Developmental dynamics of the epigenome and methods to find relevant regulatory motifs

Studying the epigenome and which transcription factors interact with it gives us a better understanding of how developmental processes are regulated and harmoniously orchestrated. For sensory neurons, such signals correspond to environmental stimuli. A group of genes called immediate early genes (IEGs) are known to play important roles during development, and they are some of the first to respond to signals a cell receives. They tend to encode for transcription factors (TFs), are activated within minutes and regulate the activity of other genes. Studying the features of these genes, we found a new epigenetic signature that hints at why they can be induced so fast. They have the active H3K27ac mark on their promoters, and the repressive H3K27me3 mark on their gene bodies. We found a few hundred genes with this signature and called them ‘bipartite’ genes. Bipartite genes are very lowly expressed, or not at all. They are, however, in a poised state that is even more ready to be quickly induced than the known bivalent genes. The needed transcriptional machinery is already sitting at the promoter. We used t-distributed stochastic neighbor embedding to jointly visualize chromatin accessibility and several histone marks on all genes in barrelette neurons of the somatosensory system in mice. Moreover, we used several developmental time points to visualize genome-wide changes in chromatin states across development. This allowed us to visualize the epigenetic dynamics that bipartite genes undergo by observing how they move from one developmental time point to another in these chromatin landscapes. As mentioned, IEGs correspond to TFs that have important regulatory roles. Knowing which TFs play relevant or functional roles is key to understanding the underlying developmental processes. Motivated by the importance of finding relevant TFs, we developed computational methods that enable us to make predictions, in an unbiased way, about which TFs could explain an experimental measure of interest, typically coming from sequencing data. We created an R package called monaLisa, short for “motif analysis with Lisa”, that allows for these methods to be used in a user-friendly manner. The package offers two main ways of identifying regulatory motifs. In the first approach, we made use of an existing method of correcting for sequence composition differences to apply a binned motif enrichment analysis. This method links motif enrichment to an experimental value, for example changes in DNA methylation between two conditions. The second approach uses linear regression to select a set of TFs that are likely to explain the given observations. Specifically, we use randomized lasso stability selection to discover relevant motifs. The new epigenetic signature with the bipartite genes illustrates how the epigenome can control a timely transcriptional response during development, and the methods in monaLisa further enable us to decipher which TFs could be key players

A unique bipartite Polycomb signature regulates stimulus-response transcription during development

Rapid cellular responses to environmental stimuli are fundamental for development and maturation. Immediate early genes can be transcriptionally induced within minutes in response to a variety of signals. How their induction levels are regulated and their untimely activation by spurious signals prevented during development is poorly understood. We found that in developing sensory neurons, before perinatal sensory-activity-dependent induction, immediate early genes are embedded into a unique bipartite Polycomb chromatin signature, carrying active H3K27ac on promoters but repressive Ezh2-dependent H3K27me3 on gene bodies. This bipartite signature is widely present in developing cell types, including embryonic stem cells. Polycomb marking of gene bodies inhibits mRNA elongation, dampening productive transcription, while still allowing for fast stimulus-dependent mark removal and bipartite gene induction. We reveal a developmental epigenetic mechanism regulating the rapidity and amplitude of the transcriptional response to relevant stimuli, while preventing inappropriate activation of stimulus-response genes.T.K. was supported by a Japan Society for the Promotion of Science fellowship, and O.J. was supported by an EMBO Long-Term fellowship. F.M.R. was supported by the Swiss National Science Foundation (31003A_149573 and 31003A_175776). This project has also received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant no. 810111-EpiCrest2Reg). F.M.R. and M.B.S. were also supported by the Novartis Research Foundation.Peer reviewe

DAMEfinder: a method to detect differential allele-specific methylation

BACKGROUND DNA methylation is a highly studied epigenetic signature that is associated with regulation of gene expression, whereby genes with high levels of promoter methylation are generally repressed. Genomic imprinting occurs when one of the parental alleles is methylated, i.e., when there is inherited allele-specific methylation (ASM). A special case of imprinting occurs during X chromosome inactivation in females, where one of the two X chromosomes is silenced, to achieve dosage compensation between the sexes. Another more widespread form of ASM is sequence dependent (SD-ASM), where ASM is linked to a nearby heterozygous single nucleotide polymorphism (SNP). RESULTS We developed a method to screen for genomic regions that exhibit loss or gain of ASM in samples from two conditions (treatments, diseases, etc.). The method relies on the availability of bisulfite sequencing data from multiple samples of the two conditions. We leverage other established computational methods to screen for these regions within a new R package called DAMEfinder. It calculates an ASM score for all CpG sites or pairs in the genome of each sample, and then quantifies the change in ASM between conditions. It then clusters nearby CpG sites with consistent change into regions. In the absence of SNP information, our method relies only on reads to quantify ASM. This novel ASM score compares favorably to current methods that also screen for ASM. Not only does it easily discern between imprinted and non-imprinted regions, but also females from males based on X chromosome inactivation. We also applied DAMEfinder to a colorectal cancer dataset and observed that colorectal cancer subtypes are distinguishable according to their ASM signature. We also re-discover known cases of loss of imprinting. CONCLUSION We have designed DAMEfinder to detect regions of differential ASM (DAMEs), which is a more refined definition of differential methylation, and can therefore help in breaking down the complexity of DNA methylation and its influence in development and disease