Annotation of Tribolium nuclear receptors reveals an evolutionary overacceleration of a network controlling the ecdysone cascade

TL;DR

This study characterizes the nuclear receptor set in Tribolium, revealing an overaccelerated evolution of key regulators in the ecdysone signaling pathway during the divergence of Mecopterida insects.

Contribution

It provides the first complete nuclear receptor set for Tribolium and uncovers an overacceleration of evolution in ecdysone cascade regulators in Mecopterida.

Findings

Nuclear receptors are conserved across holometabolous insects.

Overacceleration of evolutionary rates observed in ecdysone pathway regulators.

Tribolium nuclear receptor set reveals lineage-specific evolutionary dynamics.

Abstract

The Tribolium genome contains 21 nuclear receptors, representing all of the six known subfamilies. When compared to other species, this first complete set for a Coleoptera reveals a strong conservation of the number and identity of nuclear receptors in holometabolous insects. Two novelties are observed: the atypical NR0 gene knirps is present only in brachyceran flies, while the NR2E6 gene is found only in Tribolium and in Apis. Using a quantitative analysis of the evolutionary rate, we discovered that nuclear receptors could be divided into two groups. In one group of 13 proteins, the rates follow the trend of the Mecopterida genome-wide acceleration. In a second group of five nuclear receptors, all acting together at the top of the ecdysone cascade, we observed an overacceleration of the evolutionary rate during the early divergence of Mecopterida. We thus extended our analysis to the twelve classic ecdysone transcriptional regulators and found that six of them (ECR, USP, HR3, E75, HR4 and Kr-h1) underwent an overacceleration at the base of the Mecopterida lineage. By contrast, E74, E93, BR, HR39, FTZ-F1 and E78 do not show this divergence. We suggest that coevolution occurred within a network of regulators that control the ecdysone cascade. The advent of Tribolium as a powerful model should allow a better understanding of this evolution.