Uncovering de novo gene birth in yeast using deep transcriptomics

Abstract

De novo gene origination has been recently established as an important mechanism for the formation of new genes. In organisms with a large genome, intergenic and intronic regions provide plenty of raw material for new transcriptional events to occur, but little is know about how de novo transcripts originate in more densely-packed genomes. Here, we identify 213 de novo originated transcripts in Saccharomyces cerevisiae using deep transcriptomics and genomic synteny information from multiple yeast species grown in two different conditions. We find that about half of the de novo transcripts are expressed from regions which already harbor other genes in the opposite orientation; these transcripts show similar expression changes in response to stress as their overlapping counterparts, and some appear to translate small proteins. Thus, a large fraction of de novo genes in yeast are likely to co-evolve with already existing genes.

A community-driven roadmap to advance research on translated open reading frames detected by Ribo-seq

“…While the focus of the current article is on the annotation of Ribo-seq ORFs identified in human, it should be noted that Ribo-seq has also been used to identify translated ORFs in many other species, such as mouse (Ingolia et al, 2011;Ruiz-Orera et al, 2018), zebrafish (Bazzini et al, 2012(Bazzini et al, , 2014Chew et al, 2013), fly (Patraquim et al, 2020), nematode (Stadler and Fire, 2011), plant (Hsu et al, 2016;Juntawong et al, 2014), yeast (Blevins et al, 2021;Brar et al, 2012;Carvunis et al, 2012;Durand et al, 2019;Ingolia et al, 2009;Smith et al, 2014;Wilson and Masel, 2011) and bacterial and viral genomes (Finkel et al, 2021;Fremin et al, 2020;Hücker et al, 2017;Stern-Ginossar et al, 2012).…”

Foster thy young: Enhanced prediction of orphan genes in assembled genomes

“…The proportion of functional genes that are unannotated in any given species is unclear; we posit that, depending on the species, a sizable proportion of orphan genes remain unannotated. This is because many are sparsely expressed 16,25,44,48 3 for predictions of all tested scenario). For each prediction scenario, the ability to predict genes was greater for the genes of oldest phylostratum (Cellular Organisms) and gradually decreased for the younger phylostrata.…”

“…The proportion of functional genes that are unannotated in any given species is unclear; we posit that, depending on the species, a sizable proportion of orphan genes remain unannotated. This is because many are sparsely expressed16,25,44,48 , by definition none have homologs, many may have not yet evolved the canonical features by which a gene can be recognized ab initio, and there is a grey area in evolution between "noise" and "gene". Black arrows, evolutionary transitions; red font, protein-coding genes; green font, non-[protein]-coding genes; grey font, non-genic transcripts; blue oval, annotated protein-coding genes; green oval, annotated non-[protein]-coding genes.…”

Landscape of the Dark Transcriptome Revealed Through Re-mining Massive RNA-Seq Data

“…However, because it is not a given that newly evolved genes have canonical features, direct alignment of transcriptomic and/or proteomic data to the genome is critical for annotating orphan genes, as well as non-coding transcripts (lncRNAs, etc.) (Carvunis et al, 2012;Ruiz-Orera et al, 2014González et al, 2016;Lu et al, 2017;Wu and Knudson, 2018;Li et al, 2021;Blevins et al, 2021).…”