Taking into account nucleosomes for predicting gene expression

Predicting p53-dependent cell transitions from thermodynamic models

A cell's fate involves transitions among its various states, each defined by a distinct gene expression profile governed by the topology of gene regulatory networks, which are affected by 3D genome organization. Here, we develop thermodynamic models to determine the fate of a malignant cell as governed by the tumor suppressor p53 signaling network, taking into account long-range chromatin interactions in the mean-field approximation. The tumor suppressor p53 responds to stress by selectively triggering one of the potential transcription programs that influence many layers of cell signaling. These range from p53 phosphorylation to modulation of its DNA binding affinity, phase separation phenomena, and internal connectivity among cell fate genes. We use the minimum free energy of the system as a fundamental property of biological networks that influences the connection between the gene network topology and the state of the cell. We constructed models based on network topology and equilibrium thermodynamics. Our modeling shows that the binding of phosphorylated p53 to promoters of target genes can have properties of a first order phase transition. We apply our model to cancer cell lines ranging from breast cancer (MCF-7), colon cancer (HCT116), and leukemia (K562), with each one characterized by a specific network topology that determines the cell fate. Our results clarify the biological relevance of these mechanisms and suggest that they represent flexible network designs for switching between developmental decisions.

DNA sequence-dependent formation of heterochromatin nanodomains

The mammalian epigenome contains thousands of heterochromatin nanodomains (HNDs) marked by di- and trimethylation of histone H3 at lysine 9 (H3K9me2/3), which have a typical size of 3–10 nucleosomes. However, what governs HND location and extension is only partly understood. Here, we address this issue by introducing the chromatin hierarchical lattice framework (ChromHL) that predicts chromatin state patterns with single-nucleotide resolution. ChromHL is applied to analyse four HND types in mouse embryonic stem cells that are defined by histone methylases SUV39H1/2 or GLP, transcription factor ADNP or chromatin remodeller ATRX. We find that HND patterns can be computed from PAX3/9, ADNP and LINE1 sequence motifs as nucleation sites and boundaries that are determined by DNA sequence (e.g. CTCF binding sites), cooperative interactions between nucleosomes as well as nucleosome-HP1 interactions. Thus, ChromHL rationalizes how patterns of H3K9me2/3 are established and changed via the activity of protein factors in processes like cell differentiation.

The ability to predict epigenetic regulation is an important challenge in biology. Here the authors describe heterochromatin nanodomains (HNDs) and compare four different types of H3K9me2/3-marked HNDs in mouse embryonic stem cells. They further develop a computational framework to predict genome-wide HND maps from DNA sequence and protein concentrations, at single-nucleotide resolution.

Hetero-association models of non-covalent molecular complexation

The present review discusses the current state-of-the-art in building models enabling the description of non-covalent equilibrium complexation of different types of molecules in solution, which results in the formation of supramolecular structures different in length and composition (hetero-association or supramolecular multicomponent co-polymerisation). The description is focused on standard physical and chemical quantities such as experimental observables and equilibrium parameters of interaction (equilibrium constants and concentrations). The major partial cases of the hetero-association models, such as finite and indefinite isodesmic and cooperative complexations, and Benesi-Hildebrand and Langmuir adsorption models are considered. Future challenges in the development of the hetero-association models are provided.

Poly(ADP-ribosyl)ation associated changes in CTCF-chromatin binding and gene expression in breast cells

CTCF is an evolutionarily conserved and ubiquitously expressed architectural protein regulating a plethora of cellular functions via different molecular mechanisms. CTCF can undergo a number of post-translational modifications which change its properties and functions. One such modifications linked to cancer is poly(ADP-ribosyl)ation (PARylation). The highly PARylated CTCF form has an apparent molecular mass of 180 kDa (referred to as CTCF180), which can be distinguished from hypo- and non-PARylated CTCF with the apparent molecular mass of 130 kDa (referred to as CTCF130). The existing data accumulated so far have been mainly related to CTCF130. However, the properties of CTCF180 are not well understood despite its abundance in a number of primary tissues. In this study we performed ChIP-seq and RNA-seq analyses in human breast cells 226LDM, which display predominantly CTCF130 when proliferating, but CTCF180 upon cell cycle arrest. We observed that in the arrested cells the majority of sites lost CTCF, whereas fewer sites gained CTCF or remain bound (i.e. common sites). The classical CTCF binding motif was found in the lost and common, but not in the gained sites. The changes in CTCF occupancies in the lost and common sites were associated with increased chromatin densities and altered expression from the neighboring genes. Based on these results we propose a model integrating the CTCF130/180 transition with CTCF-DNA binding and gene expression changes. This study also issues an important cautionary note concerning the design and interpretation of any experiments using cells and tissues where CTCF180 may be present.

