DNA physical properties determine nucleosome occupancy from yeast to fly.

Laboratoire Statistique et Génome, CNRS/INRA/UEVE, 523 place des Terrasses, 91000 Evry, France.
Nucleic Acids Research (Impact Factor: 8.28). 06/2008; 36(11):3746-56. DOI: 10.1093/nar/gkn262
Source: PubMed

ABSTRACT Nucleosome positioning plays an essential role in cellular processes by modulating accessibility of DNA to proteins. Here, using only sequence-dependent DNA flexibility and intrinsic curvature, we predict the nucleosome occupancy along the genomes of Saccharomyces cerevisiae and Drosophila melanogaster and demonstrate the predictive power and universality of our model through its correlation with experimentally determined nucleosome occupancy data. In yeast promoter regions, the computed average nucleosome occupancy closely superimposes with experimental data, exhibiting a <200 bp region unfavourable for nucleosome formation bordered by regions that facilitate nucleosome formation. In the fly, our model faithfully predicts promoter strength as encoded in distinct chromatin architectures characteristic of strongly and weakly expressed genes. We also predict that nucleosomes are repositioned by active mechanisms at the majority of fly promoters. Our model uses only basic physical properties to describe the wrapping of DNA around the histone core, yet it captures a substantial part of chromatin's structural complexity, thus leading to a much better prediction of nucleosome occupancy than methods based merely on periodic curved DNA motifs. Our results indicate that the physical properties of the DNA chain, and not just the regulatory factors and chromatin-modifying enzymes, play key roles in eukaryotic transcription.

  • [Show abstract] [Hide abstract]
    ABSTRACT: Identifying regulatory elements and revealing their role in gene expression regulation remains a central goal of plant genome research. We exploited the detailed genomic sequencing information of a large number of Arabidopsis thaliana accessions to characterize known and to identify novel cis-regulatory elements in gene promoter regions of Arabidopsis by relying on conservation as the hallmark signal of functional relevance. Based on the genomic layout and the obtained density profiles of single nucleotide polymorphisms (SNPs) in sequence regions upstream of transcription start sites, the average length of promoter regions in Arabidopsis could be established at 500 bp. Genes associated with high degree of variability of their respective upstream regions are preferentially involved in environmental response and signaling processes, while low levels of promoter SNP-density are common among housekeeping genes. Known cis-elements were found to exhibit a decreased SNP-density than sequence regions not associated with known motifs. For 15 known cis-element motifs, strong positional preferences relative to the transcription start site were detected based on their promoter SNP density profiles. Five novel candidate cis-element motifs were identified as consensus motifs of 17 sequence hexamers exhibiting increased sequence conservation combined with evidence of positional preferences, annotation information, and functional relevance for inducing correlated gene expression. Our study demonstrates that the currently available resolution of SNP data offers novel ways for the identification of functional genomic elements and the characterization of gene promoter sequences.
    Plant physiology 11/2013; · 6.56 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Nucleosome organization plays a key role in the regulation of gene expression. However, despite the striking advances in the accuracy of nucleosome maps, there are still severe discrepancies on individual nucleosome positioning and how this influences gene regulation. The variability among nucleosome maps, which precludes the fine analysis of nucleosome positioning, might emerge from diverse sources. We have carefully inspected the extrinsic factors that may induce diversity by the comparison of microccocal nuclease (MNase)-Seq derived nucleosome maps generated under distinct conditions. Furthermore, we have also explored the variation originated from intrinsic nucleosome dynamics by generating additional maps derived from cell cycle synchronized and asynchronous yeast cultures. Taken together, our study has enabled us to measure the effect of noise in nucleosome occupancy and positioning and provides insights into the underlying determinants. Furthermore, we present a systematic approach that may guide the standardization of MNase-Seq experiments in order to generate reproducible genome-wide nucleosome patterns.
    Nucleic Acids Research 02/2014; · 8.28 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Nucleosome positioning participates in many cellular activities and plays significant roles in regulating cellular processes. With the avalanche of genome sequences generated in the postgenomic age, it is highly desired to develop automated methods for rapidly and effectively identifying nucleosome positioning. Although some computational methods were proposed, most of them were species specific and neglected the intrinsic local structural properties that might play important roles in determining the nucleosome positioning on a DNA sequence. Here a predictor called " INUC-PSEKNC " was developed for predicting nucleosome positioning in Homo sapiens, Caenorhabditis elegans, and Drosophila melanogaster genomes, respectively. In the new predictor, the samples of DNA sequences were formulated by a novel feature-vector called "pseudo k-tuple nucleotide composition", into which six DNA local structural properties were incorporated. It was observed by the rigorous cross-validation tests on the three stringent benchmark datasets that the overall success rates achieved by INUC-PSEKNC in predicting the nucleosome positioning of the aforementioned three genomes were 86.27%, 86.90% and 79.97%, respectively. Meanwhile, the results obtained by INUC-PSEKNC on various benchmark datasets used by the previous investigators for different genomes also indicated that the current predictor remarkably outperformed its counterparts. A user-friendly web-server, INUC-PSEKNC is freely accessible at, (H.L.);, (W.C.); (KCC).
    Bioinformatics 02/2014; · 5.47 Impact Factor

Full-text (2 Sources)

Available from
May 22, 2014