[
Bernabucci U., Lacetera N., Danieli P.P., Bani P., Nardone A., Ronchi B. (2009). Influence of different periods of exposure to hot environment on rumen function and diet digestibility in sheep. Int. J. Biometeorol., 53: 387–395.
]Search in Google Scholar
[
Bernabucci U., Lacetera N., Baumgard L.H., Rhoads R.P., Ronchi B., Nardone A. (2010). Metabolic and hormonal acclimation to heat stress in domesticated ruminants. Animal, 4: 1167–1183.
]Search in Google Scholar
[
Bicalho M.L.S., Machado V.S., Higgins C.H., Lima F.S., Bicalho R.C. (2017). Genetic and functional analysis of the bovine uterine microbiota. Part I: Metritis versus healthy cows. J. Dairy Sci., 100: 3850–3862.
]Search in Google Scholar
[
Biscarini F., Palazzo F., Castellani F., Masetti G., Grotta L., Cichelli A., Martino, G. (2018). Rumen microbiome in dairy calves fed copper and grape-pomace dietary supplementations: Composition and predicted functional profile. PLoS One, 13: e0205670.
]Search in Google Scholar
[
Chaidanya K., Soren N.M., Sejian V., Bagath M., Manjunathareddy G.B., Kurien K.E., Varma G., Bhatta R. (2017). Impact of heat stress, nutritional stress and combined (heat and nutritional) stresses on rumen associated fermentation characteristics, histopathology and HSP70 gene expression in goats. J. Anim. Behav. Biometerol., 5: 36–48.
]Search in Google Scholar
[
Chen S., Wang J., Peng D., Li G., Chen J., Gu X. (2018). Exposure to heat-stress environment affects the physiology, circulation levels of cytokines, and microbiome in dairy cows. Sci. Rep., 8: 14606.
]Search in Google Scholar
[
Cholewińska P., Górniak W., Wojnarowski K. (2021). Impact of selected environmental factors on microbiome of the digestive tract of ruminants. BMC Vet. Res., 17: 25.
]Search in Google Scholar
[
Contreras-Jodar A., Nayan N.H., Hamzaoui S., Caja G., Salama A.A. (2019). Heat stress modifies the lactational performances and the urinary metabolomic profile related to gastrointestinal microbiota of dairy goats. PLoS One, 14(2), e0202457.
]Search in Google Scholar
[
Correia Sales, G.F., Carvalho, B.F., Schwan, R.F., de Figueiredo Vilela, L., Meneses, J.A.M., Gionbelli, M.P. and da Silva Avila, C.L. (2021). Heat stress influence the microbiota and organic acids concentration in beef cattle rumen. J. Therm. Biol., 97: 102897.
]Search in Google Scholar
[
Cui Y., Qi J., Cai D., Fang J., Xie Y., Guo H., Chen S., Ma X., Gou L., Cui H., Geng, Y. (2021). Metagenomics Reveals That Proper Placement After Long-Distance Transportation Significantly Affects Calf Nasopharyngeal Microbiota and Is Critical for the Prevention of Respiratory Diseases. Front. Microbiol., 12: 700704.
]Search in Google Scholar
[
Czech B., Szyda J., Wang K., Luo H., Wang Y. (2022) Fecal microbiota and their association with heat stress in Bos taurus. BMC Microbiol., 22: 171.
]Search in Google Scholar
[
Dean C.J., Slizovskiy I.B., Crone K.K., Pfennig A.X., Heins B.J., Caixeta L.S., Noyes N.R. (2021). Investigating the cow skin and teat canal microbiomes of the bovine udder using different sampling and sequencing approaches. J. Dairy Sci., 104: 644–661.
]Search in Google Scholar
[
Eom J.S., Lee S.J., Gu B.H., Lee S.J., Lee S.S., Kim S.H., Kim B.W., Lee S.S., Kim M. (2022). Metabolomic and transcriptomic study to understand changes in metabolic and immune responses in steers under heat stress. Anim. Nutr., 11: 87–101.
]Search in Google Scholar
[
Fievez V., Vlaeminck B., Dhanoa M.S., Dewhurst R.J. (2003). Use of principal component analysis to investigate the origin of heptadecenoic and conjugated linoleic acids in milk. J. Dairy Sci., 86: 4047–4053.
]Search in Google Scholar
[
Flint H.J., Bayer E.A., Rincon M.T., Lamed R., White B.A. (2008). Polysaccharide utilization by gut bacteria: potential for new insights from genomic analysis. Nat. Rev. Microbiol., 6: 121–131.
