Additional file 1: of SMITE: an R/Bioconductor package that identifies network modules by integrating genomic and epigenomic information

Supplementary Methods. Figure S1 Proportions of RNA-seq reads from T. gondii-infected HFFs aligning to a composite hg19/Toxoplasma genome. Figure S2 Comparison of distance weighting effect on gene scores. Figure S3 Representation of simulations demonstrating the effects on high scoring genes of variation of weightings. Figure S4 Comparison of gene scores with reduced and full SMITE models. Figure S5 Examples of modules generated by full and reduced SMITE models. Figure S6 KS test results comparing SMITE and FEM module genes and a random sampling of 10,000 genes. Figure S7 Comparison of the performance of the full SMITE model with the FEM model. Table S1 Criteria for defining genomic contexts in HFFs. Table S2 Weighting criteria used for SMITE analysis of the T. gondii HFF dataset. Appendix 1 R code for analyzing T. gondii HFF dataset with SMITE. Appendix 2 R code for analyzing T. gondii HFF dataset with FEM. Supplementary references (PDF 5642 kb

Additional file 2: of SMITE: an R/Bioconductor package that identifies network modules by integrating genomic and epigenomic information

Supplementary Tables. Table S3 Gene symbol and score of the high scoring genes using three different methods: SMITE full model, SMITE reduced model, and FEM. Table S4 Modules discovered using FEM and genes composing the modules with their DNA methylation, expression, and overall statistics. Table S5 Modules discovered using the reduced model of SMITE (SMITE-R) with spin-glass. Table S6 Modules discovered using the full model of SMITE (SMITE-F) with spin-glass. Table S7 Pathways associated with the genes composing the modules discovered by FEM. Table S8 Pathways associated with the genes composing the modules discovered by the reduced model of SMITE (SMITE-R) using spin-glass. Table S9 Pathways associated with the genes composing the modules discovered by the full model of SMITE (SMITE-F) using spin-glass. Table S10 Quantifying the number of times pathways were found to be associated the modules discovered by either FEM, the reduced model of SMITE (SMITE-R) using spin-glass, or the full model of SMITE(SMITE-F) using spin-glass. Table S11 Genes composing the “summary network” found by either the reduced (SMITE-R) or full (SMITE-F) SMITE models using the Heinz algorithm. Table S12 Pathways associated with the genes composing the “summary network” discovered by the reduced model of SMITE(SMITE-R) using the Heinz algorithm. Table S13 Pathways associated with the genes composing the “summary network” discovered by the full model of SMITE (SMITE-F) using the Heinz algorithm. Table S14 Genes composing the “modules” found using no weights instead of weighting by distance. Table S15 Pathways associated with the genes in the modules identified without using distance weighting. (XLSX 269 kb

Weak association between aging effects in sun-protected human skin and tail skin from CB6F1 mice.

<p>The expression fold-change (old/young) over 40 years (human) or 2 years (mouse) was calculated for 15,203 transcripts associated with orthologous human and mouse genes. The scatterplot shows the human-mouse association between fold change estimates in (A) female human subjects versus female mice and (B) male human subjects versus male mice. The dashed blue line represents the least squares regression estimate, and the estimated Pearson correlation (<i>r</i>) is shown in the lower right quadrant (blue font). The yellow region in (A) and (B) outlines the central 50% of data points closest to the bivariate median (based upon Mahalanobis distance). The grey region outlines the central 80% of data points closest to the bivariate median (based upon Mahalanobis distance). A bivariate association, if present, would be indicated by an oblong (non-circular) shape of the yellow or grey region. In (A), the estimated correlation coefficient is significantly negative (<i>r</i> = −0.096; P<0.001). In (B), the estimated correlation coefficient is non-significant (<i>r</i> = −0.002; P = 0.77). Absence of significant correspondence between human and mouse aging effects was further supported based upon three other statistical methods for comparing gene expression profiles (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s007" target="_blank">Figures S7</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s008" target="_blank">S8</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s009" target="_blank">S9</a>).</p

Top-ranked motifs associated with aging effects in mouse tail skin (CB6F1 strain): Overlap with top-ranked human motifs but dissimilar associations with aging.

