Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA243568 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR1217085_1.fastq.gz | Fastqsanger.gz | |||
| SRR1217085_2.fastq.gz | Fastqsanger.gz | |||
| SRR1217086_1.fastq.gz | Fastqsanger.gz | |||
| SRR1217086_2.fastq.gz | Fastqsanger.gz | |||
| SRR1217087_1.fastq.gz | Fastqsanger.gz |
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Project description:Gene fusions and chimeric transcripts occur frequently in cancers and in some cases drive the development of the disease. An accurate detection of these events is crucial for cancer research and in a long-term perspective could be applied for personalized therapy. RNA-seq technology has been established as an efficient approach to investigate transcriptomes and search for gene fusions and chimeric transcripts on a genome-wide scale. A number of computational methods for the detection of gene fusions from RNA-seq data have been developed. However, recent studies demonstrate differences between commonly used approaches in terms of specificity and sensitivity. Moreover their ability to detect gene fusions on the isoform level has not been studied carefully so far. Here we propose a novel computational approach called InFusion for fusion gene detection from deep RNA sequencing data. Validation of InFusion on simulated and on several public RNA-seq datasets demonstrated better detection accuracy compared to other tools. We also performed deep RNA sequencing of two well-established prostate cancer cell lines. Using these data we showed that InFusion is capable of discovering alternatively spliced gene fusion isoforms as well as chimeric transcripts that include non-exonic regions. In addition our method can detect anti-sense transcription in the fusions by incorporating strand specificity of the sequencing library.
2014-12-01 | GSE56512 | GEO
Project description:Paired-end RNA-seq of follicular T cell lymphoma for the discovery of fusion transcripts
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Project description:Next Generation Sequencing technologies have enabled de novo gene fusion discovery that could reveal candidates with therapeutic significance in cancer. Here we present an open-source software package, ChimeraScan, for the discovery of chimeric transcription between two independent transcripts. Three cancer cell lines with known gene fusions
2011-09-01 | E-GEOD-29098 | biostudies-arrayexpress
Project description:Next Generation Sequencing technologies have enabled de novo gene fusion discovery that could reveal candidates with therapeutic significance in cancer. Here we present an open-source software package, ChimeraScan, for the discovery of chimeric transcription between two independent transcripts.
2011-09-01 | GSE29098 | GEO
Project description:Intervention type:DRUG. Intervention1:Huaier, Dose form:GRANULES, Route of administration:ORAL, intended dose regimen:20 to 60/day by either bulk or split for 3 months to extended term if necessary. Control intervention1:None.
Primary outcome(s): For mRNA libraries, focus on mRNA studies. Data analysis includes sequencing data processing and basic sequencing data quality control, prediction of new transcripts, differential expression analysis of genes. Gene Ontology (GO) and the KEGG pathway database are used for annotation and enrichment analysis of up-regulated genes and down-regulated genes.
For small RNA libraries, data analysis includes sequencing data process and sequencing data process QC, small RNA distribution across the genome, rRNA, tRNA, alignment with snRNA and snoRNA, construction of known miRNA expression pattern, prediction New miRNA and Study of their secondary structure Based on the expression pattern of miRNA, we perform not only GO / KEGG annotation and enrichment, but also different expression analysis.. Timepoint:RNA sequencing of 240 blood samples of 80 cases and its analysis, scheduled from June 30, 2022..
| 2612481 | ecrin-mdr-crc
Project description:Advantages of RNA-Seq over array based platforms are quantitative gene expression and discovery of expressed single nucleotide variants (eSNVs) and fusion transcripts from a single platform, but the sensitivity for each of these characteristics is unknown. We measured gene expression in a set of manually degraded RNAs, nine pairs of matched fresh-frozen, and FFPE RNA isolated from breast tumor with the hybridization based, NanoString nCounter, (226 gene panel) and with whole transcriptome RNA-Seq using RiboZeroGold ScriptSeq V2 library preparation kits. We performed correlation analyses of gene expression between samples and across platforms. We then specifically assessed whole transcriptome expression of lincRNA and discovery of eSNVs and fusion transcripts in the FFPE RNA-Seq data. For gene expression in the manually degraded samples, we observed Pearson correlation of >0.94 and >0.80 with NanoString and ScriptSeq protocols respectively. Gene expression data for matched fresh-frozen and FFPE samples yielded mean Pearson correlations of 0.874 and 0.783 for NanoString (226 genes) and ScriptSeq whole transcriptome protocols respectively. Specifically for lincRNAs, we observed superb Pearson correlation (0.988) between matched fresh-frozen and FFPE pairs. FFPE samples across NanoString and RNA-Seq platforms gave a mean Pearson correlation of 0.838. In FFPE libraries, we detected 53.4% of high confidence SNVs and 24% of high confidence fusion transcripts. Sensitivity of fusion transcript detection was not overcome by an increase in depth of sequencing up to 3-fold (increase from ~56 to ~159 million reads). Both NanoString and ScriptSeq RNA-Seq technologies yield reliable gene expression data for degraded and FFPE material. The high degree of correlation between NanoString and RNA-Seq platforms suggests discovery based whole transciptome studies from FFPE material will produce reliable expression data. The RiboZeroGold ScriptSeq protocol performed particularly well for lincRNA expression from FFPE libraries but detection of eSNV and fusion transcripts was less sensitive. We performed RNASeq on RNA from nine matched pairs of fresh-frozen and FFPE tissues from breast cancer patients. The goal was to test the RiboZeroGold ScriptSeq complete low input library preparation kit for degraded RNA samples.