]Search in Google Scholar
[
Gaafar H.M.A., El-Din A.M. a. M., Basiuoni M.I., El-Riedy K.F.A. (2009). Effect of concentrate to roughage ratio and baker’s yeast supplementation during hot season on performance of lactating buffaloes. Slovak J. Anim. Sci., 42: 188–195
]Search in Google Scholar
[
Galperin M.Y., Koonin E.V. (2000). Who’s your neighbor? New computational approaches for functional genomics. Nat. Biotechnol., 18: 609–613.
]Search in Google Scholar
[
He H., Fang C., Liu L., Li M., Liu W. (2024). Environmental Driving of Adaptation Mechanism on Rumen Microorganisms of Sheep Based on Metagenomics and Metabolomics Data Analysis. Int. J. Mol. Sci., 25: 10957.
]Search in Google Scholar
[
Hoque M.N., Istiaq A., Clement R.A., Sultana M., Crandall K.A., Siddiki A.Z., Hossain M.A. (2019). Metagenomic deep sequencing reveals association of microbiome signature with functional biases in bovine mastitis. Sci. Rep., 9: 13536.
]Search in Google Scholar
[
Iqbal M.W., Zhang Q., Yang Y., Li L., Zou C., Huang C., Lin B. (2018). Comparative study of rumen fermentation and microbial community differences between water buffalo and Jersey cows under similar feeding conditions. J. Appl. Anim. Res., 46: 740–748.
]Search in Google Scholar
[
Islam M., Kim S.H., Son A.R., Ramos S.C., Jeong C.D., Yu Z., Kang S.H., Cho Y.I., Lee S.S., Cho K.K., Lee S.S. (2021). Seasonal Influence on Rumen Microbiota, Rumen Fermentation, and Enteric Methane Emissions of Holstein and Jersey Steers under the Same Total Mixed Ration. Animals, 11: 1184.
]Search in Google Scholar
[
Islam M., Lee S.S. (2018). Recent application technologies of rumen microbiome is the key to enhance feed fermentation. J. Life Sci., 28: 1244–1253.
]Search in Google Scholar
[
Jami E., White B.A., Mizrahi I. (2014). Potential role of the bovine rumen microbiome in modulating milk composition and feed efficiency. PLoS One, 9: e85423.
]Search in Google Scholar
[
Jolliffe I.T., Cadima J. (2016). Principal component analysis: a review and recent developments. Phil. Trans. R. Soc. A., 374: 20150202.
]Search in Google Scholar
[
Kamra D.N. (2005). Rumen microbial ecosystem. Curr. Sci., 89:124–135.
]Search in Google Scholar
[
Kanehisa M. (2000). KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res., 28: 27–30.
]Search in Google Scholar
[
Kim D.H., Kim M.H., Kim S.B., Ha S.M., Son J.K., Lee J.H., Hur T.Y., Lee J.Y., Park J.H., Choi H.C., Lee H.J. (2019). Effects of heat-stress on rumen bacterial diversity and composition of Holstein cows. J. Kor. Grassl. Forage Sci., 39: 227–234.
]Search in Google Scholar
[
Kim D.H., Kim M.H., Kim S.B., Son J.K., Lee J.H., Joo S.S., Gu B.H., Park T., Park B.Y., Kim, E.T. (2020). Differential dynamics of the ruminal microbiome of Jersey cows in a heat stress environment. Animals, 10: 1127.
]Search in Google Scholar
[
Kim S.H., Ramos S.C., Valencia R.A., Cho Y.I., Lee S.S. (2022). Heat stress: effects on rumen microbes and host physiology, and strategies to alleviate the negative impacts on lactating dairy cows. Front. Microbiol., 13: 804562.
]Search in Google Scholar
[
Kocherginskaya S., Aminov R., White B. (2001). Analysis of the Rumen Bacterial Diversity under two Different Diet Conditions using Denaturing Gradient Gel Electrophoresis, Random Sequencing, and Statistical Ecology Approaches. Anaerobe, 7: 119–134.
]Search in Google Scholar
[
Krause D.O., Nagaraja T.G., Wright A.D.G., Callaway T.R. (2013). Board-invited review: Rumen microbiology: Leading the way in microbial ecology1,2. J. Anim. Sci., 91: 331–341.
]Search in Google Scholar
[
Krishnan G., Silpa M.V., Sejian, V. (2023). Environmental physiology and thermoregulation in farm animals. In: Das P.K., Sejian V., Mukherjee J., Banerjee D. (eds). Textbook of Veterinary Physiology. Springer, Singapore, pp. 723–749.
