Publications

Peer-reviewed publications at QGG

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Vardhan, B. V. S., Khedkar, M., Srivastava, I., Thakre, P. & Bokde, N. D. (2023). A Comparative Analysis of Hyperparameter Tuned Stochastic Short Term Load Forecasting for Power System Operator. Energies, 16(3), [1243]. https://doi.org/10.3390/en16031243

Si, J., Dai, D., Li, K., Fang, L. & Zhang, Y. (2023). A Multi-Tissue Gene Expression Atlas of Water Buffalo (Bubalus bubalis) Reveals Transcriptome Conservation between Buffalo and Cattle. Genes, 14(4). https://doi.org/10.3390/genes14040890

Guillenea, A., Lund, M. S., Evans, R., Boerner, V. & Karaman, E. (2023). A breed-of-origin of alleles model that includes crossbred data improves predictive ability for crossbred animals in a multi-breed population. Genetics, selection, evolution : GSE, 55(1), 34. https://doi.org/10.1186/s12711-023-00806-1

Salimiyekta, Y., Jensen, J., Su, G. & Gebreyesus, G. (2023). Age-dependent genetic and environmental variance of semen quality in Nordic Holstein bulls. Journal of Dairy Science, 106(4), 2598-2612. https://doi.org/10.3168/jds.2022-22442

Sahu, S. K., Mokhade, A. & Bokde, N. D. (2023). An Overview of Machine Learning, Deep Learning, and Reinforcement Learning-Based Techniques in Quantitative Finance: Recent Progress and Challenges. Applied Sciences (Switzerland), 13(3), [1956]. https://doi.org/10.3390/app13031956

Hein, L. & Kargo, M., (2023). Analyse af anvendelse af Blåkvægssæd i økologisk produktion, No. 2021-0244490, 58 p., Feb 09, 2023.

Tiwari, S., Sengupta, J. & Bokde, N. D. (2023). Analysis of Individual User Data Rate in a TDMA-RIS-NOMA Downlink System: Beyond the Limitation of Conventional NOMA. Electronics (Switzerland), 12(3), [618]. https://doi.org/10.3390/electronics12030618

Yousaf, M. F., Zia, M. A. B. & Naeem, M. (2023). Application of SolCAP Genotyping in Potato (Solanum tuberosum L.) Association Mapping. In Y. Shavrukov (Ed.), Plant Genotyping (pp. 415-435). Humana Press. Methods in Molecular Biology Vol. 2638 https://doi.org/10.1007/978-1-0716-3024-2_30

Therkildsen, M., Vestergaard, M., Kargo, M., Keto, L., Ertbjerg, P., Thorkelsson, G., Gudjónsdóttir, M., Kjetså, M., Honkatukia, M., Egelandsdal, B., Svartedal, N., Røe, M., Fikse, F. W., Karlssom, A. H. & Hessle, A. (2023). Carcass characteristics of Nordic native cattle breeds. Genetic Resources, 4(7), 1-19. https://doi.org/10.46265/genresj.LWUP7415

Khaipho-Burch, M., Ferebee, T., Giri, A., Ramstein, G., Monier, B., Yi, E., Cinta Romay, M. & Buckler, E. S. (2023). Elucidating the patterns of pleiotropy and its biological relevance in maize. PLOS Genetics, 19(3), [e1010664]. https://doi.org/10.1371/journal.pgen.1010664

Gebreyesus, G., Cheruiyot Bett , R., Nkirote Kunyanga , C., MBI Tanga, C., Nakimbugwe, D., Khamis, F., Kinyua, J., Muchina, K., Roos, N., Walusimbi, S., Geoffrey, S. & Sahana, G. (2023, Jan). FLYgene - Stakeholders’ workshop report in WP1. Center for Kvantitativ genetik og genomforskning (QGG), Aarhus Universitet.

