A de novo originated gene depresses budding yeast mating pathway and is repressed by the protein encoded by its antisense strand

Evolutionarily new genes in humans with disease phenotypes reveal functional enrichment patterns shaped by adaptive innovation and sexual selection

New genes (or young genes) are genetic novelties pivotal in mammalian evolution. However, their phenotypic impacts and evolutionary patterns over time remain elusive in humans due to the technical and ethical complexities of functional studies. Integrating gene age dating with Mendelian disease phenotyping, our research shows a gradual rise in disease gene proportion as gene age increases. Logistic regression modeling indicates that this increase in older genes may be related to their longer sequence lengths and higher burdens of deleterious de novo germline variants (DNVs). We also find a steady integration of new genes with biomedical phenotypes into the human genome over macroevolutionary timescales (~0.07% per million years). Despite this stable pace, we observe distinct patterns in phenotypic enrichment, pleiotropy, and selective pressures across gene ages. Notably, young genes show significant enrichment in diseases related to the male reproductive system, indicating strong sexual selection. Young genes also exhibit disease-related functions in tissues and systems potentially linked to human phenotypic innovations, such as increased brain size, musculoskeletal phenotypes, and color vision. We further reveal a logistic growth pattern of pleiotropy over evolutionary time, indicating a diminishing marginal growth of new functions for older genes due to intensifying selective constraints over time. We propose a pleiotropy-barrier model that delineates higher potentials for phenotypic innovation in young genes compared to older genes, a process that is subject to natural selection. Our study demonstrates that evolutionarily new genes are critical in influencing human reproductive evolution and adaptive phenotypic innovations driven by sexual and natural selection, with low pleiotropy as a selective advantage.

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.

Massively integrated coexpression analysis reveals transcriptional regulation, evolution and cellular implications of the yeast noncanonical translatome

BACKGROUND

Recent 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.

RESULTS

Our 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.

CONCLUSIONS

Our 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.

ifDEEPre: large protein language-based deep learning enables interpretable and fast predictions of enzyme commission numbers

Accurate understanding of the biological functions of enzymes is vital for various tasks in both pathologies and industrial biotechnology. However, the existing methods are usually not fast enough and lack explanations on the prediction results, which severely limits their real-world applications. Following our previous work, DEEPre, we propose a new interpretable and fast version (ifDEEPre) by designing novel self-guided attention and incorporating biological knowledge learned via large protein language models to accurately predict the commission numbers of enzymes and confirm their functions. Novel self-guided attention is designed to optimize the unique contributions of representations, automatically detecting key protein motifs to provide meaningful interpretations. Representations learned from raw protein sequences are strictly screened to improve the running speed of the framework, 50 times faster than DEEPre while requiring 12.89 times smaller storage space. Large language modules are incorporated to learn physical properties from hundreds of millions of proteins, extending biological knowledge of the whole network. Extensive experiments indicate that ifDEEPre outperforms all the current methods, achieving more than 14.22% larger F1-score on the NEW dataset. Furthermore, the trained ifDEEPre models accurately capture multi-level protein biological patterns and infer evolutionary trends of enzymes by taking only raw sequences without label information. Meanwhile, ifDEEPre predicts the evolutionary relationships between different yeast sub-species, which are highly consistent with the ground truth. Case studies indicate that ifDEEPre can detect key amino acid motifs, which have important implications for designing novel enzymes. A web server running ifDEEPre is available at https://proj.cse.cuhk.edu.hk/aihlab/ifdeepre/ to provide convenient services to the public. Meanwhile, ifDEEPre is freely available on GitHub at https://github.com/ml4bio/ifDEEPre/.

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.

Biological factors and statistical limitations prevent detection of most noncanonical proteins by mass spectrometry

Ribosome profiling experiments indicate pervasive translation of short open reading frames (ORFs) outside of annotated protein-coding genes. However, shotgun mass spectrometry (MS) 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 MS 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 MS 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 4 noncanonical proteins in MS data, which were also supported by evolution and translation data. These results illustrate the power of MS to validate unannotated genes predicted by ribosome profiling, but also its substantial limitations in finding many biologically relevant lowly expressed proteins.

Evolutionarily new genes in humans with disease phenotypes reveal functional enrichment patterns shaped by adaptive innovation and sexual selection

New genes (or young genes) are structural novelties pivotal in mammalian evolution. Their phenotypic impact on humans, however, remains elusive due to the technical and ethical complexities in functional studies. Through combining gene age dating with Mendelian disease phenotyping, our research reveals that new genes associated with disease phenotypes steadily integrate into the human genome at a rate of ~ 0.07% every million years over macroevolutionary timescales. Despite this stable pace, we observe distinct patterns in phenotypic enrichment, pleiotropy, and selective pressures between young and old genes. Notably, young genes show significant enrichment in the male reproductive system, indicating strong sexual selection. Young genes also exhibit functions in tissues and systems potentially linked to human phenotypic innovations, such as increased brain size, bipedal locomotion, and color vision. Our findings further reveal increasing levels of pleiotropy over evolutionary time, which accompanies stronger selective constraints. We propose a "pleiotropy-barrier" model that delineates different potentials for phenotypic innovation between young and older genes subject to natural selection. Our study demonstrates that evolutionary new genes are critical in influencing human reproductive evolution and adaptive phenotypic innovations driven by sexual and natural selection, with low pleiotropy as a selective advantage.

