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

Cut from the same cloth: RNAs transcribed from regulatory elements

A certain degree of chromatin openness is necessary for the activity of transcription-regulating regions within the genome, facilitating accessibility to RNA polymerases and subsequent synthesis of regulatory element RNAs (regRNAs) from these regions. The rapidly increasing number of studies underscores the significance of regRNAs across diverse cellular processes and diseases, challenging the paradigm that these transcripts are non-functional transcriptional noise. This review explores the multifaceted roles of regRNAs in human cells, encompassing rather well-studied entities such as promoter RNAs and enhancer RNAs (eRNAs), while also providing insights into overshadowed silencer RNAs and insulator RNAs. Furthermore, we assess notable examples of shorter regRNAs, like miRNAs, snRNAs, and snoRNAs, playing important roles. Expanding our discourse, we deliberate on the potential usage of regRNAs as biomarkers and novel targets for cancer and other human diseases.

Challenges in LncRNA Biology: Views and Opinions

This is a mini-review capturing the views and opinions of selected participants at the 2021 IEEE BIBM 3rd Annual LncRNA Workshop, held in Dubai, UAE. The views and opinions are expressed on five broad themes related to problems in lncRNA, namely, challenges in the computational analysis of lncRNAs, lncRNAs and cancer, lncRNAs in sports, lncRNAs and COVID-19, and lncRNAs in human brain activity.

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.

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

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

Beyond traditional translation: ncRNA derived peptides as modulators of tumor behaviors

Within the intricate tapestry of molecular research, noncoding RNAs (ncRNAs) were historically overshadowed by a pervasive presumption of their inability to encode proteins or peptides. However, groundbreaking revelations have challenged this notion, unveiling select ncRNAs that surprisingly encode peptides specifically those nearing a succinct 100 amino acids. At the forefront of this epiphany stand lncRNAs and circRNAs, distinctively characterized by their embedded small open reading frames (sORFs). Increasing evidence has revealed different functions and mechanisms of peptides/proteins encoded by ncRNAs in cancer, including promotion or inhibition of cancer cell proliferation, cellular metabolism (glucose metabolism and lipid metabolism), and promotion or concerted metastasis of cancer cells. The discoveries not only accentuate the depth of ncRNA functionality but also open novel avenues for oncological research and therapeutic innovations. The main difficulties in the study of these ncRNA-derived peptides hinge crucially on precise peptide detection and sORFs identification. Here, we illuminate cutting-edge methodologies, essential instrumentation, and dedicated databases tailored for unearthing sORFs and peptides. In addition, we also conclude the potential of clinical applications in cancer therapy.

Experimental Evaluation of a Direct Fitness Effect of the De Novo Evolved Mouse Gene Pldi

De novo evolved genes emerge from random parts of noncoding sequences and have, therefore, no homologs from which a function could be inferred. While expression analysis and knockout experiments can provide insights into the function, they do not directly test whether the gene is beneficial for its carrier. Here, we have used a seminatural environment experiment to test the fitness of the previously identified de novo evolved mouse gene Pldi, which has been implicated to have a role in sperm differentiation. We used a knockout mouse strain for this gene and competed it against its parental wildtype strain for several generations of free reproduction. We found that the knockout (ko) allele frequency decreased consistently across three replicates of the experiment. Using an approximate Bayesian computation framework that simulated the data under a demographic scenario mimicking the experiment's demography, we could estimate a selection coefficient ranging between 0.21 and 0.61 for the wildtype allele compared to the ko allele in males, under various models. This implies a relatively strong selective advantage, which would fix the new gene in less than hundred generations after its emergence.

