Differences between the de novo proteome and its non-functional precursor can result from neutral constraints on its birth process, not necessarily from natural selection alone

Abstract

Proteins are among the most important constituents of biological systems. Because all proteins ultimately evolved from previously non-coding DNA, the properties of these non-coding sequences and how they shape the birth of novel proteins are also expected to influence the organization of biological networks. When trying to explain and predict the properties of novel proteins, it is of particular importance to distinguish the contributions of natural selection and other evolutionary forces. Studies in the field typically use non-coding DNA and GC-content-based random-sequence models to generate random expectations for the properties of novel functional proteins. Deviations from these expectations have been interpreted as the result of natural selection. However, interpreting such deviations requires a yet-unattained understanding of the raw material of de novo gene birth and its relation to novel functional proteins. We mathematically show how the importance of the "junk" polypeptides that make up this raw material goes beyond their average properties and their filtering by natural selection. We find that the mean of any property among novel functional proteins also depends on its variance among junk polypeptides and its correlation with their rate of evolutionary turnover. In order to exemplify the use of our general theoretical results, we combine them with a simple model that predicts the means and variances of the properties of junk polypeptides from the genomic GC content alone. Under this model, we predict the effect of GC content on the mean length and mean intrinsic disorder of novel functional proteins as a function of evolutionary parameters. We use these predictions to formulate new evolutionary interpretations of published data on the length and intrinsic disorder of novel functional proteins. This work provides a theoretical framework that can serve as a guide for the prediction and interpretation of past and future results in the study of novel proteins and their properties under various evolutionary models. Our results provide the foundation for a better understanding of the properties of cellular networks through the evolutionary origin of their components.

The high turnover of ribosome-associated transcripts fromde novoORFs produces gene-like characteristics available forde novogene emergence in wild yeast populations

“…First, the acquisition of an Open Reading Frames (ORFs) by mutations conferring a gain of in-frame start and stop codons and second, the acquisition of regulatory sites to allow the ORF transcription and translation and to produce de novo polypeptides. The third step would correspond to the retention of this structure by natural selection because of its positive effects on fitness (Schlotterer 2015;Nielly-Thibault and Landry 2018). The subsequent maintenance of the structure by purifying selection will lead to the gene being shared among species, as we see for groups of orthologous canonical genes.…”