Biological Factors and Statistical Limitations Prevent Detection of Most Noncanonical Proteins by Mass Spectrometry

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.

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.

Discovery of long non-coding RNAs in Aspergillus flavus response to water activity, CO2 concentration, and temperature changes

Although the role of long non-coding RNAs (lncRNAs) in key biological processes in animals and plants has been confirmed for decades, their identification in fungi remains limited. In this study, we discovered and characterized lncRNAs in Aspergillus flavus in response to changes in water activity, CO₂ concentration, and temperature, and predicted their regulatory roles in cellular functions. A total of 472 lncRNAs were identified in the genome of A. flavus, consisting of 470 novel lncRNAs and 2 putative lncRNAs (EFT00053849670 and EFT00053849665). Our analysis of lncRNA expression revealed significant differential expression under stress conditions in A. flavus. Our findings indicate that lncRNAs in A. flavus, particularly down-regulated lncRNAs, may play pivotal regulatory roles in aflatoxin biosynthesis, respiratory activities, cellular survival, and metabolic maintenance under stress conditions. Additionally, we predicted that sense lncRNAs down-regulated by a temperature of 30 °C, osmotic stress, and CO₂ concentration might indirectly regulate proline metabolism. Furthermore, subcellular localization analysis revealed that up-and down-regulated lncRNAs are frequently localized in the nucleus under stress conditions, particularly at a water activity of 0.91, while most up-regulated lncRNAs may be located in the cytoplasm under high CO₂ concentration.

The Lost and Found: Unraveling the Functions of Orphan Genes

Orphan Genes (OGs) are a mysterious class of genes that have recently gained significant attention. Despite lacking a clear evolutionary history, they are found in nearly all living organisms, from bacteria to humans, and they play important roles in diverse biological processes. The discovery of OGs was first made through comparative genomics followed by the identification of unique genes across different species. OGs tend to be more prevalent in species with larger genomes, such as plants and animals, and their evolutionary origins remain unclear but potentially arise from gene duplication, horizontal gene transfer (HGT), or de novo origination. Although their precise function is not well understood, OGs have been implicated in crucial biological processes such as development, metabolism, and stress responses. To better understand their significance, researchers are using a variety of approaches, including transcriptomics, functional genomics, and molecular biology. This review offers a comprehensive overview of the current knowledge of OGs in all domains of life, highlighting the possible role of dark transcriptomics in their evolution. More research is needed to fully comprehend the role of OGs in biology and their impact on various biological processes.

A vast evolutionarily transient translatome contributes to phenotype and fitness

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. 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.

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.

Systematic genetic modifications of cell wall biosynthesis enhanced the secretion and surface-display of polysaccharide degrading enzymes in Saccharomyces cerevisiae

Saccharomyces cerevisiae is a robust cell factory to secrete or surface-display cellulase and amylase for the conversion of agricultural residues into valuable chemicals. Engineering the secretory pathway is a well-known strategy for overproducing these enzymes. Although cell wall biosynthesis can be tightly linked to the secretory pathway by regulation of all involved processes, the effect of its modifications on protein production has not been extensively studied. In this study, we systematically studied the effect of engineering cell wall biosynthesis on the activity of cellulolytic enzyme β-glucosidase (BGL1) by comparing seventy-nine gene knockout S. cerevisiae strains and newly identified that inactivation of DFG5, YPK1, FYV5, CCW12 and KRE1 obviously improved BGL1 secretion and surface-display. Combinatorial modifications of these genes, particularly double deletion of FVY5 and CCW12, along with the use of rich medium, increased the activity of secreted and surface-displayed BGL1 by 6.13-fold and 7.99-fold, respectively. Additionally, we applied this strategy to improve the activity of the cellulolytic cellobiohydrolase and amylolytic α-amylase. Through proteomic analysis coupled with reverse engineering, we found that in addition to the secretory pathway, regulation of translation processes may also involve in improving enzyme activity by engineering cell wall biosynthesis. Our work provides new insight into the construction of a yeast cell factory for efficient production of polysaccharide degrading enzymes.

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.

Origins, evolution, and physiological implications of de novo genes in yeast

De novo gene birth is the process by which new genes emerge in sequences that were previously noncoding. Over the past decade, researchers have taken advantage of the power of yeast as a model and a tool to study the evolutionary mechanisms and physiological implications of de novo gene birth. We summarize the mechanisms that have been proposed to explicate how noncoding sequences can become protein-coding genes, highlighting the discovery of pervasive translation of the yeast transcriptome and its presumed impact on evolutionary innovation. We summarize current best practices for the identification and characterization of de novo genes. Crucially, we explain that the field is still in its nascency, with the physiological roles of most young yeast de novo genes identified thus far still utterly unknown. We hope this review inspires researchers to investigate the true contribution of de novo gene birth to cellular physiology and phenotypic diversity across yeast strains and species.

The Origins and Functions of De Novo Genes: Against All Odds?

"De novo" genes evolve from previously non-genic DNA. This strikes many of us as remarkable, because it seems extraordinarily unlikely that random sequence would produce a functional gene. How is this possible? In this two-part review, I first summarize what is known about the origins and molecular functions of the small number of de novo genes for which such information is available. I then speculate on what these examples may tell us about how de novo genes manage to emerge despite what seem like enormous opposing odds.

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.

