Construction of miRNA-mRNA network in the differentiation of chicken preadipocytes

ABSTRACT

1. MicroRNAs (miRNAs) play key roles in regulating lipid metabolism, adipogenesis and fat deposition in chicken. To date, there are only a few miRNAs that have been confirmed to be involved in chicken adipogenesis. The detailed mechanisms by which miRNAs regulate chicken adipogenesis remain largely unknown.

2. To identify candidate miRNAs involved in chicken preadipocyte differentiation and explore potential mechanisms behind their functions, the following study analysed and identified miRNA and mRNA expression levels in undifferentiated and differentiated preadipocytes. Hub miRNA-mRNA interactions were identified, and the degree of connectivity of DE miRNAs in the network was established.

3. A total of 145 DE miRNAs and 660 DE mRNAs were identified between undifferentiated and differentiated preadipocytes. An miRNA-mRNA network was constructed, including 29 DE miRNAs and 155 DE mRNAs, forming 470 miRNA-mRNA interactions. Functional enrichment analysis showed that DE mRNAs in the network were significantly enriched in 712 biological processes and 13 KEGG pathways. Based on the connectivity degree, five DE miRNAs with higher degrees miR-195-x, gga-miR-200a-3p, gga-miR-135a-5p, novel-m0067-5p and novel-m0270-5p were identified as hub miRNAs. Fifty-eight DE mRNAs interacted with these five hub miRNAs and formed 70 miRNA-mRNA interactions.

4. This study constructed a miRNA-mRNA network associated with chicken preadipocyte differentiation and identified five hub miRNAs in the network. The findings identified a number of chicken adipogenic miRNAs and laid the foundation for elucidating the miRNA-mediated regulatory mechanism in chicken adipogenesis.

KEYWORDS:

• Chicken
• preadipocyte differentiation
• miRNA-mRNA network
• RNA-seq
• adipogenesis

Data availability statement

The data that support the findings of this study are openly available in the Genome Sequence Archive (Genomics, Proteomics & Bioinformatics 2021) in National Genomics Data Center China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences, under accession number CRA004841 (miRNA-seq) and CRA004840 (RNA-seq) that are publicly accessible at https://ngdc.cncb.ac.cn/gsa.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This work was supported by The National Natural Science Foundation of China [32102532], The Priority Academic Program Development of Jiangsu Higher Education Institutions [PAPD]; The China Agriculture Research System of MOF and MARA [CARS-41]; The Natural Science Foundation of Jiangsu Province [BK20180909]; The Yangzhou University Science and Technique Innovation Foundation [2019CXJ168] and the Open Project Program of Joint International Research Laboratory of Agriculture and Agri-Product Safety, the Ministry of Education of China, Yangzhou University [JILAR-KF202016].