Project description:We characterized the expression patterns of sense-antisense transcripts, based on available cDNA sequences, in colon (colorectal) cancer tissues and in normal tissues surrounding the cancer tissues. Although expression balances (ratios) of most of sense and antisense transcript pairs did not change between patients or between normal and cancer tissues, we found 68 sense-antisense transcripts whose expression balances were altered specifically in colon cancer tissues.
Project description:We characterized the expression patterns of sense-antisense transcripts, based on available cDNA sequences, in colon (colorectal) cancer tissues and in normal tissues surrounding the cancer tissues. Although expression balances (ratios) of most of sense and antisense transcript pairs did not change between patients or between normal and cancer tissues, we found 68 sense-antisense transcripts whose expression balances were altered specifically in colon cancer tissues. We conducted DNA microarray analyses by using the same set of probes designed for 2621 sense-antisense pairs to detect transcripts expressed in colon cancer tissues. These probes comprise 2358 pairs for the detection of protein-coding transcripts only, 250 pairs for the detection of protein-coding transcripts paired with non-protein-coding transcripts, and 13 pairs for the detection of non-protein-coding transcripts only.
Project description:<p>High throughput RNA Sequencing has revealed that the human genome is widely transcribed. However, the extent of natural antisense transcription, the molecular mechanisms by which natural antisense transcripts (NATs) might affect their cognate sense genes, and the role of NATs in cancer are less well understood. Here, we use strand-specific paired-end RNA sequencing (ssRNASeq) on a cohort of 376 cancer patients covering 9 tissue types to comprehensively characterize the landscape of antisense expression. Our results reveal that greater than 60% of annotated transcripts have measureable antisense expression and the expression of sense and antisense transcript pairs is in general positively correlated. Furthermore, by studying the expression of sense/antisense pairs across tissues we identify lineage-specific, ubiquitous and cancer-specific antisense loci. Our results raise the possibility that NATs participate in the regulation of well-known tumor suppressors and oncogenes. Finally, this study provides a catalogue of cancer related genes with significant antisense transcription (oncoNAT). This resource will allow researchers to investigate the molecular mechanisms of sense/antisense regulation and further advance our understanding of their role in cancer.</p>
Project description:Transcriptome profiling studies suggest that a large fraction of the genome is transcribed and many transcripts function independent of their protein coding potential. The relevance of noncoding RNAs (ncRNAs) in normal physiological processes and in tumorigenesis is increasingly recognized. Here, we describe consistent and significant differences in the distribution of sense and antisense transcripts between normal and neoplastic breast tissues. Many of the differentially expressed antisense transcripts likely represent long ncRNAs. A subset of genes that mainly generate antisense transcripts in normal but not cancer cells is involved in essential metabolic processes. These findings suggest fundamental differences in global RNA regulation between normal and cancer cells that might play a role in tumorigenesis. Global strand-specific transcriptome profilings of 4 samples in cancer from clinical breast tissue using Agilent Technologies Custom microarray.
Project description:We systematically identified long noncoding natural antisense transcripts (lncNATs), defined as lncRNAs transcribed from the opposite DNA strand of coding or noncoding genes. We identified in total 37,238 sense-antisense transcript pairs and found 70% mRNAs are associated with antisense transcripts in Arabidopsis. To detect the expression levels of these NAT pairs, we designed an Agilent custom array, ATH NAT array, and analyzed RNA samples from Arabidopsis inflorescences, leaves and roots, with 3 biological replicates each.