Frequency Modulation of Transcriptional Bursting Enables Sensitive and Rapid Gene Regulation

Gene regulation is a complex non-equilibrium process. Here, we show that quantitating the temporal regulation of key gene states (transcriptionally inactive, active, and refractory) provides a parsimonious framework for analyzing gene regulation. Our theory makes two non-intuitive predictions. First, for transcription factors (TFs) that regulate transcription burst frequency, as opposed to amplitude or duration, weak TF binding is sufficient to elicit strong transcriptional responses. Second, refractoriness of a gene after a transcription burst enables rapid responses to stimuli. We validate both predictions experimentally by exploiting the natural, optogenetic-like responsiveness of the Neurospora GATA-type TF White Collar Complex (WCC) to blue light. Further, we demonstrate that differential regulation of WCC target genes is caused by different gene activation rates, not different TF occupancy, and that these rates are tuned by both the core promoter and the distance between TF-binding site and core promoter. In total, our work demonstrates the relevance of a kinetic, non-equilibrium framework for understanding transcriptional regulation.

A sequence level model of an intact locus predicts the location and function of nonadditive enhancers

Metazoan gene expression is controlled through the action of long stretches of noncoding DNA that contain enhancers-shorter sequences responsible for controlling a single aspect of a gene's expression pattern. Models built on thermodynamics have shown how enhancers interpret protein concentration in order to determine specific levels of gene expression, but the emergent regulatory logic of a complete regulatory locus shows qualitative and quantitative differences from isolated enhancers. Such differences may arise from steric competition limiting the quantity of DNA that can simultaneously influence the transcription machinery. We incorporated this competition into a mechanistic model of gene regulation, generated efficient algorithms for this computation, and applied it to the regulation of Drosophila even-skipped (eve). This model finds the location of enhancers and identifies which factors control the boundaries of eve expression. This model predicts a new enhancer that, when assayed in vivo, drives expression in a non-eve pattern. Incorporation of chromatin accessibility eliminates this inconsistency.

Specificity-Determining DNA Triplet Code for Positioning of Human Preinitiation Complex

The notion that transcription factors bind DNA only through specific, consensus binding sites has been recently questioned. No specific consensus motif for the positioning of the human preinitiation complex (PIC) has been identified. Here, we reveal that nonconsensus, statistical, DNA triplet code provides specificity for the positioning of the human PIC. In particular, we reveal a highly nonrandom, statistical pattern of repetitive nucleotide triplets that correlates with the genomewide binding preferences of PIC measured by Chip-exo. We analyze the triplet enrichment and depletion near the transcription start site and identify triplets that have the strongest effect on PIC-DNA nonconsensus binding. Using statistical mechanics, a random-binder model without fitting parameters, with genomic DNA sequence being the only input, we further validate that the nonconsensus nucleotide triplet code constitutes a key signature providing PIC binding specificity in the human genome. Our results constitute a proof-of-concept for, to our knowledge, a new design principle for protein-DNA recognition in the human genome, which can lead to a better mechanistic understanding of transcriptional regulation.

Nucleosome repositioning during differentiation of a human myeloid leukemia cell line

Cell differentiation is associated with changes in chromatin organization and gene expression. In this study, we examine chromatin structure following differentiation of the human myeloid leukemia cell line (HL-60/S4) into granulocytes with retinoic acid (RA) or into macrophage with phorbol ester (TPA). We performed ChIP-seq of histone H3 and its modifications, analyzing changes in nucleosome occupancy, nucleosome repeat length, eu-/heterochromatin redistribution and properties of epichromatin (surface chromatin adjacent to the nuclear envelope). Nucleosome positions changed genome-wide, exhibiting a specific class of alterations involving nucleosome loss in extended (∼1kb) regions, pronounced in enhancers and promoters. Genes that lost nucleosomes at their promoters showed a tendency to be upregulated. On the other hand, nucleosome gain did not show simple effects on transcript levels. The average genome-wide nucleosome repeat length (NRL) did not change significantly with differentiation. However, we detected an approximate 10 bp NRL decrease around the haematopoietic transcription factor (TF) PU.1 and the architectural protein CTCF, suggesting an effect on NRL proximal to TF binding sites. Nucleosome occupancy changed in regions associated with active promoters in differentiated cells, compared with untreated HL-60/S4 cells. Epichromatin regions revealed an increased GC content and high nucleosome density compared with surrounding chromatin. Epichromatin showed depletion of major histone modifications and revealed enrichment with PML body-associated genes. In general, chromatin changes during HL-60/S4 differentiation appeared to be more localized to regulatory regions, compared with genome-wide changes among diverse cell types studied elsewhere.

