The impact of trans-regulation on the evolutionary rates of metazoan proteins

Abstract

Transcription factor (TF) and microRNA (miRNA) are two crucial trans-regulatory factors that coordinately control gene expression. Understanding the impacts of these two factors on the rate of protein sequence evolution is of great importance in evolutionary biology. While many biological factors associated with evolutionary rate variations have been studied, evolutionary analysis of simultaneously accounting for TF and miRNA regulations across metazoans is still uninvestigated. Here, we provide a series of statistical analyses to assess the influences of TF and miRNA regulations on evolutionary rates across metazoans (human, mouse and fruit fly). Our results reveal that the negative correlations between trans-regulation and evolutionary rates hold well across metazoans, but the strength of TF regulation as a rate indicator becomes weak when the other confounding factors that may affect evolutionary rates are controlled. We show that miRNA regulation tends to be a more essential indicator of evolutionary rates than TF regulation, and the combination of TF and miRNA regulations has a significant dependent effect on protein evolutionary rates. We also show that trans-regulation (especially miRNA regulation) is much more important in human/mouse than in fruit fly in determining protein evolutionary rates, suggesting a considerable variation in rate determinants between vertebrates and invertebrates.

Figure 1.

Pearson’s coefficient of correlations (r) between N_TF and N_miR in human, mouse and fruit fly. The analyses were based on genes with TFBSs, miRNA targets and the other eight confounding factors (6870 human genes, 4903 mouse genes and 1768 fruit fly genes). Significance: ***P < 0.001.

Figure 2.

The distributions of relative impact of single-factor and dual-factor regulations on evolutionary rates: (A) d_N, (B) d_S and (C) d_N/d_S. The three vertical bars separately represent a set of genes regulated by miRNAs alone (denoted as ‘G_miR’), by both of TFs and miRNAs (denoted as ‘G_Both’) and by TFs alone (denoted as ‘G_TF’). Statistical significance is estimated using the two-tailed Wilcoxon rank sum test: ***P < 0.001.

Figure 3.

The RCVE of the ten factors: N_TF, N_miR, protein connectivity (PPI), expression level (ExpLvl), tissue specificity (τ), UTR length (UTRLeng), intron length (InLeng), intron number (InNum), solvent accessibility (SolAcc) and disorder content (DisCont) on d_N/d_S in human, mouse and fruit fly. The analyses were based on 6870 human genes, 4903 mouse genes and 1768 fruit fly genes.