, J. (2019). Genetic parameters for body weight and different definitions of residual feed intake in broiler chickens. Genetics Selection Evolution, 51(1), Article 53. https://doi.org/10.1186/s12711-019-0494-2

Rohde, P. D., Jensen, I. R., Sarup, P. M., Ørsted, M., Demontis, D., Sørensen, P. & Kristensen, T. N. (2019). Genetic Signatures of Drug Response Variability in Drosophila melanogaster. Genetics (Print), 213(2), 633-650. https://doi.org/10.1534/genetics.119.302381

Aliakbari, A., Ehsani, A., Vaez Torshizi, R., Løvendahl, P., Esfandyari, H., Jensen, J. & Sarup, P. (2019). Genetic variance of metabolomic features and their relationship with body weight and body weight gain in Holstein cattle. Journal of Animal Science, 97(9), 3832-3844. https://doi.org/10.1093/jas/skz228

Zhang, T., Gao, H., Sahana, G., Zan, Y., Fan, H., Liu, J., Shi, L., Liu, J., Du, L., Wang, L. & Zhao, F. (2019). Genome-wide association studies revealed candidate genes for tail fat deposition and body size in the Hulun Buir sheep. Journal of Animal Breeding and Genetics, 136(5), 362-370. https://doi.org/10.1111/jbg.12402

Gan, Q. F., Li, Y. R., Lund, M., Su, G. S. & Liang, X. W. (2019). Genome-wide association study identifies loci linked to serum electrolyte traits in Chinese Holstein cattle. Animal Genetics, 50(6), 744-748. https://doi.org/10.1111/age.12851

Mebratie, W., Reyer, H., Wimmers, K., Bovenhuis, H. & Jensen, J. (2019). Genome wide association study of body weight and feed efficiency traits in a commercial broiler chicken population, a re-visitation. Scientific Reports, 9, Article 922. https://doi.org/10.1038/s41598-018-37216-z

Kristensen, P. S., Jensen, J., Andersen, J. R., Guzmán, C., Jihad, O. & Jahoor, A. (2019). Genomic Prediction and Genome-Wide Association Studies of Flour Yield and Alveograph Quality Traits Using Advanced Winter Wheat Breeding Material. Genes, 10(9), Article 669. https://doi.org/10.3390/genes10090669

Guo, X., Cericola, F., Fè, D., Greve-Pedersen, M., Lenk, I., Jensen, C. S., Jensen, J. & Janss, L. (2019). Genomic Prediction in Tetraploid Ryegrass. Abstract from PAG 2017, San Diego, United States.

Kristensen, P. S. (2019). Genomic prediction of baking quality in winter wheat. Aarhus University.

Cao, L., Liu, H., Mulder, H. A., Henryon, M., Thomasen, J. R., Kargo, M. & Sørensen, A. C. (2019). Genomic selection breeding program benefits more than traditional one in presence of GxE. 528-528. Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgium.

Slagboom, M., Kargo, M., Sørensen, A. C., Thomasen, J. R. & Mulder, H. A. (2019). Genomic selection improves the possibility of applying multiple breeding programs in different environments. Journal of Dairy Science, 102(9), 8197-8209. https://doi.org/10.3168/jds.2018-15939

Robertsen, C. D., Hjortshøj, R. L. & Janss, L. L. (2019). Genomic selection in cereal breeding. Agronomy, 9(2), Article 95. https://doi.org/10.3390/agronomy9020095

Thomasen, J. R. & Lassen, J. (2019). Genomic Selection in the Nordic Countries. 45-47. Abstract from ZAR-Seminar 2019, Austria. https://www.rinderzucht.at/downloads/seminarunterlagen.html

Liu, A., Su, G., Höglund, J., Zhang, Z., Thomasen, J. R., Christiansen, I. A., Wang, Y. & Kargo, M. (2019). Genotype by environment interaction for female fertility traits under conventional and organic production systems in Danish Holsteins. Journal of Dairy Science, 102(9), 8134-8147. https://doi.org/10.3168/jds.2018-15482

Zhang, Z., Kargo, M., Liu, A., Thomasen, J. R., Pan, Y. & Su, G. (2019). Genotype-by-environment interaction of fertility traits in Danish Holstein cattle using a single-step genomic reaction norm model. Heredity, 123(2), 202-214. https://doi.org/10.1038/s41437-019-0192-4

Chu, T. T., Rome, H. J. S., Norberg, E., Marois, D., Henshall, J. & Jensen, J. (2019). GxE interactions of body weight for broilers raised in bio-secure and commercial environments. Abstract from Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgium.