Can We Predict Gene Expression by Understanding Proximal Promoter Architecture?

We review computational predictions of expression from the promoter architecture - the set of transcription factors that can bind the proximal promoter. We focus on spatial expression patterns in animals with complex body plans and many distinct tissue types. This field is ripe for change as functional genomics datasets accumulate for both expression and protein-DNA interactions. While there has been some success in predicting the breadth of expression (i.e., the fraction of tissue types a gene is expressed in), predicting tissue specificity remains challenging. We discuss how progress can be achieved through either machine learning or complementary combinatorial data mining. The likely impact of single-cell expression data is considered. Finally, we discuss the design of artificial promoters as a practical application.

NucTools: analysis of chromatin feature occupancy profiles from high-throughput sequencing data

Background

Biomedical applications of high-throughput sequencing methods generate a vast amount of data in which numerous chromatin features are mapped along the genome. The results are frequently analysed by creating binary data sets that link the presence/absence of a given feature to specific genomic loci. However, the nucleosome occupancy or chromatin accessibility landscape is essentially continuous. It is currently a challenge in the field to cope with continuous distributions of deep sequencing chromatin readouts and to integrate the different types of discrete chromatin features to reveal linkages between them.

Results

Here we introduce the NucTools suite of Perl scripts as well as MATLAB- and R-based visualization programs for a nucleosome-centred downstream analysis of deep sequencing data. NucTools accounts for the continuous distribution of nucleosome occupancy. It allows calculations of nucleosome occupancy profiles averaged over several replicates, comparisons of nucleosome occupancy landscapes between different experimental conditions, and the estimation of the changes of integral chromatin properties such as the nucleosome repeat length. Furthermore, NucTools facilitates the annotation of nucleosome occupancy with other chromatin features like binding of transcription factors or architectural proteins, and epigenetic marks like histone modifications or DNA methylation. The applications of NucTools are demonstrated for the comparison of several datasets for nucleosome occupancy in mouse embryonic stem cells (ESCs) and mouse embryonic fibroblasts (MEFs).

Conclusions

The typical workflows of data processing and integrative analysis with NucTools reveal information on the interplay of nucleosome positioning with other features such as for example binding of a transcription factor CTCF, regions with stable and unstable nucleosomes, and domains of large organized chromatin K9me2 modifications (LOCKs). As potential limitations and problems we discuss how inter-replicate variability of MNase-seq experiments can be addressed.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3580-2) contains supplementary material, which is available to authorized users.

Nucleosome positioning: resources and tools online

Nucleosome positioning is an important process required for proper genome packing and its accessibility to execute the genetic program in a cell-specific, timely manner. In the recent years hundreds of papers have been devoted to the bioinformatics, physics and biology of nucleosome positioning. The purpose of this review is to cover a practical aspect of this field, namely, to provide a guide to the multitude of nucleosome positioning resources available online. These include almost 300 experimental datasets of genome-wide nucleosome occupancy profiles determined in different cell types and more than 40 computational tools for the analysis of experimental nucleosome positioning data and prediction of intrinsic nucleosome formation probabilities from the DNA sequence. A manually curated, up to date list of these resources will be maintained at http://generegulation.info.

Affinity, stoichiometry and cooperativity of heterochromatin protein 1 (HP1) binding to nucleosomal arrays

Heterochromatin protein 1 (HP1) participates in establishing and maintaining heterochromatin via its histone-modification-dependent chromatin interactions. In recent papers HP1 binding to nucleosomal arrays was measured in vitro and interpreted in terms of nearest-neighbour cooperative binding. This mode of chromatin interaction could lead to the spreading of HP1 along the nucleosome chain. Here, we reanalysed previous data by representing the nucleosome chain as a 1D binding lattice and showed how the experimental HP1 binding isotherms can be explained by a simpler model without cooperative interactions between neighboring HP1 dimers. Based on these calculations and spatial models of dinucleosomes and nucleosome chains, we propose that binding stoichiometry depends on the nucleosome repeat length (NRL) rather than protein interactions between HP1 dimers. According to our calculations, more open nucleosome arrays with long DNA linkers are characterized by a larger number of binding sites in comparison to chains with a short NRL. Furthermore, we demonstrate by Monte Carlo simulations that the NRL dependent folding of the nucleosome chain can induce allosteric changes of HP1 binding sites. Thus, HP1 chromatin interactions can be modulated by the change of binding stoichiometry and the type of binding to condensed (methylated) and non-condensed (unmethylated) nucleosome arrays in the absence of direct interactions between HP1 dimers.

