Quantitative modelling predicts the impact of DNA methylation on RNA polymerase II traffic

MeCP2 binds to methylated DNA independently of phase separation and heterochromatin organisation

Correlative evidence has suggested that the methyl-CpG-binding protein MeCP2 contributes to the formation of heterochromatin condensates via liquid-liquid phase separation. This interpretation has been reinforced by the observation that heterochromatin, DNA methylation and MeCP2 co-localise within prominent foci in mouse cells. The findings presented here revise this view. MeCP2 localisation is independent of heterochromatin as MeCP2 foci persist even when heterochromatin organisation is disrupted. Additionally, MeCP2 foci fail to show hallmarks of phase separation in live cells. Importantly, we find that mouse cellular models are highly atypical as MeCP2 distribution is diffuse in most mammalian species, including humans. Notably, MeCP2 foci are absent in Mus spretus which is a mouse subspecies lacking methylated satellite DNA repeats. We conclude that MeCP2 has no intrinsic tendency to form condensates and its localisation is independent of heterochromatin. Instead, the distribution of MeCP2 in the nucleus is primarily determined by global DNA methylation patterns.

MECP2 directly interacts with RNA polymerase II to modulate transcription in human neurons

Mutations in the methyl-DNA-binding protein MECP2 cause the neurodevelopmental disorder Rett syndrome (RTT). How MECP2 contributes to transcriptional regulation in normal and disease states is unresolved; it has been reported to be an activator and a repressor. We describe here the first integrated CUT&Tag, transcriptome, and proteome analyses using human neurons with wild-type (WT) and mutant MECP2 molecules. MECP2 occupies CpG-rich promoter-proximal regions in over four thousand genes in human neurons, including a plethora of autism risk genes, together with RNA polymerase II (RNA Pol II). MECP2 directly interacts with RNA Pol II, and genes occupied by both proteins showed reduced expression in neurons with MECP2 patient mutations. We conclude that MECP2 acts as a positive cofactor for RNA Pol II gene expression at many neuronal genes that harbor CpG islands in promoter-proximal regions and that RTT is due, in part, to the loss of gene activity of these genes in neurons.

The Causes for Genomic Instability and How to Try and Reduce Them Through Rational Design of Synthetic DNA

Genetic engineering has revolutionized our ability to manipulate DNA and engineer organisms for various applications. However, this approach can lead to genomic instability, which can result in unwanted effects such as toxicity, mutagenesis, and reduced productivity. To overcome these challenges, smart design of synthetic DNA has emerged as a promising solution. By taking into consideration the intricate relationships between gene expression and cellular metabolism, researchers can design synthetic constructs that minimize metabolic stress on the host cell, reduce mutagenesis, and increase protein yield. In this chapter, we summarize the main challenges of genomic instability in genetic engineering and address the dangers of unknowingly incorporating genomically unstable sequences in synthetic DNA. We also demonstrate the instability of those sequences by the fact that they are selected against conserved sequences in nature. We highlight the benefits of using ESO, a tool for the rational design of DNA for avoiding genetically unstable sequences, and also summarize the main principles and working parameters of the software that allow maximizing its benefits and impact.

DNA-sequence and epigenomic determinants of local rates of transcription elongation

Across all branches of life, transcription elongation is a crucial, regulated phase in gene expression. Many recent studies in eukaryotes have focused on the regulation of promoter-proximal pausing of RNA Polymerase II (Pol II), but rates of productive elongation also vary substantially throughout the gene body, both within and across genes. Here, we introduce a probabilistic model for systematically evaluating potential determinants of the local elongation rate based on nascent RNA sequencing (NRS) data. Our model is derived from a unified model for both the kinetics of Pol II movement along the DNA template and the generation of NRS read counts at steady state. It allows for a continuously variable elongation rate along the gene body, with the rate at each nucleotide defined by a generalized linear relationship with nearby genomic and epigenomic features. High-dimensional feature vectors are accommodated through a sparse-regression extension. We show with simulations that the model allows accurate detection of associated features and accurate prediction of local elongation rates. In an analysis of public PRO-seq and epigenomic data, we identify several features that are strongly associated with reductions in the local elongation rate, including DNA methylation, splice sites, RNA stem-loops, CTCF binding sites, and several histone marks, including H3K36me3 and H4K20me1. By contrast, low-complexity sequences and H3K79me2 marks are associated with increases in elongation rate. In an analysis of DNA k -mers, we find that cytosine nucleotides are strongly associated with reductions in local elongation rate, particularly when preceded by guanines and followed by adenines or thymines. Increases in elongation rate are associated with thymines and A+T-rich k -mers. These associations are generally shared across cell types, and by considering them our model is effective at predicting features of held-out PRO-seq data. Overall, our analysis is the first to permit genome-wide predictions of relative nucleotide-specific elongation rates based on complex sets of genomic and epigenomic covariates. We have made predictions available for the K562, CD14+, MCF-7, and HeLa-S3 cell types in a UCSC Genome Browser track.

