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Center for Quantitative Genetics and Genomics

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Peer-reviewed publications at QGG

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2016

Book anthology

Le, T. H. (2016). Breeding for robust sows: Association between leg conformation, fertility and sow stayability. Aarhus University, Science and Technology.

Ismael, A. I. S. (2016). Genotype by environment interaction for automated and traditional fertility traits in dairy cattle. Aarhus University, Science and Technology.

Hamzic, E. (2016). Genetics of mechanisms controlling responses to two major pathogens in broiler and layer chickens. Aarhus University, Science and Technology.

Guo, X. (2016). Genomic prediction and GWAS for reproduction traits in Danish pigs. Aarhus University, Science and Technology.

Esfandyari, H. (2016). Genomic selection for crossbred performance. Aarhus University, Science and Technology. http://library.wur.nl/WebQuery/wurpubs/fulltext/369078

Chen, M. (2016). Studies on selection signatures in the genome of domestic animals. Aarhus University, Science and Technology.

Szekeres, B. D., Schönherz, A., Nielsen, V. H. & Guldbrandtsen, B. (2016). Gamle danske husdyrracers genomer - Racernes oprindelse og slægtskab. DCA - Nationalt Center for Fødevarer og Jordbrug,. DCA rapport No. 082

Kargo, M., Buitenhuis, A. J. & Munk, A. (2016). Fedtsyreprofilen i mælk fra malkekøer - potentiale og perspektiver. DCA - Nationalt Center for Fødevarer og Jordbrug,. DCA rapport No. 088

2016

Contribution to journal

Liu, Y., Lucas-Hahn, A., Petersen, B., Li, R., Hermann, D., Hassel, P., Ziegler, M., Li, J., Larsen, K. E., Niemann, H. & Callesen, H. (2016). Histone acetylation profile of porcine embryos produced by 2 cloning methods with or without in-vitro culture. Reproduction, Fertility and Development, 28, 137 (abst 15). https://doi.org/10.1071/RDv28n2abs

de Haas, Y., Pryce, J. E., Wall, E., McParland, S., Manzanilla-Pech, C., Difford, G. & Lassen, J. (2016). Genomic selection for methane emission. Journal of Animal Science, 94(supplement 5), 197-198. Article 0407. https://doi.org/10.2527/jam2016-0407

Simianer, H. & Sørensen, P. (2016). ICQG 5 on Madison's Isthmus links genomics and statistics of complex traits. Journal of Animal Breeding and Genetics (Online), 133(4), 249-250. https://doi.org/10.1111/jbg.12231

Zhang, Q., Guldbrandtsen, B., Calus, M. P. L., Lund, M. S. & Sahana, G. (2016). Comparison of gene-based rare variant association mapping methods for quantitative traits in a bovine population with complex familial relationships. Genetics Selection Evolution, 48(1), Article 60. https://doi.org/10.1186/s12711-016-0238-5

Zhang, Q., Guldbrandtsen, B., Thomasen, J. R., Lund, M. S. & Sahana, G. (2016). Genome-wide association study for longevity with whole-genome sequencing in 3 cattle breeds. Journal of Dairy Science, 99(9), 7289-7298. https://doi.org/10.3168/jds.2015-10697

Yang, H. & Su, G. (2016). Impact of phenotypic information of previous generations and depth of pedigree on estimates of genetic parameters and breeding values. Livestock Science, 187, 61-67. https://doi.org/10.1016/j.livsci.2016.03.001

Xiang, T., Nielsen, B., Su, G., Legarra, A. & Christensen, O. F. (2016). Application of single-step genomic evaluation for crossbred performance in pig. Journal of Animal Science, 94(3), 936-948. https://doi.org/10.2527/jas.2015-9930

Xiang, T., Christensen, O. F., Vitezica, Z. G. & Legarra, A. (2016). Genomic evaluation by including dominance effects and inbreeding depression for purebred and crossbred performance with an application in pigs. Genetics Selection Evolution, 48(1), 1-14. Article 98. https://doi.org/10.1186/s12711-016-0271-4

