A Continuum of Evolving De Novo Genes Drives Protein-Coding Novelty in Drosophila

New perspectives on Drosophila melanogaster de novo gene origination revealed by investigation of ancient African genetic variation

De novo genes can be defined as sequences producing evolutionarily derived transcripts that are not homologous to transcripts produced in an ancestor. While they appear to be taxonomically widespread, there is little agreement regarding their abundance, their persistence times in genomes, the population genetic processes responsible for their spread or loss, or their possible functions. In Drosophila melanogaster, 2 approaches have been used to discover these genes and investigate their properties. One uses traditional comparative approaches and existing genomic resources and annotations. A second approach uses raw transcriptome data to discover unannotated genes for which there is no evidence of presence in related species. Investigations using the second approach have focused on D. melanogaster genotypes from recently established cosmopolitan populations. However, most of the genetic variation in the species is found in African populations, suggesting the possibility that fuller understanding of genetic novelties in the species may follow from studies of these populations. Here, we investigate de novo gene candidates expressed in testis and accessory glands in a sample of flies from Zambia and compare them with candidate de novo genes expressed in North American populations. We report a large number of previously undiscovered de novo gene candidates, most of which are expressed polymorphically. Many are predicted to code for secreted proteins. In spite of much different levels of genomic variation in Zambian and North American populations, they express similar numbers of candidate de novo genes. We find evidence from genetic analysis of Raleigh inbred lines that a fraction of rarely expressed gene candidates in this population represent deleterious transcription promoted by inbreeding depression. Many de novo gene candidates are expressed in multiple tissues and both sexes, raising questions about how they may interact with natural selection. The relative importance of positive and negative selection, however, remains unclear.

DeNoFo: a file format and toolkit for standardised, comparable de novo gene annotation

Motivation

De novo genes emerge from previously non-coding regions of the genome, challenging the traditional view that new genes primarily arise through duplication and adaptation of existing ones. Characterised by their rapid evolution and their novel structural properties or functional roles, de novo genes represent a young area of research. Therefore, the field currently lacks established standards and methodologies, leading to inconsistent terminology and challenges in comparing and reproducing results.

Results

This work presents a standardised annotation format to document the methodology of de novo gene datasets in a reproducible way. We developed DeNoFo, a toolkit to provide easy access to this format that simplifies annotation of datasets and facilitates comparison across studies. Unifying the different protocols and methods in one standardised format, while providing integration into established file formats, such as fasta or gff, ensures comparability of studies and advances new insights in this rapidly evolving field.

Availability and Implementation

DeNoFo is available through the official Python Package Index (PyPI) and at https://github.com/EDohmen/denofo . All tools have a graphical user interface and a command line interface. The toolkit is implemented in Python3, available for all major platforms and installable with pip and uv.

An orphan gene is essential for efficient sperm entry into eggs in Drosophila melanogaster

While spermatogenesis has been extensively characterized in the Drosophila melanogaster model system, very little is known about the genes required for fly sperm entry into eggs. We identified a lineage-specific gene, which we named katherine johnson (kj), that is required for efficient fertilization. Males that do not express kj produce and transfer sperm that are stored normally in females, but sperm from these males enter eggs with severely reduced efficiency. Using a tagged transgenic rescue construct, we observed that the KJ protein localizes around the edge of the nucleus at various stages of spermatogenesis but is undetectable in mature sperm. These data suggest that kj exerts an effect on sperm development, the loss of which results in reduced fertilization ability. Interestingly, KJ protein lacks detectable sequence similarity to any other known protein, suggesting that kj could be a lineage-specific orphan gene. While previous bioinformatic analyses indicated that kj was restricted to the melanogaster group of Drosophila, we identified putative orthologs with conserved synteny, male-biased expression, and predicted protein features across the genus, as well as likely instances of gene loss in some lineages. Thus, kj was likely present in the Drosophila common ancestor. It is unclear whether its role in fertility had already evolved at that time or developed later in the lineage leading to D. melanogaster. Our results demonstrate a new aspect of male reproduction that has been shaped by a lineage-specific gene and provide a molecular foothold for further investigating the mechanism of sperm entry into eggs in Drosophila.

Orphan genes are not a distinct biological entity

The genome sequencing revolution has revealed that all species possess a large number of unique genes critical for trait variation, adaptation, and evolutionary innovation. One widely used approach to identify such genes consists of detecting protein-coding sequences with no homology in other genomes, termed orphan genes. These genes have been extensively studied, under the assumption that they represent valid proxies for species-specific genes. Here, we critically evaluate taxonomic, phylogenetic, and sequence evolution evidence showing that orphan genes belong to a range of evolutionary ages and thus cannot be assigned to a single lineage. Furthermore, we show that the processes generating orphan genes are substantially more diverse than generally thought and include horizontal gene transfer, transposable element domestication, and overprinting. Thus, orphan genes represent a heterogeneous collection of genes rather than a single biological entity, making them unsuitable as a subject for meaningful investigation of gene evolution and phenotypic innovation.

An orphan gene is essential for efficient sperm entry into eggs in Drosophila melanogaster

While spermatogenesis has been extensively characterized in the Drosophila melanogaster model system, very little is known about the genes required for fly sperm entry into eggs. We identified a lineage-specific gene, which we named katherine johnson (kj), that is required for efficient fertilization. Males that do not express kj produce and transfer sperm that are stored normally in females, but sperm from these males enter eggs with severely reduced efficiency. Using a tagged transgenic rescue construct, we observed that the KJ protein localizes around the edge of the nucleus at various stages of spermatogenesis but is undetectable in mature sperm. These data suggest that kj exerts an effect on sperm development, the loss of which results in reduced fertilization ability. Interestingly, KJ protein lacks detectable sequence similarity to any other known protein, suggesting that kj could be a lineage-specific orphan gene. While previous bioinformatic analyses indicated that kj was restricted to the melanogaster group of Drosophila, we identified putative orthologs with conserved synteny, male-biased expression, and predicted protein features across the genus, as well as likely instances of gene loss in some lineages. Thus, kj was likely present in the Drosophila common ancestor and subsequently evolved an essential role in fertility in D. melanogaster. Our results demonstrate a new aspect of male reproduction that has been shaped by a lineage-specific gene and provide a molecular foothold for further investigating the mechanism of sperm entry into eggs in Drosophila.

