title: Confident gene activity prediction based on single histone modification H2BK5ac in human cell lines.
abstract: BACKGROUND
  The histones in the core of nucleosomes may be subject to covalent post-transcriptional modifications. These modifications are thought to correlate with and possibly affect various genomic functions, including transcription. Each modification may alone or in combination with other modifications influence or be influenced by transcription. We aimed to identify correlations between single modifications or combinations of modifications at specific nucleosome sized gene regions with transcription activity based on global histone modification and transcription data of human CD4+ T cells and three other human cell lines. Transcription activity was defined in a binary fashion as either on or off. The analysis was done using the Classification and Regression Tree (CART) data mining protocol, and the Multifactorial Dimensionality Reduction (MDR) method was performed to confirm the CART results. These powerful methods have not previously been used for analysis of histone modification data.
  
  
  RESULTS
  We showed that analysis of the single histone modification H2BK5ac at only four gene regions correctly predicted transcription activity status of over 75% of genes in CD4+ T-cells. The H2BK5ac modification status also had high power for prediction of gene transcription activity in the three other cell lines studied. The informative gene regions with the H2BK5ac modification were all positioned proximal to transcription initiation sites. The CART and MDR methods were appropriate tools for the analysis performed. In the study, we also developed a non-arbitrary protocol for binary classification of genes as transcriptionally active or inactive.
  
  
  CONCLUSIONS
  The importance of H2BK5ac modification with regards to transcription control has not previously been emphasized. Analysis of this single modification at only four nucleosome sized gene regions, all of which are at or proximal to transcription initiation, has high power for prediction of gene transcription activity.
authors.affiliation: Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
authors.forename: Fereshteh
authors.initials: F
authors.lastname: Chitsazian
authors.affiliation: National Institute for Genetic Engineering and Biotechnology, Tehran, Iran.
authors.forename: Mehdi
authors.initials: M
authors.lastname: Sadeghi
authors.affiliation: School of Biology, College of Science, University of Tehran, Tehran, Iran. elaheelahi@ut.ac.ir.|Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran. elaheelahi@ut.ac.ir.
authors.forename: Elahe
authors.initials: E
authors.lastname: Elahi
mesh_terms: D000465:Algorithms; D015496:CD4-Positive T-Lymphocytes / Q000166:cytology / Q000378:metabolism; D002460:Cell Line; D005786:Gene Expression Regulation; D042421:Histone Code; D006657:Histones / Q000378:metabolism*; D006801:Humans; D012984:Software; D060388:Support Vector Machine; D013728:Terminator Regions, Genetic; D024363:Transcription Initiation Site
chemical_list: D006657:Histones
keywords: CART; H2BK5ac; Histone modifications; MDR; Transcription