{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T12:30:21Z","timestamp":1786624221341,"version":"build-2736575974"},"reference-count":29,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T00:00:00Z","timestamp":1786579200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008871","name":"Yunnan Major Science and Technology Special Project","doi-asserted-by":"publisher","award":["202602AE090078"],"award-info":[{"award-number":["202602AE090078"]}],"id":[{"id":"10.13039\/501100008871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genes"],"abstract":"<jats:p>Background\/Objectives: Bovine heat-stress RNA-seq studies differ in tissue, age, physiological state, and exposure design. We asked which responses recur across these contexts and which depend on the evidence base. Methods: We reprocessed 107 libraries from five in vivo Bos taurus studies and synthesized within-study heat-minus-control log2 fold changes using restricted maximum-likelihood random-effects models with modified Knapp\u2013Hartung inference. Eight tissue- and age-aware scenarios tested the cross-context estimate. A six-component heat-stress transcriptomic stability index (HSTSI) was benchmarked against five simpler rankings, and an independent mammary single-nucleus dataset provided cell-resolved comparison. Results: Of 266 FDR-significant pathways, 259 retained direction across all five study deletions and 21 remained significant in every deletion. Translation, ribosome, protein folding, endoplasmic-reticulum processing, proteasome, and heat-response programs formed the most recurrent axis. Four principal sensitivity scenarios retained 0.920\u20130.932 gene-direction agreement and 0.957\u20130.981 effect-rank correlation with the five-study analysis. In the single-nucleus dataset, leading-edge genes from the principal proteostasis programs showed 89.4\u2013100% pooled-nucleus direction agreement and 94.7\u2013100% agreement among published cluster-level differentially expressed genes. HSTSI had the highest mean top-200 held-out direction agreement (0.583 versus 0.516\u20130.562), with variation among folds. None of 16,756 genes met a modified Knapp\u2013Hartung FDR below 0.10. IL1R2 and SDCBP2 were externally concordant, whereas GZMK and CD8A were context-dependent. Conclusions: A coordinated proteostasis program was the most transferable heat-stress signal. Energy remodeling, immune-associated bulk signals, and individual genes showed greater context dependence and define priorities for tissue-matched follow-up.<\/jats:p>","DOI":"10.3390\/genes17080946","type":"journal-article","created":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T11:33:46Z","timestamp":1786620826000},"page":"946","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Study-Aware Meta-Analysis Reveals a Recurrent Proteostasis Program and Context-Dependent Gene-Level Responses in Bovine Heat-Stress Transcriptomes"],"prefix":"10.3390","volume":"17","author":[{"given":"Xiaotong","family":"Zhao","sequence":"first","affiliation":[{"name":"College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hua","family":"Chang","sequence":"additional","affiliation":[{"name":"College of Veterinary Medicine, Yunnan Agricultural University, Kunming 650201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quanpeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Kunming Animal Health Supervision Institute, Kunming 650041, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhuoyu","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sihui","family":"He","sequence":"additional","affiliation":[{"name":"College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zongyan","family":"Lu","sequence":"additional","affiliation":[{"name":"College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xun","family":"Xiang","sequence":"additional","affiliation":[{"name":"College of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3207","DOI":"10.3168\/jds.2023-24059","article-title":"Effects of Heat Stress on Feed Intake, Milk Yield, Milk Composition, and Feed Efficiency in Dairy Cows: A Meta-Analysis","volume":"107","author":"Chen","year":"2024","journal-title":"J. Dairy Sci."