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RNA-seq of biopsies from the bowels of patients with Ulcerative Colitis classified as healed versus non-healed according to different classification scores. RNA-seq of biopsies from the bowels of patients with Ulcerative Colitis classified as healed versus non-healed according to different classification scores

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NIAID Data Ecosystem2026-03-12 收录
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https://www.ncbi.nlm.nih.gov/bioproject/PRJEB41128
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The objective of the study was to understand gene expression patterns and pathways that relate to Endoscopic Remission and Histologic remission in IBD as defined by different endoscopic and histological disease activity scores. Colonic Endoscopic biopsies were collected in RNAlater from 21 UC patients undergoingcolonoscopies withthe endocytoscope CF- Y-0058-1 prototype Olympus, Japan). RNA was extracted using RNeasy columns (Qiagen) and quantified by Qubit (Life Technologies). 0.5ng RNA was used to prepare uniquely indexed cDNA QIAseq UPX 3’ Transcriptome libraries according to manufacturer’s instructions (Qiagen). Libraries were quantified and quality-controlled using the QIAseq Library Quant Assay Kit and tapestation analysis and sequenced on the Miseq and Nextseq Illumina platforms using the illumina sequencing primer and PhiX 15% to a depth of 1-3milion reads/sample. Read numbers were set as 101 bp (R1) x 51 bp (R2). Fastq files were obtained through BaseSpace and reads de-multiplexed, aligned to human genome GRCh38, quantified and normalised by the TPM method using the CLC Genomics Workbench (Qiagen). The following differential expression procedure was performed for participants classified as healed versus non-healed according different histologic and endoscpic scores which included the histological scores: Nancy and Robarts Histological Index (RHI) as well as the mayo endoscopic score (MES) and the endocytoscopy score system (ECSS). Normalised values were log-transformed with a pseudocount of 1 added. Transcripts with 1 was used to further filter the genes. To understand the biological significance and pathways, we also performed enrichment analysis using EnrichR involving three databases: Gene ontology, Wiki pathways and Kyoto Encyclopaedia of Genes and Genomes (KEGG).
创建时间:
2021-01-02
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