Expression of Random Sequences and de novo Evolved Genes From the Mouse in Human Cells Reveals Functional Diversity and Specificity

Proteins that emerge de novo from noncoding DNA could negatively or positively influence cellular physiology in the sense of providing a possible adaptive advantage. Here, we employ two approaches to study such effects in a human cell line by expressing random sequences and mouse de novo genes that lack homologs in the human genome. We show that both approaches lead to differential growth effects of the cell clones dependent on the sequences they express. For the random sequences, 53% of the clones decreased in frequency, and about 8% increased in frequency in a joint growth experiment. Of the 14 mouse de novo genes tested in a similar joint growth experiment, 10 decreased, and 3 increased in frequency. When individually analysed, each mouse de novo gene triggers a unique transcriptomic response in the human cells, indicating mostly specific rather than generalized effects. Structural analysis of the de novo gene open reading frames (ORFs) reveals a range of intrinsic disorder scores and/or foldability into alpha-helices or beta sheets, but these do not correlate with their effects on the growth of the cells. Our results indicate that de novo evolved ORFs could easily become integrated into cellular regulatory pathways, since most interact with components of these pathways and could therefore become directly subject to positive selection if the general conditions allow this.

De Novo Genes

Although the majority of annotated new genes in a given genome appear to have arisen from duplication-related mechanisms, recent studies have shown that genes can also originate de novo from ancestrally nongenic sequences. Investigating de novo-originated genes offers rich opportunities to understand the origin and functions of new genes, their regulatory mechanisms, and the associated evolutionary processes. Such studies have uncovered unexpected and intriguing facets of gene origination, offering novel perspectives on the complexity of the genome and gene evolution. In this review, we provide an overview of the research progress in this field, highlight recent advancements, identify key technical and conceptual challenges, and underscore critical questions that remain to be addressed.

The ribosome profiling landscape of yeast reveals a high diversity in pervasive translation

BACKGROUND

Pervasive translation is a widespread phenomenon that plays a critical role in the emergence of novel microproteins, but the diversity of translation patterns contributing to their generation remains unclear. Based on 54 ribosome profiling (Ribo-Seq) datasets, we investigated the yeast Ribo-Seq landscape using a representation framework that allows the comprehensive inventory and classification of the entire diversity of Ribo-Seq signals, including non-canonical ones.

RESULTS

We show that if coding regions occupy specific areas of the Ribo-Seq landscape, noncoding regions encompass a wide diversity of Ribo-Seq signals and, conversely, populate the entire landscape. Our results show that pervasive translation can, nevertheless, be associated with high specificity, with 1055 noncoding ORFs exhibiting canonical Ribo-Seq signals. Using mass spectrometry under standard conditions or proteasome inhibition with an in-house analysis protocol, we report 239 microproteins originating from noncoding ORFs that display canonical but also non-canonical Ribo-Seq signals. Each condition yields dozens of additional microprotein candidates with comparable translation properties, suggesting a larger population of volatile microproteins that are challenging to detect. Our findings suggest that non-canonical translation signals may harbor valuable information and underscore the significance of considering them in proteogenomic studies. Finally, we show that the translation outcome of a noncoding ORF is primarily determined by the initiating codon and the codon distribution in its two alternative frames, rather than features indicative of functionality.

CONCLUSION

Our results enable us to propose a topology of a species' Ribo-Seq landscape, opening the way to comparative analyses of this translation landscape under different conditions.

Sequence, Structure, and Functional Space of Drosophila De Novo Proteins

During de novo emergence, new protein coding genes emerge from previously nongenic sequences. The de novo proteins they encode are dissimilar in composition and predicted biochemical properties to conserved proteins. However, functional de novo proteins indeed exist. Both identification of functional de novo proteins and their structural characterization are experimentally laborious. To identify functional and structured de novo proteins in silico, we applied recently developed machine learning based tools and found that most de novo proteins are indeed different from conserved proteins both in their structure and sequence. However, some de novo proteins are predicted to adopt known protein folds, participate in cellular reactions, and to form biomolecular condensates. Apart from broadening our understanding of de novo protein evolution, our study also provides a large set of testable hypotheses for focused experimental studies on structure and function of de novo proteins in Drosophila.

smAMPsTK: a toolkit to unravel the smORFome encoding AMPs of plant species

The pervasive repertoire of plant molecules with the potential to serve as a substitute for conventional antibiotics has led to obtaining better insights into plant-derived antimicrobial peptides (AMPs). The massive distribution of Small Open Reading Frames (smORFs) throughout eukaryotic genomes with proven extensive biological functions reflects their practicality as antimicrobials. Here, we have developed a pipeline named smAMPsTK to unveil the underlying hidden smORFs encoding AMPs for plant species. By applying this pipeline, we have elicited AMPs of various functional activity of lengths ranging from 5 to 100 aa by employing publicly available transcriptome data of five different angiosperms. Later, we studied the coding potential of AMPs-smORFs, the inclusion of diverse translation initiation start codons, and amino acid frequency. Codon usage study signifies no such codon usage biases for smORFs encoding AMPs. Majorly three start codons are prominent in generating AMPs. The evolutionary and conservational study proclaimed the widespread distribution of AMPs encoding genes throughout the plant kingdom. Domain analysis revealed that nearly all AMPs have chitin-binding ability, establishing their role as antifungal agents. The current study includes a developed methodology to characterize smORFs encoding AMPs, and their implications as antimicrobial, antibacterial, antifungal, or antiviral provided by SVM score and prediction status calculated by machine learning-based prediction models. The pipeline, complete package, and the results derived for five angiosperms are freely available at https://github.com/skbinfo/smAMPsTK.Communicated by Ramaswamy H. Sarma.

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.

Are Most Human-Specific Proteins Encoded by Long Noncoding RNAs?

By looking for a lack of homologs in a reference database of 27 well-annotated proteomes of primates and 52 well-annotated proteomes of other mammals, 170 putative human-specific proteins were identified. While most of them are deemed uncertain, 2 are known at the protein level and 23 at the transcript level, according to UniProt. Interestingly, 23 of these 25 proteins are found to be encoded or to have close homologs in an open reading frame of a long noncoding human RNA. However, half of them are predicted to be at least 80% globular, with a single structural domain, according to IUPred, and with at least 80% of ordered residues, according to flDPnn. Strikingly, there is a near-complete lack of structural knowledge about these proteins, with no tertiary structure presently available in the Protein Data Bank and a fair prediction for one of them in the AlphaFold Protein Structure Database. Moreover, knowledge about the function of these possibly key proteins remains scarce.

