Uncovering de novo gene birth in yeast using deep transcriptomics

The hidden bacterial microproteome

Microproteins encoded by small open reading frames comprise the "dark matter" of proteomes. Although microproteins have been detected in diverse organisms from all three domains of life, many more remain to be identified, and only a few have been functionally characterized. In this comprehensive study of intergenic small open reading frames (ismORFs, 15-70 codons) in 5,668 bacterial genomes of the family Enterobacteriaceae, we identify 67,297 clusters of ismORFs subject to purifying selection. Expression of tagged Escherichia coli microproteins is detected for 11 of the 16 tested, validating the predictions. Although the ismORFs mainly code for hydrophobic, potentially transmembrane, unstructured, or minimally structured microproteins, some globular folds, oligomeric structures, and possible interactions with proteins encoded by neighboring genes are predicted. Complete information on the predicted microprotein families, including evidence of transcription and translation, and structure predictions are available as an easily searchable resource for investigation of microprotein functions.

A de novo Gene Promotes Seed Germination Under Drought Stress in Arabidopsis

The origin of genes from noncoding sequences is a long-term and fundamental biological question. However, how de novo genes originate and integrate into the existing pathways to regulate phenotypic variations is largely unknown. Here, we selected 7 genes from 782 de novo genes for functional exploration based on transcriptional and translational evidence. Subsequently, we revealed that Sun Wu-Kong (SWK), a de novo gene that originated from a noncoding sequence in Arabidopsis thaliana, plays a role in seed germination under osmotic stress. SWK is primarily expressed in dry seed, imbibing seed and silique. SWK can be fully translated into an 8 kDa protein, which is mainly located in the nucleus. Intriguingly, SWK was integrated into an extant pathway of hydrogen peroxide content (folate synthesis pathway) via the upstream gene cytHPPK/DHPS, an Arabidopsis-specific gene that originated from the duplication of mitHPPK/DHPS, and downstream gene GSTF9, to improve seed germination in osmotic stress. In addition, we demonstrated that the presence of SWK may be associated with drought tolerance in natural populations of Arabidopsis. Overall, our study highlights how a de novo gene originated and integrated into the existing pathways to regulate stress adaptation.

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.

Microprotein-encoding RNA regulation in cells treated with pro-inflammatory and pro-fibrotic stimuli

BACKGROUND

Recent analysis of the human proteome via proteogenomics and ribosome profiling of the transcriptome revealed the existence of thousands of previously unannotated microprotein-coding small open reading frames (smORFs). Most functional microproteins were chosen for characterization because of their evolutionary conservation. However, one example of a non-conserved immunomodulatory microprotein in mice suggests that strict sequence conservation misses some intriguing microproteins.

RESULTS

We examine the ability of gene regulation to identify human microproteins with potential roles in inflammation or fibrosis of the intestine. To do this, we collected ribosome profiling data of intestinal cell lines and peripheral blood mononuclear cells and used gene expression of microprotein-encoding transcripts to identify strongly regulated microproteins, including several examples of microproteins that are only conserved with primates.

CONCLUSION

This approach reveals a number of new microproteins worthy of additional functional characterization and provides a dataset that can be queried in different ways to find additional gut microproteins of interest.

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.

De Novo Emerged Gene Search in Eukaryotes with DENSE

The discovery of de novo emerged genes, originating from previously noncoding DNA regions, challenges traditional views of species evolution. Indeed, the hypothesis of neutrally evolving sequences giving rise to functional proteins is highly unlikely. This conundrum has sparked numerous studies to quantify and characterize these genes, aiming to understand their functional roles and contributions to genome evolution. Yet, no fully automated pipeline for their identification is available. Therefore, we introduce DENSE (DE Novo emerged gene SEarch), an automated Nextflow pipeline based on two distinct steps: detection of taxonomically restricted genes (TRGs) through phylostratigraphy, and filtering of TRGs for de novo emerged genes via genome comparisons and synteny search. DENSE is available as a user-friendly command-line tool, while the second step is accessible through a web server upon providing a list of TRGs. Highly flexible, DENSE provides various strategy and parameter combinations, enabling users to adapt to specific configurations or define their own strategy through a rational framework, facilitating protocol communication, and study interoperability. We apply DENSE to seven model organisms, exploring the impact of its strategies and parameters on de novo gene predictions. This thorough analysis across species with different evolutionary rates reveals useful metrics for users to define input datasets, identify favorable/unfavorable conditions for de novo gene detection, and control potential biases in genome annotations. Additionally, predictions made for the seven model organisms are compiled into a requestable database, which we hope will serve as a reference for de novo emerged gene lists generated with specific criteria combinations.

