Publications

Peer-reviewed publications at QGG

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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.

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

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

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.

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

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

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.

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

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.

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

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

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.

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.

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. & 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.

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

Salleh, S. M., Mazzoni, G., Løvendahl, P. & Kadarmideen, H. N. (2018). Gene co-expression networks from RNA sequencing of dairy cattle identifies genes and pathways affecting feed efficiency. BMC Bioinformatics, 19(1), Article 513. https://doi.org/10.1186/s12859-018-2553-z

Cai, Z., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2018). Retraction Note: Dissecting closely linked association signals in combination with the mammalian phenotype database can identify candidate genes in dairy cattle ( Reference: BMC Genetics (2018) 19:30 DOI: 10.1186/s12863-018-0620-0). BMC Genetics, 19(1), Article 111. https://doi.org/10.1186/s12863-018-0698-4

Vestergaard, H. T., Thomsen, M. K., Nielsen, L. & Panum, I. (2018). Diagnostik af kongenit cytomegalovirusinfektion i Danmark. Ugeskrift for Læger, 180(50).

Madsen, M. D., Madsen, P., Nielsen, B., Kristensen, T. N., Jensen, J. & Shirali, M. (2018). Macro-environmental sensitivity for growth rate in Danish Duroc pigs is under genetic control. Journal of Animal Science, 96(12), 4967-4977. https://doi.org/10.1093/jas/sky376

Ma, X., Li, P. H., Zhu, M. X., He, L. C., Sui, S. P., Gao, S., Su, G. S., Ding, N. S., Huang, Y., Lu, Z. Q., Huang, X. G. & Huang, R. H. (2018). Genome-wide association analysis reveals genomic regions on Chromosome 13 affecting litter size and candidate genes for uterine horn length in Erhualian pigs. Animal, 12(12), 2453-2461. https://doi.org/10.1017/S1751731118000332

Fang, L., Sørensen, P., Sahana, G., Panitz, F., Su, G., Zhang, S., Yu, Y., Li, B., Ma, L., Liu, G., Lund, M. S. & Thomsen, B. (2018). MicroRNA-guided prioritization of genome-wide association signals reveals the importance of microRNA-target gene networks for complex traits in cattle. Scientific Reports, 8(1), Article 9345. https://doi.org/10.1038/s41598-018-27729-y

Løvendahl, P., Difford, G. F., Li, B., Chagunda, M. G. G., Huhtanen, P., Lidauer, M. H., Lassen, J. & Lund, P. (2018). Review: Selecting for improved feed efficiency and reduced methane emissions in dairy cattle. Animal, 12(S2), S336-S349. https://doi.org/10.1017/S1751731118002276

Zhang, Z., Zhang, Q., Xiao, Q., Sun, H., Gao, H., Yang, Y., Chen, J., Li, Z., Xue, M., Ma, P., Yang, H., Xu, N., Wang, Q. & Pan, Y. (2018). Distribution of runs of homozygosity in Chinese and Western pig breeds evaluated by reduced-representation sequencing data. Animal Genetics, 49(6), 579-591. https://doi.org/10.1111/age.12730

Stephansen, R. S., Fogh, A. & Norberg, E. (2018). Genetic parameters for handling and milking temperament in Danish first-parity Holstein cows. Journal of Dairy Science, 101(12), 11033-11039. https://doi.org/10.3168/jds.2018-14804

Zetouni, L., Difford, G. F., Lassen, J., Byskov, M. V., Norberg, E. & Løvendahl, P. (2018). Is rumination time an indicator of methane production in dairy cows? Journal of Dairy Science, 101(12), 11074-11085. https://doi.org/10.3168/jds.2017-14280

Gao, H., Madsen, P., Pösö, J., Aamand, G. P., Lidauer, M. & Jensen, J. (2018). Short communication: Multivariate outlier detection for routine Nordic dairy cattle genetic evaluation in the Nordic Holstein and Red population. Journal of Dairy Science, 101(12), 11159-11164. https://doi.org/10.3168/jds.2018-15123

