New Loci and Neuronal Pathways for Resilience to Heat Stress in Cattle
Open accessPublished version of a preprint
Abstract
Abstract Climate change and resilience to warming climates have implications for humans, livestock, and wildlife. The genetic mechanisms that confer thermotolerance to mammals are still not well characterized. We used dairy cows as a model to study heat tolerance because they are lactating, and therefore often prone to thermal stress. The data comprised almost 0.5 million milk records (milk, fat, and proteins) of 29,107 Australian Holsteins, each having around 15 million imputed sequence variants. Dairy animals often reduce their milk production when temperature and humidity rise; thus, the phenotypes used to measure an individual’s heat tolerance were defined as the rate of milk production decline (slope traits) with a rising temperature-humidity index. With these slope traits, we performed a genome-wide association study (GWAS) using different approaches, including conditional analyses, to correct for the relationship between heat tolerance and level of milk production. The results revealed multiple novel loci for heat tolerance, including 61 potential functional variants at sites highly conserved across vertebrate species. Moreover, it was interesting that specific candidate variants and genes are related to the neuronal system ( ITPR1, ITPR2, and GRIA4 ) and neuroactive ligand-receptor interaction functions for heat tolerance ( NPFFR2, CALCR, and GHR ), providing a novel insight that can help to develop genetic and management approaches to combat heat stress. Author summary While understanding the genetic basis of heat tolerance is crucial in the context of global warming’s effect on humans, livestock, and wildlife, the specific genetic variants and biological features that confer thermotolerance in animals are still not well characterized. The ability to tolerate heat varies across individuals, with substantial genetic control of this complex trait. Dairy cattle are excellent model in which to find genes associated with individual variations in heat tolerance since they significantly suffer from heat stress due to the metabolic heat of lactation. By genome-wide association studies of more than 29,000 cows with 15 million sequence variants and controlled phenotype measurements, we identify many new loci associated with heat tolerance. The biological functions of these loci are linked to the neuronal system and neuroactive ligand-receptor interaction functions. Also, several putative causal mutations for heat tolerance are at genomic sites that are otherwise evolutionarily conserved across 100 vertebrate species. Overall, our findings provide new insight into the molecular and biological basis of heat tolerance that can help to develop genetic and management approaches to combat heat stress.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
GRIA4 has been reported as a candidate gene for heat tolerance in Australian Holsteins, enriched in the glutamatergic synapse pathway, suggesting that GRIA4 mediates response to both cold and heat stress through thermoregulation.
“GRIA4 has been reported as a candidate gene for heat tolerance in Australian Holsteins, enriched in the glutamatergic synapse pathway [106], suggesting that GRIA4 mediates response to both cold and heat stress through thermoregulation.”
From The Genomic Landscape of Cattle: Domestication, Dispersal, and Adaptive Evolution (2026) · cites this paper as [106]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890 · see citing works
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089 · see citing works
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., et al. (2010) · Genome Research · doi:10.1101/gr.107524.110 · Cited by 27,895 · see citing works
Cingolani, P., Platts, A., Wang, L. L., Coon, M., Nguyen, T., Wang, L., Land, S. J., Lu, X., & Ruden, D. M. (2012) · Fly · doi:10.4161/fly.19695 · Cited by 11,816 · see citing works
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692 · see citing works
GCTA: a tool for genome-wide complex trait analysis
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.11.011 · Cited by 8,279 · see citing works
Structural absorption by barbule microstructures of super black bird of paradise feathers
McCoy, D. E., Feo, T., Harvey, T. A., & Prum, R. O. (2018) · Nature Communications · doi:10.1038/s41467-017-02088-w · Cited by 7,424 · see citing works
Ammonia as a case study for the spontaneous ionization of a simple hydrogen-bonded compound
Palasyuk, T., Troyan, I. A., Eremets, M. I., Drozd, V., Medvedev, S. A., Zaleski‐Ejgierd, P., Magos–Palasyuk, E., Wang, H., Bonev, S., Dudenko, D., et al. (2014) · Nature Communications · doi:10.1038/ncomms4460 · Cited by 3,235 · see citing works
Partitioning heritability by functional annotation using genome-wide association summary statistics
