Antioxidants promote metabolic remodeling in cattle rumen epithelium revealed by single-cell resolution

Abstract

Oxygen signaling is essential for cellular homeostasis and tightly linked to metabolism, growth, and survival. In dairy cows, oxidative stress, arising from an imbalance between reactive oxygen species and antioxidants, is a major postpartum challenge that contributes to disease susceptibility. Using single-cell transcriptomes from 1,793,854 cells across 59 tissues, we analyzed oxygen signaling states within 1006 cellular clusters. The gastrointestinal tract (GIT) epithelium, particularly the forestomach, exhibits the strongest antioxidant activity, closely coupled to oxidative phosphorylation (OXPHOS) and glycolysis, with OXPHOS levels surpassing those of cardiomyocytes and hepatocytes (Cohen's d > 3.9, p < 0.001). Pseudotime and spatial transcriptomics demonstrated that both OXPHOS and antioxidant capacity increase progressively along the basal-to-luminal differentiation axis. Functional experiments in primary rumen epithelial cells showed that antioxidant supplementation or GPX1 modulation enhances mitochondrial respiration, boosts intracellular glutathione, and accelerates epithelial differentiation. Limited proteolysis-mass spectrometry (LiP-MS) analysis identified GPX1, GSTP1, COX7A2, and COX6B1 as candidate targets mediating antioxidant-driven metabolic remodeling. Together, these results reveal a redox-governed metabolic program in the forestomach epithelium and highlight antioxidant interventions as a potential strategy to support epithelial development and mitigate oxidative stress-related disorders in dairy cattle.

Keywords

antioxidant mechanisms / dairy cows / rumen epithelial cells / single-cell RNA sequencing / spatial transcriptomics

References

[1] Rauf, Abdur, Anees Ahmed Khalil, Samir Awadallah, Shahid Ali Khan, Tareq Abu-Izneid, Muhammad Kamran, Hassan A. Hemeg, et al. 2024. “Reactive Oxygen Species in Biological Systems: Pathways, Associated Diseases, and Potential Inhibitors—A Review.” Food Science & Nutrition 12: 675-693. https://doi.org/10.1002/fsn3.3784

[2] Sena, Laura A., and Navdeep S. Chandel. 2012. “Physiological Roles of Mitochondrial Reactive Oxygen Species.” Molecular Cell 48: 158-167. https://doi.org/10.1016/j.molcel.2012.09.025

[3] Lee, Yew Mun, Weifeng He, and Yih-Cherng Liou. 2021. “The Redox Language in Neurodegenerative Diseases: Oxidative Post-Translational Modifications by Hydrogen Peroxide.” Cell Death & Disease 12: 58. https://doi.org/10.1038/s41419-020-03355-3

[4] Sies, Helmut, Carsten Berndt, and Dean P. Jones. 2017. “Oxidative Stress.” Annual Review of Biochemistry 86: 715-748. https://doi.org/10.1146/annurev-biochem-061516-045037

[5] Zhang, Lixiao, Xianwei Wang, Xianwei Wang, Ramón Cueto, Comfort Effi, Yuling Zhang, Hongmei Tan, and Xuebin Qin, et al. 2019. “Biochemical Basis and Metabolic Interplay of Redox Regulation.” Redox Biology 26: 101284. https://doi.org/10.1016/j.redox.2019.101284

[6] Halliwell, Barry. 2023. “Understanding Mechanisms of Antioxidant Action in Health and Disease.” Nature Reviews Molecular Cell Biology 25: 13-33. https://doi.org/10.1038/s41580-023-00645-4

[7] Sies, Helmut, and Dean P. Jones. 2020. “Reactive Oxygen Species (ROS) as Pleiotropic Physiological Signalling Agents.” Nature Reviews Molecular Cell Biology 21: 363-383. https://doi.org/10.1038/s41580-020-0230-3

[8] Chen, Po-Yuan, and Tai-Ming Ko. 2024. “OXidative Stress PREDictor: A Supervised Learning Approach for Annotating Cellular Oxidative Stress States in Inflammatory Cells.” Advanced Intelligent Systems 7: 2400321. https://doi.org/10.1002/aisy.202400321

