Biology subjects

Vakirlis, N.

Publications and source records attributed to Vakirlis, N..

14 recordsLinked to original sources

bioRxiv2026

Evolutionary origins of protein novelty across an entire yeast subphylum

Novel protein-coding sequences fuel molecular and cellular evolutionary innovations and frequently contribute to species-defining characteristics. They can originate either de novo from previously noncoding sequences or through extreme divergence of already coding ones. How frequently each mechanism occurs and how they shape the structural and functional potential of the resulting proteins remains unclear. Here, we conducted a broad computational investigation of genetic and protein novelty throughout the entire subphylum of Saccharomycotina yeasts. We detected more than 5,000 robust de novo genes across 332 species and compared them to more than 6,000 novel genes resulting from extreme sequence divergence, revealing two quantitatively similar but qualitatively distinct modes of evolution of novelty. A remarkable 40% of de novo proteins are predicted to localize to mitochondria compared to only 20% of divergent, with the latter also being substantially longer and more disordered. A detailed analysis of conservatively predicted tertiary structures of novel proteins shows that ''invention'' of new folds occurs more frequently through de novo emergence. We also illustrate cases of evolutionary ''re-invention'' of existing protein folds from noncoding sequences. Our work deepens our understanding of the origins and importance of novel proteins, opening new directions for further structural and functional characterization.

genomics↗

bioRxiv2026

Identification and Classification of Expressed Orphan Genes, Spurious Orphan Genes, and Conserved Genes in the Human Gut Microbiome

Orphan genes - genes lacking detectable homologs outside a species - are widespread in microbial genomes and are thought to contribute to their adaptation and molecular innovation. However, not all predicted orphan genes may represent novel functional coding sequences. False positive orphan genes, also called spurious orphan genes, can arise from gene prediction errors. We reason that orphan genes lacking detectable expression are more likely to be spurious. To test this, we combined large-scale metatranscriptomic profiling of the human gut microbiome with machine learning to distinguish expressed orphan genes from spurious ones and to compare them with conserved genes found in multiple species. Using nearly 5,000 metatranscriptome libraries, we identified [~]218,000 orphan genes supported by expression evidence, while [~]330,000 predicted orphan genes lacked detectable expression, and were classified as spurious. We extracted 154 features for sequence, structural, and evolutionary properties for each gene and trained XGBoost classifiers while accounting for genomic representation. The models achieved an area under the receiver operating characteristic curve (AUC) of 0.82 in distinguishing expressed orphan genes from spurious orphan genes and an AUC of 0.93 in distinguishing expressed orphan genes from conserved genes. SHAP-based interpretation revealed clear biological signals. Particularly, expressed orphans were present in more genomes than spurious ones and expressed orphan genes were shorter than conserved genes. This work improves orphan gene discovery and suggests that expressed orphan genes differ systematically from conserved genes and spurious orphan genes in sequence composition, structural constraints, and evolutionary signals. Significance statementSpecies-specific genes, also called orphan genes, are abundant in bacterial genomes and have the potential to drive evolutionary innovation. However, the study of orphan genes is confounded by annotation errors that produce spurious gene predictions. Here, we leveraged nearly 5,000 metatranscriptomes from the human gut microbiome and implemented machine learning models to distinguish expressed orphan genes from non-expressed, likely spurious, genes and conserved genes. We show that a substantial fraction of predicted orphan genes lacks expression support and they exhibit distinct sequence and evolutionary signatures from expressed orphans. By integrating expression evidence with sequence-, structure-, and evolution-based features, our work refines orphan gene catalogs. This work improves the reliability of orphan gene discovery and provides new insights into the biological characteristics of orphan genes in human microbial communities.

genomics↗

bioRxiv2025

Machine learning can identify orphans that have diverged into the ''twilight zone'' of sequence similarity