ReproGen Consortium, Finucane, H. K., Schizophrenia Working Group of the Psychiatric Genomics Consortium, The RACI Consortium, Bulik-Sullivan, B., Gusev, A., Trynka, G., Reshef, Y., Loh, P.-R., Anttila, V., et al. (2015) · Nature Genetics · doi:10.1038/ng.3404 · Cited by 2,604 · see citing works
Efficient generation of mouse models of human diseases via ABE- and BE-mediated base editing
Liu, Z., Lu, Z., Yang, G., Huang, S., Li, G., Feng, S., Liu, Y., Li, J., Yu, W., Zhang, Y., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04768-7 · Cited by 2,103 · see citing works
Reference-based phasing using the Haplotype Reference Consortium panel
Loh, P.-R., Danecek, P., Palamara, P. F., Fuchsberger, C., A Reshef, Y., K Finucane, H., Schoenherr, S., Forer, L., McCarthy, S., Abecasis, G. R., et al. (2016) · Nature Genetics · doi:10.1038/ng.3679 · Cited by 1,894 · see citing works
The Electronic Medical Records and Genomics (eMERGE) Consortium, Wood, A. R., The MIGen Consortium, The PAGE Consortium, Study, T. L. C., Esko, T., Yang, J., Vedantam, S., Pers, T. H., Gustafsson, S., et al. (2014) · Nature Genetics · doi:10.1038/ng.3097 · Cited by 1,853 · see citing works
Economic Losses from Heat Stress by US Livestock Industries
St-Pierre, N. R., Cobanov, B., & Schnitkey, G. (2003) · Journal of Dairy Science · doi:10.3168/jds.s0022-0302(03)74040-5 · Cited by 1,755 · see citing works
Fast and accurate genotype imputation in genome-wide association studies through pre-phasing
Howie, B., Fuchsberger, C., Stephens, M., Marchini, J., & Abecasis, G. R. (2012) · Nature Genetics · doi:10.1038/ng.2354 · Cited by 1,737 · see citing works
A new approach for efficient genotype imputation using information from relatives
Sargolzaei, M., Chesnais, J. P., & Schenkel, F. S. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-478 · Cited by 1,043 · see citing works
Metabolic and hormonal acclimation to heat stress in domesticated ruminants
Bernabucci, U., Lacetera, N., Baumgard, L. H., Rhoads, R. P., Ronchi, B., & Nardone, A. (2010) · animal · doi:10.1017/s175173111000090x · Cited by 966 · see citing works
Effects of Heat Stress on Postabsorptive Metabolism and Energetics
Baumgard, L. H., & Rhoads, R. P. (2012) · Annual Review of Animal Biosciences · doi:10.1146/annurev-animal-031412-103644 · Cited by 909 · see citing works
Invited review: Effects of heat stress on dairy cattle welfare
Polsky, L., & von Keyserlingk, M. A. G. (2017) · Journal of Dairy Science · doi:10.3168/jds.2017-12651 · Cited by 872 · see citing works
Future of the human climate niche
Xu, C., Kohler, T. A., Lenton, T. M., Svenning, J.-C., & Scheffer, M. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1910114117 · Cited by 862 · see citing works
Effects of heat stress on energetic metabolism in lactating Holstein cows
Wheelock, J. B., Rhoads, R. P., VanBaale, M. J., Sanders, S. R., & Baumgard, L. H. (2010) · Journal of Dairy Science · doi:10.3168/jds.2009-2295 · Cited by 833 · see citing works
<i>De novo</i> assembly of the cattle reference genome with single-molecule sequencing
Rosen, B. D., Bickhart, D. M., Schnabel, R. D., Koren, S., Elsik, C. G., Tseng, E., Rowan, T. N., Low, W. Y., Zimin, A., Couldrey, C., et al. (2020) · GigaScience · doi:10.1093/gigascience/giaa021 · Cited by 802 · see citing works
Physiological and cellular adaptations of zebu cattle to thermal stress
Hansen, P. J. (2004) · Animal Reproduction Science · doi:10.1016/j.anireprosci.2004.04.011 · Cited by 642 · see citing works
Review: Adaptation of animals to heat stress
Sejian, V., Bhatta, R., Gaughan, J. B., Dunshea, F. R., & Lacetera, N. (2018) · animal · doi:10.1017/s1751731118001945 · Cited by 587 · see citing works
Cai, Y., Xue, F., Fleming, C., Yang, J., Ding, C., Ma, Y., Liu, M., Zhang, H., Zheng, J., Xiong, N., et al. (2016) · Nature Communications · doi:10.1038/ncomms11354 · Cited by 531 · see citing works
Genetic Component of Heat Stress in Dairy Cattle, Development of Heat Index Function
Ravagnolo, O., Misztal, I., & Hoogenboom, G. (2000) · Journal of Dairy Science · doi:10.3168/jds.s0022-0302(00)75094-6 · Cited by 512 · see citing works
A thermosensory pathway that controls body temperature
Nakamura, K., & Morrison, S. F. (2007) · Nature Neuroscience · doi:10.1038/nn2027 · Cited by 503 · see citing works
Hayes, B. J., & Daetwyler, H. D. (2018) · Annual Review of Animal Biosciences · doi:10.1146/annurev-animal-020518-115024 · Cited by 467 · see citing works
Grisart, B., Farnir, F., Karim, L., Cambisano, N., Kim, J.-J., Kvasz, A., Mni, M., Simon, P., Frère, J., Coppieters, W. R., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0308518100 · Cited by 448 · see citing works
Blott, S. C., Kim, J.-J., Moisio, S., Schmidt‐Küntzel, A., Cornet, A. M., Berzi, P., Cambisano, N., Ford, C. A., Grisart, B., Johnson, D., et al. (2003) · Genetics · doi:10.1093/genetics/163.1.253 · Cited by 417 · see citing works