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

Species-specific genes, also known as orphans, are ubiquitous across life's domains. In prokaryotes, species-specific orphan genes (SSOGs) are mostly thought to originate in external elements such as viruses followed by horizontal gene transfer, whereas the scenario of native origination, through rapid divergence or de novo, is mostly dismissed. However, quantitative evidence supporting either scenario is lacking. Here, we systematically analyzed genomes from 4644 human gut microbiome species and identified more than 600,000 unique SSOGs, representing an average of 2.6% of a given species' pangenome. These sequences are mostly rare within each species yet show signs of purifying selection. Overall, SSOGs use optimal codons less frequently, and their proteins are more disordered than those of conserved genes (i.e., non-SSOGs). Importantly, across species, the GC content of SSOGs closely matches that of conserved ones. In contrast, the ∼5% of SSOGs that share similarity to known viral sequences have distinct characteristics, including lower GC content. Thus, SSOGs with similarity to viruses differ from the remaining SSOGs, contrasting an external origination scenario for most of them. By examining the orthologous genomic region in closely related species, we show that a small subset of SSOGs likely evolved natively de novo and find that these genes also differ in their properties from the remaining SSOGs. Our results challenge the notion that external elements are the dominant source of prokaryotic genetic novelty and will enable future studies into the biological role and relevance of species-specific genes in the human gut.

How antisense transcripts can evolve to encode novel proteins

Protein coding features can emerge de novo in non coding transcripts, resulting in emergence of new protein coding genes. Studies across many species show that a large fraction of evolutionarily novel non-coding RNAs have an antisense overlap with protein coding genes. The open reading frames (ORFs) in these antisense RNAs could also overlap with existing ORFs. In this study, we investigate how the evolution an ORF could be constrained by its overlap with an existing ORF in three different reading frames. Using a combination of mathematical modeling and genome/transcriptome data analysis in two different model organisms, we show that antisense overlap can increase the likelihood of ORF emergence and reduce the likelihood of ORF loss, especially in one of the three reading frames. In addition to rationalising the repeatedly reported prevalence of de novo emerged genes in antisense transcripts, our work also provides a generic modeling and an analytical framework that can be used to understand evolution of antisense genes.

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.

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.

High Polymorphism Levels of De Novo ORFs in a Yoruba Human Population

During evolution, new open reading frames (ORFs) with the potential to give rise to novel proteins continuously emerge. A recent compilation of noncanonical ORFs with translation signatures in humans has identified thousands of cases with a putative de novo origin. However, it is not known which is their distribution in the population. Are they universally translated? Here, we use ribosome profiling data from 65 lymphoblastoid cell lines from individuals of Yoruba origin to investigate this question. We identify 2,587 de novo ORFs translated in at least one of the cell lines. In line with their de novo origin, the encoded proteins tend to be smaller than 100 amino acids and encode positively charged proteins. We observe that the de novo ORFs are more polymorphic in the population than the set of canonical proteins, with a substantial fraction of them being translated in only some of the cell lines. Remarkably, this difference remains significant after controlling for differences in the translation levels. These results suggest that variations in the level translation of de novo ORFs could be a relevant source of intraspecies phenotypic diversity in humans.

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.

ER stress-induced transcriptional response reveals tolerance genes in yeast

Saccharomyces cerevisiae is important for protein secretion studies, yet the complexities of protein synthesis and secretion under endoplasmic reticulum (ER) stress conditions remain not fully understood. ER stress, triggered by alterations in the ER protein folding environment, poses substantial challenges to cells, especially during heterologous protein production. In this study, we used RNA-seq to analyze the transcriptional responses of yeast strains to ER stress induced by reagents such as tunicamycin (Tm) or dithiothreitol (DTT). Our gene expression analysis revealed several crucial genes, such as HMO1 and BIO5, that are involved in ER-stress tolerance. Through metabolic engineering, the best engineered strain R23 with HMO1 overexpression and BIO5 deletion, showed enhanced ER stress tolerance and improved protein folding efficiency, leading to a 2.14-fold increase in α-amylase production under Tm treatment and a 2.04-fold increase in cell density under DTT treatment. Our findings contribute to the understanding of cellular responses to ER stress and provide a basis for further investigations into the mechanisms of ER stress at the cellular level.

Pervasive translation of Xrn1-sensitive unstable long noncoding RNAs in yeast

Despite being predicted to lack coding potential, cytoplasmic long noncoding (lnc)RNAs can associate with ribosomes. However, the landscape and biological relevance of lncRNA translation remain poorly studied. In yeast, cytoplasmic Xrn1-sensitive unstable transcripts (XUTs) are targeted by nonsense-mediated mRNA decay (NMD), suggesting a translation-dependent degradation process. Here, we report that XUTs are pervasively translated, which impacts their decay. We show that XUTs globally accumulate upon translation elongation inhibition, but not when initial ribosome loading is impaired. Ribo-seq confirmed ribosomes binding to XUTs and identified ribosome-associated 5'-proximal small ORFs. Mechanistically, the NMD-sensitivity of XUTs mainly depends on the 3'-untranslated region length. Finally, we show that the peptide resulting from the translation of an NMD-sensitive XUT reporter exists in NMD-competent cells. Our work highlights the role of translation in the posttranscriptional metabolism of XUTs. We propose that XUT-derived peptides could be exposed to natural selection, while NMD restricts XUT levels.

