Gene connectivity and enzyme evolution in the human metabolic network

Abstract

Background: Determining the factors involved in the likelihood of a gene being under adaptive selection is still a challenging goal in Evolutionary Biology. Here, we perform an evolutionary analysis of the human metabolic genes to explore the associations between network structure and the presence and strength of natural selection in the genes whose products are involved in metabolism. Purifying and positive selection are estimated at interspecific (among mammals) and intraspecific (among human populations) levels, and the connections between enzymatic reactions are differentiated between incoming (in-degree) and outgoing (out-degree) links.

Results: We confirm that purifying selection has been stronger in highly connected genes. Long-term positive selection has targeted poorly connected enzymes, whereas short-term positive selection has targeted different enzymes depending on whether the selective sweep has reached fixation in the population: genes under a complete selective sweep are poorly connected, whereas those under an incomplete selective sweep have high out-degree connectivity. The last steps of pathways are more conserved due to stronger purifying selection, with long-term positive selection targeting preferentially enzymes that catalyze the first steps. However, short-term positive selection has targeted enzymes that catalyze the last steps in the metabolic network. Strong signals of positive selection have been found for metabolic processes involved in lipid transport and membrane fluidity and permeability.

Conclusions: Our analysis highlights the importance of analyzing the same biological system at different evolutionary timescales to understand the evolution of metabolic genes and of distinguishing between incoming and outgoing links in a metabolic network. Short-term positive selection has targeted enzymes with a different connectivity profile depending on the completeness of the selective sweep, while long-term positive selection has targeted genes with fewer connections that code for enzymes that catalyze the first steps in the network.

Reviewers: This article was reviewed by Diamantis Sellis and Brandon Invergo.

Keywords: Connectivity; Degree; Enzymes; Metabolism; Network topology; Positive selection; Purifying selection.

Fig. 1

Strength of purifying selection estimated among mammals versus gene connectivity in the human metabolic network. Nodes were divided using the 25th, 50th, and 75th percentiles and the mean ± standard error of the residuals of a linear regression of dN/dS controlling for genomic variables (CDS length, codon bias, and GC content) is plotted for each group. Global differences between groups were assessed by Kruskal-Wallis Rank Sum test. Highly connected genes are under stronger purifying selection

Fig. 2

Relationship between recent selection in humans and metabolic functions. Individual metabolic pathways were classified based on a global view of the metabolism as a three-layered system as described in [5]. Mean ± standard error of the residuals of a linear regression of the Hierarchical Boosting (HB) scores controlling for genomic variables (CDS length, codon bias, and GC content) is plotted for each category. a) Complete HB scores in CEU, b) Incomplete HB scores in CEU, c) Complete HB scores in CHB, and d) Incomplete HB scores in CHB. Inner Core: Glycolysis / Tricarboxylic Acid Cycle / Pentose Phosphate and Polysaccharides; Intermediate: Membrane Lipids, Nucleotide, Fatty Acid / Triacylglyceride, Cofactor, Fatty Acid / Hormone, and Amino acid; Outer: Steroid, Secondary Metabolism and Detoxification. Pair-wise p-values are adjusted by FDR (ns: p > 0.05; *: p < = 0.05; **: p < = 0.01; ***: p < = 0.001; ****: p < = 0.0001)