Stochastic modeling of the mRNA life process: A generalized master equation

The mRNA life cycle is a complex biochemical process, involving transcription initiation, elongation, termination, splicing, and degradation. Each of these molecular events is multistep and can create a memory. The effect of this molecular memory on gene expression is not clear, although there are many related yet scattered experimental reports. To address this important issue, we develop a general theoretical framework formulated as a master equation in the sense of queue theory, which can reduce to multiple previously studied gene models in limiting cases. This framework allows us to interpret experimental observations, extract kinetic parameters from experimental data, and identify how the mRNA kinetics vary under regulatory influences. Notably, it allows us to evaluate the influences of elongation processes on mature RNA distribution; e.g., we find that the non-exponential elongation time can induce the bimodal mRNA expression and there is an optimal elongation noise intensity such that the mature RNA noise achieves the lowest level. In a word, our framework can not only provide insight into complex mRNA life processes but also bridge a dialogue between theoretical studies and experimental data.

Uncovering the effect of RNA polymerase steric interactions on gene expression noise: Analytical distributions of nascent and mature RNA numbers

The telegraph model is the standard model of stochastic gene expression, which can be solved exactly to obtain the distribution of mature RNA numbers per cell. A modification of this model also leads to an analytical distribution of nascent RNA numbers. These solutions are routinely used for the analysis of single-cell data, including the inference of transcriptional parameters. However, these models neglect important mechanistic features of transcription elongation, such as the stochastic movement of RNA polymerases and their steric (excluded-volume) interactions. Here we construct a model of gene expression describing promoter switching between inactive and active states, binding of RNA polymerases in the active state, their stochastic movement including steric interactions along the gene, and their unbinding leading to a mature transcript that subsequently decays. We derive the steady-state distributions of the nascent and mature RNA numbers in two important limiting cases: constitutive expression and slow promoter switching. We show that RNA fluctuations are suppressed by steric interactions between RNA polymerases, and that this suppression can in some instances even lead to sub-Poissonian fluctuations; these effects are most pronounced for nascent RNA and less prominent for mature RNA, since the latter is not a direct sensor of transcription. We find a relationship between the parameters of our microscopic mechanistic model and those of the standard models that ensures excellent consistency in their prediction of the first and second RNA number moments over vast regions of parameter space, encompassing slow, intermediate, and rapid promoter switching, provided the RNA number distributions are Poissonian or super-Poissonian. Furthermore, we identify the limitations of inference from mature RNA data, specifically showing that it cannot differentiate between highly distinct RNA polymerase traffic patterns on a gene.

Bayesian inference of polymerase dynamics over the exclusion process

Transcription is a complex phenomenon that permits the conversion of genetic information into phenotype by means of an enzyme called RNA polymerase, which erratically moves along and scans the DNA template. We perform Bayesian inference over a paradigmatic mechanistic model of non-equilibrium statistical physics, i.e. the asymmetric exclusion processes in the hydrodynamic limit, assuming a Gaussian process prior for the polymerase progression rate as a latent variable. Our framework allows us to infer the speed of polymerases during transcription given their spatial distribution, while avoiding the explicit inversion of the system's dynamics. The results, which show processing rates strongly varying with genomic position and minor role of traffic-like congestion, may have strong implications for the understanding of gene expression.

Differential dynamics specify MeCP2 function at methylated DNA and nucleosomes

Methyl-CpG-binding protein 2 (MeCP2) is an essential chromatin-binding protein whose mutations cause Rett syndrome (RTT), a leading cause of monogenic intellectual disabilities in females. Despite its significant biomedical relevance, the mechanism by which MeCP2 navigates the chromatin epigenetic landscape to regulate chromatin structure and gene expression remains unclear. Here, we used correlative single-molecule fluorescence and force microscopy to directly visualize the distribution and dynamics of MeCP2 on a variety of DNA and chromatin substrates. We found that MeCP2 exhibits differential diffusion dynamics when bound to unmethylated and methylated bare DNA. Moreover, we discovered that MeCP2 preferentially binds nucleosomes within the context of chromatinized DNA and stabilizes them from mechanical perturbation. The distinct behaviors of MeCP2 at bare DNA and nucleosomes also specify its ability to recruit TBLR1, a core component of the NCoR1/2 co-repressor complex. We further examined several RTT mutations and found that they disrupt different aspects of the MeCP2-chromatin interaction, rationalizing the heterogeneous nature of the disease. Our work reveals the biophysical basis for MeCP2's methylation-dependent activities and suggests a nucleosome-centric model for its genomic distribution and gene repressive functions. These insights provide a framework for delineating the multifaceted functions of MeCP2 and aid in our understanding of the molecular mechanisms of RTT.

