Chromatin immunoprecipitation indirect peaks highlight long-range interactions of insulator proteins and Pol II pausing.

Eukaryotic chromosomes are partitioned into topologically associating domains (TADs) that are demarcated by distinct insulator-binding proteins (IBPs) in Drosophila. Whether IBPs regulate specific long-range contacts and how this may impact gene expression remains unclear. Here we identify "indirect peaks" of multiple IBPs that represent their distant sites of interactions through long-range contacts. Indirect peaks depend on protein-protein interactions among multiple IBPs and their common cofactors, including CP190, as confirmed by high-resolution analyses of long-range contacts. Mutant IBPs unable to interact with CP190 impair long-range contacts as well as the expression of hundreds of distant genes that are specifically flanked by indirect peaks. Regulation of distant genes strongly correlates with RNAPII pausing, highlighting how this key transcriptional stage may trap insulator-based long-range interactions. Our data illustrate how indirect peaks may decipher gene regulatory networks through specific long-range interactions.

Substrate stiffness tunes the dynamics of polyvalent rolling motors.

Nature has evolved many mechanisms for achieving directed motion on the subcellular level. The burnt-bridges ratchet (BBR) is one mechanism used to achieve superdiffusive molecular motion over long distances through the successive cleavage of surface-bound energy-rich substrate sites. This mechanism has been associated with both nanoscale and microscale movement, with the latter accomplished through polyvalent interactions between a large hub (e.g. influenza virus) and substrate (e.g. cell surface receptors). Experimental successes in achieving superdiffusive motion by synthetic polyvalent BBRs have raised questions about the dynamics of their motility, including whether rolling or translation is better able to direct motion of microscale spherical hubs. Here we simulate the three-dimensional dynamics of a polyvalent sphere moving on and cleaving an elastic substrate. We find that substrate stiffness plays an important role in controlling both the motor's mode of motility and its directional persistence. As we tune lateral substrate stiffness from soft to stiff we find there exists an intermediate value that optimizes rolling behaviour. We also find that there is an optimal substrate stiffness for maximizing persistence length, while stiffness does not influence as strongly the superdiffusive dynamics of the particle. Lastly, we examine the effect of substrate density, and show that softer landscapes are better able to buffer against decreases in substrate occupancy, with the spherical motor maintaining superdiffusive motion more on softer landscapes than on stiff landscapes as occupancy drops. Our results highlight the importance of surface in controlling the motion of polyvalent BBRs.

Abrupt, Asynchronous Changes in Action Representations by Anterior Cingulate Cortex Neurons during Trial and Error Learning.

The ability to act on knowledge about the value of stimuli or actions factors into simple foraging behaviors as well as complex forms of decision-making. In striatal regions, action representations are thought to acquire value through a gradual (reinforcement-learning based) process. It is unclear whether this is also true for anterior cingulate cortex (ACC) where neuronal representations tend to change abruptly. We recorded from ensembles of ACC neurons as rats deduced which of 3 levers was rewarded each day. The rat's lever preferences changed gradually throughout the sessions as they eventually came to focus on the rewarded lever. Most individual neurons changed their responses to both rewarded and nonrewarded lever presses abruptly (<2 trials). These transitions occurred asynchronously across the population but peaked near the point where the rats began to focus on the rewarded lever. Because the individual transitions were asynchronous, the overall change at the population level appeared gradual. Abrupt transitions in action representations of ACC neurons may be part of a mechanism that alters choice strategies as new information is acquired.

A maximum-entropy model for predicting chromatin contacts.

The packaging of DNA inside a nucleus shows complex structure stabilized by a host of DNA-bound factors. Both the distribution of these factors and the contacts between different genomic locations of the DNA can now be measured on a genome-wide scale. This has advanced the development of models aimed at predicting the conformation of DNA given only the locations of bound factors-the chromatin folding problem. Here we present a maximum-entropy model that is able to predict a contact map representation of structure given a sequence of bound factors. Non-local effects due to the sequence neighborhood around contacting sites are found to be important for making accurate predictions. Lastly, we show that the model can be used to infer a sequence of bound factors given only a measurement of structure. This opens up the possibility for efficiently predicting sequence regions that may play a role in generating cell-type specific structural differences.

Children's biobehavioral reactivity to challenge predicts DNA methylation in adolescence and emerging adulthood.