Rohner, M., Manzanares, C., Yates, S., Thorogood, D., Copetti, D., Lübberstedt, T., Asp, T. & Studer, B. (2023). Fine-Mapping and Comparative Genomic Analysis Reveal the Gene Composition at the S and Z Self-incompatibility Loci in Grasses. Molecular Biology and Evolution, 40(1). https://doi.org/10.1093/molbev/msac259

Raffo, M. A. & Jensen, J. (2023). Gene × gene and genotype × environment interactions in wheat. Crop Science. https://doi.org/10.1002/csc2.20986

Raffo, M. A. (2023). Gene-by-gene and genotype-by-environment interactions in wheat. Aarhus Universitet.

Skovbjerg, C. K., Angra, D., Robertson-Shersby-Harvie, T., Kreplak, J., Keeble-Gagnère, G., Kaur, S., Ecke, W., Windhorst, A., Nielsen, L. K., Schiemann, A., Knudsen, J., Gutierrez, N., Tagkouli, V., Fechete, L. I., Janss, L., Stougaard, J., Warsame, A., Alves, S., Khazaei, H. ... Andersen, S. U. (2023). Genetic analysis of global faba bean diversity, agronomic traits and selection signatures. Theoretical and Applied Genetics, 136(5), [114]. https://doi.org/10.1007/s00122-023-04360-8

Bornhofen, E., Fé, D., Nagy, I., Lenk, I., Greve, M., Didion, T., Jensen, C. S., Asp, T. & Janss, L. (2023). Genetic architecture of inter-specific and -generic grass hybrids by network analysis on multi-omics data. BMC Genomics, 24(1), [213]. https://doi.org/10.1186/s12864-023-09292-7

Byg, L. M., Speed, M., Speed, D. & Østergaard, S. D. (2023). Genetic liability to bipolar disorder and body mass index: A bidirectional two-sample mendelian randomization study. Bipolar Disorders, 25(1), 25-31. https://doi.org/10.1111/bdi.13267

Zaalberg, R. M., Chu, T. T., Bovbjerg, H., Jensen, J. & Villumsen, T. M. (2023). Genetic parameters for early piglet weight, litter traits and number of functional teats in organic pigs. Animal, 17(3), [100717]. https://doi.org/10.1016/j.animal.2023.100717

Mei, Q., Liu, H., Zhao, S., Xiang, T. & Christensen, O. F. (2023). Genomic evaluation for two-way crossbred performance in cattle. Genetics Selection Evolution, 55(1), [17]. https://doi.org/10.1186/s12711-023-00792-4

Legarra, A. & Christensen, O. F. (2023). Genomic evaluation methods to include intermediate correlated features such as high-throughput or omics phenotypes. JDS Communications , 4(1), 55-60. https://doi.org/10.3168/jdsc.2022-0276

Guillenea, A. (2023). Genomic prediction and QTL mapping in multi-breed and crossbred cattle populations considering breed origin of the alleles. Aarhus Universitet.

Raffo, M. A., Cuyabano, B. C. D., Rincent, R., Sarup, P., Moreau, L., Mary-Huard, T. & Jensen, J. (2023). Genomic prediction for grain yield and micro-environmental sensitivity in winter wheat. Frontiers in Plant Science, 13, [1075077]. https://doi.org/10.3389/fpls.2022.1075077

Ahuja, B., Doriya, R., Salunke, S., Hashmi, M. F., Gupta, A. & Bokde, N. D. (2023). HDIEA: high dimensional color image encryption architecture using five-dimensional Gauss-logistic and Lorenz system. Connection Science, 35(1), [2175792]. https://doi.org/10.1080/09540091.2023.2175792

Zhang, Z., Shi, S., Zhang, Q., Aamand, G. P., Lund, M. S., Su, G. & Ding, X. (2023). Improving Genomic Prediction Accuracy in the Chinese Holstein Population by Combining with the Nordic Holstein Reference Population. Animals, 13(4), [636]. https://doi.org/10.3390/ani13040636

Lund, P., Børsting, C. F., Albrektsen, R., Nielsen, O-K. & Villumsen, T. M., (2023). Input til udledningspostnotat om malkekvægs fordøjelse, No. 2023-0504452, 10 p., May 01, 2023.