Characterizing the targets of transcription regulators by aggregating ChIP-seq and perturbation expression data sets

Mapping the gene targets of chromatin-associated transcription regulators (TRs) is a major goal of genomics research. ChIP-seq of TRs and experiments that perturb a TR and measure the differential abundance of gene transcripts are a primary means by which direct relationships are tested on a genomic scale. It has been reported that there is a poor overlap in the evidence across gene regulation strategies, emphasizing the need for integrating results from multiple experiments. Although research consortia interested in gene regulation have produced a valuable trove of high-quality data, there is an even greater volume of TR-specific data throughout the literature. In this study, we show a workflow for the identification, uniform processing, and aggregation of ChIP-seq and TR perturbation experiments for the ultimate purpose of ranking human and mouse TR-target interactions. Focusing on an initial set of eight regulators (ASCL1, HES1, MECP2, MEF2C, NEUROD1, PAX6, RUNX1, and TCF4), we identified 497 experiments suitable for analysis. We used this corpus to examine data concordance, to identify systematic patterns of the two data types, and to identify putative orthologous interactions between human and mouse. We build upon commonly used strategies to forward a procedure for aggregating and combining these two genomic methodologies, assessing these rankings against independent literature-curated evidence. Beyond a framework extensible to other TRs, our work also provides empirically ranked TR-target listings, as well as transparent experiment-level gene summaries for community use.

Buffering of transcription rate by mRNA half-life is a conserved feature of Rett syndrome models

Transcriptional changes in Rett syndrome (RTT) are assumed to directly correlate with steady-state mRNA levels, but limited evidence in mice suggests that changes in transcription can be compensated by post-transcriptional regulation. We measure transcription rate and mRNA half-life changes in RTT patient neurons using RATEseq, and re-interpret nuclear and whole-cell RNAseq from Mecp2 mice. Genes are dysregulated by changing transcription rate or half-life and are buffered when both change. We utilized classifier models to predict the direction of transcription rate changes and find that combined frequencies of three dinucleotides are better predictors than CA and CG. MicroRNA and RNA-binding Protein (RBP) motifs are enriched in 3'UTRs of genes with half-life changes. Nuclear RBP motifs are enriched on buffered genes with increased transcription rate. We identify post-transcriptional mechanisms in humans and mice that alter half-life or buffer transcription rate changes when a transcriptional modulator gene is mutated in a neurodevelopmental disorder.

Epigenetic and epitranscriptomic regulation of axon regeneration

Effective axonal regeneration in the adult mammalian nervous system requires coordination of elevated intrinsic growth capacity and decreased responses to the inhibitory environment. Intrinsic regenerative capacity largely depends on the gene regulatory network and protein translation machinery. A failure to activate these pathways upon injury is underlying a lack of robust axon regeneration in the mature mammalian central nervous system. Epigenetics and epitranscriptomics are key regulatory mechanisms that shape gene expression and protein translation. Here, we provide an overview of different types of modifications on DNA, histones, and RNA, underpinning the regenerative competence of axons in the mature mammalian peripheral and central nervous systems. We highlight other non-neuronal cells and their epigenetic changes in determining the microenvironment for tissue repair and axon regeneration. We also address advancements of single-cell technology in charting transcriptomic and epigenetic landscapes that may further facilitate the mechanistic understanding of differential regenerative capacity in neuronal subtypes. Finally, as epigenetic and epitranscriptomic processes are commonly affected by brain injuries and psychiatric disorders, understanding their alterations upon brain injury would provide unprecedented mechanistic insights into etiology of injury-associated-psychiatric disorders and facilitate the development of therapeutic interventions to restore brain function.

A screen for MeCP2-TBL1 interaction inhibitors using a luminescence-based assay

Understanding the molecular pathology of neurodevelopmental disorders should aid the development of therapies for these conditions. In MeCP2 duplication syndrome (MDS)-a severe autism spectrum disorder-neuronal dysfunction is caused by increased levels of MeCP2. MeCP2 is a nuclear protein that binds to methylated DNA and recruits the nuclear co-repressor (NCoR) complex to chromatin via an interaction with the WD repeat-containing proteins TBL1 and TBLR1. The peptide motif in MeCP2 that binds to TBL1/TBLR1 is essential for the toxicity of excess MeCP2 in animal models of MDS, suggesting that small molecules capable of disrupting this interaction might be useful therapeutically. To facilitate the search for such compounds, we devised a simple and scalable NanoLuc luciferase complementation assay for measuring the interaction of MeCP2 with TBL1/TBLR1. The assay allowed excellent separation between positive and negative controls, and had low signal variance (Z-factor = 0.85). We interrogated compound libraries using this assay in combination with a counter-screen based on luciferase complementation by the two subunits of protein kinase A (PKA). Using this dual screening approach, we identified candidate inhibitors of the interaction between MeCP2 and TBL1/TBLR1. This work demonstrates the feasibility of future screens of large compound collections, which we anticipate will enable the development of small molecule therapeutics to ameliorate MDS.