Time resolved DNA occupancy dynamics during the respiratory oscillation uncover a global reset point in the yeast growth program

The structural dynamics of chromatin have been implicated in the regulation of fundamental eukaryotic processes, such as DNA transcription, replication and repair. Although previous studies have revealed that the chromatin landscape, nucleosome remodeling and histone modification events are intimately tied into cellular energetics and redox state, few studies undertake defined time-resolved measurements of these state variables. Here, we use metabolically synchronous, continuously-grown yeast cultures to measure DNA occupancy and track global patterns with respect to the metabolic state of the culture. Combined with transcriptome analyses and ChIP-qPCR experiments, these paint an intriguing picture where genome-wide nucleosome focusing occurs during the recovery of energy charge, followed by clearance of the promoter regions and global transcriptional slow-down, thus indicating a nucleosome-mediated “reset point” for the cycle. The reset begins at the end of the catabolic and stress-response transcriptional programs and ends prior to the start of the anabolic and cell-growth transcriptional program, and the histones on genes from both the catabolic and anabolic superclusters are deacetylated.

Electrostatic effect of H1-histone protein binding on nucleosome repeat length

Within a simple biophysical model we describe the effect of electrostatic binding of H1 histone proteins on the nucleosome repeat length in chromatin. The length of wrapped DNA optimizes its binding energy to the histone core and the elastic energy penalty of DNA wrapping. The magnitude of the effect predicted from our model is in agreement with the systematic experimental data on the linear variation of nucleosome repeat lengths with H1/nucleosome ratio (Woodcock C L et al 2006 Chromos. Res. 14 17-25). We compare our model to the data for different cell types and organisms, with a widely varying ratio of bound H1 histones per nucleosome. We underline the importance of this non-specific histone-DNA charge-balance mechanism in regulating the positioning of nucleosomes and the degree of compaction of chromatin fibers in eukaryotic cells.

Regulation of the nucleosome repeat length in vivo by the DNA sequence, protein concentrations and long-range interactions

The nucleosome repeat length (NRL) is an integral chromatin property important for its biological functions. Recent experiments revealed several conflicting trends of the NRL dependence on the concentrations of histones and other architectural chromatin proteins, both in vitro and in vivo, but a systematic theoretical description of NRL as a function of DNA sequence and epigenetic determinants is currently lacking. To address this problem, we have performed an integrative biophysical and bioinformatics analysis in species ranging from yeast to frog to mouse where NRL was studied as a function of various parameters. We show that in simple eukaryotes such as yeast, a lower limit for the NRL value exists, determined by internucleosome interactions and remodeler action. For higher eukaryotes, also the upper limit exists since NRL is an increasing but saturating function of the linker histone concentration. Counterintuitively, smaller H1 variants or non-histone architectural proteins can initiate larger effects on the NRL due to entropic reasons. Furthermore, we demonstrate that different regimes of the NRL dependence on histone concentrations exist depending on whether DNA sequence-specific effects dominate over boundary effects or vice versa. We consider several classes of genomic regions with apparently different regimes of the NRL variation. As one extreme, our analysis reveals that the period of oscillations of the nucleosome density around bound RNA polymerase coincides with the period of oscillations of positioning sites of the corresponding DNA sequence. At another extreme, we show that although mouse major satellite repeats intrinsically encode well-defined nucleosome preferences, they have no unique nucleosome arrangement and can undergo a switch between two distinct types of nucleosome positioning.

Nucleosome repositioning links DNA (de)methylation and differential CTCF binding during stem cell development

During differentiation of embryonic stem cells, chromatin reorganizes to establish cell type-specific expression programs. Here, we have dissected the linkages between DNA methylation (5mC), hydroxymethylation (5hmC), nucleosome repositioning, and binding of the transcription factor CTCF during this process. By integrating MNase-seq and ChIP-seq experiments in mouse embryonic stem cells (ESC) and their differentiated counterparts with biophysical modeling, we found that the interplay between these factors depends on their genomic context. The mostly unmethylated CpG islands have reduced nucleosome occupancy and are enriched in cell type-independent binding sites for CTCF. The few remaining methylated CpG dinucleotides are preferentially associated with nucleosomes. In contrast, outside of CpG islands most CpGs are methylated, and the average methylation density oscillates so that it is highest in the linker region between nucleosomes. Outside CpG islands, binding of TET1, an enzyme that converts 5mC to 5hmC, is associated with labile, MNase-sensitive nucleosomes. Such nucleosomes are poised for eviction in ESCs and become stably bound in differentiated cells where the TET1 and 5hmC levels go down. This process regulates a class of CTCF binding sites outside CpG islands that are occupied by CTCF in ESCs but lose the protein during differentiation. We rationalize this cell type-dependent targeting of CTCF with a quantitative biophysical model of competitive binding with the histone octamer, depending on the TET1, 5hmC, and 5mC state.