Open Access Research article

Responsiveness of genes to manipulation of transcription factors in ES cells is associated with histone modifications and tissue specificity

Alexei A Sharov1, Akira Nishiyama2, Yulan Piao1, Lina S Correa-Cerro1, Tomokazu Amano1, Marshall Thomas1, Samir Mehta1 and Minoru SH Ko1*

Author Affiliations

1 Developmental Genomics and Aging Section, Laboratory of Genetics, National Institute on Aging, NIH, Baltimore, MD 21224, USA

2 Department of Immunology, Graduate School of Medicine and Faculty of Medicine, Yokohama City University, Yokohama, Kanagawa 236-0004, Japan

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BMC Genomics 2011, 12:102  doi:10.1186/1471-2164-12-102

Published: 9 February 2011

Additional files

Additional file 1:

Data sets used in the study.

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Additional file 2:

TF-responsiveness estimated from expression change in ES cells after induction of 50 transcription factors and 3 other genes [9].

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Additional file 3:

Data on chromatin status [7], binding of transcription factors [9,16,17], and presence of binding motifs in promoters of genes in mouse ES cells.

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Additional file 4:

TF-responsiveness estimated from the "NIA Other Perturbations" data set.

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Additional file 5:

Comparison of TF-responsiveness estimated from two databases: "NIA ES Bank, 53 genes", and "NIA Other Perturbations".

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Additional file 6:

Frequency distribution of mRNA decay rates (1/hr) [14]in groups of responsive and non-responsive genes.

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Additional file 7:

Gene Ontology (GO) categories over-represented in groups of responsive and non-responsive genes.

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Additional file 8:

Association between TF-responsiveness in ES cells and tissue specificity in the GNF database.

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Additional file 9:

Association between TF-responsiveness in ES cells and tissue specificity in the NIA database.

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Additional file 10:

Correlation of TF-responsiveness (Bi) estimated using three subsets of TFs: stem cell-specific, tissue-specific, and widely expressed. (A-C) and their association with tissue-specificity, measured by information on the basis of gene expression in differentiated cells and tissues from NIA database (D-F). Each dot represents the average for 100 genes with similar TF-responsiveness.

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Additional file 11:

Predicting tissue specificity (information) with regression analysis.

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Additional file 12:

Characterization of responsive and non-responsive genes. Proportion of genes with chromatin modifications, binding of transcription factors (TFs), and TF binding motifs in promoters.

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Additional file 13:

Comparison of chromatin modifications [7], binding of transcription factors [9,16,17], and binding motifs among responsive and non-responsive genes with no CpG islands. "n/s" = non-significant, otherwise significant (p < 0.05).

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Additional file 14:

Difference between responsive and non-responsive genes in the strength of H3K4 and H3K27 tri-methylation in promoters.

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Additional file 15:

Regression analysis of the effect of various factors on the TF-responsiveness of genes.

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Additional file 16:

Relationship between TF-responsiveness (Bi) measured from the alternative data set "NIA Other Perturbations" among genes with CpG islands and chromatin status. Chromatin status is characterized by the proportion of genes with H3K27me3 and H3K36me3 chromatin marks (scale on left side), and strength of H3K4 tri-methylation (number of ChIP-seq tags, scale on right side), estimated in groups of 100 genes with similar TF-responsiveness.

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Additional file 17:

Correspondence between gene expression in mouse ES cells measured by microarrays [9]and RNA-seq methods [19].

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