A critique of the hypothesis that CA repeats are primary targets of neuronal MeCP2

The DNA-binding protein MeCP2 is reported to bind methylated cytosine in CG and CA motifs in genomic DNA, but it was recently proposed that arrays of tandemly repeated CA containing either methylated or hydroxymethylated cytosine are the primary targets for MeCP2 binding and function. Here we investigated the predictions of this hypothesis using a range of published datasets. We failed to detect enrichment of cytosine modification at genomic CA repeat arrays in mouse brain regions and found no evidence for preferential MeCP2 binding at CA repeats. Moreover, we did not observe a correlation between the CA repeat density near genes and their degree of transcriptional deregulation when MeCP2 was absent. Our results do not provide support for the hypothesis that CA repeats are key mediators of MeCP2 function. Instead, we found that CA repeats are subject to CAC methylation to a degree that is typical of the surrounding genome and contribute modestly to MeCP2-mediated modulation of gene expression in accordance with their content of this canonical target motif.

Aging is associated with a systemic length-associated transcriptome imbalance

Aging is among the most important risk factors for morbidity and mortality. To contribute toward a molecular understanding of aging, we analyzed age-resolved transcriptomic data from multiple studies. Here, we show that transcript length alone explains most transcriptional changes observed with aging in mice and humans. We present three lines of evidence supporting the biological importance of the uncovered transcriptome imbalance. First, in vertebrates the length association primarily displays a lower relative abundance of long transcripts in aging. Second, eight antiaging interventions of the Interventions Testing Program of the National Institute on Aging can counter this length association. Third, we find that in humans and mice the genes with the longest transcripts enrich for genes reported to extend lifespan, whereas those with the shortest transcripts enrich for genes reported to shorten lifespan. Our study opens fundamental questions on aging and the organization of transcriptomes.

Convergent cerebrospinal fluid proteomes and metabolic ontologies in humans and animal models of Rett syndrome

MECP2 loss-of-function mutations cause Rett syndrome, a neurodevelopmental disorder resulting from a disrupted brain transcriptome. How these transcriptional defects are decoded into a disease proteome remains unknown. We studied the proteome of Rett cerebrospinal fluid (CSF) to identify consensus Rett proteome and ontologies shared across three species. Rett CSF proteomes enriched proteins annotated to HDL lipoproteins, complement, mitochondria, citrate/pyruvate metabolism, synapse compartments, and the neurosecretory protein VGF. We used shared Rett ontologies to select analytes for orthogonal quantification and functional validation. VGF and ontologically selected CSF proteins had genotypic discriminatory capacity as determined by receiver operating characteristic analysis in Mecp2 ^-/y and Mecp2 ^-/+ . Differentially expressed CSF proteins distinguished Rett from a related neurodevelopmental disorder, CDKL5 deficiency disorder. We propose that Mecp2 mutant CSF proteomes and ontologies inform putative mechanisms and biomarkers of disease. We suggest that Rett syndrome results from synapse and metabolism dysfunction.

Long-Term Treatment with Bortezomib Induces Specific Methylation Changes in Differentiated Neuronal Cells

Simple Summary

We exposed LUHMES cells, differentiated into mature neurons, to bortezomib (BTZ) in two treatment cycles and analyzed the methylomes of these cells after each cycle, controlling the analysis for the methylation changes potentially induced by the long-term culture. Our results show that BTZ induces methylation changes that may affect cell morphogenesis, neurogenesis, and neurotransmission. These changes are specifically enriched within transcription factor binding sites of EBF, PAX, DLX, LHX, and HNF family members, which have been shown to regulate neurogenesis and neuronal differentiation. We further show that the observed methylation changes are not present in the SH-SY5Y cells that we used to study mechanisms of development of BTZ resistance. Altogether, our results show that BTZ treatment induces very specific changes in the methylomes of neuronal cells.

