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. 2023 Oct 17;19(1):209.
doi: 10.1186/s12917-023-03780-4.

Coexpression analysis of lncRNAs and mRNAs identifies potential regulatory long noncoding RNAs involved in the inflammatory effects of lipopolysaccharide on bovine mammary epithelial cells

Xiaojing Xia  1 , Jie Hou  2 , Pengfei Ren  2 , Mingcheng Liu  2   3 , Lei Wang  2 , Xiaobing Wei  2 , Zhanwei Teng  2 , Oksana Kasianenko  3 , Likun Cheng  4 , Jianhe Hu  2
Affiliations

Coexpression analysis of lncRNAs and mRNAs identifies potential regulatory long noncoding RNAs involved in the inflammatory effects of lipopolysaccharide on bovine mammary epithelial cells

Xiaojing Xia et al. BMC Vet Res. .

Abstract

Background: The infection of bovine mammary glands by pathogenic microorganisms not only causes animal distress but also greatly limits the development of the dairy industry and animal husbandry. A deeper understanding of the host's initial response to infection may increase the accuracy of selecting drug-resistant animals or facilitate the development of new preventive or therapeutic intervention strategies. In addition to their functions of milk synthesis and secretion, bovine mammary epithelial cells (BMECs) play an irreplaceable role in the innate immune response. To better understand this process, the current study identified differentially expressed long noncoding lncRNAs (DE lncRNAs) and mRNAs (DE mRNAs) in BMECs exposed to Escherichia coli lipopolysaccharide (LPS) and further explored the functions and interactions of these lncRNAs and mRNAs.

Results: In this study, transcriptome analysis was performed by RNA sequencing (RNA-seq), and the functions of the DE mRNAs and DE lncRNAs were predicted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Next, we constructed a modulation network to gain a deeper understanding of the interactions and roles of these lncRNAs and mRNAs in the context of LPS-induced inflammation. A total of 231 DE lncRNAs and 892 DE mRNAs were identified. Functional enrichment analysis revealed that pathways related to inflammation and the immune response were markedly enriched in the DE genes. In addition, research results have shown that cell death mechanisms, such as necroptosis and pyroptosis, may play key roles in LPS-induced inflammation.

Conclusions: In summary, the current study identified DE lncRNAs and mRNAs and predicted the signaling pathways and biological processes involved in the inflammatory response of BMECs that might become candidate therapeutic and prognostic targets for mastitis. This study also revealed several possible pathogenic mechanisms of mastitis.

Keywords: Mammary gland epithelial cells; Mastitis; RNA-seq; lncRNA; mRNA.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
DE lncRNA and mRNA expression profiles in the LPS group and the control group. (A) Hierarchical clustering of DE lncRNAs; (B) Hierarchical clustering of DE mRNAs; (C) Volcano plot of DE lncRNAs; (D) Volcano plot of DE mRNAs. DE, differentially expressed
Fig. 2
Fig. 2
Validation of RNA-seq data using RT‒qPCR. *P < 0.05; **P < 0.01; ***P < 0.001
Fig. 3
Fig. 3
GO enrichment analysis of the target genes of the DE lncRNAs and the DE mRNAs. (A) The top 10 biological process, cellular component and molecular function GO terms enriched in the target genes of the DE lncRNAs; (B) The top 20 GO terms enriched in the target genes of the DE lncRNAs; (C) The top 10 GO biological process, cellular component and molecular function terms enriched in the DE mRNAs; (D) The top 20 GO terms enriched in the DE mRNAs
Fig. 4
Fig. 4
KEGG enrichment analysis of the target genes of the DE lncRNAs (A) and the DE mRNAs (B)
Fig. 5
Fig. 5
Coexpression network diagram of the inflammation-related mRNAs and lncRNAs
Fig. 6
Fig. 6
DE mRNAs and lncRNAs involved in cell death in LPS-treated bovine mammary epithelial cells. (A) The list of DE mRNAs related to cell death; (B) Coexpression network diagram of the cell death-related mRNAs and lncRNAs
See this image and copyright information in PMC

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