Promoter recruitment drives the emergence of proto-genes in a long-term evolution experiment with Escherichia coli

The phenomenon of de novo gene birth-the emergence of genes from non-genic sequences-has received considerable attention due to the widespread occurrence of genes that are unique to particular species or genomes. Most instances of de novo gene birth have been recognized through comparative analyses of genome sequences in eukaryotes, despite the abundance of novel, lineage-specific genes in bacteria and the relative ease with which bacteria can be studied in an experimental context. Here, we explore the genetic record of the Escherichia coli long-term evolution experiment (LTEE) for changes indicative of "proto-genic" phases of new gene birth in which non-genic sequences evolve stable transcription and/or translation. Over the time span of the LTEE, non-genic regions are frequently transcribed, translated and differentially expressed, with levels of transcription across low-expressed regions increasing in later generations of the experiment. Proto-genes formed downstream of new mutations result either from insertion element activity or chromosomal translocations that fused preexisting regulatory sequences to regions that were not expressed in the LTEE ancestor. Additionally, we identified instances of proto-gene emergence in which a previously unexpressed sequence was transcribed after formation of an upstream promoter, although such cases were rare compared to those caused by recruitment of preexisting promoters. Tracing the origin of the causative mutations, we discovered that most occurred early in the history of the LTEE, often within the first 20,000 generations, and became fixed soon after emergence. Our findings show that proto-genes emerge frequently within evolving populations, can persist stably, and can serve as potential substrates for new gene formation.

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.

Translation variation across genetic backgrounds reveals a post-transcriptional buffering signature in yeast

Gene expression is known to vary among individuals, and this variability can impact the phenotypic diversity observed in natural populations. While the transcriptome and proteome have been extensively studied, little is known about the translation process itself. Here, we therefore performed ribosome and transcriptomic profiling on a genetically and ecologically diverse set of natural isolates of the Saccharomyces cerevisiae yeast. Interestingly, we found that the Euclidean distances between each profile and the expression fold changes in each pairwise isolate comparison were higher at the transcriptomic level. This observation clearly indicates that the transcriptional variation observed in the different isolates is buffered through a phenomenon known as post-transcriptional buffering at the translation level. Furthermore, this phenomenon seemed to have a specific signature by preferentially affecting essential genes as well as genes involved in complex-forming proteins, and low transcribed genes. We also explored the translation of the S. cerevisiae pangenome and found that the accessory genes related to introgression events displayed similar transcription and translation levels as the core genome. By contrast, genes acquired through horizontal gene transfer events tended to be less efficiently translated. Together, our results highlight both the extent and signature of the post-transcriptional buffering.

Origin of functional de novo genes in humans from "hopeful monsters"

For a long time, it was believed that new genes arise only from modifications of preexisting genes, but the discovery of de novo protein-coding genes that originated from noncoding DNA regions demonstrates the existence of a "motherless" origination process for new genes. However, the features, distributions, expression profiles, and origin modes of these genes in humans seem to support the notion that their origin is not a purely "motherless" process; rather, these genes arise preferentially from genomic regions encoding preexisting precursors with gene-like features. In such a case, the gene loci are typically not brand new. In this short review, we will summarize the definition and features of human de novo genes and clarify their process of origination from ancestral non-coding genomic regions. In addition, we define the favored precursors, or "hopeful monsters," for the origin of de novo genes and present a discussion of the functional significance of these young genes in brain development and tumorigenesis in humans. This article is categorized under: RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution.

Regulatory activity is the default DNA state in eukaryotes

Genomes encode for genes and non-coding DNA, both capable of transcriptional activity. However, unlike canonical genes, many transcripts from non-coding DNA have limited evidence of conservation or function. Here, to determine how much biological noise is expected from non-genic sequences, we quantify the regulatory activity of evolutionarily naive DNA using RNA-seq in yeast and computational predictions in humans. In yeast, more than 99% of naive DNA bases were transcribed. Unlike the evolved transcriptome, naive transcripts frequently overlapped with opposite sense transcripts, suggesting selection favored coherent gene structures in the yeast genome. In humans, regulation-associated chromatin activity is predicted to be common in naive dinucleotide-content-matched randomized DNA. Here, naive and evolved DNA have similar co-occurrence and cell-type specificity of chromatin marks, challenging these as indicators of selection. However, in both yeast and humans, extreme high activities were rare in naive DNA, suggesting they result from selection. Overall, basal regulatory activity seems to be the default, which selection can hone to evolve a function or, if detrimental, repress.