Abstract

Bortezomib (BTZ) is proteasome inhibitor, effectively used in the treatment of multiple myeloma, but frequently discontinued due to peripheral neuropathy, which develops in patients after consecutive treatment cycles. The molecular mechanisms affected by BTZ in neuronal cells, which result in neuropathy, remain unknown. However, BTZ is unlikely to lead to permanent morphological nerve damage, because neuropathy reverses after discontinuation of treatment, and nerve cells have very limited renewal capacity. We have previously shown that BTZ induces methylation changes in SH-SY5Y cells, which take part in the development of treatment resistance. Here, we hypothesized that BTZ affects the methylomes of mature neurons, and these changes are associated with BTZ neurotoxicity. Thus, we studied methylomes of neuronal cells, differentiated from the LUHMES cell line, after cycles of treatment with BTZ. Our results show that BTZ induces specific methylation changes in mature neurons, which are not present in SH-SY5Y cells after BTZ treatment. These changes appear to affect genes involved in morphogenesis, neurogenesis, and neurotransmission. Furthermore, identified methylation changes are significantly enriched within binding sites of transcription factors previously linked to neuron physiology, including EBF, PAX, DLX, LHX, and HNF family members. Altogether, our results indicate that methylation changes are likely to be involved in BTZ neurotoxicity.

Slow nucleosome dynamics set the transcriptional speed limit and induce RNA polymerase II traffic jams and bursts

Nucleosomes are recognized as key regulators of transcription. However, the relationship between slow nucleosome unwrapping dynamics and bulk transcriptional properties has not been thoroughly explored. Here, an agent-based model that we call the dynamic defect Totally Asymmetric Simple Exclusion Process (ddTASEP) was constructed to investigate the effects of nucleosome-induced pausing on transcriptional dynamics. Pausing due to slow nucleosome dynamics induced RNAPII convoy formation, which would cooperatively prevent nucleosome rebinding leading to bursts of transcription. The mean first passage time (MFPT) and the variance of first passage time (VFPT) were analytically expressed in terms of the nucleosome rate constants, allowing for the direct quantification of the effects of nucleosome-induced pausing on pioneering polymerase dynamics. The mean first passage elongation rate γ(h_c, h_o) is inversely proportional to the MFPT and can be considered to be a new axis of the ddTASEP phase diagram, orthogonal to the classical αβ-plane (where α and β are the initiation and termination rates). Subsequently, we showed that, for β = 1, there is a novel jamming transition in the αγ-plane that separates the ddTASEP dynamics into initiation-limited and nucleosome pausing-limited regions. We propose analytical estimates for the RNAPII density ρ, average elongation rate v, and transcription flux J and verified them numerically. We demonstrate that the intra-burst RNAPII waiting times t_in follow the time-headway distribution of a max flux TASEP and that the average inter-burst interval tIBI¯ correlates with the index of dispersion D_e. In the limit γ→0, the average burst size reaches a maximum set by the closing rate h_c. When α≪1, the burst sizes are geometrically distributed, allowing large bursts even while the average burst size NB¯ is small. Last, preliminary results on the relative effects of static and dynamic defects are presented to show that dynamic defects can induce equal or greater pausing than static bottle necks.

To perform specific functions, cells must express specific genes by copying the information in DNA into RNA via transcription. Structural proteins called nucleosomes are spaced every 200 base pairs along the length of a strand of DNA and play a crucial function in the regulation of gene activity by tightly binding DNA strands and condensing them into heterochromatin, preventing transcription by RNA polymerase II (RNAPII). Even on active genes where nucleosomes are loosely attached to DNA strands, the wrapping and unwrapping of nucleosomes pause transcription as RNAPII passes by. Previous mathematical models of transcription have compared this biological process to traffic on a one lane highway without obstructions. In contrast, our proposed model simulates transcription like traffic in a grid system where nucleosomes can be thought of as pedestrians or other vehicles crossing the road at regularly spaced intersections. Just as side street traffic and pedestrian crossings can cause cars to form convoys and cause jams limiting the max speed in an area, nucleosomes can cause RNAPII to form convoys that lead to bursts of mRNA production and limit the average polymerase flux through the gene.

Transcriptomic and Epigenomic Landscape in Rett Syndrome

Rett syndrome (RTT) is an extremely invalidating, cureless, developmental disorder, and it is considered one of the leading causes of intellectual disability in female individuals. The vast majority of RTT cases are caused by de novo mutations in the X-linked Methyl-CpG binding protein 2 (MECP2) gene, which encodes a multifunctional reader of methylated DNA. MeCP2 is a master epigenetic modulator of gene expression, with a role in the organization of global chromatin architecture. Based on its interaction with multiple molecular partners and the diverse epigenetic scenario, MeCP2 triggers several downstream mechanisms, also influencing the epigenetic context, and thus leading to transcriptional activation or repression. In this frame, it is conceivable that defects in such a multifaceted factor as MeCP2 lead to large-scale alterations of the epigenome, ranging from an unbalanced deposition of epigenetic modifications to a transcriptional alteration of both protein-coding and non-coding genes, with critical consequences on multiple downstream biological processes. In this review, we provide an overview of the current knowledge concerning the transcriptomic and epigenomic alterations found in RTT patients and animal models.

