Computational protocol: ChIP-seq analysis of histone H3K9 trimethylation inperipheral blood mononuclear cells of membranous nephropathy patients

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Protocol publication

[…] ChIP DNA-end repairing, adaptor ligation, and amplification were performed as described earlier (). Fragments of about 100 bp (without linkers) were isolated from agarose gels and used for sequencing with a Solexa/Illumina 2G genetic analyzer (CD Genomics, USA). Sequencing tags were aligned to the bosTau4 Oct 2007 release of the reference genome using SOAP 2.21 (BGI, China) and Bowtie, an ultrafast memory-efficient short-read aligner (). We considered those tags that aligned uniquely with less than two mismatches. For enriched-region (peak) identification (peak calling), we used the Model-based Analysis of ChIP-seq (MACS) algorithm () with the MACS version 1.4.0 software (BGI). A simple yet effective technique for the analysis of eukaryotes, MACS was designed to identify transcription factor binding sites and histone modification-enriched regions in ChIP-seq data sets, with or without control samples (). Sequence reads that map to multiple sites in the human genome were removed. The MACS program was used to determine enriched H3K9me3 peaks using healthy volunteers as control. The parameters for MACS were: effective genome size=2.70e+09; tag size=49; model fold=10.30; P value cutoff=0.05. Peaks were displayed through the UCSC Genome Browser (http://genome.ucsc.edu/). The enriched peaks were annotated with the gene annotation using AmiGO 1.8. AmiGO is accessible online at the Gene Ontology (GO) website (http://www.geneontology.org/) for users to obtain the data provided by the GO Consortium (). MEME 4.7.0 was used for motif discovery in the present study. […]

Pipeline specifications

Software tools Bowtie, AmiGO
Databases UCSC Genome Browser
Application ChIP-seq analysis
Organisms Homo sapiens, Mus musculus
Diseases DiGeorge Syndrome, Kidney Diseases