<p>The chart lists the top-scoring motifs associated with genes (A) increased by aging of tail skin in female mice, (B) decreased by aging of tail skin in female mice, (C) increased by aging of tail skin in males, and (D) decreased by aging of tail skin in males. For each motif (left margin), gene sets associated with a varying number of motif occurrences (in the region 2000 BP upstream/200 BP downstream of the transcription start site) were derived. For any one motif, gene sets with fewer motif occurrences were always larger than those sets containing genes with more motif occurrences (see legend in right margin). Thus, larger symbols correspond to larger gene sets with few motif occurrences while smaller symbols correspond to smaller gene sets with a larger number of motif occurrences (see legend). For each set, the proportion of age-increased to age-decreased genes was calculated (open symbols and horizontal axis; see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s003" target="_blank">Figure S3</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s004" target="_blank">S4</a> legends). A motif-expression association is indicated by deviation of this proportion from 0.50, with blue symbols corresponding to gene sets for which the estimated proportion differs significantly from 0.50 (comparison-wise P<0.05; Fisher's exact test), and yellow symbols corresponding to sets significant at a more stringent threshold (FDR-adjusted P<0.05; Bejamini-Hochberg correction). We noted two motif-aging associations that, for the same sex, were consistent in direction with those identified in humans (blue font; compare with <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s003" target="_blank">Figures S3</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s004" target="_blank">S4</a>). However, we noted nine associations that, for the same sex, were contrasting in direction compared to those identified in humans (magenta font; compare with <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s003" target="_blank">Figures S3</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s004" target="_blank">S4</a>). For each motif listed, candidate target genes are listed in the right margin (red labels for age-increased genes; green labels for age-decreased genes; see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s003" target="_blank">Figure S3</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s004" target="_blank">S4</a> legends).</p

Clusterin (<i>Clu</i>) expression is altered by aging in human and mouse organs and <i>Clu</i> expression is decreased in long-lived <i>Pit1</i>(<i>dw</i>/<i>dw</i>) mice (liver and hippocampus).

<p>Plots (A) and (B) display the expression of human clusterin (<i>CLU</i>) relative to age, where each open circle indicates the microarray-based expression estimate in sun-protected skin from an individual female or male. Red lines correspond to the least squares estimate for the regression of expression versus subject age, and blue lines represent the same regression but obtained using the Loess procedure. Panel (C) displays mean microarray-based expression levels of mouse <i>Clu</i> (±1 standard error) in tail skin from young (5 month) and old (30 months) CB6F1 mice (<i>n</i> = 5 per group). Panels (D)–(G) display average expression of mouse <i>Clu</i> in mice from three age groups (5 months, 17 months and 30 months) and from both sexes (<i>n</i> = 5–6 mice for each sex/age combination; RT-PCR with 18S ribosomal RNA used as an internal control gene for calculation of relative expression). Each panel (D)–(G) displays the mean expression levels in each group (± one standard error) normalized to the average expression level of the young (5 month) female group. For each sex, the average expression of middle-aged (17 month) and old groups (30 months) was compared to that of the young group (5 months). A red star indicates a significant difference relative to the youngest group of the same sex (P<0.05; two-sided two-sample t-test). A blue star is used to indicate a significant difference based upon a two-sample non-parametric statistical test (P<0.05; either Wilcoxon or Kruskal-Wallis rank sum test). Panels (H) and (I) display average expression of mouse clusterin (<i>Clu</i>) in long-lived <i>Pit1</i>(<i>dw</i>/<i>dw</i>) dwarf mice as compared to littermate controls with normal phenotypes (<i>n</i> = 6 per genotype; males; six months of age; <i>Actb</i> was used as an internal reference for calculation of relative expression).</p

<i>In silico</i> inflammation profiles of aging in mouse skin and other tissues: Tail skin aging leads to decreased expression of genes associated with antigen-presenting cells.

<p>An algorithm for calculation of inflammation profiles based on microarray data was used to establish a gene expression-based mapping of inflammation events associated with aging in mouse tail skin (CB6F1 strain) and other tissue types <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204-Swindell2" target="_blank">[31]</a> (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#s4" target="_blank">Methods</a>). This figure can be interpreted as described in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone-0033204-g001" target="_blank">Figure 1</a> legend and is based upon the influence of aging on the expression of “signature transcripts” associated with different cell populations (listed in left margin). Red colors in the chart denote evidence for an age-related expansion or infiltration of the cell population type listed in each row (sees color scale and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone-0033204-g001" target="_blank">Figure 1</a> legend). The opposite trend is denoted by green colors (see color scale and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone-0033204-g001" target="_blank">Figure 1</a> legend).</p

<i>Clec7a</i> expression is decreased with age in tail skin but increased by age in heart and lung from CB6F1 mice.

<p>RT-PCR was used to evaluate the expression of <i>Clec7a</i> in mice from three age groups (5 months, 17 months and 30 months) and both sexes (<i>n</i> = 5–6 mice for each sex/age combination). The expression of 18S ribosomal RNA (Rn18s) was used as an internal control gene for calculation of relative expression in each sample. Plots (A)–(F) show mean expression levels in each group (± one standard error), which have been normalized to the average expression level of the young (5 month) female group. In each plot, and for each sex, the average expression of middle-aged (17 month) and old groups (30 months) was compared to that of the young group (5 months). A blue star is used to indicate a significant difference based upon a two-sample non-parametric statistical test (P<0.05; either Wilcoxon or Kruskal-Wallis rank sum test).</p

<i>In silico</i> inflammation profiles of aging in human tissues: Sex-specific lymphocyte signatures in skin.

