Whole Transcriptome Profiling of Lesional Psoriatic and Adjacent Normal Skin Tissues

Purpose: To identify the differentially expressed genes in lesional skin of psoriasis patients compared to adjacent normal skin tissue by Next Generation Sequencing. Methods: Total RNA was isolated from 24 paired lesional and adjacent normal skin tissue samples and Next Generation Sequencing was performed. The sequences reads were trimmed of adapter sequences and quality trimmed using CutAdapt, followed by alignment to the human genome (hg19/GRCh37) by 'STAR (v2.7.10a)'. The aligned files were sorted based on chromosomal location. Trancript assembly was performed using StringTie (v1.3.3b) and python script prepDE.py was used to obtain the raw read counts for all annotated genes. Differnetial expression analysis was performed with the raw reads using R-package 'edgeR'. Gene ontology with the deregulated genes was performed uign DAVID GO. The differentially expressed genes were integrated with differentially expressed miRNAs (GSE183547) and differentially methylated CpGs (GSE115797) to identify the genes regulated by miRNA and DNA metylation respectively. Results: We identified 1,541 differentially expressed protein-coding genes with at least 2-fold deregulation that were statistically significant (FDR ≤ 0.05). The deregulated genes were found to be associated with biological processes including inflammatory response, cytokine mediated signaling, keratinization, neutrophil chemotaxis and defense response to virus among the top enriched processes. Inetgrative analysis with small RNA-seq and DNA methylation profiling using Illumina Infinum 450K BeadArray identified 487 and 321 genes to be regulated by miRNA and DNA methylation respectively. Conclusions: Our multi-omics integrative analysis identfied the biological processes regulated exclusively as well as combinatorially by miRNAs and DNA methylation in the disease pathogenesis of psoriasis.