Ancestral Sequence Reconstruction as a Tool to Detect and Study De Novo Gene Emergence

Abstract

Abstract New protein-coding genes can evolve from previously noncoding genomic regions through a process known as de novo gene emergence. Evidence suggests that this process has likely occurred throughout evolution and across the tree of life. Yet, confidently identifying de novo emerged genes remains challenging. Ancestral sequence reconstruction is a promising approach for inferring whether a gene has emerged de novo or not, as it allows us to inspect whether a given genomic locus ancestrally harbored protein-coding capacity. However, the use of ancestral sequence reconstruction in the context of de novo emergence is still in its infancy and its capabilities, limitations, and overall potential are largely unknown. Notably, it is difficult to formally evaluate the protein-coding capacity of ancestral sequences, particularly when new gene candidates are short. How well-suited is ancestral sequence reconstruction as a tool for the detection and study of de novo genes? Here, we address this question by designing an ancestral sequence reconstruction workflow incorporating different tools and sets of parameters and by introducing a formal criterion that allows to estimate, within a desired level of confidence, when protein-coding capacity originated at a particular locus. Applying this workflow on ∼2,600 short, annotated budding yeast genes (<1,000 nucleotides), we found that ancestral sequence reconstruction robustly predicts an ancient origin for the most widely conserved genes, which constitute “easy” cases. For less robust cases, we calculated a randomization-based empirical P-value estimating whether the observed conservation between the extant and ancestral reading frame could be attributed to chance. This formal criterion allowed us to pinpoint a branch of origin for most of the less robust cases, identifying 49 genes that can unequivocally be considered de novo originated since the split of the Saccharomyces genus, including 37 Saccharomyces cerevisiae-specific genes. We find that for the remaining equivocal cases we cannot rule out different evolutionary scenarios including rapid evolution, multiple gene losses, or a recent de novo origin. Overall, our findings suggest that ancestral sequence reconstruction is a valuable tool to study de novo gene emergence but should be applied with caution and awareness of its limitations.