A deformation energy-based model for predicting nucleosome dyads and occupancy

DNA Sequence-Dependent Properties of Nucleosome Positioning in Regions of Distinct Chromatin States in Mouse Embryonic Stem Cells

Chromatin architecture is orchestrated, and plays crucial roles during the developmental process by regulating gene expression. In embryonic stem cells (ESCs), three types of chromatin states, including active, repressive and poised states, were previously identified and characterized with specific chromatin modification marks and different transcription activity, but it is largely unknown how nucleosomes are organized in these chromatin states. In this study, by using a DNA deformation energy model, we investigated the sequence-dependent nucleosome organization within the chromatin states in mouse ESCs. The results revealed that: (1) compared with poised genes, active genes are characterized with a higher level of nucleosome occupancy around their transcription start sites (TSS) and transcription termination sites (TTS), and both types of genes do not have a nucleosome-depleted region at their TTS, contrasting with the MNase-seq based result; (2) based on our previous DNA bending energy model, we developed an improved model capable of predicting both rotational positioning and nucleosome occupancy determined by a chemical mapping approach; (3) DNA bending-energy-based analyses demonstrated that the fragile nucleosomes positioned at both gene ends could be explained largely by enhanced rotational positioning signals encoded in DNA, but nucleosome phasing around the TSS of active genes was not determined by sequence preference; (4) the nucleosome occupancy landscape around the binding sites of some developmentally important transcription factors known to bind with different chromatin contexts, was also successfully predicted; (5) the difference of nucleosome occupancy around the TSS between CpG-rich and CpG-poor promoters was partly captured by our sequence-dependent model. Taken together, by developing an improved deformation-energy-based model, we revealed some sequence-dependent properties of the nucleosome arrangements in regions of distinct chromatin states in mouse ESCs.

Chromatin accessibility shapes meiotic recombination in mouse primordial germ cells through assisting double-strand breaks and loop formation

Meiotic recombination is a driver of evolution, and aberrant recombination is a major contributor to aneuploidy in mammals. Mechanism of recombination remains elusive yet. Here, we present a computational analysis to explore recombination-related dynamics of chromatin accessibility in mouse primordial germ cells (PGCs). Our data reveals that: (1) recombination hotspots which get accessible at meiosis-specific DNase I-hypersensitive sites (DHSs) only when PGCs enter meiosis are located preferentially in intronic and distal intergenic regions; (2) stable DHSs maintained stably across PGC differentiation are enriched by CTCF motifs and CTCF binding and mediate chromatin loop formation; (3) compared with the specific DHSs aroused at meiotic stage, stable DHSs are largely encoded in DNA sequence and also enriched by epigenetic marks; (4) PRDM9 is likely to target nucleosome-occupied hotspot regions and remodels local chromatin structure to make them accessible for recombination machinery; and (5) cells undergoing meiotic recombination are deficient in TAD structure and chromatin loop arrays are organized regularly along the axis formed between homologous chromosomes. Taken together, by analyzing DHS-related DNA features, epigenetic marks and 3D genome structure, we revealed some specific roles of chromatin accessibility in recombination, which would expand our understanding of recombination mechanism.

Epigenetic Marks and Variation of Sequence-Based Information Along Genomic Regions Are Predictive of Recombination Hot/Cold Spots in Saccharomyces cerevisiae

Characterization and identification of recombination hotspots provide important insights into the mechanism of recombination and genome evolution. In contrast with existing sequence-based models for predicting recombination hotspots which were defined in a ORF-based manner, here, we first defined recombination hot/cold spots based on public high-resolution Spo11-oligo-seq data, then characterized them in terms of DNA sequence and epigenetic marks, and finally presented classifiers to identify hotspots. We found that, in addition to some previously discovered DNA-based features like GC-skew, recombination hotspots in yeast can also be characterized by some remarkable features associated with DNA physical properties and shape. More importantly, by using DNA-based features and several epigenetic marks, we built several classifiers to discriminate hotspots from coldspots, and found that SVM classifier performs the best with an accuracy of ∼92%, which is also the highest among the models in comparison. Feature importance analysis combined with prediction results show that epigenetic marks and variation of sequence-based features along the hotspots contribute dominantly to hotspot identification. By using incremental feature selection method, an optimal feature subset that consists of much less features was obtained without sacrificing prediction accuracy.