A growing body of research has documented associations between adverse childhood environments and DNA methylation, highlighting epigenetic processes as potential mechanisms through which early external contexts influence health across the life course. The present study tested a complementary hypothesis: indicators of children's early internal, biological, and behavioral responses to stressful challenges may also be linked to stable patterns of DNA methylation later in life. Children's autonomic nervous system reactivity, temperament, and mental health symptoms were prospectively assessed from infancy through early childhood, and principal components analysis (PCA) was applied to derive composites of biological and behavioral reactivity. Buccal epithelial cells were collected from participants at 15 and 18 years of age. Findings revealed an association between early life biobehavioral inhibition/disinhibition and DNA methylation across many genes. Notably, reactive, inhibited children were found to have decreased DNA methylation of the DLX5 and IGF2 genes at both time points, as compared to non-reactive, disinhibited children. Results of the present study are provisional but suggest that the gene's profile of DNA methylation may constitute a biomarker of normative or potentially pathological differences in reactivity. Overall, findings provide a foundation for future research to explore relations among epigenetic processes and differences in both individual-level biobehavioral risk and qualities of the early, external childhood environment.

Splitting the task: Ubp8 and Ubp10 deubiquitinate different cellular pools of H2BK123.

Monoubiquitination of H2BK123 (H2BK123ub), catalyzed by Rad6/Bre1, is a transient histone modification with roles in transcription and is essential for establishing H3K4 and H3K79 trimethylations (H3K4me3 and H3K79me3). Here, we investigated the chromatin network around H2BK123ub by examining its localization and co-occurrence with its dependent marks as well as the transcription elongation mark H3K36me3 across the genome of Saccharomyces cerevisiae. In yeast, H2BK123ub is removed by the deubiquitinases Ubp8 and Ubp10, but their genomic target regions remain to be determined. Genome-wide maps of H2BK123ub in the absence of Ubp8 and Ubp10 revealed their distinct target loci, which were genomic sites enriched for H3K4me3 and H3K79me3, respectively. We propose an extended model of the H2BK123ub cross-talk by integrating existing relationships with the substrate specificities of Ubp8 and Ubp10 reported here.

Dense neural networks for predicting chromatin conformation.

BACKGROUND: DNA inside eukaryotic cells wraps around histones to form the 11nm chromatin fiber that can further fold into higher-order DNA loops, which may depend on the binding of architectural factors. Predicting how the DNA will fold given a distribution of bound factors, here viewed as a type of sequence, is currently an unsolved problem and several heterogeneous polymer models have shown that many features of the measured structure can be reproduced from simulations. However a model that determines the optimal connection between sequence and structure and that can rapidly assess the effects of varying either one is still lacking. RESULTS: Here we train a dense neural network to solve for the local folding of chromatin, connecting structure, represented as a contact map, to a sequence of bound chromatin factors. The network includes a convolutional filter that compresses the large number of bound chromatin factors into a single 1D sequence representation that is optimized for predicting structure. We also train a network to solve the inverse problem, namely given only structural information in the form of a contact map, predict the likely sequence of chromatin states that generated it. CONCLUSIONS: By carrying out sensitivity analysis on both networks, we are able to highlight the importance of chromatin contexts and neighborhoods for regulating long-range contacts, along with critical alterations that affect contact formation. Our analysis shows that the networks have learned physical insights that are informative and intuitive about this complex polymer problem.

Insulators recruit histone methyltransferase dMes4 to regulate chromatin of flanking genes.

Chromosomal domains in Drosophila are marked by the insulator-binding proteins (IBPs) dCTCF/Beaf32 and cofactors that participate in regulating long-range interactions. Chromosomal borders are further enriched in specific histone modifications, yet the role of histone modifiers and nucleosome dynamics in this context remains largely unknown. Here, we show that IBP depletion impairs nucleosome dynamics specifically at the promoters and coding sequence of genes flanked by IBP binding sites. Biochemical purification identifies the H3K36 histone methyltransferase NSD/dMes-4 as a novel IBP cofactor, which specifically co-regulates the chromatin accessibility of hundreds of genes flanked by dCTCF/Beaf32. NSD/dMes-4 presets chromatin before the recruitment of transcriptional activators including DREF that triggers Set2/Hypb-dependent H3K36 trimethylation, nucleosome positioning, and RNA splicing. Our results unveil a model for how IBPs regulate nucleosome dynamics and gene expression through NSD/dMes-4, which may regulate H3K27me3 spreading. Our data uncover how IBPs dynamically regulate chromatin organization depending on distinct cofactors.