Xia, D., Zhang, S., Nielsen, E., Ivarsen, A. R., Liang, C., Li, Q., Thomsen, K., Hjortdal, J. Ø. & Dong, M. (2016). The Ultrastructures and Mechanical Properties of the Descement's Membrane in Fuchs Endothelial Corneal Dystrophy. Scientific Reports, 6, Article 23096. https://doi.org/10.1038/srep23096

Wu, X., Guldbrandtsen, B., Lund, M. S. & Sahana, G. (2016). Association analysis for feet and legs disorders with whole-genome sequence variants in 3 dairy cattle breeds. Journal of Dairy Science, 99(9), 7221–7231. https://doi.org/10.3168/jds.2015-10705

van den Berg, I., Boichard, D. & Lund, M. S. (2016). Comparing power and precision of within-breed and multibreed genome-wide association studies of production traits using whole-genome sequence data for 5 French and Danish dairy cattle breeds. Journal of Dairy Science, 99(11), 8932-8945. https://doi.org/10.3168/jds.2016-11073

van den Berg, I., Boichard, D., Guldbrandtsen, B. & Lund, M. S. (2016). Using Sequence Variants in Linkage Disequilibrium with Causative Mutations to Improve Across-Breed Prediction in Dairy Cattle: A Simulation Study. G3: Genes, Genomes, Genetics, 6(8), 2553-2561. https://doi.org/10.1534/g3.116.027730

Ulrich-Lynge, S. L., Juul-Madsen, H. R., Kjærup, R. B., Okimoto, R., Abrahamsen, M., Maurischat, S., Sørensen, P. & Dalgaard, T. S. (2016). Broilers with low serum Mannose-binding Lectin show increased faecal shedding of Salmonella enterica serovar Montevideo. Poultry Science, 95(8), 1779-1786. https://doi.org/10.3382/ps/pew101

Thomasen, J. R., Willam, A., Egger-Danner, C. & Sørensen, A. C. (2016). Reproductive technologies combine well with genomic selection in dairy breeding programs. Journal of Dairy Science, 99(2), 1331-40. https://doi.org/10.3168/jds.2015-9437

Thodberg, K., Sørensen, L. U., Videbech, P. B., Haun Poulsen, P., Houbak, B., Damgaard, V., Keseler, I., Edwards, D. & Christensen, J. W. (2016). Behavioral Responses of Nursing Home Residents to Visits From a Person with a Dog,a Robot Seal or a Toy Cat. Anthrozoos, 29(1), 107-121. https://doi.org/10.1080/08927936.2015.1089011

Thodberg, K., Uhrskov, L., Christensen, J. W., Haun Poulsen, P., Houbak, B., Damgaard, V. J., Keseler, I., Edwards, D. & Videbech, P. (2016). Therapeutic effects of dog visits in nursing homes for the elderly. Psychogeriatrics, 16(5), 289-297. https://doi.org/10.1111/psyg.12159

Suravajhala, P., Kogelman, L. J. A. & Kadarmideen, H. N. (2016). Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare. Genetics Selection Evolution, 48(1), Article 38. https://doi.org/10.1186/s12711-016-0217-x

Su, G., Ma, P., Nielsen, U. S., Aamand, G. P., Wiggans, G., Guldbrandtsen, B. & Lund, M. S. (2016). Sharing reference data and including cows in the reference population improve genomic predictions in Danish Jersey. Animal, 10(6), 1067-1075. https://doi.org/10.1017/S1751731115001792

Stjernholm, T., Ommen, P., Langkilde, A., Johansen, C., Iversen, L., Rosada, C. & Stenderup, K. (2016). Leptin-deficiency in mice counteracts imiquimod (IMQ)-induced psoriasis-like skin inflammation while leptin stimulation induces inflammation in human keratinocytes. Experimental Dermatology, 26(4), 338-345. https://doi.org/10.1111/exd.13149

Steffensen, S., Pedersen, H., Adhikari, K., Laursen, B., Jensen, C., Høyer, S., Borre, M., Pedersen, H. H., Borre, M., Edwards, D. & Fomsgaard, I. S. (2016). Benzoxazinoids in Prostate Cancer Patients after a Rye-Intensive Diet: Methods and Initial Results. Journal of Agricultural and Food Chemistry, 64(43), 8235-8245. https://doi.org/10.1021/acs.jafc.6b03765

