Ontology highlight
ABSTRACT:
PROVIDER: PRJNA717318 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:This study intends to explore the clinicopathological characteristics and survival prognosis of locally recurrent colorectal cancer patients with different treatment modes by retrospectively analyzing the medical records of locally recurrent colorectal cancer patients who received hospitalization in our center. Transcriptome sequencing and public databases were used to screen for molecular markers related to locally recurrent colorectal cancer and to explore molecular markers’ regulatory role in the progression of locally recurrent colorectal cancer.
| 116635 | ecrin-mdr-crc
Project description:In order to more accurately discover the cause of drug resistance in tumor treatment, and to provide a new basis for precise treatment.
Therefore, based on the umbrella theory of precision medicine, we carried out this single-center, prospective, and observational study to include patients with liver metastases from colorectal cancer. By combining genome, transcriptome, and proteomic sequencing data, we established a basis for colorectal cancer liver Transfer the multi-omics data of the sample, describe the reason for the resistance of the first-line treatment, and search for new therapeutic targets.
| 2349788 | ecrin-mdr-crc
Project description:GelC-MS analysis of Naja naja snake venom that goes alongside a genome sequencing and transcriptome analysis of the Indian cobra.
2019-11-08 | MSV000084564 | MassIVE
Project description:Objectives: To perform long-read transcriptome and proteome profiling of pathogen-stimulated peripheral blood mononuclear cells (PBMCs) from healthy donors. We aim to discover new transcripts and protein isoforms expressed during immune responses to diverse pathogens. Methods: PBMCs were exposed to four microbial stimuli for 24 hours: the TLR4 ligand lipopolysaccharide (LPS), the TLR3 ligand Poly(I:C), heat-inactivated Staphylococcus aureus, Candida albicans, and RPMI medium as negative controls. Long-read sequencing (PacBio) of one donor and secretome proteomics and short-read sequencing of five donors were performed. IsoQuant was used for transcriptome construction, Metamorpheus/FlashLFQ for proteome analysis, and Illumina short-read 3’-end mRNA sequencing for transcript quantification. Results: Long-read transcriptome profiling reveals the expression of novel sequences and isoform switching induced upon pathogen stimulation, including transcripts that are difficult to detect using traditional short-read sequencing. We observe widespread loss of intron retention as a common result of all pathogen stimulations. We highlight novel transcripts of NFKB1 and CASP1 that may indicate novel immunological mechanisms. In general, RNA expression differences did not result in differences in the amounts of secreted proteins. Interindividual differences in the proteome were larger than the differences between stimulated and unstimulated PBMCs. Clustering analysis of secreted proteins revealed a correlation between chemokine (receptor) expression on the RNA and protein levels in C. albicans- and Poly(I:C)-stimulated PBMCs. Conclusion: Isoform aware long-read sequencing of pathogen-stimulated immune cells highlights the potential of these methods to identify novel transcripts, revealing a more complex transcriptome landscape than previously appreciated.
2023-09-16 | PXD045237 | Pride
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.
2021-02-02 | PXD023373 | Pride
Project description:Here, we integrated high-throughput transcriptome and proteome sequencing to construct a comprehensive protein database for the byssus of Chinese green mussel (Perna viridis), aiming at providing novel insights into the molecular mechanisms of byssal binding to heavy metals.
