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1 Imipramine Treatment and Resiliency Exhibit Similar Imipramine Treatment and Resiliency Exhibit Similar Chromatin Regulation in the Mouse Nucleus Accumbens in Depression Models Wilkinson et al. Supplemental Material 1. Supplemental Methods 2. Supplemental References for Tables 3. Supplemental Tables S1 – S24 SUPPLEMENTAL TABLE S1: Genes Demonstrating Increased Repressive DimethylK9/K27-H3 Methylation in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S2: Genes Demonstrating Decreased Repressive DimethylK9/K27-H3 Methylation in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S3: Genes Demonstrating Increased Repressive DimethylK9/K27-H3 Methylation in the Social Isolation Model (p<0.001) SUPPLEMENTAL TABLE S4: Genes Demonstrating Decreased Repressive DimethylK9/K27-H3 Methylation in the Social Isolation Model (p<0.001) SUPPLEMENTAL TABLE S5: Genes Demonstrating Common Altered Repressive DimethylK9/K27-H3 Methylation in the Social Defeat and Social Isolation Models (p<0.001) SUPPLEMENTAL TABLE S6: Genes Demonstrating Increased Repressive DimethylK9/K27-H3 Methylation in the Social Defeat and Social Isolation Models (p<0.001) SUPPLEMENTAL TABLE S7: Genes Demonstrating Decreased Repressive DimethylK9/K27-H3 Methylation in the Social Defeat and Social Isolation Models (p<0.001) SUPPLEMENTAL TABLE S8: Genes Demonstrating Increased Phospho-CREB Binding in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S9: Genes Demonstrating Decreased Phospho-CREB Binding in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S10: Genes Demonstrating Increased Phospho-CREB Binding in the Social Isolation Model (p<0.001) SUPPLEMENTAL TABLE S11: Genes Demonstrating Decreased Phospho-CREB Binding in the Social Isolation Model (p<0.001) SUPPLEMENTAL TABLE S12: Genes Demonstrating Altered Phospho-CREB Binding in the Social Defeat and Social Isolation Models (p<0.001) 1 SUPPLEMENTAL TABLE S13: Genes Demonstrating Reversal of Decreased Repressive DimethylK9/K27-H3 Methylation by Imipramine in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S14: Genes Demonstrating Reversal of Increased Repressive DimethylK9/K27-H3 Methylation by Imipramine in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S15: Genes Demonstrating Reversal of Decreased Phospho-CREB Binding by Imipramine in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S16: Genes Demonstrating Reversal of Increased Phospho-CREB Binding by Imipramine in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S17: Genes Demonstrating Increased Repressive DimethylK9/K27-H3 Methylation in Resilient Animals Compared to Susceptible Animals (p<0.001) SUPPLEMENTAL TABLE S18: Genes Demonstrating Decreased Repressive DimethylK9/K27-H3 Methylation in Resilient Animals Compared to Susceptible Animals (p<0.001) SUPPLEMENTAL TABLE S19: Genes Demonstrating Increased Phospho-CREB Binding in Resilient Animals Compared to Susceptible Animals(p<0.001) SUPPLEMENTAL TABLE S20: Genes Demonstrating Decreased Phospho-CREB Binding in Resilient Animals Compared to Susceptible Animals(p<0.001) SUPPLEMENTAL TABLE S21: Genes Demonstrating Reversal of Decreased Repressive DimethylK9/K27-H3 Methylation by Imipramine and by Resiliency in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S22: Genes Demonstrating Reversal of Increased Repressive DimethylK9/K27-H3 Methylation by Imipramine and by Resiliency in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S23: Genes Demonstrating Reversal of Decreased Phospho-CREB Binding by Imipramine and by Resiliency in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S24: Genes Demonstrating Reversal of Increased Phospho-CREB Binding by Imipramine and by Resiliency in the Social Defeat Model (p<0.001) 2 1. Supplemental Methods Analyses of ChIP-chip and gene expression data Pre-processing and normalization of ChIP-chip data The log2 ratios of signal intensities between the immunoprecipitated samples and control genomic DNA (input) were calculated. These ratios were scaled by Tukey’s Bi-weight method (Statistical Algorithms Description Document, 2002, Affymetrix), such that the values are robust against outliers. The data were then median-normalized in R software (R Development Core Team) as described previously (Gentleman et al., 2005). The floor method, which treats all negative values as zero, was used to handle background noises. Negative values represent background noise where control genomic sample shows the same or more gene enrichment than immunoprecipitated sample. These genes were not considered as endogenous gene targets of the chromatin modification or transcription factor under investigation. Identifying significant alterations from ChIP-chip data To identify the probes at which histone methylation is altered after chronic social defeat or social isolation, we