The Cryptic Bacterial Microproteome

Microproteins encoded by small open reading frames (smORFs) comprise the "dark matter" of proteomes. Although functional microproteins were identified in diverse organisms from all three domains of life, bacterial smORFs remain poorly characterized. In this comprehensive study of intergenic smORFs (ismORFs, 15-70 codons) in 5,668 bacterial genomes of the family Enterobacteriaceae, we identified 67,297 clusters of ismORFs subject to purifying selection. The ismORFs mainly code for hydrophobic, potentially transmembrane, unstructured, or minimally structured microproteins. Using AlphaFold Multimer, we predicted interactions of some of the predicted microproteins encoded by transcribed ismORFs with proteins encoded by neighboring genes, revealing the potential of microproteins to regulate the activity of various proteins, particularly, under stress. We compiled a catalog of predicted microprotein families with different levels of evidence from synteny analysis, structure prediction, and transcription and translation data. This study offers a resource for investigation of biological functions of microproteins.

Four classic "de novo" genes all have plausible homologs and likely evolved from retro-duplicated or pseudogenic sequences

Despite being previously regarded as extremely unlikely, the idea that entirely novel protein-coding genes can emerge from non-coding sequences has gradually become accepted over the past two decades. Examples of "de novo origination", resulting in lineage-specific "orphan" genes, lacking coding orthologs, are now produced every year. However, many are likely cases of duplicates that are difficult to recognize. Here, I re-examine the claims and show that four very well-known examples of genes alleged to have emerged completely "from scratch"- FLJ33706 in humans, Goddard in fruit flies, BSC4 in baker's yeast and AFGP2 in codfish-may have plausible evolutionary ancestors in pre-existing genes. The first two are likely highly diverged retrogenes coding for regulatory proteins that have been misidentified as orphans. The antifreeze glycoprotein, moreover, may not have evolved from repetitive non-genic sequences but, as in several other related cases, from an apolipoprotein that could have become pseudogenized before later being reactivated. These findings detract from various claims made about de novo gene birth and show there has been a tendency not to invest the necessary effort in searching for homologs outside of a very limited syntenic or phylostratigraphic methodology. A robust approach is used for improving detection that draws upon similarities, not just in terms of statistical sequence analysis, but also relating to biochemistry and function, to obviate notable failures to identify homologs.

Alternative Reading Frames are an Underappreciated Source of Protein Sequence Novelty

Protein-coding DNA sequences can be translated into completely different amino acid sequences if the nucleotide triplets used are shifted by a non-triplet amount on the same DNA strand or by translating codons from the opposite strand. Such "alternative reading frames" of protein-coding genes are a major contributor to the evolution of novel protein products. Recent studies demonstrating this include examples across the three domains of cellular life and in viruses. These sequences increase the number of trials potentially available for the evolutionary invention of new genes and also have unusual properties which may facilitate gene origin. There is evidence that the structure of the standard genetic code contributes to the features and gene-likeness of some alternative frame sequences. These findings have important implications across diverse areas of molecular biology, including for genome annotation, structural biology, and evolutionary genomics.

Comparing Mitochondrial Activity, Oxidative Stress Tolerance, and Longevity of Thirteen Ascomycota Yeast Species

Aging is characterized by a number of hallmarks including loss of mitochondrial homeostasis and decay in stress tolerance, among others. Unicellular eukaryotes have been widely used to study chronological aging. As a general trait, calorie restriction and activation of mitochondrial respiration has been proposed to contribute to an elongated lifespan. Most aging-related studies have been conducted with the Crabtree-positive yeasts Saccharomyces cerevisiae and Schizosaccharomyces pombe, and with deletion collections deriving from these conventional yeast models. We have performed an unbiased characterization of longevity using thirteen fungi species, including S. cerevisiae and S. pombe, covering a wide range of the Ascomycota clade. We have determined their mitochondrial activity by oxygen consumption, complex IV activity, and mitochondrial redox potential, and the results derived from these three methodologies are highly overlapping. We have phenotypically compared the lifespans of the thirteen species and their capacity to tolerate oxidative stress. Longevity and elevated tolerance to hydrogen peroxide are correlated in some but not all yeasts. Mitochondrial activity per se cannot anticipate the length of the lifespan. We have classified the strains in four groups, with members of group 1 (Kluyveromyces lactis, Saccharomyces bayanus and Lodderomyces elongisporus) displaying high mitochondrial activity, elevated resistance to oxidative stress, and elongated lifespan.

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.

Inferring and comparing metabolism across heterogeneous sets of annotated genomes using AuCoMe

Comparative analysis of genome-scale metabolic networks (GSMNs) may yield important information on the biology, evolution, and adaptation of species. However, it is impeded by the high heterogeneity of the quality and completeness of structural and functional genome annotations, which may bias the results of such comparisons. To address this issue, we developed AuCoMe, a pipeline to automatically reconstruct homogeneous GSMNs from a heterogeneous set of annotated genomes without discarding available manual annotations. We tested AuCoMe with three data sets, one bacterial, one fungal, and one algal, and showed that it successfully reduces technical biases while capturing the metabolic specificities of each organism. Our results also point out shared and divergent metabolic traits among evolutionarily distant algae, underlining the potential of AuCoMe to accelerate the broad exploration of metabolic evolution across the tree of life.

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.

