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
Raffo, M. A., Sarup, P., Andersen, J. R., Orabi, J., Jahoor, A.
& Jensen, J. (2022).
Integrating a growth degree-days based reaction norm methodology and multi-trait modeling for genomic prediction in wheat.
Frontiers in Plant Science,
13, Article 939448.
https://doi.org/10.3389/fpls.2022.939448
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
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), Article 505.
https://doi.org/10.1186/s12864-022-08697-0
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
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
Martinez Boggio, G., Meynadier, A.
, Buitenhuis, A. J. & Marie-Etancelin, C. (2022).
Host genetic control on rumen microbiota and its impact on dairy traits in sheep.
Genetics, selection, evolution : GSE,
54(1), Article 77.
https://doi.org/10.1186/s12711-022-00769-9
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), Article 1926.
https://doi.org/10.3390/ani12151926
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
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
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
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
Malinowska, M., Ruud, A. K., Jensen, J., Svane, S. F., Smith, A. G.
, Bellucci, A., Lenk, I.
, Nagy, I., Fois, M., Didion, T., Thorup-Kristensen, K., Jensen, C. S.
& Asp, T. (2022).
Relative importance of genotype, gene expression, and DNA methylation on complex traits in perennial ryegrass.
The Plant Genome,
15(4), Article e20253.
https://doi.org/10.1002/tpg2.20253
Lund, P., Hojberg, O., Børsting, C. F., Nielsen, M. O., Villumsen, T. M. & Weisbjerg, M. R. (2022).
Muligheder for at begrænse metan fra drøvtyggere.
Vand & Jord, (3), 93-95.
http://vand-og-jord.dk/
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
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
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
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
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, Article 80.
https://doi.org/10.1186/s12711-022-00771-1
Kingsley, N. B., Sandmeyer, L., Norton, E. M.
, Speed, D., Dwyer, A., Lassaline, M., McCue, M. & Bellone, R. R. (2022).
Heritability of insidious uveitis in Appaloosa horses.
Animal Genetics,
53(6), 872-877.
https://doi.org/10.1111/age.13267
Hansen, P. B., Ruud, A. K., de Los Campos, G.
, Malinowska, M., Nagy, I., Svane, S. F., Thorup-Kristensen, K., Jensen, J. D., Krusell, L.
& Asp, T. (2022).
Integration of DNA Methylation and Transcriptome Data Improves Complex Trait Prediction in Hordeum vulgare.
Plants,
11(17), Article 2190.
https://doi.org/10.3390/plants11172190
Grace, C. A., Sousa Carvalho, K. S., Sousa Lima, M. I., Costa Silva, V., Reis-Cunha, J. L., Brune, M. J., Forrester, S., Pedrozo E Silva de Azevedo, C. D. M., Costa, D. L.
, Speed, D., Mottram, J. C., Jeffares, D. C. & Costa, C. H. N. (2022).
Parasite Genotype Is a Major Predictor of Mortality from Visceral Leishmaniasis.
mBio,
13(6), e0206822.
https://doi.org/10.1128/mbio.02068-22
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
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), Article skac174.
https://doi.org/10.1093/jas/skac174
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
Eiríksson, J. H., Strandén, I.
, Su, G., Mäntysaari, E. A.
& Christensen, O. F. (2022).
Local breed proportions and local breed heterozygosity in genomic predictions for crossbred dairy cows.
Journal of Dairy Science,
105(12), 9822-9836.
https://doi.org/10.3168/jds.2022-22225
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, Article 984720.
https://doi.org/10.3389/fgene.2022.984720
Consortium, V. G., Nijman, I. J., Rosen, B. D., Bardou, P., Faraut, T., Cumer, T., Daly, K. G., Zheng, Z., Cai, Y., Asadollahpour, H., Kul, B. Ç., Zhang, W.-Y., Guangxin, E., Ayin, A., Baird, H., Bakhtin, M., Bâlteanu, V. A., Barfield, D., Berger, B. ... Lenstra, J. A. (2022).
Geographical contrasts of Y-chromosomal haplogroups from wild and domestic goats reveal ancient migrations and recent introgressions.