Boerner, V., Nguyen, T. T. T. & Nieuwhof, G. J. (2023). Integration of Interbull's multiple across-country evaluation approach breeding values into the multiple-trait single-step random regression test-day genetic evaluation for yield traits of Australian Red breeds. Journal of Dairy Science, 106(2), 1159-1167. https://doi.org/10.3168/jds.2022-21816

Berrandou, T-E., Balding, D. & Speed, D. (2023). LDAK-GBAT: Fast and powerful gene-based association testing using summary statistics. American Journal of Human Genetics, 110(1), 23-29. https://doi.org/10.1016/j.ajhg.2022.11.010

Sahana, J., Cortés-Sánchez, J. L., Sandt, V., Melnik, D., Corydon, T. J., Schulz, H., Cai, Z., Evert, K., Grimm, D. & Wehland, M. (2023). Long-Term Simulation of Microgravity Induces Changes in Gene Expression in Breast Cancer Cells. International Journal of Molecular Sciences , 24(2), [1181]. https://doi.org/10.3390/ijms24021181

Jiang, Y. F., Wang, S., Wang, C. L., Xu, R. H., Wang, W. W., Jiang, Y., Wang, M. S., Jiang, L., Dai, L. H., Wang, J. R., Chu, X. H., Zeng, Y. Q., Fang, L. Z., Wu, D. D., Zhang, Q. & Ding, X. D. (2023). Pangenome obtained by long-read sequencing of 11 genomes reveal hidden functional structural variants in pigs. iScience, 26(3), [106119]. https://doi.org/10.1016/j.isci.2023.106119

Salunke, S., Shrivastava, A. K., Hashmi, M. F., Ahuja, B. & Bokde, N. D. (2023). Quad Key-Secured 3D Gauss Encryption Compression System with Lyapunov Exponent Validation for Digital Images. Applied Sciences (Switzerland), 13(3), [1616]. https://doi.org/10.3390/app13031616

Gebreyesus, G., Milkevych, V., Lassen, J. & Sahana, G. (2023). Supervised learning techniques for dairy cattle body weight prediction from 3D digital images. Frontiers in Genetics. https://doi.org/10.3389/fgene.2022.947176

Christensen, B., Buitenhuis, A. J., Jacobsen, L. N., Ostenfeld, M. S. & Sørensen, E. S. (2023). The Effect of Human and Bovine Milk Osteopontin on Intestinal Caco-2 Cells: A Transcriptome Comparison. Nutrients, 15(5). https://doi.org/10.3390/nu15051166

Jayakodi, M., Golicz, A. A., Kreplak, J., Fechete, L. I., Angra, D., Bednář, P., Bornhofen, E., Zhang, H., Boussageon, R., Kaur, S., Cheung, K., Čížková, J., Gundlach, H., Hallab, A., Imbert, B., Keeble-Gagnère, G., Koblížková, A., Kobrlová, L., Krejčí, P. ... Andersen, S. U. (2023). The giant diploid faba genome unlocks variation in a global protein crop. Nature, 615(7953), 652-659. https://doi.org/10.1038/s41586-023-05791-5

Liu, T., Nielsen, B., Christensen, O. F., Lund, M. S. & Su, G. (2023). The impact of genotyping strategies and statistical models on accuracy of genomic prediction for survival in pigs. Journal of Animal Science and Biotechnology, 14(1), [1]. https://doi.org/10.1186/s40104-022-00800-5

Christensen, B. S., Buitenhuis, A. J., Jacobsen, L. N., S. Ostenfeld, M. & Sørensen, E. S. (2023). Transcriptome comparison of Intestinal Caco-2 cells in response to Human and Bovine Milk Osteopontin. Nutrients. https://doi.org/10.3390/nu15051166

Long, E. M., Romay, M. C., Ramstein, G., Buckler, E. S. & Robbins, K. R. (2023). Utilizing evolutionary conservation to detect deleterious mutations and improve genomic prediction in cassava. Frontiers in Plant Science, 13, [1041925]. https://doi.org/10.3389/fpls.2022.1041925

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), [5321]. https://doi.org/10.3390/app12115321

