Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1000513 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR25462644_1.fastq.gz | Fastqsanger.gz | |||
| SRR25462645_1.fastq.gz | Fastqsanger.gz | |||
| SRR25462646_1.fastq.gz | Fastqsanger.gz | |||
| SRR25462647_1.fastq.gz | Fastqsanger.gz | |||
| SRR25462648_1.fastq.gz | Fastqsanger.gz |
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Project description:Deregulated gene expression is a hallmark of cancer, however most studies to date have analyzed short-read RNA-sequencing data with inherent limitations. Here, we combine PacBio long-read isoform sequencing (Iso-Seq) and Illumina paired-end short read RNA sequencing to comprehensively survey the transcriptome of gastric cancer (GC), a leading cause of global cancer mortality. We performed full-length transcriptome analysis across 10 GC cell lines covering four major GC molecular subtypes (chromosomal unstable, Epstein-Barr positive, genome stable and microsatellite unstable). We identify 60,239 non-redundant full-length transcripts, of which >66% are novel compared to current transcriptome databases. Novel isoforms are more likely to be cell-line and subtype specific, expressed at lower levels with larger number of exons, with longer isoform/coding sequence lengths. Most novel isoforms utilize an alternate first exon, and compared to other alternative splicing categories are expressed at higher levels and exhibit higher variability. Collectively, we observe alternate promoter usage in 25% of detected genes, with the majority (84.2%) of known/novel promoter pairs exhibiting potential changes in their coding sequences. Mapping these alternate promoters to TCGA GC samples, we identify several cancer-associated isoforms, including novel variants of oncogenes. Tumor-specific transcript isoforms tend to alter protein coding sequences to a larger extent than other isoforms. Analysis of outcome data suggests that novel isoforms may impart additional prognostic information. Our results provide a rich resource of full-length transcriptome data for deeper studies of GC and other gastrointestinal malignancies.
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Project description:To examine the mechanisms that control flower development, we sequenced the flower bud transcriptomes of ‘High Noon’, a reblooming cultivar of P. suffruticosa × P. lutea. Both full-length isoforms and RNA-seq were sequenced in 3 floral developmental stages. A total of 15.94 Gb raw data and 457.0 million reads were generated in full-length transcript sequencing and RNA-seq.
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Project description:CCAR1 mRNA have two transcripts, the 3.5 kb full length transcript and the 2.5 kb shorter transcript which contained a deletion in exon 15—exon 22 of full-length CCAR1 cDNA, where sequences mapped to 1196–3120 bp were missed. CCAR1L and CCAR1S shared a common N-terminus and a common C-terminal end, but the latter had a deletion of SAP domain. As a DNA/RNA-binding domain, the SAP motif is involved in chromosomal organization and apoptosis. To explaine the divergence of CCAR1L and CCAR1S in regulating apoptosis,we purified CCAR1L and CCAR1S from flag-CCAR1L or CCAR1S overexpressing A549 cells by performing IP-MS to screening the possible proteins which are specifically interacting with CCAR1L or CCAR1S.
2018-05-15 | PXD009266 | Pride
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..
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Project description:Purpose:The goals of this study to compare NGS-derived transcriptome profiling (RNA-seq) to examine differentially expressed genes berween A549 infected with Zika virus and A549 Control . Methods: A549 cells mRNA profiles of A549 cells-infected with Zika virus and aun-infected A549 cells were generated by deep sequencing, in triplicate, using Illumina Hiseq4000. The mapped reads of each sample were assembled by StringTie (v1.3.1) (Mihaela Pertea.et al. 2016) in a reference-based approach. StringTie uses a novel network flow algorithm as well as an optional de novo assembly step to assemble and quantitate full-length transcripts representing multiple splice variants for each gene locus. Results: Using an optimized data analysis workflow, we mapped about identified 11124 transcripts in the A549 cells of control and Zika virus with Cuffcompare workflow. RNA-seq data confirmed stable expression of 20 known housekeeping genes, and 10 of these were validated with qRT–PCR. Approximately 10% of the transcripts showed differential expression between the control and DV, with a fold change >1 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Conclusions: Our study represents the first detailed analysis of A549 cells transcriptomes, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
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