Wu, X., Mesbah-Uddin, M., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2019). Haplotypes responsible for early embryonic lethality detected in Nordic Holsteins. Journal of Dairy Science, 102(12), 11116-11123. https://doi.org/10.3168/jds.2019-16651

Wiking, L., Bjerring, M., Løkke, M. M., Løvendahl, P. & Kristensen, T. (2019). Herd factors influencing free fatty acid concentrations in bulk tank milk. Journal of Dairy Research, 86(2), 226-232. Article 0022029919000190. https://doi.org/10.1017/S0022029919000190

Larsen, F. T., Bed'hom, B., Guldbrandtsen, B. & Dalgaard, T. S. (2019). Identification and tissue-expression profiling of novel chicken c-type lectin-like domain containing proteins as potential targets for carbohydrate-based vaccine strategies. Molecular Immunology, 114(October), 216-225. https://doi.org/10.1016/j.molimm.2019.07.022

Mesbah-Uddin, M. (2019). Identification of causal factors for recessive lethals in dairy cattle with special focus on large chromosomal deletions. Århus Universitet.

Bordbar, F., Jensen, J., Zhu, B., Wang, Z., Xu, L., Chang, T., Xu, L., Du, M., Zhang, L., Gao, H., Xu, L. & Li, J. (2019). Identification of muscle-specific candidate genes in Simmental beef cattle using imputed next generation sequencing. PLOS ONE, 14(10), Article e0223671. https://doi.org/10.1371/journal.pone.0223671

Buitenhuis, B., Lassen, J., Noel, S. J., Plichta, D. R., Sørensen, P., Difford, G. F. & Poulsen, N. A. (2019). Impact of the rumen microbiome on milk fatty acid composition of Holstein cattle. Genetics Selection Evolution, 51(1), Article 23. https://doi.org/10.1186/s12711-019-0464-8

de los Campos, G., Sorensen, D. A. & Toro, M. A. (2019). Imperfect linkage disequilibrium generates phantom epistasis (& perils of big data). G3: Genes, Genomes, Genetics, 9(5), 1429-1436. https://doi.org/10.1534/g3.119.400101

Wang, X., Lund, M. S., Ma, P., Janss, L., Kadarmideen, H. N. & Su, G. (2019). Improving genomic predictions by correction of genotypes from genotyping by sequencing in livestock populations. Journal of Animal Science and Biotechnology, 10, Article 8. https://doi.org/10.1186/s40104-019-0315-z

Chen, M., Su, G., Fu, J., Wang, A., Liu, J. F., Lund, M. S. & Guldbrandtsen, B. (2019). Introgression of Chinese haplotypes contributed to the improvement of Danish Duroc pigs. Evolutionary Applications, 12(2), 292-300. https://doi.org/10.1111/eva.12716

Mesbah-Uddin, M., Guldbrandtsen, B., Lund, M. S., Boichard, D. & Sahana, G. (2019). Joint imputation of whole-genome sequence variants and large chromosomal deletions in cattle. Journal of Dairy Science, 102(12), 11193-11206. https://doi.org/10.3168/jds.2019-16946

Kargo, M., Hein, L., Poulsen, N. A. & Buitenhuis, A. J. (2019). Keeping up with a healthy milk fatty acid profile requires selection. 604-604. Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgium.

Due, H., Schönherz, A. A., Ryø, L., Primo, M. N., Jespersen, D. S., Thomsen, E. A., Roug, A. S., Xiao, M., Tan, X., Pang, Y., Young, K. H., Bøgsted, M., Mikkelsen, J. G. & Dybkær, K. (2019). MicroRNA-155 controls vincristine sensitivity and predicts superior clinical outcome in diffuse large B-cell lymphoma. Blood Advances, 3(7), 1185-1196. https://doi.org/10.1182/bloodadvances.2018029660

Heidaritabar, M., Bijma, P., Janss, L., Bortoluzzi, C., Nielsen, H. M., Madsen, P., Ask, B. & Christensen, O. F. (2019). Models with indirect genetic effects depending on group sizes: a simulation study assessing the precision of the estimates of the dilution parameter. Genetics Selection Evolution, 51(1), 24. Article 24. https://doi.org/10.1186/s12711-019-0466-6