[9] Chen, Junhui, Qian Zhang, Qian Zhang, Di Jinan Guo, Di Gu, Jing Liu, Piao Luo, Yunmeng Bai, et al. 2024. “Single-Cell Transcriptomics Reveals the Ameliorative Effect of Rosmarinic Acid on Diabetic Nephropathy-Induced Kidney Injury by Modulating Oxidative Stress and Inflammation.” Acta Pharmaceutica Sinica B 14: 1661-1676. https://doi.org/10.1016/j.apsb.2024.01.003

[10] Chen, Xiao, Kefan Fang, Bo Li, Yingxing Li, Yuehua Ke, Weixin Ke, Tian Tian, et al. 2025. “Macrophage-Derived Reactive Oxygen Species Promote Salmonella Aggresome Formation Contributing to Bacterial Antibiotic Persistence.” iMeta 4: e70059. https://doi.org/10.1002/imt2.70059

[11] Shi, Jialu, Wenjun Mao, Yuqing Song, Yuxin Wang, Lili Zhang, Yan Xu, Huiwen Gu, et al. 2025. “Butyrate Alleviates Food Allergy by Improving Intestinal Barrier Integrity Through Suppressing Oxidative Stress-Mediated Notch Signaling.” iMeta 4: e70024. https://doi.org/10.1002/imt2.70024

[12] Shandilya, Shruti, Sandeep Kumar, Niraj Kumar Jha, Kavindra Kumar Kesari, and Janne Ruokolainen. 2022. “Interplay of Gut Microbiota and Oxidative Stress: Perspective on Neurodegeneration and Neuroprotection.” Journal of Advanced Research 38: 223-244. https://doi.org/10.1016/j.jare.2021.09.005

[13] Gross, J. J., and R. M. Bruckmaier. 2019. “Invited Review: Metabolic Challenges and Adaptation during Different Functional Stages of the Mammary Gland in Dairy Cows: Perspectives for Sustainable Milk Production.” Journal of Dairy Science 102: 2828-2843. https://doi.org/10.3168/jds.2018-15713

[14] Zachut, Maya, and G. Andres Contreras. 2022. “Symposium Review: Mechanistic Insights into Adipose Tissue Inflammation and Oxidative Stress in Periparturient Dairy Cows.” Journal of Dairy Science 105: 3670-3686. https://doi.org/10.3168/jds.2021-21225

[15] Abuelo, Angel, Joaquín Hernández, José L. Benedito, and Cristina Castillo. 2019. “Redox Biology in Transition Periods of Dairy Cattle: Role in the Health of Periparturient and Neonatal Animals.” Antioxidants 8: 20. https://doi.org/10.3390/antiox8010020

[16] Choudhury, Abbas Alam, and V. Devi Rajeswari. 2021. “Gestational Diabetes Mellitus - A Metabolic and Reproductive Disorder.” Biomedicine & Pharmacotherapy 143: 112183. https://doi.org/10.1016/j.biopha.2021.112183

[17] Chevalier, Stéphanie, and Samaneh Farsijani. 2014. “Cancer Cachexia and Diabetes: Similarities in Metabolic Alterations and Possible Treatment.” Applied Physiology, Nutrition, and Metabolism 39: 643-653. https://doi.org/10.1139/apnm-2013-0369

[18] Gu, Fengfei, Senlin Zhu, Jinxiu Hou, Yifan Tang, Jian-Xin Liu, Qingbiao Xu, and Hui-Zeng Sun. 2023. “The Hindgut Microbiome Contributes to Host Oxidative Stress in Postpartum Dairy Cows by Affecting Glutathione Synthesis Process.” Microbiome 11: 87. https://doi.org/10.1186/s40168-023-01535-9

[19] Zhu, Sen-Lin, Feng-Fei Gu, Yi-Fan Tang, Xiao-Han Liu, Ming-Hui Jia, Teresa G. Valencak, Jian-Xin Liu, and Hui-Zeng Sun. 2024. “Dynamic Fecal Microenvironment Properties Enable Predictions and Understanding of Peripartum Blood Oxidative Status and Non-Esterified Fatty Acids in Dairy Cows.” Journal of Dairy Science 107: 573-592. https://doi.org/10.3168/jds.2022-23066

