Natural selection governs local, but not global, evolutionary gene coexpression networks in Caenorhabditis elegans

Abstract

Background: Large-scale evaluation of gene expression variation among Caenorhabditis elegans lines that have diverged from a common ancestor allows for the analysis of a novel class of biological networks - evolutionary gene coexpression networks. Comparative analysis of these evolutionary networks has the potential to uncover the effects of natural selection in shaping coexpression network topologies since C. elegans mutation accumulation (MA) lines evolve essentially free from the effects of natural selection, whereas natural isolate (NI) populations are subject to selective constraints.

Results: We compared evolutionary gene coexpression networks for C. elegans MA lines versus NI populations to evaluate the role that natural selection plays in shaping the evolution of network topologies. MA and NI evolutionary gene coexpression networks were found to have very similar global topological properties as measured by a number of network topological parameters. Observed MA and NI networks show node degree distributions and average values for node degree, clustering coefficient, path length, eccentricity and betweeness that are statistically indistinguishable from one another yet highly distinct from randomly simulated networks. On the other hand, at the local level the MA and NI coexpression networks are highly divergent; pairs of genes coexpressed in the MA versus NI lines are almost entirely different as are the connectivity and clustering properties of individual genes.

Conclusion: It appears that selective forces shape how local patterns of coexpression change over time but do not control the global topology of C. elegans evolutionary gene coexpression networks. These results have implications for the evolutionary significance of global network topologies, which are known to be conserved across disparate complex systems.

Figure 1

Evolutionary gene coexpression networks. (A) Gene expression levels were measured across lines of C. elegans that diverged from a common ancestor. Relative expression levels across five MA lines (41, 24, 83, 99, N2) are shown for six genes. (B) Relative levels of gene expression across lines were compared for all pairs of genes using the Pearson correlation coefficient as shown here for genes B0024.11 × 3T27AS8.2. (C) In the evolutionary gene coexpression networks, genes are represented as nodes and gene pairs with r-values above the threshold cut-off are linked by edges.

Figure 2

Node degree (k) distributions for the MA, NI coexpression networks. (A) The connectivity distribution [f(k) × k] is shown for the MA (blue diamonds) and NI (red squares) coexpression networks. The inset of the panel shows the same plot with the axes in log₁₀-log₁₀ scale. (B-C) Comparison of exponential versus power-law curve fitting to the node degree distributions, shown without the tails. The best fitting power-law (dashed lines) and exponential (solid lines) trends are shown for each distribution. (B) Node degree distributions are shown in log₁₀-log₁₀ scale where a power-law distribution should follow a straight line. (C) Distributions are shown in semi-log₁₀ scale where an exponential distribution should follow a straight line. The data are better fit by an exponential distribution.

Figure 3

Node degree (k) distributions for random MA and NI networks. The connectivity distribution [f(k) × k] is shown for the random MA (blue diamonds) and random NI (red squares) coexpression networks. The inset of the figure shows the same plot with the axes in log₁₀-log₁₀ scale. The distributions are bell shaped and do not resemble the exponential-type distributions seen for the observed coexpression networks (Figure 1).

Figure 4

Comparison of k- and C-values for nodes (genes) found in both the MA and NI coexpression networks. MA- and NI-specific ordered vectors were populated with values of k and C for the 1,906 genes found in both networks. Values of k (A) and C (B) are plotted [MA × NI] and the linear trend in the data is shown. Essential genes are shown in pink and non-essential genes are shown in black.