Mastitis is a common and multifactorial disease in dairy cattle that leads to a major challenge in the livestock industry, in terms of both animal welfare and economic factors. Despite extensive research on mastitis, particularly gene expression profiling, the role of RNA stability dynamics remains unexplored and no study has investigated RNA stability dynamics in this disease. We hypothesized that genes important for mastitis development exhibit similar RNA stability patterns, with increased stability following infection as a response mechanism. Therefore, RNA stability pattern of genes between healthy and infected samples were investigated to identify potential modules associated with bovine mastitis. To test this hypothesis, gene stability was estimated based on an RNA-Seq dataset and a gene co-expression network was constructed using WGCNA approach. Finally, a novel propagation-based algorithm was developed to assess identified module consistency. A total of 13 gene modules with three different RNA stability patterns were identified: (1) increased stability in infected samples for the red module (innate immunity), (2) increased stability in infected samples for the yellow module (cytokine pathways), and (3) decreased stability in infected samples for the blue module (health related pathways). Of these, genes in yellow and red modules showed an increase of stability after infection. The red module was significantly associated with the innate immune activation (adjusted p-value < 0.05), while cytokine/chemokine-related pathways was predominantly enriched in the yellow module (adjusted p-value < 0.05). Propagation network analysis demonstrated the functional relationships of genes in both modules. In fact, the distinct RNA stability profiles between healthy and infected samples provided a powerful approach to identify two biologically meaningful and disease-related modules. Further investigations revealed that a large number of genes in these modules have been previously reported as important regulators involved in mastitis development including IL6, IL1B, IL1RN, TLR2, TNFAIP3, VEGFA NFKB1, STAT6, TYK2, CD74 and CREBBP. Moreover, a number of genes, including RELB, ARHGEF2, TNIP2, CACTIN, DHX9, IFNGR1, ATF4, RIPK2, IRAK2, SMAD4 and SDC4 were of particular interest because they are well-known immune response-associated genes and can be considered novel candidates involved in mastitis. These findings highlighted the importance role of RNA stability in the progression of mastitis. The results of this study contribute to a better understanding of the molecular mechanisms of the disease and provide a foundation for future research aimed at improving the health and productivity of dairy cattle.

RNA stability: a novel perspective on gene regulatory networks in bovine mastitis

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2025年12月6日

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Mohammad Amin Shirazi,
Mohammad Reza Bakhtiarizadeh,
Abdolreza Salehi

摘要

Mastitis is a common and multifactorial disease in dairy cattle that leads to a major challenge in the livestock industry, in terms of both animal welfare and economic factors. Despite extensive research on mastitis, particularly gene expression profiling, the role of RNA stability dynamics remains unexplored and no study has investigated RNA stability dynamics in this disease. We hypothesized that genes important for mastitis development exhibit similar RNA stability patterns, with increased stability following infection as a response mechanism. Therefore, RNA stability pattern of genes between healthy and infected samples were investigated to identify potential modules associated with bovine mastitis. To test this hypothesis, gene stability was estimated based on an RNA-Seq dataset and a gene co-expression network was constructed using WGCNA approach. Finally, a novel propagation-based algorithm was developed to assess identified module consistency. A total of 13 gene modules with three different RNA stability patterns were identified: (1) increased stability in infected samples for the red module (innate immunity), (2) increased stability in infected samples for the yellow module (cytokine pathways), and (3) decreased stability in infected samples for the blue module (health related pathways). Of these, genes in yellow and red modules showed an increase of stability after infection. The red module was significantly associated with the innate immune activation (adjusted p-value < 0.05), while cytokine/chemokine-related pathways was predominantly enriched in the yellow module (adjusted p-value < 0.05). Propagation network analysis demonstrated the functional relationships of genes in both modules. In fact, the distinct RNA stability profiles between healthy and infected samples provided a powerful approach to identify two biologically meaningful and disease-related modules. Further investigations revealed that a large number of genes in these modules have been previously reported as important regulators involved in mastitis development including IL6, IL1B, IL1RN, TLR2, TNFAIP3, VEGFA NFKB1, STAT6, TYK2, CD74 and CREBBP. Moreover, a number of genes, including RELB, ARHGEF2, TNIP2, CACTIN, DHX9, IFNGR1, ATF4, RIPK2, IRAK2, SMAD4 and SDC4 were of particular interest because they are well-known immune response-associated genes and can be considered novel candidates involved in mastitis. These findings highlighted the importance role of RNA stability in the progression of mastitis. The results of this study contribute to a better understanding of the molecular mechanisms of the disease and provide a foundation for future research aimed at improving the health and productivity of dairy cattle.