Sørensen, A. C. (2016). Den perfekte øko-so forudsætter uafhængigt avlsarbejde. Oekologi & Erhverv, (584), 12. http://orgprints.org/29908/1/Sorensen_2016_avlsarbejde_svineproduktion.pdf

Sørensen, L. P., Bjerring, M. & Løvendahl, P. (2016). Monitoring individual cow udder health in automated milking systems using online somatic cell counts. Journal of Dairy Science, 99(1), 608-620. https://doi.org/10.3168/jds.2014-8823

Slagboom, M., Kargo, M., Edwards, D., Sørensen, A. C., Thomasen, J. R. & Hjortø, L. (2016). Herd characteristics influence farmers’ preferences for trait improvements in Danish Red and Danish Jersey cows. Acta Agriculturae Scandinavica, Section A - Animal Science, 66(3), 177-182. https://doi.org/10.1080/09064702.2016.1277550

Slagboom, M., Kargo, M., Edwards, D., Sørensen, A. C., Thomasen, J. R. & Hjortø, L. (2016). Organic dairy farmers put more emphasis on production traits than conventional farmers. Journal of Dairy Science, 99(12), 9845–9856. https://doi.org/10.3168/jds.2016-11346

Shetty, N., Løvendahl, P., Lund, M. S. & Buitenhuis, A. J. (2016). Prediction and validation of residual feed intake and dry matter intake in Danish lactating dairy cows using mid-infrared spectroscopy of milk. Journal of Dairy Science, 100(1), 253-264. https://doi.org/10.3168/jds.2016-11609

Schönherz, A. A., Lorenzen, N., Guldbrandtsen, B., Buitenhuis, B. & Einer-Jensen, K. (2016). Ultra-deep sequencing of VHSV isolates contributes to understanding the role of viral quasispecies. Veterinary Research, 47(10), Article 10. https://doi.org/10.1186/s13567-015-0298-5

Sarup, P. M., Jensen, J., Ostersen, T., Henryon, M. & Sørensen, P. (2016). Increased prediction accuracy using a genomic feature model including prior information on quantitative trait locus regions in purebred Danish Duroc pigs. BMC Genetics, 17(11), Article 11. https://doi.org/10.1186/s12863-015-0322-9

Sarup, P., Petersen, S. M. M., Nielsen, N. C., Loeschcke, V. & Malmendal, A. (2016). Mild heat treatments induce long-term changes in metabolites associated with energy metabolism in Drosophila melanogaster. Biogerontology, 17(5), 873-882. Article 873. https://doi.org/10.1007/s10522-016-9657-5

Sahana, G., Iso-Touru, T., Wu, X., Nielsen, U., de Koning, D.-J., Lund, M. S., Vilkki, J. & Guldbrandtsen, B. (2016). A 0.5-Mbp deletion on bovine chromosome 23 is a strong candidate for stillbirth in Nordic Red cattle. Genetics Selection Evolution, 48(1), Article 35. https://doi.org/10.1186/s12711-016-0215-z

Rovere, G., Ducro, B. J., van Arendonk, J. A. M., Norberg, E. & Madsen, P. (2016). Analysis of competition performance in dressage and show jumping of Dutch Warmblood horses. Journal of Animal Breeding and Genetics, 133(6), 503-512. https://doi.org/10.1111/jbg.12221

Rohde, P. D., Krag, K., Loeschcke, V., Overgaard, J., Sørensen, P. & Kristensen, T. N. (2016). A Quantitative Genomic Approach for Analysis of Fitness and Stress Related Traits in a Drosophila melanogaster Model Population. International Journal of Genomics, 2016, 1-11. Article 2157494. https://doi.org/10.1155/2016/2157494

Rohde, P. D., Demontis, D., Castro Dias Cuyabano, B., Børglum, A. & Sørensen, P. (2016). Covariance Association Test (CVAT) Identifies Genetic Markers Associated with Schizophrenia in Functionally Associated Biological Processes. Genetics (Print), 203(4), 1901-1913. https://doi.org/10.1534/genetics.116.189498