Operational Principles for the Dynamics of the In Vitro ParA-ParB System.

In many bacteria the ParA-ParB protein system is responsible for actively segregating DNA during replication. ParB proteins move by interacting with DNA bound ParA-ATP, stimulating their unbinding by catalyzing hydrolysis, that leads to rectified motion due to the creation of a wake of depleted ParA. Recent in vitro experiments have shown that a ParB covered magnetic bead can move with constant speed over a DNA covered substrate that is bound by ParA. It has been suggested that the formation of a gradient in ParA leads to diffusion-ratchet like motion of the ParB bead but how it forms and generates a force is still a matter of exploration. Here we develop a deterministic model for the in vitro ParA-ParB system and show that a ParA gradient can spontaneously form due to any amount of initial spatial noise in bound ParA. The speed of the bead is independent of this noise but depends on the ratio of the range of ParA-ParB force on the bead to that of removal of surface bound ParA by ParB. We find that at a particular ratio the speed attains a maximal value. We also consider ParA rebinding (including cooperativity) and ParA surface diffusion independently as mechanisms for ParA recovery on the surface. Depending on whether the DNA covered surface is undersaturated or saturated with ParA, we find that the bead can accelerate persistently or potentially stall. Our model highlights key requirements of the ParA-ParB driving force that are necessary for directed motion in the in vitro system that may provide insight into the in vivo dynamics of the ParA-ParB system.

Dissecting genealogy and cell cycle as sources of cell-to-cell variability in MAPK signaling using high-throughput lineage tracking.

Cells, even those having identical genotype, exhibit variability in their response to external stimuli. This variability arises from differences in the abundance, localization, and state of cellular components. Such nongenetic differences are likely heritable between successive generations and can also be influenced by processes such as cell cycle, age, or interplay between different pathways. To address the contribution of nongenetic heritability and cell cycle in cell-to-cell variability we developed a high-throughput and fully automated microfluidic platform that allows for concurrent measurement of gene expression, cell-cycle periods, age, and lineage information under a large number of temporally changing medium conditions and using multiple strains. We apply this technology to examine the role of nongenetic inheritance in cell heterogeneity of yeast pheromone signaling. Our data demonstrate that the capacity to respond to pheromone is passed across generations and that the strength of the response correlations between related cells is affected by perturbations in the signaling pathway. We observe that a ste50Δ mutant strain exhibits highly heterogeneous response to pheromone originating from a unique asymmetry between mother and daughter response. On the other hand, fus3Δ cells were found to exhibit an unusually high correlation between mother and daughter cells that arose from a combination of extended cell-cycle periods of fus3Δ mothers, and decreased cell-cycle modulation of the pheromone pathway. Our results contribute to the understanding of the origins of cell heterogeneity and demonstrate the importance of automated platforms that generate single-cell data on several parameters.

Probing long-range interactions by extracting free energies from genome-wide chromosome conformation capture data.

BACKGROUND: A variety of DNA binding proteins are involved in regulating and shaping the packing of chromatin. They aid the formation of loops in the DNA that function to isolate different structural domains. A recent experimental technique, Hi-C, provides a method for determining the frequency of such looping between all distant parts of the genome. Given that the binding locations of many chromatin associated proteins have also been measured, it has been possible to make estimates for their influence on the long-range interactions as measured by Hi-C. However, a challenge in this analysis is the predominance of non-specific contacts that mask out the specific interactions of interest. RESULTS: We show that transforming the Hi-C contact frequencies into free energies gives a natural method for separating out the distance dependent non-specific interactions. In particular we apply Principal Component Analysis (PCA) to the transformed free energy matrix to identify the dominant modes of interaction. PCA identifies systematic effects as well as high frequency spatial noise in the Hi-C data which can be filtered out. Thus it can be used as a data driven approach for normalizing Hi-C data. We assess this PCA based normalization approach, along with several other normalization schemes, by fitting the transformed Hi-C data using a pairwise interaction model that takes as input the known locations of bound chromatin factors. The result of fitting is a set of predictions for the coupling energies between the various chromatin factors and their effect on the energetics of looping. We show that the quality of the fit can be used as a means to determine how much PCA filtering should be applied to the Hi-C data. CONCLUSIONS: We find that the different normalizations of the Hi-C data vary in the quality of fit to the pairwise interaction model. PCA filtering can improve the fit, and the predicted coupling energies lead to biologically meaningful insights for how various chromatin bound factors influence the stability of DNA loops in chromatin.

