PLX085409

GSE142582: High-throughput transcriptome analysis of clinical psoriasis

  • Organsim human
  • Type RNASEQ
  • Target gene
  • Project ARCHS4

Purpose: The present study is aiming to understand transcriptome changes during psoriatic changes using high-throughput sequencing and thereby comprehensively assess the diseases and guide future research directions.; Methods: Clinical psoriatic samples, including psoriatic lesions and their adjacent normal skin samples, and the surgical derived skins from healthy individuals as comparative controls were collected and analysed of their RNA expression profile using Illumina HiSeq 4000. raw sequencing reads were processed and pre-qualified using Trimmomatic and Fragments Per kb Per Million Reads (FPKM) method was used to calculate the abundance of each transcript followed by Negative Binomial Distribution tests to identify significant differences in each comparison.; Results: Total reads for mRNAs, lncRNAs and miRNAs was 108,552, 105,136 and 2762, respectively, including 649 novel lncRNAs and 905 novel miRNAs. 5383 DE_mRNAs, 1201 DE_lncRNAs and 80 DE_miRNAs were identified in the comparison of the psoriasis lesions-adjacent normal group (PN) vs. healthy control-derived normal skin group (NN; PN vs. NN). A total of 9513 DE_mRNAs, 1940 DE_lncRNAs and 251 DE_miRNAs were identified in the psoriasis lesion group (PS) vs. NN comparison (PS vs. NN), and 4946 DE_mRNAs, 1559 DE_lncRNAs and 92 DE_miRNAs were identified in the PS vs. PN comparison.; Conclusions: We identified numerous differentially expressed RNAs, including mRNAs, long non-coding RNAs (lncRNAs) and microRNAs (miRNAs). Our results reveal transcriptomic changes, expand our mechanistic understanding of psoriasis, and may lead to new directions for psoriasis research. SOURCE: Zengyang Yu (yuzengyang@tongji.edu.cn) - Shanghai Tenth People's Hospital, Tongji University School of Medicine

View on GEOView in Pluto

Key Features

Enhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.

Learn More

14K+ Published Experiments

Access an extensive range of curated bioinformatics data sets, including genomic, transcriptomic, and proteomic data.

Easy Data Import

Request imports from GEO or TCGA directly within Pluto Bio. Seamlessly integrate external data sets into your workflow.

Advanced Search Capabilities

Utilize powerful search tools to quickly find the data sets relevant to your research. Filter by type, disease, gene, and more.

Analyze and visualize data for this experiment

Use Pluto's intuitive interface to analyze and visualize data for this experiment. Pluto's platform is equipped with an API & SDKs, making it easy to integrate into your internal bioinformatics processes.

Read about post-pipeline analysis

View QC data and experiment metadata

View quality control data and experiment metadata for this experiment.

Request import of other GEO data

Request imports from GEO or TCGA directly within Pluto Bio.

Chat with our Scientific Insights team