AtQQS orphan gene and NtNF-YC4 boost protein accumulation and pest resistance in tobacco (Nicotiana tabacum)

Qua-Quine Starch (QQS), an orphan gene exclusively found in Arabidopsis thaliana, interacts with Nuclear Factor Y subunit C4 (NF-YC4) and regulates carbon and nitrogen allocation in different plant species. Several studies uncovered its potential in increasing total protein and resistance against pathogens/pests in Arabidopsis and soybean. However, it is still unclear if these attributes QQS offers are universal in all flowering plants. Here we studied AtQQS and Nicotiana tabacum NF-YC4's (NtNF-YC4) influence on starch/protein content and pest resistance in tobacco. Our results showed both AtQQS and NtNF-YC4 had a positive impact on the plant's total protein accumulation. Simultaneously, we have also observed reduced starch biosynthesis and increased resistance against common pests like whiteflies (Bemisia tabaci) and aphids (Myzus persicae) in tobacco plants expressing AtQQS or overexpressing NtNF-YC4. Real-time PCR also revealed increased NF-YC4 expression after aphid infestation in tobacco varieties with higher pest resistance but decreased/unchanged NF-YC4 expression in varieties susceptible to pests. Further analysis revealed that QQS expression and overexpression of NtNF-YC4 strongly repressed expression of genes such as sugar transporter SWEET10 and Flowering Locus T (FT), suggesting involvement of SWEET10 and FT in the QQS and NF-YC4 mediated carbon and nitrogen allocation in tobacco. Our data suggested that the activity of species-specific orphan genes may not be limited to the original species or its close relatives. Sequence alignment revealed the conserved sequence of the NF-YC4s in different plant species that may be responsible for the resulting shift in metabolism, pest resistance. Cis-acting DNA element analysis of NtNF-YC4 promoter region may outline potential mechanisms for these phenotypic changes.

Identification of a novel gene required for competitive growth at high temperature in the thermotolerant yeast Kluyveromyces marxianus

It is important to understand the basis of thermotolerance in yeasts to broaden their application in industrial biotechnology. The capacity to run bioprocesses at temperatures above 40 °C is of great interest but this is beyond the growth range of most of the commonly used yeast species. In contrast, some industrial yeasts such as Kluyveromyces marxianus can grow at temperatures of 45 °C or higher. Such species are valuable for direct use in industrial biotechnology and as a vehicle to study the genetic and physiological basis of yeast thermotolerance. In previous work, we reported that evolutionarily young genes disproportionately changed expression when yeast were growing under stressful conditions and postulated that such genes could be important for long-term adaptation to stress. Here, we tested this hypothesis in K. marxianus by identifying and studying species-specific genes that showed increased expression during high-temperature growth. Twelve such genes were identified and 11 were successfully inactivated using CRISPR-mediated mutagenesis. One gene, KLMX_70384, is required for competitive growth at high temperature, supporting the hypothesis that evolutionary young genes could play roles in adaptation to harsh environments. KLMX_70384 is predicted to encode an 83 aa peptide, and RNA sequencing and ribo-sequencing were used to confirm transcription and translation of the gene. The precise function of KLMX_70384 remains unknown but some features are suggestive of RNA-binding activity. The gene is located in what was previously considered an intergenic region of the genome, which lacks homologues in other yeasts or in databases. Overall, the data support the hypothesis that genes that arose de novo in K. marxianus after the speciation event that separated K. marxianus and K. lactis contribute to some of its unique traits.

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.

Population biology of accessory gland-expressed de novo genes in Drosophila melanogaster

Early work on de novo gene discovery in Drosophila was consistent with the idea that many such genes have male-biased patterns of expression, including a large number expressed in the testis. However, there has been little formal analysis of variation in the abundance and properties of de novo genes expressed in different tissues. Here, we investigate the population biology of recently evolved de novo genes expressed in the Drosophila melanogaster accessory gland, a somatic male tissue that plays an important role in male and female fertility and the post mating response of females, using the same collection of inbred lines used previously to identify testis-expressed de novo genes, thus allowing for direct cross tissue comparisons of these genes in two tissues of male reproduction. Using RNA-seq data, we identify candidate de novo genes located in annotated intergenic and intronic sequence and determine the properties of these genes including chromosomal location, expression, abundance, and coding capacity. Generally, we find major differences between the tissues in terms of gene abundance and expression, though other properties such as transcript length and chromosomal distribution are more similar. We also explore differences between regulatory mechanisms of de novo genes in the two tissues and how such differences may interact with selection to produce differences in D. melanogaster de novo genes expressed in the two tissues.

Foster thy young: enhanced prediction of orphan genes in assembled genomes

Proteins encoded by newly-emerged genes ('orphan genes') share no sequence similarity with proteins in any other species. They provide organisms with a reservoir of genetic elements to quickly respond to changing selection pressures. Here, we systematically assess the ability of five gene prediction pipelines to accurately predict genes in genomes according to phylostratal origin. BRAKER and MAKER are existing, popular ab initio tools that infer gene structures by machine learning. Direct Inference is an evidence-based pipeline we developed to predict gene structures from alignments of RNA-Seq data. The BIND pipeline integrates ab initio predictions of BRAKER and Direct inference; MIND combines Direct Inference and MAKER predictions. We use highly-curated Arabidopsis and yeast annotations as gold-standard benchmarks, and cross-validate in rice. Each pipeline under-predicts orphan genes (as few as 11 percent, under one prediction scenario). Increasing RNA-Seq diversity greatly improves prediction efficacy. The combined methods (BIND and MIND) yield best predictions overall, BIND identifying 68% of annotated orphan genes, 99% of ancient genes, and give the highest sensitivity score regardless dataset in Arabidopsis. We provide a light weight, flexible, reproducible, and well-documented solution to improve gene prediction.

