Aguilar I., Misztal I., Tsuruta S., Genetic components of heat stress for dairy cattle with multiple lactations. J. Dairy Sci. 92 (2009), 5702–5711 https://doi.org/10.3168/jds.2008-1928 19841230.
Bang N.N., Hayes B.J., Lyons R.E., Randhawa I.A.S., Gaughan J.B., Trach N.X., McNeill D.M., Genomic prediction and genome-wide association studies for productivity, conformation and heat tolerance traits in tropical smallholder dairy cows. J. Anim. Breed. Genet. 142 (2025), 322–341 https://doi.org/10.1111/jbg.12907 39462234.
Bekele R., Taye M., Abebe G., Meseret S., Genomic regions and candidate genes associated with milk production traits in Holstein and its crossbred cattle: A review. Int. J. Genomics, 2023, 2023, 8497453 https://doi.org/10.1155/2023/8497453 37547753.
Bellanger J.-M., Lazaro J.-B., Diriong S., Fernandez A., Lamb N., Debant A., The two guanine nucleotide exchange factor domains of Trio link the Rac1 and the RhoA pathways in vivo. Oncogene 16 (1998), 147–152 https://doi.org/10.1038/sj.onc.1201532 9464532.
Bernabucci U., Lacetera N., Baumgard L.H., Rhoads R.P., Ronchi B., Nardone A., Metabolic and hormonal acclimation to heat stress in domesticated ruminants. Animal 4 (2010), 1167–1183 https://doi.org/10.1017/S175173111000090X 22444615.
Blanchard P.J., Everett R.W., Searle S.R., Estimation of genetic trends and correlations for Jersey cattle. J. Dairy Sci. 66 (1983), 1947–1954 https://doi.org/10.3168/jds.S0022-0302(83)82033-5.
Carabaño M.J., Díaz C., Ramón M., Breeding for thermotolerance in dairy cattle: Production versus fertility traits. J. Dairy Sci. 108 (2025), 9915–9929 https://doi.org/10.3168/jds.2025-26258 40639653.
Carabaño M.J., Ramón M., Díaz C., Molina A., Pérez-Guzmán M.D., Serradilla J.M., Breeding and Genetics Symposium: Breeding for resilience to heat stress effects in dairy ruminants. A comprehensive review. J. Anim. Sci. 95 (2017), 1813–1826 https://doi.org/10.2527/jas2016.1114 28464073.
Chen Y., Hu H., Atashi H., Grelet C., Wijnrocx K., Lemal P., Gengler N., Genetic analysis of milk citrate predicted by milk mid-infrared spectra of Holstein cows in early lactation. J. Dairy Sci. 107 (2024), 3047–3061 https://doi.org/10.3168/jds.2023-23903 38056571.
Cheruiyot E.K., Haile-Mariam M., Cocks B.G., Pryce J.E., Improving genomic selection for heat tolerance in dairy cattle: Current opportunities and future directions. Front. Genet., 13, 2022, 894067 https://doi.org/10.3389/fgene.2022.894067 35769985.
Collier R.J., Collier J.L., Rhoads R.P., Baumgard L.H., Invited review: Genes involved in the bovine heat stress response. J. Dairy Sci. 91 (2008), 445–454 https://doi.org/10.3168/jds.2007-0540 18218730.
Dikmen S., Cole J.B., Null D.J., Hansen P.J., Heritability of rectal temperature and genetic correlations with production and reproduction traits in dairy cattle. J. Dairy Sci. 95 (2012), 3401–3405 https://doi.org/10.3168/jds.2011-4306 22612974.
Grelet C., Dardenne P., Soyeurt H., Fernandez J.A., Vanlierde A., Stevens F., Gengler N., Dehareng F., Large-scale phenotyping in dairy sector using milk MIR spectra: Key factors affecting the quality of predictions. Methods 186 (2021), 97–111 https://doi.org/10.1016/j.ymeth.2020.07.012 32763376.
Gungor B., Gombos I., Crul T., Ayaydin F., Szabó L., Török Z., Mátés L., Vígh L., Horváth I., Rac1 participates in thermally induced alterations of the cytoskeleton, cell morphology and lipid rafts, and regulates the expression of heat shock proteins in B16F10 melanoma cells. PLoS One, 9, 2014, e89136 https://doi.org/10.1371/journal.pone.0089136 24586549.