Factors underlying variable DNA methylation in a human community cohort.

Epigenetics is emerging as an attractive mechanism to explain the persistent genomic embedding of early-life experiences. Tightly linked to chromatin, which packages DNA into chromosomes, epigenetic marks primarily serve to regulate the activity of genes. DNA methylation is the most accessible and characterized component of the many chromatin marks that constitute the epigenome, making it an ideal target for epigenetic studies in human populations. Here, using peripheral blood mononuclear cells collected from a community-based cohort stratified for early-life socioeconomic status, we measured DNA methylation in the promoter regions of more than 14,000 human genes. Using this approach, we broadly assessed and characterized epigenetic variation, identified some of the factors that sculpt the epigenome, and determined its functional relation to gene expression. We found that the leukocyte composition of peripheral blood covaried with patterns of DNA methylation at many sites, as did demographic factors, such as sex, age, and ethnicity. Furthermore, psychosocial factors, such as perceived stress, and cortisol output were associated with DNA methylation, as was early-life socioeconomic status. Interestingly, we determined that DNA methylation was strongly correlated to the ex vivo inflammatory response of peripheral blood mononuclear cells to stimulation with microbial products that engage Toll-like receptors. In contrast, our work found limited effects of DNA methylation marks on the expression of associated genes across individuals, suggesting a more complex relationship than anticipated.

Action and outcome activity state patterns in the anterior cingulate cortex.

Although there are numerous theories regarding anterior cingulate cortex (ACC) function, most suggest that it is involved in some form of action or outcome processing. The present study characterized the dominant patterns of ACC activity on a task in which actions and outcomes could vary independently. Patterns of activity were detected using a modified form of principal component analysis (PCA), termed constrained PCA in which a regression procedure was applied prior to PCA to eliminate the contribution of nontask-related activity. When trials were grouped according to outcome, a PC was found in all subjects and sessions that had large fluctuations during actions but only differentiated correct versus error trials prior to the end of the delay and again at time of the outcome. Another PC was always present that separated right from left lever presses, but only around the time of the actual lever press. Individual neurons exhibited significant selectivities for trials involving different actions and/or outcomes. Of the ACC neurons that exhibited significant outcome selectivity, the majority fired more on error trials. The present study revealed separate as well as integrated action and outcome monitoring in the ACC, especially, although not exclusively, under conditions when an error is likely.

Neural basis of cognitive control signals in anterior cingulate cortex during delay discounting.

Cognitive control involves allocating cognitive effort according to internal needs and task demands and the Anterior Cingulate Cortex (ACC) is hypothesized to play a central role in this process. We investigated the neural basis of cognitive control in the ACC of rats performing an adjusting-amount delay discounting task. Decision-making in this this task can be guided by using either a lever-value tracking strategy, requiring a 'resource-based' form of cognitive effort or a lever-biased strategy requiring a 'resistance-based' form of cognitive effort. We found that ACC ensembles always tightly tracked lever value on each trial, indicative of a resource-based control signal. These signals were prevalent in the neural recordings and were influenced by the delay. A shorter delay was associated with devaluing of the immediate option and a longer delay was associated with overvaluing of the immediate option. In addition, ACC theta (6-12Hz) oscillations were observed at the choice point of rats exhibiting a resistance-based strategy. These data provide candidates of neural activity patterns in the ACC that underlie the use of 'resource-based' and 'resistance-based' cognitive effort. Furthermore, these data illustrate how strategies can be engaged under different conditions in individual subjects.

CHROMATRA: a Galaxy tool for visualizing genome-wide chromatin signatures.

UNLABELLED: CHROMATRA (CHROmatin Mapping Across TRAnscripts) is a visualization tool available as plug-in for the Galaxy platform. It allows detailed yet concise presentations of data derived from ChIP-chip or ChIP-seq experiments by visualizing enrichment scores across genes or other genomic features while accounting for their length and additional characteristics such as gene expression. It integrates into typical analysis workflows and enables rapid graphical assessment and comparison of genome-wide data at a glance. AVAILABILITY: https://github.com/cmmt/chromatra.

Optimizing Efficiency and Motility of a Polyvalent Molecular Motor.

