Publikationer

Peer-reviewed publikationer ved QGG

2018

Bidrag til konference

Nayee, N. K., Su, G., Gajjar, S. G., Sahana, G., Saha, S., Trivedi, K. R., Guldbrandtsen, B. & Lund, M. S. (2018). Genomic prediction by single-step genomic BLUP using cow reference population in Holstein crossbred cattle in India. Poster session præsenteret på ICAR Conference and World Congress on Genetics Applied to Livestock Production 2018, 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 præsenteret på The 11th World Congress on Genetics Applied to Livestock Production , Auckland, New Zealand.

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.

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

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.

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.

Demirovic, D., Buitenhuis, A. J., Poulsen, N. A., Munk, A. & Kargo, M. (2018). Large scale screening of the Danish dairy cattle population for their milk fatty acid profile. Poster session præsenteret på IDF World Dairy Summit 2018, Daejeon, Sydkorea.

2018

Bidrag til bog-antologi

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

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

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. I Faglig årsberetning 2017: Kopenhagen Fur Research Annual Report 2017 (s. 16-21) https://issuu.com/kopenhagenfur/docs/289208__rsberetning_2017

Villumsen, T. M., Su, G., Cai, Z., Guldbrandtsen, B., Asp, T., Sahana, G. & Lund, M. S. (2018). Genomic selection in mink yield higher accuracies with a Bayesian approach allowing for heterogeneous variance than a GBLUP model. I Proceedings of the World Congress on Genetics Applied to Livestock Production, 2018: Volume Methods and Tools - Prediction 2 artikel 11.618 http://www.wcgalp.org/proceedings/2018/genomic-selection-mink-yield-higher-accuracies-bayesian-approach-allowing

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

Su, G., Mansan Gordo, D. G., Li, B., Aamand, G., Lund, M. S. & Lassen, J. (2018). Genomic prediction for dry matter intake in Nordic Holsteins. I Proceedings of the World Congress on Genetics Applied to Livestock Production, 2018 (Bind Volume Electronic Poster Session - Methods and Tools - Prediction 2). artikel 474 WCGALP. http://www.wcgalp.org/system/files/proceedings/2018/genomic-prediction-dry-matter-intake-nordic-holsteins.pdf

Rovere, G. A., Madsen, P., Christiansen, K., Holm, M. & Lund, M. S. (2018). Prevalence and genetic variability of osteochondrosis in Danish Warmblood horses. I Proceedings of the World Congress on Genetics Applied to Livestock Production, 11.929 http://www.wcgalp.org/system/files/proceedings/2018/prevalence-and-genetic-variability-osteochondrosis-danish-warmblood-horses.pdf

Poulsen, N. A., Le, T. T. T., Gregersen, V. R., Christensen, B. S., Sørensen, E. S., Larsen, L. B. & Buitenhuis, A. J. (2018). Genetic parameter estimation of high value milk proteins and whey to casein ratio in Danish Holstein. I Proceedings of the 11th World Congress on Genetics Applied to Livestock Production (WCGALP), Auckland, New Zealand artikel 312

Nielsen, H-M., Ask, B., Christensen, O. F., Janss, L., Heidaritabar, M. & Madsen, P. (2018). Social genetic effects for growth in Landrace pigs with varying group sizes. I Proceedings of the World Congress on Genetics Applied to Livestock Production, 11.212 http://www.wcgalp.org/system/files/proceedings/2018/social-genetic-effects-growth-landrace-pigs-varying-group-sizes.pdf

Nayee, N. K., Su, G., Gajjar, S., Sahana, G., Saha, S., Trivedi, K. R., Guldbrandtsen, B. & Lund, M. S. (2018). Genomic prediction by single-step genomic BLUP using cow reference population in Holstein crossbred cattle in India. I Proceedings of the World Congress on Genetics Applied to Livestock Production, 2018: Volume Electronic Poster Session - Theory to Application - 1 (Bind 11). artikel 11.411 http://www.wcgalp.org/proceedings/2018/genomic-prediction-single-step-genomic-blup-using-cow-reference-population-holstein

