In vitro versus in vivo compositional landscapes of histone sequence preferences in eucaryotic genomes

Risultato della ricerca: Articlepeer review

4 Citazioni (Scopus)

Abstract

Motivation: Although the nucleosome occupancy along a genome can be in part predicted by in vitro experiments, it has been recently observed that the chromatin organization presents important differences in vitro with respect to in vivo. Such differences mainly regard the hierarchical and regular structures of the nucleosome fiber, whose existence has long been assumed, and in part also observed in vitro, but that does not apparently occur in vivo. It is also well known that the DNA sequence has a role in determining the nucleosome occupancy. Therefore, an important issue is to understand if, and to what extent, the structural differences in the chromatin organization between in vitro and in vivo have a counterpart in terms of the underlying genomic sequences.Results: We present the first quantitative comparison between the in vitro and in vivo nucleosome maps of two model organisms (S. cerevisiae and C. elegans). The comparison is based on the construction of weighted k-mer dictionaries. Our findings show that there is a good level of sequence conservation between in vitro and in vivo in both the two organisms, in contrast to the abovementioned important differences in chromatin structural organization. Moreover, our results provide evidence that the two organisms predispose themselves differently, in terms of sequence composition and both in vitro and in vivo, for the nucleosome occupancy. This leads to the conclusion that, although the notion of a genome encoding for its own nucleosome occupancy is general, the intrinsic histone k-mer sequence preferences tend to be species-specific.Availability and implementation: The files containing the dictionaries and the main results of the analysis are available at http://math.unipa.it/rombo/material.Supplementary information: Supplementary data are available at Bioinformatics online.
Lingua originaleEnglish
pagine (da-a)3454-3460
Numero di pagine7
RivistaBioinformatics
Volume34
Stato di pubblicazionePublished - 2018

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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