Zhou, Y., Zhang, Z., Bao, Z., Li, H., Lyu, Y., Zan, Y., Wu, Y., Cheng, L., Fang, Y., Wu, K., Zhang, J., Lyu, H., Lin, T., Gao, Q., Saha, S., Mueller, L., Fei, Z., Städler, T., Xu, S. ... Huang, S. (2022). Graph pangenome captures missing heritability and empowers tomato breeding. Nature, 606(7914), 527-534. https://doi.org/10.1038/s41586-022-04808-9

Salunke, S., Ahuja, B., Hashmi, M. F., Marriboyina, V. & Bokde, N. D. (2022). 5D Gauss Map Perspective to Image Encryption with Transfer Learning Validation. Applied Sciences, 12(11), Article 5321. https://doi.org/10.3390/app12115321

Shende, M. K., Salih, S. Q., Bokde, N. D., Scholz, M., Oudah, A. Y. & Yaseen, Z. M. (2022). Natural Time Series Parameters Forecasting: Validation of the Pattern-Sequence-Based Forecasting (PSF) Algorithm; A New Python Package. Applied Sciences (Switzerland), 12(12), Article 6194. https://doi.org/10.3390/app12126194

Sterenborg, R. B. T. M., Galesloot, T. E., Teumer, A., Netea-Maier, R. T., Speed, D., Meima, M. E., Visser, W. E., Smit, J. W. A., Peeters, R. P. & Medici, M. (2022). The effects of common genetic variation in 96 genes involved in thyroid hormone regulation on TSH and FT4 concentrations. The Journal of Clinical Endocrinology & Metabolism, 107(6), e2276-e2283. https://doi.org/10.1210/clinem/dgac136

Sammad, A., Zhang, H., Shi, R., Dong, Y., Luo, H., Chen, Z., Liu, L., Guo, G., Liu, A. & Wang, Y. (2022). A Post-GWAS Functional Analysis Confirming Effects of Three BTA13 Genes CACNB2, SLC39A12, and ZEB1 on Dairy Cattle Reproduction. Frontiers in Genetics, 13, Article 882951. https://doi.org/10.3389/fgene.2022.882951

Zhang, Q., Zhang, Q. & Jensen, J. (2022). Association Studies and Genomic Prediction for Genetic Improvements in Agriculture. Frontiers in Plant Science, 13, Article 904230. https://doi.org/10.3389/fpls.2022.904230

Slagboom, M., Milkevych, V., Liu, H., Thomasen, J. R., Kargo, M. & Schmidtmann, C. (2022). Conservation of local Red cattle breeds by collaboration with a mainstream Red dairy cattle breed. Livestock Science, 260, Article 104936. https://doi.org/10.1016/j.livsci.2022.104936

Løvendahl, P. & Buitenhuis, A. J. (2022). Genetic and phenotypic variation and consistency in cow preference and circadian use of robotic milking units. Journal of Dairy Science, 105(6), 5283-5295. https://doi.org/10.3168/jds.2021-21593

Poulsen, B. G. (2022). Genetic associations between survival at different parities in commercial crossbred sows.

Eiríksson, J. H., Byskov, K., Su, G., Thomasen, J. R. & Christensen, O. F. (2022). Genomic predictions for crossbred dairy cows by combining solutions from purebred evaluation based on breed origin of alleles. Journal of Dairy Science, 105(6), 5178-5191. https://doi.org/10.3168/jds.2021-21644

Velasco-Galilea, M., Buitenhuis, A. J., Ramayo-Caldas, Y., Ballester, M., Piles, M. & Sanchez, J. P. (2022). GENOMIC REGIONS OF MEAT RABBIT INVOLVED IN THE VARIATION OF ITS CAECAL MICROBIOTA. In 46 Symposium de Cunicultura - Proceedings https://asescu.com/wp-content/uploads/2023/05/Libro-de-Actas_46-Symposium-Cunicultura-2022-1.pdf