Species-specific orphan genes (orphans) lack homologues outside of a given taxon and frequently underlie unique species traits. It is thus important to elucidate the evolutionary origins of orphans. Orphan genes can result from sequence divergence beyond recognition, when homologous proteins diverge to an extent at which tools that rely on sequence similarity to establish homology can no longer identify them as homologues. Orphans can also result from other processes, including de novo gene emergence from previously noncoding sequences, in which a homologous protein-coding gene truly does not exist. Here we propose that orphans resulting from divergence might be recognizable from their patterns of non-statistically significant similarity hits which are almost always discarded. To test this, we simulated diverged orphan protein sequences based on conserved proteins from the Unified Human Gastrointestinal Protein catalogue (UHGP) and used reversed protein sequences as negative data sets. We trained four machine learning classifiers on features extracted from the similarity search tool DIAMONDs output, like total query coverage or maximum bit score. We tested the influence of evolutionary parameters such as simulation tree branch length, indel rate and among-site rate heterogeneity. We found that the performance of the models depends on the simulation parameters: when the underlying simulated divergence was moderate, accuracy reached [~]90%, but when extremely diverged scenarios where simulated accuracy dropped to [~]70%. The most important features for the classification were the number of alignments (hits) and the minimum hit E-value. When applying our classifier on a set of [~]170,000 eligible simulated orphans from the UHGP dataset, we found that [~]30% of them are predicted to be divergent and these are shorter and more disordered than the rest. Our classifiers and pre-processing python scripts are available at https://github.com/emiliostassios/Classification-of-divergent-genes-using-ML and can be readily used as a computationally fast means to obtain a candidate set of diverged orphans from any similarity search output. Therefore, our work allows to study such orphans across the tree of life and in doing so to recover cases of remote homology, get better estimates of the evolutionary age of protein families, detect cases of rapid divergence and more generally better understand how genetic novelty arises.

bioinformatics↗

bioRxiv2025

Intergenic polyA/T tracts explain the propensity of yeast de novo genes to encode transmembrane domains

New genes can emerge de novo from non-genic genomic regions. In budding yeast, computational predictions have shown that intergenic regions harbor a higher-than-expected propensity to encode transmembrane domains, and this propensity seems to be linked to the high prevalence of predicted transmembrane domains in evolutionarily young genes. However, what accounts for this enriched propensity is not known. Here we show that specific arrangements of polyA/T tracts, which are abundant and enriched in yeast intergenic regions explain this observation. We provide evidence that polyA/T tracts, which are known to act as Nucleosome Depleted Regions in a regulatory context, have been coopted through de novo gene emergence for the evolution of novel small genes encoding proteins with predicted transmembrane domains. Our findings contribute to our understanding of the process of de novo gene evolution and show how seemingly distinct but interacting levels of functionality can exist within the same genomic loci.

genomics↗

bioRxiv2024

Degradation determinants are abundant in human noncanonical proteins

The comprehensive characterization of human proteins, a key objective in contemporary biology, has been revolutionized by the identification of thousands of potential novel proteins through ribosome profiling and proteomics. Determining the physiological activity of these noncanonical proteins has proven difficult, because they are encoded by different types of coding regions and tend to share no sequence similarity with canonical polypeptides. Evidence from immunopeptidomic assays combined with a better understanding of the quality control of protein synthesis suggest that many noncanonical proteins may possess low stability in the cellular environment. Here, we tested this hypothesis by analyzing the frequency of multiple sequence features eliciting either proteasomal degradation or autophagy across 91,003 canonical (annotated) protein isoforms and 232,460 noncanonical proteins. Overall, noncanonical proteins were enriched for degradation-related features compared to all canonical proteins. Notably, degradation determinants were also enriched in canonical protein isoforms starting with a non-methionine amino acid. Analyses of original and shuffled sequences showed evidence of selective pressure either against or towards the accumulation of specific degradation signatures only in major isoforms of canonical proteins. However, stability was significantly higher in noncanonical proteins with evidence of phenotypic effects when knocked-out in cell lines. Notably, we found that the C-terminal tail hydrophobicity represents a reliable proxy for degradation propensity with potential applications in identifying functional noncanonical proteins. These findings underscore the critical role of degradation processes in regulating the half-life of noncanonical proteins and demonstrate the power of degradation-associated signatures in discriminating noncanonical genes likely to encode for biologically functional molecules.

genomics↗

bioRxiv2024

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

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 the Saccharomyces genus, including 20 S. 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.

evolutionary biology↗

bioRxiv2023

Large-scale investigation of orphan genes in the human gut microbiome elucidates their evolutionary origins

Species-specific genes, also known as orphans, are ubiquitous across lifes domains. In prokaryotes, species-specific orphan genes (SSOGs) are mostly thought to originate in external elements such as viruses, followed by horizontal gene transfer, while the scenario of native origination, through rapid divergence or de novo, is mostly dismissed. However, quantitative evidence supporting either scenario is lacking. Here, we systematically analyzed genomes from 4,644 human gut microbiome species and identified over 600,000 unique SSOGs, representing an average of 2.6% of a given species pangenome. These sequences are mostly rare within each species yet show signs of purifying selection. Overall, SSOGs use optimal codons less frequently, and their proteins are more disordered than those of conserved genes (i.e., non-SSOGs). Importantly, across species, the GC content of SSOGs closely matches that of conserved ones. In contrast, the [~]5% of SSOGs that share similarity to known viral sequences have distinct characteristics, including lower GC content. Thus, SSOGs with similarity to viruses differ from the remaining SSOGs, contrasting an external origination scenario for most SSOGs. By examining the orthologous genomic region in closely related species, we show that a small subset of SSOGs likely evolved natively de novo and find that these genes also differ in their properties from the remaining SSOGs. Our results challenge the notion that external elements are the dominant source of prokaryotic genetic novelty and will enable future studies into the biological role and relevance of species-specific genes in the human gut.