FMRP attenuates activity dependent modifications in the mitochondrial proteome

Homeostatic plasticity is necessary for the construction and maintenance of functional neuronal networks, but principal molecular mechanisms required for or modified by homeostatic plasticity are not well understood. We recently reported that homeostatic plasticity induced by activity deprivation is dysregulated in cortical neurons from Fragile X Mental Retardation protein (FMRP) knockout mice (Bulow et al. in Cell Rep 26: 1378-1388 e1373, 2019). These findings led us to hypothesize that identifying proteins sensitive to activity deprivation and/or FMRP expression could reveal pathways required for or modified by homeostatic plasticity. Here, we report an unbiased quantitative mass spectrometry used to quantify steady-state proteome changes following chronic activity deprivation in wild type and Fmr1-/y cortical neurons. Proteome hits responsive to both activity deprivation and the Fmr1-/y genotype were significantly annotated to mitochondria. We found an increased number of mitochondria annotated proteins whose expression was sensitive to activity deprivation in Fmr1-/y cortical neurons as compared to wild type neurons. These findings support a novel role of FMRP in attenuating mitochondrial proteome modifications induced by activity deprivation.

Molecular motor traffic with a slow binding site

We discuss how the presence of a slow binding site in molecular motor traffic gives rise to defect-induced "traffic jams" that have properties different from those of the well-studied boundary-induced jams that originate from an imbalance between initiation and termination. To this end we analyze in detail the stationary distribution of a lattice gas model for traffic of molecular motors with a defect. In particular, we obtain analytically the exact spatial distribution of motors, the probability distribution of the random position of the molecular traffic jam and we report unexpected spatial anticorrelations between local molecular motor densities near the defect.

SALL4 controls cell fate in response to DNA base composition

Mammalian genomes contain long domains with distinct average compositions of A/T versus G/C base pairs. In a screen for proteins that might interpret base composition by binding to AT-rich motifs, we identified the stem cell factor SALL4, which contains multiple zinc fingers. Mutation of the domain responsible for AT binding drastically reduced SALL4 genome occupancy and prematurely upregulated genes in proportion to their AT content. Inactivation of this single AT-binding zinc-finger cluster mimicked defects seen in Sall4 null cells, including precocious differentiation of embryonic stem cells (ESCs) and embryonic lethality in mice. In contrast, deletion of two other zinc-finger clusters was phenotypically neutral. Our data indicate that loss of pluripotency is triggered by downregulation of SALL4, leading to de-repression of a set of AT-rich genes that promotes neuronal differentiation. We conclude that base composition is not merely a passive byproduct of genome evolution and constitutes a signal that aids control of cell fate.

Neuronal non-CG methylation is an essential target for MeCP2 function

DNA methylation is implicated in neuronal biology via the protein MeCP2, the mutation of which causes Rett syndrome. MeCP2 recruits the NCOR1/2 co-repressor complexes to methylated cytosine in the CG dinucleotide, but also to sites of non-CG methylation, which are abundant in neurons. To test the biological significance of the dual-binding specificity of MeCP2, we replaced its DNA binding domain with an orthologous domain from MBD2, which can only bind mCG motifs. Knockin mice expressing the domain-swap protein displayed severe Rett-syndrome-like phenotypes, indicating that normal brain function requires the interaction of MeCP2 with sites of non-CG methylation, specifically mCAC. The results support the notion that the delayed onset of Rett syndrome is due to the simultaneous post-natal accumulation of mCAC and its reader MeCP2. Intriguingly, genes dysregulated in both Mecp2 null and domain-swap mice are implicated in other neurological disorders, potentially highlighting targets of relevance to the Rett syndrome phenotype.

Emerging Insights into the Distinctive Neuronal Methylome

The genomes of mammalian neurons are enriched for unique forms of DNA methylation, including exceptionally high levels of non-CG methylation. Here, we review recent studies defining how non-CG methylation accumulates in neurons and is read out by the critical regulator of neuronal transcription, MeCP2. We discuss the role of gene expression and genome architecture in establishing non-CG methylation and highlight emerging mechanistic insights into how non-CG methylation and MeCP2 control transcription. Further, we describe the cell type-specific functions of this methylation and explore growing evidence that disruption of this regulatory pathway contributes to neurodevelopmental disorders. These findings uncover how the distinctive epigenome in neurons facilitates the development and function of the complex mammalian brain.

