Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcriptome of normal,paracancerous and cancerous colon tissues based on RNA-seq method

ABSTRACT: To support our research of colon cancer in human genome, we conducted massively parallel pyrosequencing of mRNAs (RNA-seq) using normal,paracancerouse and cancerous human colon tissues. We obtained a total of 29.9M reads from normal,33.0M reads from paracancerous and 36.5M reads from cancerous.The RNA-seq data derived from the sample illustrated the differencially expreesion genes among normal,paracancerous and cancerous colon tissues of human. 3 samples examined: normal tissue, paracancerous tissue, cancerous tissue.

ORGANISM(S): Homo sapiens

SUBMITTER: qianru ai

PROVIDER: E-GEOD-33782 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Transcriptome profiling of the cancer, adjacent non-tumor and distant normal tissues from a colorectal cancer patient by deep sequencing.

Wu Yan'an Y Wang Xuetao X Wu Fangbo F Huang Ruolei R Xue Fangqin F Liang Guantao G Tao Min M Cai Pengwei P Huang Yi Y

PloS one 20120808 8

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers in the world. A genome-wide screening of transcriptome dysregulation between cancer and normal tissue would provide insight into the molecular basis of CRC initiation and progression. Compared with microarray technology, which is commonly used to identify transcriptional changes, the recently developed RNA-seq technique has the ability to detect other abnormal regulations in the cancer transcriptome, such as alternative splici ...[more]

PMID: 22905095

Similar Datasets

Project description:RNA-seq is a powerful tool for comprehensive characterization of whole transcriptome at both gene and exon levels and with a unique ability of identifying novel splicing variants. To date, RNA-seq analysis of HBV-related HCC has not been reported. In this study, we performed transcriptome analyses for 10 matched pairs of cancer and non-cancerous tissues from Chinese HBV-related hepatocelluar carcinoma patients using 36bp single-end sequencing approach on Solexa/Illumina GAII platform. On average, about 21.6 million sequencing reads and 10.6 million aligned reads were obtained for samples sequenced on each lane, which was able to identify > 50% of all the annotated genes for each sample. Furthermore, from by far the largest database of transcripts expressed in HCC tissues, we identified 1,378 significantly differently expressed genes (DEGs) and 24, 338 differentially expressed exons (DEEs). Comprehensive function analyses indicated that cell growth-related, metabolism-related and immune-related pathways were most significantly enriched by DEGs, pointing to a complex mechanism for HCC carcinogenesis. Positional gene enrichment analysis showed that DEGs were most significantly enriched at chromosome 8q21.3-24.3. The most interesting findings were from the analysis at exon levels where we characterized three major patterns of expression changes between gene levels and exon levels, implying a much complex landscape of transcript-specific differential expressions in HCC. Finally, we identified a novel highly up-regulated exon-exon junction in ATAD2 (ATPase family, AAA domain containing 2) gene in HCC tissues. Overall, to our best knowledge, our study represents the most comprehensive characterization of the HBV-related HCC transcriptome including exon level expression changes and novel splicing variants, which illustrated the power of RNA-seq and provided important clues for understanding the molecular mechanisms of HCC pathogenesis at system-wide levels. A comprehensive analysis of transcriptome for 10 match-paired HBV-related Chinese HCC and non-cancerous adjacent tissues. Processed data files: Exon-level results, gene-level results, differentially expressed exons, and differently expressed genes (DEGs).

Dataset Information

Transcriptome of normal,paracancerous and cancerous colon tissues based on RNA-seq method

Publications

Transcriptome profiling of the cancer, adjacent non-tumor and distant normal tissues from a colorectal cancer patient by deep sequencing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure