Calculation of nucleosomal DNA deformation energy: its implication for nucleosome positioning

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.

LeNup: learning nucleosome positioning from DNA sequences with improved convolutional neural networks

Motivation

Nucleosome positioning plays significant roles in proper genome packing and its accessibility to execute transcription regulation. Despite a multitude of nucleosome positioning resources available on line including experimental datasets of genome-wide nucleosome occupancy profiles and computational tools to the analysis on these data, the complex language of eukaryotic Nucleosome positioning remains incompletely understood.

Results

Here, we address this challenge using an approach based on a state-of-the-art machine learning method. We present a novel convolutional neural network (CNN) to understand nucleosome positioning. We combined Inception-like networks with a gating mechanism for the response of multiple patterns and long term association in DNA sequences. We developed the open-source package LeNup based on the CNN to predict nucleosome positioning in Homo sapiens, Caenorhabditis elegans, Drosophila melanogaster as well as Saccharomyces cerevisiae genomes. We trained LeNup on four benchmark datasets. LeNup achieved greater predictive accuracy than previously published methods.

Availability and implementation

LeNup is freely available as Python and Lua script source code under a BSD style license from https://github.com/biomedBit/LeNup.

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

Physical properties of DNA may direct the binding of nucleoid-associated proteins along the E. coli genome

Nucleoid-associated proteins (NAPs) play important roles in both chromosome packaging and gene regulation in bacteria. The underlying mechanisms, however, remain elusive particularly for how NAPs contribute to chromosome packaging. We report here a characterization of the binding sites for several major NAPs in E. coli, namely HNS, IHF, Fis, Dps and a non-NAP protein, FNR, in terms of the physical properties of their binding DNA. Our study shows that (i) as compared with flanking regions, the binding sites for IHF, Fis and FNR tend to have high intrinsic curvature, while no characterized pattern of intrinsic curvature distribution around those of HNS and Dps; (ii) all the binding sites analyzed in this study except those of HNS are characterized by high structural flexibility; (iii) the intrinsic curvature and flexibility at the binding sites for Fis and IHF are found to be coupled with the sequence specificity required in their binding, while the physical properties of the binding regions for both Dps and FNR are independent of sequence specificity. Our data suggest that physical properties of DNA sequence may contribute to binding of NAPs and mediate genome packaging and transcriptional regulation of the downstream genes. Our results should be informative for prediction of NAPs binding sites and understanding of the bacterial chromosome packaging.

Evolutionary direction of processed pseudogenes

While some pseudogenes have been reported to play important roles in gene regulation, little is known about the possible relationship between pseudogene functions and evolutionary process of pseudogenes, or about the forces responsible for the pseudogene evolution. In this study, we characterized human processed pseudogenes in terms of evolutionary dynamics. Our results show that pseudogenes tend to evolve toward: lower GC content, strong dinucleotide bias, reduced abundance of transcription factor binding motifs and short palindromes, and decreased ability to form nucleosomes. We explored possible evolutionary forces that shaped the evolution pattern of pseudogenes, and concluded that mutations in pseudogenes are likely determined, at least partially, by neighbor-dependent mutational bias and recombination-associated selection.

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

Nucleosome plays an essential role in various cellular processes, such as DNA replication, recombination, and transcription. Hence, it is important to decode the mechanism of nucleosome positioning and identify nucleosome positions in the genome. In this paper, we present a model for predicting nucleosome positioning based on DNA deformation, in which both bending and shearing of the nucleosomal DNA are considered. The model successfully predicted the dyad positions of nucleosomes assembled in vitro and the in vitro map of nucleosomes in Saccharomyces cerevisiae. Applying the model to Caenorhabditis elegans and Drosophila melanogaster, we achieved satisfactory results. Our data also show that shearing energy of nucleosomal DNA outperforms bending energy in nucleosome occupancy prediction and the ability to predict nucleosome dyad positions is attributed to bending energy that is associated with rotational positioning of nucleosomes.

Nucleosome Organization around Pseudogenes in the Human Genome

Pseudogene, disabled copy of functional gene, plays a subtle role in gene expression and genome evolution. The first step in deciphering RNA-level regulation of pseudogenes is to understand their transcriptional activity. So far, there has been no report on possible roles of nucleosome organization in pseudogene transcription. In this paper, we investigated the effect of nucleosome positioning on pseudogene transcription. For transcribed pseudogenes, the experimental nucleosome occupancy shows a prominent depletion at the regions both upstream of pseudogene start positions and downstream of pseudogene end positions. Intriguingly, the same depletion is also observed for nontranscribed pseudogenes, which is unexpected since nucleosome depletion in those regions is thought to be unnecessary in light of the nontranscriptional property of those pseudogenes. The sequence-dependent prediction of nucleosome occupancy shows a consistent pattern with the experimental data-based analysis. Our results indicate that nucleosome positioning may play important roles in both the transcription initiation and termination of pseudogenes.