[20] Jia, Minghui, Senlin Zhu, Ming-Yuan Xue, Hongyi Chen, Jinghong Xu, Mengdi Song, Yifan Tang, et al. 2024. “Single-Cell Transcriptomics Across 2534 Microbial Species Reveals Functional Heterogeneity in the Rumen Microbiome.” Nature Microbiology 9: 1884-1898. https://doi.org/10.1038/s41564-024-01723-9

[21] Uchiyama, Jun, Masahiro Akiyama, Koji Hase, Yoshito Kumagai, and Yun-Gi Kim. 2022. “Gut Microbiota Reinforce Host Antioxidant Capacity Via the Generation of Reactive Sulfur Species.” Cell Reports 38: 110479. https://doi.org/10.1016/j.celrep.2022.110479

[22] Kruidenier, Laurens, Ineke Kuiper, Wim van Duijn, Stefan L. Marklund, Ruud A. van Hogezand, Cornelis Bhw Lamers, and Hein W. Verspaget. 2003. “Differential Mucosal Expression of Three Superoxide Dismutase Isoforms in Inflammatory Bowel Disease.” Journal of Pathology 201: 7-16. https://doi.org/10.1002/path.1407

[23] Tang, Dazhi, Jianmin Wu, Hongchao Jiao, Xiaojuan Wang, Jingpeng Zhao, and Hai Lin. 2019. “The Development of Antioxidant System in the Intestinal Tract of Broiler Chickens.” Poultry Science 98: 664-678. https://doi.org/10.3382/ps/pey415

[24] Bhattacharyya, Asima, Ranajoy Chattopadhyay, Sankar Mitra, and Sheila E. Crowe. 2014. “Oxidative Stress: An Essential Factor in the Pathogenesis of Gastrointestinal Mucosal Diseases.” Physiological Reviews 94: 329-354. https://doi.org/10.1152/physrev.00040.2012

[25] Han, Bo, Houcheng Li, Weijie Zheng, Qi Zhang, Ao Chen, Senlin Zhu, Tao Shi, et al. 2025. “A Multi-Tissue Single-Cell Expression Atlas in Cattle.” Nature Genetics 57: 2546-2561. https://doi.org/10.1038/s41588-025-02329-5

[26] Schieber, Michael, and Navdeep S. Chandel. 2014. “ROS Function in Redox Signaling and Oxidative Stress.” Current Biology 24: R453-R462. https://doi.org/10.1016/j.cub.2014.03.034

[27] Yager, Roland R., and Liping Liu. 2008. “Classic Works of the Dempster-Shafer Theory of Belief Functions.” Studies in Fuzziness and Soft Computing 219: 1-806. https://doi.org/10.1007/978-3-540-44792-4

[28] Shafer, Glenn. 1976. A Mathematical Theory of Evidence (pp. 3-34). Princeton University Press. https://doi.org/10.2307/j.ctv10vm1qb

[29] Rosales, Carlos. 2018. “Neutrophil: A Cell With Many Roles in Inflammation or Several Cell Types?” Frontiers in Physiology 9: 113. https://doi.org/10.3389/fphys.2018.00113

[30] Zhang, Lingling, Chenhao Xin, Shuo Wang, Shixuan Zhuo, Jing Zhu, Zi Li, Yuyi Liu, Lifeng Yang, and Yan Chen. 2024. “Lactate Transported by MCT1 Plays an Active Role in Promoting Mitochondrial Biogenesis and Enhancing TCA Flux in Skeletal Muscle.” Science Advances 10: eadn4508. https://doi.org/10.1126/sciadv.adn4508

[31] Wu, Jia-Jin, Senlin Zhu, Yi-Fan Tang, Fengfei Gu, Teresa G. Valencak, Jian-Xin Liu, and Hui-Zeng Sun. 2023. “Age- and Microbiota-Dependent Cell Stemness Plasticity Revealed by Cattle Cell Landscape.” Research 6: 0025. https://doi.org/10.34133/research.0025

[32] Wu, Jia-Jin, Senlin Zhu, Fengfei Gu, Teresa G. Valencak, Jian-Xin Liu, and Hui-Zeng Sun. 2022. “Cross-Tissue Single-Cell Transcriptomic Landscape Reveals the Key Cell Subtypes and Their Potential Roles in the Nutrient Absorption and Metabolism in Dairy Cattle.” Journal of Advanced Research 37: 1-18. https://doi.org/10.1016/j.jare.2021.11.009