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.

An Overview on Identification and Regulatory Mechanisms of Long Non-coding RNAs in Fungi

For decades, more and more long non-coding RNAs (lncRNAs) have been confirmed to play important functions in key biological processes of different organisms. At present, most identified lncRNAs and those with known functional roles are from mammalian systems. However, lncRNAs have also been found in primitive eukaryotic fungi, and they have different functions in fungal development, metabolism, and pathogenicity. In this review, we highlight some recent researches on lncRNAs in the primitive eukaryotic fungi, particularly focusing on the identification of lncRNAs and their regulatory roles in diverse biological processes.

Uncovering de novo gene birth in yeast using deep transcriptomics

De novo gene origination has been recently established as an important mechanism for the formation of new genes. In organisms with a large genome, intergenic and intronic regions provide plenty of raw material for new transcriptional events to occur, but little is know about how de novo transcripts originate in more densely-packed genomes. Here, we identify 213 de novo originated transcripts in Saccharomyces cerevisiae using deep transcriptomics and genomic synteny information from multiple yeast species grown in two different conditions. We find that about half of the de novo transcripts are expressed from regions which already harbor other genes in the opposite orientation; these transcripts show similar expression changes in response to stress as their overlapping counterparts, and some appear to translate small proteins. Thus, a large fraction of de novo genes in yeast are likely to co-evolve with already existing genes.

The new chimeric chiron genes evolved essential roles in zebrafish embryonic development by regulating NAD+ levels

The origination of new genes is important for generating genetic novelties for adaptive evolution and biological diversity. However, their potential roles in embryonic development, evolutionary processes into ancient networks, and contributions to adaptive evolution remain poorly investigated. Here, we identified a novel chimeric gene family, the chiron family, and explored its genetic basis and functional evolution underlying the adaptive evolution of Danioninae fishes. The ancestral chiron gene originated through retroposition of nampt in Danioninae 48-54 million years ago (Mya) and expanded into five duplicates (chiron1-5) in zebrafish 1-4 Mya. The chiron genes (chirons) likely originated in embryonic development and gradually extended their expression in the testis. Functional experiments showed that chirons were essential for zebrafish embryo development. By integrating into the NAD⁺ synthesis pathway, chirons could directly catalyze the NAD⁺ rate-limiting reaction and probably impact two energy metabolism genes (nmnat1 and naprt) to be under positive selection in Danioninae fishes. Together, these results mainly demonstrated that the origin of new chimeric chiron genes may be involved in adaptive evolution by integrating and impacting the NAD⁺ biosynthetic pathway. This coevolution may contribute to the physiological adaptation of Danioninae fishes to widespread and varied biomes in Southeast Asian.

Evolution of new proteins from translated sORFs in long non-coding RNAs

High throughput RNA sequencing techniques have revealed that a large fraction of the genome is transcribed into long non-coding RNAs (lncRNAs). Unlike canonical protein-coding genes, lncRNAs do not contain long open reading frames (ORFs) and tend to be poorly conserved across species. However, many of them contain small ORFs (sORFs) that exhibit translation signatures according to ribosome profiling or proteomics data. These sORFs are a source of putative novel proteins; some of them may confer a selective advantage and be maintained over time, a process known as de novo gene birth. Here we review the mechanisms by which randomly occurring sORFs in lncRNAs can become new functional proteins.

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

Recent evidence demonstrates that novel protein-coding genes can arise de novo from non-genic loci. This evolutionary innovation is thought to be facilitated by the pervasive translation of non-genic transcripts, which exposes a reservoir of variable polypeptides to natural selection. Here, we systematically characterize how these de novo emerging coding sequences impact fitness in budding yeast. Disruption of emerging sequences is generally inconsequential for fitness in the laboratory and in natural populations. Overexpression of emerging sequences, however, is enriched in adaptive fitness effects compared to overexpression of established genes. We find that adaptive emerging sequences tend to encode putative transmembrane domains, and that thymine-rich intergenic regions harbor a widespread potential to produce transmembrane domains. These findings, together with in-depth examination of the de novo emerging YBR196C-A locus, suggest a novel evolutionary model whereby adaptive transmembrane polypeptides emerge de novo from thymine-rich non-genic regions and subsequently accumulate changes molded by natural selection.

There is increasing evidence that protein-coding genes can emerge de novo from noncoding genomic regions. Vakirlis et al. propose that sequences encoding transmembrane polypeptides can emerge de novo in thymine-rich genomic regions and provide organisms with fitness benefits.

Two young genes reshape a novel interaction network in Brassica napus

New genes often drive the evolution of gene interaction networks. In Brassica napus, the widely used genic male sterile breeding system 7365ABC is controlled by two young genes, Bnams4^b and BnaMs3. However, the interaction mechanism of these two young genes remains unclear. Here, we confirmed that Bnams4^b interacts with the nuclear localised E3 ligase BRUTUS (BTS). Ectopic expression of AtBRUTUS (AtBTS) and comparison between Bnams4^b -transgenic Arabidopsis and bts mutants suggested that Bnams4^b may drive translocation of BTS to cause various toxic defects. BnaMs3 gained an exclusive interaction with the plastid outer-membrane translocon Toc33 compared with Bnams3 and AtTic40, and specifically compensated for the toxic effects of Bnams4^b . Heat shock treatment also rescued the sterile phenotype, and high temperature suppressed the interaction between Bnams4^b and BTS in yeast. Furthermore, the ubiquitin system and TOC (translocon at the outer envelope membrane of chloroplasts) component accumulation were affected in Bnams4^b -transgenic Arabidopsis plants. Taken together, these results indicate that new chimeric Bnams4^b carries BTS from nucleus to chloroplast, which may disrupt the normal ubiquitin-proteasome system to cause toxic effects, and these defects can be compensated by BnaMs3-Toc33 interaction or environmental heat shock. It reveals a scenario in which two population-specific coevolved young genes reshape a novel interaction network in plants.