Rohde, P. D., Madsen, L. S., Arvidson, S. M. N., Loeschcke, V., Demontis, D. & Kristensen, T. N. (2016). Testing candidate genes for attention-deficit/hyperactivity disorder in fruit flies using a high throughput assay for complex behavior. Fly, 10(1), 25-34. Article 1158365. https://doi.org/10.1080/19336934.2016.1158365

Poulsen, J. B., Lescai, F., Grove, J., Bækvad-Hansen, M., Christiansen, M., Hagen, C. M., Maller, J., Stevens, C., Li, S., Li, Q., Sun, J., Wang, J., Nordentoft, M., Werge, T. M., Mortensen, P. B., Børglum, A. D., Daly, M., Hougaard, D. M., Bybjerg-Grauholm, J. & Hollegaard, M. V. (2016). High-Quality Exome Sequencing of Whole-Genome Amplified Neonatal Dried Blood Spot DNA. PLOS ONE, 11(4), e0153253. Article e0153253. https://doi.org/10.1371/journal.pone.0153253

Pertoldi, C., Bahrndorff, S., Kurbalija Novicic, Z. & Rohde, P. D. (2016). The Novel Concept of “Behavioural Instability” and Its Potential Applications. Symmetry, 8(11), 1-13. Article 135. https://doi.org/10.3390/sym8110135

Pedersen, H. S., Løvendahl, P., Larsen, K. E., Madsen, L. B. & Callesen, H. (2016). Porcine oocyte mtDNA copy number is high or low depending on the donor. Zygote, 24(4), 617-623. https://doi.org/10.1017/S0967199415000611

Pedersen, H. S., Callesen, H., Løvendahl, P., Chen, F., Nyengaard, J. R., Nikolaisen, N. K., Holm, P. & Hyttel, P. (2016). Ultrastructure and mitochondrial numbers in pre- and postpubertal pig oocytes. Reproduction, Fertility and Development, 28(5), 586-598. https://doi.org/10.1071/RD14220

Pedersen, L., Idorn, M., Olofsson, G. H., Lauenborg, B., Nookaew, I., Hansen, R. H., Johannesen, H. H., Becker, J. C., Pedersen, K. S., Dethlefsen, C., Nielsen, J., Gehl, J., Pedersen, B. K., Thor Straten, P. & Hojman, P. (2016). Voluntary Running Suppresses Tumor Growth through Epinephrine- and IL-6-Dependent NK Cell Mobilization and Redistribution. Cell Metabolism, 23(3), 554-62. https://doi.org/10.1016/j.cmet.2016.01.011

Ostersen, T., Christensen, O. F., Madsen, P. & Henryon, M. (2016). Sparse single-step method for genomic evaluation in pigs. Genetics Selection Evolution, 48(1), Article 48. https://doi.org/10.1186/s12711-016-0227-8

Østergaard, S., Ettema, J. F., Hjortø, L., Pedersen, J., Lassen, J. & Kargo, M. (2016). Avoiding double counting when deriving economic values through stochastic dairy herd simulation. Livestock Science, 187, 114-124. https://doi.org/10.1016/j.livsci.2016.03.004

Nielsen, B., Christensen, O. F. & Velander, I. (2016). Nurse capacity, fertility, and litter size in crossbred sows and genetic correlation to purebred sow information. Journal of Animal Science, 94(5), 1827-1833. https://doi.org/10.2527/jas.2015-0199

Moyes, K. M., Sørensen, P. & Bionaz, M. (2016). The impact of intramammary Escherichia coli challenge on liver and mammary transcriptome and cross-talk in dairy cows during early lactation using RNAseq. P L o S One, 11(6), Article e0157480. https://doi.org/10.1371/journal.pone.0157480

Michot, P., Chahory, S., Marete, A. G., Grohs, C., Dagios, D., Donzel, E., Aboukadiri, A., Deloche, M.-C., Allais-Bonnet, A., Chambrial, M., Barbey, S., Genestout, L., Boussaha, M., Danchin-Burge, C., Fritz, S., Boichard, D. & Capitan, A. (2016). A reverse genetic approach identifies an ancestral frameshift mutation in RP1 causing recessive progressive retinal degeneration in European cattle breeds. Genetics Selection Evolution, 48. https://doi.org/10.1186/s12711-016-0232-y