[33] Bond, J. Jude, Alistair J. Donaldson, Joelle V. F. Coumans, Katie Austin, Dan Ebert, David Wheeler, and V. Hutton Oddy. 2019. “Protein Profiles of Enzymatically Isolated Rumen Epithelium in Sheep Fed a Fibrous Diet.” Journal of Animal Science and Biotechnology 10: 1-14. https://doi.org/10.1186/s40104-019-0314-0

[34] Wang, Shuxiong, Michael L. Drummond, Christian F. Guerrero-Juarez, Eric Tarapore, Adam L. MacLean, Adam R. Stabell, Stephanie C. Wu, et al. 2020. “Single Cell Transcriptomics of Human Epidermis Identifies Basal Stem Cell Transition States.” Nature Communications 11: 4239. https://doi.org/10.1038/s41467-020-18075-7

[35] He, Helen, Hemant Suryawanshi, Pavel Morozov, Jesús Gay-Mimbrera, Ester Del Duca, Hyun Je Kim, Naoya Kameyama, et al. 2020. “Single-Cell Transcriptome Analysis of Human Skin Identifies Novel Fibroblast Subpopulation and Enrichment of Immune Subsets in Atopic Dermatitis.” Journal of Allergy and Clinical Immunology 145: 1615-1628. https://doi.org/10.1016/j.jaci.2020.01.042

[36] Xue, Ming-Yuan, Yun-Yi Xie, Xin-Wei Zang, Yi-Fan Zhong, Xiao-Jiao Ma, Hui-Zeng Sun, and Jian-Xin Liu. 2024. “Deciphering Functional Groups of Rumen Microbiome and Their Underlying Potentially Causal Relationships in Shaping Host Traits.” iMeta 3: e225. https://doi.org/10.1002/imt2.225

[37] Cappelletti, Valentina, Thomas Hauser, Ilaria Piazza, Monika Pepelnjak, Liliana Malinovska, Tobias Fuhrer, Yaozong Li, et al. 2021. “Dynamic 3D Proteomes Reveal Protein Functional Alterations at High Resolution in Situ.” Cell 184: 545-559.e22. https://doi.org/10.1016/j.cell.2020.12.021

[38] Paukštytė, Jurgita, Rosa María López Cabezas, Yuehan Feng, Kai Tong, Daniela Schnyder, Ellinoora Elomaa, Pavlina Gregorova, et al. 2023. “Global Analysis of Aging-Related Protein Structural Changes Uncovers Enzyme-Polymerization-Based Control of Longevity.” Molecular Cell 83: 3360-3376.e11. https://doi.org/10.1016/j.molcel.2023.08.015

[39] Tars, Kaspars, Anna-Karin Larsson, Abeer Shokeer, Birgit Olin, Bengt Mannervik, and Gerard J. Kleywegt. 2006. “Structural Basis of the Suppressed Catalytic Activity of Wild-Type Human Glutathione Transferase T1-1 Compared to Its W234R Mutant.” Journal of Molecular Biology 355: 96-105. https://doi.org/10.1016/j.jmb.2005.10.049

[40] Xiang, Ruidong, Lingzhao Fang, Shuli Liu, Iona M. Macleod, Zhiqian Liu, Edmond J. Breen, Yahui Gao, et al. 2023. “Gene Expression and RNA Splicing Explain Large Proportions of the Heritability for Complex Traits in Cattle.” Cell Genomics 3: 100385. https://doi.org/10.1016/j.xgen.2023.100385

[41] Kerwin, A. L., W. S. Burhans, S. Mann, D. V. Nydam, S. K. Wall, K. M. Schoenberg, K. L. Perfield, and T. R. Overton. 2022. “Transition Cow Nutrition and Management Strategies of Dairy Herds in the Northeastern United States: Part II—Associations of Metabolic- and Inflammation-Related Analytes with Health, Milk Yield, and Reproduction.” Journal of Dairy Science 105: 5349-5369. https://doi.org/10.3168/jds.2021-20863