Molecular Ecology,
31(16), 4364-4380.
https://doi.org/10.1111/mec.16579
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
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(1), 273. Article 273.
https://doi.org/10.1186/s12915-022-01459-0
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
Cai, Z., Christensen, O. F., Lund, M. S., Ostersen, T.
& Sahana, G. (2022).
Large-scale association study on daily weight gain in pigs reveals overlap of genetic factors for growth in humans.
BMC Genomics,
23, Article 133.
https://doi.org/10.1186/s12864-022-08373-3
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), Article 100017.
https://doi.org/10.1016/j.anopes.2022.100017
Bornhofen, E., Fè, D., Lenk, I., Greve, M., Didion, T., Jensen, C. S.
, Asp, T. & Janss, L. (2022).
Leveraging spatiotemporal genomic breeding value estimates of dry matter yield and herbage quality in ryegrass via random regression models.
The Plant Genome,
15(4), Article e20255.
https://doi.org/10.1002/tpg2.20255
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
Bolormaa, S., MacLeod, I. M., Khansefid, M., Marret, L., Wales, B., Miglior, F., Baes, C. F., Schenkel, F. S., Connor, E. E.
, Manzanilla Pech, C. I. V., Coffey, M., Stothard, P., Herman, E., Nieuwhof, G. J., Goddard, M. E. & Pryce, J. (2022).
Sharing of either phenotypes or genetic variants can increase the accuracy of genomic prediction of feed efficiency.
Genetics Selection Evolution,
54(1), Article 60.
https://doi.org/10.1186/s12711-022-00749-z
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
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
Laursen, S. F.
, Hansen, L. S., Bahrndorff, S.
, Nielsen, H. M., Noer, N. K., Renault, D.
, Sahana, G., Sørensen, J. G. & Kristensen, T. N. (2021).
Data on: contrasting manual and automated assessment of larval body size and thermal stress responses in black soldier flies and houseflies. Dataset, Dryad Digital Repository.
https://doi.org/10.5061/dryad.cjsxksn5p
Olesen, J. E., Ingvartsen, K. L., Williams, M. H., Hertel, O., Jacobsen, C. S., Lund, M. S., Bach, H. & Halberg, N. (2021).
Besparelser rammer grøn forskning på Aarhus Universitet: Er politikerne overhovedet klar over konsekvenserne? Altinget.
https://www.altinget.dk/forskning/artikel/forskere-nedskaeringer-i-forskningskapacitet-koster-paa-den-groenne-omstilling
Eiríksson, J. H., Byskov, K., Thomassen, J. R.
, Su, G. & Christensen, O. F. (2021).
Genomic predictions of crossbred dairy cows based on breed of origin of alleles. 520-520. Abstract from 72nd Annual Meeting of the European Federation of Animal Science, Davos, Switzerland.
Olijhoek, D., Hellwing, A. L. F., Lund, P., Weisbjerg, M. R., Løvendahl, P. & Børsting, C. F. (2021).
Enteric methane emission of Holstein and Jersey dairy cows at high dietary concentrate proportions. Poster session presented at Meeting in iClimate.
Johansen, K., Hein, L., Spleth, P.
, Vestergaard, M., Nielsen, H. M. & Kargo, M. (2021).
Comparing growth and feed intake in pure- and crossbred heifers fed different energy concentrations. In E. Strandberg, L. Pinotti, S. Messori, D. Kenny, M. Lee, J. F. Hocquette, V. A. P. Cadavez, S. Millet, R. Evans, T. Veldkamp, M. Pastell & G. Pollott (Eds.),
Book of Abstracts of the 72nd Annual Meeting of the European Federation of Animal Science (pp. 521). Wageningen Academic Publishers.
https://doi.org/10.3920/978-90-8686-918-3
Stephansen, R. B., Lidauer, M., Nielsen, U. S., Pösö, J., Fikse, F.
, Manzanilla Pech, C. I. V. & Aamand, G. P. (2021).
