Computational protocol: Viral targeting of TFIIB impairs de novo polymerase II recruitment and affects antiviral immunity

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Protocol publication

[…] Total RNA was isolated as described above. Library preparation and RNA sequencing was performed by Max Planck-Genome-Centre Cologne, Germany (http://mpgc.mpipz.mpg.de/home/). For RNA-Seq analysis trimmed and quality-filtered reads were mapped with Tophat2 [] to the Ensembl genome annotation (version 70) and the human genome assembly GRCh37. Expression levels and differential gene expression were quantified using the cufflinks2 package []. In order to stabilize extreme fold change ratios generated by cuffdiff, we filtered out genes with a maximum per sample read count below 10 and calculated stabilized fold change values as the ratio of sample FPKM values each shifted by +2. The datasets can be found under GEO GSE105154. [...] Raw mass-spectrometry data were processed with MaxQuant software versions 1.4.1.8 and version 1.5.1.6 [] using the built-in Andromeda search engine to search against human and mouse proteomes (UniprotKB, release 2012_06) containing forward and reverse sequences, and the label-free quantitation algorithm as described previously [,]. In MaxQuant, carbamidomethylation was set as fixed and methionine oxidation and N-acetylation as variable modifications, using an initial mass tolerance of 6 ppm for the precursor ion and 0.5 Da for the fragment ions. For SILAC samples, multiplicity was set to 2 and Arg10 and Lys8 were set as heavy label parameters. Search results were filtered with a false discovery rate (FDR) of 0.01 for peptide and protein identifications. Protein tables were filtered to eliminate the identifications from the reverse database and common contaminants. Data were analysed in Perseus.In analysing mass spectrometry data from affinity purifications, only proteins identified on the basis of at least two peptides and a minimum of three quantitation events in at least one experimental group were considered. Label-free quantitation (LFQ) protein intensity values were log-transformed and missing values filled by imputation with random numbers drawn from a normal distribution, whose mean and standard deviation were chosen to best simulate low abundance values. Significant interactors of bait proteins were determined by multiple equal variance t-tests with permutation-based false discovery rate statistics. We performed 250 permutations and the FDR threshold was set between 0.02 and 0.1. The parameter S0 was empirically set between 0.2 and 1, to separate background from specifically enriched interactors.For data analysis from pulsed SILAC experiments, we used log-transformed heavy to light protein ratios. Only proteins with valid values were considered for analysis. Profile plots were generated using LFQ intensities of log-transformed heavy-labelled protein intensities. Missing values were filled by imputation. [...] For the quantification of occupancies of TFIIB, Pol II, NELF and DSIF, we re-analysed published HeLa ChIP-Seq data from [,]. Trimmed and quality-filtered reads were mapped to genome assembly GRCh37 with bowtie2 [] and filtered by mapping quality score (cutoff 30). A custom genome annotation file was generated based on Ensembl canonical transcripts containing target intervals relative to the transcription start site of -500 to +500bp (promoter), -50 to +300bp (downstream promoter) and +300bp to transcript end (gene body). Transcripts shorter than 1000bp were not considered. Read-coverage for these intervals was quantified using featureCounts [] (TFIIB and H3K4me3: promoter; Pol II, NELF and DSIF: downstream promoter; Pol2: gene body). Where replicate samples were available, counts were normalized by library size, background-corrected by subtraction of input control and averaged across replicates. Gene pausing indices were calculated based on the Pol II samples from [] as the length-normalized count ratio between the downstream promoter and the gene body intervals [,].P-values for the significance of differential read coverage between selected sets of genes were calculated using a negative binomial count model with a log link function in R (using the MASS package). […]

Pipeline specifications

Software tools Bowtie2, Subread
Application ChIP-seq analysis
Organisms Viruses, Thogoto thogotovirus