Project description:We selected humann intervertebral disc samples to perform proteomics analysis. There were 1 case of grade I , 1 case of grade II, 3 cases of grade Ⅲ and 3 cases of grade Ⅳ according to Pfirrmann classfication. RNA seqencing analysis and single-cell RNA sequencing were integrated with proteomics data to identify the hub genes for intervertebral disc degeneration using bioinformatic method.
Project description:Adenovirus is a common human pathogen that relies on host cell processes for transcription and processing of viral RNA and protein production. Although adenoviral promoters, splice junctions, and cleavage and polyadenylation sites have been characterized using low-throughput biochemical techniques or short read cDNA-based sequencing, these technologies do not fully capture the complexity of the adenoviral transcriptome. By combining Illumina short-read and nanopore long-read direct RNA sequencing approaches, we mapped transcription start sites and cleavage and polyadenylation sites across the adenovirus genome. In addition to confirming the known canonical viral early and late RNA cassettes, our analysis of splice junctions within long RNA reads revealed an additional 35 novel viral transcripts. These RNAs include fourteen new splice junctions which lead to expression of canonical open reading frames (ORF), six novel ORF-containing transcripts, and fifteen transcripts encoding for messages that potentially alter protein functions through truncations or fusion of canonical ORFs. In addition, we also detect RNAs that bypass canonical cleavage sites and generate potential chimeric proteins by linking separate gene transcription units. Of these, an evolutionary conserved protein was detected containing the N-terminus of E4orf6 fused to the downstream DBP/E2A ORF. Loss of this novel protein, E4orf6/DBP, was associated with aberrant viral replication center morphology and poor viral spread. Our work highlights how long-read sequencing technologies can reveal further complexity within viral transcriptomes.
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
Project description:1. Evaluate the diagnostic value of long noncoding RNA (CCAT1) expression by RT-PCR in peripheral blood in colorectal cancer patients versus normal healthy control personal.
2. Evaluate the clinical utility of detecting long noncoding RNA (CCAT1) expression in diagnosis of colorectal cancer patients & its relation to tumor staging.
3. Evaluate the clinical utility of detecting long noncoding RNA (CCAT1) expression in precancerous colorectal diseases.
4. Compare long noncoding RNA (CCAT1) expression with traditional marker; carcinoembryonic antigen (CEA) and Carbohydrate antigen 19-9 (CA19-9) in diagnosis of colorectal cancer.
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..
Project description:Discovering noncanonical peptides has been a common application of proteogenomics. Recent studies suggest that certain noncanonical peptides, known as ncMAPs (noncanonical MHC-I-associated peptides), that bind to major histocompatibility complex I may make good immunotherapeutic targets. De novo peptide sequencing is a great way to find ncMAPs since it can detect peptide sequences from their tandem mass spectra without using any sequence databases. However, this strategy hasn’t been widely applied for ncMAP identification because there is not a good way to estimate its false-positive rates. In order to completely and accurately identify immunopeptides using de novo peptide sequencing, we describe a unique pipeline called pXg. In contrast to current pipelines, it makes use of genomic data, RNA-Seq abundance and sequencing quality, in addition to proteomic features to increase the sensitivity and specificity of peptide identification. We show that the peptide-spectrum match quality and genetic traits have a clear relationship, showing that they can be utilized to evaluate peptide-spectrum matches. From ten samples, we found 24,449 cMAPs (canonical MHC-I-associated peptides) and 956 ncMAPs by using a target-decoy competition. 387 ncMAPs and 1,611 cMAPs were novel identifications that had not yet been published. We discovered 11 ncMAPs produced from a squirrel monkey retrovirus in human cell lines in addition to the 2 ncMAPs originating from a complementarity determining region 3 in an antibody thanks to the unrestricted search space assumed by de novo sequencing. These entirely new identifications show that pXg can make the most of de novo peptide sequencing's advantages and its potential use in the search for new immunotherapeutic targets.