A deformation energy model reveals sequence-dependent property of nucleosome positioning

We present a deformation energy model for predicting nucleosome positioning, in which a position-dependent structural parameter set derived from crystal structures of nucleosomes was used to calculate the DNA deformation energy. The model is successful in predicting nucleosome occupancy genome-wide in budding yeast, nucleosome free energy, and rotational positioning of nucleosomes. Our model also indicates that the genomic regions underlying the MNase-sensitive nucleosomes in budding yeast have high deformation energy and, consequently, low nucleosome-forming ability, while the MNase-sensitive non-histone particles are characterized by much lower DNA deformation energy and high nucleosome preference. In addition, we also revealed that remodelers, SNF2 and RSC8, are likely to act in chromatin remodeling by binding to broad nucleosome-depleted regions that are intrinsically favorable for nucleosome positioning. Our data support the important role of position-dependent physical properties of DNA in nucleosome positioning.

Deform-nu: A DNA Deformation Energy-Based Predictor for Nucleosome Positioning

The structure and function of chromatin can be regulated through positioning patterns of nucleosomes. DNA-based processes are regulated via nucleosomes. Therefore, it is significant to determine nucleosome positions in DNA-based processes. A deformation energy model was proposed to predict nucleosome positions in our previous study. A free web server based on the model (http://lin-group.cn/server/deform-nu/) was firstly established to estimate the occupancy and rotational positioning of nucleosomes in the study. Then, the performance of the model was verified by several examples. The results indicated that nucleosome positioning relied on the physical properties of DNA, such as deformation energy.

The affinity of DNA sequences containing R5Y5 motif and TA repeats with 10.5-bp periodicity to histone octamer in vitro

Nucleosome positioning along the genome is partially determined by the intrinsic DNA sequence preferences on histone. RRRRRYYYYY (R5Y5, R = Purine and Y = Pyrimidine) motif in nucleosome DNA, which was presented based on several theoretical models by Trifonov et al., might be a facilitating sequence pattern for nucleosome assembly. However, there is not a high conformity experimental evidence to support the concept that R5Y5 motif is a key element for the determination of nucleosome positioning. In this work, the ability of the canonical, H2A.Z- and H3.3-containing octamers to assemble nucleosome on DNA templates containing R5Y5 motif and TA repeats within 10.5-bp periodicity was investigated by using salt-dialysis method in vitro. The results showed that the10.5-bp periodical distributions of both R5Y5 motif and TA repeats along DNA templates can significantly promote canonical nucleosome assembly and may be key sequence factors for canonical nucleosome assembly. Compared with TA repeats within 10.5-bp periodicity, R5Y5 motif in DNA templates did not elevate H2A.Z- and H3.3-containing nucleosome formation efficiency in vitro. This result indicates that R5Y5 motif probably isn't a pivotal factor to regulate nucleosome assembly on histone variants. It is speculated that the regulatory mechanism of nucleosome assembly is different between canonical and variant histone. These conclusions can provide a deeper insight on the mechanism of nucleosome positioning. Communicated by Ramaswamy H. Sarma.