Mao, X., Kadri, N. K., Thomasen, J. R., de Koning, D. J., Sahana, G. & Guldbrandtsen, B. (2016). Fine mapping of a calving QTL on Bos taurus autosome 18 in Holstein cattle. Journal of Animal Breeding and Genetics, 133(3), 207-218. https://doi.org/10.1111/jbg.12187

Mao, X., Sahana, G., De Koning, D.-J. & Guldbrandtsen, B. (2016). Genome-wide association studies of growth traits in three dairy cattle breeds using whole-genome sequence data. Journal of Animal Science, 94(4), 1426-1437. https://doi.org/10.2527/jas.2015-9838

Mao, X., Johansson, A. M., Sahana, G., Guldbrandtsen, B. & De Koning, D.-J. (2016). Short communication: Imputation of markers on the Bovine X chromosome. Journal of Dairy Science, 99(9), 7313-7318. https://doi.org/10.3168/jds.2016-11160

Manzanares, C., Barth, S., Thorogood, D., Byrne, S., Yates, S., Czaban, A., Asp, T., Yang, B. & Studer, B. (2016). A Gene Encoding a DUF247 Domain Protein Cosegregates with the S Self-Incompatibility Locus in Perennial Ryegrass. Molecular Biology and Evolution, 33(4), 870-884. https://doi.org/10.1093/molbev/msv335

Lund, M. S., van den Berg, I., Ma, P., Brøndum, R. F. & Su, G. (2016). Review: How to improve genomic predictions in small dairy cattle populations. Animal, 10(6), 1042-1049. https://doi.org/10.1017/S1751731115003031

Løvendahl, P. & Sorensen, L. P. (2016). Frequently recorded sensor data may correctly provide health status of cows if data are handled carefully and errors are filtered away. Biotechnologie, Agronomie, Société et Environnement, 20(1), 3-12. http://popups.ulg.ac.be/1780-4507/index.php?id=12562

Løvendahl, P. & Sehested, J. (2016). Short communication: Individual cow variation in urinary excretion of phosphorus. Journal of Dairy Science, 99(6), 4580-4585. Article 74483. https://doi.org/10.3168/jds.2015-10338

Løvendahl, P., Sørensen, L. P., Bjerring, M. & Lassen, J. (2016). Short communication: Genetic variation in choice consistency for cows accessing automatic milking units. Journal of Dairy Science, 99(12), 9857-9863. https://doi.org/10.3168/jds.2016-11287

Lopes, M. S., Bastiaansen, J. W. M., Janss, L., Knol, E. F. & Bovenhuis, H. (2016). Genomic prediction of growth in pigs based on a model including additive and dominance effects. Journal of Animal Breeding and Genetics (Online), 133(3), 180-186. https://doi.org/10.1111/jbg.12195

Liu, H., Henryon, M. & Sørensen, A. C. (2016). Mating strategies with genomic information reduce rates of inbreeding in animal breeding schemes without compromising genetic gain. Animal, 11(4), 547-555. https://doi.org/10.1017/S1751731116001786

Li, B., Fikse, W. F., Lassen, J., Lidauer, M. H., Løvendahl, P., Mäntysaari, P. & Berglund, B. (2016). Genetic parameters for dry matter intake in primiparous Holstein, Nordic Red, and Jersey cows in the first half of lactation. Journal of Dairy Science, 99(9), 7232-7239. https://doi.org/10.3168/jds.2015-10669

Li, X., Lund, M. S., Zhang, Q., Costa, C. N., Ducrocq, V. & Su, G. (2016). Short communication: Improving accuracy of predicting breeding values in Brazilian Holstein population by adding data from Nordic and French Holstein populations. Journal of Dairy Science, 99(6), 4574-4579. Article 74482. https://doi.org/10.3168/jds.2015-10609

Le, T. H., Madsen, P., Lundeheim, N., Nilsson, K. & Norberg, E. (2016). Genetic association between leg conformation in young pigs and sow longevity. Journal of Animal Breeding and Genetics, 133(4), 283-290. https://doi.org/10.1111/jbg.12193