Zhang, Q., Schönherz, A. A., Lund, M. S. & Guldbrandtsen, B. (2022). Positive Selection and Adaptive Introgression of Haplotypes from Bos indicus Improve the Modern Bos taurus Cattle. Agriculture (Switzerland), 12(6), Article 844. https://doi.org/10.3390/agriculture12060844

Chu, T. T., Zaalberg, R. M., Jensen, J. & Villumsen, T. M. (2022). Selection for piglet mortality and litter size in outdoor organic pig production systems. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://wcgalp.com/wp-content/uploads/2022/07/e-WCGALP22-programme-booklet.pdf

Manzanilla Pech, C. I. V., Stephansen, R. B., Difford, G., Løvendahl, P. & Lassen, J. (2022). Selecting for feed efficient cows will help to reduce methane gas emissions. Frontiers in Genetics, 13, Article 885932. https://doi.org/10.3389/fgene.2022.885932

Buitenhuis, A. J., Kongsted, H., Villumsen, T. M. & Lund, M. S., (2022). Et resumé af Leverdrejning (lobus sinister lateralis) i grise: Et pilotstudie der undersøger, om der er en simpel genetisk baggrund, No. 2021-0237290, 6 p., May 12, 2022.

Croiseau, P., Saintilan, R., Baur, A., Croue, I., Ducrocq, V., Thomasen, J. R., Karaman, E., Boichard, D., Leclerc, H. & Cuyabano, B. C. D. (2022). Accuracy of prediction for a genomic evaluation in rotational crossbreeding scheme (Montbéliarde x Holstein x Red Danish). In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/02_001.pdf

Goutam, B., Hashimi, M. F., Geem, Z. W. & Bokde, N. (2022). A Comprehensive Review of Deep Learning Strategies in Retinal Disease Diagnosis Using Fundus Images. IEEE Access, 10, 57796-57823. https://doi.org/10.1109/ACCESS.2022.3178372

Hjortø, L., Andersen, T., Kargo, M. & Sørensen, A. C. (2022). Breeding schemes with optimum-contribution selection or truncation selection for beef cattle destined for use on dairy females. Journal of Dairy Science, 105(5), 4314-4323. https://doi.org/10.3168/jds.2021-21258

Chu, T. T., Zaalberg, R. M., Bovbjerg, H., Jensen, J. & Villumsen, T. M. (2022). Genetic variation in piglet mortality in outdoor organic production systems. Animal : an international journal of animal bioscience, 16(5), Article 100529. https://doi.org/10.1016/j.animal.2022.100529

Speed, D., Kaphle, A. & Balding, D. J. (2022). SNP-based heritability and selection analyses: Improved models and new results. BioEssays, 44(5), e2100170. Article 2100170. https://doi.org/10.1002/bies.202100170

Lou, W., Zhang, H., Luo, H., Chen, Z., Shi, R., Guo, X., Zou, Y., Liu, L., Brito, L. F., Guo, G. & Wang, Y. (2022). Genetic analyses of blood β-hydroxybutyrate predicted from milk infrared spectra and its association with longevity and female reproductive traits in Holstein cattle. Journal of Dairy Science, 105(4), 3269-3281. https://doi.org/10.3168/jds.2021-20389

Barre, P., Asp, T., Byrne, S., Casler, M., Faville, M., Rognli, O. A., Roldan-Ruiz, I., Skøt, L. & Ghesquière, M. (2022). Genomic Prediction of Complex Traits in Forage Plants Species: Perennial Grasses Case. In Methods in Molecular Biology (pp. 521-541). Humana Press Inc. https://doi.org/10.1007/978-1-0716-2205-6_19

Bordbar, F., Mohammadabadi, M., Jensen, J., Xu, L., Li, J. & Zhang, L. (2022). Identification of Candidate Genes Regulating Carcass Depth and Hind Leg Circumference in Simmental Beef Cattle Using Illumina Bovine Beadchip and Next-Generation Sequencing Analyses. Animals, 12(9), Article 1103. https://doi.org/10.3390/ani12091103