2019-04-30 | PXD009183 | Pride
Project description:Whole genome shotgun bisulfite sequencing, small RNA sequencing and transcriptome sequencing of wildtype Arabidopsis plants (Col-0), and met1, drm1 drm2 cmt3, and ros1 dml2 dml3 null mutants using the Illumina Genetic Analyzer. A comparison was performed with regions of the genome containing cytosine DNA methylation identified by methylcytosine immunoprecipitation and whole-genome oligonucleotide tiling microarrays, for wildtype Col-0. Understanding the epigenetic regulatory mechanisms that mediate control of transcription at multiple levels is critical to understanding how plants develop and respond to their environment. We combined next-generation sequencing by synthesis (SBS) technology with novel methods for direct sequencing of the entire cytosine methylome (methylC-seq), transcriptome (RNA-seq), and the small RNA component of the transcriptome (smRNA-seq) to create a set of highly integrated epigenome maps for Arabidopsis thaliana, in conjunction with a set of informative mutants defective in DNA methyltransferase and DNA demethylase activity. At single-base resolution we discovered extensive, previously undetected, DNA methylation, identified the context and level of methylation at each site, and found that local composition has effects upon DNA methylation state. Deep sequencing of the smRNAome exposed a direct relationship between the location and abundance of smRNAs and DNA methylation, perturbation of smRNA biogenesis upon loss of CpG DNA methylation, and a tendency for smRNAs to direct strand-specific DNA methylation in the region of RNA-DNA homology. Finally, strand-specific RNA-seq revealed changes in the transcript abundance of hundreds of genes upon alteration of the DNA methylation state, and enabled the identification of numerous previously unidentified genes regulated by DNA methylation. Keywords: Whole genome shotgun bisulfite sequencing, small RNA sequencing, transcriptome sequencing, methylcytosine immunoprecipitation, whole-genome oligonucleotide tiling microarrays Whole genome shotgun bisulfite sequencing, small RNA sequencing and transcriptome sequencing of wildtype Arabidopsis plants (Col-0), and met1, drm1 drm2 cmt3, and ros1 dml2 dml3 null mutants using the Illumina Genetic Analyzer. A comparison was performed with regions of the genome containing cytosine DNA methylation identified by methylcytosine immunoprecipitation and whole-genome oligonucleotide tiling microarrays, for wildtype Col-0.
2008-04-20 | E-GEOD-10877 | biostudies-arrayexpress
Project description:We combined an iTRAQ-based proteome-level analysis with an RNA sequencing-based transcriptome-level analysis to detect the proteins and genes related to fruit peel colour development during two fruit development stages in the ‘Tunisia’ and ‘White’ pomegranate cultivars.
2018-10-19 | PXD009129 | Pride
Project description:Proteomics data from a combind transcriptome/proteome study of three sexually deceptive orchids of the genus Ophrys. Data are from labella of mature, unpollinated flowers of (1) Ophrys exaltata subsp. archipelagi, (2) O. sphegodes, and (3) O. garganica. Proteomics data were searched against SwissProt and TAIR databases and further against organism-specific databases obtained from transcriptome sequencing (454, Sanger ESTs and Solexa data). Thirteen trypsinised gel slices per sample were subjected to electrospray ionisation-based LC-MS/MS analysis with a 2D linear ion trap Finnigan LTQ (Thermo Electron Corporation) equipped with an Ultimate Nano HPLC System (Dionex Corporation). Mass spectra were searched against SwissProt and Arabidopsis TAIR9 protein databases to identify peptides. Additionally, spectra were searched against protein databases created from the Ophrys reference transcriptome obtained in this study. Stringent criteria were used for the assignment of spectra to peptides (95% peptide identification probability) in Scaffold 3.3 (Proteome Software Inc., USA). In order to maximise the utility of proteomics data for uncovering proteins predicted by the orchid transcriptome, a minimum of one unique peptide was used for protein identification, while using two different stringency levels for the probabilistic assignment of peptides to proteins (99% for highest quality, HQ; 90% to maximise protein discovery, PD, in the absence of a fully sequenced genome). Concerning the sequencing and transcriptomics results: Three normalised cDNA libraries were constructed from three different Ophrys species, O. exaltata, O. garganica, and O. sphegodes. These libraries were 454 pyrosequenced and all the high quality reads generated in this study are available in the Sequence Read Archive (SRA) of the National Centre for Biotechnology Information (NCBI) with the accession number SRA060767. Additional sequencing of O. sphegodes flower labella yielded 1.7 Mbp of Sanger (dbEST library LIBEST_028084; dbEST IDs 77978749-77979571; GenBank accessions JZ163765-JZ164587) and 2.5 Gbp of Illumina Solexa (SRA060767) data.
2013-06-21 | PXD000069 | Pride
Project description:Microbiome sequencing model is a Named Entity Recognition (NER) model that identifies and annotates microbiome nucleic acid sequencing method or platform in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with sequencing metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications
2022-02-21 | MODEL2202170012 | BioModels