Lassen, J., Poulsen, N. A., Larsen, M. K. & Buitenhuis, A. J. (2016). Genetic and genomic relationship between methane production measured in breath and fatty acid content in milk samples from Danish Holsteins. Animal Production Science, 56(2-3), 298-303. https://doi.org/10.1071/AN15489

Lassen, J. & Løvendahl, P. (2016). Heritability estimates for enteric methane emissions from Holstein cattle measured using noninvasive methods. Journal of Dairy Science, 99(3), 1959-1967. https://doi.org/10.3168/jds.2015-10012

Laplat, F., Jensen, J. & Madsen, P. (2016). Genomic Prediction of Manganese Efficiency in Winter Barley. The Plant Genome, 9(2), 1-13. https://doi.org/10.3835/plantgenome2015.09.0085

Kumar, A., Kumar, S., Kumar, U., Suravajhala, P. & Gajula, M. N. V. P. (2016). Functional and structural insights into novel DREB1A transcription factors in common wheat (Triticum aestivum L.): A molecular modeling approach. Computational Biology and Chemistry, 64, 217-226. https://doi.org/10.1016/j.compbiolchem.2016.07.008

Knol, E. F., Nielsen, B. & Knap, P. W. (2016). Genomic selection in commercial pig breeding. Animal Frontiers, 6(1), 15-22. https://doi.org/10.2527/af.2016-0003

Katam, R., Sakata, K., Suravajhala, P., Pechan, T., Kambiranda, D. M., Naik, K. S., Guo, B. & Basha, S. M. (2016). Comparative leaf proteomics of drought-tolerant and -susceptible peanut in response to water stress. Journal of Proteomics, 143, 209-226. https://doi.org/10.1016/j.jprot.2016.05.031

Jönsson, L., Madsen, P. & Mark, T. (2016). Modelling repeated competition records in genetic evaluations of Danish sport horses. Journal of Animal Breeding and Genetics (Online), 133(4), 291-302. https://doi.org/10.1111/jbg.12190

Jimenez Mena, B., Tataru, P., Brøndum, R. F., Sahana, G., Guldbrandtsen, B. & Bataillon, T. (2016). One size fits all? Direct evidence for the heterogeneity of genetic drift throughout the genome. Biology Letters, 12(7), Article 20160426. https://doi.org/10.1098/rsbl.2016.0426

Jensen, J. (2016). Estimation of genetic variance in the age of genomics. Journal of Animal Breeding and Genetics, 133(5), 333. https://doi.org/10.1111/jbg.12235

Iso-Touru, T., Sahana, G., Guldbrandtsen, B., Lund, M. S. & Vilkki, J. (2016). Genome-wide association analysis of milk yield traits in Nordic Red Cattle using imputed whole genome sequence variants. BMC Genetics, 17(1), Article 55. https://doi.org/10.1186/s12863-016-0363-8

Ismael, A., Strandberg, E., Berglund, B., Kargo, M., Fogh, A. & Løvendahl, P. (2016). Genotype by environment interaction for activity-based estrus traits in relation to production level for Danish Holstein. Journal of Dairy Science, 99(12), 9834-9844. https://doi.org/10.3168/jds.2016-11446

Ismael, A. I. S., Strandberg, E., Berglund, B., Kargo, M., Fogh, A. & Løvendahl, P. (2016). Genotype by environment interaction for the interval from calving to first insemination with regard to calving month and geographic location in Holstein cows in Denmark and Sweden. Journal of Dairy Science, 99(7), 5498-5507. Article 10.3168/jds.2015-10820. https://doi.org/10.3168/jds.2015-10820

Ismael, A. I. S., Strandberg, E., Berglund, B., Fogh, A. & Løvendahl, P. (2016). Seasonality of fertility measured by physical activity traits in Holstein cows. Journal of Dairy Science, 99(4), 2837-2848. https://doi.org/10.3168/jds.2015-10067

Iddamalgoda, L., Das, P. S., Aponso, A., Sundararajan, V. S., Suravajhala, P. & Valadi, J. K. (2016). Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications. Frontiers in Genetics, 7(AUG), Article 136. https://doi.org/10.3389/fgene.2016.00136

