voyAGEr is freely available at https://compbio.imm.medicina.ulisboa.pt/voyAGEr
voyAGEr is composed of four main sections (the tabs in the navigation bar at the top):
Home (depicted by the home icon): to visually explain the used method and its associated findings featured in the application.
Gene: to lead a gene-centric investigation, namely to assess how the expression of a specific gene changes with age and sex in a specific tissue.
Tissue: to analyse how tissue-specific transcriptomes change with age and sex.
Module: to further examine sets of co-expressed genes whose expression is altered with age namely through their enrichment in specific cell types, biological pathways and association with diseases.
voyAGEr leverages RNA-seq datasets from the GTEx project (Lonsdale et al., 2013), encompassing tissue samples from hundreds of donors aged from 20 to 70 years.
Cellular senescence is a stress-induced cell cycle arrest limiting proliferation of potentially oncogenic cells but progressively creating an inflammatory environment in tissues as they age and therefore an example of a process whose molecular mechanisms are of particular interest to ageing researchers (Gorgoulis et al., 2019; Van Deursen, 2014).
Senescence markers, such as CDKN2A, encoding cell cycle regulatory protein p16INK4A that accumulates in senescent cells (Erickson et al., 1998; Gil & Peters, 2006), can thus be studied as putative markers of ageing of certain tissues.
To examine CDKN2A expression changes across age:
Go to the “Gene” section
Type CDKN2A in the “Gene” field
Note that gene names in voyAGEr are HGNC (HUGO Gene Nomenclature Committee) symbols. For each gene, the respective NCBI and GeneCards webpages can be accessed by clicking on their names next to its HGNC symbol on the plot’s title.
Figure 2.1: Heatmap of tissue-specific CDKN2A expression over age.
Figure 2.2: Heatmap of significance of tissue-specific Age-associated CDKN2A expression alterations over age.
Enter/select “Lung” in the “Tissue” field to investigate CDKN2A expression changes in that specific tissue.
Plots of CDKN2A expression (top panel, identical to that in the "Profile" sub-tab) and the significance of its alterations over age (bottom panel) are then featured (Figure 2.3). Significant CDKN2A expression changes are observed in around 30 years-old, late forties and mid fifties.
The user can also check the overall changes of CDKN2A with age, represented as the subtitle of this figure. These are the results of fitting the ShARP-LM model on the entire age range, providing both p-value and t-statistic. A dashed line in orange summarizes these changes. A positive t-statistic represents an increase of expression with age.
Figure 2.3: CDKN2A expression in the lung (top panel) and significance of its alterations (bottom panel) over age.
GTEx transcriptomic data are from “healthy” tissue samples from donors that had, nonetheless, reported medical conditions (Lonsdale et al., 2013).
Click on “Sex” in the “Coloured by” field, leaving “All” in the “Shaped by” field.
CDKN2A lung expression progression with age appears to be influenced by the donors’ sex, particularly in the mid-thirties (Figure 2.4). The statistics of such observation can be assessed in the “Alteration” sub-tab by clicking on “Sex” in the “Alterations associated with” field.
As described in the previous point, the user can check the overall changes of CDKN2A between sexes, represented as the subtitle of this figure. The large dots represent the average gene expression in each sex (female in pink, male in blue) in the average age.
If the user intends to explore how the differences between sexes of age-associated changes in gene expression evolve with age, one can do so by browsing the “Age&Sex” option in the “Alterations associated with” field.
Back in the “Profile” sub-tab, click on “All” in the “Coloured by” field and on “Condition” in the “Shaped by” field. Enter/select “MHCOPD” in the “Select” field.
The CDKN2A lung expression profile is herein associated with medical conditions (positive if the donor suffered from the condition, negative if not and unknown if the association is uncharted). Moreover, the median gene expression values for positive and negative conditions are displayed. The significance of Kruskal-Wallis tests for the difference in gene expression medians between positive and negative donors is used to rank conditions. In this case, the condition selected (Chronic Respiratory Disease) is amongst those displaying a significant difference in median (adjusted p-value below 0.05). On the scatter plot with CDKN2A lung expression over age, the curves fitted independently for positive and negative conditions show that such differences in gene expression occurs mostly after the age of 55 (Figure 2.5).
Limitations: In the GTEx dataset, there are conditions for which very few donors are positive and others for which very few donors have their condition state annotated. The significance of the Kruskal-Wallis tests must therefore be regarded with caution and as providing limited information. In this case, for example, even though significant differences in median were found for the Chronic Respiratory Disease, the low number of positive samples and their incidence in limited age ranges hamper any solid conclusion.
Figure 2.4: CDNK2A expression in the lung, discriminated between donors sex (female in pink, male in blue) over age.
Figure 2.5: CDNK2A expression in the lung, discriminated between donors with (green) and without (orange) Chronic Respiratory Disease, over age.
Go to the “Tissue” section.
The landscape of Age-, Sex- and Age&Sex-associated global gene expression alterations along age for all tissues can be profiled using the significance of proportions of altered genes. Three periods stand out with significant transcriptional changes associated with Age (keeping the default “All tissues” in the “Tissue” field and “Age” in the “Alterations associated with” field), after 55 years old (Figure 3.1). Moreover, most of the significant transcriptional differences between sexes appear to occur in the fifth and sixth decades of life (“All tissues” in the “Tissue” field and “Sex” in the “Alterations associated with” field) (Figure 3.2).
Figure 3.1: Heatmap of significance of tissue-specific Age-associated global gene expression alterations over age.
Figure 3.2: Heatmap of significance of tissue-specific Sex-associated global gene expression alterations over age.
Enter “Adipose – Subcutaneous” in the “Tissue” field and click on “Age” in the “Alterations associated with” field.
The progression of the percentage of Age-associated altered genes over age is now featured (Figure 3.3). The statistical significance of each proportion is also illustrated with a colour scale.Two periods of major transcriptional changes appear to occur, at late 20’s (13.6% altered genes) and late 40’s (4.7% altered genes).
Click on the dot at 29.57 years old (hovering over each point in the plot will show its details). The list of altered genes, ordered by their significance, appears on the sidebar on the left. Although visually not exactly the same as in the web app, you can also explore the table below.
Figure 3.3: Progression of the percentage of Age-associated altered genes over age in Adipose - Subcutaneous. For each age, the list of the most altered genes can be obtained by clicking on the respective dot.