Biology subjects

Carvunis, A.-R.

Publications and source records attributed to Carvunis, A.-R..

17 recordsLinked to original sources

bioRxiv2026

Environmental stress and phenotypic tradeoff modulate the adaptive potential of novel coding sequences for de novo gene birth

Novel protein-coding genes can emerge de novo from ancestrally noncoding sequences and promote adaptation to environmental stresses. Previous work proposes that pervasive translation of lowly expressed open reading frames (ORFs) in noncoding regions creates a rich reservoir of 'proto-genes,' of which subsequent acquisition of gene-like properties, such as increased expression, may be favored or purged by natural selection depending on their phenotypic impact. However, whether and how environmental conditions affect the phenotypic impact of proto-genes remains unclear. Here, we experimentally simulated proto-gene evolution in Saccharomyces cerevisiae by individually increasing the expression of nearly a thousand de novo ORFs with prior evidence of native translation under osmotic and endoplasmic-reticulum stress and in control environments. High-throughput phenotyping revealed that growth effects of increased expression varied strongly across environments for de novo ORFs. A follow-up screen across 22 diverse environments revealed a robust positive correlation between environmental stress severity and the mean growth effects of increased de novo ORF expression. At the individual level, 5.4% of tested de novo ORFs conferred beneficial phenotypes in at least one environment, and 83.3% of these also caused deleterious effects elsewhere, revealing widespread phenotypic tradeoffs. We demonstrate that increased expression of the de novo translated ORF YLR112W results in increased growth in the presence of rapamycin through general dampening of the growth-repressing transcriptomic response induced by this drug. Together, these findings demonstrate that stress severity shapes the phenotypic consequences of increased proto-gene expression and shed light on tradeoffs and transcriptome remodeling as mechanisms underlying such environmental dependency.

evolutionary biology↗

bioRxiv2026

The origin of taxonomically restricted genes in yeast

The evolutionary origins of taxonomically restricted "orphan" genes (TRGs), which lack known homologs outside of a specific taxon, have fueled a decades-long controversy. On the one hand, thousands of TRGs are proposed to have originated de novo from previously non-genic DNA. These include an expansive repertoire of newly discovered microproteins that were missed from genome annotations yet can mediate important phenotypes. On the other hand, critics contend that many TRGs are not novel gene creations, but rather the products of extreme sequence divergence leading to homology detection failure. Here, we resolve this controversy by systematically dissecting the origins of TRGs across the Saccharomyces taxon, using a sensitive profile-profile alignment approach to identify challenging homologs. Our results reconcile the two competing models by revealing a temporal shift in the mechanisms underlying TRG formation. We demonstrate that most species-specific TRGs are genuine de novo gene births whereas most of the TRGs that are conserved across the Saccharomyces genus derive from highly diverged ancestral genes whose homology is no longer detectable using common methods. These findings suggest that, in Saccharomyces, a high rate of de novo birth events is balanced by evolutionary attrition with little to no survivors after a few million years. Therefore, nearly all de novo genes appear destined to vanish, with little contribution to the stable genetic repertoire over deep evolutionary time, despite providing important contributions to species-specific physiology and adaptation in the present time.

evolutionary biology↗

bioRxiv2025

An expanded reference catalog of translated open reading frames for biomedical research

Non-canonical (i.e., unannotated) open reading frames (ncORFs) have until recently been omitted from reference genome annotations, despite evidence of their translation, limiting their incorporation into biomedical research. To address this, in 2022, we initiated the TransCODE consortium and built the first community-driven consensus catalog of human ncORFs, which was openly distributed to the research community via Ensembl-GENCODE. While this catalog represented a starting point for reference ncORF annotation, major technical and scientific issues remained. In particular, this initial catalogue had no standardized framework to judge the evidence of translation for individual ncORFs. Here, we present an expanded and refined catalog of the human reference annotation of ncORFs. By incorporating more datasets and by lifting constraints on ORF length and start-codon, we define a comprehensive set of 28,359 ncORFs that is nearly four times the size of the previous catalog. Furthermore, to aid users who wish to work with ncORFs with the strongest and most reproducible signals of translation, we utilized a data-driven framework (i.e. translation signature scores) to assess the accumulated evidence for any individual ncORF. Using this approach, we derive a subset of 7,888 ncORFs with translation evidence on par with canonical protein-coding genes, which we refer to as the Primary set. This set can serve as a reliable reference for downstream analyses and validation, with a particular emphasis on high quality. Overall, this update reflects continual community-driven efforts to make ncORFs accessible and actionable to the broader research public and further iterations of the catalog will continue to expand and refine this resource.