Chen, C. J., Garrick, D., Fernando, R., Karaman, E., Stricker, C., Keehan, M. & Cheng, H. (2022). XSim Version 2: Simulation of Modern Breeding Programs. G3: Genes, Genomes, Genetics, 12(4), Article jkac032. https://doi.org/10.1093/g3journal/jkac032

Mallawaarachchi, S., Tonkin-Hill, G., Croucher, N. J., Turner, P., Speed, D., Corander, J. & Balding, D. (2022). Genome-wide association, prediction and heritability in bacteria with application to Streptococcus pneumoniae. NAR Genomics & Bioinformatics, 4(1), Article lqac011. https://doi.org/10.1093/nargab/lqac011

Guillenea, A., Su, G., Lund, M. S. & Karaman, E. (2022). Genomic prediction in Nordic Red dairy cattle considering breed origin of alleles. Journal of Dairy Science, 105(3), 2426-2438. https://doi.org/10.3168/jds.2021-21173

Raffo, M. A., Sarup, P., Guo, X., Liu, H., Andersen, J. R., Orabi, J., Jahoor, A. & Jensen, J. (2022). Improvement of genomic prediction in advanced wheat breeding lines by including additive-by-additive epistasis. Theoretical and Applied Genetics, 135(3), 965-978. https://doi.org/10.1007/s00122-021-04009-4

Liu, T., Luo, C., Ma, J., Wang, Y., Shu, D., Qu, H. & Su, G. (2022). Including dominance effects in the prediction model through locus-specific weights on heterozygous genotypes can greatly improve genomic predictive abilities. Heredity, 128(3), 154-158. https://doi.org/10.1038/s41437-022-00504-6

Alemu, S. W., Bijma, P., Calus, M. P. L., Liu, H., Fernando, R. L. & Dekkers, J. C. M. (2022). Comparison of linkage disequilibrium estimated from genotypes versus haplotypes for crossbred populations. Genetics Selection Evolution, 54(1), Article 12. https://doi.org/10.1186/s12711-022-00703-z

Manzanilla Pech, C. I. V., Difford, G., Sahana, G., Rome, H. J. S., Løvendahl, P. & Lassen, J. (2022). Genome-wide association study for methane emission traits in Danish Holstein cattle. Journal of Dairy Science, 105(2), 1357-1368. https://doi.org/10.3168/jds.2021-20410

Mesbah-Uddin, M., Guldbrandtsen, B., Capitan, A., Lund, M. S., Boichard, D. & Sahana, G. (2022). Genome-wide association study with imputed whole-genome sequence variants including large deletions for female fertility in 3 Nordic dairy cattle breeds. Journal of Dairy Science, 105(2), 1298-1313. https://doi.org/10.3168/jds.2021-20655

Zaalberg, R. M., Nielsen, H. M., Sorensen, A. C., Chu, T. T., Jensen, J. & Villumsen, T. M. (2022). The Effect of Using Organic or Conventional Sires on Genetic Gain in Organic Pigs: A Simulation Study. Animals, 12(4), Article 455. https://doi.org/10.3390/ani12040455

Lu, X., Arbab, A. A. I., Abdalla, I. M., Liu, D., Zhang, Z., Xu, T., Su, G. & Yang, Z. (2022). Genetic Parameter Estimation and Genome-Wide Association Study-Based Loci Identification of Milk-Related Traits in Chinese Holstein. Frontiers in Genetics, 12, Article 799664. https://doi.org/10.3389/fgene.2021.799664

Fois, M., Bellucci, A., Malinowska, M., Greve, M., Ruud, A. K. & Asp, T. (2022). Genome-wide association mapping of crown and brown rust resistance in perennial ryegrass. Genes, 13(1), Article 20. https://doi.org/10.3390/genes13010020

Moeskjær, S., Skovbjerg, C. K., Tausen, M., Wind, R., Roulund, N., Janss, L. & Andersen, S. U. (2022). Major effect loci for plant size before onset of nitrogen fixation allow accurate prediction of yield in white clover. Theoretical and Applied Genetics, 135(1), 125-143. https://doi.org/10.1007/s00122-021-03955-3

Clasen, J. B., Fikse, W. F., Su, G. & Karaman, E. (2022). Breed-origin-of-alleles approach using summary statistics for multi-breed genomic prediction in dairy cattle. In WCGALP 2022: Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/25_014.pdf

Raffo, M. A., Sarup, P. M., Andersen, J. R., Orabi, J., Jahoor, A. & Jensen, J. (2022). Genomic prediction for complex traits in wheat: a growth degree-days based reaction norm and multi-trait approach. Abstract from XVIIIth Eucarpia Biometrics in Plant Breeding Conference.