Winter, A., Krämer, W., Werner, F. A. O., Kollers, S., Kata, S. R., Durstewitz, G., Buitkamp, J., Womack, J. E., Thaller, G. E., & Fries, R. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.142293799 · Cited by 404 · see citing works
Bolormaa, S., Pryce, J. E., Reverter, A., Zhang, Y., Barendse, W., Kemper, K. E., Tier, B., Savin, K. W., Hayes, B. J., & Goddard, M. E. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004198 · Cited by 282 · see citing works
Self-citationCowley, F. C., Barber, D. G., Houlihan, A. V., & Poppi, D. P. (2015) · Journal of Dairy Science · doi:10.3168/jds.2014-8442 · Cited by 269 · see citing works
Genomic selection for tolerance to heat stress in Australian dairy cattle
Nguyen, T. T. T., Bowman, P. J., Haile‐Mariam, M., Pryce, J. E., & Hayes, B. J. (2016) · Journal of Dairy Science · doi:10.3168/jds.2015-9685 · Cited by 240 · see citing works
Self-citationEscalating global exposure to compound heat-humidity extremes with warming
Li, D., Yuan, J., & Kopp, R. E. (2020) · Environmental Research Letters · doi:10.1088/1748-9326/ab7d04 · Cited by 226 · see citing works
The effects of heat stress on protein metabolism in lactating Holstein cows
Gao, S., Guo, J., Quan, S., Nan, X., Sanz-Fernandez, M. V., Baumgard, L. H., & Bu, D. (2017) · Journal of Dairy Science · doi:10.3168/jds.2016-11913 · Cited by 225 · see citing works
Sveinbjörnsson, G., Albrechtsen, A., Zink, F., Gudjonsson, S. A., Oddsson, Á., Másson, G., Hólm, H., Kong, A., Þorsteinsdóttir, U., Sulem, P., et al. (2016) · Nature Genetics · doi:10.1038/ng.3507 · Cited by 175 · see citing works
Liberation of recalcitrant cell wall sugars from oak barrels into bourbon whiskey during aging
Gollihue, J., Richmond, M. D., Wheatley, H., Pook, V. G., Nair, M., Kagan, I. A., & DeBolt, S. (2018) · Scientific Reports · doi:10.1038/s41598-018-34204-1 · Cited by 172 · see citing works
Xiang, R., van den Berg, I., MacLeod, I. M., Hayes, B. J., Prowse-Wilkins, C., Wang, M., Bolormaa, S., Liu, Z., Rochfort, S. J., Reich, C. M., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1904159116 · Cited by 171 · see citing works
Self-citationHayes, B. J., Bowman, P. J., Chamberlain, A. J., Savin, K. W., Tassell, C. P. V., Sonstegard, T. S., & Goddard, M. E. (2009) · PLoS ONE · doi:10.1371/journal.pone.0006676 · Cited by 161 · see citing works
Littlejohn, M. D., Tiplady, K., Fink, T., Lehnert, K., Lopdell, T., Johnson, T., Couldrey, C., Keehan, M., Sherlock, R. G., Harland, C., et al. (2016) · Scientific Reports · doi:10.1038/srep25376 · Cited by 158 · see citing works
Functionally reciprocal mutations of the prolactin signalling pathway define hairy and slick cattle
Littlejohn, M. D., Henty, K., Tiplady, K., Johnson, T., Harland, C., Lopdell, T., Sherlock, R. G., Li, W., Lukefahr, S. D., Shanks, B. C., et al. (2014) · Nature Communications · doi:10.1038/ncomms6861 · Cited by 151 · see citing works
Dikmen, S., Cole, J. B., Null, D. J., & Hansen, P. J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0069202 · Cited by 135 · see citing works
Dikmen, S., Cole, J. B., Null, D. J., & Hansen, P. J. (2012) · Journal of Dairy Science · doi:10.3168/jds.2011-4306 · Cited by 128 · see citing works
The role of RFamide peptides in feeding
Bechtold, D. A., & Luckman, S. M. (2007) · Journal of Endocrinology · doi:10.1677/joe-06-0069 · Cited by 124 · see citing works
Pausch, H., MacLeod, I. M., Fries, R., Emmerling, R., Bowman, P. J., Daetwyler, H. D., & Goddard, M. E. (2017) · Genetics Selection Evolution · doi:10.1186/s12711-017-0301-x · Cited by 124 · see citing works
Self-citationHayes, B. J., Carrick, M., Bowman, P. J., & Goddard, M. E. (2003) · Journal of Dairy Science · doi:10.3168/jds.s0022-0302(03)73980-0 · Cited by 123 · see citing works
Rhoads, M. L., Kim, J. W., Collier, R. J., Crooker, B. A., Boisclair, Y. R., Baumgard, L. H., & Rhoads, R. P. (2010) · Journal of Dairy Science · doi:10.3168/jds.2009-2469 · Cited by 112 · see citing works
Modeling heat stress effect on Holstein cows under hot and dry conditions: Selection tools
Carabaño, M. J., Bachagha, K., Ramón, M., & Díaz, C. (2014) · Journal of Dairy Science · doi:10.3168/jds.2014-8023 · Cited by 112 · see citing works
Sigdel, A., Abdollahi-Arpanahi, R., Aguilar, I., & Peñagaricano, F. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00928 · Cited by 95 · see citing works
Bryant, J. R., Lopez-Villalobos, N., Pryce, J. E., Holmes, C. W., & Johnson, D. L. (2007) · New Zealand Journal of Agricultural Research · doi:10.1080/00288230709510301 · Cited by 92 · see citing works
Self-citationThe novel estrogen-induced gene EIG121 regulates autophagy and promotes cell survival under stress
Deng, L., Feng, J., & Broaddus, R. R. (2010) · Cell Death and Disease · doi:10.1038/cddis.2010.9 · Cited by 87 · see citing works