Hjortø, L., Thomassen, J. R., Kargo, M., Sørensen, A. C. & Slagboom, M. (2016). Mælkeproducenter prioriterer forskellige egenskaber i avlen. Kvaeg, (6), 48-49. https://www.landbrugsinfo.dk/Kvaeg/Avl/Sider/KvaegJuni2016_side48.pdf

Hjortø, L. (2016). Mælkeproducenter vægter ydelse højt i avlsmålet. Oekologi & Erhverv, (588), 10. Article 588. http://okologi.dk/media/890423/oekologi-erhverv-nr-588.pdf

Herold, C., Hooli, B. V., Mullin, K., Liu, T., Roehr, J. T., Mattheisen, M., Parrado, A. R., Bertram, L., Lange, C. & Tanzi, R. E. (2016). Family-based association analyses of imputed genotypes reveal genome-wide significant association of Alzheimer's disease with OSBPL6, PTPRG, and PDCL3. Molecular Psychiatry, 21(11), 1608-1612. https://doi.org/10.1038/mp.2015.218

Henten, A. M. V., Loeschcke, V., Pedersen, J. G., Leisner, J. J. & Sarup, P. (2016). Injuries can prolong lifespan in Drosophila melanogaster males. Biogerontology, 17(2), 337-346. https://doi.org/10.1007/s10522-015-9616-6

Hamzic, E., Kjærup, R. B., Mach , N., Minozzi, G., Strozzi, F., Gualdi, V., Williams, J. L., Chen, J., Wattrang, E., Buitenhuis, A. J., Juul-Madsen, H. R. & Dalgaard, T. S. (2016). RNA sequencing based analysis of the spleen transcriptome following the infectious bronchitis virus infection of chickens selected for different mannose-binding lectin serum concentrations. BMC Genomics, 17(1), Article 82. https://doi.org/10.1186/s12864-016-2403-1

Guo, X., Su, G., Christensen, O. F., Janss, L. & Lund, M. S. (2016). Genome-wide association analyses using a Bayesian approach for litter size and piglet mortality in Danish Landrace and Yorkshire pigs. BMC Genomics, 17, Article 468. https://doi.org/10.1186/s12864-016-2806-z

Guo, X., Christensen, O. F., Ostersen, T., Wang, Y., Lund, M. S. & Su, G. (2016). Genomic prediction using models with dominance and imprinting effects for backfat thickness and average daily gain in Danish Duroc pigs. Genetics Selection Evolution, 48(1), Article 67. https://doi.org/10.1186/s12711-016-0245-6

Groeneveld, L. F., Gregusson, S., Guldbrandtsen, B., Hiemstra, S. J., Hveem, K., Kantanen, J., Lohi, H., Stroemstedt, L. & Berg, P. (2016). Domesticated Animal Biobanking: Land of Opportunity. PLoS Biology, 14(7), Article e1002523. https://doi.org/10.1371/journal.pbio.1002523

Gebreyesus, G., Lund, M. S., Janss, L., Poulsen, N. A., Larsen, L. B., Bovenhuis, H. & Buitenhuis, A. J. (2016). Short communication: Multi-trait estimation of genetic parameters for milk protein composition in the Danish Holstein. Journal of Dairy Science, 99(4), 2863-2866. https://doi.org/10.3168/jds.2015-10501

Fè, D., Ashraf, B. H., Pedersen, M. G., Janss, L., Byrne, S., Roulund, N., Lenk, I., Didion, T., Asp, T., Jensen, C. S. & Jensen, J. (2016). Accuracy of genomic prediction in a commercial perennial ryegrass breeding program. The Plant Genome, 9(3). https://doi.org/10.3835/plantgenome2015.11.0110

Fang, L., Hou, Y., An, J., Li, B., Song, M., Wang, X., Sørensen, P., Dong, Y., Liu, C., Wang, Y., Zhu, H., Zhang, S. & Yu, Y. (2016). Genome-wide transcriptional and post-transcriptional regulation of innate immune and defense responses of bovine mammary gland to Staphylococcus aureus. Frontiers in cellular and infection microbiology, 6, Article 193. https://doi.org/10.3389/fcimb.2016.00193