evolutionary biology↗

bioRxiv2023

Pan-transcriptome reveals a large accessory genome contribution to gene expression variation in yeast

Gene expression is an essential step in the translation of genotypes into phenotypes. However, little is known about the transcriptome architecture and the underlying genetic effects at a species-level. Here, we generated and analyzed the pan-transcriptome of [~]1,000 yeast natural isolates across 4,977 core and 1,468 accessory genes. We found that the accessory genome is an underappreciated driver of the transcriptome divergence. Global gene expression patterns combined with population structure show that the heritable expression variation mainly lies within subpopulation-specific signatures, for which the accessory genes are overrepresented. Genome-wide association analyses consistently highlight that the accessory genes are associated with proportionally more variants with larger effect sizes, illustrating the critical role of the accessory genome on the transcriptional landscape within and between populations.

genomics↗

bioRxiv2022

Intergenic regions of Saccharomycotina yeasts are enriched in potential to form transmembrane domains

Intergenic genomic regions have essential regulatory and structural roles that impose constraints on their sequences. But regions that do not currently encode proteins, also carry the potential to do so in the future. De novo gene emergence, the evolution of novel genes out of previously non-coding sequences has now been established as a potent force for genomic novelty. Recently, it was shown that intergenic regions in the genome of S. cerevisiae harbor pervasive cryptic potential to, if theoretically translated, form transmembrane domains (TM domains) more frequently than expected by chance, a property that we refer to as TM-forming enrichment. The source and biological relevance of this property is unknown. Here we expand the investigation into the TM-forming potential of intergenic regions to the entire Saccharomycotina budding yeast subphylum, in an effort to explain this property and understand its importance. We find pervasive but variable enrichment in TM-forming potential across the subphylum, regardless of the composition and average size of intergenic regions. This cryptic property is evenly spread across the genome, cannot be explained by the hydrophobic content of the sequence, and does not appear to localize to regions containing regulatory motifs. This TM-forming enrichment specifically, and not the actual TM-forming potential, is associated, across genomes, with more TM domains in evolutionarily young genes. Our findings shed light on this newly discovered feature of yeast genomes and constitute a first step towards understanding its evolutionary importance.

genomics↗

bioRxiv2022

Distinct chromosomal niches in the genome of S. cerevisiae provide the background for genomic innovation and shape the fate of gene duplicates

Gene duplication is a major source of genomic innovation in all eukaryotes, with large proportions of genes being the result of either small-scale (SSD) or genome-wide duplication (WGD) events. In the model unicellular eukaryote Saccharomyces cerevisiae, of which nearly one third of the genome corresponds to gene duplicates, the two modes of duplication have been shown to follow different evolutionary fates, with SSD genes being more prone to acquire novel functionalities (neofunctionalization) and WGD more likely to retain different parts of the original ancestral function (subfunctionalization). Having previously described aspects of functional compartmentalization for the genes of S. cerevisiae, in this work we set out to investigate the existence of positional preferences of gene duplicates. We found that SSD and WGD genes are organized in distinct gene clusters that are, furthermore, segregated, occupying different regions, with SSD being more peripheral and WGD more centrally positioned close to centromeric chromatin. Duplicate gene clusters differ from the rest of the genome in terms of gene size and spacing, gene expression variability and regulatory complexity. What is more interesting, some of these properties are also shared by singleton genes residing in duplicate-rich regions in a position-dependent manner. Our analysis further reveals particular chromatin architectures in the promoters of duplicate genes, which are generally longer, with less pronounced nucleosome-free regions, strong structural constraints and a larger number of regulatory elements. Such structural features appear to be important for gene evolution as we find SSD gene-pair co-expression to be strongly associated with the similarity of nucleosome positioning patterns. We propose that specific regions of the yeast genome provide a favourable environment for the generation and maintenance of small-scale gene duplicates. The existence of such genomic "niches" is supported by the enrichment of these regions in singleton genes bearing similarities with gene "relics", remnants of recent duplications that have reverted to single gene status. Our findings provide a valuable framework for the study of genomic innovation and suggest taking into account positional preferences in the study of gene emergence and fixation in experimentally and naturally evolving populations.