Taye, M., Lee, W., Caetano-Anollés, K., Dessie, T., Hanotte, O., Mwai, O. A., Kemp, S. J., Cho, S., Oh, S. J., Lee, H., et al. (2017) · Animal Science Journal · doi:10.1111/asj.12851 · Cited by 85 · see citing works
Dado-Senn, B., Skibiel, A. L., Fabris, T. F., Zhang, Y., Dahl, G. E., Peñagaricano, F., & Laporta, J. (2018) · Scientific Reports · doi:10.1038/s41598-018-29420-8 · Cited by 85 · see citing works
Gao, S., Ma, L., Zhou, Z., Zhou, Z., Baumgard, L. H., Jiang, D., Bionaz, M., & Bu, D. (2019) · Physiological Genomics · doi:10.1152/physiolgenomics.00039.2019 · Cited by 79 · see citing works
Freitas, P. H. F., Wang, Y., Yan, P., de Oliveira, H. R., Schenkel, F. S., Zhang, Y., Xu, Q., & Brito, L. F. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.604823 · Cited by 77 · see citing works
Nguyen, T. T. T., Bowman, P. J., Haile‐Mariam, M., Nieuwhof, G. J., Hayes, B. J., & Pryce, J. E. (2017) · Journal of Dairy Science · doi:10.3168/jds.2017-12898 · Cited by 76 · see citing works
Self-citationUnraveling genetic sensitivity of beef cattle to environmental variation under tropical conditions
Carvalheiro, R., Costilla, R., Neves, H. H. D. R., de Albuquerque, L. G., Moore, S. S., & Hayes, B. J. (2019) · Genetics Selection Evolution · doi:10.1186/s12711-019-0470-x · Cited by 76 · see citing works
Abolished InsP3R2 function inhibits sweat secretion in both humans and mice
Klar, J., Hisatsune, C., Baig, S. M., Tariq, M., Johansson, A., Rasool, M., Malik, N. A., Ameur, A., Sugiura, K., Feuk, L., et al. (2014) · Journal of Clinical Investigation · doi:10.1172/jci70720 · Cited by 75 · see citing works
Macciotta, N. P. P., Biffani, S., Bernabucci, U., Lacetera, N., Vitali, A., Ajmone‐Marsan, P., & Nardone, A. (2017) · Journal of Dairy Science · doi:10.3168/jds.2016-12249 · Cited by 68 · see citing works
Thermotolerance and plasticity of camel somatic cells exposed to acute and chronic heat stress
Saadeldin, I. M., Swelum, A. A., Elsafadi, M. A., Mahmood, A., Osama, A., Shikshaky, H., Alfayez, M. A., Alowaimer, A. N., & Magdeldin, S. (2019) · Journal of Advanced Research · doi:10.1016/j.jare.2019.11.009 · Cited by 68 · see citing works
Diet-induced adaptive thermogenesis requires neuropeptide FF receptor-2 signalling
Zhang, L., Ip, C. K., Lee, I.-C. J., Qi, Y., Reed, F. M., Karl, T., Low, J. K., Enriquez, R. F., Lee, N. J., Baldock, P. A. J., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-06462-0 · Cited by 66 · see citing works
Cheruiyot, E. K., Nguyen, T. T. T., Haile‐Mariam, M., Cocks, B. G., Abdelsayed, M., & Pryce, J. E. (2019) · Journal of Dairy Science · doi:10.3168/jds.2019-17609 · Cited by 63 · see citing works
Self-citationOtto, P. I., Guimarães, S. E. F., Verardo, L. L., Azevedo, A. L. S., Vandenplas, J., Sevillano, C. A., Marques, D. B. D., Pires, M. D. F. Á., de Freitas, C., Verneque, R. S., et al. (2019) · Journal of Dairy Science · doi:10.3168/jds.2018-15305 · Cited by 62 · see citing works
Fang, N. N., Zhu, M., Rose, A., Wu, K., & Mayor, T. (2016) · Nature Communications · doi:10.1038/ncomms12907 · Cited by 60 · see citing works
Menegazzi, P., Yoshii, T., & Helfrich‐Förster, C. (2012) · Journal of Biological Rhythms · doi:10.1177/0748730412463181 · Cited by 56 · see citing works
Pegolo, S., Mach, N., Ramayo‐Caldas, Y., Schiavon, S., Bittante, G., & Cecchinato, A. (2018) · Scientific Reports · doi:10.1038/s41598-017-18916-4 · Cited by 55 · see citing works
Symposium review: Building a better cow—The Australian experience and future perspectives
Pryce, J. E., Nguyen, T. T. T., Axford, M., Nieuwhof, G. J., & Shaffer, M. (2018) · Journal of Dairy Science · doi:10.3168/jds.2017-13377 · Cited by 53 · see citing works
Self-citationKim, K., Seibert, J. T., Edea, Z., Graves, K. L., Kim, E.-S., Keating, A. F., Baumgard, L. H., Ross, J. W., & Rothschild, M. F. (2018) · Journal of Animal Science · doi:10.1093/jas/sky131 · Cited by 51 · see citing works
Heat Shock Factor 2 Protects against Proteotoxicity by Maintaining Cell-Cell Adhesion
Joutsen, J., Da Silva, A. J., Luoto, J. C., Budzynski, M. A., Nylund, A. S., de Thonel, A., Concordet, J.-P., Mezger, V., Sabéran-Djoneidi, D., Henriksson, E., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2019.12.037 · Cited by 51 · see citing works
Neuropeptide FF and Its Receptors: Therapeutic Applications and Ligand Development
Nguyen, T., Marusich, J. A., Li, J.-X., & Zhang, Y. (2020) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.0c00643 · Cited by 51 · see citing works
Sensorimotor stroke alters hippocampo-thalamic network activity
Baumgartner, P., Amki, M. E., Bracko, O., Luft, A. R., & Wegener, S. (2018) · Scientific Reports · doi:10.1038/s41598-018-34002-9 · Cited by 49 · see citing works
Goda, T., Doi, M., Umezaki, Y., Murai, I., Shimatani, H., Chu, M. L., Nguyen, V. H., Okamura, H., & Hamada, F. N. (2018) · Genes & Development · doi:10.1101/gad.307884.117 · Cited by 42 · see citing works
