Linear regression of gene connectivity of seven taxa analyzed.

<p>Taxa: <i>A</i>. <i>thaliana</i>, <i>G</i>. <i>max</i>, <i>Populus spp</i>., <i>S</i>. <i>lycopersicum</i>, <i>Vitis spp</i>., <i>O</i>. <i>sativa</i>, and <i>Z</i>. <i>mays</i>, against (a): non-synonymous substitutions (<i>dN</i>), (b): synonymous substitutions (<i>dS</i>), (c): estimates of adaptive evolution (ω = <i>dN</i>/<i>dS</i>) and (d): number of connections in ortholog comparison. Circles represent genes, while the regression coefficient, represented as Kendall's tau (τ) coefficient, is the dashed line. Significance is indicated by bold text. Note that all significant results except the two marked with an asterisk (*) remained significant after correcting for multiple comparisons (see text for details).</p

Connectivity in gene coexpression networks negatively correlates with rates of molecular evolution in flowering plants

<div><p>Gene coexpression networks are a useful tool for summarizing transcriptomic data and providing insight into patterns of gene regulation in a variety of species. Though there has been considerable interest in studying the evolution of network topology across species, less attention has been paid to the relationship between network position and patterns of molecular evolution. Here, we generated coexpression networks from publicly available expression data for seven flowering plant taxa (<i>Arabidopsis thaliana</i>, <i>Glycine max</i>, <i>Oryza sativa</i>, <i>Populus</i> spp., <i>Solanum lycopersicum</i>, <i>Vitis</i> spp., and <i>Zea mays</i>) to investigate the relationship between network position and rates of molecular evolution. We found a significant negative correlation between network connectivity and rates of molecular evolution, with more highly connected (i.e., “hub”) genes having significantly lower nonsynonymous substitution rates and <i>dN</i>/<i>dS</i> ratios compared to less highly connected (i.e., “peripheral”) genes across the taxa surveyed. These findings suggest that more centrally located hub genes are, on average, subject to higher levels of evolutionary constraint than are genes located on the periphery of gene coexpression networks. The consistency of this result across disparate taxa suggests that it holds for flowering plants in general, as opposed to being a species-specific phenomenon.</p></div

Simplified representation of a hypothetical coexpression network.

<p>Node A represents a hub gene while node B represents a peripheral gene. Lines connecting nodes represent network edges, and reflect correlations in expression.</p

Table listing the output of GO term enrichment analysis for each co-expression network module.

Each tab contains a GO term along with over represented and under represented P-values, the number of DEGs found belonging to that category, the total number of genes belonging to that category, the description of the GO term, and the GO ontology category that term belongs to. Each tab corresponds to a different module in the network. (XLSX)</p

Phenotypic means and standard deviations of all measured traits (n = 21).

Phenotypic means and standard deviations of all measured traits (n = 21).</p

Table displaying the results of the module/intersection enrichment analysis.

Results are broken down into two tabs, one for leaf tissue and one for root tissue. The first column represents each stress and stress combination through single letter abbreviations (D = dry-down, P = PEG, S = salt, N = low-nutrient), the second column lists the module being tested for enrichment within the given intersection, the third column lists the under represented P-value, and the fourth column represents the over represented P-value. (XLSX)</p

Phenotypic trait comparison for control vs. stress scenarios.

In all panels, control is shown in gray, dry-down in blue, PEG in red, salt in yellow, and low-nutrient in green. (A) Boxplot of overall plant performance measured as total biomass. Black horizontal bars indicate median, while white diamonds indicate mean values per treatment. Letters above each box correspond to their post hoc Wilcoxon groupings. (B) Principal component analysis (PCA) for all measured traits (n = 21) illustrated using the first two PCs. (C) PCA of all size-independent traits (n = 10) illustrated using the first two PCs.</p

Table of differentially expressed genes and their expression data.

Each tab is a different test of differential comparison. The leaf_DEGs and root_DEGs tabs test all four stresses against the control treatments for leaf and root tissue respectively. The following tabs are identified using a common naming theme: The first letters in the tab correspond to the stress being compared against the control treatments (DD = dry-down, P = PEG, S = salt, N = low-nutrient) and the next letter corresponds to the tissue type (L = leaf, R = root) followed by “_DEGs”. (XLSX)</p

Table listing the output of KEGG term enrichment analysis for each co-expression network module.

Each tab contains a KEGG term along with the description of the KEGG term, over represented and under represented P-values, the number of DEGs found belonging to that category, and the total number of genes belonging to that category. Each tab corresponds to a different module in the network. (XLSX)</p

Visual depiction of correlations between gene co-expression modules and tissue/treatment.

Correlation values (upper text) and P-values (lower, parenthetical text) are presented in each cell. Color is determined by the sign and magnitude of the correlation. Positive correlations (red) indicate genes within a module are upregulated within a stress/tissue combination while negative correlations (blue) indicate that genes within the module are downregulated.</p