Slagboom, M., Wallenbeck, A., Hjortø, L., Sørensen, A. C., Rydhmer, L., Thomasen, J. R. & Kargo, M. (2018). Simulating consequences of choosing a breeding goal for organic dairy production. Journal of Dairy Science, 101(12), 11086-11096. https://doi.org/10.3168/jds.2017-14316

Ettema, J. F., Kudahl, A. B., Børsting, C. F. & Østergaard, S. (2018). Tørkeråd: Køb grovfoder i stedet for at slagte dyr. KvægNYT, 23, 2-2. https://www.landbrugsinfo.dk/kvaeg/kvaegnyt/sider/startside.aspx

Zhang, Q., Sahana, G., Su, G., Guldbrandtsen, B., Lund, M. S. & Calus, M. P. L. (2018). Impact of rare and low-frequency sequence variants on reliability of genomic prediction in dairy cattle. Genetics Selection Evolution, 50(1), Article 62. https://doi.org/10.1186/s12711-018-0432-8

Colli, L., Milanesi, M., Talenti, A., Bertolini, F., Chen, M., Crisà, A., Daly, K. G., Del Corvo, M., Guldbrandtsen, B., Lenstra, J. A., Rosen, B. D., Vajana, E., Catillo, G., Joost, S., Nicolazzi, E. L., Rochat, E., Rothschild, M. F., Servin, B., Sonstegard, T. S. ... The ADAPTMAP consortium (Vivi Hunnicke Nielsen; member) (2018). Genome-wide SNP profiling of worldwide goat populations reveals strong partitioning of diversity and highlights post-domestication migration routes. Genetics Selection Evolution, 50(1), Article 58. https://doi.org/10.1186/s12711-018-0422-x

Bertolini, F., Servin, B., Talenti, A., Rochat, E., Kim, E. S., Oget, C., Palhière, I., Crisà, A., Catillo, G., Steri, R., Amills, M., Colli, L., Marras, G., Milanesi, M., Nicolazzi, E., Rosen, B. D., Van Tassell, C. P., Guldbrandtsen, B., Sonstegard, T. S. ... The ADAPTMAP consortium (Vivi Hunnicke Nielsen; member) (2018). Signatures of selection and environmental adaptation across the goat genome post-domestication. Genetics Selection Evolution, 50, 57. https://doi.org/10.1186/s12711-018-0421-y

Cai, Z., Villumsen, T. M., Asp, T., Guldbrandtsen, B., Sahana, G. & Lund, M. S. (2018). SNP markers associated with body size and pelt length in American mink (Neovison vison). BMC Genetics, 19(1), Article 103. https://doi.org/10.1186/s12863-018-0688-6

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

Karaman, E., Lund, M. S., Anche, M. T., Janss, L. & Su, G. (2018). Genomic Prediction Using Multi-trait Weighted GBLUP Accounting for Heterogeneous Variances and Covariances Across the Genome. G3: Genes, Genomes, Genetics (Bethesda), 8(11), 3549-3558. https://doi.org/10.1534/g3.118.200673

Olijhoek, D. W., Løvendahl, P., Lassen, J., Hellwing, A. L. F., Höglund, J. K., Weisbjerg, M. R., Noel, S. J., McLean, F., Højberg, O. & Lund, P. (2018). Methane production, rumen fermentation, and diet digestibility of Holstein and Jersey dairy cows being divergent in residual feed intake and fed at 2 forage-to-concentrate ratios. Journal of Dairy Science, 101(11), 9926-9940. https://doi.org/10.3168/jds.2017-14278

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

Li, B., Fikse, F., Løvendahl, P., Lassen, J., Lidauer, M., Mäntysaari, P. & Berglund, B. (2018). Genetic heterogeneity of feed intake, energy-corrected milk, and body weight across lactation in primiparous Holstein, Nordic Red, and Jersey cows. Journal of Dairy Science, 101(11), 10011-10021. https://doi.org/10.3168/jds.2018-14611

Poulsen, N. A., C. Robinson, R., Buitenhuis, A. J., Sundekilde, U. K., Lemay, D. G., Barile, D., Larsen, L. B. & Holm, L.-E. (2018). GWAS and expression of candidate genes for oligosaccharide synthesis in Danish dairy breeds. Abstract from 15th International Symposium on Milk Genomics and Human Health, Sacramento, California, United States.

