Dataset Information

Integrated analysis of differential expression and alternative splicing of non-small cell lung cancer based on RNA sequencing.

ABSTRACT: Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, with high morbidity and mortality rates. Numerous diagnosis and treatment methods have been proposed, and the prognosis of NSCLC has improved to a certain extent. However, the mechanisms of NSCLC remain largely unknown, and additional studies are required. In the present study, the RNA sequencing dataset of NSCLC was downloaded from the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/). The clean reads obtained from the raw data were mapped to the University of California Santa Cruz human genome (hg19), based on TopHat, and were assembled into transcripts via Cufflink. The differential expression (DE) and differential alternative splicing (DAS) genes were screened out through Cuffdiff and rMATS, respectively. The significantly enriched gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes pathways were obtained through the Database of Annotation, Visualization and Integrated Discovery (DAVID). Different numbers of DE and DAS genes were identified in different types of NSCLC samples, but a number of common functions and pathways were obtained, including biological processes associated with abnormal immune and cell activity. GO terms and pathways associated with substance metabolism, including the insulin signaling pathway and oxidative phosphorylation, were enriched in DAS genes rather than DE genes. Integrated analysis of differential expression and alternative splicing may be helpful in understanding the mechanisms of NSCLC, in addition to its early diagnosis and treatment.

SUBMITTER: Li Z

PROVIDER: S-EPMC5529932 | biostudies-other | 2017 Aug

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:The continuously prolonged human lifespan is accompanied by increase in neurodegenerative diseases incidence, calling for the development of inexpensive blood-based diagnostics. Analyzing blood cell transcripts by RNA-Seq is a robust means to identify novel biomarkers that rapidly becomes a commonplace. However, there is lack of tools to discover novel exons, junctions and splicing events and to precisely and sensitively assess differential splicing through RNA-Seq data analysis and across RNA-Seq platforms. Here, we present a new and comprehensive computational workflow for whole-transcriptome RNA-Seq analysis, using an updated version of the software AltAnalyze, to identify both known and novel high-confidence alternative splicing events, and to integrate them with both protein-domains and microRNA binding annotations. We applied the novel workflow on RNA-Seq data from Parkinson's disease (PD) patients' leukocytes pre- and post- Deep Brain Stimulation (DBS) treatment and compared to healthy controls. Disease-mediated changes included decreased usage of alternative promoters and N-termini, 5'-end variations and mutually-exclusive exons. The PD regulated FUS and HNRNP A/B included prion-like domains regulated regions. We also present here a workflow to identify and analyze long non-coding RNAs (lncRNAs) via RNA-Seq data. We identified reduced lncRNA expression and selective PD-induced changes in 13 of over 6,000 detected leukocyte lncRNAs, four of which were inversely altered post-DBS. These included the U1 spliceosomal lncRNA and RP11-462G22.1, each entailing sequence complementarity to numerous microRNAs. Analysis of RNA-Seq from PD and unaffected controls brains revealed over 7,000 brain-expressed lncRNAs, of which 3,495 were co-expressed in the leukocytes including U1, which showed both leukocyte and brain increases. Furthermore, qRT-PCR validations confirmed these co-increases in PD leukocytes and two brain regions, the amygdala and substantia-nigra, compared to controls. This novel workflow allows deep multi-level inspection of RNA-Seq datasets and provides a comprehensive new resource for understanding disease transcriptome modifications in PD and other neurodegenerative diseases.

Dataset Information

Integrated analysis of differential expression and alternative splicing of non-small cell lung cancer based on RNA sequencing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets