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Articles

Study on the roles of melatonin in regulating dermal fibroblast growth in Liaoning cashmere goats by transcriptome sequencing

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Abstract

In this study, the genes related to the Downy growth of Liaoning cashmere goats were screened for their expression with simultaneous melatonin administration, so as to investigate the effects of target genes on the proliferation of skin fibroblasts in this animal species. Genes related to the villus growth of skin fibroblasts were screened by in vitro transcriptome sequencing and verified by qPCR. In addition, gene overexpression and interference were used to study the effects of target genes on the proliferation of skin fibroblasts. Groups treated with M1_24H, M2_24H and M2_72H exhibited significant differences compared with the control group. Among them, the differentially expressed transcripts in the M2_72H group were significantly enriched in the TNF and NOD-like receptor signaling pathways, which are associated with the villus. In addition, eight differentially expressed genes were screened from the TNF and the NOD-like receptor signaling pathways. Verification by qPCR showed that the expression of TNF-α, IL-6, TNFAIP3, PYCARD and NFKBIA genes were significantly upregulated, which was consistent with the sequencing results. Melatonin treatments can significantly lead to an increase in the expression of IL-6 and TNF-α genes. Besides, melatonin treatments can affect cashmere growth in Liaoning cashmere goats by regulating several signaling pathways, including TNF, NOD-like receptor and NF-κB.

Disclosure statement

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

Data availability statement

The data in this study are not intended to be shared for the public, but they can be obtained at reasonable requests to the corresponding authors.

Additional information

Funding

This study was supported by National Natural Science Foundation of China [grant number 31772557]; Liaoning Natural Science Foundation [grant number 20170540577]; Dalian Science and Technology Innovation Fund Project [grant number 2019J12SN65].

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