The Rapid Evolution of De Novo Proteins in Structure and Complex

Recent studies in the rice genome-wide have established that de novo genes, evolving from noncoding sequences, enhance protein diversity through a stepwise process. However, the pattern and rate of their evolution in protein structure over time remain unclear. Here, we addressed these issues within a surprisingly short evolutionary timescale (<1 million years for 97% of Oryza de novo genes) with comparative approaches to gene duplicates. We found that de novo genes evolve faster than gene duplicates in the intrinsically disordered regions (such as random coils), secondary structure elements (such as α helix and β strand), hydrophobicity, and molecular recognition features. In de novo proteins, specifically, we observed an 8% to 14% decay in random coils and intrinsically disordered region lengths and a 2.3% to 6.5% increase in structured elements, hydrophobicity, and molecular recognition features, per million years on average. These patterns of structural evolution align with changes in amino acid composition over time as well. We also revealed higher positive charges but smaller molecular weights for de novo proteins than duplicates. Tertiary structure predictions showed that most de novo proteins, though not typically well folded on their own, readily form low-energy and compact complexes with other proteins facilitated by extensive residue contacts and conformational flexibility, suggesting a faster-binding scenario in de novo proteins to promote interaction. These analyses illuminate a rapid evolution of protein structure in de novo genes in rice genomes, originating from noncoding sequences, highlighting their quick transformation into active, protein complex-forming components within a remarkably short evolutionary timeframe.

Random, de novo, and conserved proteins: How structure and disorder predictors perform differently

Understanding the emergence and structural characteristics of de novo and random proteins is crucial for unraveling protein evolution and designing novel enzymes. However, experimental determination of their structures remains challenging. Recent advancements in protein structure prediction, particularly with AlphaFold2 (AF2), have expanded our knowledge of protein structures, but their applicability to de novo and random proteins is unclear. In this study, we investigate the structural predictions and confidence scores of AF2 and protein language model-based predictor ESMFold for de novo and conserved proteins from Drosophila and a dataset of comparable random proteins. We find that the structural predictions for de novo and random proteins differ significantly from conserved proteins. Interestingly, a positive correlation between disorder and confidence scores (pLDDT) is observed for de novo and random proteins, in contrast to the negative correlation observed for conserved proteins. Furthermore, the performance of structure predictors for de novo and random proteins is hampered by the lack of sequence identity. We also observe fluctuating median predicted disorder among different sequence length quartiles for random proteins, suggesting an influence of sequence length on disorder predictions. In conclusion, while structure predictors provide initial insights into the structural composition of de novo and random proteins, their accuracy and applicability to such proteins remain limited. Experimental determination of their structures is necessary for a comprehensive understanding. The positive correlation between disorder and pLDDT could imply a potential for conditional folding and transient binding interactions of de novo and random proteins.

Emergence of an Orphan Nitrogenase Protein Following Atmospheric Oxygenation

Molecular innovations within key metabolisms can have profound impacts on element cycling and ecological distribution. Yet, much of the molecular foundations of early evolved enzymes and metabolisms are unknown. Here, we bring one such mystery to relief by probing the birth and evolution of the G-subunit protein, an integral component of certain members of the nitrogenase family, the only enzymes capable of biological nitrogen fixation. The G-subunit is a Paleoproterozoic-age orphan protein that appears more than 1 billion years after the origin of nitrogenases. We show that the G-subunit arose with novel nitrogenase metal dependence and the ecological expansion of nitrogen-fixing microbes following the transition in environmental metal availabilities and atmospheric oxygenation that began ∼2.5 billion years ago. We identify molecular features that suggest early G-subunit proteins mediated cofactor or protein interactions required for novel metal dependency, priming ancient nitrogenases and their hosts to exploit these newly diversified geochemical environments. We further examined the degree of functional specialization in G-subunit evolution with extant and ancestral homologs using laboratory reconstruction experiments. Our results indicate that permanent recruitment of the orphan protein depended on the prior establishment of conserved molecular features and showcase how contingent evolutionary novelties might shape ecologically important microbial innovations.

High-throughput Selection of Human de novo-emerged sORFs with High Folding Potential

De novo genes emerge from previously noncoding stretches of the genome. Their encoded de novo proteins are generally expected to be similar to random sequences and, accordingly, with no stable tertiary fold and high predicted disorder. However, structural properties of de novo proteins and whether they differ during the stages of emergence and fixation have not been studied in depth and rely heavily on predictions. Here we generated a library of short human putative de novo proteins of varying lengths and ages and sorted the candidates according to their structural compactness and disorder propensity. Using Förster resonance energy transfer combined with Fluorescence-activated cell sorting, we were able to screen the library for most compact protein structures, as well as most elongated and flexible structures. We find that compact de novo proteins are on average slightly shorter and contain lower predicted disorder than less compact ones. The predicted structures for most and least compact de novo proteins correspond to expectations in that they contain more secondary structure content or higher disorder content, respectively. Our experiments indicate that older de novo proteins have higher compactness and structural propensity compared with young ones. We discuss possible evolutionary scenarios and their implications underlying the age-dependencies of compactness and structural content of putative de novo proteins.

The origin and structural evolution of de novo genes in Drosophila

Recent studies reveal that de novo gene origination from previously non-genic sequences is a common mechanism for gene innovation. These young genes provide an opportunity to study the structural and functional origins of proteins. Here, we combine high-quality base-level whole-genome alignments and computational structural modeling to study the origination, evolution, and protein structures of lineage-specific de novo genes. We identify 555 de novo gene candidates in D. melanogaster that originated within the Drosophilinae lineage. Sequence composition, evolutionary rates, and expression patterns indicate possible gradual functional or adaptive shifts with their gene ages. Surprisingly, we find little overall protein structural changes in candidates from the Drosophilinae lineage. We identify several candidates with potentially well-folded protein structures. Ancestral sequence reconstruction analysis reveals that most potentially well-folded candidates are often born well-folded. Single-cell RNA-seq analysis in testis shows that although most de novo gene candidates are enriched in spermatocytes, several young candidates are biased towards the early spermatogenesis stage, indicating potentially important but less emphasized roles of early germline cells in the de novo gene origination in testis. This study provides a systematic overview of the origin, evolution, and protein structural changes of Drosophilinae-specific de novo genes.

Quantification and modeling of turnover dynamics of de novo transcripts in Drosophila melanogaster

Most of the transcribed eukaryotic genomes are composed of non-coding transcripts. Among these transcripts, some are newly transcribed when compared to outgroups and are referred to as de novo transcripts. De novo transcripts have been shown to play a major role in genomic innovations. However, little is known about the rates at which de novo transcripts are gained and lost in individuals of the same species. Here, we address this gap and estimate the de novo transcript turnover rate with an evolutionary model. We use DNA long reads and RNA short reads from seven geographically remote samples of inbred individuals of Drosophila melanogaster to detect de novo transcripts that are gained on a short evolutionary time scale. Overall, each sampled individual contains around 2500 unspliced de novo transcripts, with most of them being sample specific. We estimate that around 0.15 transcripts are gained per year, and that each gained transcript is lost at a rate around 5× 10-5 per year. This high turnover of transcripts suggests frequent exploration of new genomic sequences within species. These rate estimates are essential to comprehend the process and timescale of de novo gene birth.