Evolution of Plant Architecture in Oryza Driven by the PROG1 Locus

The genetic control of plant architecture in crops is critical for agriculture and understanding morphological evolution. This study showed that an open reading frame (ORF) of the rice domestication gene PROG1 appeared 3.4-3.9 million years ago (Mya). Subsequently, it acquired a novel protein-coding gene function in the genome of O. rufipogon (~0.3-0.4 Mya). This extremely young gene and its paralogous C2H2 genes located nearby define the prostrate architecture of O. rufipogon and, thus, are of adaptive significance for wild rice in swamp and water areas. However, selection for dense planting and high yield during rice domestication silenced the PROG1 gene and caused the loss of the RPAD locus containing functional C2H2 paralogs; hence, domesticated lines exhibit an erect plant architecture. Analysis of the stepwise origination process of PROG1 and its evolutionary genetics revealed that this zinc-finger coding gene may have rapidly evolved under positive selection and promoted the transition from non- or semi-prostrate growth to prostrate growth. A transgenic assay showed that PROG1 from O. rufipogon exerts a stronger function compared with PROG1 sequences from other Oryza species. However, the analysis of the expression levels of PROG1 in different Oryza species suggests that the transcriptional regulation of PROG1 has played an important role in its evolution. This study provides the first strong case showing how a fundamental morphological trait evolved in Oryza species driven by a gene locus.

A de novo evolved gene in the house mouse regulates female pregnancy cycles

The de novo emergence of new genes has been well documented through genomic analyses. However, a functional analysis, especially of very young protein-coding genes, is still largely lacking. Here, we identify a set of house mouse-specific protein-coding genes and assess their translation by ribosome profiling and mass spectrometry data. We functionally analyze one of them, Gm13030, which is specifically expressed in females in the oviduct. The interruption of the reading frame affects the transcriptional network in the oviducts at a specific stage of the estrous cycle. This includes the upregulation of Dcpp genes, which are known to stimulate the growth of preimplantation embryos. As a consequence, knockout females have their second litters after shorter times and have a higher infanticide rate. Given that Gm13030 shows no signs of positive selection, our findings support the hypothesis that a de novo evolved gene can directly adopt a function without much sequence adaptation.

Different species have specific genes that set them apart from other species. Yet exactly how these species-specific genes originate is not fully known. The traditional view is that existing old genes are duplicated to make a ‘spare’ copy, which can change through mutations into a new gene with a new role gradually over time. Despite there being lots of evidence supporting this theory, not all new genes found in recent years can be traced back to older genes. This led to an alternative view – that recently evolved genes can also appear ‘de novo’, and come from regions of random DNA sequences that did not previously code for a protein.

So far, the possibility of genes forming de novo during evolution has largely been supported by comparing and analyzing the genomes of related species. However, very little is known about the biological role these de novo genes play. Now, Xie et al. have generated a list of recently evolved de novo mouse genes, and carried out a detailed analysis of one de novo gene expressed in females at the time when embryos implant into the uterus wall.

To study the role of this gene, Xie et al. created a strain of knock-out mice that have a defunct version of the protein coded by the gene. Loss of this protein caused female mice to have their second litter after a shorter period of time and increased the likelihood that female mice would terminate their newborn pups. This suggests that this newly discovered de novo gene is involved in regulating the female reproductive cycles of mice.

Further analysis showed that this de novo gene counteracts the action of an older gene that promotes the implantation of embryos. This gene has therefore likely evolved due to the benefit it offers mothers, as it protects them from experiencing the increased physiological stress caused by a premature second pregnancy.

These findings support the idea that genes which have evolved de novo can have an essential biological purpose despite coming from random DNA sequences. This establishes that de novo evolution of genes is the second major mechanism of how new genes with significant biological roles can form in the genome.