DNA physical properties outperform sequence compositional information in classifying nucleosome-enriched and -depleted regions

The nucleosome is the fundamental structural unit of eukaryotic chromatin and plays an essential role in the epigenetic regulation of cellular processes, such as DNA replication, recombination, and transcription. Hence, it is important to identify nucleosome positions in the genome. Our previous model based on DNA deformation energy, in which a set of DNA physical descriptors was used, performed well in predicting nucleosome dyad positions and occupancy. In this study, we established a machine-learning model for predicting nucleosome occupancy in order to further verify the physical descriptors. Results showed that (1) our model outperformed several other sequence compositional information-based models, indicating a stronger dependence of nucleosome positioning on DNA physical properties; (2) nucleosome-enriched and -depleted regions have distinct features in terms of DNA physical descriptors like sequence-dependent flexibility and equilibrium structure parameters; (3) gene transcription start sites and termination sites can be well characterized with the distribution patterns of the physical descriptors, indicating the regulatory role of DNA physical properties in gene transcription. In addition, we developed a web server for the model, which is freely accessible at http://lin-group.cn/server/iNuc-force/.

The implication of DNA bending energy for nucleosome positioning and sliding

Nucleosome not only directly affects cellular processes, such as DNA replication, recombination, and transcription, but also severs as a fundamentally important target of epigenetic modifications. Our previous study indicated that the bending property of DNA is important in nucleosome formation, particularly in predicting the dyad positions of nucleosomes on a DNA segment. Here, we investigated the role of bending energy in nucleosome positioning and sliding in depth to decipher sequence-directed mechanism. The results show that bending energy is a good physical index to predict the free energy in the process of nucleosome reconstitution in vitro. Our data also imply that there are at least 20% of the nucleosomes in budding yeast do not adopt canonical positioning, in which underlying sequences wrapped around histones are structurally symmetric. We also revealed distinct patterns of bending energy profile for distinctly organized chromatin structures, such as well-positioned nucleosomes, fuzzy nucleosomes, and linker regions and discussed nucleosome sliding in terms of bending energy. We proposed that the stability of a nucleosome is positively correlated with the strength of the bending anisotropy of DNA segment, and both accessibility and directionality of nucleosome sliding is likely to be modulated by diverse patterns of DNA bending energy profile.

Evolutionary analysis of nucleosome positioning sequences based on New Symmetric Relative Entropy

New Symmetric Relative Entropy (NSRE) was applied innovatively to analyze the nucleosome sequences in S. cerevisiae, S. pombe and Drosophila. NSRE distributions could well reflect the characteristic differences of nucleosome sequences among three organisms, and the differences indicate a concerted evolution in the sequence usage of nucleosome. Further analysis about the nucleosomes around TSS shows that the constitutive property of +1/-1 nucleosomes in S. cerevisiae is different from that in S. pombe and Drosophila, which indicates that S. cerevisiae has a different transcription regulation mechanism based on nucleosome. However, in either case, the nucleosome dyad region is conserved and always has a higher NSRE. Base composition analysis shows that this conservative property in nucleosome dyad region is mainly determined by base A and T, and the dependence degrees on base A and T are consistent in three organisms.

CAME: identification of chromatin accessibility from nucleosome occupancy and methylome sequencing

Motivation

Chromatin accessibility plays a key role in epigenetic regulation of gene activation and silencing. Open chromatin regions allow regulatory elements such as transcription factors and polymerases to bind for gene expression while closed chromatin regions prevent the activity of transcriptional machinery. Recently, Methyltransferase Accessibility Protocol for individual templates-Bisulfite Genome Sequencing (MAPit-BGS) and nucleosome occupancy and methylome sequencing (NOMe-seq) have been developed for simultaneously profiling chromatin accessibility and DNA methylation on single molecules. Therefore, there is a great demand in developing computational methods to identify chromatin accessibility from MAPit-BGS and NOMe-seq.

Results

In this article, we present CAME (Chromatin Accessibility and Methylation), a seed-extension based approach that identifies chromatin accessibility from NOMe-seq. The efficiency and effectiveness of CAME were demonstrated through comparisons with other existing techniques on both simulated and real data, and the results show that our method not only can precisely identify chromatin accessibility but also outperforms other methods.

Availability and Implementation

CAME is implemented in java and the program is freely available online at http://sourceforge.net/projects/came/.

Contacts

jechoi@gru.edu or khryu@dblab.chungbuk.ac.kr.

Supplementary information

Supplementary data are available at Bioinformatics online.