The ORFans' tale: new insights in plant biology

Orphan genes (OGs) are protein-coding genes without a significant sequence similarity in closely related species. Despite their functional importance, very little is known about the underlying molecular mechanisms by which OGs participate in diverse biological processes. Here, we discuss the evolutionary mechanisms of OGs' emergence with relevance to species-specific adaptations. We also provide a mechanistic view of the involvement of OGs in multiple processes, including growth, development, reproduction, and carbon-metabolism-mediated immunity. We highlight the interconnection between OGs and the sucrose nonfermenting 1 (SNF1)-related protein kinases (SnRKs)-target of rapamycin (TOR) signaling axis for phytohormone signaling, nutrient metabolism, and stress responses. Finally, we propose a high-throughput pipeline for OGs' interspecies and intraspecies gene transfer through a transgenic approach for future biotechnological advances.

Evolution of termination codons of proteins and the TAG-TGA paradox

In most eukaryotes and prokaryotes TGA is used at a significantly higher frequency than TAG as termination codon of protein-coding genes. Although this phenomenon has been recognized several years ago, there is no generally accepted explanation for the TAG-TGA paradox. Our analyses of human mutation data revealed that out of the eighteen sense codons that can give rise to a nonsense codon by single base substitution, the CGA codon is exceptional: it gives rise to the TGA stop codon at an order of magnitude higher rate than the other codons. Here we propose that the TAG-TGA paradox is due to methylation and hypermutabilty of CpG dinucleotides. In harmony with this explanation, we show that the coding genomes of organisms with strong CpG methylation have a significant bias for TGA whereas those from organisms that lack CpG methylation use TGA and TAG termination codons with similar probability.

Towards understanding paleoclimate impacts on primate de novo genes

De novo genes are genes that emerge as new genes in some species, such as primate de novo genes that emerge in certain primate species. Over the past decade, a great deal of research has been conducted regarding their emergence, origins, functions, and various attributes in different species, some of which have involved estimating the ages of de novo genes. However, limited by the number of species available for whole-genome sequencing, relatively few studies have focused specifically on the emergence time of primate de novo genes. Among those, even fewer investigate the association between primate gene emergence with environmental factors, such as paleoclimate (ancient climate) conditions. This study investigates the relationship between paleoclimate and human gene emergence at primate species divergence. Based on 32 available primate genome sequences, this study has revealed possible associations between temperature changes and the emergence of de novo primate genes. Overall, findings in this study are that de novo genes tended to emerge in the recent 13 MY when the temperature continues cooling, which is consistent with past findings. Furthermore, in the context of an overall trend of cooling temperature, new primate genes were more likely to emerge during local warming periods, where the warm temperature more closely resembled the environmental condition that preceded the cooling trend. Results also indicate that both primate de novo genes and human cancer-associated genes have later origins in comparison to random human genes. Future studies can be in-depth on understanding human de novo gene emergence from an environmental perspective as well as understanding species divergence from a gene emergence perspective.

Identifying candidate de novo genes expressed in the somatic female reproductive tract of Drosophila melanogaster

Most eukaryotic genes have been vertically transmitted to the present from distant ancestors. However, variable gene number across species indicates that gene gain and loss also occurs. While new genes typically originate as products of duplications and rearrangements of preexisting genes, putative de novo genes-genes born out of ancestrally nongenic sequence-have been identified. Previous studies of de novo genes in Drosophila have provided evidence that expression in male reproductive tissues is common. However, no studies have focused on female reproductive tissues. Here we begin addressing this gap in the literature by analyzing the transcriptomes of 3 female reproductive tract organs (spermatheca, seminal receptacle, and parovaria) in 3 species-our focal species, Drosophila melanogaster-and 2 closely related species, Drosophila simulans and Drosophila yakuba, with the goal of identifying putative D. melanogaster-specific de novo genes expressed in these tissues. We discovered several candidate genes, located in sequence annotated as intergenic. Consistent with the literature, these genes tend to be short, single exon, and lowly expressed. We also find evidence that some of these genes are expressed in other D. melanogaster tissues and both sexes. The relatively small number of intergenic candidate genes discovered here is similar to that observed in the accessory gland, but substantially fewer than that observed in the testis.

The origin and structural evolution of de novo genes in Drosophila

Although previously thought to be unlikely, recent studies have shown that de novo gene origination from previously non-genic sequences is a relatively common mechanism for gene innovation in many species and taxa. These young genes provide a unique set of candidates to study the structural and functional origination of proteins. However, our understanding of their protein structures and how these structures originate and evolve are still limited, due to a lack of systematic studies. Here, we combined high-quality base-level whole genome alignments, bioinformatic analysis, and computational structure modeling to study the origination, evolution, and protein structure of lineage-specific de novo genes. We identified 555 de novo gene candidates in D. melanogaster that originated within the Drosophilinae lineage. We found a gradual shift in sequence composition, evolutionary rates, and expression patterns with their gene ages, which indicates possible gradual shifts or adaptations of their functions. Surprisingly, we found little overall protein structural changes for de novo genes in the Drosophilinae lineage. Using Alphafold2, ESMFold, and molecular dynamics, we identified a number of de novo gene candidates with protein products that are potentially well-folded, many of which are more likely to contain transmembrane and signal proteins compared to other annotated protein-coding genes. Using ancestral sequence reconstruction, we found that most potentially well-folded proteins are often born folded. Interestingly, we observed one case where disordered ancestral proteins become ordered within a relatively short evolutionary time. Single-cell RNA-seq analysis in testis showed that although most de novo genes are enriched in spermatocytes, several young de novo genes are biased in the early spermatogenesis stage, indicating potentially important but less emphasized roles of early germline cells in the de novo gene origination in testis. This study provides a systematic overview of the origin, evolution, and structural changes of Drosophilinae-specific de novo genes.