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Dahl, G.E., Tao, S., and Laporta, J. (2020). Heat Stress Impacts Immune Status in Cows Across the Life Cycle. Front. Vet. Sci., 7.","DOI":"10.3389\/fvets.2020.00116"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Cartwright, S.L., Schmied, J., Karrow, N., and Mallard, B.A. (2023). Impact of Heat Stress on Dairy Cattle and Selection Strategies for Thermotolerance: A Review. Front. Vet. Sci., 10.","DOI":"10.3389\/fvets.2023.1198697"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4471","DOI":"10.3168\/jds.2022-22727","article-title":"Invited Review: From Heat Stress to Disease\u2014Immune Response and Candidate Genes Involved in Cattle Thermotolerance","volume":"106","author":"Lemal","year":"2023","journal-title":"J. Dairy Sci."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Worku, D., Hussen, J., De Matteis, G., Schusser, B., and Alhussien, M.N. (2023). Candidate Genes Associated with Heat Stress and Breeding Strategies to Relieve Its Effects in Dairy Cattle: A Deeper Insight into the Genetic Architecture and Immune Response to Heat Stress. Front. Vet. Sci., 10.","DOI":"10.3389\/fvets.2023.1151241"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"11096","DOI":"10.1038\/s41598-018-29420-8","article-title":"RNA-Seq Reveals Novel Genes and Pathways Involved in Bovine Mammary Involution During the Dry Period and Under Environmental Heat Stress","volume":"8","author":"Skibiel","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1152\/physiolgenomics.00039.2019","article-title":"Heat Stress Negatively Affects the Transcriptome Related to Overall Metabolism and Milk Protein Synthesis in Mammary Tissue of Midlactating Dairy Cows","volume":"51","author":"Gao","year":"2019","journal-title":"Physiol. Genom."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"604","DOI":"10.3168\/jdsc.2025-0760","article-title":"Transcriptomic Changes Induced by Controlled Cyclical Heat Stress in the Bovine Mammary Gland During Lactation","volume":"6","author":"Ellett","year":"2025","journal-title":"JDS Commun."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Li, G., Yu, X., Portela Fontoura, A.B., Javaid, A., S\u00e1inz de la Maza-Escol\u00e0, V., Salandy, N.S., Fubini, S.L., Grilli, E., McFadden, J.W., and Duan, J.E. (2023). Transcriptomic Regulations of Heat Stress Response in the Liver of Lactating Dairy Cows. BMC Genom., 24.","DOI":"10.1186\/s12864-023-09484-1"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4390","DOI":"10.3168\/jds.2024-25975","article-title":"Preweaning Heat Stress Alters Liver Transcriptome and DNA Methylation in Dairy Calves","volume":"108","author":"Laporta","year":"2025","journal-title":"J. Dairy Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"103852","DOI":"10.1016\/j.jtherbio.2024.103852","article-title":"Skin Transcriptome Analysis in Brangus Cattle Under Heat Stress","volume":"121","author":"Balbi","year":"2024","journal-title":"J. Therm. Biol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"17021","DOI":"10.1038\/s41598-025-01082-3","article-title":"Heat Stress Induces Specific Methylation, Transcriptomic and Metabolic Pattern in Dairy Cows and Their Female Progeny","volume":"15","author":"Halli","year":"2025","journal-title":"Sci. Rep."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Koch, F., Viergutz, T., K\u00fchn, C., and Kuhla, B. (2025). Dynamic Immune and Molecular Responses to Chronic Heat Stress in Blood and Peripheral Blood Mononuclear Cells of Dairy Cows. Front. Immunol., 16.","DOI":"10.3389\/fimmu.2025.1633453"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1038\/s42003-026-10151-w","article-title":"Multi-Omics Dissection of Heat Stress Reveals CIITA as a Central Regulator of Metabolic Thermotolerance in Cattle (Bos taurus)","volume":"9","author":"Liu","year":"2026","journal-title":"Commun. Biol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1186\/s40104-026-01468-x","article-title":"Single-Nucleus RNA Sequencing Reveals Cell Type-Specific Responses to Heat Stress in Bovine Mammary Gland","volume":"17","author":"Yu","year":"2026","journal-title":"J. Anim. Sci. Biotechnol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"R\u00f6ver, C., Knapp, G., and