Profile of microRNAs following rat sciatic nerve injury by deep sequencing: implication for mechanisms of nerve regeneration

Abstract

Unlike the central nervous system, peripheral nerves can regenerate when damaged. MicroRNA (miRNA) is a novel class of small, non-coding RNA that regulates gene expression at the post-transcriptional level. Here, we report regular alterations of miRNA expression following rat sciatic nerve injury using deep sequencing. We harvested dorsal root ganglia tissues and the proximal stumps of the nerve, and identified 201 and 225 known miRNAs with significant expression variance at five time points in these tissues after sciatic nerve transaction, respectively. Subsequently, hierarchical clustering, miRNA expression pattern and co-expression network were performed. We screened out specific miRNAs and further obtained the intersection genes through target analysis software (Targetscan and miRanda). Moreover, GO and KEGG enrichment analyses of these intersection genes were performed. The bioinformatics analysis indicated that the potential targets for these miRNAs were involved in nerve regeneration, including neurogenesis, neuron differentiation, vesicle-mediated transport, homophilic cell adhesion and negative regulation of programmed cell death that were known to play important roles in regulating nerve repair. Finally, we combined differentially expressed mRNA with the predicted targets for selecting inverse miRNA-target pairs. Our results show that the abnormal expression of miRNA may contribute to illustrate the molecular mechanisms of nerve regeneration and that miRNAs are potential targets for therapeutic interventions and may enhance intrinsic regenerative ability.

Figure 1. The overall procedure of combinatorial approach to annotate known miRNA and identify their targets.

Figure 2. Size and frequency distribution of the sequencing reads, and calssification of small RNAs.

A. Length distribution of the non-redundant sequencing reads from normal DRG. B. Length distribution of the non-redundant sequencing reads from normal SN. C. Classification of the sequenced small RNA tags from normal DRG. D. Classification of the sequenced small RNA tags from normal SN.

Figure 3. The heatmap for the miRNA with significant expression variance.

A. Heatmap and cluster dendrogram of differentially expressed 201 miRNAs from DRG with or without injury. B. Heatmap and cluster dendrogram of differentially expressed 225 miRNAs from SN with or without injury. The color scale shown on the top illustrates the relative expression level of the indicated miRNA across all samples: red denotes expression >0 and green denotes expression <0.

Figure 4. The expression pattern for differentially expression miRNAs and co-expression network.

A. The expression pattern for 201 differentially expression miRNAs from DRG. B. The expression pattern for 225 differentially expression miRNAs from SN. C. Co-expression network of 201 miRNAs from DRG. D. Co-expression network of 225 miRNAs from SN.

Figure 5. The subnetwork for target genes mapped in particular GO terms and the miRNAs.

A. The network of target genes in neuron differentiation and miRNAs of D6. B. The network of target genes in vesicle-mediated transport and miRNAs of D9. C. The network of target genes in neurogenesis and miRNAs of S6. D. The network of target genes in homophilic cell adhesion and negative regulation of programmed cell death and miRNAs of S9.

Figure 6. Schematic representation of the role of miRNAs during nerve regeneration.