Igoshin, A. V., Yurchenko, A. A., Belonogova, N. M., Petrovsky, D. V., Aitnazarov, R. B., Soloshenko, V. A., Yudin, N. S., & Larkin, D. M. (2019) · BMC Genetics · doi:10.1186/s12863-019-0725-0 · Cited by 42 · see citing works
Xiang, R., van den Berg, I., MacLeod, I. M., Daetwyler, H. D., & Goddard, M. E. (2020) · Communications Biology · doi:10.1038/s42003-020-0823-6 · Cited by 35 · see citing works
Self-citationKim, J., Lim, K., Byun, M.-J., Lee, K., Yang, Y.-R., Park, M. N., Lim, D., Chai, H., Bang, H. T., Hwangbo, J., et al. (2017) · Cell Stress and Chaperones · doi:10.1007/s12192-017-0809-6 · Cited by 33 · see citing works
Guangxin, E., Basang, W., & Zhu, Y. (2019) · Journal of Animal Breeding and Genetics · doi:10.1111/jbg.12403 · Cited by 31 · see citing works
Neuropeptide FF receptors antagonist, RF9, attenuates opioid-evoked hypothermia in mice
Wang, Y., Guo, J., Wang, S.-B., Fang, Q., He, F., & Wang, R. (2008) · Peptides · doi:10.1016/j.peptides.2008.02.016 · Cited by 26 · see citing works
The use of milk mid-infrared spectroscopy to improve genomic prediction accuracy of serum biomarkers
van den Berg, I., Ho, P. N., Luke, T. D. W., Haile‐Mariam, M., Bolormaa, S., & Pryce, J. E. (2020) · Journal of Dairy Science · doi:10.3168/jds.2020-19468 · Cited by 25 · see citing works
Self-citationWang, T., Chen, Y. P., MacLeod, I. M., Pryce, J. E., Goddard, M. E., & Hayes, B. J. (2017) · BMC Genomics · doi:10.1186/s12864-017-4030-x · Cited by 20 · see citing works
Self-citation1507 The effects of heat stress on protein metabolism in lactating Holstein cows
Gao, S., Guo, J., Quan, S., Nan, X., Baumgard, L. H., & Bu, D. (2016) · Journal of Animal Science · doi:10.2527/jam2016-1507 · Cited by 6 · see citing works
Flagged first, then by citations
3 of the 83 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Habimana, V., Nguluma, A. S., Nziku, Z. C., Ekine-Dzivenu, C. C., Morota, G., Mrode, R., & Chenyambuga, S. W. (2023) · Frontiers in Veterinary Science · doi:10.3389/fvets.2023.1121499 · Cited by 80 · see citing works
Lemal, P., May, K., König, S., Schroyen, M., & Gengler, N. (2023) · Journal of Dairy Science · doi:10.3168/jds.2022-22727 · Cited by 67 · see citing works
Automated Monitoring of Cattle Heat Stress and Its Mitigation
Islam, M. A., Lomax, S., Doughty, A. K., Islam, M. R., Jay, O., Thomson, P. C., & Clark, C. (2021) · Frontiers in Animal Science · doi:10.3389/fanim.2021.737213 · Cited by 62 · see citing works
Heat Stress: A Serious Disruptor of the Reproductive Physiology of Dairy Cows
Dovolou, E., Giannoulis, T., Nanas, I., & Amiridis, G. S. (2023) · Animals · doi:10.3390/ani13111846 · Cited by 69 · see citing works
Rajawat, D., Panigrahi, M., Kumar, H., Nayak, S. S., Parida, S., Bhushan, B., Gaur, G. K., Dutt, T., & Mishra, B. P. (2022) · Gene · doi:10.1016/j.gene.2021.146165 · Cited by 51 · see citing works
Cheruiyot, E. K., Haile‐Mariam, M., Cocks, B. G., & Pryce, J. E. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.894067 · Cited by 51 · see citing works
Self-citationWorku, D., Hussen, J., De Matteis, G., Schusser, B., & Alhussien, M. N. (2023) · Frontiers in Veterinary Science · doi:10.3389/fvets.2023.1151241 · Cited by 43 · see citing works
“…the researchers have conducted validation of GWAS to prioritize the variants most likely to be causal to thermo-tolerance and to provide several biological insights that can be leveraged to minimize HS while maintaining milk production in dairy cattle using a large dataset (2, 12, 14, 93).”
InfluentialYin, T., Halli, K., & König, S. (2022) · Journal of Dairy Science · doi:10.3168/jds.2022-21804 · Cited by 29 · see citing works
Kambal, S., Tijjani, A., Ibrahim, S. A. E., Ahmed, M. A., Mwacharo, J. M., & Hanotte, O. (2023) · Animal Genetics · doi:10.1111/age.13353 · Cited by 27 · see citing works
Zamorano‐Algandar, R., Medrano, J. F. F., Thomas, M., Enns, R. M., Speidel, S. E., Sanchez-Castro, M. A., Luna-Nevárez, G., Leyva-Corona, J. C., & Luna‐Nevárez, P. (2023) · Biology · doi:10.3390/biology12050679 · Cited by 26 · see citing works
Genes and models for estimating genetic parameters for heat tolerance in dairy cattle
Habimana, V., Ekine-Dzivenu, C. C., Nguluma, A. S., Nziku, Z. C., Morota, G., Chenyambuga, S. W., & Mrode, R. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1127175 · Cited by 26 · see citing works
Džermeikaitė, K., Šidlauskaitė, M., Antanaitis, R., & Anskienė, L. (2025) · Dairy · doi:10.3390/dairy6050050 · Cited by 25 · see citing works
Cuellar, C. J., Saleem, M. N., Jensen, L. M., & Hansen, P. J. (2023) · Journal of Dairy Science · doi:10.3168/jds.2022-22725 · Cited by 23 · see citing works
Boonkum, W., Teawyoneyong, W., Chankitisakul, V., Duangjinda, M., & Buaban, S. (2024) · Animals · doi:10.3390/ani14203026 · Cited by 22 · see citing works
General resilience in dairy cows: A review
Kašná, E., Zavadilová, L., Vařeka, J., & Kyselová, J. (2022) · Czech Journal of Animal Science · doi:10.17221/149/2022-cjas · Cited by 20 · see citing works