Fan, S., Geissmann, Q., Lakatos, E., Lukauskas, S., Ale, A., Babtie, A. C., Kirk, P. D. W. & Stumpf, M. P. H. (2016). MEANS: Python package for Moment Expansion Approximation, iNference and Simulation. Bioinformatics, 32(18), 2863-2865. https://doi.org/10.1093/bioinformatics/btw229

Esfandyari, H., Bijma, P., Henryon, M., Christensen, O. F. & Sørensen, A. C. (2016). Genomic prediction of crossbred performance based on purebred Landrace and Yorkshire data using a dominance model. Genetics Selection Evolution, 48(1), Article 40. https://doi.org/10.1186/s12711-016-0220-2

Ehsani, A., Janss, L., Pomp, D. & Sørensen, P. (2016). Decomposing genomic variances in a mouse F2 population using information from GWA, GWE and eQTL analyses. Animal Genetics, 47(2), 165-173. https://doi.org/10.1111/age.12396

Edwards, S. M., Sørensen, I. F., Sarup, P., Mackay, T. F. C. & Sørensen, P. (2016). Genomic prediction for quantitative traits is improved by mapping variants to gene ontology categories in Drosophila melanogaster. Genetics, 203(4), 1871-1883. https://doi.org/10.1534/genetics.116.187161

Christensen, M. H., Jensen, S. B., Miettinen, J. J., Luecke, S., Prabakaran, T., Reinert, L. S., Mettenleiter, T., Chen, Z. J., Knipe, D. M., Sandri-Goldin, R. M., Enquist, L. W., Hartmann, R., Mogensen, T. H., Rice, S. A., Nyman, T. A., Matikainen, S. & Paludan, S. R. (2016). HSV-1 ICP27 targets the TBK1-activated STING signalsome to inhibit virus-induced type I IFN expression. EMBO Journal, 35(13), 1385-1399. https://doi.org/10.15252/embj.201593458

Chen, M., Pan, D., Ren, H., Fu, J., Li, J., Su, G., Wang, A., Jiang, L., Zhang, Q. & Liu, J.-F. (2016). Identification of selective sweeps reveals divergent selection between Chinese Holstein and Simmental cattle populations. Genetics Selection Evolution, 48(1), 1-12. Article 76. https://doi.org/10.1186/s12711-016-0254-5

Buitenhuis, A. J., Poulsen, N. A., Gebreyesus, G. & Larsen, L. B. (2016). Estimation of genetic parameters and detection of chromosomal regions affecting the major milk proteins and their post translational modifications in Danish Holstein and Danish Jersey cattle. BMC Genetics, 17(1), Article 114. https://doi.org/10.1186/s12863-016-0421-2

Bovenhuis, H., Visker, M. H. P. W., Poulsen, N. A., Sehested, J., van Valenberg, H. J. F., van Arendonk, J. A. M., Larsen, L. B. & Buitenhuis, A. J. (2016). Effects of the diacylglycerol o-acyltransferase 1 (DGAT1) K232A polymorphism on fatty acid, protein, and mineral composition of dairy cattle milk. Journal of Dairy Science, 99(4), 3113-3123. https://doi.org/10.3168/jds.2015-10462

Bertelsen, H. P., Gregersen, V. R., Poulsen, N. A., Nielsen, R. O., Das, A., Madsen, L. B., Buitenhuis, A. J., Holm, L.-E., Panitz, F., Larsen, L. B. & Bendixen, C. (2016). Detection of genetic variation affecting milk coagulation properties in Danish Holstein dairy cattle by analyses of pooled whole-genome sequences from phenotypically extreme samples (pool-seq). Journal of Animal Science, 94(4), 1365-1376. https://doi.org/10.2527/jas.2015-9884

Bengtsson, C., Fogh, A. & Kargo, M. (2016). Avlsindekset for persistens har begrænset information om ydelsen i sen laktation. Ny KvægForskning, (5), 7-8.

Begli, H. E., Torshizi, R. V., Masoudi, A. A., Ehsani, A. & Jensen, J. (2016). Longitudinal analysis of body weight, feed intake and residual feed intake in F₂ chickens. Livestock Science, 184, 28-34. https://doi.org/10.1016/j.livsci.2015.11.018

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