Conserved temporal ordering of promoter activation implicates common mechanisms governing the immediate early response across cell types and stimuli

The promoters of immediate early genes (IEGs) are rapidly activated in response to an external stimulus. These genes, also known as primary response genes, have been identified in a range of cell types, under diverse extracellular signals and using varying experimental protocols. Genomic dissection on a case-by-case basis has not resulted in a comprehensive catalogue of IEGs. I completed a rigorous meta-analysis of eight genome-wide FANTOM5 CAGE (cap analysis of gene expression) time-course datasets, and it revealed successive waves of promoter activation in IEGs, recapitulating known relationships between cell types and stimuli. I found a set of 57 (42 protein-coding) candidate IEGs possessing promoters that consistently drive a rapid but transient increase in expression following external stimulation. These genes show significant enrichment for known IEGs reported previously, pathways associated with the immediate early response, and include a number of non-coding RNAs with roles in proliferation and differentiation. There was strong conservation of the ordering of activation for these genes, such that 77 pairwise promoter activation orderings were conserved. Leveraging comprehensive CAGE time series data across cell types, I also observed extensive alternative promoter usage by such genes, which is likely to hinder their discovery from previous, smaller-scale studies. The common activation ordering of the core set of early-responding genes I identified may indicate conserved underlying regulatory mechanisms. By contrast, the considerably larger number of transiently activated genes that are specific to each cell type and stimulus illustrates the breadth of the primary response

Conserved temporal ordering of promoter activation implicates common mechanisms governing the immediate early response across cell types and stimuli

Conserved temporal precedence between IEGs (light blue nodes) and other protein-coding genes (green nodes) is shown by directed edges. Genes annotated with the GO term 'response to endoplasmic reticulum stress' (GO:003497) have a red rectangle around the gene name; red squares indicate genes with CAGE clusters enriched for XBP1 transcription factor binding sites

At the intersection of cultural and natural heritage: Distribution and conservation of the type localities of Italian endemic vascular plants

We conducted a GIS spatial analysis with the aim of providing the first quantitative large-scale overview of the distribution patterns of 1536 type localities (loci classici) of 1216 Italian endemic vascular plants and their relationship with a set of descriptive variables. Whereas some variables were used to model the presence-absence distribution patterns of the type localities for the whole set of endemics as well as for the subset of narrow endemics, others (e.g., presence inside or outside protected areas and Italian Important Plant Areas) were considered with the purpose of assessing potential assets or risks for conservation. The largest number of type localities was found within the Mediterranean biogeographic region (1134), followed by the Alpine region (306) and Continental region (96). A total of 670 locations are located on islands, whereas 866 are located on the Italian mainland (139 and 124 in the case of narrow endemics, respectively). A large number of type localities are located in mountainous areas and along the coastline, which can be seen as a potential risk for conservation. On the contrary, we detected a positive correlation with the distance from roads, which might be considered to be an asset. Importantly, 1030 type localities fall inside protected areas, whereas 506 localities fall outside protected areas, with 259 of these unprotected localities on islands. We propose considering the results of the analysis of the distribution of type localities of Italian endemics to be a strategic tool for conservation planning and resource management. Application of plant micro-reserves and integration of diverse legislation tools are suggested to strengthen efforts and increase conservation success

Figure S1. Methodology from Conserved temporal ordering of promoter activation implicates common mechanisms governing the immediate early response across cell types and stimuli

For each time series, the Bayesian evidence (log Z) is calculated for each of four predefined models. The time series is classified to the best fitting model. In this example, a time course for the immediate early gene FOS is assigned to the peak model. The prediction of the peak model for the inferred parameters is shown by the blue line in the bottom plot

Figure S5. Classifications for non-coding RNA TSS from Conserved temporal ordering of promoter activation implicates common mechanisms governing the immediate early response across cell types and stimuli

Stacked barcharts show, for each dataset, the numbers of TSSs for non-coding genes classified as peak, decay, dip, and linear, and the total percentage of TSS that could be classified

Figure S8. Distributions of expression change and t_p across datasets from Conserved temporal ordering of promoter activation implicates common mechanisms governing the immediate early response across cell types and stimuli

The differences between maximal expression and basal expression are greater for IEG than for other protein coding (A) and for non-coding genes (B). Times of peaking are comparable between peaking IEGs and other protein coding genes (C) but are significantly different between IEGs and non-coding RNAs (significant difference is indicated by an asterisk)

Supplementary data file 1 from Conserved temporal ordering of promoter activation implicates common mechanisms governing the immediate early response across cell types and stimuli

Peaking times for genes in the robust set in all dataset

Figure S4. IEGs are enriched in genes classified as peaks from Conserved temporal ordering of promoter activation implicates common mechanisms governing the immediate early response across cell types and stimuli

(A) Stacked bars show the numbers of known IEGs (light blue) and TFs (yellow) recovered for the four models of interest (linear, dip, decay and peak) in each time series dataset. Significant enrichment for known IEGs is denoted by an asterisk. Pie charts show the percentage of IEGs contained in the robust set (B) and in the group of genes peaking exclusively in one dataset (C), respectively

Figure S3. Sharing of peaking TSSs for known IEGs and candidate IEGs in the robust set from Conserved temporal ordering of promoter activation implicates common mechanisms governing the immediate early response across cell types and stimuli

For each gene in the robust set, bar charts show the number of datasets where each TSS is found to peak

Figure S6. Sharing of peaking TSSs for ncRNA in the robust set from Conserved temporal ordering of promoter activation implicates common mechanisms governing the immediate early response across cell types and stimuli

For each ncRNA in the robust set, bar charts show the number of datasets where each TSS is found to peak