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Genome-wide analysis of circRNA regulation during spleen development of Chinese indigenous breed Meishan pigs

文献类型： 外文期刊

作者： Wang, Yifu 1 ; Cheng, Jinhua 4 ; Xu, Chao 1 ; Jin, Jian 2 ; Bao, Wenbin 1 ; Wu, Shenglong 1 ; Wu, Zhengchang 1 ;

作者机构： 1.Yangzhou Univ, Coll Anim Sci & Technol, Yangzhou 225009, Peoples R China

2.Yangzhou Univ, Inst Comparat Med, Coll Vet Med, Yangzhou 225009, Peoples R China

3.Yangzhou Univ, Int Res Lab Prevent & Control Important Anim Infec, Yangzhou 225009, Peoples R China

4.Jiangsu Acad Agr Sci, Inst Anim Sci, Nanjing 210014, Peoples R China

关键词： Porcine; CircRNAs; Spleen; Development

期刊名称：BMC GENOMICS （ 2022影响因子：4.4； 五年影响因子：4.7 ）

ISSN： 1471-2164

年卷期： 2023 年 24 卷 1 期

页码：

收录情况： SCI

摘要： BackgroundNumerous circular RNAs (circRNAs) have been recently identified in porcine tissues and cell types. Nevertheless, their significance in porcine spleen development is yet unelucidated. Herein, we reported an extensive overlook of circRNA expression profile during spleen development in Meishan pigs.ResultsOverall, 39,641 circRNAs were identified from 6,914 host genes. Among them, many circRNAs are up- or down-regulated at different time points of pig spleen development. Using WGCNA analysis, we revealed two essential modules for protein-coding genes and circRNAs. Subsequent correlation analysis revealed 67 circRNAs/co-expressed genes that participated in immnue-associated networks. Furthermore, a competing endogenous RNA (ceRNA) network analysis of circRNAs revealed that 12 circRNAs modulated CD226, MBD2, SAMD3, SIT1, SRP14, SYTL3 gene expressions via acting as miRNA sponges. Moreover, the circRNA_21767/miR-202-3p axis regulated SIT1 expression in a ceRNA manner, which is critical for the immune-based regulation of spleen development in Meishan pigs.ConclusionsOverall, our results demonstrated that the circRNAs were differentially expressed during different stages of porcine spleen development, meanwhile the circRNAs interacted with immune-related genes in a ceRNA-based fashion. Moreover, we presented biomedical researchers with RNAseqTools, a user-friendly and powerful software for the visualization of transcriptome profile data.

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