]Search in Google Scholar
[
Lees A.M., Lees J.C., Lisle A.T., Sullivan M.L., Gaughan J.B. (2018). Effect of heat stress on rumen temperature of three breeds of cattle. Int. J. Biomet., 62: 207–215.
]Search in Google Scholar
[
Li L., Wang Y., Li C., Wang G. (2017). Proteomic analysis to unravel the effect of heat stress on gene expression and milk synthesis in bovine mammary epithelial cells. Anim. Sci. J., 88: 2090–2099.
]Search in Google Scholar
[
Li Y., Zang Y., Zhao X., Liu L., Qiu Q., Ouyang K., Qu M. (2021). Dietary supplementation with creatine pyruvate alters rumen microbiota protein function in heat-stressed beef cattle. Front. Microbiol., 12: 715088.
]Search in Google Scholar
[
Liu J., Taft D.H., Maldonado-Gomez M.X., Johnson D., Treiber M.L., Lemay D.G., DePeters E.J., Mills D.A. (2019). The fecal resistome of dairy cattle is associated with diet during nursing. Nat. Commun., 10: 4406.
]Search in Google Scholar
[
Liu X., Sha Y., Dingkao R., Zhang W., Lv W., Wei H., Shi H., Hu J., Wang J., Li S., Hao Z. (2020). Interactions between rumen microbes, VFAs, and host genes regulate nutrient absorption and epithelial barrier function during cold season nutritional stress in Tibetan sheep. Front. Microbiol., 11: 593062.
]Search in Google Scholar
[
Lv W., Liu X., Sha Y., Shi H., Wei H., Luo Y., Wang J., Li S., Hu J., Guo X., Pu X. (2021). Rumen fermentation – microbiota – host gene expression interactions to reveal the adaptability of Tibetan sheep in different periods. Animals, 11: 3529.
]Search in Google Scholar
[
Matthews C., Crispie F., Lewis E., Reid M., O’Toole P.W., Cotter P.D. (2019). The rumen microbiome: a crucial consideration when optimising milk and meat production and nitrogen utilisation efficiency. Gut Microb., 10: 115–132.
]Search in Google Scholar
[
Mayorga O.L., Kingston-Smith A.H., Kim E.J., Allison G.G., Wilkinson T.J., Hegarty M.J., Theodorou M.K., Newbold C.J., Huws S.A. (2016). Temporal metagenomic and metabolomic characterization of fresh perennial ryegrass degradation by rumen bacteria. Front. Microbiol., 7: 1854.
]Search in Google Scholar
[
McGovern E., Waters S.M., Blackshields G., McCabe M.S. (2018). Evaluating established methods for rumen 16S rRNA amplicon sequencing with mock microbial populations. Front. Microbiol., 9: 1365.
]Search in Google Scholar
[
McManus C., Paludo G.R., Louvandini H., Gugel R., Sasaki L.C.B. and Paiva S.R. (2009). Heat tolerance in Brazilian sheep: Physiological and blood parameters. Trop. Anim. Health Prod., 41: 95–101.
]Search in Google Scholar
[
Morgavi D.P., Forano E., Martin C., Newbold C.J. (2010). Microbial ecosystem and methanogenesis in ruminants. Animal, 4: 1024–1036.
]Search in Google Scholar
[
Morrison S.R. (1983). Ruminant heat stress: effect on production and means of alleviation. J. Anim. Sci., 57: 1594–1600.
]Search in Google Scholar
[
Naqvi S., Sejian V. (2011). Global climate change: role of livestock. Asian J. Agric. Sci., 3: 19-25.
]Search in Google Scholar
[
Natale D.A., Shankavaram U.T., Galperin M.Y., Wolf Y.I., Aravind L., Koonin E.V. (2000). Towards understanding the first genome sequence of a crenarchaeon by genome annotation using clusters of orthologous groups of proteins (COGs). Genome Biol., 1:0009.1.
]Search in Google Scholar
[
Nonaka I., Takusari N., Tajima K., Suzuki T., Higuchi K., Kurihara M. (2008). Effects of high environmental temperatures on physiological and nutritional status of prepubertal Holstein heifers. Livest. Sci., 113: 14–23.
]Search in Google Scholar
[
Pragna P., Sejian V., Bagath M., Krishnan G., Archana P.R., Soren N.M., Beena V. and Bhatta R. (2018) Comparative assessment of growth performance of three different indigenous goat breeds exposed to summer heat stress. J. Anim. Physiol. Anim. Nutr., 102: 825–836.
]Search in Google Scholar
[
Premathilake H.U. (2021). Elucidation of structural and functional characteristics of the gut microbiome of beef cattle under water stress. Thesis, The Oklahoma State University.