derived a score (calculating the alteration for each probe from the mean; hereafter, alteration score) for each probe using the following procedures. First, the mean methylation signal for each probe under each condition was calculated by averaging the normalized log2 ratios of intensities of immunoprecipitated samples and input across the replicated samples. Second, methylation signal difference between the defeat or social isolation conditions and its control condition was calculated. Third, a moving average of the methylation signal difference of three adjacent probes within the promoter region of each gene was calculated to stabilize the signal, using an algorithm similar to the ChIPOTle algorithm (Buck et al., 2005). The alteration scores that 3 were more than 3.1 standard deviations from the mean were considered as significant, as described in Kim et al. (2005). False discovery rates (FDR) (Benjamini and Hochberg, 1995; Efron and Tibshirani, 2002) were further calculated using R ClassComparison package, which calculated FDR by fitting a beta-uniform mixture model (Pounds and Morris, 2003) to a set of p-values. For histone methylation data, the probes with p-values less than 0.001, corresponding to more than 3.1 standard deviation away from the mean, are claimed as significant probes, corresponding to FDR’s less than 0.18 and 0.16 for the defeat and isolation conditions, respectively. Certain gene promoters displayed both significant increases and decreases in H3 methylation at various probes along their promoter regions under defeat or isolation conditions. These genes were included in the Supplemental Tables as both up-regulated and down-regulated to avoid averaging out the information. The same analysis methods were applied to phospho-CREB ChIP-chip data to identify the probes with binding changes under defeat or isolation conditions. Promoter plots and genome-wide spatial binding patterns We used mpeak software (Zheng et al., 2007) to derive the signal peaks and overall spatial pattern of the locations of dimethylK9/K27-H3 and phospho-CREB binding relative to transcriptional start sites. The empirical densities of the peak location were plotted and compared between defeat (or isolation) condition and control condition. The empirical densities were estimated using R statistical software with all default settings (adjust=1). In this circumstance, the bandwidth was determined by R density function automatically according to the number of enrichment probes, identified from the mpeak package. The bandwidths for H3 methylation and phospho-CREB binding are 271 and 623, respectively, in social defeat. The bandwidths for H3 methylation and phospho-CREB binding are 315 and 649 respectively, in social isolation. Heatmaps 4 The heatmaps included in Figs. 1-4 of the manuscript depict the signal strength averaged across probes for each gene. Genes listed in the Tables are those with greater than 1.1 fold change in our published DNA expression arrays (Berton et al., 2006; Krishnan et al., 2007; Wallace et al., 2009). The genes were rearranged using the Spearman hierarchical clustering method (Genespring). Quality Control As one measure of quality control, we determined the consistency between biological replicates by calculating the overlap of significantly enriched genes for each replicate. As an example, we show the data for dimethylK9/K27-H3 for group- housed mice below. We observed similar reproducibility for other data, typically with between 70-80% identity between replicates at p values approaching zero (calculated as described above). Furthermore, the Pearson’s correlations between two replicates are about 0.6-0.9. Hierarchical clustering also confirmed that biological replicates clustered together. H3methylationingrouphousedmice 324 1272 375 5 2. Supplemental References Abdelhaleem M (2005) RNA helicases: regulators of differentiation. Clin Biochem 38:499-503. Akaishi J, Onda M, Okamoto J, Miyamoto S, Nagahama M, Ito K, Yoshida A, Shimizu K (2007) Down- regulation of an inhibitor of cell growth, transmembrane protein 34 (TMEM34), in anaplastic thyroid cancer. J Cancer Res Clin Oncol 133:213-218. Armache KJ, Kettenberger H, Cramer P (2005) The dynamic machinery of mRNA elongation. Curr Opin Struct Biol 15:197-203. Ashrafi MR, Shams S, Nouri M, Mohseni M, Shabanian R, Yekaninejad MS, Chegini N, Khodadad A, Safaralizadeh R (2007) A probable causative factor for an old problem: selenium and glutathione peroxidase appear to play important roles in epilepsy pathogenesis. Epilepsia 48:1750-1755. Bearer EL, Abraham MT (1999) 2E4 (kaptin): a novel actin-associated protein from human blood platelets found in lamellipodia and the tips of the stereocilia of the inner ear. Eur J Cell Biol 78:117-126. Bemark M, Martensson A, Liberg D, Leanderson
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