Poulsen, N. A., Buitenhuis, A. J., Le, T. T. T., Gregersen, V. R., Lindahl, I. E. I., Christensen, B. S., Sørensen, E. S. & Larsen, L. B. (2018). Milk Genomics: Variation in Danish Dairy milk and its possible exploitation in the dairy chain. Abstract from 15th International Symposium on Milk Genomics and Human Health, Sacramento, California, United States.

Mebratie, W., Madsen, P., Hawken, R. & Jensen, J. (2018). Multi-trait estimation of genetic parameters for body weight in a commercial broiler chicken population. Livestock Science, 217, 15-18. https://doi.org/10.1016/j.livsci.2018.09.007

Gao, H., Koivula, M., Jensen, J., Strandén, I., Madsen, P., Pitkänen, T., Aamand, G. P. & Mäntysaari, E. A. (2018). Short communication: Genomic prediction using different single-step methods in the Finnish red dairy cattle population. Journal of Dairy Science, 101(11), 10082-10088. https://doi.org/10.3168/jds.2018-14913

Difford, G. F., Plichta, D. R., Løvendahl, P., Lassen, J., Noel, S. J., Højberg, O., Wright, A.-D. G., Zhu, Z., Kristensen, L., Nielsen, H. B., Guldbrandtsen, B. & Sahana, G. (2018). Host genetics and the rumen microbiome jointly associate with methane emissions in dairy cows. PLoS Genetics, 14(10), e1007580. Article e1007580. https://doi.org/10.1371/journal.pgen.1007580

Sorg, D., Difford, G. F., Mühlbach, S., Kuhla, B., Swalve, H. H., Lassen, J., Strabel, T. & Pszczola, M. (2018). Comparison of a laser methane detector with the GreenFeed and two breath analysers for on-farm measurements of methane emissions from dairy cows. Computers and Electronics in Agriculture, 153, 285-294. https://doi.org/10.1016/j.compag.2018.08.024

Vagndorf, N. J., Kristensen, P. S., Andersen, J. R., Jahoor, A. & Orabi, J. (2018). Marker-assisted plant breeding in wheat. In Y. O. Çiftçi (Ed.), Next Generation Plant Breeding (pp. 107). InTechOpen. https://doi.org/10.5772/intechopen.74724

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

Cai, Z., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2018). Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle. BMC Genomics, 19(1), Article 656. https://doi.org/10.1186/s12864-018-5050-x

Begli, H. E., Torshizi, R. V., Masoudi, A. A., Ehsani, A. & Jensen, J. (2018). Genomic dissection and prediction of feed intake and residual feed intake traits using a longitudinal model in F2 chickens. Animal, 12(9), 1792-1798. https://doi.org/10.1017/S1751731117003354

Larsen, M., Buitenhuis, A. J., Hedemann, M. S. & Sehested, J. (2018). Prediction of individual dairy cow performance using LC-MS metabolome spectra. In R. Baumont, M. Silberberg & I. Cassar-Malek (Eds.), Proceedings of the 10th International Symposium on the Nutrition of Herbivores (Vol. 9). Article 623 Cambridge University Press.