Laodim, T., Koonawootrittriron, S., Elzo, M. A., Suwanasopee, T., Jattawa, D., & Sarakul, M. (2023) · Animal Bioscience · doi:10.5713/ab.23.0246 · Cited by 20 · see citing works
Igoshin, A., Yudin, N., Aitnazarov, R., Yurchenko, A. A., & Larkin, D. M. (2021) · Life · doi:10.3390/life11090959 · Cited by 19 · see citing works
Sölzer, N., May, K., Yin, T., & König, S. (2022) · Journal of Dairy Science · doi:10.3168/jds.2022-22087 · Cited by 18 · see citing works
Wu, X. Y., Fan, Y., Feng, J., Ma, K., & Li, J. (2023) · Aquaculture and Fisheries · doi:10.1016/j.aaf.2023.05.007 · Cited by 17 · see citing works
Genetic analysis of phenotypic indicators for heat tolerance in crossbred dairy cattle
Oloo, R. D., Ekine-Dzivenu, C. C., Mrode, R., Bennewitz, J., Ojango, J. M. K., Kipkosgei, G., Gebreyohanes, G., Okeyo, A. M., & Chagunda, M. G. G. (2024) · animal · doi:10.1016/j.animal.2024.101139 · Cited by 16 · see citing works
Sesay, A. R. (2023) · Journal of Applied and Advanced Research · doi:10.21839/jaar.2023.v8.8371 · Cited by 16 · see citing works
Elayadeth‐Meethal, M., Tiambo, C. K., Naseef, P. P., Kuruniyan, M. S., & Maloney, S. K. (2022) · Journal of Thermal Biology · doi:10.1016/j.jtherbio.2022.103426 · Cited by 15 · see citing works
Wen, H., Johnson, J. S., Freitas, P. H. F., Maskal, J. M., Glória, L. S., Araujo, A. C., Pedrosa, V. B., Tiezzi, F., Maltecca, C., Huang, Y., et al. (2023) · Genetics Selection Evolution · doi:10.1186/s12711-023-00868-1 · Cited by 15 · see citing works
Reich, P., Möller, S., Stock, K. F., Nolte, W., Prondzinski, M. V. D., Reents, R., Kalm, E., Kühn, C., Thaller, G. E., Falker‐Gieske, C., et al. (2024) · Genetics Selection Evolution · doi:10.1186/s12711-024-00914-6 · Cited by 15 · see citing works
Scerri, T. M., Lomax, S., & Clark, C. (2023) · Frontiers in Animal Science · doi:10.3389/fanim.2023.1169743 · Cited by 15 · see citing works
Cheruiyot, E. K., Haile‐Mariam, M., Cocks, B. G., MacLeod, I. M., Mrode, R., & Pryce, J. E. (2022) · Genetics Selection Evolution · doi:10.1186/s12711-022-00708-8 · Cited by 13 · see citing works
Self-citationMbuthia, J. M., Mayer, M., & Reinsch, N. (2021) · Livestock Science · doi:10.1016/j.livsci.2021.104794 · Cited by 10 · see citing works
Gaspa, G., Cesarani, A., Pauciullo, A., Peana, I., & Macciotta, N. P. P. (2024) · Animals · doi:10.3390/ani14243585 · Cited by 9 · see citing works
Batool, I., Kausar, R., & Hussain, T. (2025) · Journal of Thermal Biology · doi:10.1016/j.jtherbio.2025.104201 · Cited by 9 · see citing works
Feng, Y., Zhang, S., Suo, D., Fu, T., Li, Y., Li, Z., Wang, C., & Fan, X. (2024) · Nutrients · doi:10.3390/nu17010088 · Cited by 8 · see citing works
Williams‐Simon, P. A., Oster, C., Moaton, J. A., Ghidey, R., Ng’oma, E., Middleton, K. M., Zars, T. D., & King, E. G. (2024) · Genetics · doi:10.1093/genetics/iyae040 · Cited by 7 · see citing works
Xu, J., Hu, L.-R., Ning, J., Zhang, F., Xu, Q., & Wang, Y.-C. (2025) · BMC Genomics · doi:10.1186/s12864-025-11716-5 · Cited by 7 · see citing works
Kalemkeridou, M., Nanas, I., Moutou, K. A., Amiridis, G. S., Τσιπουρλιάνος, Α., Dovolou, E., Mamuris, Z., & Giannoulis, T. (2022) · Reproduction in Domestic Animals · doi:10.1111/rda.14274 · Cited by 7 · see citing works
Pantoja, M. H. D. A., Poleti, M., de Novais, F. J., Duarte, K. K. S., Mateescu, R. G., Mourão, G. B., Coutinho, L. L., Fukumasu, H., & Titto, C. G. (2023) · International Journal of Biometeorology · doi:10.1007/s00484-023-02602-4 · Cited by 7 · see citing works
Mancin, E., Maltecca, C., Jiang, J., Huang, Y., & Tiezzi, F. (2024) · BMC Genomics · doi:10.1186/s12864-024-11052-0 · Cited by 6 · see citing works
Singh, A., Verma, A., Dutta, G., Gowane, G. R., Ludri, A., & Alex, R. (2024) · 3 Biotech · doi:10.1007/s13205-024-04018-2 · Cited by 5 · see citing works
Fathoni, A., Boonkum, W., Chankitisakul, V., Buaban, S., & Duangjinda, M. (2024) · Animals · doi:10.3390/ani15010043 · Cited by 5 · see citing works
Papo, M. L., Ncube, K. T., Lashmar, S. F., Modiba, M. C., & Mtileni, B. J. (2026) · Animals · doi:10.3390/ani16060947 · Cited by 4 · see citing works
Xiang, R., Breen, E. J., Bolormaa, S., Liu, Z., Jagt, C. J. V., Dong, M. X., Lindblad‐Toh, K., Rochfort, S. J., Pryce, J. E., Chamberlain, A. J., et al. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2514736122 · Cited by 4 · see citing works
Self-citationPersichilli, C., Biffani, S., Senczuk, G., Civita, M. D., Bitew, M. K., Bosco, A., Rinaldi, L., Grande, S., Cringoli, G., & Pilla, F. (2024) · animal · doi:10.1016/j.animal.2024.101403 · Cited by 4 · see citing works
Heat stress of dairy cows in Serbia: Review
Cincović, M., Majkić, M., Spasojević, J., Hristov, S., Stanković, B. M., Nakov, D., Nikolić, S., & Stanojević, J. (2023) · Acta agriculturae Serbica · doi:10.5937/aaser2356107c · Cited by 4 · see citing works