Neutral Models of De Novo Gene Emergence Suggest that Gene Evolution has a Preferred Trajectory

New protein coding genes can emerge from genomic regions that previously did not contain any genes, via a process called de novo gene emergence. To synthesize a protein, DNA must be transcribed as well as translated. Both processes need certain DNA sequence features. Stable transcription requires promoters and a polyadenylation signal, while translation requires at least an open reading frame. We develop mathematical models based on mutation probabilities, and the assumption of neutral evolution, to find out how quickly genes emerge and are lost. We also investigate the effect of the order by which DNA features evolve, and if sequence composition is biased by mutation rate. We rationalize how genes are lost much more rapidly than they emerge, and how they preferentially arise in regions that are already transcribed. Our study not only answers some fundamental questions on the topic of de novo emergence but also provides a modeling framework for future studies.

A de novo gene originating from the mitochondria controls floral transition in Arabidopsis thaliana

De novo genes created in the plant mitochondrial genome have frequently been transferred into the nuclear genome via intergenomic gene transfer events. Therefore, plant mitochondria might be a source of de novo genes in the nuclear genome. However, the functions of de novo genes originating from mitochondria and the evolutionary fate remain unclear. Here, we revealed that an Arabidopsis thaliana specific small coding gene derived from the mitochondrial genome regulates floral transition. We previously identified 49 candidate de novo genes that induce abnormal morphological changes on overexpression. We focused on a candidate gene derived from the mitochondrial genome (sORF2146) that encodes 66 amino acids. Comparative genomic analyses indicated that the mitochondrial sORF2146 emerged in the Brassica lineage as a de novo gene. The nuclear sORF2146 emerged following an intergenomic gene transfer event in the A. thaliana after the divergence between Arabidopsis and Capsella. Although the nuclear and mitochondrial sORF2146 sequences are the same in A. thaliana, only the nuclear sORF2146 is transcribed. The nuclear sORF2146 product is localized in mitochondria, which may be associated with the pseudogenization of the mitochondrial sORF2146. To functionally characterize the nuclear sORF2146, we performed a transcriptomic analysis of transgenic plants overexpressing the nuclear sORF2146. Flowering transition-related genes were highly regulated in the transgenic plants. Subsequent phenotypic analyses demonstrated that the overexpression and knockdown of sORF2146 in transgenic plants resulted in delayed and early flowering, respectively. These findings suggest that a lineage-specific de novo gene derived from mitochondria has an important regulatory effect on floral transition.

Peptidomics Methods Applied to the Study of Flower Development

Understanding the global and dynamic nature of plant developmental processes requires not only the study of the transcriptome, but also of the proteome, including its largely uncharacterized peptidome fraction. Recent advances in proteomics and high-throughput analyses of translating RNAs (ribosome profiling) have begun to address this issue, evidencing the existence of novel, uncharacterized, and possibly functional peptides. To validate the accumulation in tissues of sORF-encoded polypeptides (SEPs), the basic setup of proteomic analyses (i.e., LC-MS/MS) can be followed. However, the detection of peptides that are small (up to ~100 aa, 6-7 kDa) and novel (i.e., not annotated in reference databases) presents specific challenges that need to be addressed both experimentally and with computational biology resources. Several methods have been developed in recent years to isolate and identify peptides from plant tissues. In this chapter, we outline two different peptide extraction protocols and the subsequent peptide identification by mass spectrometry using the database search or the de novo identification methods.

The Modular Architecture of Metallothioneins Facilitates Domain Rearrangements and Contributes to Their Evolvability in Metal-Accumulating Mollusks

Protein domains are independent structural and functional modules that can rearrange to create new proteins. While the evolution of multidomain proteins through the shuffling of different preexisting domains has been well documented, the evolution of domain repeat proteins and the origin of new domains are less understood. Metallothioneins (MTs) provide a good case study considering that they consist of metal-binding domain repeats, some of them with a likely de novo origin. In mollusks, for instance, most MTs are bidomain proteins that arose by lineage-specific rearrangements between six putative domains: α, β1, β2, β3, γ and δ. Some domains have been characterized in bivalves and gastropods, but nothing is known about the MTs and their domains of other Mollusca classes. To fill this gap, we investigated the metal-binding features of NpoMT1 of Nautilus pompilius (Cephalopoda class) and FcaMT1 of Falcidens caudatus (Caudofoveata class). Interestingly, whereas NpoMT1 consists of α and β1 domains and has a prototypical Cd2+ preference, FcaMT1 has a singular preference for Zn2+ ions and a distinct domain composition, including a new Caudofoveata-specific δ domain. Overall, our results suggest that the modular architecture of MTs has contributed to MT evolution during mollusk diversification, and exemplify how modularity increases MT evolvability.