Hammami H., Vandenplas J., Vanrobays M.-L., Rekik B., Bastin C., Gengler N., Genetic analysis of heat stress effects on yield traits, udder health, and fatty acids of Walloon Holstein cows. J. Dairy Sci. 98 (2015), 4956–4968 https://doi.org/10.3168/jds.2014-9148 25958288.
Hu H., Atashi H., Franceschini S., Lemal P., Grelet C., Chen Y., Wijnrocx K., Soyeurt H., Gengler N., Using single-step genome-wide association analyses to compare predicted negative energy balance and a novel energy deficiency score in early-lactation Holstein cows. JDS Commun. 6 (2025), 792–796 https://doi.org/10.3168/jdsc.2025-0778 41221001.
Jerônimo R., Moraes M.N., de Assis L.V.M., Ramos B.C., Rocha T., Castrucci A.M.de L., Thermal stress in Danio rerio: A link between temperature, light, thermo-TRP channels, and clock genes. J. Therm. Biol. 68 (2017), 128–138 https://doi.org/10.1016/j.jtherbio.2017.02.009 28689714.
Khan M.Z., Ma Y., Ma J., Xiao J., Liu Y., Liu S., Khan A., Khan I.M., Cao Z., Association of DGAT1 with cattle, buffalo, goat, and sheep milk and meat production traits. Front. Vet. Sci., 8, 2021, 712470 https://doi.org/10.3389/fvets.2021.712470 34485439.
Kim J.-M., Lim K.-S., Byun M., Lee K.-T., Yang Y., Park M., Lim D., Chai H.-H., Bang H.-T., Hwangbo J., Choi Y., Cho Y.-M., Park J.-E., Identification of the acclimation genes in transcriptomic responses to heat stress of White Pekin duck. Cell Stress Chaperones 22 (2017), 787–797 https://doi.org/10.1007/s12192-017-0809-6 28634817.
Lemal P., Grelet C., Dehareng F., Soyeurt H., Schroyen M., Gengler N., Residual analysis for the identification of potential mid-infrared-derived biomarkers of heat stress in dairy cattle. J. Dairy Sci. 108 (2025), 1714–1729 https://doi.org/10.3168/jds.2024-25440 39694247.
Lemal P., Grelet C., Dehareng F., Soyeurt H., Schroyen M., Gengler N., Prediction of heat stress response in dairy cows using milk mid-infrared spectra. Sci. Rep., 16, 2026, 14258 https://doi.org/10.1038/s41598-026-39287-9 41857082.
Li Q.-L., Ju Z.-H., Huang J.-M., Li J.-B., Li R.-L., Hou M.-H., Wang C.-F., Zhong J.-F., Two novel SNPs in HSF1 gene are associated with thermal tolerance traits in Chinese Holstein cattle. DNA Cell Biol. 30 (2011), 247–254 https://doi.org/10.1089/dna.2010.1133 21189066.
Lopdell T.J., Using QTL to identify genes and pathways underlying the regulation and production of milk components in cattle. Animals (Basel), 13, 2023, 911 https://doi.org/10.3390/ani13050911 36899768.
Markey A., Groβe-Brinkhaus C., Mörlein D., Mörlein J., Wilmot H., Tholen E., Gengler N., Genetic investigations into the use of sensory evaluation: The case of boar taint discrimination in Pietrain sired crossbreds. J. Anim. Sci., 103, 2025, skae389 https://doi.org/10.1093/jas/skae389 39718970.
Misztal I., Brito L.F., Lourenco D., Breeding for improved heat tolerance in dairy cattle: Methods, challenges, and progress. JDS Commun. 6 (2025), 464–468 https://doi.org/10.3168/jdsc.2024-0651 40458150.
Misztal I., Tsuruta S., Lourenco D., Masuda Y., Aguilar I., Legarra A., Vitezica Z., Manual for BLUPF90 family of programs, 2014, University of Georgia, Athens, GA.
Nayeri S., Schenkel F., Fleming A., Kroezen V., Sargolzaei M., Baes C., Cánovas A., Squires J., Miglior F., Genome-wide association analysis for β-hydroxybutyrate concentration in milk in Holstein dairy cattle. BMC Genet., 20, 2019, 58 https://doi.org/10.1186/s12863-019-0761-9 31311492.