More than the SRY: The Non-Coding Landscape of the Y Chromosome and Its Importance in Human Disease

Historically, the Y chromosome has presented challenges to classical methodology and philosophy of understanding the differences between males and females. A genetic unsolved puzzle, the Y chromosome was the last chromosome to be fully sequenced. With the advent of the Human Genome Project came a realization that the human genome is more than just genes encoding proteins, and an entire universe of RNA was discovered. This dark matter of biology and the black box surrounding the Y chromosome have collided over the last few years, as increasing numbers of non-coding RNAs have been identified across the length of the Y chromosome, many of which have played significant roles in disease. In this review, we will uncover what is known about the connections between the Y chromosome and the non-coding RNA universe that originates from it, particularly as it relates to long non-coding RNAs, microRNAs and circular RNAs.

Elsayed A, López-Berestein G, Amero P, Rodríguez-Aguayo C. An Overview of the Immune Modulatory Properties of Long Non-Coding RNAs and Their Potential Use as Therapeutic Targets in Cancer

Long non-coding RNAs (lncRNAs) play pivotal roles in regulating immune responses, immune cell differentiation, activation, and inflammatory processes. In cancer, they are gaining prominence as potential therapeutic targets due to their ability to regulate immune checkpoint molecules and immune-related factors, suggesting avenues for bolstering anti-tumor immune responses. Here, we explore the mechanistic insights into lncRNA-mediated immune modulation, highlighting their impact on immunity. Additionally, we discuss their potential to enhance cancer immunotherapy, augmenting the effectiveness of immune checkpoint inhibitors and adoptive T cell therapies. LncRNAs as therapeutic targets hold the promise of revolutionizing cancer treatments, inspiring further research in this field with substantial clinical implications.

In-depth characterization and identification of translatable lncRNAs

Long non-coding RNAs (LncRNAs) are non-protein coding transcripts more than 200 nucleotides in length. Deep sequencing technologies have unveiled lncRNAs can harbor translatable short open reading frames (sORFs). Yet the regulatory mechanisms governing lncRNA translation events remain poorly understood. Here, we exhaustively detected the sequence, functional element, and structure features relevant to lncRNA translation in human. Extensive identification and analysis reveal that translatable lncRNAs contain richer protein-coding related sequence features, cap-dependent and cap-independent translation initiation mechanisms, and more stable secondary structures, as compared to untranslatable lncRNAs. These findings strongly support lncRNAs serve as a repository for the production of new small peptides. Based on the feature fusion affecting translation and the extreme gradient boosting (XGBoost) algorithm, we developed the first computational tool that dedicated for predicting translatable lncRNAs, named TransLncPred. Benchmark experimental results show that our method outperforms several state-of-the-art RNA coding potential prediction tools on the same training and testing datasets. The 100-time 10-fold cross-validation tests also demonstrate that regulatory element-derived features, especially N7-methylguanosine (m7G) and internal ribosome entry site (IRES), contribute to the improvement in predictive performance.

What Can Ribo-Seq, Immunopeptidomics, and Proteomics Tell Us About the Noncanonical Proteome?

Ribosome profiling (Ribo-Seq) has proven transformative for our understanding of the human genome and proteome by illuminating thousands of noncanonical sites of ribosome translation outside the currently annotated coding sequences (CDSs). A conservative estimate suggests that at least 7000 noncanonical ORFs are translated, which, at first glance, has the potential to expand the number of human protein CDSs by 30%, from ∼19,500 annotated CDSs to over 26,000 annotated CDSs. Yet, additional scrutiny of these ORFs has raised numerous questions about what fraction of them truly produce a protein product and what fraction of those can be understood as proteins according to conventional understanding of the term. Adding further complication is the fact that published estimates of noncanonical ORFs vary widely by around 30-fold, from several thousand to several hundred thousand. The summation of this research has left the genomics and proteomics communities both excited by the prospect of new coding regions in the human genome but searching for guidance on how to proceed. Here, we discuss the current state of noncanonical ORF research, databases, and interpretation, focusing on how to assess whether a given ORF can be said to be "protein coding."

