Distinct chromosomal “niches” in the genome of<i>Saccharomyces cerevisiae</i>provide the background for genomic innovation and shape the fate of gene duplicates

Stavropoulou, Athanasia; Tassios, Emilios; Kalyva, Maria; Georgoulopoulos, Michalis; Vakirlis, Nikolaos; Iliopoulos, Ioannis; Nikolaou, Christoforos

doi:10.1093/nargab/lqac086

Cited by 2 publications

(1 citation statement)

References 76 publications

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“…This search was conducted with BLASTp 32 using an E-value cut-off of 0.001 and the -max_target_seqs flag set to 1000. The results of the similarity searches were processed as in 36 : For each gene, we first obtained the list of all fungal species with a significant similarity match. Phylogenetic age of each gene was then calculated as the most recent common ancestor of all species with a match.…”

Section: Methodsmentioning

confidence: 99%

Ancestral Sequence Reconstruction as a tool to detect and study de novo gene emergence

Vakirlis,

Acar,

Cherupally

et al. 2024

Preprint

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New protein-coding genes can evolve from previously non-coding 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 (ASR) is a promising approach for inferring whether a gene has emerged de novo or not, as it can enable us to inspect whether a given genomic locus ancestrally harbored protein-coding capacity. However, the use of ASR 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 ASR as a tool for the detection and study of de novo genes? Here, we address this question by designing an ASR 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 ASR robustly predicts an ancient origin for 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 33 genes that can unequivocally be considered de novo originated since the split of theSaccharomycesgenus, including 20S. cerevisiae-specific genes. We find that the remaining, equivocal cases, may be explained by different evolutionary scenarios including rapid evolution and multiple losses, as well as a very recent de novo origin. Overall, our findings suggest that ASR is a valuable tool to study de novo gene emergence but should be applied with caution and awareness of its limitations.

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Section: Methodsmentioning

confidence: 99%

Ancestral Sequence Reconstruction as a tool to detect and study de novo gene emergence

Vakirlis,

Acar,

Cherupally

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

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

Vakirlis,

Acar,

Cherupally

et al. 2024

Genome Biology and Evolution

View full text Add to dashboard Cite

New protein-coding genes can evolve from previously non-coding 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 (ASR) is a promising approach for inferring whether a gene has emerged de novo or not, as it can enable us to inspect whether a given genomic locus ancestrally harbored protein-coding capacity. However, the use of ASR 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 ASR as a tool for the detection and study of de novo genes? Here, we address this question by designing an ASR 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 ASR robustly predicts an ancient origin for 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 S. cerevisiae-specific genes. We find that for the remaining equivocal cases, we cannot rule out different evolutionary scenarios including rapid evolution and multiple losses, or a recent de novo origin. Overall, our findings suggest that ASR is a valuable tool to study de novo gene emergence but should be applied with caution and awareness of its limitations.

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Distinct chromosomal “niches” in the genome ofSaccharomyces cerevisiaeprovide the background for genomic innovation and shape the fate of gene duplicates

Cited by 2 publications

References 76 publications

Ancestral Sequence Reconstruction as a tool to detect and study de novo gene emergence

Ancestral Sequence Reconstruction as a tool to detect and study de novo gene emergence

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

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