De Novo Emergence of Peptides That Confer Antibiotic Resistance

The origin of novel genes and beneficial functions is of fundamental interest in evolutionary biology. New genes can originate from different mechanisms, including horizontal gene transfer, duplication-divergence, and de novo from noncoding DNA sequences. Comparative genomics has generated strong evidence for de novo emergence of genes in various organisms, but experimental demonstration of this process has been limited to localized randomization in preexisting structural scaffolds. This bypasses the basic requirement of de novo gene emergence, i.e., lack of an ancestral gene. We constructed highly diverse plasmid libraries encoding randomly generated open reading frames and expressed them in Escherichia coli to identify short peptides that could confer a beneficial and selectable phenotype in vivo (in a living cell). Selections on antibiotic-containing agar plates resulted in the identification of three peptides that increased aminoglycoside resistance up to 48-fold. Combining genetic and functional analyses, we show that the peptides are highly hydrophobic, and by inserting into the membrane, they reduce membrane potential, decrease aminoglycoside uptake, and thereby confer high-level resistance. This study demonstrates that randomized DNA sequences can encode peptides that confer selective benefits and illustrates how expression of random sequences could spark the origination of new genes. In addition, our results also show that this question can be addressed experimentally by expression of highly diverse sequence libraries and subsequent selection for specific functions, such as resistance to toxic compounds, the ability to rescue auxotrophic/temperature-sensitive mutants, and growth on normally nonused carbon sources, allowing the exploration of many different phenotypes.IMPORTANCE De novo gene origination from nonfunctional DNA sequences was long assumed to be implausible. However, recent studies have shown that large fractions of genomic noncoding DNA are transcribed and translated, potentially generating new genes. Experimental validation of this process so far has been limited to comparative genomics, in vitro selections, or partial randomizations. Here, we describe selection of novel peptides in vivo using fully random synthetic expression libraries. The peptides confer aminoglycoside resistance by inserting into the bacterial membrane and thereby partly reducing membrane potential and decreasing drug uptake. Our results show that beneficial peptides can be selected from random sequence pools in vivo and support the idea that expression of noncoding sequences could spark the origination of new genes.

A Molecular Portrait of De Novo Genes in Yeasts

New genes, with novel protein functions, can evolve "from scratch" out of intergenic sequences. These de novo genes can integrate the cell's genetic network and drive important phenotypic innovations. Therefore, identifying de novo genes and understanding how the transition from noncoding to coding occurs are key problems in evolutionary biology. However, identifying de novo genes is a difficult task, hampered by the presence of remote homologs, fast evolving sequences and erroneously annotated protein coding genes. To overcome these limitations, we developed a procedure that handles the usual pitfalls in de novo gene identification and predicted the emergence of 703 de novo gene candidates in 15 yeast species from 2 genera whose phylogeny spans at least 100 million years of evolution. We validated 85 candidates by proteomic data, providing new translation evidence for 25 of them through mass spectrometry experiments. We also unambiguously identified the mutations that enabled the transition from noncoding to coding for 30 Saccharomyces de novo genes. We established that de novo gene origination is a widespread phenomenon in yeasts, only a few being ultimately maintained by selection. We also found that de novo genes preferentially emerge next to divergent promoters in GC-rich intergenic regions where the probability of finding a fortuitous and transcribed ORF is the highest. Finally, we found a more than 3-fold enrichment of de novo genes at recombination hot spots, which are GC-rich and nucleosome-free regions, suggesting that meiotic recombination contributes to de novo gene emergence in yeasts.

Computational Prediction of De Novo Emerged Protein-Coding Genes

De novo genes, that is, protein-coding genes originating from previously noncoding sequence, have gone from being considered impossibly unlikely to being recognized as an important source of genetic novelty in eukaryotic genomes. It is clear that de novo gene evolution is a rare but consistent feature of eukaryotic genomes, being detected in every genome studied. However, different studies often use different computational methods, and the numbers and identities of the detected genes vary greatly. Here we present a coherent protocol for the computational identification of de novo genes by comparative genomics. The method described uses homology searches, identification of syntenic regions, and ancestral sequence reconstruction to produce high-confidence candidates with robust evidence of de novo emergence. It is designed to be easily applicable given the basic knowledge of bioinformatic tools and scalable so that it can be applied on large and small datasets.

Translation of Small Open Reading Frames: Roles in Regulation and Evolutionary Innovation

The translatome can be defined as the sum of the RNA sequences that are translated into proteins in the cell by the ribosomal machinery. Until recently, it was generally assumed that the translatome was essentially restricted to evolutionary conserved proteins encoded by the set of annotated protein-coding genes. However, it has become increasingly clear that it also includes small regulatory open reading frames (ORFs), functional micropeptides, de novo proteins, and the pervasive translation of likely nonfunctional proteins. Many of these ORFs have been discovered thanks to the development of ribosome profiling, a technique to sequence ribosome-protected RNA fragments. To fully capture the diversity of translated ORFs, we propose a comprehensive classification that includes the new types of translated ORFs in addition to standard proteins.

Exaptation at the molecular genetic level

The realization that body parts of animals and plants can be recruited or coopted for novel functions dates back to, or even predates the observations of Darwin. S.J. Gould and E.S. Vrba recognized a mode of evolution of characters that differs from adaptation. The umbrella term aptation was supplemented with the concept of exaptation. Unlike adaptations, which are restricted to features built by selection for their current role, exaptations are features that currently enhance fitness, even though their present role was not a result of natural selection. Exaptations can also arise from nonaptations; these are characters which had previously been evolving neutrally. All nonaptations are potential exaptations. The concept of exaptation was expanded to the molecular genetic level which aided greatly in understanding the enormous potential of neutrally evolving repetitive DNA-including transposed elements, formerly considered junk DNA-for the evolution of genes and genomes. The distinction between adaptations and exaptations is outlined in this review and examples are given. Also elaborated on is the fact that such distinctions are sometimes more difficult to determine; this is a widespread phenomenon in biology, where continua abound and clear borders between states and definitions are rare.