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

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, [882951]. https://doi.org/10.3389/fgene.2022.882951

Sawant, M., Patil, R., Shikhare, T., Nagle, S., Chavan, S., Negi, S. & Bokde, N. D. (2022). A Selective Review on Recent Advancements in Long, Short and Ultra-Short-Term Wind Power Prediction. Energies, 15(21), [8107]. https://doi.org/10.3390/en15218107

Liu, S., Gao, Y., Canela-Xandri, O., Wang, S., Yu, Y., Cai, W., Li, B., Xiang, R., Chamberlain, A. J., Pairo-Castineira, E., D'Mellow, K., Rawlik, K., Xia, C., Yao, Y., Navarro, P., Rocha, D., Li, X., Yan, Z., Li, C. ... Fang, L. (2022). A multi-tissue atlas of regulatory variants in cattle. Nature Genetics, 54(9), 1438-1447. https://doi.org/10.1038/s41588-022-01153-5

Dahl, M. & Christensen, O. F. (2022). A phasing algorithm targeted at dairy cattle populations having genotyped ancestors with many genotyped offspring. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/30_006.pdf

Gredler-Grandl, B., Raymond, B., Schopen, G. C. B., Chitneedi, P. K., Cai, Z., Manzanilla Pech, C. I. V., Iso-Touru, T., Fischer, D., Bolormaa, S., Chud, T. C. S., Schenkel, F. S., Wang, Y., Li, C., Hailemariam, D., Villanueva, B., Fernandez, A., Kuehn, C., Sahana, G., Lidauer, M. ... Bouwman, A. C. (2022). Accuracy of genomic prediction of dry matter intake in Dutch Holsteins using sequence variants from meta-analyses. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/02_010.pdf

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

Saintilan, R., Croiseau, P., 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 Proceedings of the 2022 Interbull Meeting (pp. 18-22). Interbull Bulletin Vol. 57 https://journal.interbull.org/index.php/ib

Khare, S. K., Gaikwad, N. & Bokde, N. D. (2022). An Intelligent Motor Imagery Detection System Using Electroencephalography with Adaptive Wavelets. Sensors (Switzerland), 22(21), [8128]. https://doi.org/10.3390/s22218128

Marašinskienė, Š., Šveistienė, R., Kosińska-Selbi, B., Schmidtmann, C., Ettema, J. F., Juškienė, V. & Kargo, M. (2022). Application of a Bio-Economic Model to Demonstrate the Importance of Health Traits in Herd Management of Lithuanian Dairy Breeds. Animals, 12(15), [1926]. https://doi.org/10.3390/ani12151926

Kotlarz, K., Kosinska-Selbi, B., Cai, Z., Sahana, G. & Szyda, J. (2022). Application of mixed linear models for the estimation of functional effects on bovine stature based on SNP summary statistics from a whole-genome association study. Genetics Selection Evolution, 54, [80]. https://doi.org/10.1186/s12711-022-00771-1

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

Berrandou, T. E. & Bouatia-Naji, N. (2022). Base polygénique de la dysplasie fibromusculaire artérielle. Medecine sciences : M/S, 38(11), 870-873. https://doi.org/10.1051/medsci/2022134

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

Henryon, M., Ostersen, T., Guo, X., Su, G. & Sørensen, A. C. (2022). Breeding for component traits of litter size at day 5 increases piglet survival while maintaining litter size at day 5. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/68_016.pdf

Manzanilla Pech, C. I. V., Stephansen, R. B. & Lassen, J. (2022). Breeding for feed efficient and low methane-emitting dairy cows is feasible. Abstract from 73 Annual Meeting of the European Federation of Animal Science, Porto, Portugal.

