Marie Kristin Lebherz, Bharat Ravi Iyengar, Erich Bornberg-Bauer
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Modeling Length Changes in De Novo Open Reading Frames during Neutral Evolution.
For protein coding genes to emerge de novo from a non-genic DNA, the DNA sequence must gain an open reading frame (ORF) and the ability to be transcribed. The newborn de novo gene can further evolve to accumulate changes in its sequence. Consequently, it can also elongate or shrink with time. Existing literature shows that older de novo genes have longer ORF, but it is not clear if they elongated with time or remained of the same length since their inception. To address this question we developed a mathematical model of ORF elongation as a Markov-jump process, and show that ORFs tend to keep their length in short evolutionary timescales. We also show that if change occurs it is likely to be a truncation. Our genomics and transcriptomics data analyses of seven Drosophila melanogaster populations are also in agreement with the model's prediction. We conclude that selection could facilitate ORF length extension that may explain why longer ORFs were observed in old de novo genes in studies analysing longer evolutionary time scales. Alternatively, shorter ORFs may be purged because they may be less likely to yield functional proteins.
期刊介绍:
About the journal
Genome Biology and Evolution (GBE) publishes leading original research at the interface between evolutionary biology and genomics. Papers considered for publication report novel evolutionary findings that concern natural genome diversity, population genomics, the structure, function, organisation and expression of genomes, comparative genomics, proteomics, and environmental genomic interactions. Major evolutionary insights from the fields of computational biology, structural biology, developmental biology, and cell biology are also considered, as are theoretical advances in the field of genome evolution. GBE’s scope embraces genome-wide evolutionary investigations at all taxonomic levels and for all forms of life — within populations or across domains. Its aims are to further the understanding of genomes in their evolutionary context and further the understanding of evolution from a genome-wide perspective.