Translation and natural selection of micropeptides from long non-canonical RNAs

Long noncoding RNAs (lncRNAs) are transcripts longer than 200 nucleotides but lacking canonical coding sequences. Apparently unable to produce peptides, lncRNA function seems to rely only on RNA expression, sequence and structure. Here, we exhaustively detect in-vivo translation of small open reading frames (small ORFs) within lncRNAs using Ribosomal profiling during Drosophila melanogaster embryogenesis. We show that around 30% of lncRNAs contain small ORFs engaged by ribosomes, leading to regulated translation of 100 to 300 micropeptides. We identify lncRNA features that favour translation, such as cistronicity, Kozak sequences, and conservation. For the latter, we develop a bioinformatics pipeline to detect small ORF homologues, and reveal evidence of natural selection favouring the conservation of micropeptide sequence and function across evolution. Our results expand the repertoire of lncRNA biochemical functions, and suggest that lncRNAs give rise to novel coding genes throughout evolution. Since most lncRNAs contain small ORFs with as yet unknown translation potential, we propose to rename them "long non-canonical RNAs".

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.

An Integrated Approach for Microprotein Identification and Sequence Analysis

Next-generation sequencing (NGS) has propelled the field of genomics forward and produced whole genome sequences for numerous animal species and model organisms. However, despite this wealth of sequence information, comprehensive gene annotation efforts have proven challenging, especially for small proteins. Notably, conventional protein annotation methods were designed to intentionally exclude putative proteins encoded by short open reading frames (sORFs) less than 300 nucleotides in length to filter out the exponentially higher number of spurious noncoding sORFs throughout the genome. As a result, hundreds of functional small proteins called microproteins (<100 amino acids in length) have been incorrectly classified as noncoding RNAs or overlooked entirely. Here we provide a detailed protocol to leverage free, publicly available bioinformatic tools to query genomic regions for microprotein-coding potential based on evolutionary conservation. Specifically, we provide step-by-step instructions on how to examine sequence conservation and coding potential using Phylogenetic Codon Substitution Frequencies (PhyloCSF) on the user-friendly University of California Santa Cruz (UCSC) Genome Browser. Additionally, we detail steps to efficiently generate multiple species alignments of identified microprotein sequences to visualize amino acid sequence conservation and recommend resources to analyze microprotein characteristics, including predicted domain structures. These powerful tools can be used to help identify putative microprotein-coding sequences in noncanonical genomic regions or to rule out the presence of a conserved coding sequence with translational potential in a noncoding transcript of interest.

Multiple Pristionchus pacificus genomes reveal distinct evolutionary dynamics between de novo candidates and duplicated genes

The birth of new genes is a major molecular innovation driving phenotypic diversity across all domains of life. Although repurposing of existing protein-coding material by duplication is considered the main process of new gene formation, recent studies have discovered thousands of transcriptionally active sequences as a rich source of new genes. However, differential loss rates have to be assumed to reconcile the high birth rates of these incipient de novo genes with the dominance of ancient gene families in individual genomes. Here, we test this rapid turnover hypothesis in the context of the nematode model organism Pristionchus pacificus We extended the existing species-level phylogenomic framework by sequencing the genomes of six divergent P. pacificus strains. We used these data to study the evolutionary dynamics of different age classes and categories of origin at a population level. Contrasting de novo candidates with new families that arose by duplication and divergence from known genes, we find that de novo candidates are typically shorter, show less expression, and are overrepresented on the sex chromosome. Although the contribution of de novo candidates increases toward young age classes, multiple comparisons within the same age class showed significantly higher attrition in de novo candidates than in known genes. Similarly, young genes remain under weak evolutionary constraints with de novo candidates representing the fastest evolving subcategory. Altogether, this study provides empirical evidence for the rapid turnover hypothesis and highlights the importance of the evolutionary timescale when quantifying the contribution of different mechanisms toward new gene formation.

Native RNA sequencing in fission yeast reveals frequent alternative splicing isoforms

The unicellular yeast Schizosaccharomyces pombe (fission yeast) retains many of the splicing features observed in humans and is thus an excellent model to study the basic mechanisms of splicing. Nearly half the genes contain introns, but the impact of alternative splicing in gene regulation and proteome diversification remains largely unexplored. Here we leverage Oxford Nanopore Technologies native RNA sequencing (dRNA), as well as ribosome profiling data, to uncover the full range of polyadenylated transcripts and translated open reading frames. We identify 332 alternative isoforms affecting the coding sequences of 262 different genes, 97 of which occur at frequencies >20%, indicating that functional alternative splicing in S. pombe is more prevalent than previously suspected. Intron retention events make ∼80% of the cases; these events may be involved in the regulation of gene expression and, in some cases, generate novel protein isoforms, as supported by ribosome profiling data in 18 of the intron retention isoforms. One example is the rpl22 gene, in which intron retention is associated with the translation of a protein of only 13 amino acids. We also find that lowly expressed transcripts tend to have longer poly(A) tails than highly expressed transcripts, highlighting an interdependence between poly(A) tail length and transcript expression level. Finally, we discover 214 novel transcripts that are not annotated, including 158 antisense transcripts, some of which also show translation evidence. The methodologies described in this work open new opportunities to study the regulation of splicing in a simple eukaryotic model.