[42] Sies, Helmut, Ryan J. Mailloux, and Ursula Jakob. 2024. “Fundamentals of Redox Regulation in Biology.” Nature Reviews Molecular Cell Biology 25: 701-719. https://doi.org/10.1038/s41580-024-00730-2

[43] Luo, Haoran, Hong Liang, Hongwei Liu, Zhoujie Fan, Yanhui Wei, Xiaohui Yao, and Shan Cong. 2024. “TEMINET: A Co-Informative and Trustworthy Multi-Omics Integration Network for Diagnostic Prediction.” International Journal of Molecular Sciences 25: 1655. https://doi.org/10.3390/ijms25031655

[44] Harnik, Yotam, Oran Yakubovsky, Rouven Hoefflin, Roy Novoselsky, Keren Bahar Halpern, Tal Barkai, Yael Korem Kohanim, et al. 2024. “A Spatial Expression Atlas of the Adult Human Proximal Small Intestine.” Nature 632: 1101-1109. https://doi.org/10.1038/s41586-024-07793-3

[45] Huang, Pan, Quanbin Dong, Yifeng Wang, Yunfan Tian, Shunhe Wang, Chengcheng Zhang, Leilei Yu, et al. 2024. “Gut Microbial Genomes with Paired Isolates From China Illustrate Probiotic and Cardiometabolic Effects.” Cell Genomics 4: 100559. https://doi.org/10.1016/j.xgen.2024.100559

[46] Tomofuji, Yoshihiko, Toshihiro Kishikawa, Yuichi Maeda, Kotaro Ogawa, Yuriko Otake-Kasamoto, Shuhei Kawabata, Takuro Nii, et al. 2022. “Prokaryotic and Viral Genomes Recovered From 787 Japanese Gut Metagenomes Revealed Microbial Features Linked to Diets, Populations, and Diseases.” Cell Genomics 2: 100219. https://doi.org/10.1016/j.xgen.2022.100219

[47] Gonzales, Kevin Andrew Uy, and Elaine Fuchs. 2017. “Skin and Its Regenerative Powers: An Alliance between Stem Cells and Their Niche.” Developmental Cell 43: 387-401. https://doi.org/10.1016/j.devcel.2017.10.001

[48] Zhang, Kai, Yali Zhang, Jing Qin, Haining Zhu, Ning Liu, Daming Sun, Yuyang Yin, et al. 2024. “Early Concentrate Starter Introduction Induces Rumen Epithelial Parakeratosis by Blocking Keratinocyte Differentiation With Excessive Ruminal Butyrate Accumulation.” Journal of Advanced Research 66: 71-86. https://doi.org/10.1016/j.jare.2023.12.016

[49] Li, Xiang, Fan Wu, Stefan Günther, Mario Looso, Carsten Kuenne, Ting Zhang, Marion Wiesnet, et al. 2023. “Inhibition of Fatty Acid Oxidation Enables Heart Regeneration in Adult Mice.” Nature 622: 619-626. https://doi.org/10.1038/s41586-023-06585-5

[50] Xie, Saiyang, Si-Chi Xu, Wei Deng, and Qizhu Tang. 2023. “Metabolic Landscape in Cardiac Aging: Insights Into Molecular Biology and Therapeutic Implications.” Signal Transduction and Targeted Therapy 8: 114. https://doi.org/10.1038/s41392-023-01378-8

[51] Goldberg, Ira J., Chad M. Trent, and P. Christian Schulze. 2012. “Lipid Metabolism and Toxicity in the Heart.” Cell Metabolism 15: 805-812. https://doi.org/10.1016/j.cmet.2012.04.006

[52] Hodson, Leanne, and Pippa J. Gunn. 2019. “The Regulation of Hepatic Fatty Acid Synthesis and Partitioning: The Effect of Nutritional State.” Nature Reviews Endocrinology 15: 689-700. https://doi.org/10.1038/s41574-019-0256-9

[53] Chrysopoulou, Maria, and Markus M. Rinschen. 2024. “Metabolic Rewiring and Communication: An Integrative View of Kidney Proximal Tubule Function.” Annual Review of Physiology 86: 405-427. https://doi.org/10.1146/annurev-physiol-042222-024724

