Identification of differentially expressed genes in lesional versus nonlesional skin of patients with atopic dermatitis by using high-throughput transcriptome-wide RNA sequencing
- VernacularTitle: 基于高通量RNA转录组测序技术分析特应性皮炎患者皮损与非皮损组织差异表达基因
- Author:
Lijie CHEN
1
;
Jingyao LIANG
;
Xibao ZHANG
;
Lei SHAO
;
Qingli PAN
;
Suling HE
;
Yumei LIU
;
Jianqin WANG
Author Information
- Publication Type:Journal Article
- Keywords: Dermatitis, atopic; Transcriptome; Sequence alignment; Interleukin-17; RNA-seq
- From: Chinese Journal of Dermatology 2019;52(10):729-735
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To identify differentially expressed genes in the transcriptome of the lesional versus nonlesional skin tissues of patients with moderate and severe atopic dermatitis (AD) , and to elucidate their roles in the pathogenesis of AD.
Methods:From July to October in 2016, lesional and nonlesional skin tissues were obtained from 5 outpatients of Han nationality with AD in Guangzhou Institute of Dermatology, Institute of Dermatology, Guangzhou Medical University. The next-generation high-throughput transcriptome-wide RNA sequencing (RNA-seq) was performed to identify differentially expressed genes, which were subjected to GO function annotation and KEGG pathway analysis. Real-time fluorescence-based quantitative PCR (qRT-PCR) was conducted to verify differences in candidate gene expression between lesional and nonlesional skin tissues.
Results:An average of 10.96 GBs sequence reads were acquired among 10 samples. A total of 21 729 genes were detected, including 19 268 known genes and 2 545 predicted novel genes. A total of 23 153 new transcripts were detected, of which 18 889 were new alternative splicing subtypes of known protein-coding genes, 2 545 were transcripts belonging to new protein-coding genes, and the remaining 1 719 belonged to long-stranded non-coding RNA. Totally, 78 differentially expressed genes were identified between the lesional and nonlesional skin tissues, including 69 upregulated and 11 downregulated genes in the lesional skin tissues. Among them, there were several genes known to be associated with AD inflammation (CXCL1/2/8, IL6/IL1β, MMP1, SERPINB4, S100A2, GZMB, OASL, OSM) and barrier (KRT16, FABP5, CYP1A1) and keratinocyte differentiation (IL-20) . GO analysis revealed that functions of 72 differentially expressed genes could be annotated. KEGG pathway analysis showed that the differentially expressed genes were grouped into 132 signaling pathways, of which 13 were significantly enriched, including the interleukin (IL) -17 pathway, NOD-like receptor signaling pathway, Toll-like receptor signaling pathway, etc. qRT-PCR showed that the mRNA expression levels of candidate genes CXCL1, KRT6A, IL36A, SERPINB4 and PSAPL1 was consistent with the transcriptome sequencing results.
Conclusions:Differentially expressed genes and related important regulatory signaling pathways were identified between the lesional and nonlesional skin tissues of patients with AD at the transcriptional level, and the IL-17 pathway was found to be mostly enriched in AD lesions in patients of Han nationality. These findings provide an important basis for further study on the pathogenesis of AD..