NTH2 1271_1272delTA Gene Disruption Results in Salt Tolerance in Saccharomyces cerevisiae

Trehalose is a common energy reservoir, and its accumulation results in osmotic protection. This sugar can accumulate through its synthesis or slow degradation of the reservoir by trehalase enzymes. Saccharomyces cerevisiae contains two neutral trehalases, NTH1 and NTH2, responsible for 75% and 25% of the enzymatic metabolism. We were interested in the loss-of-function of both enzymes with CRISPR/Cas9. The later NTH2 was of great importance since it is responsible for minor metabolic degradation of this sugar. It was believed that losing its functionality results in limited osmotic protection. We constructed an osmotolerant superior yeast capable of growing in 0.85 M NaCl after independent nth2 1271_1272delTA mutation by CRISPR/Cas9 technology, compared with nth1 893_894insT and wild type. We suggest that this yeast model could give clues to breeding commercial yeast resulting in non-GMO salinity-tolerant strains.

Pervasive translation in Mycobacterium tuberculosis

Most bacterial ORFs are identified by automated prediction algorithms. However, these algorithms often fail to identify ORFs lacking canonical features such as a length of >50 codons or the presence of an upstream Shine-Dalgarno sequence. Here, we use ribosome profiling approaches to identify actively translated ORFs in Mycobacterium tuberculosis. Most of the ORFs we identify have not been previously described, indicating that the M. tuberculosis transcriptome is pervasively translated. The newly described ORFs are predominantly short, with many encoding proteins of ≤50 amino acids. Codon usage of the newly discovered ORFs suggests that most have not been subject to purifying selection, and hence are unlikely to contribute to cell fitness. Nevertheless, we identify 90 new ORFs (median length of 52 codons) that bear the hallmarks of purifying selection. Thus, our data suggest that pervasive translation of short ORFs in Mycobacterium tuberculosis serves as a rich source for the evolution of new functional proteins.

Bacterial Small Membrane Proteins: the Swiss Army Knife of Regulators at the Lipid Bilayer

Small membrane proteins represent a subset of recently discovered small proteins (≤100 amino acids), which are a ubiquitous class of emerging regulators underlying bacterial adaptation to environmental stressors. Until relatively recently, small open reading frames encoding these proteins were not designated genes in genome annotations. Therefore, our understanding of small protein biology was primarily limited to a few candidates associated with previously characterized larger partner proteins. Following the first systematic analyses of small proteins in Escherichia coli over a decade ago, numerous small proteins across different bacteria have been uncovered. An estimated one-third of these newly discovered proteins in E. coli are localized to the cell membrane, where they may interact with distinct groups of membrane proteins, such as signal receptors, transporters, and enzymes, and affect their activities. Recently, there has been considerable progress in functionally characterizing small membrane protein regulators aided by innovative tools adapted specifically to study small proteins. Our review covers prototypical proteins that modulate a broad range of cellular processes, such as transport, signal transduction, stress response, respiration, cell division, sporulation, and membrane stability. Thus, small membrane proteins represent a versatile group of physiology regulators at the membrane and the whole cell. Additionally, small membrane proteins have the potential for clinical applications, where some of the proteins may act as antibacterial agents themselves while others serve as alternative drug targets for the development of novel antimicrobials.

Identification of Taxonomically Restricted Transcripts from Illumina RNA Sequencing Data

In order to perform a well-balanced comparative transcriptomic analysis, the reference genome and annotations for all species included in the comparison must be of a similar quality and completeness. Frequently, comparative transcriptomic analyses include non-model organisms whose annotations are not as well curated; this inequality can lead to biases.To avoid potential biases stemming from incomplete annotations, a comparative transcriptomic analysis can incorporate de novo transcriptome assemblies for each species, which reduces this disparity. This chapter covers all of the steps which are necessary to run a comparative transcriptomic analysis with de novo transcriptome assemblies, from the first step of the experimental design to the sequencing, and ultimately the bioinformatic analysis.

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 long non-coding RNA landscape of Candida yeast pathogens

Long non-coding RNAs (lncRNAs) constitute a poorly studied class of transcripts with emerging roles in key cellular processes. Despite efforts to characterize lncRNAs across a wide range of species, these molecules remain largely unexplored in most eukaryotic microbes, including yeast pathogens of the Candida clade. Here, we analyze thousands of publicly available sequencing datasets to infer and characterize the lncRNA repertoires of five major Candida pathogens: Candida albicans, Candida tropicalis, Candida parapsilosis, Candida auris and Candida glabrata. Our results indicate that genomes of these species encode hundreds of lncRNAs that show levels of evolutionary constraint intermediate between those of intergenic genomic regions and protein-coding genes. Despite their low sequence conservation across the studied species, some lncRNAs are syntenic and are enriched in shared sequence motifs. We find co-expression of lncRNAs with certain protein-coding transcripts, hinting at potential functional associations. Finally, we identify lncRNAs that are differentially expressed during infection of human epithelial cells for four of the studied species. Our comprehensive bioinformatic analyses of Candida lncRNAs pave the way for future functional characterization of these transcripts.