[54] Weinberg, Samuel E., Benjamin D. Singer, Elizabeth M. Steinert, Carlos A. Martinez, Manan M. Mehta, Inmaculada Martínez-Reyes, Peng Gao, et al. 2019. “Mitochondrial Complex III Is Essential for Suppressive Function of Regulatory T Cells.” Nature 565: 495-499. https://doi.org/10.1038/s41586-018-0846-z

[55] Purhonen, Janne, Rishi Banerjee, Vilma Wanne, Nina Sipari, Matthias Mörgelin, Vineta Fellman, and Jukka Kallijärvi. 2023. “Mitochondrial Complex III Deficiency Drives c-MYC Overexpression and Illicit Cell Cycle Entry Leading to Senescence and Segmental Progeria.” Nature Communications 14: 2356. https://doi.org/10.1038/s41467-023-38027-1

[56] Cox, Carly S., Sharen E. McKay, Marissa A. Holmbeck, Brooke E. Christian, Andrew C. Scortea, Annie J. Tsay, Laura E. Newman, and Gerald S. Shadel. 2018. “Mitohormesis in Mice via Sustained Basal Activation of Mitochondrial and Antioxidant Signaling.” Cell Metabolism 28: 776-786.e5. https://doi.org/10.1016/j.cmet.2018.07.011

[57] Cappel, David A., Stanisław Deja, João A.G. Duarte, Blanka Kucejova, Melissa Iñigo, Justin A. Fletcher, Xiaorong Fu, et al. 2019. “Pyruvate-Carboxylase-Mediated Anaplerosis Promotes Antioxidant Capacity by Sustaining TCA Cycle and Redox Metabolism in Liver.” Cell Metabolism 29: 1291-1305.e8. https://doi.org/10.1016/j.cmet.2019.03.014

[58] Hamanaka, Robert B., Andrea Glasauer, Paul Hoover, Shuangni Yang, Hanz Blatt, Andrew R. Mullen, Spiro Getsios, et al. 2013. “Mitochondrial Reactive Oxygen Species Promote Epidermal Differentiation and Hair Follicle Development.” Science Signaling 6: ra8. https://doi.org/10.1126/scisignal.2003638

[59] Polito, Maria Pia, Alessio Romaldini, Serena Rinaldo, and Elena Enzo. 2024. “Coordinating Energy Metabolism and Signaling Pathways in Epithelial Self-Renewal and Differentiation.” Biology Direct 19: 63. https://doi.org/10.1186/s13062-024-00510-0

[60] Circu, Magdalena L., and Tak Yee Aw. 2011. “Redox Biology of the Intestine.” Free Radical Research 45: 1245-1266. https://doi.org/10.3109/10715762.2011.611509

[61] Elmhadi, Mawada E., Darien K. Ali, Mawahib K. Khogali, and Hongrong Wang. 2022. “Subacute Ruminal Acidosis in Dairy Herds: Microbiological and Nutritional Causes, Consequences, and Prevention Strategies.” Animal Nutrition 10: 148-155. https://doi.org/10.1016/j.aninu.2021.12.008

[62] Ulrich, Kathrin, and Ursula Jakob. 2019. “The Role of Thiols in Antioxidant Systems.” Free Radical Biology and Medicine 140: 14-27. https://doi.org/10.1016/j.freeradbiomed.2019.05.035

[63] Van Laer, Koen, Chris J. Hamilton, and Joris Messens. 2013. “Low-Molecular-Weight Thiols in Thiol-Disulfide Exchange.” Antioxidants & Redox Signaling 18: 1642-1653. https://doi.org/10.1089/ars.2012.4964

[64] Rath, Eva, and Dirk Haller. 2022. “Intestinal Epithelial Cell Metabolism at the Interface of Microbial Dysbiosis and Tissue Injury.” Mucosal Immunology 15: 595-604. https://doi.org/10.1038/s41385-022-00514-x

[65] Gao, Yahui, Lingzhao Fang, Ransom L. Baldwin, Erin E. Connor, John B. Cole, Curtis P. Van Tassell, Li Ma, Cong-jun Li, and George E. Liu. 2021. “Single-Cell Transcriptomic Analyses of Dairy Cattle Ruminal Epithelial Cells During Weaning.” Genomics 113: 2045-2055. https://doi.org/10.1016/j.ygeno.2021.04.039