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. I Proceedings of the World Congress on Genetics Applied to Livestock Production, 2018: Volume Electronic Poster Session - Molecular Genetics 3 (Bind 11). artikel 662 http://www.wcgalp.org/proceedings/2018/genotype-call-chromosomal-deletions-using-read-depth-whole-genome-sequence-variants

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

Luo, H., Xu, W., Liu, A., Li, X., Liu, L. & Wang, Y. (2018). Genome-wide association study for rectal temperature in Chinese Holstein population. I Proceedings of the World Congress on Genetics Applied to Livestock Production, 2018 artikel 587 http://www.wcgalp.org/system/files/proceedings/2018/genome-wide-association-study-rectal-temperature-chinese-holstein-population.pdf

Liu, A., Lund, M. S., Boichard, D., Fritz, S., Karaman, E., Wang, Y. & Su, G. (2018). Using additional single nucleotide polymorphisms selected from whole genome sequence data for genomic prediction in Danish Jersey. I Proceedings of the World Congress on Genetics Applied to Livestock Production, 2018 artikel 586 http://www.wcgalp.org/system/files/proceedings/2018/using-additional-single-nucleotide-polymorphisms-selected-whole-genome-sequence-data-genomic.pdf

Guldbrandtsen, B., Cai, Z., Sahana, G., Villumsen, T. M., Asp, T., Thomsen, B. & Lund, M. S. (2018). Genomics using the Assembly of the Mink Genome. I Proceedings of the World Congress on Genetics Applied to Livestock Production, 2018: Volume Electronic Poster Session - Molecular Genetics 1 artikel 539 http://www.wcgalp.org/proceedings/2018/genomics-using-assembly-mink-genome

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

Gajjar, S. G., Guldbrandtsen, B., Nayee, N. G., Sudhakar, A., Trivedi, K. R., Lund, M. S. & Sahana, G. (2018). Genetic composition, divergence, admixture and use of ancestry informative markers in indigenous breeds of cattle in India. I Proceedings of the World Congress on Genetics Applied to Livestock Production, 2018: Volume Challenges - Species Conservation artikel 585 http://www.wcgalp.org/archive?f%5Bauthor%5D=14045

Difford, G. F., Løvendahl, P., Lassen, J., Guldbrandtsen, B. & Sahana, G. (2018). Microbiability – new insights into (genetic) modelling methane emissions of cattle. I Proceedings of the World Congress on Genetics Applied to Livestock Production, 2018: Volume Challenges - Environmental (Bind 11). artikel 405 http://www.wcgalp.org/proceedings/2018/microbiability%E2%80%93-new-insights-genetic-modelling-methane-emissions-cattle

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

Anche, M. T., Su, G., Karaman, E., Janss, L. & Lund, M. S. (2018). Genomic prediction using multi-trait model with heterogeneous genomic (co)variance. I Proceedings of the World Congress on Genetics Applied to Livestock, 2018 (Bind Volume Methods and Tools - Models and Computing Strategies 2, s. 1-6). artikel 284 http://www.wcgalp.org/system/files/proceedings/2018/genomic-prediction-using-multi-trait-model-heterogeneous-genomic-covariance.pdf

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

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

2018

Bog-antologi

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.

Zetouni, L. (2018). Opportunities to select for low methane emitting dairy cattle.

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

Marete, A. G. (2018). Use of large scale cow genotyping to dissect dairy complex traits beyond additive effects.

Liu, A. (2018). Improvement of genetic evaluation and detection of quantitative trait loci for female fertility traits in dairy cattle.

Li, B. (2018). Genetic properties of feed efficiency and related traits in dairy cattle.

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

Difford, G. (2018). Genetic control of methane emission, feed efficiency and metagenomics in dairy cattle.

