Computational protocol: Chromatin topology is coupled to Polycomb group protein subnuclear organization

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Protocol publication

[…] After three days of induction with 0.5 mM CuSO4 Drosophila S2 cells, S2 cells or S2 cells expressing either Ph-WT or Ph-ML were harvested, and total RNA was extracted using Qaigen RNA easy kit. RNA (5 μg) from each sample were treated with Ribozero gold kit (Epicenter) and Trueseq kit (Illumina) to deplete ribosomal RNA and generate double-stranded DNA fragments (∼200 bp), respectively. Sequencing libraries were generated as for ChIP-seq. Libraries were sequenced on Illumina Hi-seq 2000 for 50 bp single-end reads. Reads were mapped to the Drosophila genome (release 5) using TopHat (91–92% alignment). We then used Cufflinks with Cuffmerge to assemble the transcripts, and Cuffnorm and Cuffdiff to normalize and compare the transcriptomes. To generate the final lists of differentially regulated genes, we filtered genes for a corrected P value of <0.01, fragments per kilobase of transcript per million mapped reads (FPKM) of at least five in one of the two data sets being compared and a fold-change of at least two. The overall trends in the data are identical if less stringent filters are used. We present analysis at the level of transcription start sites rather than genes. The reason for this is that when using gene-level analysis, some loci contain multiple genes (because these transcripts overlap), while transcription start sites map to single transcripts. All of the analysis presented was carried out at the gene level as well, and the results are very similar.To analyse the overlap between ChIP-seq peaks and differentially regulated genes, we divided genes into classes of ‘up in both Ph-ML and Ph-WT versus S2', ‘down in both' or up/down in only Ph-ML or Ph-WT. We used regioneR (Bioconductor) to compare the observed overlap to overlap when ChIP-seq peaks are randomized (using ‘permTest' with ‘randomizeRegions'), or to compare overlaps of genes randomly selected from all Drosophila genes to each gene set (using ‘permTest' with ‘resampleRegions' and 1,000 permutations). The latter analysis generated the P values shown in , although the results of the two are very similar. […]

Pipeline specifications

Software tools TopHat, Cufflinks, regioneR
Application RNA-seq analysis