[66] Soto, Delia Alba, and Pablo Juan Ross. 2021. “Similarities Between Bovine and Human Germline Development Revealed Bby Single-Cell RNA Sequencing.” Reproduction 161: 239-253. https://doi.org/10.1530/REP-20-0313

[67] Davenport, Kimberly M., M. Sofia Ortega, Hongyu Liu, Eleanore V. O'Neil, Andrew M. Kelleher, Wesley C. Warren, and Thomas E. Spencer. 2023. “Single-Nuclei RNA Sequencing (snRNA-seq) Uncovers Trophoblast Cell Types and Lineages in the Mature Bovine Placenta.” Proceedings of the National Academy of Sciences 120: e2221526120. https://doi.org/10.1073/pnas.2221526120

[68] Wang, Xiuge, Chunhong Yang, Xiaochao Wei, Yaran Zhang, Yao Xiao, Jinpeng Wang, Qiang Jiang, et al. 2024. “Single-Cell RNA Sequencing Reveals the Critical Role of Alternative Splicing in Cattle Testicular Spermatagonia.” Biology Direct 19: 145. https://doi.org/10.1186/s13062-024-00579-7

[69] Korsunsky, Ilya, Nghia Millard, Jean Fan, Kamil Slowikowski, Fan Zhang, Kevin Wei, Yuriy Baglaenko, et al. 2019. “Fast, Sensitive and Accurate Integration of Single-Cell Data With Harmony.” Nature Methods 16: 1289-1296. https://doi.org/10.1038/s41592-019-0619-0

[70] Hao, Yuhan, Stephanie Hao, Erica Andersen-Nissen, William M. Mauck, Shiwei Zheng, Andrew Butler, Maddie J. Lee, et al. 2021. “Integrated Analysis of Multimodal Single-Cell Data.” Cell 184: 3573-3587.e29. https://doi.org/10.1016/j.cell.2021.04.048

[71] Subramanian, Ayshwarya, Mikhail Alperovich, Yiming Yang, and Bo Li. 2022. “Biology-Inspired Data-Driven Quality Control for Scientific Discovery in Single-Cell Transcriptomics.” Genome Biology 23: 267. https://doi.org/10.1186/s13059-022-02820-w

[72] McGinnis, Christopher S., Lyndsay M. Murrow, and Zev J. Gartner. 2019. “DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors.” Cell Systems 8: 329-337.e4. https://doi.org/10.1016/j.cels.2019.03.003

[73] Xu, Shuangbin, Erqiang Hu, Yantong Cai, Zijing Xie, Xiao Luo, Li Zhan, Wenli Tang, et al. 2024. “Using Clusterprofiler to Characterize Multiomics Data.” Nature Protocols 19: 3292-3320. https://doi.org/10.1038/s41596-024-01020-z

[74] Carlson, Marc. 2022. “org.Bt.eg.db: Genome Wide Annotation for Bovine.” R package version 3(15). https://doi.org/10.18129/B9.BIOC.ORG.BT.EG.DB

[75] Mi, Huaiyu, Anushya Muruganujan, John T. Casagrande, and Paul D. Thomas. 2013. “Large-Scale Gene Function Analysis With the PANTHER Classification System.” Nature Protocols 8: 1551-1566. https://doi.org/10.1038/nprot.2013.092

[76] Aleksander, Suzi A., James Balhoff, Seth Carbon, J. Michael Cherry, Harold J. Drabkin, Dustin Ebert, Marc Feuermann, et al. 2023. “The Gene Ontology Knowledgebase in 2023.” Genetics 224: iyad031. https://doi.org/10.1093/genetics/iyad031

[77] Wolf, F. Alexander, Philipp Angerer, and Fabian J. Theis. 2018. “SCANPY: Large-Scale Single-Cell Gene Expression Data Analysis.” Genome Biology 19: 15. https://doi.org/10.1186/s13059-017-1382-0

[78] Fan, Chuiqin, Fuyi Chen, Yuanguo Chen, Liangping Huang, Manna Wang, Yulin Liu, Yu Wang, et al. 2024. “irGSEA: The Integration of Single-Cell Rank-Based Gene Set Enrichment Analysis.” Briefings in Bioinformatics 25: bbae243. https://doi.org/10.1093/bib/bbae243