Genomic prediction of residual feed intake in the Nordic breeds using data from research herds and 3D cameras in commercial herds. In
Interbull Bulletin: Proceedings of the 2021 Interbull Meeting (Vol. 56 (2021), pp. 162-166)
https://journal.interbull.org/index.php/ib/article/view/66
Jørgensen, U., Kristensen, T., Jørgensen, J. R., Kongsted, A. G., De Notaris, C., Nielsen, C., Mortensen, E. Ø., Ambye-Jensen, M., Jensen, S. K., Stødkilde-Jørgensen, L., Dalsgaard, T. K., Møller, A. H., Grøn Sørensen, C., Asp, T., Lehmann Olsen, F. & Gylling, M. (2021).
Green biorefining of grassland biomass. DCA - Nationalt Center for Fødevarer og Jordbrug. DCA rapport No. 193
https://dcapub.au.dk/djfpublikation/index.asp?action=show&id=1480
Gautason, E., Sahana, G., Su, G., Benjamínsson, B. H., Jóhannesson, G.
& Guldbrandtsen, B. (2021).
Erratum to: Short communication: investigation of the feasibility of genomic selection in Icelandic Cattle.
Journal of Animal Science,
99(8), Article skab234.
https://doi.org/10.1093/jas/skab234
Mohammadabadi, M., Bordbar, F.
, Jensen, J., Du, M. & Guo, W. (2021).
Key genes regulating skeletal muscle development and growth in farm animals.
Animals,
11(3), Article 835.
https://doi.org/10.3390/ani11030835
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
Zhu, Z., Difford, G., Noel, S. J., Lassen, J., Løvendahl, P. & Hojberg, O. (2021).
Stability Assessment of the Rumen Bacterial and Archaeal Communities in Dairy Cows Within a Single Lactation and Its Association With Host Phenotype.
Frontiers in Microbiology,
12, Article 636223.
https://doi.org/10.3389/fmicb.2021.636223
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
Zhang, H.
, Liu, A., Wang, Y., Luo, H., Yan, X.
, Guo, X., Li, X., Liu, L.
& Su, G. (2021).
Genetic Parameters and Genome-Wide Association Studies of Eight Longevity Traits Representing Either Full or Partial Lifespan in Chinese Holsteins.
Frontiers in Genetics,
12, Article 634986.
https://doi.org/10.3389/fgene.2021.634986/full
Zaalberg, R. M., Poulsen, N. A., Bovenhuis, H.
, Sehested, J., Larsen, L. B. & Buitenhuis, A. J. (2021).
Genetic analysis on infrared-predicted milk minerals for Danish dairy cattle.
Journal of Dairy Science,
104(8), 8947-8958.
https://doi.org/10.3168/jds.2020-19638
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
Villumsen, T. M., Su, G., Guldbrandtsen, B.
, Asp, T. & Lund, M. S. (2021).
Genomic selection in American mink (Neovison vison) using a single-step genomic best linear unbiased prediction model for size and quality traits graded on live mink.
Journal of Animal Science,
99(1), Article skab003.
https://doi.org/10.1093/jas/skab003
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
Song, Y., Wilson, A. J., Zhang, X. C., Thoms, D., Sohrabi, R., Song, S.
, Geissmann, Q., Liu, Y., Walgren, L., He, S. Y. & Haney, C. H. (2021).
FERONIA restricts Pseudomonas in the rhizosphere microbiome via regulation of reactive oxygen species.
Nature Plants,
7(5), 644-654.
https://doi.org/10.1038/s41477-021-00914-0
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
Shi, S., Li, X., Fang, L.
, Liu, A., Su, G., Zhang, Y., Luobu, B., Ding, X. & Zhang, S. (2021).
Genomic Prediction Using Bayesian Regression Models With Global-Local Prior.
Frontiers in Genetics,
12, Article 628205.
https://doi.org/10.3389/fgene.2021.628205
Shi, R., Brito, L. F.
, Liu, A., Luo, H., Chen, Z., Liu, L., Guo, G., Mulder, H., Ducro, B., van der Linden, A. & Wang, Y. (2021).
Genotype-by-environment interaction in Holstein heifer fertility traits using single-step genomic reaction norm models.