Genome annotation: From human genetics to biodiversity genomics

Within the next decade, the genomes of 1.8 million eukaryotic species will be sequenced. Identifying genes in these sequences is essential to understand the biology of the species. This is challenging due to the transcriptional complexity of eukaryotic genomes, which encode hundreds of thousands of transcripts of multiple types. Among these, a small set of protein-coding mRNAs play a disproportionately large role in defining phenotypes. Due to their sequence conservation, orthology can be established, making it possible to define the universal catalog of eukaryotic protein-coding genes. This catalog should substantially contribute to uncovering the genomic events underlying the emergence of eukaryotic phenotypes. This piece briefly reviews the basics of protein-coding gene prediction, discusses challenges in finalizing annotation of the human genome, and proposes strategies for producing annotations across the eukaryotic Tree of Life. This lays the groundwork for obtaining the catalog of all genes-the Earth's code of life.

What can Ribo-seq and proteomics tell us about the non-canonical proteome?

Ribosome profiling (Ribo-seq) has proven transformative for our understanding of the human genome and proteome by illuminating thousands of non-canonical sites of ribosome translation outside of the currently annotated coding sequences (CDSs). A conservative estimate suggests that at least 7,000 non-canonical open reading frames (ORFs) are translated, which, at first glance, has the potential to expand the number of human protein-coding sequences by 30%, from ∼19,500 annotated CDSs to over 26,000. Yet, additional scrutiny of these ORFs has raised numerous questions about what fraction of them truly produce a protein product and what fraction of those can be understood as proteins according to conventional understanding of the term. Adding further complication is the fact that published estimates of non-canonical ORFs vary widely by around 30-fold, from several thousand to several hundred thousand. The summation of this research has left the genomics and proteomics communities both excited by the prospect of new coding regions in the human genome, but searching for guidance on how to proceed. Here, we discuss the current state of non-canonical ORF research, databases, and interpretation, focusing on how to assess whether a given ORF can be said to be "protein-coding".

In brief

The human genome encodes thousands of non-canonical open reading frames (ORFs) in addition to protein-coding genes. As a nascent field, many questions remain regarding non-canonical ORFs. How many exist? Do they encode proteins? What level of evidence is needed for their verification? Central to these debates has been the advent of ribosome profiling (Ribo-seq) as a method to discern genome-wide ribosome occupancy, and immunopeptidomics as a method to detect peptides that are processed and presented by MHC molecules and not observed in traditional proteomics experiments. This article provides a synthesis of the current state of non-canonical ORF research and proposes standards for their future investigation and reporting.

Highlights

Combined use of Ribo-seq and proteomics-based methods enables optimal confidence in detecting non-canonical ORFs and their protein products.Ribo-seq can provide more sensitive detection of non-canonical ORFs, but data quality and analytical pipelines will impact results.Non-canonical ORF catalogs are diverse and span both high-stringency and low-stringency ORF nominations.A framework for standardized non-canonical ORF evidence will advance the research field.

Evolution and implications of de novo genes in humans

Genes and translated open reading frames (ORFs) that emerged de novo from previously non-coding sequences provide species with opportunities for adaptation. When aberrantly activated, some human-specific de novo genes and ORFs have disease-promoting properties-for instance, driving tumour growth. Thousands of putative de novo coding sequences have been described in humans, but we still do not know what fraction of those ORFs has readily acquired a function. Here, we discuss the challenges and controversies surrounding the detection, mechanisms of origin, annotation, validation and characterization of de novo genes and ORFs. Through manual curation of literature and databases, we provide a thorough table with most de novo genes reported for humans to date. We re-evaluate each locus by tracing the enabling mutations and list proposed disease associations, protein characteristics and supporting evidence for translation and protein detection. This work will support future explorations of de novo genes and ORFs in humans.

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.