genomics↗

bioRxiv2025

Detection of human unannotated microproteins by mass spectrometry-based proteomics: a community assessment

Thousands of short open reading frames (sORFs) are translated outside of annotated coding sequences. Recent studies have pioneered searching for sORF-encoded microproteins in mass spectrometry (MS)- based proteomics and peptidomics datasets. Here, we assessed literature-reported MS-based identifications of unannotated human proteins. We find that studies vary by three orders of magnitude in the number of unannotated proteins they report. Of nearly 10,000 reported sORF-encoded peptides, 96% were unique to a single study, and 12% mapped to annotated proteins or proteoforms. Manual curation of a benchmark dataset of 406 manually evaluated spectra from 204 sORF-encoded proteins revealed large variation in peptide-spectrum match (PSM) quality between studies, with immunopeptidomics studies generally reporting higher quality PSMs than conventional enzymatic digests of whole cell lysates. We estimate that 65% of predicted sORF-encoded protein detections in immunopeptidomics studies were supported by high-quality PSMs versus 7.8% in non-immunopeptidomics datasets. Our work stresses the need for standardized protocols and analysis workflows to guide future advancements in microprotein detection by MS towards uncovering how many human microproteins exist.

genomics↗

bioRxiv2024

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins

A major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.

molecular biology↗

bioRxiv2024

Cellular processing of beneficial de novo emerging proteins

Recent evidence demonstrates that eukaryotic genomes encode thousands of evolutionarily novel proteins that originate de novo from non-coding DNA and can contribute to species-specific adaptations. Yet, it remains unclear how these incipient proteins--whose sequences are entirely new to nature--navigate the cellular environment to bring about phenotypic change. Here, we conduct a systematic in vivo investigation of yeast de novo proteins with enhanced growth phenotypes, revealing the early stages of cellular integration. We find that these proteins are strongly enriched at the endoplasmic reticulum (ER) relative to conserved proteins, and that they integrate into cellular systems through conserved membrane targeting, trafficking, and degradation pathways. Despite having unrelated sequences, ER-localized de novo proteins share a common molecular signature: a C-terminal transmembrane domain that likely enables recognition by conserved post-translational ER insertion pathways. After insertion, ER-localized de novo proteins traffic from the ER and their homeostasis is regulated by conserved proteasomal and vacuolar degradation pathways. Our findings demonstrate that ancient targeting and degradation pathways can accommodate young de novo proteins sharing a convergent molecular signature. These pathways may act as selective filters, biasing which young de novo proteins persist. Significance StatementDeeply conserved genes shape the core structure and function of cells, but novel genes are key drivers of biodiversity. Novel genes can arise by divergence from ancient genes, or de novo from non-genic DNA. For de novo genes to develop novel functions, it is necessary for them to be processed by the cell so that their protein levels and localization are regulated. However, little is known about how novel de novo genes obtain the capacity to engage the cellular machinery needed for this regulation. Here, we experimentally assess how a set of endoplasmic reticulum (ER)-localized proteins encoded by recently-evolved de novo genes are localized and degraded in yeast cells. We discover that, despite having entirely unique amino acid sequences, these proteins share biochemical signatures allowing them to engage the same ancient cellular machinery and localize to the ER membrane. Interestingly though, this machinery is not the one that targets most ancient proteins to the ER. These results indicate that even recently emerged proteins without an extensive period of evolutionary adaptation can be recognized by specific ancient cellular pathways, facilitating their localization and homeostasis.

evolutionary biology↗

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

Exploring the noncanonical translatome using massively integrated coexpression analysis

BackgroundRecent studies uncovered pervasive transcription and translation of thousands of noncanonical open reading frames (nORFs) outside of annotated genes. The contribution of nORFs to cellular phenotypes is difficult to infer using conventional approaches because nORFs tend to be short, of recent de novo origins, and lowly expressed. Here we develop a dedicated coexpression analysis framework that accounts for low expression to investigate the transcriptional regulation, evolution, and potential cellular roles of nORFs in Saccharomyces cerevisiae. ResultsOur results reveal that nORFs tend to be preferentially coexpressed with genes involved in cellular transport or homeostasis but rarely with genes involved in RNA processing. Mechanistically, we discover that young de novo nORFs located downstream of conserved genes tend to leverage their neighbors promoters through transcription readthrough, resulting in high coexpression and high expression levels. Transcriptional piggybacking also influences the coexpression profiles of young de novo nORFs located upstream of genes, but to a lesser extent and without detectable impact on expression levels. Transcriptional piggybacking influences, but does not determine, the transcription profiles of de novo nORFs emerging nearby genes. About 40% of nORFs are not strongly coexpressed with any gene but are transcriptionally regulated nonetheless and tend to form entirely new transcription modules. We offer a web browser interface (https://carvunislab.csb.pitt.edu/shiny/coexpression/) to efficiently query, visualize and download our coexpression inferences. ConclusionsOur results suggest that nORF transcription is highly regulated. Our coexpression dataset serves as an unprecedented resource for unraveling how nORFs integrate into cellular networks, contribute to cellular phenotypes, and evolve.