Olesen, J. E., Petersen, S. O., Lund, P., Jørgensen, U., Kristensen, T., Elsgaard, L., Sørensen, P. & Lassen, J. (2018). Virkemidler til reduktion af klimagasser i landbruget. DCA - Nationalt Center for Fødevarer og Jordbrug. DCA rapport No. 130 http://web.agrsci.dk/djfpublikation/index.asp?action=show&id=1273

Nayee, N., Sahana, G., Gajjar, S., Sudhakar, A., Trivedi, K., Lund, M. S. & Guldbrandtsen, B. (2018). Suitability of existing commercial single nucleotide polymorphism chips for genomic studies in Bos indicus cattle breeds and their Bos taurus crosses. Journal of Animal Breeding and Genetics (Online), 135(6), 432-441. https://doi.org/10.1111/jbg.12356

Ma, P., Huang, J., Gong, W., Li, X., Gao, H., Zhang, Q., Ding, X. & Wang, C. (2018). The impact of genomic relatedness between populations on the genomic estimated breeding values. Journal of Animal Science and Biotechnology, 9(1), Article 64. https://doi.org/10.1186/s40104-018-0279-4

Guo, X., Cericola, F., Fè, D., Pedersen, M. G., Lenk, I., Jensen, C. S., Jensen, J. & Janss, L. L. (2018). Genomic prediction in tetraploid ryegrass using allele frequencies based on genotyping by sequencing. Frontiers in Plant Science, 9, Article 1165. https://doi.org/10.3389/fpls.2018.01165

Su, G., Madsen, P., Nielsen, B., Ostersen, T., Shirali, M., Jensen, J. & Christensen, O. F. (2018). Estimation of variance components and prediction of breeding values based on group records from varying group sizes. Genetics Selection Evolution, 50(1), Article 42. https://doi.org/10.1186/s12711-018-0413-y

Sverrisdóttir, E., Sundmark, E. H. R., Johnsen, H. Ø., Kirk, H. G., Asp, T., Janss, L., Bryan, G. & Nielsen, K. L. (2018). The value of expanding the training population to improve genomic selection models in tetraploid potato. Frontiers in Plant Science, 9, Article 1118. https://doi.org/10.3389/fpls.2018.01118

Cuyabano, B. C. D., Sørensen, A. C. & Sørensen, P. (2018). Understanding the potential bias of variance components estimators when using genomic models. Genetics Selection Evolution, 50(1), Article 41. https://doi.org/10.1186/s12711-018-0411-0

Zhang, Q., Calus, M., Bosse, M., Sahana, G., Lund, M. S. & Guldbrandtsen, B. (2018). Human-Mediated Introgression of Haplotypes in a Modern Dairy Cattle Breed. Genetics, 209(4), 1305-1317. https://doi.org/10.1534/genetics.118.301143

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

Salleh, S. M., Mazzoni, G., Nielsen, M. O., Løvendahl, P. & Kadarmideen, H. (2018). Identification of Expression QTLs Targeting Candidate Genes for Residual Feed Intake in Dairy Cattle Using Systems Genomics. Journal of Genetics and Genome Research, 5(1), Article 035. https://www.clinmedjournals.org/articles/jggr/journal-of-genetics-and-genome-research-jggr-5-035.pdf?jid=jggr

Cao, L. (2018). Effect of G×E on Breeding Cooperation Using Genomic Selection. Abstract from 12th World Conference on Animal Production (WCAP) & 2018 ASAS-CSAS Annual Meeting, Vancouver, British Columbia, Canada.

Mukherjee, A., Mukherjee, S., Dhakal, R., Mech, M., Longkumer, I., Haque, N., Vupru, K., Khate, K., Jamir, I. Y., Pongen, P., Rajkhowa, C., Mitra, A., Guldbrandtsen, B. & Sahana, G. (2018). High-density Genotyping reveals Genomic Characterization, Population Structure and Genetic Diversity of Indian Mithun (Bos frontalis). Scientific Reports, 8(1), Article 10316. https://doi.org/10.1038/s41598-018-28718-x

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

Xiang, T., Christensen, O. F., Vitezica, Z. G. & Legarra, A. (2018). Genomic model with correlation between additive and dominance effects. Genetics, 209(3), 711-723. https://doi.org/10.1534/genetics.118.301015