Current-density relation in the exclusion process with dynamic obstacles

We investigate the totally asymmetric simple exclusion process (TASEP) in the presence of obstacles that dynamically bind and unbind from the lattice. The model is motivated by biological processes such as transcription in the presence of DNA-binding proteins. Similar models have been studied before using the mean-field approximation, but the exact relation between the particle current and density remains elusive. Here, we first show using extensive Monte Carlo simulations that the current-density relation in this model assumes a quasiparabolic form similar to that of the ordinary TASEP without obstacles. We then attempt to explain this relation using exact calculations in the limit of low and high density of particles. Our results suggest that the symmetric, quasiparabolic current-density relation arises through a nontrivial cancellation of higher-order terms, similarly as in the standard TASEP.

Quantitative analysis questions the role of MeCP2 as a global regulator of alternative splicing

MeCP2 is an abundant protein in mature nerve cells, where it binds to DNA sequences containing methylated cytosine. Mutations in the MECP2 gene cause the severe neurological disorder Rett syndrome (RTT), provoking intensive study of the underlying molecular mechanisms. Multiple functions have been proposed, one of which involves a regulatory role in splicing. Here we leverage the recent availability of high-quality transcriptomic data sets to probe quantitatively the potential influence of MeCP2 on alternative splicing. Using a variety of machine learning approaches that can capture both linear and non-linear associations, we show that widely different levels of MeCP2 have a minimal effect on alternative splicing in three different systems. Alternative splicing was also apparently indifferent to developmental changes in DNA methylation levels. Our results suggest that regulation of splicing is not a major function of MeCP2. They also highlight the importance of multi-variate quantitative analyses in the formulation of biological hypotheses.

Absence of MeCP2 binding to non-methylated GT-rich sequences in vivo

MeCP2 is a nuclear protein that binds to sites of cytosine methylation in the genome. While most evidence confirms this epigenetic mark as the primary determinant of DNA binding, MeCP2 is also reported to have an affinity for non-methylated DNA sequences. Here we investigated the molecular basis and in vivo significance of its reported affinity for non-methylated GT-rich sequences. We confirmed this interaction with isolated domains of MeCP2 in vitro and defined a minimal target DNA sequence. Binding depends on pyrimidine 5′ methyl groups provided by thymine and requires adjacent guanines and a correctly orientated A/T-rich flanking sequence. Unexpectedly, full-length MeCP2 protein failed to bind GT-rich sequences in vitro. To test for MeCP2 binding to these motifs in vivo, we analysed human neuronal cells using ChIP-seq and ATAC-seq technologies. While both methods robustly detected DNA methylation-dependent binding of MeCP2 to mCG and mCAC, neither showed evidence of MeCP2 binding to GT-rich motifs. The data suggest that GT binding is an in vitro phenomenon without in vivo relevance. Our findings argue that MeCP2 does not read unadorned DNA sequence and therefore support the notion that its primary role is to interpret epigenetic modifications of DNA.

Regulation of GABAA Receptor Subunit Expression in Substance Use Disorders

The modulation of neuronal cell firing is mediated by the release of the neurotransmitter GABA (γ-aminobuytric acid), which binds to two major families of receptors. The ionotropic GABAA receptors (GABA_ARs) are composed of five distinct subunits that vary in expression by brain region and cell type. The action of GABA on GABA_ARs is modulated by a variety of clinically and pharmacologically important drugs such as benzodiazepines and alcohol. Exposure to and abuse of these substances disrupts homeostasis and induces plasticity in GABAergic neurotransmission, often via the regulation of receptor expression. Here, we review the regulation of GABA_AR subunit expression in adaptive and pathological plasticity, with a focus on substance use. We examine the factors influencing the expression of GABA_AR subunit genes including the regulation of the 5′ and 3′ untranslated regions, variations in DNA methylation, immediate early genes and transcription factors that regulate subunit expression, translational and post-translational modifications, and other forms of receptor regulation beyond expression. Advancing our understanding of the factors regulating GABA_AR subunit expression during adaptive plasticity, as well as during substance use and withdrawal will provide insight into the role of GABAergic signaling in substance use disorders, and contribute to the development of novel targeted therapies.

The Molecular Basis of MeCP2 Function in the Brain

MeCP2 is a reader of the DNA methylome that occupies a large proportion of the genome due to its high abundance and the frequency of its target sites. It has been the subject of extensive study because of its link with 'MECP2-related disorders', of which Rett syndrome is the most prevalent. This review integrates evidence from patient mutation data with results of experimental studies using mouse models, cell lines and in vitro systems to critically evaluate our understanding of MeCP2 protein function. Recent evidence challenges the idea that MeCP2 is a multifunctional hub that integrates diverse processes to underpin neuronal function, suggesting instead that its primary role is to recruit the NCoR1/2 co-repressor complex to methylated sites in the genome, leading to dampening of gene expression.