Molecular motors play a vital role in the transport of material within the cell. A family of motors of growing interest are burnt bridge ratchets (BBRs). BBRs rectify spatial fluctuations into directed motion by creating and destroying motor-substrate bonds. It has been shown that the motility of a BBR can be optimized as a function of the system parameters. However, the amount of energy input required to generate such motion and the resulting efficiency has been less well characterized. Here, using a deterministic model, we calculate the efficiency of a particular type of BBR, namely a polyvalent hub interacting with a surface of substrate. We find that there is an optimal burn rate and substrate concentration that leads to optimal efficiency. Additionally, the substrate turnover rate has important implications on motor efficiency. We also consider the effects of force-dependent unbinding on the efficiency and find that under certain conditions the motor works more efficiently when bond breaking is included. Our results provide guidance for how to optimize the efficiency of BBRs.

Extensive androgen receptor enhancer heterogeneity in primary prostate cancers underlies transcriptional diversity and metastatic potential.

Androgen receptor (AR) drives prostate cancer (PCa) development and progression. AR chromatin binding profiles are highly plastic and form recurrent programmatic changes that differentiate disease stages, subtypes and patient outcomes. While prior studies focused on concordance between patient subgroups, inter-tumor heterogeneity of AR enhancer selectivity remains unexplored. Here we report high levels of AR chromatin binding heterogeneity in human primary prostate tumors, that overlap with heterogeneity observed in healthy prostate epithelium. Such heterogeneity has functional consequences, as somatic mutations converge on commonly-shared AR sites in primary over metastatic tissues. In contrast, less-frequently shared AR sites associate strongly with AR-driven gene expression, while such heterogeneous AR enhancer usage also distinguishes patients' outcome. These findings indicate that epigenetic heterogeneity in primary disease is directly informative for risk of biochemical relapse. Cumulatively, our results illustrate a high level of AR enhancer heterogeneity in primary PCa driving differential expression and clinical impact.

BEAF regulates cell-cycle genes through the controlled deposition of H3K9 methylation marks into its conserved dual-core binding sites.

Chromatin insulators/boundary elements share the ability to insulate a transgene from its chromosomal context by blocking promiscuous enhancer-promoter interactions and heterochromatin spreading. Several insulating factors target different DNA consensus sequences, defining distinct subfamilies of insulators. Whether each of these families and factors might possess unique cellular functions is of particular interest. Here, we combined chromatin immunoprecipitations and computational approaches to break down the binding signature of the Drosophila boundary element-associated factor (BEAF) subfamily. We identify a dual-core BEAF binding signature at 1,720 sites genome-wide, defined by five to six BEAF binding motifs bracketing 200 bp AT-rich nuclease-resistant spacers. Dual-cores are tightly linked to hundreds of genes highly enriched in cell-cycle and chromosome organization/segregation annotations. siRNA depletion of BEAF from cells leads to cell-cycle and chromosome segregation defects. Quantitative RT-PCR analyses in BEAF-depleted cells show that BEAF controls the expression of dual core-associated genes, including key cell-cycle and chromosome segregation regulators. beaf mutants that impair its insulating function by preventing proper interactions of BEAF complexes with the dual-cores produce similar effects in embryos. Chromatin immunoprecipitations show that BEAF regulates transcriptional activity by restricting the deposition of methylated histone H3K9 marks in dual-cores. Our results reveal a novel role for BEAF chromatin dual-cores in regulating a distinct set of genes involved in chromosome organization/segregation and the cell cycle.

Chromosome driven spatial patterning of proteins in bacteria.

The spatial patterning of proteins in bacteria plays an important role in many processes, from cell division to chemotaxis. In the asymmetrically dividing bacteria Caulobacter crescentus, a scaffolding protein, PopZ, localizes to both poles and aids the differential patterning of proteins between mother and daughter cells during division. Polar patterning of misfolded proteins in Escherichia coli has also been shown, and likely plays an important role in cellular ageing. Recent experiments on both of the above systems suggest that the presence of chromosome free regions along with protein multimerization may be a mechanism for driving the polar localization of proteins. We have developed a simple physical model for protein localization using only these two driving mechanisms. Our model reproduces all the observed patterns of PopZ and misfolded protein localization--from diffuse, unipolar, and bipolar patterns and can also account for the observed patterns in a variety of mutants. The model also suggests new experiments to further test the role of the chromosome in driving protein patterning, and whether such a mechanism is responsible for helping to drive the differentiation of the cell poles.