Incipient de novo genes can evolve from frozen accidents that escaped rapid transcript turnover

Abstract

A recent surge of studies have suggested that many novel genes arise de novo from previously noncoding DNA and not by duplication. However, most studies concentrated on longer evolutionary time scales and rarely considered protein structural properties. Therefore, it remains unclear how these properties are shaped by evolution, depend on genetic mechanisms and influence gene survival. Here we compare open reading frames (ORFs) from high coverage transcriptomes from mouse and another four mammals covering 160 million years of evolution. We find that novel ORFs pervasively emerge from noncoding regions but are rapidly lost again, while relatively fewer arise from the divergence of coding sequences but are retained much longer. We also find that a subset (14%) of the mouse-specific ORFs bind ribosomes and are potentially translated, showing that such ORFs can be the starting points of gene emergence. Surprisingly, disorder and other protein properties of young ORFs hardly change with gene age in short time frames. Only length and nucleotide composition change significantly. Thus, some transcribed de novo genes resemble 'frozen accidents' of randomly emerged ORFs that survived initial purging. This perspective complies with very recent studies indicating that some neutrally evolving transcripts containing random protein sequences may be translated and be viable starting points of de novo gene emergence.

De novoemergence of adaptive membrane proteins from thymine-rich intergenic sequences

“…1, 6). This model, consistent with studies showing that de novo emerging sequences remain volatile for millions of years 5,22,[41][42][43][44] , emphasizes that the selective pressures acting on proto-genes are different from those acting on canonical protein-coding genes. 20 Our work suggests that incipient proto-genes that expose cryptic TM domains through translation are more likely to carry adaptive potential than others, and thus more likely to contribute to evolutionary innovation through positive selection in S. cerevisiae (Figs.…”

Enhancers facilitate the birth of de novo genes and their integration into regulatory networks

“…We considered a set of 56,262 ORFs from transcripts expressed in the liver, brain, and testis of Mus musculus. Previous work assigned phylogenetic ages to these ORFs (Schmitz, et al 2018), based on the presence of homologous sequences in the transcriptomes of other mammalian species, including rat, human, and opossum (Fig. 1A).…”

“…For protein-coding genes, the essential prerequisites of this process are the formation of an open reading frame (ORF), together with the transcription and translation of that ORF. Because much of the genome is transcribed (Kapranov, et al 2007; Neme and Tautz 2016) and many lineage-specific transcripts containing ORFs show evidence of translation (Wilson and Masel 2011; Ingolia, et al 2014; Ruiz-Orera, et al 2014; Prabh and Rödelsperger 2016; Ruiz-Orera, et al 2018; Schmitz, et al 2018; Ruiz-Orera and Alba 2019; Zhang, et al 2019), the de novo evolution of new protein-coding genes is also a likely contributor to the growth of gene regulatory networks.…”

Frequent birth ofde novogenes in the compact yeast genome

“…The process of de novo gene birth appears to be universal to all organisms. Studies have identified de novo genes in several kingdoms; for example, baker's yeast (Carvunis et al 2012;Vakirlis et al 2018), fruit fly (Zhou et al 2008;Palmieri et al 2014;Zhao et al 2014), Arabidopsis (Li et al 2016), and mammals (Toll-Riera et al 2009;Ruiz-Orera et al 2015;Guerzoni and McLysaght 2016;Schmitz et al 2018;Wilson et al 2017;Wu et al 2011). A common feature that is shared between these studies is that de novo genes typically encode small proteins, the coding sequences tend to include infrequent codons, and they often display patterns of rapid evolution.…”

“…Estimating the rate of de novo gene birth is challenging; the prevalence of this mechanism for new gene creation is still a matter of debate (Light et al 2014;Casola 2018). On the one hand, studies which incorporate expression data (RNA-Seq and/or Ribo-Seq) find evidence of numerous new transcriptional events, and that many of the new transcripts are likely to be translated (Carvunis et al 2012;Schmitz et al 2018;Ruiz-Orera et al 2014;Lu et al 2017;Ruiz-Orera et al 2015). On the other hand, studies based mostly on annotated protein-coding genes and genomic comparisons result in much lower (and more conservative) estimates of de novo gene birth rates (Guerzoni and McLysaght 2016;Vakirlis et al 2018;Ekman and Elofsson 2010).…”