systems biology↗

bioRxiv2023

Rare detection of noncanonical proteins in yeast mass spectrometry studies

Ribosome profiling experiments indicate pervasive translation of short open reading frames (ORFs) outside of annotated protein-coding genes. However, shotgun mass spectrometry experiments typically detect only a small fraction of the predicted protein products of this noncanonical translation. The rarity of detection could indicate that most predicted noncanonical proteins are rapidly degraded and not present in the cell; alternatively, it could reflect technical limitations. Here we leveraged recent advances in ribosome profiling and mass spectrometry to investigate the factors limiting detection of noncanonical proteins in yeast. We show that the low detection rate of noncanonical ORF products can largely be explained by small size and low translation levels and does not indicate that they are unstable or biologically insignificant. In particular, proteins encoded by evolutionarily young genes, including those with well-characterized biological roles, are too short and too lowly-expressed to be detected by shotgun mass spectrometry at current detection sensitivities. Additionally, we find that decoy biases can give misleading estimates of noncanonical protein false discovery rates, potentially leading to false detections. After accounting for these issues, we found strong evidence for four noncanonical proteins in mass spectrometry data, which were also supported by evolution and translation data. These results illustrate the power of mass spectrometry to validate unannotated genes predicted by ribosome profiling, but also its substantial limitations in finding many biologically relevant lowly-expressed proteins.

genomics↗

bioRxiv2022

Unexpected growth of a classic yeast auxotroph

Organisms must either synthesize or assimilate essential organic compounds to survive. The homocysteine synthase Met15 has been considered essential for inorganic sulfur assimilation in yeast since its discovery in the 1970s. As a result, MET15 has served as a genetic marker for hundreds of experiments that play a foundational role in eukaryote genetics and systems biology. Nevertheless, we demonstrate here through structural and evolutionary modeling, in vitro kinetic assays, and genetic complementation, that an alternative homocysteine synthase encoded by the previously uncharacterized gene YLL058W enables cells lacking Met15 to assimilate enough inorganic sulfur for survival and proliferation. These cells however fail to grow in patches or liquid cultures unless provided with exogenous methionine or other organosulfurs. We show that this growth failure, which has historically justified the status of MET15 as a classic auxotrophic marker, is largely explained by toxic accumulation of the gas hydrogen sulfide due to a metabolic bottleneck. When patched or cultured with a hydrogen sulfide chelator, and when propagated as colony grids, cells without Met15 assimilate inorganic sulfur and grow, and cells with Met15 achieve even higher yields. Thus, Met15 is not essential for inorganic sulfur assimilation in yeast. Instead, MET15 is the first example of a yeast gene whose loss conditionally prevents growth in a manner that depends on local gas exchange. Our results have broad implications for investigations of sulfur metabolism, including studies of stress response, methionine restriction, and aging. More generally, our findings illustrate how unappreciated experimental variables can obfuscate biological discovery.

molecular biology↗

bioRxiv2021

A reference translatome map reveals two modes of protein evolution

Translation is the process by which ribosomes synthesize proteins. Ribosome profiling recently revealed that many short sequences previously thought to be noncoding are pervasively translated. To identify protein-coding genes in this noncanonical translatome, we combine an integrative framework for extremely sensitive ribosome profiling analysis, iRibo, with high-powered selection inferences tailored for short sequences. We construct a reference translatome for Saccharomyces cerevisiae comprising 5,400 canonical and almost 19,000 noncanonical translated elements. Only 14 noncanonical elements were evolving under detectable purifying selection. Surprisingly, a representative subset of translated elements lacking signatures of selection demonstrated involvement in processes including DNA repair, stress response and post-transcriptional regulation. Our results suggest that most translated elements are not conserved protein-coding genes and contribute to genotype-phenotype relationships through fast-evolving molecular mechanisms.