Islam, M. S., Van der Werf, JHJ., Henryon, M., Chu, T. T., Wood, B. J. & Hermesch, S. (2022). Genotyping dead animals improves post-weaning survival of pigs in breeding programs. In WCGALP2022 Programme book Wageningen Academic Publishers. https://wcgalp.com/wp-content/uploads/2022/07/e-WCGALP22-programme-booklet.pdf

Raffo, M. A., Sarup, P. M., Andersen, J. R., Guo, X., Liu, H., Orabi, J., Jahoor, A. & Jensen, J. (2022). Improvement of genomic prediction in advanced wheat breeding lines by including additive-by-additive epistasis. Abstract from Plant and Animal Genome - IWGSC.

Nielsen, B., Horndrup, L. V. & Ask, B. (2022). Modeller for social genetiske effekter hos grise og betydningen for dyrevelfærd. In Symposium i anvendt statistik (pp. 126-128). SEGES Innovation. http://www.statistiksymposium.dk/Symposium%202022_Web.pdf

Clasen, J. B., Nielsen, H. M., Hein, L., Johansen, K., Vestergaard, M. & Kargo, M. (2022). Performance of first parity Holstein, Danish Red and their crosses in an experimental setting. In Book of Abstracts of the 73rd Annual Meeting of the European Federation of Animal Science (EAAP): Book of abstracts No. 28 (2022) (pp. 671). Wageningen Academic Publishers. https://www.eaap2022.org/docs/AbstractBookEAAP.pdf

Poulsen, B. G., Ostersen, T., Nielsen, B. & Christensen, O. F. (2022). Predictive performances of animal models using different multibreed relationship matrices in systems with rotational crossbreeding. Genetics, selection, evolution : GSE, 54, Article 25. https://doi.org/10.1186/s12711-022-00714-w

Thomasen, J. R., Nielsen, H. M., Kargo, M. & Slagboom, M. (2022). Purebred breeding goals optimized for crossbreeding improves crossbred performance. In Book of Abstracts of the 73rd Annual Meeting - EAAp (pp. 598). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-937-4

Kempe, R. M., Mehtiö, T., Leino, A.-M., Koivula, M., Pitkänen, T. J., Stephansen, R. B., Mäntysaari, P., Negussie, E., Pösö, J., Nielsen, U. S., Fikse, W. F., Aamand, G. P. & Lidauer, M. H. (2022). Single-step genomic prediction for metabolic body weight of Nordic Red dairy cattle. In WCGALP 2022: Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/14_005.pdf

Sargent, C., Kosmadopoulos, A., Zhou, X. & Roach, G. D. (2022). Timing of Sleep in the Break Between Two Consecutive Night-Shifts: The Effect of Different Strategies on Daytime Sleep and Night-Time Neurobehavioural Function. Nature and Science of Sleep, 14, 231-242. https://doi.org/10.2147/NSS.S336795

Econogene Consortium, Ajmone-Marsan, P., Bradley, D. G., Colli, L., Drögemüller, C., Lei, C., Mannen, H., Pompanon, F., Tosser-Klopp, G. & Jiang, Y. (2022). Y-chromosomal haplogroups from wild and domestic goats reveal ancient migrations and recent introgressions. In R. F. Veerkamp & Y. de Haas (Eds.), Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP): Technical and species orientated innovations in animal breeding, and contribution of genetics to solving societal challenges (pp. 886-889). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-940-4_208

Zhang, Q., Privé, F., Vilhjálmsson, B. & Speed, D. (2021). Improved genetic prediction of complex traits from individual-level data or summary statistics. Nature Communications, 12(1), Article 4192. https://doi.org/10.1038/s41467-021-24485-y