<p>An algorithm for calculation of inflammation profiles based on microarray data was used to establish a gene expression-based mapping of inflammation events associated with aging in human skin and other tissue types (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#s4" target="_blank">Methods</a> section and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone-0033204-g002" target="_blank">Figure 2</a> from Swindell et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204-Swindell2" target="_blank">[31]</a>). Colors reflect age-associated gene expression patterns among “signature transcripts” that exhibit elevated expression in different cell populations (listed in left margin). Dark red colors indicate cases in which signature transcripts for a given cell population increase with age (i.e., the ratio of age-increased to age-decreased signature transcripts is greater than one). Filled black circles indicate significant bias towards age-increased expression among signature transcripts (FDR-adjusted P<0.05; Fisher's exact test), suggesting increased abundance or infiltration of that cell population with aging. The opposite pattern, in which signature transcripts are disproportionately decreased with age, is indicated by green squares within the chart (indicative of decreased cell type abundance with age). For most cell population categories (rows), data from multiple cell populations was available, which permitted calculation of several signature transcript ratios (<i>r</i>₁, <i>r</i>₂…<i>r_n</i>). In these cases, the maximum ratio is displayed in the chart if the median value of <i>r</i>₁, <i>r</i>₂… <i>r_n</i> is greater than 0.50 (since, in this case, most evidence suggests bias towards age-increased expression among the <i>n</i> replicate sets of signature transcripts). The minimum ratio is displayed if the median value of <i>r</i>₁, <i>r</i>₂… <i>r_n</i> is less than 0.50 (since, in this case, most evidence suggests bias towards age-decreased expression among the <i>n</i> replicate sets of signature transcripts).</p

Signature transcripts of CD4+ T-cells exhibit sex-specific shifts in gene expression with age in human skin.

<p>We identified 500 probe sets (from the Affymetrix Human Genome U133 Plus 2.0 array) representing signature transcripts that exhibit high expression in CD4+ T-cells isolated from peripheral blood (based on data obtained under GEO series accession GSE14278). Scatterplots (A) and (C) display expression of these transcripts in skin samples from young and old human subjects. Red symbols represent probe sets with higher expression in old subjects, and green symbols represent probe sets with higher expression in young subjects. The relative proportion of these two probe set groups is indicated by the pie chart shown in each figure. In (A) (females), young subjects were between 18 and 22 years of age (<i>n</i> = 5) and old subjects were between 57 and 75 years of age (<i>n</i> = 5). In (C) (males), young subjects were between 18 and 27 years of age (<i>n</i> = 5) and old subjects were between 57 and 60 years of age (<i>n</i> = 5). Among all T-cell-associated probe sets, the average increase in old subjects was 11% in females, but in males, T-cell-associated probe sets decreased by 5.3% on average (P<0.001; two-sample t-test). Across all probe sets, moreover, fold-change differences between old and young mice were negatively correlated between the sexes (<i>r</i> = −0.13, P<0.001). In parts (B) and (D), subjects were divided into different age groups (<i>n</i> = 2–3 subjects per group). 40-year fold-change estimates (old/young) were then averaged across subjects belonging to the same age group for each of the 500 probe sets associated with the CD4+ T-cell signature. Grey boxes denote the median and inter-quartile range for the 500 fold-change estimates in each age group. The red background region denotes an average fold-change larger than one (i.e., signature transcripts are age-increased on average), while the green background region denotes an average fold-change less than one (i.e., signature transcripts are age-decreased on average).</p

Unsupervised clustering of gene expression signatures from humans and mice reveals that aging effects are predominantly species-specific.

<p>We generated gene expression profiles for aging in human and mouse skin and compared these with 25 aging profiles from human tissues and 28 aging profiles from mouse tissues. All human profiles (black labels) were generated based on data from the Affymetrix Human Genome U133 Plus 2.0 array platform and all mouse profiles (red labels) were generated based on data from the Affymetrix Mouse Genome 430 2.0 array platform (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s021" target="_blank">Tables S1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s022" target="_blank">S2</a>). The cluster analysis is based upon a total of 3785 human-mouse transcript pairs, which collectively, were associated with 3646 unique human genes and 3580 unique mouse genes. All human-mouse transcript pairs were significantly altered by aging with respect to at least three separate human profiles or at least three separate mouse profiles (FDR-adjusted P<0.05). Heat map colors denote an adjusted fold-change ratio (old/young) in units of standard deviations to permit visual and quantitative comparison across tissues and species. In humans, adjusted ratios were obtained by calculating the estimated 40-year fold change (old/young) for each transcript and dividing this ratio by the standard deviation of all 3785 ratios calculated in a given profile (i.e., each row of the heatmap). Similarly, in mice, adjusted ratios were obtained by calculating the 2-year fold change (old/young) for each transcript and dividing this ratio by the standard deviation of all 3785 ratios calculated in a given profile (i.e., each row of the heatmap). Further details on the experimental datasets used to generate human and mouse aging profiles is provided in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#s4" target="_blank">Methods</a> section, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s021" target="_blank">Table S1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033204#pone.0033204.s022" target="_blank">Table S2</a>.</p