Transcriptome heterogeneity of porcine ear fibroblast and its potential influence on embryo development in nuclear transplantation.

There is heterogeneity among donor cells of the same source. Many studies have shown that donor cell affects the efficiency of somatic cell nuclear transfer (SCNT). However, the potential influence of donor cell heterogeneity on the efficiency of nuclear transplantation were rarely analyzed at the single-cell level. In this study, single-cell transcriptome sequencing was performed on 52 porcine ear fibroblasts randomly selected from the same source to compare their gene expression patterns. The results showed that 48 cells had similar gene expression patterns, whereas 4 cells (D11_1, D12_1, DW61_2, DW99_2) had significantly different gene expression patterns from those of other cells. There were no two cells with identical gene expression patterns. The gene expression patterns of D11_1, D12_1, DW61_2 and DW99_2 were analyzed, using the 48 cells with similar gene expression patterns as controls. Firstly, we used the R language statistics to select the differentially expressed genes in the 4 single cells, and identified the top 50 most significant differentially expressed genes. Then GO enrichment analysis and KEGG pathway analysis were performed on the differentially expressed genes. Enrichment analysis revealed that the main molecular functions of the differentially expressed genes included energy metabolism, protein metabolism and cell response to stimulation. The main pathways from KEGG enrichment were related to cell cycle, cell metabolism, and DNA replication. Finally, based on the above results and in consideration with the SCNT research progress, we discussed the potential effects of differential gene expression patterns of the 4 single cells on the embryonic development efficiency of nuclear transplantation. This study revealed transcriptional heterogeneity of porcine ear tissue fibroblasts and provided an effective method to analyze elite donor cells, thereby providing new ideas on improving the cloning efficiency of SCNT.