Population genomics reveals mechanisms and dynamics of de novo expressed open reading frame emergence in Drosophila melanogaster

Novel genes are essential for evolutionary innovations and differ substantially even between closely related species. Recently, multiple studies across many taxa showed that some novel genes arise de novo, that is, from previously noncoding DNA. To characterize the underlying mutations that allowed de novo gene emergence and their order of occurrence, homologous regions must be detected within noncoding sequences in closely related sister genomes. So far, most studies do not detect noncoding homologs of de novo genes because of incomplete assemblies and annotations, and long evolutionary distances separating genomes. Here, we overcome these issues by searching for de novo expressed open reading frames (neORFs), the not-yet fixed precursors of de novo genes that emerged within a single species. We sequenced and assembled genomes with long-read technology and the corresponding transcriptomes from inbred lines of Drosophila melanogaster, derived from seven geographically diverse populations. We found line-specific neORFs in abundance but few neORFs shared by lines, suggesting a rapid turnover. Gain and loss of transcription is more frequent than the creation of ORFs, for example, by forming new start and stop codons. Consequently, the gain of ORFs becomes rate limiting and is frequently the initial step in neORFs emergence. Furthermore, transposable elements (TEs) are major drivers for intragenomic duplications of neORFs, yet TE insertions are less important for the emergence of neORFs. However, highly mutable genomic regions around TEs provide new features that enable gene birth. In conclusion, neORFs have a high birth-death rate, are rapidly purged, but surviving neORFs spread neutrally through populations and within genomes.

Selection and geography shape male reproductive tract transcriptomes in Drosophila melanogaster

Transcriptome analysis of several animal clades suggests that male reproductive tract gene expression evolves quickly. However, the factors influencing the abundance and distribution of within-species variation, the ultimate source of interspecific divergence, are poorly known. Drosophila melanogaster, an ancestrally African species that has recently spread throughout the world and colonized the Americas in the last roughly 100 years, exhibits phenotypic and genetic latitudinal clines on multiple continents, consistent with a role for spatially varying selection in shaping its biology. Nevertheless, geographic expression variation in the Americas is poorly described, as is its relationship to African expression variation. Here, we investigate these issues through the analysis of two male reproductive tissue transcriptomes [testis and accessory gland (AG)] in samples from Maine (USA), Panama, and Zambia. We find dramatic differences between these tissues in differential expression between Maine and Panama, with the accessory glands exhibiting abundant expression differentiation and the testis exhibiting very little. Latitudinal expression differentiation appears to be influenced by the selection of Panama expression phenotypes. While the testis shows little latitudinal expression differentiation, it exhibits much greater differentiation than the accessory gland in Zambia vs American population comparisons. Expression differentiation for both tissues is non-randomly distributed across the genome on a chromosome arm scale. Interspecific expression divergence between D. melanogaster and D. simulans is discordant with rates of differentiation between D. melanogaster populations. Strongly heterogeneous expression differentiation across tissues and timescales suggests a complex evolutionary process involving major temporal changes in the way selection influences expression evolution in these organs.

Identifying candidate de novo genes expressed in the somatic female reproductive tract of Drosophila melanogaster

Most eukaryotic genes have been vertically transmitted to the present from distant ancestors. However, variable gene number across species indicates that gene gain and loss also occurs. While new genes typically originate as products of duplications and rearrangements of pre-existing genes, putative de novo genes - genes born out of previously non-genic sequence - have been identified. Previous studies of de novo genes in Drosophila have provided evidence that expression in male reproductive tissues is common. However, no studies have focused on female reproductive tissues. Here we begin addressing this gap in the literature by analyzing the transcriptomes of three female reproductive tract organs (spermatheca, seminal receptacle, and parovaria) in three species - our focal species, D. melanogaster - and two closely related species, D. simulans and D. yakuba , with the goal of identifying putative D. melanogaster -specific de novo genes expressed in these tissues. We discovered several candidate genes, which, consistent with the literature, tend to be short, simple, and lowly expressed. We also find evidence that some of these genes are expressed in other D. melanogaster tissues and both sexes. The relatively small number of candidate genes discovered here is similar to that observed in the accessory gland, but substantially fewer than that observed in the testis.

Experimental characterization of de novo proteins and their unevolved random-sequence counterparts

De novo gene emergence provides a route for new proteins to be formed from previously non-coding DNA. Proteins born in this way are considered random sequences and typically assumed to lack defined structure. While it remains unclear how likely a de novo protein is to assume a soluble and stable tertiary structure, intersecting evidence from random sequence and de novo-designed proteins suggests that native-like biophysical properties are abundant in sequence space. Taking putative de novo proteins identified in human and fly, we experimentally characterize a library of these sequences to assess their solubility and structure propensity. We compare this library to a set of synthetic random proteins with no evolutionary history. Bioinformatic prediction suggests that de novo proteins may have remarkably similar distributions of biophysical properties to unevolved random sequences of a given length and amino acid composition. However, upon expression in vitro, de novo proteins exhibit moderately higher solubility which is further induced by the DnaK chaperone system. We suggest that while synthetic random sequences are a useful proxy for de novo proteins in terms of structure propensity, de novo proteins may be better integrated in the cellular system than random expectation, given their higher solubility.

Assessing structure and disorder prediction tools for de novo emerged proteins in the age of machine learning

Background: De novo protein coding genes emerge from scratch in the non-coding regions of the genome and have, per definition, no homology to other genes. Therefore, their encoded de novo proteins belong to the so-called "dark protein space". So far, only four de novo protein structures have been experimentally approximated. Low homology, presumed high disorder and limited structures result in low confidence structural predictions for de novo proteins in most cases. Here, we look at the most widely used structure and disorder predictors and assess their applicability for de novo emerged proteins. Since AlphaFold2 is based on the generation of multiple sequence alignments and was trained on solved structures of largely conserved and globular proteins, its performance on de novo proteins remains unknown. More recently, natural language models of proteins have been used for alignment-free structure predictions, potentially making them more suitable for de novo proteins than AlphaFold2. Methods: We applied different disorder predictors (IUPred3 short/long, flDPnn) and structure predictors, AlphaFold2 on the one hand and language-based models (Omegafold, ESMfold, RGN2) on the other hand, to four de novo proteins with experimental evidence on structure. We compared the resulting predictions between the different predictors as well as to the existing experimental evidence. Results: Results from IUPred, the most widely used disorder predictor, depend heavily on the choice of parameters and differ significantly from flDPnn which has been found to outperform most other predictors in a comparative assessment study recently. Similarly, different structure predictors yielded varying results and confidence scores for de novo proteins. Conclusions: We suggest that, while in some cases protein language model based approaches might be more accurate than AlphaFold2, the structure prediction of de novo emerged proteins remains a difficult task for any predictor, be it disorder or structure.