MeCP2 Represses Enhancers through Chromosome Topology-Associated DNA Methylation

The genomes of mammalian neurons contain uniquely high levels of non-CG DNA methylation that can be bound by the Rett syndrome protein, MeCP2, to regulate gene expression. How patterns of non-CG methylation are established in neurons and the mechanism by which this methylation works with MeCP2 to control gene expression is unclear. Here, we find that genes repressed by MeCP2 are often located within megabase-scale regions of high non-CG methylation that correspond with topologically associating domains of chromatin folding. MeCP2 represses enhancers found in these domains that are enriched for non-CG and CG methylation, with the strongest repression occurring for enhancers located within MeCP2-repressed genes. These alterations in enhancer activity provide a mechanism for how MeCP2 disruption in disease can lead to widespread changes in gene expression. Hence, we find that DNA topology can shape non-CG DNA methylation across the genome to dictate MeCP2-mediated enhancer regulation in the brain.

MeCP2 Represses the Rate of Transcriptional Initiation of Highly Methylated Long Genes

Mutations in the methyl-DNA-binding repressor protein MeCP2 cause the devastating neurodevelopmental disorder Rett syndrome. It has been challenging to understand how MeCP2 regulates transcription because MeCP2 binds broadly across the genome and MeCP2 mutations are associated with widespread small-magnitude changes in neuronal gene expression. We demonstrate here that MeCP2 represses nascent RNA transcription of highly methylated long genes in the brain through its interaction with the NCoR co-repressor complex. By measuring the rates of transcriptional initiation and elongation directly in the brain, we find that MeCP2 has no measurable effect on transcriptional elongation, but instead represses the rate at which Pol II initiates transcription of highly methylated long genes. These findings suggest a new model of MeCP2 function in which MeCP2 binds broadly across highly methylated regions of DNA, but acts at transcription start sites to attenuate transcriptional initiation.

The Bright and Dark Side of DNA Methylation: A Matter of Balance

DNA methylation controls several cellular processes, from early development to old age, including biological responses to endogenous or exogenous stimuli contributing to disease transition. As a result, minimal DNA methylation changes during developmental stages drive severe phenotypes, as observed in germ-line imprinting disorders, while genome-wide alterations occurring in somatic cells are linked to cancer onset and progression. By summarizing the molecular events governing DNA methylation, we focus on the methods that have facilitated mapping and understanding of this epigenetic mark in healthy conditions and diseases. Overall, we review the bright (health-related) and dark (disease-related) side of DNA methylation changes, outlining how bulk and single-cell genomic analyses are moving toward the identification of new molecular targets and driving the development of more specific and less toxic demethylating agents.

Quantitative modelling predicts the impact of DNA methylation on RNA polymerase II traffic

Patterns of gene expression are primarily determined by proteins that locally enhance or repress transcription. While many transcription factors target a restricted number of genes, others appear to modulate transcription levels globally. An example is MeCP2, an abundant methylated-DNA binding protein that is mutated in the neurological disorder Rett syndrome. Despite much research, the molecular mechanism by which MeCP2 regulates gene expression is not fully resolved. Here, we integrate quantitative, multidimensional experimental analysis and mathematical modeling to indicate that MeCP2 is a global transcriptional regulator whose binding to DNA creates "slow sites" in gene bodies. We hypothesize that waves of slowed-down RNA polymerase II formed behind these sites travel backward and indirectly affect initiation, reminiscent of defect-induced shockwaves in nonequilibrium physics transport models. This mechanism differs from conventional gene-regulation mechanisms, which often involve direct modulation of transcription initiation. Our findings point to a genome-wide function of DNA methylation that may account for the reversibility of Rett syndrome in mice. Moreover, our combined theoretical and experimental approach provides a general method for understanding how global gene-expression patterns are choreographed.

Molecular Systems Biology of Neurodevelopmental Disorders, Rett Syndrome as an Archetype

Neurodevelopmental disorders represent a challenging biological and medical problem due to their genetic and phenotypic complexity. In many cases, we lack the comprehensive understanding of disease mechanisms necessary for targeted therapeutic development. One key component that could improve both mechanistic understanding and clinical trial design is reliable molecular biomarkers. Presently, no objective biological markers exist to evaluate most neurodevelopmental disorders. Here, we discuss how systems biology and "omic" approaches can address the mechanistic and biomarker limitations in these afflictions. We present heuristic principles for testing the potential of systems biology to identify mechanisms and biomarkers of disease in the example of Rett syndrome, a neurodevelopmental disorder caused by a well-defined monogenic defect in methyl-CpG-binding protein 2 (MECP2). We propose that such an approach can not only aid in monitoring clinical disease severity but also provide a measure of target engagement in clinical trials. By deepening our understanding of the "big picture" of systems biology, this approach could even help generate hypotheses for drug development programs, hopefully resulting in new treatments for these devastating conditions.