Gebreyesus, G., Buitenhuis, A. J., Poulsen, N. A., Visker, M. H. P. W., Zhang, Q., van Valenberg, H. J. F., Sun, D. & Bovenhuis, H. (2019). Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition. BMC Genomics, 20, Article 178. https://doi.org/10.1186/s12864-019-5573-9

Kristensen, P. S., Jahoor, A., Andersen, J. R., Jihad, O., Janss, L. & Jensen, J. (2019). Multi-Trait and Trait-Assisted Genomic Prediction of Winter Wheat Quality Traits Using Advanced Lines from Four Breeding Cycles. Hapres CBGG; Crop, Breeding, Genetics, Genomics, Article :e190010. https://doi.org/10.20900/cbgg20190010

Manzanilla Pech, C. I. V., Løvendahl, P. & Lassen, J. (2019). Multi-trait genomic prediction of methane emission in Danish Holstein. Abstract from 70th Annual Meeting of the European Federation of Animal Science (EAAP), Ghent, Belgium.

Guldbrandtsen, B., (2019). Nogle bemærkninger vedr. benefit sharing i husdyravl, No. 2019-760-001264, 7 p., May 20, 2019.

Chu, T. T., Bastiaansen, J. W. M., Berg, P. & Komen, H. (2019). Optimized grouping to increase accuracy of prediction of breeding values based on group records in genomic selection breeding programs. Genetics Selection Evolution, 51(1), Article 64. https://doi.org/10.1186/s12711-019-0509-z

Veeckman, E., Van Glabeke, S., Haegeman, A., Muylle, H., Van Parijs, F. R. D., Byrne, S. L., Asp, T., Studer, B., Rohde, A., Roldán-Ruiz, I., Vandepoele, K. & Ruttink, T. (2019). Overcoming challenges in variant calling: Exploring sequence diversity in candidate genes for plant development in perennial ryegrass (Lolium perenne). DNA Research, 26(1), 1-12. https://doi.org/10.1093/dnares/dsy033

Henryon, M., Liu, H., Berg, P., Su, G., Nielsen, H. M., Gebregiwergis, G. T. & Sørensen, A. C. (2019). Pedigree relationships to control inbreeding in optimum-contribution selection realise more genetic gain than genomic relationships. Genetics Selection Evolution, 51(1), Article 39. https://doi.org/10.1186/s12711-019-0475-5

Vestergaard, M., Jørgensen, K. F., Çakmakçı, C., Kargo, M., Therkildsen, M., Munk, A. & Kristensen, T. (2019). Performance and carcass quality of crossbred beef x Holstein bull and heifer calves in comparison with purebred Holstein bull calves slaughtered at 17 months of age in an organic production system. Livestock Science, 223, 184-192. https://doi.org/10.1016/j.livsci.2019.03.018

Knorst, V., Byrne, S., Yates, S., Asp, T., Widmer, F., Studer, B. & Kölliker, R. (2019). Pooled DNA sequencing to identify SNPs associated with a major QTL for bacterial wilt resistance in Italian ryegrass (Lolium multiflorum Lam.). Theoretical and Applied Genetics, 132(4), 947-958. https://doi.org/10.1007/s00122-018-3250-z

Alexandre, P., Porto-Neto, L., Karaman, E., Lehnert, S. & Reverter, A. (2019). Pooled genotyping strategies for the rapid construction of genomic reference populations. Journal of Animal Science, 97(12), 4761– 4769. https://doi.org/10.1093/jas/skz344

Slagboom, M., Hjortø, L., Sørensen, A. C., Mulder, H. A., Thomasen, J. R. & Kargo, M. (2019). Possibilities for a specific breeding program for organic dairy production. 215-215. Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgium.

Nielsen, B., Ask, B., Gao, H. & Su, G. (2019). Prediction of individual breeding values from group recordings. Abstract from Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgium.

Cai, Z., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2019). Prioritizing candidate genes for fertility in dairy cows using gene-based analysis, functional annotation and differential gene expression. BMC Genomics, 20, Article 255. https://doi.org/10.1186/s12864-019-5638-9

Xiang, R., Van Den Berg, I., MacLeod, I. M., Hayes, B. J., Prowse-Wilkins, C. P., Wang, M., Bolormaa, S., Liu, Z., Rochfort, S. J., Reich, C. M., Mason, B. A., Vander Jagt, C. J., Daetwyler, H. D., Lund, M. S., Chamberlain, A. J. & Goddard, M. E. (2019). Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits. Proceedings of the National Academy of Sciences (PNAS), 116(39), 19398-19408. https://doi.org/10.1073/pnas.1904159116

Slagboom, M. (2019). Quantifying the value of specific breeding lines for organic dairy cattle. Aarhus University.