Chessari, G., Reich, P., Criscione, A., Falker‐Gieske, C., Mastrangelo, S., Tumino, S., Bordonaro, S., Marletta, D., & Tetens, J. (2025) · BMC Genomics · doi:10.1186/s12864-025-12256-8 · Cited by 3 · see citing works
Wang, W., Shi, Y., He, F., Fang, D., Gan, J., Wu, F., Yueda, A. G., Deng, X., Cao, Q., Duo, C., et al. (2022) · Animals · doi:10.3390/ani12233239 · Cited by 3 · see citing works
Lu, T., Li, L., Li, Y., & Li, X. (2023) · The Journal of Poultry Science · doi:10.2141/jpsa.2023012 · Cited by 3 · see citing works
Atalay, S., & Kök, S. (2023) · Kafkas Universitesi Veteriner Fakultesi Dergisi · doi:10.9775/kvfd.2023.29256 · Cited by 3 · see citing works
Ogawa, S., Okamura, T., Fukuzawa, Y., Nishio, M., Ishii, K., Kimata, M., Tomiyama, M., & Satoh, M. (2024) · Journal of Animal Breeding and Genetics · doi:10.1111/jbg.12871 · Cited by 2 · see citing works
Marshall, A. C., Lopez-Villalobos, N., Vigolo, V., MARCHI, M. D., Loveday, S. M., Weeks, M., & McNabb, W. C. (2025) · Animal Biotechnology · doi:10.1080/10495398.2025.2516688 · Cited by 2 · see citing works
Bolormaa, S., MacLeod, I. M., Xiang, R., Goddard, M. E., Pryce, J. E., & Haile‐Mariam, M. (2026) · Journal of Dairy Science · doi:10.3168/jds.2025-27314 · Cited by 2 · see citing works
Self-citationMacPhillamy, C., Ren, Y. X., Chen, T., Hiendleder, S., & Low, W. Y. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1329939 · Cited by 2 · see citing works
An AI-based hybrid model for dairy cattle heat tolerance phenotype
Chlingaryan, A., Thomson, P. C., Garcia, S. C., & Clark, C. (2025) · Smart Agricultural Technology · doi:10.1016/j.atech.2025.101455 · Cited by 2 · see citing works
The Genomic Landscape of Cattle: Domestication, Dispersal, and Adaptive Evolution
Liu, Y., Dao, W., Gao, R., Fan, X., Yang, R., & Miao, Y. (2026) · Animals · doi:10.3390/ani16050776 · Cited by 1 · see citing works
Hasbi, H., Putra, W. P. B., Maulana, T., Agung, P. P., Said, S., Sonjaya, H., Baco, S., Gustina, S., Duma, Y., Tanari, M., et al. (2023) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/1255/1/012039 · Cited by 1 · see citing works
Wen, H., Johnson, J. S., Mulim, H. A., Araujo, A. C., de Carvalho, F. E., Rocha, A. O., Huang, Y., Tiezzi, F., Maltecca, C., Schinckel, A. P., et al. (2024) · Frontiers in Genetics · doi:10.3389/fgene.2024.1498380 · Cited by 1 · see citing works
Candidate genes and genomic regions relevant for adaptation to extreme climates in livestock
Cheruiyot, E. K., Negussie, E., Tarekegn, G. M., & Haile‐Mariam, M. (2025) · CABI Reviews · doi:10.1079/cabireviews.2025.0052 · Cited by 1 · see citing works
Self-citationМолекулярные маркеры адаптации к холодному климату у крупного рогатого скота
Н.С, Ю. (2023) · Письма в Вавиловский журнал генетики и селекции · doi:10.18699/lettersvj-2023-9-02 · Cited by 2 · see citing works
Pryce, J. E. (2022) · Springer eBooks · doi:10.1007/978-1-4939-2493-6_1117-1
Self-citationPryce, J. E. (2022) · Encyclopedia of sustainability science and technology series · doi:10.1007/978-1-0716-2460-9_1117
Self-citation214. Are autozygosity estimates from imputed genotypes reliable?
Ferenčaković, M., Čurik, I., Garcia, J. F., Sölkner, J., & Carvalheiro, R. (2022) · World Congress on Genetics Applied to Livestock Production (WCGALP) · doi:10.3920/978-90-8686-940-4_214
RETRACTED: Influence of heat resistance on reproduction and productivity of Red Dairy Breed cows
Kosov, V. A., Khrystenko, V., Tresnitskiy, S. N., Tresnitskiy, A., & Rudenko, A. A. (2024) · BIO Web of Conferences · doi:10.1051/bioconf/20248401047
RetractedRoudbari, Z., Eskandarynasab, S., Mohamadabadi, M., & Mokhtari, M. (2024) · Annual report. · doi:10.61186/rap.15.2.11
Food Security Through Sustainable Livestock Production
Biswas, B. K., & Das, S. K. (2024) · CABI climate change series. · doi:10.1079/9781800625037.0007
Genome-environment association analysis reveals climate-driven adaptation of chickens
Zhao, X., Zhang, J.-X., Wen, J.-H., Zhang, X., Li, H., Wang, H., Zhu, T., Nie, C.-S., Li, X.-H., Yang, W.-F., et al. (2025) · Genetics Selection Evolution · doi:10.1186/s12711-025-00989-9
Dikmen, S., Vukasinovic, N., Sanchez-Castro, M. A., & Hansen, P. J. (2025) · Journal of Animal Science · doi:10.1093/jas/skaf386
Jemaa, S. B., Senczuk, G., Persichilli, C., Negro, A., Carta, F., Riggio, S., Sardina, M. T., Cesarani, A., & Mastrangelo, S. (2025) · animal · doi:10.1016/j.animal.2025.101723
Reich, P., Möller, S., Stock, K. F., Nolte, W., Prondzinski, M. V. D., Reents, R., Kalm, E., Kühn, C., Thaller, G., Falker‐Gieske, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26733487
Reich, P., Möller, S., Stock, K. F., Nolte, W., Prondzinski, M. V. D., Reents, R., Kalm, E., Kühn, C., Thaller, G., Falker‐Gieske, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26733481
Wen, H., Johnson, J. S., Freitas, P. H. F., Maskal, J. M., Gloria, L. S., Araujo, A. C., Pedrosa, V. B., Tiezzi, F., Maltecca, C., Huang, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26657230