Pan, Z., Yao, Y., Yin, H., Cai, Z., Wang, Y., Bai, L., Kern, C., Halstead, M., Chanthavixay, G., Trakooljul, N., Wimmers, K., Sahana, G., Su, G., Lund, M. S., Fredholm, M., Karlskov-Mortensen, P., Ernst, C. W., Ross, P., Tuggle, C. K. ... Zhou, H. (2021). Pig genome functional annotation enhances the biological interpretation of complex traits and human disease. Nature Communications, 12(1), Article 5848. https://doi.org/10.1038/s41467-021-26153-7

Eiríksson, J. H., Karaman, E., Su, G. & Christensen, O. F. (2021). Breed of origin of alleles and genomic predictions for crossbred dairy cows. Genetics Selection Evolution, 53(1), Article 84. https://doi.org/10.1186/s12711-021-00678-3

Madsen, M. D., van der Werf, J., Börner, V., Mulder, H. A. & Clark, S. (2021). Estimation of macro- and micro-genetic environmental sensitivity in unbalanced datasets. Animal, 15(12), Article 100411. https://doi.org/10.1016/j.animal.2021.100411

Atrian-Afiani, F., Gao, H., Joezy-Shekalgorabi, S., Madsen, P., Aminafshar, M., Ali, S. & Jensen, J. (2021). Genotype by climate zone interactions for fertility, somatic cell score, and production in Iranian Holsteins. Journal of Dairy Science, 104(12), 12994-13007. https://doi.org/10.3168/jds.2020-20084, https://doi.org/10.3168/jds.2020-20084

Slagboom, M., Sørensen, A. C., Thomasen, J. R., Liu, H., Kargo, M. & Hjortø, L. (2021). Ignoring genotype by environment interaction in the genetic evaluation of dairy cattle reduces accuracy but may increase selection intensity. Journal of Dairy Science, 104(12), 12756-12764. https://doi.org/10.3168/jds.2021-20876

Zhao, Q., Liu, H., Qadri, Q. R., Wang, Q., Pan, Y. & Su, G. (2021). Long-term impact of conventional and optimal contribution conservation methods on genetic diversity and genetic gain in local pig breeds. Heredity, 127(6), 546-553. https://doi.org/10.1038/s41437-021-00484-z

Poulsen, N. A., Sundekilde, U. K., Lindahl, E. I., Buitenhuis, A. J. & Larsen, L. B. (2021). Milk Genomics: Variation in milk composition in major Danish dairy breeds and exploitation in dairy products. DCA - Nationalt Center for Fødevarer og Jordbrug. DCA Report No. 194 https://dcapub.au.dk/djfpublikation/index.asp?action=show&id=1479

Washburn, J. D., Cimen, E., Ramstein, G., Reeves, T., O’Briant, P., McLean, G., Cooper, M., Hammer, G. & Buckler, E. S. (2021). Predicting phenotypes from genetic, environment, management, and historical data using CNNs. Theoretical and Applied Genetics, 134(12), 3997-4011. https://doi.org/10.1007/s00122-021-03943-7

Salimiyekta, Y., Vaez‐torshizi, R., Abbasi, M. A., Emmamjome‐kashan, N., Amin‐afshar, M., Guo, X. & Jensen, J. (2021). Random regression model for genetic evaluation and early selection in the iranian holstein population. Animals, 11(12), Article 3492. https://doi.org/10.3390/ani11123492

Fu, C., Ostersen, T., Christensen, O. F. & Xiang, T. (2021). Single-step genomic evaluation with metafounders for feed conversion ratio and average daily gain in Danish Landrace and Yorkshire pigs. Genetics Selection Evolution, 53(1), 79. Article 79. https://doi.org/10.1186/s12711-021-00670-x

Chu, T. T., Henryon, M., Jensen, J., Ask, B. & Christensen, O. F. (2021). Statistical model and testing designs to increase response to selection with constrained inbreeding in genomic breeding programs for pigs affected by social genetic effects. Genetics Selection Evolution, 53(1), Article 1. https://doi.org/10.1186/s12711-020-00598-8