Marete, A. G., Sahana, G., Fritz, S., Lefebvre, R., Barbat, A., Lund, M. S., Guldbrandtsen, B. & Boichard, D. (2018). Genome-wide association study for milking speed in French Holstein cows. Journal of Dairy Science, 101(7), 6205-6219. https://doi.org/10.3168/jds.2017-14067

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

Rohde, P. D., Sørensen, I. F. & Sørensen, P. (2018). Genomic Feature Prediction Models - Improved Prediction Accuracy by Joint Marker Estimation. Poster session presented at ESHG 2018: European Society of Human Genetics, Milano, Italy.

Christensen, O. F., Kongsted, H. & Lund, M. S., (2018). Evaluering af avl for LG5, No. 2018-760-000656, 35 p., Jun 01, 2018.

Song, H., Li, L., Ma, P., Zhang, S., Su, G., Lund, M. S., Zhang, Q. & Ding, X. (2018). Short communication: Improving the accuracy of genomic prediction of body conformation traits in Chinese Holsteins using markers derived from high-density marker panels. Journal of Dairy Science, 101(6), 5250-5254. https://doi.org/10.3168/jds.2017-13456

López-Correa, R. D., Peñagaricano, F., Rovere, G. & Urioste, J. I. (2018). Genetic parameter estimation for long endurance trials in the Uruguayan Criollo horse. Journal of Animal Breeding and Genetics, 135(3), 186-193. https://doi.org/10.1111/jbg.12324

Rohde, P. D., Østergaard, S., Kristensen, T. N., Sørensen, P., Loeschcke, V., F C Mackay, T. & Sarup, P. M. (2018). Functional validation of candidate genes detected by genomic feature models. G3: Genes, Genomes, Genetics (Bethesda), 8(5), 1659-1668. https://doi.org/10.1534/g3.118.200082

Welderufael, B. G., Løvendahl, P., De Koning, D.-J., Janss, L. & Fikse, F. (2018). Genome-wide association study for susceptibility to and recoverability from mastitis in Danish Holstein cows. Frontiers in Genetics, 9(APR), Article 141. https://doi.org/10.3389/fgene.2018.00141

Villumsen, T. M., Thirstrup, J. P., Lund, M. S. & Malmkvist, J. (2018). Selektion for mere tillidsfulde mink medfører ikke tilbagegang for størrelse, kvalitet og frugtbarhed. In Faglig årsberetning 2017: Kopenhagen Fur Research Annual Report 2017 (pp. 16-21) https://issuu.com/kopenhagenfur/docs/289208__rsberetning_2017

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

Cericola, F., Lenk, I., Fè, D., Byrne, S., Jensen, C. S., Pedersen, M. G., Asp, T., Jensen, J. & Janss, L. (2018). Optimized Use of Low-Depth Genotyping-by-Sequencing for Genomic Prediction among multi-parental Family Pools and Single Plants in Perennial Ryegrass (Lolium perenne L.). Frontiers in Plant Science, 9, Article 369. https://doi.org/10.3389/fpls.2018.00369

Bouwman, A. C., Daetwyler, H. D., Chamberlain, A. J., Ponce, C. H., Sargolzaei, M., Schenkel, F. S., Sahana, G., Govignon-Gion, A., Boitard, S., Dolezal, M., Pausch, H., Brøndum, R. F., Bowman, P. J., Thomsen, B., Guldbrandtsen, B., Lund, M. S., Servin, B., Garrick, D. J., Reecy, J. ... Hayes, B. J. (2018). Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals. Nature Genetics, 50(3), 362-367. https://doi.org/10.1038/s41588-018-0056-5

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

Hein, L., Sørensen, L. P., Kargo, M. & Buitenhuis, A. J. (2018). Genetic analysis of predicted fatty acid profiles of milk from Danish Holstein and Danish Jersey cattle populations. Journal of Dairy Science, 101(3), 2148-2157. https://doi.org/10.3168/jds.2017-13225

Zetouni, L., Kargo, M., Norberg, E. & Lassen, J. (2018). Genetic correlations between methane production and fertility, health and body type traits in Danish Holstein cows. Journal of Dairy Science, 101(3), 2273-2280. https://doi.org/10.3168/jds.2017-13402

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.