A Comprehensive Analysis of Transcript-Supported De Novo Genes in Saccharomyces sensu stricto Yeasts

Novel genes arising from random DNA sequences (de novo genes) have been suggested to be widespread in the genomes of different organisms. However, our knowledge about the origin and evolution of de novo genes is still limited. To systematically understand the general features of de novo genes, we established a robust pipeline to analyze >20,000 transcript-supported coding sequences (CDSs) from the budding yeast Saccharomyces cerevisiae. Our analysis pipeline combined phylogeny, synteny, and sequence alignment information to identify possible orthologs across 20 Saccharomycetaceae yeasts and discovered 4,340 S. cerevisiae-specific de novo genes and 8,871 S. sensu stricto-specific de novo genes. We further combine information on CDS positions and transcript structures to show that >65% of de novo genes arose from transcript isoforms of ancient genes, especially in the upstream and internal regions of ancient genes. Fourteen identified de novo genes with high transcript levels were chosen to verify their protein expressions. Ten of them, including eight transcript isoform-associated CDSs, showed translation signals and five proteins exhibited specific cytosolic localizations. Our results suggest that de novo genes frequently arise in the S. sensu stricto complex and have the potential to be quickly integrated into ancient cellular network.

Raising orphans from a metadata morass: A researcher's guide to re-use of public 'omics data

More than 15 petabases of raw RNAseq data is now accessible through public repositories. Acquisition of other 'omics data types is expanding, though most lack a centralized archival repository. Data-reuse provides tremendous opportunity to extract new knowledge from existing experiments, and offers a unique opportunity for robust, multi-'omics analyses by merging metadata (information about experimental design, biological samples, protocols) and data from multiple experiments. We illustrate how predictive research can be accelerated by meta-analysis with a study of orphan (species-specific) genes. Computational predictions are critical to infer orphan function because their coding sequences provide very few clues. The metadata in public databases is often confusing; a test case with Zea mays mRNA seq data reveals a high proportion of missing, misleading or incomplete metadata. This metadata morass significantly diminishes the insight that can be extracted from these data. We provide tips for data submitters and users, including specific recommendations to improve metadata quality by more use of controlled vocabulary and by metadata reviews. Finally, we advocate for a unified, straightforward metadata submission and retrieval system.

Genome-wide Identification and Characterization of Natural Antisense Transcripts by Strand-specific RNA Sequencing in Ganoderma lucidum

Ganoderma lucidum is a white-rot fungus best-known for its medicinal and ligninolytic activities. To discover the underlying genes responsible for these activities, we identified and characterized the natural antisense transcripts (NATs) using strand-specific (ss) RNA-seq data obtained from the mycelia, primordia and fruiting bodies. NATs were identified using a custom pipeline and then subjected to functional enrichment and differential expression analyses. A total of 1613 cis- and 244 trans- sense and antisense transcripts were identified. Mapping to GO terms and KEGG pathways revealed that NATs were frequently associated with genes of particular functional categories in particular stages. ssRT-qPCR experiments showed that the expression profiles of 30 of 50 (60%) transcripts were highly correlated with those of the RNA-seq results (r ≥ 0.9). Expression profiles of 22 of 25 (88%) pairs of NATs and STs were highly correlated (p ≤ 0.01), with 15 having r ≥ 0.8 and 4 having r ≤ -0.8. Six lignin-modifying genes and their NATs were analyzed in detail. Diverse patterns of differential expression among different stages and positive and negative correlations were observed. These results suggested that NATs were implicated in gene expression regulation in a function-group and developmental-stage specific manner through complex mechanisms.

Genome Diversity and Evolution in the Budding Yeasts (Saccharomycotina)

Considerable progress in our understanding of yeast genomes and their evolution has been made over the last decade with the sequencing, analysis, and comparisons of numerous species, strains, or isolates of diverse origins. The role played by yeasts in natural environments as well as in artificial manufactures, combined with the importance of some species as model experimental systems sustained this effort. At the same time, their enormous evolutionary diversity (there are yeast species in every subphylum of Dikarya) sparked curiosity but necessitated further efforts to obtain appropriate reference genomes. Today, yeast genomes have been very informative about basic mechanisms of evolution, speciation, hybridization, domestication, as well as about the molecular machineries underlying them. They are also irreplaceable to investigate in detail the complex relationship between genotypes and phenotypes with both theoretical and practical implications. This review examines these questions at two distinct levels offered by the broad evolutionary range of yeasts: inside the best-studied Saccharomyces species complex, and across the entire and diversified subphylum of Saccharomycotina. While obviously revealing evolutionary histories at different scales, data converge to a remarkably coherent picture in which one can estimate the relative importance of intrinsic genome dynamics, including gene birth and loss, vs. horizontal genetic accidents in the making of populations. The facility with which novel yeast genomes can now be studied, combined with the already numerous available reference genomes, offer privileged perspectives to further examine these fundamental biological questions using yeasts both as eukaryotic models and as fungi of practical importance.

Natural gene expression variation studies in yeast

The rise of sequence information across different yeast species and strains is driving an increasing number of studies in the emerging field of genomics to associate polymorphic variants, mRNA abundance and phenotypic differences between individuals. Here, we gathered evidence from recent studies covering several layers that define the genotype-phenotype gap, such as mRNA abundance, allele-specific expression and translation efficiency to demonstrate how genetic variants co-evolve and define an individual's genome. Moreover, we exposed several antecedents where inter- and intra-specific studies led to opposite conclusions, probably owing to genetic divergence. Future studies in this area will benefit from the access to a massive array of well-annotated genomes and new sequencing technologies, which will allow the fine breakdown of the complex layers that delineate the genotype-phenotype map. Copyright © 2016 John Wiley & Sons, Ltd.