]Search in Google Scholar
[
Provolo G., Riva E. (2009). One year study of lying and standing behaviour of dairy cows an a frestall barn in Italy. J. Agric. Eng., 40: 27–34.
]Search in Google Scholar
[
Ranjan R., Rani A., Metwally A., McGee H.S., Perkins D.L. (2016). Analysis of the microbiome: Advantages of whole genome shotgun versus 16S amplicon sequencing. Biochem. Biophys. Res. Commun., 469: 967–977.
]Search in Google Scholar
[
Reddy B., Singh K.M., Patel A.K., Antony A., Panchasara H.J., Joshi C.G. (2014). Insights into resistome and stress responses genes in Bubalus bubalis rumen through metagenomic analysis. Mol. Biol. Rep., 41: 6405–6417.
]Search in Google Scholar
[
Rojas-Downing M.M., Nejadhashemi A.P., Harrigan T., Woznicki S.A. (2017). Climate change and livestock: Impacts, adaptation, and mitigation. Clim. Risk Manag., 16: 145–163.
]Search in Google Scholar
[
Sanschagrin S., Yergeau E. (2014). Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons. J. Vis. Exp., 90: 51709.
]Search in Google Scholar
[
Sejian V., Maurya V.P., Naqvi S.M.K., Kumar D., Joshi A. (2010). Effect of induced body condition score differences on physiological response, productive and reproductive performance of Malpura ewes kept in a hot, semi-arid environment. J. Anim. Physiol. Anim. Nutr., 94: 154–161.
]Search in Google Scholar
[
Sejian V., Bhatta R., Gaughan J.B., Dunshea F.R., Lacetera N. (2018). Review: Adaptation of animals to heat stress. Animal, 12: s431–s444.
]Search in Google Scholar
[
Sejian V., Chauhan S.S., Devaraj C., Malik P.K., Vadhana E., Silpa M.V., Shashank C.G. and Bhatta R. (2021 c). Future vision for climate change associated livestock production. In: Climate change and livestock production: recent advances and future perspectives, Sejian V., Chauhan S.S., Devaraj C., Malik P.K., Bhatta R. (eds). Springer, Singapore, pp. 293–306.
]Search in Google Scholar
[
Sejian V., Silpa M.V., Lees A.M., Krishnan G., Devaraj C., Bagath M., Anisha J.P., Reshma Nair M.R., Manimaran A., Bhatta R., Gaughan J.B. (2021 a). Opportunities, challenges, and ecological footprint of sustaining small ruminant production in the changing climate scenario. In: Agroecological footprints management for sustainable food system, Banerjee A., Meena R.S., Jhariya M.K., Yadav D.K. (eds). Springer, Singapore, pp. 365–396.
]Search in Google Scholar
[
Sejian V., Silpa M.V., Devaraj C., Trivedi S., Ezhil Vadhana P., Ruban W., Suganthi R.U., Manimaran A., Maurya V.P., Bhatta R. (2021 b). Impact of climate change on animal production and welfare. In: Climate change and livestock production: recent advances and future perspectives, Sejian V., Chauhan S.S., Devaraj C., Malik P.K., Bhatta R. (eds). Springer, Singapore, pp. 3–14.
]Search in Google Scholar
[
Sha Y., Hu J., Shi B., Dingkao R., Wang J., Li S., Zhang W., Luo Y., Liu X. (2021). Supplementary feeding of cattle-yak in the cold season alters rumen microbes, volatile fatty acids, and expression of SGLT1 in the rumen epithelium. Peer. J., 9: e11048.
]Search in Google Scholar
[
Shilja S., Sejian V., Bagath M., Mech A., David C.G., Kurien E.K., Varma G., Bhatta R. (2016). Adaptive capability as indicated by behavioral and physiological responses, plasma HSP70 level, and PBMC HSP70 mRNA expression in Osmanabadi goats subjected to combined (heat and nutritional) stressors. Int. J. Biometeorol., 60: 1311–1323.
]Search in Google Scholar
[
Silanikove N. (2000). The physiological basis of adaptation in goats to harsh environments. Small Rumin. Res., 35: 181–193.
]Search in Google Scholar
[
Tajima K., Aminov R.I., Nagamine T., Matsui H., Nakamura M., Benno Y. (2001). Diet-Dependent Shifts in the Bacterial Population of the Rumen Revealed with Real-Time PCR. Appl. Environ. Microbiol., 67: 2766–2774.