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

Gebreyesus, G., Secher, J. B-M., Lund, M. S., Kupisiewicz, K., Ivask, M. & Su, G. (2022). Bull effects on in vitro embryo production quality traits are repeatable and heritable. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/21_004.pdf

Nagy, I., Veeckman, E., Liu, C., Bel, M. V., Vandepoele, K., Jensen, C. S., Ruttink, T. & Asp, T. (2022). Chromosome-scale assembly and annotation of the perennial ryegrass genome. BMC Genomics, 23(1), [505]. https://doi.org/10.1186/s12864-022-08697-0

Chen, S., Liu, S., Shi, S., Jiang, Y., Cao, M., Tang, Y., Li, W., Liu, J., Fang, L., Yu, Y. & Zhang, S. (2022). Comparative epigenomics reveals the impact of ruminant-specific regulatory elements on complex traits. BMC Biology, 20, 273. https://doi.org/10.1186/s12915-022-01459-0

Yang, W., Yu, J., Yao, Y., Chen, S., Zhao, B., Liu, S., Zhou, L., Fang, L. & Liu, J. (2022). Comparative immune-relevant transcriptome reveals the evolutionary basis of complex traits. iScience, 25(12), [105572]. https://doi.org/10.1016/j.isci.2022.105572

Yao, Y., Liu, S., Xia, C., Gao, Y., Pan, Z., Canela-Xandri, O., Khamseh, A., Rawlik, K., Wang, S., Li, B., Zhang, Y., Pairo-Castineira, E., D’Mellow, K., Li, X., Yan, Z., Li, C. J., Yu, Y., Zhang, S., Ma, L. ... Tenesa, A. (2022). Comparative transcriptome in large-scale human and cattle populations. Genome Biology, 23(1), [176]. https://doi.org/10.1186/s13059-022-02745-4

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), [12]. https://doi.org/10.1186/s12711-022-00703-z

Nielsen, H. M. & Kargo, M. (2022). Conservation of an endangered pig breed using optimum contribution selection. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/72_007.pdf

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, [104936]. https://doi.org/10.1016/j.livsci.2022.104936

Bouquet, A. E. R., Slagboom, M., Thomasen, J. R., Friggens, N., Kargo, M. & Puillet, L. (2022). Coupling genetic and mechanistic models to benchmark selection strategies for feed efficiency in dairy cows: sensitivity analysis validating this novel approach. Animal - Open Space, 1(1), [100017]. https://doi.org/10.1016/j.anopes.2022.100017

Milkevych, V., Michelle Villumsen, T., Løvendahl, P. & Sahana, G. (2022). Data synchronization for gas emission measurements from dairy cattle: A matched filter approach. Computers and Electronics in Agriculture, 201, [107299]. https://doi.org/10.1016/j.compag.2022.107299

Olesen, I., Kettunen, A., Rosendal, G. K. & Nielsen, H. M. (2022). Defining animal breeding objectives and strategies within the framework of responsible research and innovation (RRI). In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/62_005.pdf

Zaalberg, R. M., Villumsen, T. M., Jensen, J. & Chu, T. T. (2022). Effective Selection for Lower Mortality in Organic Pigs through Selection for Total Number Born and Number of Dead Piglets. Animals, 12(14), [1796]. https://doi.org/10.3390/ani12141796

Bengtsson, C., Thomasen, J. R., Kargo, M., Bouquet, A. & Slagboom, M. (2022). Emphasis on resilience in dairy cattle breeding: Possibilities and consequences. Journal of Dairy Science, 105(9), 7588-7599. https://doi.org/10.3168/jds.2021-21049

Rome, H. J. S., Chu, T. T., Marois, D., Huang, C-H., Madsen, P. & Jensen, J. (2022). Estimating environmental direct-maternal covariance in real data – illustration on broilers. In WCGALP 2022 Programme Book Wageningen Academic Publishers. https://wcgalp.com/wp-content/uploads/2022/07/e-WCGALP22-programme-booklet.pdf

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.

