Systematic analysis and characterization of long non-coding RNA genes in inflammatory bowel disease

炎症性肠病中长链非编码 RNA 基因的系统分析和表征

阅读:10
作者:Rania Velissari, Mirolyuba Ilieva, James Dao, Henry E Miller, Jens Hedelund Madsen, Jan Gorodkin, Masanori Aikawa, Hideshi Ishii, Shizuka Uchida

Abstract

The cases of inflammatory bowel disease (IBD) are increasing rapidly around the world. Due to the multifactorial causes of IBD, there is an urgent need to understand the pathogenesis of IBD. As such, the usage of high-throughput techniques to profile genetic mutations, microbiome environments, transcriptome and proteome (e.g. lipidome) is increasing to understand the molecular changes associated with IBD, including two major etiologies of IBD: Crohn disease (CD) and ulcerative colitis (UC). In the case of transcriptome data, RNA sequencing (RNA-seq) technique is used frequently. However, only protein-coding genes are analyzed, leaving behind all other RNAs, including non-coding RNAs (ncRNAs) to be unexplored. Among these ncRNAs, long non-coding RNAs (lncRNAs) may hold keys to understand the pathogenesis of IBD as lncRNAs are expressed in a cell/tissue-specific manner and dysregulated in a disease, such as IBD. However, it is rare that RNA-seq data are analyzed for lncRNAs. To fill this gap in knowledge, we re-analyzed RNA-seq data of CD and UC patients compared with the healthy donors to dissect the expression profiles of lncRNA genes. As inflammation plays key roles in the pathogenesis of IBD, we conducted loss-of-function experiments to provide functional data of IBD-specific lncRNA, lung cancer associated transcript 1 (LUCAT1), in an in vitro model of macrophage polarization. To further facilitate the lncRNA research in IBD, we built a web database, IBDB (https://ibd-db.shinyapps.io/IBDB/), to provide a one-stop-shop for expression profiling of protein-coding and lncRNA genes in IBD patients compared with healthy donors.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。