Friede, T. (2015). Hartung\u2013Knapp\u2013Sidik\u2013Jonkman Approach and Its Modification for Random-Effects Meta-Analysis with Few Studies. BMC Med. Res. Methodol., 15.","DOI":"10.1186\/s12874-015-0091-1"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"e010247","DOI":"10.1136\/bmjopen-2015-010247","article-title":"Plea for Routinely Presenting Prediction Intervals in Meta-Analysis","volume":"6","author":"IntHout","year":"2016","journal-title":"BMJ Open"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1038\/nmeth.4197","article-title":"Salmon Provides Fast and Bias-Aware Quantification of Transcript Expression","volume":"14","author":"Patro","year":"2017","journal-title":"Nat. Methods"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1521","DOI":"10.12688\/f1000research.7563.2","article-title":"Differential Analyses for RNA-Seq: Transcript-Level Estimates Improve Gene-Level Inferences [version 2; peer review: 2 approved]","volume":"4","author":"Soneson","year":"2016","journal-title":"F1000Research"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"550","DOI":"10.1186\/s13059-014-0550-8","article-title":"Moderated Estimation of Fold Change and Dispersion for RNA-Seq Data with DESeq2","volume":"15","author":"Love","year":"2014","journal-title":"Genome Biol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v036.i03","article-title":"Conducting Meta-Analyses in R with the metafor Package","volume":"36","author":"Viechtbauer","year":"2010","journal-title":"J. Stat. Softw."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J. R. Stat. Soc. Ser. B Methodol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"15545","DOI":"10.1073\/pnas.0506580102","article-title":"Gene Set Enrichment Analysis: A Knowledge-Based Approach for Interpreting Genome-Wide Expression Profiles","volume":"102","author":"Subramanian","year":"2005","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_24","first-page":"100141","article-title":"clusterProfiler 4.0: A Universal Enrichment Tool for Interpreting Omics Data","volume":"2","author":"Wu","year":"2021","journal-title":"Innovation"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1152\/physiolgenomics.00127.2024","article-title":"Heat Stress and Recovery Induce Transcriptomic Changes in Lactogenic-Like Bovine Mammary Epithelial (MAC-T) Cells","volume":"57","author":"Yu","year":"2025","journal-title":"Physiol. Genom."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"104246","DOI":"10.1016\/j.jtherbio.2025.104246","article-title":"Characterization of Transcriptomic and Proteomic Changes in Bovine Myocytes Subject to Temporal Heat Stress","volume":"132","author":"Eckhardt","year":"2025","journal-title":"J. Therm. Biol."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Kim, H., Jo, J.-H., Lee, H.-G., Park, W., Lee, H.-K., Park, J.-E., and Shin, D. (2024). Inflammatory Response in Dairy Cows Caused by Heat Stress and Biological Mechanisms for Maintaining Homeostasis. PLoS ONE, 19.","DOI":"10.1371\/journal.pone.0300719"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Supino, D., Minute, L., Mariancini, A., Riva, F., Magrini, E., and Garlanda, C. (2022). Negative Regulation of the IL-1 System by IL-1R2 and IL-1R8: Relevance in Pathophysiology and Disease. Front. Immunol., 13.","DOI":"10.3389\/fimmu.2022.804641"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Xin, C., Liu, P., Zhan, Q., and Cao, W. (2025). GZMK+ CD8 T Cells in Inflammatory Diseases. Front. Immunol., 16.","DOI":"10.3389\/fimmu.2025.1661755"}],"container-title":["Genes"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-4425\/17\/8\/946\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T11:44:08Z","timestamp":1786621448000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-4425\/17\/8\/946"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,13]]},"references-count":29,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2026,8]]}},"alternative-id":["genes17080946"],"URL":"https:\/\/doi.org\/10.3390\/genes17080946","relation":{},"ISSN":["2073-4425"],"issn-type":[{"value":"2073-4425","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,13]]}}}