genomics↗

bioRxiv2021

De novo birth of functional, human-specific microproteins

We now have a growing understanding that functional short proteins can be translated out of small Open Reading Frames (sORF). Such "microproteins" can perform crucial biological tasks and can have considerable phenotypic consequences. However, their size makes them less amenable to genomic analysis, and their evolutionary origins and conservation are poorly understood. Given their short length it is plausible that some of these functional microproteins have recently originated entirely de novo from non-coding sequence. Here we test the possibility that de novo gene birth can produce microproteins that are functional "out-of-the-box". We reconstructed the evolutionary origins of human microproteins previously found to have measurable, statistically significant fitness effects. By tracing the appearance of each ORF and its transcriptional activation, we were able to show that, indeed, novel small proteins with significant phenotypic effects have emerged de novo throughout animal evolution, including many after the human-chimpanzee split. We show that traditional methods for assessing the coding potential of such sequences often fall short, due to the high variability present in the alignments and the absence of telltale evolutionary signatures that are not yet measurable. Thus we provide evidence that the functional potential intrinsic to sORFs can be rapidly, and frequently realised through de novo gene birth.

evolutionary biology↗

bioRxiv2019

Synteny-based analyses indicate that sequence divergence is not the dominant source of orphan genes

The origin of "orphan" genes, species-specific sequences that lack detectable homologues, has remained mysterious since the dawn of the genomic era. There are two dominant explanations for orphan genes: complete sequence divergence from ancestral genes, such that homologues are not readily detectable; and de novo emergence from ancestral non-genic sequences, such that homologues genuinely do not exist. The relative contribution of the two processes remains unknown. Here, we harness the special circumstance of conserved synteny to estimate the contribution of complete divergence to the pool of orphan genes. By separately comparing yeast, fly and human genes to related taxa using conservative criteria, we find that complete divergence accounts, on average, for at most a third of eukaryotic orphan and taxonomically restricted genes. We observe that complete divergence occurs at a stable rate within a phylum but at different rates between phyla, and is frequently associated with gene shortening akin to pseudogenization. Two cancer-related human genes, DEC1 and DIRC1, have likely originated via this route in a primate ancestor.

evolutionary biology↗

bioRxiv2019

De novo emergence of adaptive membrane proteins from thymine-rich intergenic sequences

Recent evidence demonstrates that novel protein-coding genes can arise de novo from intergenic loci. This evolutionary innovation is thought to be facilitated by the pervasive translation of intergenic transcripts, which exposes a reservoir of variable polypeptides to natural selection. Do intergenic translation events yield polypeptides with useful biochemical capacities? The answer to this question remains controversial. Here, we systematically characterized how de novo emerging coding sequences impact fitness. In budding yeast, overexpression of these sequences was enriched in beneficial effects, while their disruption was generally inconsequential. We found that beneficial emerging sequences have a strong tendency to encode putative transmembrane proteins, which appears to stem from a cryptic propensity for transmembrane signals throughout thymine-rich intergenic regions of the genome. These findings suggest that novel genes with useful biochemical capacities, such as transmembrane domains, tend to evolve de novo within intergenic loci that already harbored a blueprint for these capacities.

evolutionary biology↗

bioRxiv2017

A Molecular Portrait Of De Novo Genes

New genes, with novel protein functions, can evolve \"from scratch\" out of intergenic sequences. These de novo genes can integrate the cells genetic network and drive important phenotypic innovations. Therefore, identifying de novo genes and understanding how the transition from noncoding to coding occurs are key problems in evolutionary biology. However, identifying de novo genes is a difficult task, hampered by the presence of remote homologs, fast evolving sequences and erroneously annotated protein coding genes. To overcome these limitations, we developed a procedure that handles the usual pitfalls in de novo gene identification and predicted the emergence of 703 de novo genes in 15 yeast species from two genera whose phylogeny spans at least 100 million years of evolution. We established that de novo gene origination is a widespread phenomenon in yeasts, only a few being ultimately maintained by selection. We validated 82 candidates, by providing new translation evidence for 25 of them through mass spectrometry experiments. We also unambiguously identified the mutations that enabled the transition from non-coding to coding for 30 Saccharomyces de novo genes. We found that de novo genes preferentially emerge next to divergent promoters in GC-rich intergenic regions where the probability of finding a fortuitous and transcribed ORF is the highest. We found a more than 3-fold enrichment of de novo genes at recombination hot spots, which are GC-rich and nucleosome-free regions, suggesting that meiotic recombination would be a major driving force of de novo gene emergence in yeasts.

evolutionary biology↗