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Song, et al's"Deep RNA Sequencing Reveals Novel Cardiac Transcriptomic Signatures for Physiological and Pathological Hypertrophy"

Figure 2

This figure begin to explore the general interaction patterns of DEGs in PAH and PHH models, attempting to identify key players in the differentiation of the hypertrophy models.

Figure_2A

    Part A of this figure represents a network of interactions of the genes up-regulated in PAH heart tissue relative to the normal or PHH heart tissue. The network was derived through Ingenuity Pathway Analysis (IPA), a software approach which generates plausible interactions of genes/proteins, based on interactions described in scientific literature. Each red node represents a gene upregulated in PAH relative to controls or PHH heart cells. White nodes thus represent genes expressed in PAH but also control heart cells.
    This approach showed that the transcription regulator genes Foxm1 (Forkhead box M1), Plk1 (polo-like kinase 1) and E2F1 (E2F transcription factor 1) – or more directly their corresponding proteins – are implicated in the regulation of a number of other proteins involved in PAH suggesting a strong role of these proteins in PAH pathogenesis.

Part B of this figure elaborates on figures 1B and 2A, providing histograms illustrating the degree of expression of the three specific genes which, as portrayed above, are strongly implicated as upstream regulators of many factors involved in PAH. The y axes, though unlabeled, represent the relative degree of gene expression in each experimental group at each point along the gene, based on the number of reads collected from each of the four mouse types' that could be mapped to the UCSC Genome Browser database. Each of these three genes is seen to be over-expressed in the PAH models (TAC) relative to PHH models (Exercise) or controls (Sham and Sedentary), further implicating these proteins in PAH pathogenesis. Positions along each gene are designated by the blue lines below the TAC read from each gene category, where thicker segments correspond to exons.

       Part C of this figure shows variations in sequences (illustrated in the sequence logos; the four diagrams with variable T, A, G and C heights) 1000 base pairs upstream of 417 genes up-regulated in PAH. This was done to inspect whether these sequences matched the binding sites of the transcription factors FOXM1 and PU.1, to substantiate these transcription factors' influence over expression of these genes. The first and third sequence logos from the top show the consensus sequences (binding sites) of FOXM1 and PU.1 respectively (whose expression across experimental groups are represented in the horizontal heatmaps; both are particularly enhanced in PAH models), and the patterns observed in the PAH up-regulated genes are shown in the second and fourth letter diagrams from the top. Letter height relative to a given position in a motif corresponds to the frequency at whcih a given nucleotide occurs at that position. Overall height at a position corresponds to "information content," corresponding to the probability at which the given nucleotide ratio labeled at a given position will be identified.

    Given the similarity between these genes' upstream promoter regions and the consensus sequences of FOXM1 and PU.1, this figure suggests that the expression of many of the genes upregulated in PAH is influenced by activity of FOXM1 or PU.1, with FOXM1 being more selectively involved in the process as it is the only of the two proteins selectively up-regulated in PAH.
   Sh = sham; T = TAC; Se = sedentary; Ex = exercise.

     Figure 2D provides another heatmap representing the degree of expression of the genes targeted by FOXM1. Strong expression of FOXM1 as reported in figure 2C is more notable due to the accompanying increased expression of the protein's downstream targets, further implying that this protein exerts a key role in PAH pathogenesis.
    PMID = PubMed Identifier (a number associated with PubMed databases with the corresponding gene.

    Overall, figure 2 suggests FOXM1 as a likely transcription factor involved in PAH pathogenesis due to its and its targets up-regulation in PAH relative to PHH models and controls. Table 1 and subsequent figures elaborate further on some of the gene expression differences between PAH and PHH, focusing on alternative splicing, a more specific aspect of genomic alterations that may occur between PAH and PHH models.

Introduction

Figure 1

Proceed to Table 1

Figure 3

Figure 4

References

Song, H. K., Hong, S. E., Kim, T., Kim D. H., et al. (2012). Deep RNA sequencing reveals novel cardiac transcriptomic signatures for physiological and pathological hypertrophy. PLoS One, 7, e35552.

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