Taxonomically Restricted Genes in Bacillus may Form Clusters of Homologs and Can be Traced to a Large Reservoir of Noncoding Sequences

Taxonomically restricted genes (TRGs) are unique for a defined group of organisms and may act as potential genetic determinants of lineage-specific, biological properties. Here, we explore the TRGs of highly diverse and economically important Bacillus bacteria by examining commonly used TRG identification parameters and data sources. We show the significant effects of sequence similarity thresholds, composition, and the size of the reference database in the identification process. Subsequently, we applied stringent TRG search parameters and expanded the identification procedure by incorporating an analysis of noncoding and non-syntenic regions of non-Bacillus genomes. A multiplex annotation procedure minimized the number of false-positive TRG predictions and showed nearly one-third of the alleged TRGs could be mapped to genes missed in genome annotations. We traced the putative origin of TRGs by identifying homologous, noncoding genomic regions in non-Bacillus species and detected sequence changes that could transform these regions into protein-coding genes. In addition, our analysis indicated that Bacillus TRGs represent a specific group of genes mostly showing intermediate sequence properties between genes that are conserved across multiple taxa and nonannotated peptides encoded by open reading frames.

De novo birth of functional microproteins in the human lineage

Small open reading frames (sORFs) can encode functional "microproteins" that perform crucial biological tasks. However, their size makes them less amenable to genomic analysis, and their 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 noncoding sequences. Here we sought to identify such cases in the human lineage by reconstructing the evolutionary origins of human microproteins previously found to have measurable, statistically significant fitness effects. By tracing the formation of each ORF and its transcriptional activation, we show that novel microproteins with significant phenotypic effects have emerged de novo throughout animal evolution, including two after the human-chimpanzee split. Notably, traditional methods for assessing coding potential would miss most of these cases. This evidence demonstrates that the functional potential intrinsic to sORFs can be relatively rapidly and frequently realized through de novo gene emergence.

Digging into the 3D Structure Predictions of AlphaFold2 with Low Confidence: Disorder and Beyond

AlphaFold2 (AF2) has created a breakthrough in biology by providing three-dimensional structure models for whole-proteome sequences, with unprecedented levels of accuracy. In addition, the AF2 pLDDT score, related to the model confidence, has been shown to provide a good measure of residue-wise disorder. Here, we combined AF2 predictions with pyHCA, a tool we previously developed to identify foldable segments and estimate their order/disorder ratio, from a single protein sequence. We focused our analysis on the AF2 predictions available for 21 reference proteomes (AFDB v1), in particular on their long foldable segments (&gt;30 amino acids) that exhibit characteristics of soluble domains, as estimated by pyHCA. Among these segments, we provided a global analysis of those with very low pLDDT values along their entire length and compared their characteristics to those of segments with very high pLDDT values. We highlighted cases containing conditional order, as well as cases that could form well-folded structures but escape the AF2 prediction due to a shallow multiple sequence alignment and/or undocumented structure or fold. AF2 and pyHCA can therefore be advantageously combined to unravel cryptic structural features in whole proteomes and to refine predictions for different flavors of disorder.

Heterologous expression of naturally evolved putative de novo proteins with chaperones

Over the past decade, evidence has accumulated that new protein-coding genes can emerge de novo from previously non-coding DNA. Most studies have focused on large scale computational predictions of de novo protein-coding genes across a wide range of organisms. In contrast, experimental data concerning the folding and function of de novo proteins are scarce. This might be due to difficulties in handling de novo proteins in vitro, as most are short and predicted to be disordered. Here, we propose a guideline for the effective expression of eukaryotic de novo proteins in Escherichia coli. We used 11 sequences from Drosophila melanogaster and 10 from Homo sapiens, that are predicted de novo proteins from former studies, for heterologous expression. The candidate de novo proteins have varying secondary structure and disorder content. Using multiple combinations of purification tags, E. coli expression strains, and chaperone systems, we were able to increase the number of solubly expressed putative de novo proteins from 30% to 62%. Our findings indicate that the best combination for expressing putative de novo proteins in E. coli is a GST-tag with T7 Express cells and co-expressed chaperones. We found that, overall, proteins with higher predicted disorder were easier to express. STATEMENT: Today, we know that proteins do not only evolve by duplication and divergence of existing proteins but also arise from previously non-coding DNA. These proteins are called de novo proteins. Their properties are still poorly understood and their experimental analysis faces major obstacles. Here, we aim to present a starting point for soluble expression of de novo proteins with the help of chaperones and thereby enable further characterization.

The early embryonic transcriptome of a Hawaiian Drosophila picture-wing fly shows evidence of altered gene expression and novel gene evolution

A massive adaptive radiation on the Hawaiian archipelago has produced approximately one-quarter of the fly species in the family Drosophilidae. The Hawaiian Drosophila clade has long been recognized as a model system for the study of both the ecology of island endemics and the evolution of developmental mechanisms, but relatively few genomic and transcriptomic datasets are available for this group. We present here a differential expression analysis of the transcriptional profiles of two highly conserved embryonic stages in the Hawaiian picture-wing fly Drosophila grimshawi. When we compared our results to previously published datasets across the family Drosophilidae, we identified cases of both gains and losses of gene representation in D. grimshawi, including an apparent delay in Hox gene activation. We also found a high expression of unannotated genes. Most transcripts of unannotated genes with open reading frames do not have identified homologs in non-Hawaiian Drosophila species, although the vast majority have sequence matches in genomes of other Hawaiian picture-wing flies. Some of these unannotated genes may have arisen from noncoding sequence in the ancestor of Hawaiian flies or during the evolution of the clade. Our results suggest that both the modified use of ancestral genes and the evolution of new ones may occur in rapid radiations.

Open reading frame dominance indicates protein‐coding potential of RNAs

Recent studies have identified numerous RNAs with both coding and noncoding functions. However, the sequence characteristics that determine this bifunctionality remain largely unknown. In the present study, we develop and test the open reading frame (ORF) dominance score, which we define as the fraction of the longest ORF in the sum of all putative ORF lengths. This score correlates with translation efficiency in coding transcripts and with translation of noncoding RNAs. In bacteria and archaea, coding and noncoding transcripts have narrow distributions of high and low ORF dominance, respectively, whereas those of eukaryotes show relatively broader ORF dominance distributions, with considerable overlap between coding and noncoding transcripts. The extent of overlap positively and negatively correlates with the mutation rate of genomes and the effective population size of species, respectively. Tissue‐specific transcripts show higher ORF dominance than ubiquitously expressed transcripts, and the majority of tissue‐specific transcripts are expressed in mature testes. These data suggest that the decrease in population size and the emergence of testes in eukaryotic organisms allowed for the evolution of potentially bifunctional RNAs.