genomics↗

bioRxiv2021

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

Ribosome profiling (Ribo-seq) has catalyzed a paradigm shift in our understanding of the translational vocabulary of the human genome, discovering thousands of translated open reading frames (ORFs) within long non-coding RNAs and presumed untranslated regions of protein-coding genes. However, reference gene annotation projects have been circumspect in their incorporation of these ORFs due to uncertainties about their experimental reproducibility and physiological roles. Yet, it is indisputable that certain Ribo-seq ORFs make stable proteins, others mediate gene regulation, and many have medical implications. Ultimately, the absence of standardized ORF annotation has created a circular problem: while Ribo-seq ORFs remain unannotated by reference biological databases, this lack of characterisation will thwart research efforts examining their roles. Here, we outline the initial stages of a community-led effort supported by GENCODE / Ensembl, HGNC and UniProt to produce a consolidated catalog of human Ribo-seq ORFs.

genomics↗

bioRxiv2021

Elastic Network Modeling of Cellular Networks Unveils Sensor and Effector Genes that Control Information Flow

The high-level organization of the cell is embedded in long-range interactions that connect distinct cellular processes. Existing approaches for detecting long-range interactions consist of propagating information from source nodes through cellular networks, but the selection of source nodes is inherently biased by prior knowledge. Here, we sought to derive an unbiased view of long-range interactions by adapting a perturbation-response scanning strategy initially developed for identifying allosteric interactions within proteins. We deployed this strategy onto an elastic network model of the yeast genetic network. The genetic network revealed a superior propensity for long-range interactions relative to simulated networks with similar topology. Long-range interactions were detected systematically throughout the network and found to be enriched in specific biological processes. Furthermore, perturbation-response scanning identified the major sources and receivers of information in the network, named effector and sensor genes, respectively. Effectors formed dense clusters centrally integrated into the network, whereas sensors formed loosely connected antenna-shaped clusters. Long-range interactions between effector and sensor clusters represent the major paths of information in the network. Our results demonstrate that elastic network modeling of cellular networks constitutes a promising strategy to probe the high-level organization of the cell.

systems biology↗

bioRxiv2020

LI Detector: a framework for sensitive colony-based screens regardless of the distribution of fitness effects

Microbial growth characteristics have long been used to investigate fundamental questions of biology. Colony-based high-throughput screens enable parallel fitness estimation of thousands of individual strains using colony growth as a proxy for fitness. However, fitness estimation is complicated by spatial biases affecting colony growth, including uneven nutrient distribution, agar surface irregularities, and batch effects. Analytical methods that have been developed to correct for these spatial biases rely on the following assumptions: i) that fitness effects are normally distributed, and ii) that most genetic perturbations lead to minor changes in fitness. Although reasonable for many applications, these assumptions are not always warranted and can limit the ability to detect small fitness effects. Beneficial fitness effects, in particular, are notoriously difficult to detect under these assumptions. Here, we developed the linear interpolation-based detector (LI Detector) framework to enable sensitive colony-based screening without making prior assumptions about the underlying distribution of fitness effects. The LI Detector uses a grid of reference colonies to assign a relative fitness value to every colony on the plate. We show that the LI Detector is effective in correcting for spatial biases and equally sensitive towards increase and decrease in fitness. LI Detector offers a tunable system that allows the user to identify small fitness effects with unprecedented sensitivity and specificity. LI Detector can be utilized to develop and refine gene-gene and gene-environment interaction networks of colony-forming organisms, including yeast, by increasing the range of fitness effects that can be reliably detected.

bioinformatics↗

bioRxiv2019

Quantitative translation of dog-to-human aging by conserved remodeling of epigenetic networks

Mammals progress through similar physiological stages during life, from early development to puberty, aging, and death. Yet, the extent to which this conserved physiology reflects conserved molecular events is unclear. Here, we map common epigenetic changes experienced by mammalian genomes as they age, focusing on evolutionary comparisons of humans to dogs, an emerging model of aging. Using targeted sequencing, we characterize the methylomes of 104 Labrador retrievers spanning a 16 year age range, achieving >150X coverage within mammalian syntenic blocks. Comparison with human methylomes reveals a nonlinear relationship which translates dog to human years, aligns the timing of major physiological milestones between the two species, and extends to mice. Conserved changes center on specific developmental gene networks which are sufficient to capture the effects of anti-aging interventions in multiple mammals. These results establish methylation not only as a diagnostic age readout but as a cross-species translator of physiological aging milestones.

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↗