Cargando…

Characterizing nucleosome dynamics from genomic and epigenetic information using rule induction learning

BACKGROUND: Eukaryotic genomes are packaged into chromatin, a compact structure containing fundamental repeating units, the nucleosomes. The mobility of nucleosomes plays important roles in many DNA-related processes by regulating the accessibility of regulatory elements to biological machineries. A...

Descripción completa

Detalles Bibliográficos
Autores principales: Le, Ngoc Tu, Ho, Tu Bao, Tran, Dang Hung
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2788380/
https://www.ncbi.nlm.nih.gov/pubmed/19958491
http://dx.doi.org/10.1186/1471-2164-10-S3-S27
_version_ 1782174968406081536
author Le, Ngoc Tu
Ho, Tu Bao
Tran, Dang Hung
author_facet Le, Ngoc Tu
Ho, Tu Bao
Tran, Dang Hung
author_sort Le, Ngoc Tu
collection PubMed
description BACKGROUND: Eukaryotic genomes are packaged into chromatin, a compact structure containing fundamental repeating units, the nucleosomes. The mobility of nucleosomes plays important roles in many DNA-related processes by regulating the accessibility of regulatory elements to biological machineries. Although it has been known that various factors, such as DNA sequences, histone modifications, and chromatin remodelling complexes, could affect nucleosome stability, the mechanisms of how they regulate this stability are still unclear. RESULTS: In this paper, we propose a novel computational method based on rule induction learning to characterize nucleosome dynamics using both genomic and histone modification information. When applied on S. cerevisiae data, our method produced totally 98 rules characterizing nucleosome dynamics on chromosome III and promoter regions. Analyzing these rules we discovered that, some DNA motifs and post-translational modifications of histone proteins play significant roles in regulating nucleosome stability. Notably, these DNA motifs are strong determinants for nucleosome forming and inhibiting potential; and these histone modifications have strong relation with transcriptional activities, i.e. activation and repression. We also found some new patterns which may reflect the cooperation between these two factors in regulating the stability of nucleosomes. CONCLUSION: DNA motifs and histone modifications can individually and, in some cases, cooperatively regulate nucleosome stability. This suggests additional insights into mechanisms by which cells control important biological processes, such as transcription, replication, and DNA repair.
format Text
id pubmed-2788380
institution National Center for Biotechnology Information
language English
publishDate 2009
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-27883802009-12-04 Characterizing nucleosome dynamics from genomic and epigenetic information using rule induction learning Le, Ngoc Tu Ho, Tu Bao Tran, Dang Hung BMC Genomics Proceedings BACKGROUND: Eukaryotic genomes are packaged into chromatin, a compact structure containing fundamental repeating units, the nucleosomes. The mobility of nucleosomes plays important roles in many DNA-related processes by regulating the accessibility of regulatory elements to biological machineries. Although it has been known that various factors, such as DNA sequences, histone modifications, and chromatin remodelling complexes, could affect nucleosome stability, the mechanisms of how they regulate this stability are still unclear. RESULTS: In this paper, we propose a novel computational method based on rule induction learning to characterize nucleosome dynamics using both genomic and histone modification information. When applied on S. cerevisiae data, our method produced totally 98 rules characterizing nucleosome dynamics on chromosome III and promoter regions. Analyzing these rules we discovered that, some DNA motifs and post-translational modifications of histone proteins play significant roles in regulating nucleosome stability. Notably, these DNA motifs are strong determinants for nucleosome forming and inhibiting potential; and these histone modifications have strong relation with transcriptional activities, i.e. activation and repression. We also found some new patterns which may reflect the cooperation between these two factors in regulating the stability of nucleosomes. CONCLUSION: DNA motifs and histone modifications can individually and, in some cases, cooperatively regulate nucleosome stability. This suggests additional insights into mechanisms by which cells control important biological processes, such as transcription, replication, and DNA repair. BioMed Central 2009-12-03 /pmc/articles/PMC2788380/ /pubmed/19958491 http://dx.doi.org/10.1186/1471-2164-10-S3-S27 Text en Copyright ©2009 Le et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Le, Ngoc Tu
Ho, Tu Bao
Tran, Dang Hung
Characterizing nucleosome dynamics from genomic and epigenetic information using rule induction learning
title Characterizing nucleosome dynamics from genomic and epigenetic information using rule induction learning
title_full Characterizing nucleosome dynamics from genomic and epigenetic information using rule induction learning
title_fullStr Characterizing nucleosome dynamics from genomic and epigenetic information using rule induction learning
title_full_unstemmed Characterizing nucleosome dynamics from genomic and epigenetic information using rule induction learning
title_short Characterizing nucleosome dynamics from genomic and epigenetic information using rule induction learning
title_sort characterizing nucleosome dynamics from genomic and epigenetic information using rule induction learning
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2788380/
https://www.ncbi.nlm.nih.gov/pubmed/19958491
http://dx.doi.org/10.1186/1471-2164-10-S3-S27
work_keys_str_mv AT lengoctu characterizingnucleosomedynamicsfromgenomicandepigeneticinformationusingruleinductionlearning
AT hotubao characterizingnucleosomedynamicsfromgenomicandepigeneticinformationusingruleinductionlearning
AT trandanghung characterizingnucleosomedynamicsfromgenomicandepigeneticinformationusingruleinductionlearning