[79] Castanza, Anthony S., Jill M. Recla, David Eby, Helga Thorvaldsdóttir, Carol J. Bult, and Jill P. Mesirov. 2023. “Extending Support for Mouse Data in the Molecular Signatures Database (MSigDB).” Nature Methods 20: 1619-1620. https://doi.org/10.1038/s41592-023-02014-7

[80] Yan, Yunan, Senlin Zhu, Minghui Jia, Xinyi Chen, Wenlingli Qi, Fengfei Gu, Teresa G. Valencak, Jian-Xin Liu, and Hui-Zeng Sun. 2024. “Advances in Single-Cell Transcriptomics in Animal Research.” Journal of Animal Science and Biotechnology 15: 102. https://doi.org/10.1186/s40104-024-01063-y

[81] Setty, Manu, Vaidotas Kiseliovas, Jacob Levine, Adam Gayoso, Linas Mazutis, and Dana Pe'er. 2019. “Characterization of Cell Fate Probabilities in Single-Cell Data with Palantir.” Nature Biotechnology 37: 451-460. https://doi.org/10.1038/s41587-019-0068-4

[82] Van De Sande, Bram, Christopher Flerin, Kristofer Davie, Maxime De Waegeneer, Gert Hulselmans, Sara Aibar, Ruth Seurinck, et al. 2020. “A Scalable SCENIC Workflow for Single-Cell Gene Regulatory Network Analysis.” Nature Protocols 15: 2247-2276. https://doi.org/10.1038/s41596-020-0336-2

[83] Pham, Duy, Xiao Tan, Brad Balderson, Jun Xu, Laura F. Grice, Sohye Yoon, Emily F. Willis, et al. 2023. “Robust Mapping of Spatiotemporal Trajectories and Cell-Cell Interactions in Healthy and Diseased Tissues.” Nature Communications 14: 7739. https://doi.org/10.1038/s41467-023-43120-6

[84] Ma, Ying, and Xiang Zhou. 2022. “Spatially Informed Cell-Type Deconvolution for Spatial Transcriptomics.” Nature Biotechnology 40: 1349-1359. https://doi.org/10.1038/s41587-022-01273-7

[85] Xu, Lei, Yue Wang, Junhua Liu, Weiyun Zhu, and Shengyong Mao. 2018. “Morphological Adaptation of Sheep's Rumen Epithelium to High-Grain Diet Entails Alteration in the Expression of Genes Involved in Cell Cycle Regulation, Cell Proliferation and Apoptosis.” Journal of Animal Science and Biotechnology 9: 32. https://doi.org/10.1186/s40104-018-0247-z

[86] Wang, Guo-Hua, Si-Hu Wang, Wen-Zhen Zhang, Cheng-Cheng Liang, Gong Cheng, Xiao-Yu Wang, Yu Zhang, and Lin-Sen Zan. 2022. “Analysis of Stability of Reference Genes for qPCR in Bovine Preadipocytes During Proliferation and Differentiation In Vitro.” Gene 830: 146502. https://doi.org/10.1016/j.gene.2022.146502

[87] Uhlén, Mathias, Linn Fagerberg, Björn M. Hallström, Cecilia Lindskog, Per Oksvold, Adil Mardinoglu, Åsa Sivertsson, et al. 2015. “Tissue-Based Map of the Human Proteome.” Science 347: 1260419. https://doi.org/10.1126/science.1260419

[88] Jin, Suoqin, Christian F. Guerrero-Juarez, Lihua Zhang, Ivan Chang, Raul Ramos, Chen-Hsiang Kuan, Peggy Myung, Maksim V. Plikus, and Qing Nie. 2021. “Inference and Analysis of Cell-Cell Communication Using CellChat.” Nature Communications 12: 1088. https://doi.org/10.1038/s41467-021-21246-9

[89] Wiredja, Danica D., Mehmet Koyutürk, and Mark R. Chance. 2017. “The KSEA App: A Web-Based Tool for Kinase Activity Inference From Quantitative Phosphoproteomics.” Bioinformatics 33: 3489-3491. https://doi.org/10.1093/bioinformatics/btx415

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