Long non-coding RNAs (lncRNAs) play roles in key cellular processes, but remain largely unexplored in fungal pathogens such as Candida. Here, Hovhannisyan and Gabaldón analyze thousands of sequencing datasets to infer and characterize the lncRNA repertoires of five Candida species, paving the way for their future functional characterization.

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.

Lineage-Specific Genes and Family Expansions in Dictyostelid Genomes Display Expression Bias and Evolutionary Diversification during Development

Gene duplications generate new genes that can contribute to expression changes and the evolution of new functions. Genomes often consist of gene families that undergo expansions, some of which occur in specific lineages that reflect recent adaptive diversification. In this study, lineage-specific genes and gene family expansions were studied across five dictyostelid species to determine when and how they are expressed during multicellular development. Lineage-specific genes were found to be enriched among genes with biased expression (predominant expression in one developmental stage) in each species and at most developmental time points, suggesting independent functional innovations of new genes throughout the phylogeny. Biased duplicate genes had greater expression divergence than their orthologs and paralogs, consistent with subfunctionalization or neofunctionalization. Lineage-specific expansions in particular had biased genes with both molecular signals of positive selection and high expression, suggesting adaptive genetic and transcriptional diversification following duplication. Our results present insights into the potential contributions of lineage-specific genes and families in generating species-specific phenotypes during multicellular development in dictyostelids.

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.

The Ancient Salicoid Genome Duplication Event: A Platform for Reconstruction of De Novo Gene Evolution in Populus trichocarpa

Orphan genes are characteristic genomic features that have no detectable homology to genes in any other species and represent an important attribute of genome evolution as sources of novel genetic functions. Here, we identified 445 genes specific to Populus trichocarpa. Of these, we performed deeper reconstruction of 13 orphan genes to provide evidence of de novo gene evolution. Populus and its sister genera Salix are particularly well suited for the study of orphan gene evolution because of the Salicoid whole-genome duplication event which resulted in highly syntenic sister chromosomal segments across the Salicaceae. We leveraged this genomic feature to reconstruct de novo gene evolution from intergenera, interspecies, and intragenomic perspectives by comparing the syntenic regions within the P. trichocarpa reference, then P. deltoides, and finally Salix purpurea. Furthermore, we demonstrated that 86.5% of the putative orphan genes had evidence of transcription. Additionally, we also utilized the Populus genome-wide association mapping panel, a collection of 1,084 undomesticated P. trichocarpa genotypes to further determine putative regulatory networks of orphan genes using expression quantitative trait loci (eQTL) mapping. Functional enrichment of these eQTL subnetworks identified common biological themes associated with orphan genes such as response to stress and defense response. We also identify a putative cis-element for a de novo gene and leverage conserved synteny to describe evolution of a putative transcription factor binding site. Overall, 45% of orphan genes were captured in trans-eQTL networks.

Landscape of the Dark Transcriptome Revealed Through Re-mining Massive RNA-Seq Data

The "dark transcriptome" can be considered the multitude of sequences that are transcribed but not annotated as genes. We evaluated expression of 6,692 annotated genes and 29,354 unannotated open reading frames (ORFs) in the Saccharomyces cerevisiae genome across diverse environmental, genetic and developmental conditions (3,457 RNA-Seq samples). Over 30% of the highly transcribed ORFs have translation evidence. Phylostratigraphic analysis infers most of these transcribed ORFs would encode species-specific proteins ("orphan-ORFs"); hundreds have mean expression comparable to annotated genes. These data reveal unannotated ORFs most likely to be protein-coding genes. We partitioned a co-expression matrix by Markov Chain Clustering; the resultant clusters contain 2,468 orphan-ORFs. We provide the aggregated RNA-Seq yeast data with extensive metadata as a project in MetaOmGraph (MOG), a tool designed for interactive analysis and visualization. This approach enables reuse of public RNA-Seq data for exploratory discovery, providing a rich context for experimentalists to make novel, experimentally testable hypotheses about candidate genes.

From Yeast to Mammals, the Nonsense-Mediated mRNA Decay as a Master Regulator of Long Non-Coding RNAs Functional Trajectory

The Nonsense-Mediated mRNA Decay (NMD) has been classically viewed as a translation-dependent RNA surveillance pathway degrading aberrant mRNAs containing premature stop codons. However, it is now clear that mRNA quality control represents only one face of the multiple functions of NMD. Indeed, NMD also regulates the physiological expression of normal mRNAs, and more surprisingly, of long non-coding (lnc)RNAs. Here, we review the different mechanisms of NMD activation in yeast and mammals, and we discuss the molecular bases of the NMD sensitivity of lncRNAs, considering the functional roles of NMD and of translation in the metabolism of these transcripts. In this regard, we describe several examples of functional micropeptides produced from lncRNAs. We propose that translation and NMD provide potent means to regulate the expression of lncRNAs, which might be critical for the cell to respond to environmental changes.