Multi-step formation, evolution, and functionalization of new cytoplasmic male sterility genes in the plant mitochondrial genomes

New gene origination is a major source of genomic innovations that confer phenotypic changes and biological diversity. Generation of new mitochondrial genes in plants may cause cytoplasmic male sterility (CMS), which can promote outcrossing and increase fitness. However, how mitochondrial genes originate and evolve in structure and function remains unclear. The rice Wild Abortive type of CMS is conferred by the mitochondrial gene WA352c (previously named WA352) and has been widely exploited in hybrid rice breeding. Here, we reconstruct the evolutionary trajectory of WA352c by the identification and analyses of 11 mitochondrial genomic recombinant structures related to WA352c in wild and cultivated rice. We deduce that these structures arose through multiple rearrangements among conserved mitochondrial sequences in the mitochondrial genome of the wild rice Oryza rufipogon, coupled with substoichiometric shifting and sequence variation. We identify two expressed but nonfunctional protogenes among these structures, and show that they could evolve into functional CMS genes via sequence variations that could relieve the self-inhibitory potential of the proteins. These sequence changes would endow the proteins the ability to interact with the nucleus-encoded mitochondrial protein COX11, resulting in premature programmed cell death in the anther tapetum and male sterility. Furthermore, we show that the sequences that encode the COX11-interaction domains in these WA352c-related genes have experienced purifying selection during evolution. We propose a model for the formation and evolution of new CMS genes via a "multi-recombination/protogene formation/functionalization" mechanism involving gradual variations in the structure, sequence, copy number, and function.

Open questions in the study of de novo genes: what, how and why

The study of de novo protein-coding genes is maturing from the ad hoc reporting of individual cases to the systematic analysis of extensive genomic data from several species. We identify three key challenges for this emerging field: understanding how best to identify de novo genes, how they arise and why they spread. We highlight the intellectual challenges of understanding how a de novo gene becomes integrated into pre-existing functions and becomes essential. We suggest that, as with protein sequence evolution, antagonistic co-evolution may be key to de novo gene evolution, particularly for new essential genes and new cancer-associated genes.

New genes from non-coding sequence: the role of de novo protein-coding genes in eukaryotic evolutionary innovation

The origin of novel protein-coding genes de novo was once considered so improbable as to be impossible. In less than a decade, and especially in the last five years, this view has been overturned by extensive evidence from diverse eukaryotic lineages. There is now evidence that this mechanism has contributed a significant number of genes to genomes of organisms as diverse as Saccharomyces, Drosophila, Plasmodium, Arabidopisis and human. From simple beginnings, these genes have in some instances acquired complex structure, regulated expression and important functional roles. New genes are often thought of as dispensable late additions; however, some recent de novo genes in human can play a role in disease. Rather than an extremely rare occurrence, it is now evident that there is a relatively constant trickle of proto-genes released into the testing ground of natural selection. It is currently unknown whether de novo genes arise primarily through an ‘RNA-first’ or ‘ORF-first’ pathway. Either way, evolutionary tinkering with this pool of genetic potential may have been a significant player in the origins of lineage-specific traits and adaptations.

De Novo Genes Arise at a Slow but Steady Rate along the Primate Lineage and Have Been Subject to Incomplete Lineage Sorting

De novo protein-coding gene origination is increasingly recognized as an important evolutionary mechanism. However, there remains a large amount of uncertainty regarding the frequency of these events and the mechanisms and speed of gene establishment. Here, we describe a rigorous search for cases of de novo gene origination in the great apes. We analyzed annotated proteomes as well as full genomic DNA and transcriptional and translational evidence. It is notable that results vary between database updates due to the fluctuating annotation of these genes. Nonetheless we identified 35 de novo genes: 16 human-specific; 5 human and chimpanzee specific; and 14 that originated prior to the divergence of human, chimpanzee, and gorilla and are found in all three genomes. The taxonomically restricted distribution of these genes cannot be explained by loss in other lineages. Each gene is supported by an open reading frame-creating mutation that occurred within the primate lineage, and which is not polymorphic in any species. Similarly to previous studies we find that the de novo genes identified are short and frequently located near pre-existing genes. Also, they may be associated with Alu elements and prior transcription and RNA-splicing at the locus. Additionally, we report the first case of apparent independent lineage sorting of a de novo gene. The gene is present in human and gorilla, whereas chimpanzee has the ancestral noncoding sequence. This indicates a long period of polymorphism prior to fixation and thus supports a model where de novo genes may, at least initially, have a neutral effect on fitness.

A protein constructed de novo enables cell growth by altering gene regulation

Recent advances in protein design rely on rational and computational approaches to create novel sequences that fold and function. In contrast, natural systems selected functional proteins without any design a priori. In an attempt to mimic nature, we used large libraries of novel sequences and selected for functional proteins that rescue Escherichia coli cells in which a conditionally essential gene has been deleted. In this way, the de novo protein SynSerB3 was selected as a rescuer of cells in which serB, which encodes phosphoserine phosphatase, an enzyme essential for serine biosynthesis, was deleted. However, SynSerB3 does not rescue the deleted activity by catalyzing hydrolysis of phosphoserine. Instead, SynSerB3 up-regulates hisB, a gene encoding histidinol phosphate phosphatase. This endogenous E. coli phosphatase has promiscuous activity that, when overexpressed, compensates for the deletion of phosphoserine phosphatase. Thus, the de novo protein SynSerB3 rescues the deletion of serB by altering the natural regulation of the His operon.