Computational protocol: Prolonged Absence of Mechanoluminal Stimulation in Human Intestine Alters the Transcriptome and Intestinal Stem Cell Niche

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Protocol publication

[…] Total RNA was extracted using TRIzol reagent (Life Technologies) followed by Qiagen column purification with on-column DNAse digestion (Qiagen, Valencia, CA). RNA concentration was measured with Nanodrop (ThermoFisher Scientific, Waltham, MA).Total RNA from 5 paired samples were selected to make complementary DNA libraries for RNA sequencing. RNA integrity was determined using a bioanalyzer (Agilent Technologies, Santa Clara, CA). All samples had an RNA integrity number of at least 7. Before library construction, samples were spiked with Ex-Fold External RNA Controls Consortium controls (Ambion, Foster City, CA). Mix 1 was added to RNA from fed intestine and mix 2 was added to RNA from unfed intestine. Libraries initially were sequenced to 10 million reads for power analysis via the Scotty algorithm. Based on the results of the power analysis, libraries then underwent deep sequencing to 40 million base pairs. Sequences were assayed for quality using FastQC, and adapter sequences as well as poor-quality sequences were removed with Trimmomatic. By using ENCODE recommended parameters, the remaining high-quality sequences were aligned using the RNA-star short-read aligner to the Gencode human genome version 23, which corresponds to the Genome Research Consortium human genome version GRCh38.p3 (Genome Reference Consortium). Read counts per transcript were obtained using the HTSeq-count Python script. Reads per kilobase per million mapped reads were generated using the edgeR R/Bioconductor software package. Relative log expression graphs and principle component graphs were generated using the plotting functions of the EDASeq R/Bioconductor software package.Differential gene expression was analyzed based on the Ex-Fold External RNA Controls Consortium probes with the Remove Unwanted Variation R/Bioconductor software package combined with edgeR. Genes with a false-discovery rate–corrected P value less than .05 were considered significant. Gene Ontology enrichment analysis for biological pathways was performed with the Gene Ontology stats R/Bioconductor software and Gene Ontology Consortium ( Ontologic trees were created with BiNGO through Cytoscape. A threshold of a log2 fold change ≥1.5 was selected for choosing genes of interest for further evaluation.RNA sequencing raw data and processed data were deposited in the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus. They can be accessed through GEO series accession number GSE82147. The top 100 up-regulated and down-regulated genes have been provided ().For comparison of our RNA sequencing data with previously published RNA sequencing analysis of intestine with active NEC, all differentially expressed genes with a P value less than .05 were downloaded with published fold changes. Pathway analyses were performed as described earlier. Human genes involved in pathways of interest were identified from Gene Ontology human annotation lists. Overlapping pathways and genes were compared to determine depth of similarity. […]

Pipeline specifications

Software tools Scotty, FastQC, Trimmomatic, STAR, HTSeq, edgeR, EDASeq, BiNGO
Application RNA-seq analysis
Organisms Homo sapiens