BMC Genomics,
22(1), Article 193.
https://doi.org/10.1186/s12864-021-07496-3
Schmidtmann, C.
, Schönherz, A., Guldbrandtsen, B., Marjanovic, J., Calus, M., Hinrichs, D. & Thaller, G. (2021).
Assessing the genetic background and genomic relatedness of red cattle populations originating from Northern Europe.
Genetics Selection Evolution,
53(1), Article 23.
https://doi.org/10.1186/s12711-021-00613-6
Schmidtmann, C., Thaller, G.
, Kargo, M., Hinrichs, D. & Ettema, J. (2021).
Derivation of economic values for German dairy breeds by means of a bio-economic model—with special emphasis on functional traits.
Journal of Dairy Science,
104(3), 3144-3157.
https://doi.org/10.3168/jds.2019-17635
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
Rome, H. J. S., Chu, T. T., Marois, D., Huang, C.-H.
, Madsen, P. & Jensen, J. (2021).
Accounting for genetic architecture for body weight improves accuracy of predicting breeding values in a commercial line of broilers.
Journal of Animal Breeding and Genetics,
138(5), 528-540. Article 528-540.
https://doi.org/10.1111/jbg.12546
Rabaglino, M. B., O’Doherty, A., Secher, J. B. M., Lonergan, P., Hyttel, P., Fair, T.
& Kadarmideen, H. N. (2021).
Application of multi-omics data integration and machine learning approaches to identify epigenetic and transcriptomic differences between in vitro and in vivo produced bovine embryos.
PLOS ONE,
16(5 May), Article e0252096.
https://doi.org/10.1371/journal.pone.0252096
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
Milkevych, V., Karaman, E., Sahana, G., Janss, L., Cai, Z. & Lund, M. S. (2021).
MeSCoT: The tool for quantitative trait simulation through the mechanistic modeling of genes' regulatory interactions.
G3 (Bethesda, Md.),
11(7), Article jkab133.
https://doi.org/10.1093/g3journal/jkab133
Mei, Q., Fu, C.
, Sahana, G., Chen, Y., Yin, L., Miao, Y., Zhao, S. & Xiang, T. (2021).
Identification of new semen trait-related candidate genes in Duroc boars through genome-wide association and weighted gene co-expression network analyses.
Journal of Animal Science,
99(7), Article skab188.
https://doi.org/10.1093/jas/skab188
Manzanilla Pech, C. I. V., Løvendahl, P., Mansan Gordo, D. G., Difford, G., Pryce, J., Schenkel, F. S., Wegmann, S., Miglior, F., Chud, T. C. S., Moate, P. J., Williams, S. R. O., Richardson, C. M., Stothard, P.
& Lassen, J. (2021).
Breeding for reduced methane emission and feed-efficient Holstein cows: An international response.
Journal of Dairy Science,
104(8), 8983-9001.
https://doi.org/10.3168/jds.2020-19889
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
Ma, X., Christensen, O. F., Gao, H., Huang, R.
, Nielsen, B., Madsen, P., Jensen, J., Ostersen, T., Li, P.
, Shirali, M. & Su, G. (2021).
Prediction of breeding values for group-recorded traits including genomic information and an individually recorded correlated trait.
Heredity,
126(1), 206-217.
https://doi.org/10.1038/s41437-020-0339-3
Luo, H., Brito, L. F., Li, X.
, Su, G., Dou, J., Xu, W., Yan, X., Zhang, H., Guo, G., Liu, L. & Wang, Y. (2021).
Genetic parameters for rectal temperature, respiration rate, and drooling score in Holstein cattle and their relationships with various fertility, production, body conformation, and health traits.
Journal of Dairy Science,
104(4), 4390-4403.
https://doi.org/10.3168/jds.2020-19192
Luo, H., Li, X., Hu, L., Xu, W., Chu, Q.
, Liu, A., Guo, G., Liu, L., Brito, L. F. & Wang, Y. (2021).
Genomic analyses and biological validation of candidate genes for rectal temperature as an indicator of heat stress in Holstein cattle.
Journal of Dairy Science,
104(4), 4441-4451.
https://doi.org/10.3168/jds.2020-18725