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Transcriptome analysis of psoriasis in a large case-control sample: RNA-seq provides insights into disease mechanisms.

The Journal of investigative dermatology | 2014

To increase our understanding of psoriasis, we used high-throughput complementary DNA sequencing (RNA-seq) to assay the transcriptomes of lesional psoriatic and normal skin. We sequenced polyadenylated RNA-derived complementary DNAs from 92 psoriatic and 82 normal punch biopsies, generating an average of ∼38 million single-end 80-bp reads per sample. Comparison of 42 samples examined by both RNA-seq and microarray revealed marked differences in sensitivity, with transcripts identified only by RNA-seq having much lower expression than those also identified by microarray. RNA-seq identified many more differentially expressed transcripts enriched in immune system processes. Weighted gene coexpression network analysis (WGCNA) revealed multiple modules of coordinately expressed epidermal differentiation genes, overlapping significantly with genes regulated by the long noncoding RNA TINCR, its target gene, staufen-1 (STAU1), the p63 target gene ZNF750, and its target KLF4. Other coordinately expressed modules were enriched for lymphoid and/or myeloid signature transcripts and genes induced by IL-17 in keratinocytes. Dermally expressed genes were significantly downregulated in psoriatic biopsies, most likely because of expansion of the epidermal compartment. These results show the power of WGCNA to elucidate gene regulatory circuits in psoriasis, and emphasize the influence of tissue architecture in both differential expression and coexpression analysis.

Pubmed ID: 24441097 RIS Download

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Antibodies used in this publication

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Associated grants

  • Agency: NIAMS NIH HHS, United States
    Id: K08 AR060802
  • Agency: NIAMS NIH HHS, United States
    Id: R01 AR042742
  • Agency: NIAMS NIH HHS, United States
    Id: AR054966
  • Agency: NIAMS NIH HHS, United States
    Id: K01 AR064765
  • Agency: NIAMS NIH HHS, United States
    Id: R01 AR054966
  • Agency: NIAMS NIH HHS, United States
    Id: R01 AR050511
  • Agency: NIAMS NIH HHS, United States
    Id: R01 AR065183
  • Agency: NIAMS NIH HHS, United States
    Id: R01 AR063611
  • Agency: NIAMS NIH HHS, United States
    Id: K01 AR064765-01

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Kyoto Encyclopedia of Genes and Genomes Expression Database (tool)

RRID:SCR_001120

Database for mapping gene expression profiles to pathways and genomes. Repository of microarray gene expression profile data for Synechocystis PCC6803 (syn), Bacillus subtilis (bsu), Escherichia coli W3110 (ecj), Anabaena PCC7120 (ana), and other species contributed by the Japanese research community.

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Ingenuity Pathway Analysis (tool)

RRID:SCR_008653

A web-based software application that enables users to analyze, integrate, and understand data derived from gene expression, microRNA, and SNP microarrays, metabolomics, proteomics, and RNA-Seq experiments, and small-scale experiments that generate gene and chemical lists. Users can search for targeted information on genes, proteins, chemicals, and drugs, and build interactive models of experimental systems. IPA allows exploration of molecular, chemical, gene, protein and miRNA interactions, creation of custom molecular pathways, and the ability to view and modify metabolic, signaling, and toxicological canonical pathways. In addition to the networks and pathways that can be created, IPA can provide multiple layering of additional information, such as drugs, disease genes, expression data, cellular functions and processes, or a researchers own genes or chemicals of interest.

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TopHat (tool)

RRID:SCR_013035

Software tool for fast and high throughput alignment of shotgun cDNA sequencing reads generated by transcriptomics technologies. Fast splice junction mapper for RNA-Seq reads. Aligns RNA-Seq reads to mammalian-sized genomes using ultra high-throughput short read aligner Bowtie, and then analyzes mapping results to identify splice junctions between exons.TopHat2 is accurate alignment of transcriptomes in presence of insertions, deletions and gene fusions.

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