Emerging Putative Associations between Non-Coding RNAs and Protein-Coding Genes in Neuropathic Pain: Added Value from Reusing Microarray Data

Topic: Brain proteins, microglia and lab models

Regeneration of injured nerves is likely occurring in the peripheral nervous system, but not in the central nervous system. Although protein-coding gene expression has been assessed during nerve regeneration, little is currently known about the role of non-coding RNAs (ncRNAs). This leaves open questions about the potential effects of ncRNAs at transcriptome level. Due to the limited availability of human neuropathic pain (NP) data, we have identified the most comprehensive time-course gene expression profile referred to sciatic nerve (SN) injury and studied in a rat model using two neuronal tissues, namely dorsal root ganglion (DRG) and SN. We have developed a methodology to identify differentially expressed bioentities starting from microarray probes and repurposing them to annotate ncRNAs, while analyzing the expression profiles of protein-coding genes. The approach is designed to reuse microarray data and perform first profiling and then meta-analysis through three main steps. First, we used contextual analysis to identify what we considered putative or potential protein-coding targets for selected ncRNAs. Relevance was therefore assigned to differential expression of neighbor protein-coding genes, with neighborhood defined by a fixed genomic distance from long or antisense ncRNA loci, and of parental genes associated with pseudogenes. Second, connectivity among putative targets was used to build networks, in turn useful to conduct inference at interactomic scale. Last, network paths were annotated to assess relevance to NP. We found significant differential expression in long-intergenic ncRNAs (32 lincRNAs in SN and 8 in DRG), antisense RNA (31 asRNA in SN and 12 in DRG), and pseudogenes (456 in SN and 56 in DRG). In particular, contextual analysis centered on pseudogenes revealed some targets with known association to neurodegeneration and/or neurogenesis processes. While modules of the olfactory receptors were clearly identified in protein-protein interaction networks, other connectivity paths were identified between proteins already investigated in studies on disorders, such as Parkinson, Down syndrome, Huntington disease, and Alzheimer. Our findings suggest the importance of reusing gene expression data by meta-analysis approaches.

Key findings

• Relevance was therefore assigned to differential expression of neighbor protein-coding genes, with neighborhood defined by a fixed genomic distance from long or antisense ncRNA loci, and of parental genes associated with pseudogenes.
• We found significant differential expression in long-intergenic ncRNAs (32 lincRNAs in SN and 8 in DRG), antisense RNA (31 asRNA in SN and 12 in DRG), and pseudogenes (456 in SN and 56 in DRG).
• In particular, contextual analysis centered on pseudogenes revealed some targets with known association to neurodegeneration and/or neurogenesis processes.
• Our findings suggest the importance of reusing gene expression data by meta-analysis approaches.

Why it matters

This is a rat-model analysis of gene expression after sciatic nerve injury, focused on non-coding RNAs and neuropathic pain. It provides no information about treating, curing or preventing Alzheimer's disease.

Study details

• Study designmeta-analysis
• Evidence strengthHigh

Read the original

• DOI: 10.3389/fneur.2016.00168
• PubMed: 27803687
• Original source →
• Free full text: Frontiers in Neurology →

Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).

@article{raju2016-27803687,
  author  = {Raju, H. B. and Tsinoremas, N. F. and Capobianco, E.},
  title   = {{Emerging Putative Associations between Non-Coding RNAs and Protein-Coding Genes in Neuropathic Pain: Added Value from Reusing Microarray Data}},
  journal = {Frontiers in neurology},
  year    = {2016},
  doi     = {10.3389/fneur.2016.00168},
  pmid    = {27803687},
  url     = {https://doi.org/10.3389/fneur.2016.00168}
}

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