Negussie, E., Mehtiö, T., Mäntysaari, P., Løvendahl, P., Mäntysaari, E. A. & Lidauer, M. H. (2019). Reliability of breeding values for feed intake and feed efficiency traits in dairy cattle: When dry matter intake recordings are sparse under different scenarios. Journal of Dairy Science, 102(8), 7248-7262. https://doi.org/10.3168/jds.2018-16020

Gebreyesus, G., Bovenhuis, H., Lund, M. S., Poulsen, N. A., Sun, D. & Buitenhuis, B. (2019). Reliability of genomic prediction for milk fatty acid composition by using a multi-population reference and incorporating GWAS results. Genetics Selection Evolution, 51(1), Article 16. https://doi.org/10.1186/s12711-019-0460-z

Noel, S. J., Olijhoek, D., McLean, F., Løvendahl, P., Lund, P. & Hojberg, O. (2019). Rumen and Fecal Microbial Community Structure of Holstein and Jersey Dairy Cows as Affected by Breed, Diet, and Residual Feed Intake. Animals, 9(8), Article 498. https://doi.org/10.3390/ani9080498

Thirstrup, J. P., Villumsen, T. M., Malmkvist, J. & Lund, M. S. (2019). Selection for temperament has no negative consequences on important production traits in farmed mink1. Journal of Animal Science, 97(5), 1987-1995. https://doi.org/10.1093/jas/skz089

Nielsen, L. V., Nielsen, B., Christensen, O. F., Turner, S. P., Nielsen, H. M. & Ask, B. (2019). Selection of pigs for social genetic effects improves growth in crossbreeds. Paper presented at Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgium.

Madsen, M. D., Shirali, M., Jensen, J., Hansen, B. K., Møller, S. H. & Villumsen, T. M. (2019). Selektion for fodereffektivitet uden negative konsekvenser for kropsvægt og kuldstørrelse. In Temadag om aktuel minkforskning: bilag (pp. 28-31). Århus Universitet. https://anis.au.dk/fileadmin/ingen_mappe_valgt/Minktemadag_rapport_final_september2019.pdf

Kargo, M., Clasen, J., Ettema, J. F., Davis, R. B. & Østergaard, S. (2019). SimHerd Crossbred for estimating the economic effects of crossbreeding. 285-285. Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgium.

Ørsted, M., Hoffmann, A. A., Rohde, P. D., Sørensen, P. & Kristensen, T. N. (2019). Strong impact of thermal environment on the quantitative genetic basis of a key stress tolerance trait. Heredity, 122(3), 315-325. https://doi.org/10.1038/s41437-018-0117-7

Poulsen, N. A., Buitenhuis, A. J., Johansen, M. & Larsen, L. B. (2019). Sustainable dairy production and its exploitation into healthy dairy products. Abstract and oral presentation. Abstract from 16th Symposium on Milk Genomics and Human Health, Aarhus, Denmark.

Poulsen, N. A., Buitenhuis, A. J., Sehested, J., Kargo, M., Wiking, L. & Larsen, L. B. (2019). Sustainable milk production and the impact on milk quality and functionality. 16. Abstract from Dairy Research Conference 2019, Billund, Denmark.

Mebratie, W. (2019). The genetics of body weight and feed efficiency in broiler chickens. Aarhus Unversitet.

Dettmann, F., Warner, D., Buitenhuis, A. J., Kargo, M., Hostrup Kjeldsen, A. M., Nielsen, N. H., Lefebvre, D. M. & Santschi, D. E. (2019). The use of fatty acid profiles from milk recording samples to predict body weight change of dairy cows in early lactation in commercial farms. In J. Kucera, P. Bucek, D. Lipovsky, X. Bourrigan & M. Burke (Eds.), New traits and adding value to the recording and ID services in the animal production: Proceedings of the ICAR Conference held in Prague, CZ, 17-21 June 2019 (pp. 143-154). ICAR. https://www.icar.org/wp-content/uploads/2019/12/ICAR-Technical-Series-24-Prague-2019-Proceedings.pdf