Martinez Boggio, G., Meynadier, A., Rupp, R., Allain, C., Buitenhuis, A. J. & Marie-Etancelin, C. (2022). Evidence of genetic links between rumen bacteria and milk somatic cell score in Lacaune dairy sheep. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/66_004.pdf

Su, G., Liu, T., Christensen, O. F., Lund, M. S. & Nielsen, B. (2022). Feasibility of reducing mortality of pigs from birth to slaughter by genetic selection. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/68_009.pdf

Cai, Z., Wu, X., Thomsen, B. & Sahana, G. (2022). Fine-mapping young-stock survival QTL on chromosome 6 in Nordic Red Dairy Cattle. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/66_006.pdf

Manzanilla Pech, C. I. V., Difford, G., Stephansen, R. B., Løvendahl, P. & Lassen, J. (2022). Genetic (co-)variation of methane emissions, efficiency and production traits in Danish Holstein cattle along and across lactations. Journal of Dairy Science, 105(12), 9799-9809. https://doi.org/10.3168/jds.2022-22121

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, [799664]. https://doi.org/10.3389/fgene.2021.799664

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

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

Løvendahl, P. & Buitenhuis, A. J. (2022). Genetic and phenotypic variation and consistency of cow’s preference and circadian use of robotic milking units. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/32_007.pdf

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

Zhang, H., Wang, K., An, T., Zhu, L., Chang, Y., Lou, W., Liu, L., Guo, G., Liu, A., Su, G., Brito, L. F. & Wang, Y. (2022). Genetic parameters for dairy calf and replacement heifer wellness traits and their association with cow longevity and health indicators in Holstein cattle. Journal of Dairy Science, 105(8), 6749-6759. https://doi.org/10.3168/jds.2021-21450

Manzanilla Pech, C. I. V., Stephansen, R. B., Andersen, T. & Lassen, J. (2022). Genetic parameters for residual feed efficiency in three dairy cattle breeds in commercial farms using 3D cameras. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/57_011.pdf

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), [100529]. https://doi.org/10.1016/j.animal.2022.100529

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), [20]. https://doi.org/10.3390/genes13010020

Dharmateja, P., Yadav, R., Kumar, M., Babu, P., Jain, N., Mandal, P. K., Pandey, R., Shrivastava, M., Gaikwad, K. B., Bainsla, N. K., Tomar, V., Sugumar, S., Saifi, N. & Ranjan, R. (2022). Genome-wide association studies reveal putative QTLs for physiological traits under contrasting phosphorous conditions in wheat (Triticum aestivum L.). Frontiers in Genetics, 13, [984720]. https://doi.org/10.3389/fgene.2022.984720

Wang, B., Li, P., Hou, L., Zhou, W., Tao, W., Liu, C., Liu, K., Niu, P., Zhang, Z., Li, Q., Su, G. & Huang, R. (2022). Genome-wide association study and genomic prediction for intramuscular fat content in Suhuai pigs using imputed whole-genome sequencing data. Evolutionary Applications, 15(12), 2054-2066. https://doi.org/10.1111/eva.13496

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

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 and bioinformatics, 4(1), [lqac011]. https://doi.org/10.1093/nargab/lqac011

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. Methods in Molecular Biology Vol. 2467 https://doi.org/10.1007/978-1-0716-2205-6_19

Fang, F., Li, J., Guo, M., Mei, Q., Yu, M., Liu, H., Legarra, A. & Xiang, T. (2022). Genomic evaluation and genome-wide association studies for total number of teats in a combined American and Danish Yorkshire pig populations selected in China. Journal of Animal Science, 100(7), [skac174]. https://doi.org/10.1093/jas/skac174

Mei, Q., Liu, H., Xiang, T. & Christensen, O. F. (2022). Genomic evaluation for two-way crossbred performance in cattle. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/02_002.pdf

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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

Guillenea, A., Lund, M. S., Evans, R. D., Börner, V. & Karaman, E. (2022). Genomic prediction in multi-breed Irish beef cattle population using a breed origin of alleles model. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/25_013.pdf

Guillenea, A., Su, G., Lund, M. S. & Karaman, E. (2022). Genomic prediction using breed origin of alleles model accounting for probabilities in the assignment of the alleles. In WCGALP 2022 Programme book Wageningen Academic Publishers. https://www.wageningenacademic.com/pb-assets/wagen/WCGALP2022/43_004.pdf

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Gautason, E. (2022). Genomic selection and inbreeding management in a small dairy cattle population. Aarhus Universitet.

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