Su, G., Madsen, P., Nielsen, B., Ostersen, T., Shirali, M., Jensen, J. & Christensen, O. F. (2018). Efficiency of group records for prediction of breeding values. In Proceedings of the World Congress on Genetics Applied to Livestock Production: Volume Methods and Tools - Prediction 3 (pp. 1-6). Article 11.565 WCGALP. http://www.wcgalp.org/proceedings/2018/efficiency-group-records-prediction-breeding-values

Kristensen, P. S., Jahoor, A., Andersen, J. R., Cericola, F., Orabi, J., Janss, L. L. & Jensen, J. (2018). Genome-wide association studies and comparison of models and cross-validation strategies for genomic prediction of quality traits in advanced winter wheat breeding lines. Frontiers in Plant Science, 9, Article 69. https://doi.org/10.3389/fpls.2018.00069

Mesbah-Uddin, M., Guldbrandtsen, B., Iso-Touru, T., Vilkki, J., De Koning, D.-J., Boichard, D., Lund, M. S. & Sahana, G. (2018). Genome-wide mapping of large deletions and their population-genetic properties in dairy cattle. D N A Research, 25(1), 49-59. https://doi.org/10.1093/dnares/dsx037

Nielsen, H. M., Ask, B. & Madsen, P. (2018). Social genetic effects for growth in pigs differ between boars and gilts. Genetics Selection Evolution, 50(1), Article 4. https://doi.org/10.1186/s12711-018-0375-0

Madsen, P., Milkevych, V., Gao, H., Christensen, O. F. & Jensen, J. (2018). DMU - A Package for Analyzing Multivariate Mixed Models in Quantitative Genetics and Genomics. Poster session presented at ICAR Conference and World Congress on Genetics Applied to Livestock Production 2018, Auckland, New Zealand.

Zaalberg, R. M., Shetty, N., Janss, L. & Buitenhuis, A. J. (2018). Genetic analysis of Fourier transform infrared milk spectra for Danish Holstein and Danish Jersey. 302. Abstract from The 11th 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). Genetic variance in macro-environmental sensitivity in growth rate in Danish Duroc pigs. Poster session presented at ICAR Conference and World Congress on Genetics Applied to Livestock Production 2018, Auckland, New Zealand.

Gebreyesus, G., Buitenhuis, A. J., Poulsen, N. A., Visker, M. H. P. W., Zhang, Q., van Valenberg, H. J. F., Sun, D. & Bovenhuis, H. (2018). Genome-wide association study of the de novo synthesized milk fatty acids based on Dutch, Danish and Chinese Holstein Friesians. 141. Abstract from The 11th World Congress on Genetics Applied to Livestock Production , Auckland, New Zealand.

Mesbah-Uddin, M., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2018). Genotype call for chromosomal deletions using read-depth from whole genome sequence variants in cattle. Poster session presented at The 11th World Congress on Genetics Applied to Livestock Production , Auckland, New Zealand.

Shetty, N., Janss, L., Zaalberg, R. M., Kargo, M. & Buitenhuis, A. J. (2018). Lactation stage dependent genome-wide association mapping for longitudinal data of milk fatty acids in dairy cattle using Bayesian mixture models. 321. Abstract from The 11th World Congress on Genetics Applied to Livestock Production , Auckland, New Zealand.

Ørsted, M., Rohde, P. D., Hoffmann, A. A., Sørensen, P. & Kristensen, T. N. (2018). Environmental variation partitioned into separate heritable components. Evolution, 72(1), 136-152. https://doi.org/10.1111/evo.13391

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.

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Jette Odgaard Villemoes