Random peptides rich in small and disorder-promoting amino acids are less likely to be harmful

Proteins are the workhorses of the cell, yet they carry great potential for harm via misfolding and aggregation. Despite the dangers, proteins are sometimes born de novo from non-coding DNA. Proteins are more likely to be born from non-coding regions that produce peptides that do little to no harm when translated than from regions that produce harmful peptides. To investigate which newborn proteins are most likely to "first, do no harm", we estimate fitnesses from an experiment that competed Escherichia coli lineages that each expressed a unique random peptide. A variety of peptide metrics significantly predict lineage fitness, but this predictive power stems from simple amino acid frequencies rather than the ordering of amino acids. Amino acids that are smaller and that promote intrinsic structural disorder have more benign fitness effects. We validate that the amino acids that indicate benign effects in random peptides expressed in E. coli also do so in an independent dataset of random N-terminal tags in which it is possible to control for expression level. The same amino acids are also enriched in young animal proteins.

New Genomic Signals Underlying the Emergence of Human Proto-Genes

De novo genes are novel genes which emerge from non-coding DNA. Until now, little is known about de novo genes’ properties, correlated to their age and mechanisms of emergence. In this study, we investigate four related properties: introns, upstream regulatory motifs, 5′ Untranslated regions (UTRs) and protein domains, in 23,135 human proto-genes. We found that proto-genes contain introns, whose number and position correlates with the genomic position of proto-gene emergence. The origin of these introns is debated, as our results suggest that 41% of proto-genes might have captured existing introns, and 13.7% of them do not splice the ORF. We show that proto-genes which emerged via overprinting tend to be more enriched in core promotor motifs, while intergenic and intronic genes are more enriched in enhancers, even if the TATA motif is most commonly found upstream in these genes. Intergenic and intronic 5′ UTRs of proto-genes have a lower potential to stabilise mRNA structures than exonic proto-genes and established human genes. Finally, we confirm that proteins expressed by proto-genes gain new putative domains with age. Overall, we find that regulatory motifs inducing transcription and translation of previously non-coding sequences may facilitate proto-gene emergence. Our study demonstrates that introns, 5′ UTRs, and domains have specific properties in proto-genes. We also emphasize that the genomic positions of de novo genes strongly impacts these properties.

Overlapping genes in natural and engineered genomes

Modern genome-scale methods that identify new genes, such as proteogenomics and ribosome profiling, have revealed, to the surprise of many, that overlap in genes, open reading frames and even coding sequences is widespread and functionally integrated into prokaryotic, eukaryotic and viral genomes. In parallel, the constraints that overlapping regions place on genome sequences and their evolution can be harnessed in bioengineering to build more robust synthetic strains and constructs. With a focus on overlapping protein-coding and RNA-coding genes, this Review examines their discovery, topology and biogenesis in the context of their genome biology. We highlight exciting new uses for sequence overlap to control translation, compress synthetic genetic constructs, and protect against mutation.

Intergenic ORFs as elementary structural modules of de novo gene birth and protein evolution

The noncoding genome plays an important role in de novo gene birth and in the emergence of genetic novelty. Nevertheless, how noncoding sequences' properties could promote the birth of novel genes and shape the evolution and the structural diversity of proteins remains unclear. Therefore, by combining different bioinformatic approaches, we characterized the fold potential diversity of the amino acid sequences encoded by all intergenic open reading frames (ORFs) of S. cerevisiae with the aim of (1) exploring whether the structural states' diversity of proteomes is already present in noncoding sequences, and (2) estimating the potential of the noncoding genome to produce novel protein bricks that could either give rise to novel genes or be integrated into pre-existing proteins, thus participating in protein structure diversity and evolution. We showed that amino acid sequences encoded by most yeast intergenic ORFs contain the elementary building blocks of protein structures. Moreover, they encompass the large structural state diversity of canonical proteins, with the majority predicted as foldable. Then, we investigated the early stages of de novo gene birth by reconstructing the ancestral sequences of 70 yeast de novo genes and characterized the sequence and structural properties of intergenic ORFs with a strong translation signal. This enabled us to highlight sequence and structural factors determining de novo gene emergence. Finally, we showed a strong correlation between the fold potential of de novo proteins and one of their ancestral amino acid sequences, reflecting the relationship between the noncoding genome and the protein structure universe.

The Effects of Sequence Length and Composition of Random Sequence Peptides on the Growth of E. coli Cells

We study the potential for the de novo evolution of genes from random nucleotide sequences using libraries of E. coli expressing random sequence peptides. We assess the effects of such peptides on cell growth by monitoring frequency changes in individual clones in a complex library through four serial passages. Using a new analysis pipeline that allows the tracing of peptides of all lengths, we find that over half of the peptides have consistent effects on cell growth. Across nine different experiments, around 16% of clones increase in frequency and 36% decrease, with some variation between individual experiments. Shorter peptides (8-20 residues), are more likely to increase in frequency, longer ones are more likely to decrease. GC content, amino acid composition, intrinsic disorder, and aggregation propensity show slightly different patterns between peptide groups. Sequences that increase in frequency tend to be more disordered with lower aggregation propensity. This coincides with the observation that young genes with more disordered structures are better tolerated in genomes. Our data indicate that random sequences can be a source of evolutionary innovation, since a large fraction of them are well tolerated by the cells or can provide a growth advantage.

A vast pool of lineage-specific microproteins encoded by long non-coding RNAs in plants

Pervasive transcription of eukaryotic genomes results in expression of long non-coding RNAs (lncRNAs) most of which are poorly conserved in evolution and appear to be non-functional. However, some lncRNAs have been shown to perform specific functions, in particular, transcription regulation. Thousands of small open reading frames (smORFs, <100 codons) located on lncRNAs potentially might be translated into peptides or microproteins. We report a comprehensive analysis of the conservation and evolutionary trajectories of lncRNAs-smORFs from the moss Physcomitrium patens across transcriptomes of 479 plant species. Although thousands of smORFs are subject to substantial purifying selection, the majority of the smORFs appear to be evolutionary young and could represent a major pool for functional innovation. Using nanopore RNA sequencing, we show that, on average, the transcriptional level of conserved smORFs is higher than that of non-conserved smORFs. Proteomic analysis confirmed translation of 82 novel species-specific smORFs. Numerous conserved smORFs containing low complexity regions (LCRs) or transmembrane domains were identified, the biological functions of a selected LCR-smORF were demonstrated experimentally. Thus, microproteins encoded by smORFs are a major, functionally diverse component of the plant proteome.

orfipy: a fast and flexible tool for extracting ORFs

SUMMARY

Searching for open reading frames is a routine task and a critical step prior to annotating protein coding regions in newly sequenced genomes or de novo transcriptome assemblies. With the tremendous increase in genomic and transcriptomic data, faster tools are needed to handle large input datasets. These tools should be versatile enough to fine-tune search criteria and allow efficient downstream analysis. Here we present a new python based tool, orfipy, which allows the user to flexibly search for open reading frames in genomic and transcriptomic sequences. The search is rapid and is fully customizable, with a choice of FASTA and BED output formats.