Ma, X., Li, P., Zhang, Q., He, L., Su, G., Huang, Y., Lu, Z., Hu, W., Ding, H. & Huang, R. (2019). Transcriptome analysis of the endometrium from Chinese Erhualian sows that differ in calcium ion concentration and litter size. Animal Genetics, 50(4), 326-333. https://doi.org/10.1111/age.12788

Ma, P., Lund, M. S., Aamand, G. P. & Su, G. (2019). Use of a Bayesian model including QTL markers increases prediction reliability when test animals are distant from the reference population. Journal of Dairy Science, 102(8), 7237-7247. https://doi.org/10.3168/jds.2018-15815

Chu, T. T., Bastiaansen, J. WM., Berg, P., Rome, H. J. S., Marois, D., Henshall, J. & Jensen, J. (2019). Use of genomic information to exploit genotype-by-environment interactions for body weight of broiler chicken in bio-secure and production environments. Genetics Selection Evolution, 51, Article 50. https://doi.org/10.1186/s12711-019-0493-3

Chu, T. T., Bastiaansen, J. WM., Berg, P. & Komen, H. (2019). Use of genomic information to improve accuracy of prediction from group records. Abstract from Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgium.

Gao, H., Nielsen, B., Su, G., Madsen, P., Jensen, J., Christensen, O. F., Ostersen, T. & Shirali, M. (2019). Use of repeated group measurements with drop out animals for genetic analysis. Abstract from Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgium.

Gao, H., Nielsen, B., Su, G., Madsen, P., Jensen, J., Christensen, O. F., Ostersen, T. & Shirali, M. (2019). Use of Repeated Group Measurements with Drop Out Animals for Variance Component Estimation and Genetic Evaluation: A Simulation Study. G3: Genes, Genomes, Genetics, 9(9), 2935-2940. https://doi.org/10.1534/g3.119.400484

Naeemipour Younesi, H., Shariati, M. M., Zerehdaran, S., Jabbari Nooghabi, M. & Løvendahl, P. (2019). Using quantile regression for fitting lactation curve in dairy cows. Journal of Dairy Research, 86(1), 19-24. https://doi.org/10.1017/S0022029919000013

Cai, Z., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2019). Weighting sequence variants based on their annotation increases the power of genome-wide association studies in dairy cattle. Genetics Selection Evolution, 51(1), 20. Article 20. https://doi.org/10.1186/s12711-019-0463-9

Rome, H. J. S., Chu, T. T., Hawken, R., Henshall, J. & Jensen, J. (2019). WGBLUP model improves accuracy of breeding values prediction in a commercial line of broilers. Abstract from Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgium.

Holmquist, D. D., Buitenhuis, A. J., Nielsen, N. H., Poulsen, N. A., Munk, A. & Kargo, M. (2019). Where will new techologies take milk recording? Large scale screening of the Danish dairy cattle population for their milk fatty acid profile. Abstract from ICAR 2019, Prag, Czech Republic. https://www.icar.org/Documents/Prague-2019/Abstracts/S06(T)-OP-1.pdf

Mukherjee, S., Cai, Z., Mukherjee, A., Longkumer, I., Mech, M., Vupru, K., Khate, K., Rajkhowa, C., Mitra, A., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2019). Whole genome sequence and de novo assembly revealed genomic architecture of Indian Mithun (Bos frontalis). BMC Genomics, 20(1), Article 617. https://doi.org/10.1186/s12864-019-5980-y

Hosseini-Vardanjani, S. M., Mahdi Shariati, M., Janss, L., Christensen, O. F., Anche, M. T. & Lund, M. S. (2018). Accounting for breed origin of alleles increase accuracy of genomic prediction in admixed populations. Poster session presented at World Congress on Genetics Applied to Livestock Production, Auckland, New Zealand.

Madsen, M. D., Madsen, P., Nielsen, B. J., Kristensen, T. N., Jensen, J. & Shirali, M. (2018). Adjusting for Macro-Environmental Sensitivity in Growth rate of Danish Landrace and Duroc Pigs. Abstract from 69th Annual Meeting of the European Federation of Animal Science EAAP 2018, Dubrovnik, Croatia.