Wen, H., Johnson, J. S., Freitas, P. H. F., Maskal, J. M., Gloria, L. S., Araujo, A. C., Pedrosa, V. B., Tiezzi, F., Maltecca, C., Huang, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26657233
Reich, P., Möller, S., Stock, K. F., Nolte, W., Prondzinski, M. V. D., Reents, R., Kalm, E., Kühn, C., Thaller, G., Falker‐Gieske, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26036534
Reich, P., Möller, S., Stock, K. F., Nolte, W., Prondzinski, M. V. D., Reents, R., Kalm, E., Kühn, C., Thaller, G., Falker‐Gieske, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26733493
Reich, P., Möller, S., Stock, K. F., Nolte, W., Prondzinski, M. V. D., Reents, R., Kalm, E., Kühn, C., Thaller, G., Falker‐Gieske, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26733466
Wen, H., Johnson, J. S., Freitas, P. H. F., Maskal, J. M., Gloria, L. S., Araujo, A. C., Pedrosa, V. B., Tiezzi, F., Maltecca, C., Huang, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26657236
Reich, P., Möller, S., Stock, K. F., Nolte, W., Prondzinski, M. V. D., Reents, R., Kalm, E., Kühn, C., Thaller, G., Falker‐Gieske, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26733478
Reich, P., Möller, S., Stock, K. F., Nolte, W., Prondzinski, M. V. D., Reents, R., Kalm, E., Kühn, C., Thaller, G., Falker‐Gieske, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26733469
Reich, P., Möller, S., Stock, K. F., Nolte, W., Prondzinski, M. V. D., Reents, R., Kalm, E., Kühn, C., Thaller, G., Falker‐Gieske, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26733475
Reich, P., Möller, S., Stock, K. F., Nolte, W., Prondzinski, M. V. D., Reents, R., Kalm, E., Kühn, C., Thaller, G., Falker‐Gieske, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26733472
Reich, P., Möller, S., Stock, K. F., Nolte, W., Prondzinski, M. V. D., Reents, R., Kalm, E., Kühn, C., Thaller, G., Falker‐Gieske, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26036470
Reich, P., Möller, S., Stock, K. F., Nolte, W., Prondzinski, M. V. D., Reents, R., Kalm, E., Kühn, C., Thaller, G., Falker‐Gieske, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26733490
Reich, P., Möller, S., Stock, K. F., Nolte, W., Prondzinski, M. V. D., Reents, R., Kalm, E., Kühn, C., Thaller, G., Falker‐Gieske, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26733484
Worth, G. M., Donkersloot, E. G., Spaans, O. K., Spelman, R. J., & Davis, S. R. (2026) · Journal of Dairy Science · doi:10.3168/jds.2025-26976
Kyrgiafini, M.-A., Giannoulis, T., Nanas, I., Dovolou, E., Amiridis, G. S., & Mamuris, Z. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6388995
Silva, E. F. P., Gaia, R. C., Mulim, H. A., Pinto, L. F. B., Iung, L. H. D. S., Brito, L. F., & Pedrosa, V. B. (2026) · Animals · doi:10.3390/ani16111652
Giannoulis, T., Dovolou, E., Mamuris, Z., & Amiridis, G. S. (2026) · Biology · doi:10.3390/biology15120918
Ou, K., Zheng, K., Teng, J., Li, Y., Zhang, Q., Ning, C., & Wang, D. (2026) · Animals · doi:10.3390/ani16152379
Pisarenko, A. V., & Pisarenko, N. B. (2026) · Siberian Herald of Agricultural Science · doi:10.26898/0370-8799-2026-7-7
Ratto, R., Pietrucci, D., Mecocci, S., Alonso‐Hearn, M., Badia-Bringué, G., Acuti, G., Renzi, F., Gabbianelli, F., Bergagna, S., Guasco, C., et al. (2026) · Frontiers in Veterinary Science · doi:10.3389/fvets.2026.1895058
Taherkhani, L., Banabazi, M. H., & Moradi, J. M. (2026) · Research Square · doi:10.21203/rs.3.rs-10751809/v1
- Authors
- Cheruiyot, E. K., Haile-Mariam, M., Cocks, B. G., MacLeod, I. M., Xiang, R., & Pryce, J. E.
- Affiliations
- La Trobe University (AU)
- Agriculture Victoria (AU)
- The University of Melbourne (AU)
- Venue
- Scientific Reports
- Published
- 2021-08-17
- Volume
- 11
- Issue
- 1
- Pages
- 16619-16619
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC8371109
- OpenAlex
- W3194261773
- Cited by
- 81
- References
- 83
- Citations by year
- 2026: 11 · 2025: 11 · 2024: 22 · 2023: 21 · 2022: 12 · 2021: 3 · 2016: 1
- FWCI
- 11.39
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Reports (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- La Trobe University (cc-by)
- Funders
- DairyBio
- Dairy Australia
- Gardiner Foundation
- Agriculture Victoria
- Topics
- Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Effects of Environmental Stressors on Livestock
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- heat tolerance, heat stress, dairy cattle, Holstein cows, milk production decline, temperature-humidity index, genome-wide association study, novel loci, neural pathways, IP3R1, ITPR2, GRIA4, calcitonin receptor, growth hormone receptor, lactation
- MeSH terms
- Adaptation, Physiological, Animals, Cattle, Chromosome Mapping, Neurons, Phenotype, Heat-Shock Response, Polymorphism, Single Nucleotide, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