AVAILABILITY AND IMPLEMENTATION

orfipy is implemented in python and is compatible with python v3.6 and higher. Source code: https://github.com/urmi-21/orfipy. Installation: from the source, or via PyPi (https://pypi.org/project/orfipy) or bioconda (https://anaconda.org/bioconda/orfipy).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

New Genes Interacted with Recent Whole Genome Duplicates in the Fast Stem Growth of Bamboos

As drivers of evolutionary innovations, new genes allow organisms to explore new niches. However, clear examples of this process remain scarce. Bamboos, the unique grass lineage diversifying into the forest, have evolved with a key innovation of fast growth of woody stem, reaching up to 1 m/day. Here, we identify 1,622 bamboo-specific orphan genes that appeared in recent 46 million years, and 19 of them evolved from noncoding ancestral sequences with entire de novo origination process reconstructed. The new genes evolved gradually in exon−intron structure, protein length, expression specificity, and evolutionary constraint. These new genes, whether or not from de novo origination, are dominantly expressed in the rapidly developing shoots, and make transcriptomes of shoots the youngest among various bamboo tissues, rather than reproductive tissue in other plants. Additionally, the particularity of bamboo shoots has also been shaped by recent whole-genome duplicates (WGDs), which evolved divergent expression patterns from ancestral states. New genes and WGDs have been evolutionarily recruited into coexpression networks to underline fast-growing trait of bamboo shoot. Our study highlights the importance of interactions between new genes and genome duplicates in generating morphological innovation.

A putative de novo evolved gene required for spermatid chromatin condensation in Drosophila melanogaster

Comparative genomics has enabled the identification of genes that potentially evolved de novo from non-coding sequences. Many such genes are expressed in male reproductive tissues, but their functions remain poorly understood. To address this, we conducted a functional genetic screen of over 40 putative de novo genes with testis-enriched expression in Drosophila melanogaster and identified one gene, atlas, required for male fertility. Detailed genetic and cytological analyses showed that atlas is required for proper chromatin condensation during the final stages of spermatogenesis. Atlas protein is expressed in spermatid nuclei and facilitates the transition from histone- to protamine-based chromatin packaging. Complementary evolutionary analyses revealed the complex evolutionary history of atlas. The protein-coding portion of the gene likely arose at the base of the Drosophila genus on the X chromosome but was unlikely to be essential, as it was then lost in several independent lineages. Within the last ~15 million years, however, the gene moved to an autosome, where it fused with a conserved non-coding RNA and evolved a non-redundant role in male fertility. Altogether, this study provides insight into the integration of novel genes into biological processes, the links between genomic innovation and functional evolution, and the genetic control of a fundamental developmental process, gametogenesis.

Structure and function of naturally evolved de novo proteins

Comparative evolutionary genomics has revealed that novel protein coding genes can emerge randomly from non-coding DNA. While most of the myriad of transcripts which continuously emerge vanish rapidly, some attain regulatory regions, become translated and survive. More surprisingly, sequence properties of de novo proteins are almost indistinguishable from randomly obtained sequences, yet de novo proteins may gain functions and integrate into eukaryotic cellular networks quite easily. We here discuss current knowledge on de novo proteins, their structures, functions and evolution. Since the existence of de novo proteins seems at odds with decade-long attempts to construct proteins with novel structures and functions from scratch, we suggest that a better understanding of de novo protein evolution may fuel new strategies for protein design.

Stochastic Gain and Loss of Novel Transcribed Open Reading Frames in the Human Lineage

In addition to known genes, much of the human genome is transcribed into RNA. Chance formation of novel open reading frames (ORFs) can lead to the translation of myriad new proteins. Some of these ORFs may yield advantageous adaptive de novo proteins. However, widespread translation of noncoding DNA can also produce hazardous protein molecules, which can misfold and/or form toxic aggregates. The dynamics of how de novo proteins emerge from potentially toxic raw materials and what influences their long-term survival are unknown. Here, using transcriptomic data from human and five other primates, we generate a set of transcribed human ORFs at six conservation levels to investigate which properties influence the early emergence and long-term retention of these expressed ORFs. As these taxa diverged from each other relatively recently, we present a fine scale view of the evolution of novel sequences over recent evolutionary time. We find that novel human-restricted ORFs are preferentially located on GC-rich gene-dense chromosomes, suggesting their retention is linked to pre-existing genes. Sequence properties such as intrinsic structural disorder and aggregation propensity-which have been proposed to play a role in survival of de novo genes-remain unchanged over time. Even very young sequences code for proteins with low aggregation propensities, suggesting that genomic regions with many novel transcribed ORFs are concomitantly less likely to produce ORFs which code for harmful toxic proteins. Our data indicate that the survival of these novel ORFs is largely stochastic rather than shaped by selection.

Only a Single Taxonomically Restricted Gene Family in the Drosophila melanogaster Subgroup Can Be Identified with High Confidence

Taxonomically restricted genes (TRGs) are genes that are present only in one clade. Protein-coding TRGs may evolve de novo from previously noncoding sequences: functional ncRNA, introns, or alternative reading frames of older protein-coding genes, or intergenic sequences. A major challenge in studying de novo genes is the need to avoid both false-positives (nonfunctional open reading frames and/or functional genes that did not arise de novo) and false-negatives. Here, we search conservatively for high-confidence TRGs as the most promising candidates for experimental studies, ensuring functionality through conservation across at least two species, and ensuring de novo status through examination of homologous noncoding sequences. Our pipeline also avoids ascertainment biases associated with preconceptions of how de novo genes are born. We identify one TRG family that evolved de novo in the Drosophila melanogaster subgroup. This TRG family contains single-copy genes in Drosophila simulans and Drosophila sechellia. It originated in an intron of a well-established gene, sharing that intron with another well-established gene upstream. These TRGs contain an intron that predates their open reading frame. These genes have not been previously reported as de novo originated, and to our knowledge, they are the best Drosophila candidates identified so far for experimental studies aimed at elucidating the properties of de novo genes.