Pook T., van Pelt M.L., Vandenplas J., Adriaens I., Zetouni L., Orrett C., de Haas Y., Kamphuis C., Gredler-Grandl B., Characterization of a novel heat tolerance trait and subsequent haplotype block-based analysis to identify associated regions in Dutch Holstein cattle. J. Dairy Sci. 108 (2025), 13543–13564 https://doi.org/10.3168/jds.2025-26870 41043706.
Ravagnolo O., Misztal I., Genetic component of heat stress in dairy cattle, parameter estimation. J. Dairy Sci. 83 (2000), 2126–2130 https://doi.org/10.3168/jds.S0022-0302(00)75095-8 11003247.
Ravagnolo O., Misztal I., Effect of heat stress on nonreturn rate in Holstein cows : genetic analyses. J. Dairy Sci. 85 (2002), 3092–3100 https://doi.org/10.3168/jds.S0022-0302(02)74396-8 12487476.
Sanchez M.-P., Govignon-Gion A., Croiseau P., Fritz S., Hozé C., Miranda G., Martin P., Barbat-Leterrier A., Letaïef R., Rocha D., Brochard M., Boussaha M., Boichard D., Within-breed and multi-breed GWAS on imputed whole-genome sequence variants reveal candidate mutations affecting milk protein composition in dairy cattle. Genet. Sel. Evol., 49, 2017, 68 https://doi.org/10.1186/s12711-017-0344-z 28923017.
Sanchez M.-P., Rocha D., Charles M., Boussaha M., Hozé C., Brochard M., Delacroix-Buchet A., Grosperrin P., Boichard D., Sequence-based GWAS and post-GWAS analyses reveal a key role of SLC37A1, ANKH, and regulatory regions on bovine milk mineral content. Sci. Rep., 11, 2021, 7537 https://doi.org/10.1038/s41598-021-87078-1 33824377.
Snell E.J., A scaling procedure for ordered categorical data. Biometrics 20 (1964), 592–607 https://doi.org/10.2307/2528498.
Soares R.A.N., Vargas G., Duffield T., Schenkel F., Squires E.J., Genome-wide association study and functional analyses for clinical and subclinical ketosis in Holstein cattle. J. Dairy Sci. 104 (2021), 10076–10089 https://doi.org/10.3168/jds.2020-20101 34099305.
Szeri F., Lundkvist S., Donnelly S., Engelke U.F.H., Rhee K., Williams C.J., Sundberg J.P., Wevers R.A., Tomlinson R.E., Jansen R.S., van de Wetering K., The membrane protein ANKH is crucial for bone mechanical performance by mediating cellular export of citrate and ATP. PLoS Genet., 16, 2020, e1008884 https://doi.org/10.1371/journal.pgen.1008884 32639996.
Tiplady K.M., Lopdell T.J., Reynolds E., Sherlock R.G., Keehan M., Johnson T.J.J., Pryce J.E., Davis S.R., Spelman R.J., Harris B.L., Garrick D.J., Littlejohn M.D., Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle. Genet. Sel. Evol., 53, 2021, 62 https://doi.org/10.1186/s12711-021-00648-9 34284721.
Vanderick S., Mota R. R., Wijnrocx K., Gengler N., Description of the genetic evaluation systems used in the Walloon Region of Belgium. Accessed Feb. 20, 2026. https://www.elinfo.be/docs/GESen2204.pdf, 2022.
West J.W., Nutritional strategies for managing the heat-stressed dairy cow. J. Anim. Sci. 77:suppl_2 (1999), 21–35 https://doi.org/10.2527/1997.77suppl_221x 15526778.
Xu W., van Knegsel A., Saccenti E., van Hoeij R., Kemp B., Vervoort J., Metabolomics of milk reflects a negative energy balance in cows. J. Proteome Res. 19 (2020), 2942–2949 https://doi.org/10.1021/acs.jproteome.9b00706 32633519.
Xue H., Huo Y., Hu Y., Zhang J., Deng C., Zhang J., Wang X., The role of ALOX15B in heat stress-induced apoptosis of porcine Sertoli cells. Theriogenology 185 (2022), 6–15 https://doi.org/10.1016/j.theriogenology.2022.03.018 35344833.
Zhang J., Bai K., He J., Niu Y., Lu Y., Zhang L., Wang T., Curcumin attenuates hepatic mitochondrial dysfunction through the maintenance of thiol pool, inhibition of mtDNA damage, and stimulation of the mitochondrial thioredoxin system in heat-stressed broilers. J. Anim. Sci. 96 (2018), 867–879 https://doi.org/10.1093/jas/sky009 29566233.
