Publikationer

Peer-reviewed publikationer ved QGG

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, Artikel 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), Artikel 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 fra PAG 2017, San Diego, USA.

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 fra 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgien.

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), Artikel 95. https://doi.org/10.3390/agronomy9020095

Thomasen, J. R. & Lassen, J. (2019). Genomic Selection in the Nordic Countries. 45-47. Abstract fra ZAR-Seminar 2019, Østrig. 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 fra Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgien.

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. Artikel 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), Artikel 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), Artikel 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, Artikel 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 fra 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgien.

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. Artikel 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, Artikel 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, Artikel :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 fra 70th Annual Meeting of the European Federation of Animal Science (EAAP), Ghent, Belgien.

Guldbrandtsen, B., (2019). Nogle bemærkninger vedr. benefit sharing i husdyravl, Nr. 2019-760-001264, 7 s., maj 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), Artikel 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), Artikel 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 fra 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgien.

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

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, Artikel 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), Artikel 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), Artikel 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. Afhandling præsenteret på Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgien.

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. I Temadag om aktuel minkforskning: bilag (s. 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 fra 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgien.

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 fra 16th Symposium on Milk Genomics and Human Health, Aarhus, Danmark.

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 fra Dairy Research Conference 2019, Billund, Danmark.

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. I J. Kucera, P. Bucek, D. Lipovsky, X. Bourrigan & M. Burke (red.), 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 (s. 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, Artikel 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 fra Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgien.

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 fra Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgien.

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. Artikel 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 fra Abstract from 70th Annual Meeting of the European Federation of Animal Science EAAP 2019, Ghent, Belgium, Ghent, Belgien.

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 fra ICAR 2019, Prag, Tjekkiet. 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), Artikel 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 præsenteret på 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 fra 69th Annual Meeting of the European Federation of Animal Science EAAP 2018, Dubrovnik, Kroatien.

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, Artikel 522. https://doi.org/10.3389/fgene.2018.00522

Villumsen, T. M. & Lund, M. S. (2018). Anvendelse af auktionsdata i minkavlen. I S. H. Møller & J. Malmkvist (red.), Temadag om aktuel minkforskning: DCA Rapport nr. 129, September 2018 (s. 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), Artikel 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 præsenteret på 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), Artikel 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), Artikel 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), Artikel 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. Afhandling præsenteret på 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. I Proceedings of the World Congress on Genetics Applied to Livestock Production 2018: Volume theory to application (Bind 3). Artikel 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? I S. C. (red.), Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (Bind 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 fra 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

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

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

Rohde, P. D. (2018). Dissecting the genetic variation of schizophrenia and ADHD using an integrative genomic approach.

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

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 præsenteret på ICAR Conference and World Congress on Genetics Applied to Livestock Production 2018, Auckland, New Zealand.

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

Slagboom, M., Mulder, H. A., Sørensen, A. C., Hjortø, L., Thomasen, J. R. & Kargo, M. (2018). Effects of specific breeding lines for organic dairy production in Denmark. Abstract fra 69th Annual Meeting of the European Federation of Animal Science EAAP 2018, Dubrovnik, Kroatien.

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. I Proceedings of the World Congress on Genetics Applied to Livestock Production: Volume Methods and Tools - Prediction 3 (s. 1-6). Artikel 11.565 WCGALP. http://www.wcgalp.org/proceedings/2018/efficiency-group-records-prediction-breeding-values

Milkevych, V., Madsen, P., Gao, H. & Jensen, J. (2018). Efficient block-Gibbs sampling in variance component estimation for predictions which combine phenotypic and genomic information. 468. Abstract fra ICAR Conference and World Congress on Genetics Applied to Livestock Production 2018, 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

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), Artikel 42. https://doi.org/10.1186/s12711-018-0413-y

Gao, H., Madsen, P., Aamand, G. & Jensen, J. (2018). Estimation of variance components in populations under genomic selection. Afhandling præsenteret på ICAR Conference and World Congress on Genetics Applied to Livestock Production 2018, Auckland, New Zealand.

Christensen, O. F., Kongsted, H. & Lund, M. S., (2018). Evaluering af avl for LG5, Nr. 2018-760-000656, 35 s., jun. 01, 2018.

Boichard, D. A., Boussaha, M., Capitan, A., Rocha, D., Hoze, C., Sanchez, M.-P., Tribout, T., Letaief, R., Croiseau, P., Grohs, C., Li, W., Harland, C., Charlier, C., Lund, M. S., Sahana, G., Georges, M., Barbier, S., Coppieters, W., Fritz, S. & Guldbrandtsen, B. (2018). Experience from large scale use of the EuroGenomics custom SNP chip in cattle. I Proceedings of the World Congress on Genetics Applied to Livestock Production: Volume Molecular Genetics 4 (Bind 11). Artikel 11.675 http://www.wcgalp.org/proceedings/2018/experience-large-scale-use-eurogenomics-custom-snp-chip-cattle

Zhang, Q. (2018). Exploiting whole genome sequence variants in cattle breeding Unraveling the distribution of genetic variants and role of rare variants in genomic evaluation: Unraveling the distribution of genetic variants and role of rare variants in genomic evaluation.

Marete, A. G., Janss, L., Guldbrandtsen, B., Hoze, C., Sahana, G., Boichard, D. A. & Lund, M. S. (2018). Exploring non-additive variance using genome-wide dense SNP in four French and Nordic dairy cattle breeds. I Proceedings of the World Congress on Genetics Applied to Livestock Production Artikel 70

Gebreyesus, G. (2018). Fine mapping and genomic prediction for detailed milk composition. Aarhus University, Faculty of Science and Technology.

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

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), Artikel 513. https://doi.org/10.1186/s12859-018-2553-z

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 fra The 11th World Congress on Genetics Applied to Livestock Production , Auckland, New Zealand.

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Jette Odgaard Villemoes