Marete, A. G., Guldbrandtsen, B., Lund, M. S., Fritz, S., Sahana, G. & Boichard, D. (2018). A Meta-Analysis Including Pre-selected Sequence Variants Associated With Seven Traits in Three French Dairy Cattle Populations. Frontiers in Genetics, 9, Article 522. https://doi.org/10.3389/fgene.2018.00522

Villumsen, T. M. & Lund, M. S. (2018). Anvendelse af auktionsdata i minkavlen. In S. H. Møller & J. Malmkvist (Eds.), Temadag om aktuel minkforskning: DCA Rapport nr. 129, September 2018 (pp. 30-36). http://web.agrsci.dk/djfpublikation/index.asp?action=show&id=1272

Wang, X., Gao, H., G. Gebremedhin, K., Schmidt Bjerg, B., Van Os, J., Tucker, C. B. & Zhang, G. (2018). A predictive model of equivalent temperature index for dairy cattle (ETIC). Journal of Thermal Biology, 76, 165-170. https://doi.org/10.1016/j.jtherbio.2018.07.013

Jardim, J. G., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2018). Association analysis for udder index and milking speed with imputed whole-genome sequence variants in Nordic Holstein cattle. Journal of Dairy Science, 101(3), 2199-2212. https://doi.org/10.3168/jds.2017-12982

Marete, A. G., Lund, M. S., Boichard, D. A. & Ramayo-Caldas, Y. (2018). A system-based analysis of the genetic determinism of udder conformation and health phenotypes across three French dairy cattle breeds. PLOS ONE, 13(7), Article e0199931. https://doi.org/10.1371/journal.pone.0199931

Karaman, E., Lund, M. S., Anche, M. T., Janss, L. & Su, G. (2018). A two-step approach to account for heterogeneous (co)variances across the genome using GBLUP. Poster session presented at ICAR Conference and World Congress on Genetics Applied to Livestock Production 2018, Auckland, New Zealand.

Esfandyari, H., Berg, P. & Sørensen, A. C. (2018). Balanced selection on purebred and crossbred performance increases gain in crossbreds. Genetics Selection Evolution, 50(1), Article 8. https://doi.org/10.1186/s12711-018-0379-9

Shirali, M., Varley, P. F. & Jensen, J. (2018). Bayesian estimation of direct and correlated responses to selection on linear or ratio expressions of feed efficiency in pigs. Genetics Selection Evolution, 50(1), Article 33. https://doi.org/10.1186/s12711-018-0403-0

Chu, T. T., Alemu, S. W., Norberg, E., Sørensen, A. C., Henshall, J., Hawken, R. & Jensen, J. (2018). Benefits of testing in both bio-secure and production environments in genomic selection breeding programs for commercial broiler chicken. Genetics Selection Evolution, 50(1), Article 52. https://doi.org/10.1186/s12711-018-0430-x

Slagboom, M., Wallenbeck, A., Rydhmer, L., Thomasen, J. R. & Kargo, M. (2018). Breeding Goals for Organic Dairy Farming in Denmark Based on the Principles of Organic Agriculture. Paper presented at ICAR Conference and World Congress on Genetics Applied to Livestock Production 2018, Auckland, New Zealand.

Gajjar, S. G., Guldbrandtsen, B., Su, G., Nayee, N. K., Sahana, G., Trivedi, K. R. & Lund, M. S. (2018). Breed-of-origin specific genomic relationship matrix improves genomic prediction accuracy in crossbred Holstein Friesian cattle in India. In Proceedings of the World Congress on Genetics Applied to Livestock Production 2018: Volume theory to application (Vol. 3). Article 11.754 http://www.wcgalp.org/proceedings/2018/breed-origin-specific-genomic-relationship-matrix-improves-genomic-prediction

Difford, G., Gebreyesus, G., Løvendahl, P., Buitenhuis, A. J., Lassen, J., Guldbrandtsen, B. & Sahana, G. (2018). Can rumen microbes improve prediction of subclinical ketosis in dairy cows? In S. C. (Ed.), Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (Vol. 24). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-871-1

Guldbrandtsen, B., Nielsen, V. H. & Schönherz, A. (2018). Case Studies using Molecular Data in Breed Conservation. Abstract from Workshop on Genomic Selection. Espoo 2018, Helsinki, Finland.

Zhu, Z., Kristensen, L., Difford, G. F., Poulsen, M., Noel, S. J., Abu Al-Soud, W., Sørensen, S. J., Lassen, J., Løvendahl, P. & Højberg, O. (2018). Changes in rumen bacterial and archaeal communities over the transition period in primiparous Holstein dairy cows. Journal of Dairy Science, 101(11), 9847-9862. https://doi.org/10.3168/jds.2017-14366

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Jette Odgaard Villemoes