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 Nr. 130 http://web.agrsci.dk/djfpublikation/index.asp?action=show&id=1273

2018

Bidrag til artikel

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), artikel 111. https://doi.org/10.1186/s12863-018-0698-4

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

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. adv. onlinepublikation. https://doi.org/10.1111/age.12730

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

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), artikel 62. https://doi.org/10.1186/s12711-018-0432-8

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. adv. onlinepublikation. https://doi.org/10.3168/jds.2017-13402

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

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

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), artikel 141. https://doi.org/10.3389/fgene.2018.00141

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

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

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, artikel 1118. https://doi.org/10.3389/fpls.2018.01118

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

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

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

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

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

Skjerve, T. A., Grova, L., Sorheim, L. K., Slagboom, M., Eriksson, S., Kargo, M. & Wallenbeck, A. (2018). Norwegian dairy farmers' preferences for breeding goal traits and associations with herd and farm characteristics. Acta Agriculturae Scandinavica, Section A - Animal Science, 68(3), 117-123. https://doi.org/10.1080/09064702.2019.1627406

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

Schönherz, A. A., Forsberg, R., Guldbrandtsen, B., Buitenhuis, A. J. & Einer-Jensen, K. (2018). Introduction of Viral Hemorrhagic Septicemia Virus into Freshwater Cultured Rainbow Trout Is Followed by Bursts of Adaptive Evolution. Journal of Virology, 92(12), artikel e00436-18. adv. onlinepublikation. https://doi.org/10.1128/JVI.00436-18, https://doi.org/10.1128/JVI.00436-18

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

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), artikel 035. https://www.clinmedjournals.org/articles/jggr/journal-of-genetics-and-genome-research-jggr-5-035.pdf?jid=jggr

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

Pitkänen, T. J., Mäntysaari, E. A., Nielsen, U. S., Aamand, G. P., Madsen, P., Eriksson, J. & Lidauer, M. H. (2018). Incorporation of observations with different residual error variances into existing complex test-day models. Acta Agriculturae Scandinavica A: Animal Sciences, 68(1), 11-24. https://doi.org/10.1080/09064702.2018.1541361

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

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

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), artikel 4. https://doi.org/10.1186/s12711-018-0375-0

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

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), artikel 10316. https://doi.org/10.1038/s41598-018-28718-x

Milkevych, V., Munkholm, L. J., Chen, Y. & Nyord, T. (2018). Modelling approach for soil displacement in tillage using discrete element method. Soil & Tillage Research, 183(November), 60-71. https://doi.org/10.1016/j.still.2018.05.017

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. adv. onlinepublikation. https://doi.org/10.1093/dnares/dsx037

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

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

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

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

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

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), artikel 64. https://doi.org/10.1186/s40104-018-0279-4

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), 336-349. https://doi.org/10.1017/S1751731118002276

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

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. adv. onlinepublikation. https://doi.org/10.3168/jds.2018-14611

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, artikel 69. https://doi.org/10.3389/fpls.2018.00069

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

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

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, artikel 1165. https://doi.org/10.3389/fpls.2018.01165

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

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

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), artikel 9345. https://doi.org/10.1038/s41598-018-27729-y

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

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

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. artikel e1007580. https://doi.org/10.1371/journal.pgen.1007580

Difford, G. F., Olijhoek, D. W., Hellwing, A. L. F., Lund, P., Bjerring, M. A., de Haas, Y., Lassen, J. & Løvendahl, P. (2018). Ranking cows’ methane emissions under commercial conditions with sniffers versus respiration chambers. Acta Agriculturae Scandinavica A: Animal Sciences, 68(1), 25-32. https://doi.org/10.1080/09064702.2019.1572784

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), artikel 41. https://doi.org/10.1186/s12711-018-0411-0

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), artikel 58. https://doi.org/10.1186/s12711-018-0422-x

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

Chu, T. T., Bastiaansen, J. WM., Norberg, E. & Berg, P. (2018). On farm observations to increase genetic gain in breeding schemes for village poultry production – A simulation study. Acta Agriculturae Scandinavica, Section A - Animal Science, 68(1), 1-10. https://doi.org/10.1080/09064702.2018.1543444

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, artikel 369. https://doi.org/10.3389/fpls.2018.00369

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), artikel 656. https://doi.org/10.1186/s12864-018-5050-x

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), artikel 103. https://doi.org/10.1186/s12863-018-0688-6

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), 362-372. adv. onlinepublikation. https://doi.org/10.1038/s41588-018-0056-5

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

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