Abstract
The majority of mammalian promoters are CpG islands; regions of high CG density that require protection from DNA methylation to be functional. Importantly, how sequence architecture mediates this unmethylated state remains unclear. To address this question in a comprehensive manner, we developed a method to interrogate methylation states of hundreds of sequence variants inserted at the same genomic site in mouse embryonic stem cells. Using this assay, we were able to quantify the contribution of various sequence motifs towards the resulting DNA methylation state. Modeling of this comprehensive dataset revealed that CG density alone is a minor determinant of their unmethylated state. Instead, these data argue for a principal role for transcription factor binding sites, a prediction confirmed by testing synthetic mutant libraries. Taken together, these findings establish the hierarchy between the two cis-encoded mechanisms that define the DNA methylation state and thus the transcriptional competence of CpG islands.
Highlights
Multiple levels of regulation control correct expression level of a gene
We report a high-throughput genome engineering protocol and demonstrate its potential to determine the contribution of DNA sequence to the establishment of epigenetic states
We establish that DNA insertions at a given locus in mammalian genomes through Recombinase-mediated Cassette Exchange (RMCE) can be performed with high complexity DNA libraries, opening the possibility to dissect regulatory mechanisms such as the ones that govern the establishment of DNA methylation patterns
Summary
Multiple levels of regulation control correct expression level of a gene. In addition to transcription factors (TF), epigenetic signals enable temporal integration of regulatory events through dynamic processes including cell division and organism development. Generated methylation maps at basepair resolution from several tissues and organisms have experimentally identified unmethylated regions at unprecedented detail (Hodges et al, 2011; Molaro et al, 2011; Stadler et al, 2011; Xie et al, 2013; Ziller et al, 2013) These datasets revealed that many unmethylated regions (UMRs) extend far beyond the CGI definition and that CGI can show variable levels of methylation (Meissner et al, 2008; Mohn et al, 2008; Doi et al, 2009; Hodges et al, 2011; Molaro et al, 2011; Stadler et al, 2011). These studies identified CG poor regions outside of CGIs having low methylation levels (Low Methylated Regions–LMRs)
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