2013-12-06 | E-GEOD-51124 | biostudies-arrayexpress
Project description:<p>Half of prostate cancers harbor gene fusions between <i>TMPRSS2</i> and members of the <i>ETS</i> transcription factor family. To date little is known about the presence of non-ETS fusion events in prostate cancer. We employed next-generation transcriptome sequencing (RNA-Seq) in order to explore the whole transcriptome of 25 human prostate cancer samples for the presence of chimeric fusion transcripts. We generated more than 1 billion sequence reads and used a novel computational approach (FusionSeq) in order to identify novel gene fusion candidates with high confidence. In total, we discovered and characterized seven new cancer-specific gene fusions, two involving the ETS genes <i>ETV1</i> and <i>ERG</i>, and five involving non-ETS genes such as <i>CDKN1A</i> (p21), <i>CD9</i> and <i>IKBKB</i> (IKK-beta), genes known to exhibit key biological roles in cellular homeostasis or assumed to be critical in tumorigenesis of other tumor entities, as well as the oncogene PIGU and the tumor suppressor gene <i>RSRC2</i>. The novel gene fusions are found to be of low frequency but interestingly, the non-ETS fusions were all present in prostate cancer harboring the <i>TMPRSS2-ERG</i> gene fusion. Future work will focus on determining if the ETS rearrangements in prostate cancer are associated or directly predispose to a rearrangement prone phenotype.</p>
| phs000310 | dbGaP
Project description:A novel oligonucleotide microarray design is described whereby one can screen for all known oncogenic fusion transcripts by one microarray hybridization. Measurements of chimeric transcript junctions are combined with exon-wise measurements of individual fusion partners. Keywords: Nimblegen custom-design The pilot data included a design with 68,861 oligonucleotide probes covering all combinations of chimeric exon-exon junctions from 275 pairs of fusion genes, as well as sets of oligos internal to all the exons of the fusion partners. Proof of principle was demonstrated by detection of known fusion genes (such as TCF3:PBX1, ETV6:RUNX1, and TMPRSS2:ERG) from six positive controls consisting of leukemia cell lines and prostate cancer biopsies.
2010-05-06 | E-GEOD-14435 | biostudies-arrayexpress
Project description:Advantages of RNA-Seq over array based platforms are quantitative gene expression and discovery of expressed single nucleotide variants (eSNVs) and fusion transcripts from a single platform, but the sensitivity for each of these characteristics is unknown. We measured gene expression in a set of manually degraded RNAs, nine pairs of matched fresh-frozen, and FFPE RNA isolated from breast tumor with the hybridization based, NanoString nCounter, (226 gene panel) and with whole transcriptome RNA-Seq using RiboZeroGold ScriptSeq V2 library preparation kits. We performed correlation analyses of gene expression between samples and across platforms. We then specifically assessed whole transcriptome expression of lincRNA and discovery of eSNVs and fusion transcripts in the FFPE RNA-Seq data. For gene expression in the manually degraded samples, we observed Pearson correlation of >0.94 and >0.80 with NanoString and ScriptSeq protocols respectively. Gene expression data for matched fresh-frozen and FFPE samples yielded mean Pearson correlations of 0.874 and 0.783 for NanoString (226 genes) and ScriptSeq whole transcriptome protocols respectively. Specifically for lincRNAs, we observed superb Pearson correlation (0.988) between matched fresh-frozen and FFPE pairs. FFPE samples across NanoString and RNA-Seq platforms gave a mean Pearson correlation of 0.838. In FFPE libraries, we detected 53.4% of high confidence SNVs and 24% of high confidence fusion transcripts. Sensitivity of fusion transcript detection was not overcome by an increase in depth of sequencing up to 3-fold (increase from ~56 to ~159 million reads). Both NanoString and ScriptSeq RNA-Seq technologies yield reliable gene expression data for degraded and FFPE material. The high degree of correlation between NanoString and RNA-Seq platforms suggests discovery based whole transciptome studies from FFPE material will produce reliable expression data. The RiboZeroGold ScriptSeq protocol performed particularly well for lincRNA expression from FFPE libraries but detection of eSNV and fusion transcripts was less sensitive.
2013-12-06 | GSE51124 | GEO
Project description:Genomic translocation events frequently underlie cancer development through generation of gene fusions with oncogenic properties. Identification of such fusion transcripts by transcriptome sequencing might help to discover new potential therapeutic targets. We developed TRUP (Tumor-specimen suited RNA-seq Unified Pipeline (https://github.com/ruping/TRUP), a computational approach that combines split-read and read-pair analysis with de-novo assembly for the identification of chimeric transcripts in cancer specimens. We apply TRUP to RNA-seq data of different tumor types, and find it to be more sensitive than alternative tools in detecting chimeric transcripts, such as secondary
rearrangements in EML4-ALK-positive lung tumors, or recurrent inactivating rearrangements affecting RASSF8.
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