guidedNOMe-seq quantifies chromatin states at single allele resolution for hundreds of custom regions in parallel [guidedNOMe-seq]
Since the introduction of next generation sequencing technologies, the field of epigenomics has evolved rapidly. However, most commonly used assays are enrichment-based methods and thus only semi-quantitative. Nucleosome occupancy and methylome sequencing (NOMe-seq) allows for quantitative inference of chromatin states with single locus resolution, but this requires high sequencing depth and is therefore prohibitively expensive to routinely apply to organisms with large genomes. To overcome this limitation, we introduce guidedNOMe-seq, where we combine NOMe profiling with large scale sgRNA synthesis and Cas9-mediated region-of-interest (ROI) enrichment. To facilitate quantitative comparisons between multiple samples, we additionally develop an R package to standardize differential analysis of NOMe-seq data. We extensively benchmark guidedNOMe-seq in a proof-of-concept study, dissecting the interplay of ChAHP and CTCF on chromatin. In summary we introduce a cost-effective, scalable, and customizable targeted enrichment extension to the existing NOMe-seq protocol allowing genome-scale quantification of nucleosome occupancy and transcription factor binding at single allele resolution. Overall design: Two sets for guidedNOMe-seq datasets were generated. First, at steady state using biological duplicates of wt, Adnp-/- and Ctcf-FKBP12(F36V) mouse ES cells and second during an Adnp depletion and recovery time-course in Adnp-Avi-3xFLAG-FKBP12(F36V)-mNeonGreen mouse ES cells by dTAG13 treatment for 12h followed by a wash-out for 24h.