Publikationer

Peer-reviewed publikationer ved QGG

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

Geissmann, Q., Beckwith, E. J. & Gilestro, G. F. (2019). Most sleep does not serve a vital function: Evidence from Drosophila melanogaster. Science Advances, 5(2), Artikel eaau9253. https://doi.org/10.1126/sciadv.aau9253

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

Geissmann, Q., Rodriguez, L. G., Beckwith, E. J. & Gilestro, G. F. (2019). Rethomics: An R framework to analyse high-throughput behavioural data. PLOS ONE, 14(1), Artikel e0209331. https://doi.org/10.1371/journal.pone.0209331

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.

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

Yan, X., Liu, A., Dong, G., Guo, G., Li, X., Su, G. & Wang, Y. (2018). Genetic analysis of productive life in Chinese Holstein population. Abstract fra 5th International Conference on Quantitative Genetics, Madison, USA.

Zhang, H., Xu, W., Li, X., Luo, H., Liu, A. & Wang, Y. (2018). Genetic analysis of skinfold thickness and its association with body condition score, and milk production traits in Chinese Holstein population. Abstract fra ICAR Conference and World Congress on Genetics Applied to Livestock Production 2018, Auckland, New Zealand.

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

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

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

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

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

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

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

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.

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

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

Liu, A., Wang, Y., Lund, M. S. & Su, G. (2018). Genome-wide association study for female fertility traits in Chinese Holstein population. Abstract fra 5th International Conference on Quantitative Genetics, Madison, USA.

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

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

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

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

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

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

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

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