The universal distribution of evolutionary rates of genes and distinct characteristics of eukaryotic genes of different apparent ages

Abstract

The evolutionary rates of protein-coding genes in an organism span, approximately, 3 orders of magnitude and show a universal, approximately log-normal distribution in a broad variety of species from prokaryotes to mammals. This universal distribution implies a steady-state process, with identical distributions of evolutionary rates among genes that are gained and genes that are lost. A mathematical model of such process is developed under the single assumption of the constancy of the distributions of the propensities for gene loss (PGL). This model predicts that genes of different ages, that is, genes with homologs detectable at different phylogenetic depths, substantially differ in those variables that correlate with PGL. We computationally partition protein-coding genes from humans, flies, and Aspergillus fungus into age classes, and show that genes of different ages retain the universal log-normal distribution of evolutionary rates, with a shift toward higher rates in "younger" classes but also with a substantial overlap. The only exception involves human primate-specific genes that show a heavy tail of rapidly evolving genes, probably owing to gene annotation artifacts. As predicted, the gene age classes differ in characteristics correlated with PGL. Compared with "young" genes (e.g., mammal-specific human ones), "old" genes (e.g., eukaryote-specific), on average, are longer, are expressed at a higher level, possess a higher intron density, evolve slower on the short time scale, and are subject to stronger purifying selection. Thus, genome evolution fits a simple model with approximately uniform rates of gene gain and loss, without major bursts of genomic innovation.

Fig. 1.

Distributions of nucleotide sequence evolution rates for pairs of closely related eukaryotic, archaeal, and bacterial genomes. The evolutionary distances were calculated using the Jukes–Cantor correction and normalized so that the mean of each distribution was equal to 1. Metma, Methanococcus maripaludis C5 vs. M. maripaludis C7 (Euryarchaeota); Bursp, Burkholderia cenocepacia MC0–3 vs. B. vietnamiensis G4 (Proteobacteria); Salsp, Salinispora arenicola CNS-205 vs. S. tropica CNB-440 (Actinobacteria). The probability density curves were obtained by Gaussian-kernel smoothing of the individual data points (64).

Fig. 2.

Partitioning of eukaryotic gene sets into age classes. The filled portion of each bar shows those genes for which likely orthologs were identified in the corresponding closely related species, and the empty portion shows the remainder of the genes for which orthologs were not detected. (Top) Homo sapiens (orthologs in Macaca mulatta). (Middle) Drosophila melanogaster (orthologs in D. simulans). (Bottom) Aspergillus fumigatus (orthologs in Neosartorya fischeri).

Fig. 3.

Distributions of nucleotide sequence evolution rates for different age classes of eukaryotic genes. The evolutionary distances were calculated as in Fig. 1 but not normalized. (Top) H. sapiens (vs. M. mulatta). (Middle) D. melanogaster (vs. D. simulans). (Bottom) A. fumigatus (vs. N. fischeri). The probability density curves were obtained by Gaussian-kernel smoothing of the individual data points (64).

Fig. 4.

Expression of human genes from different age classes. (Top) The median EST counts. (Middle) The median expression level in microarray experiments. (Bottom) The median expression breadth (number of tissues where the gene is expressed) in microarray experiments.