Ahmad, S., Drag, M. H., Salleh, S. M., Cai, Z. & Nielsen, M. O. (2021). Transcriptomics analysis of differentially expressed genes in subcutaneous and perirenal adipose tissue of sheep as affected by their pre- and early postnatal malnutrition histories. BMC Genomics, 22(1), Article 338. https://doi.org/10.1186/s12864-021-07672-5

Hartfield, M., Poulsen, N. A., Guldbrandtsen, B. & Bataillon, T. (2021). Using singleton densities to detect recent selection in Bos taurus. Evolution Letters, 5(6), 595-606. https://doi.org/10.1002/evl3.263

Bauer, M., Glenn, T., Achtyes, E. D., Alda, M., Agaoglu, E., Altınbaş, K., Andreassen, O. A., Angelopoulos, E., Ardau, R., Vares, E. A., Aydin, M., Ayhan, Y., Baethge, C., Bauer, R., Baune, B. T., Balaban, C., Becerra-Palars, C., Behere, A. P., Behere, P. B. ... Whybrow, P. C. (2021). Variations in seasonal solar insolation are associated with a history of suicide attempts in bipolar I disorder. International Journal of Bipolar Disorders, 9(1), Article 26. https://doi.org/10.1186/s40345-021-00231-7

Bellamy, K. K. L., Lingaas, F. & Madsen, P. (2021). Heritability of distichiasis in Havanese dogs in Norway. Canine medicine and genetics, 8(1), Article 11. https://doi.org/10.1186/s40575-021-00110-5

Jefsen, O. H., Speed, M., Speed, D. & Østergaard, S. D. (2021). Bipolar disorder and cannabis use: A bidirectional two-sample Mendelian randomization study. Addiction Biology, 26(6), Article 13030. https://doi.org/10.1111/adb.13030

Stephansen, R. B., Lassen, J., Ettema, J. F., Sørensen, L. P. & Kargo, M. (2021). Economic value of residual feed intake in dairy cattle breeding goals. Livestock Science, 253, Article 104696. https://doi.org/10.1016/j.livsci.2021.104696

Manzanilla Pech, C. I. V., Stephansen, R. B. & Lassen, J. (2021). Genetic parameters for feed efficiency using 3D cameras in jersey cows in commercial Danish farms. In Proceedings of the Association for the Advancement of Animal Breeding and Genetics (pp. 226-229). Association for the Advancement of Animal Breeding and Genetics. http://www.aaabg.org/aaabghome/AAABG24papers/57Pech24226.pdf

Hao, D., Bai, J., Du, J., Wu, X., Thomsen, B., Gao, H., Su, G. & Wang, X. (2021). Overview of metabolomic analysis and the integration with multi-omics for economic traits in cattle. Metabolites, 11(11), Article 753. https://doi.org/10.3390/metabo11110753

Giri, A., Khaipho-Burch, M., Buckler, E. S. & Ramstein, G. (2021). Haplotype associated RNA expression (HARE) improves prediction of complex traits in maize. PLOS Genetics, 17(10), Article e1009568.

Christensen, O. F., Börner, V., Varona, L. & Legarra, A. (2021). Genetic evaluation including intermediate omics features. Genetics, 219(2), Article iyab130. https://doi.org/10.1093/genetics/iyab130

Kramer, L. M., Wolc, A., Esfandyari, H., Thekkoot, D. M., Zhang, C., Kemp, R. A., Plastow, G. & Dekkers, J. C. M. (2021). Purebred-crossbred genetic parameters for reproductive traits in swine. Journal of Animal Science, 99(10), Article skab270. https://doi.org/10.1093/jas/skab270

Rohde, P. D., Nyegaard, M., Kjolby, M. & Sørensen, P. (2021). Multi-Trait Genomic Risk Stratification for Type 2 Diabetes. Frontiers in Medicine, 8, Article 711208. https://doi.org/10.3389/fmed.2021.711208

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