]Search in Google Scholar
[
Thirumalesh T., Krishnamoorthy U. (2013). Rumen microbial biomass synthesis and its importance in ruminant production. Int. J. Livest. Res., 3: 5–26.
]Search in Google Scholar
[
Thukral A. (2017). A review on measurement of Alpha diversity in biology. Agric. Res. J., 54: 1.
]Search in Google Scholar
[
Tian H., Wang W., Zheng N., Cheng J., Li S., Zhang Y., Wang J. (2015). Identification of diagnostic biomarkers and metabolic pathway shifts of heat-stressed lactating dairy cows. J. Proteom., 125: 17–28.
]Search in Google Scholar
[
Poretsky R., Rodriguez-R L.M., Luo C., Tsementzi D., Konstantinidis K.T. (2014). Strengths and limitations of 16S rRNA gene amplicon sequencing in revealing temporal microbial community dynamics. PLoS One, 9: e93827.
]Search in Google Scholar
[
Uyeno Y. (2021). Heat stress on the rumen fermentation and its consequence. In: Climate change and livestock production: recent advances and future perspectives, Sejian V., Chauhan S.S., Devaraj C., Malik P.K., Bhatta R. (eds). Springer, Singapore, pp. 213–221.
]Search in Google Scholar
[
Uyeno Y., Sekiguchi Y., Tajima K., Takenaka A., Kurihara M., Kamagata Y. (2010). An rRNA-based analysis for evaluating the effect of heat stress on the rumen microbial composition of Holstein heifers. Anaerobe, 16: 27–33.
]Search in Google Scholar
[
Wang X., Li X., Zhao C., Hu P., Chen H., Liu Z., Liu G., Wang Z. (2012). Correlation between composition of the bacterial community and concentration of volatile fatty acids in the rumen during the transition period and ketosis in dairy cows. Appl. Environ. Microbiol., 78: 2386–2392.
]Search in Google Scholar
[
Wang J., Li J., Wang F., Xiao J., Wang Y., Yang H., Li S., Cao Z. (2020). Heat stress on calves and heifers: a review. J. Anim. Sci. Biotechnol., 11: 1–8.
]Search in Google Scholar
[
Wang Z., Liu L., Pang F., Zheng Z., Teng Z., Miao T., Fu T., Rushdi H.E., Yang L., Gao T., Lin F. (2022). Novel insights into heat tolerance using metabolomic and high-throughput sequencing analysis in dairy cows rumen fluid. Animal, 16: 100478.
]Search in Google Scholar
[
Wang Z., Niu K., Rushdi H.E., Zhang M., Fu T., Gao T., Yang L., Liu S., Lin F. (2022). Heat stress induces shifts in the rumen bacteria and metabolome of buffalo. Animals, 12: 1300.
]Search in Google Scholar
[
Weng H., Zeng H., Wang H., Chang H., Zhai Y., Li S., Han Z. (2024). Differences in lactation performance, rumen microbiome, and metabolome between Montbéliarde× Holstein and Holstein cows under heat stress. Microorganisms, 12: 1729.
]Search in Google Scholar
[
Willis A.D. (2019). Rarefaction, alpha diversity, and statistics. Front. Microbiol., 10: 2407.
]Search in Google Scholar
[
Xie F., Jin W., Si H., Yuan Y., Tao Y., Liu J., Wang X., Yang C., Li Q., Yan X., Lin L. (2021). An integrated gene catalog and over 10,000 metagenome-assembled genomes from the gastrointestinal microbiome of ruminants. Microbiome, 9: 137.
]Search in Google Scholar
[
Yue S., Ding S., Zhou J., Yang C., Hu X., Zhao X., Wang Z., Wang L., Peng Q., Xue B. (2020). Metabolomics approach explore diagnostic biomarkers and metabolic changes in heat-stressed dairy cows. Animals, 10: 1741.
]Search in Google Scholar
[
Zhao S., Min L., Zheng N., Wang J. (2019). Effect of heat stress on bacterial composition and metabolism in the rumen of lactating dairy cows. Animals, 9: 925.
]Search in Google Scholar
[
Zhong S., Ding Y., Wang Y., Zhou G., Guo H., Chen Y., Yang Y. (2019). Temperature and humidity index (THI)-induced rumen bacterial community changes in goats. Appl. Microbiol. Biotechnol., 103: 3193–3203.
]Search in Google Scholar
[
Zhou M., O’Hara E., Tang S., Chen Y., Walpole M.E., Górka P., Penner G.B., Guan L.L. (2021). Accessing dietary effects on the rumen microbiome: different sequencing methods tell different stories. Vet. Sci., 8: 138.
]Search in Google Scholar
