An Alternative Approach to ChIP-Seq Normalization Enables Detection of Genome-Wide Changes in Histone H3 Lysine 27 Trimethylation upon EZH2 Inhibition.
Brian EganChih-Chi YuanMadeleine Lisa CraskePaul LabhartGulfem D GulerDavid ArnottTobias M MaileJennifer BusbyChisato HenryTheresa K KellyCharles A TindellSuchit JhunjhunwalaFeng ZhaoCharlie HattonBarbara M BryantMarie ClassonPatrick TrojerPublished in: PloS one (2016)
Chromatin immunoprecipitation and DNA sequencing (ChIP-seq) has been instrumental in inferring the roles of histone post-translational modifications in the regulation of transcription, chromatin compaction and other cellular processes that require modulation of chromatin structure. However, analysis of ChIP-seq data is challenging when the manipulation of a chromatin-modifying enzyme significantly affects global levels of histone post-translational modifications. For example, small molecule inhibition of the methyltransferase EZH2 reduces global levels of histone H3 lysine 27 trimethylation (H3K27me3). However, standard ChIP-seq normalization and analysis methods fail to detect a decrease upon EZH2 inhibitor treatment. We overcome this challenge by employing an alternative normalization approach that is based on the addition of Drosophila melanogaster chromatin and a D. melanogaster-specific antibody into standard ChIP reactions. Specifically, the use of an antibody that exclusively recognizes the D. melanogaster histone variant H2Av enables precipitation of D. melanogaster chromatin as a minor fraction of the total ChIP DNA. The D. melanogaster ChIP-seq tags are used to normalize the human ChIP-seq data from DMSO and EZH2 inhibitor-treated samples. Employing this strategy, a substantial reduction in H3K27me3 signal is now observed in ChIP-seq data from EZH2 inhibitor treated samples.
Keyphrases
- genome wide
- dna methylation
- high throughput
- circulating tumor cells
- single cell
- rna seq
- copy number
- gene expression
- small molecule
- transcription factor
- dna damage
- circulating tumor
- long non coding rna
- long noncoding rna
- electronic health record
- single molecule
- endothelial cells
- drosophila melanogaster
- machine learning
- deep learning
- protein protein
- artificial intelligence
- replacement therapy