OpenVar: functional annotation of variants in non-canonical open reading frames

Background

Recent technological advances have revealed thousands of functional open reading frames (ORF) that have eluded reference genome annotations. These overlooked ORFs are found throughout the genome, in any reading frame of transcripts, mature or non-coding, and can overlap annotated ORFs in a different reading frame. The exploration of these novel ORFs in genomic datasets and of their role in genetic traits is hindered by a lack of software.

Results

Here, we present OpenVar, a genomic variant annotator that mends that gap and fosters meaningful discoveries. To illustrate the potential of OpenVar, we analysed all variants within SynMicDB, a database of cancer-associated synonymous mutations. By including non-canonical ORFs in the analysis, OpenVar yields a 33.6-fold, 13.8-fold and 8.3-fold increase in high impact variants over Annovar, SnpEff and VEP respectively. We highlighted an overlapping non-canonical ORF in the HEY2 gene where variants significantly clustered.

Conclusions

OpenVar integrates non-canonical ORFs in the analysis of genomic variants, unveiling new research avenues to better understand the genotype–phenotype relationships.

Functional Micropeptides Encoded by Long Non-Coding RNAs: A Comprehensive Review

Long non-coding RNAs (lncRNAs) were originally defined as non-coding RNAs (ncRNAs) which lack protein-coding ability. However, with the emergence of technologies such as ribosome profiling sequencing and ribosome-nascent chain complex sequencing, it has been demonstrated that most lncRNAs have short open reading frames hence the potential to encode functional micropeptides. Such micropeptides have been described to be widely involved in life-sustaining activities in several organisms, such as homeostasis regulation, disease, and tumor occurrence, and development, and morphological development of animals, and plants. In this review, we focus on the latest developments in the field of lncRNA-encoded micropeptides, and describe the relevant computational tools and techniques for micropeptide prediction and identification. This review aims to serve as a reference for future research studies on lncRNA-encoded micropeptides.

Identification and characterisation of sPEPs in Cryptococcus neoformans

Short open reading frame (sORF)-encoded peptides (sPEPs) have been found across a wide range of genomic locations in a variety of species. To date, their identification, validation, and characterisation in the human fungal pathogen Cryptococcus neoformans has been limited due to a lack of standardised protocols. We have developed an enrichment process that enables sPEP detection within a protein sample from this polysaccharide-encapsulated yeast, and implemented proteogenomics to provide insights into the validity of predicted and hypothetical sORFs annotated in the C. neoformans genome. Novel sORFs were discovered within the 5' and 3' UTRs of known transcripts as well as in "non-coding" RNAs. One novel candidate, dubbed NPB1, that resided in an RNA annotated as "non-coding", was chosen for characterisation. Through the creation of both specific point mutations and a full deletion allele, the function of the new sPEP, Npb1, was shown to resemble that of the bacterial trans-translation protein SmpB.

Short open reading frames (sORFs) and microproteins: an update on their identification and validation measures

A short open reading frame (sORFs) constitutes ≤ 300 bases, encoding a microprotein or sORF-encoded protein (SEP) which comprises ≤ 100 amino acids. Traditionally dismissed by genome annotation pipelines as meaningless noise, sORFs were found to possess coding potential with ribosome profiling (RIBO-Seq), which unveiled sORF-based transcripts at various genome locations. Nonetheless, the existence of corresponding microproteins that are stable and functional was little substantiated by experimental evidence initially. With recent advancements in multi-omics, the identification, validation, and functional characterisation of sORFs and microproteins have become feasible. In this review, we discuss the history and development of an emerging research field of sORFs and microproteins. In particular, we focus on an array of bioinformatics and OMICS approaches used for predicting, sequencing, validating, and characterizing these recently discovered entities. These strategies include RIBO-Seq which detects sORF transcripts via ribosome footprints, and mass spectrometry (MS)-based proteomics for sequencing the resultant microproteins. Subsequently, our discussion extends to the functional characterisation of microproteins by incorporating CRISPR/Cas9 screen and protein–protein interaction (PPI) studies. Our review discusses not only detection methodologies, but we also highlight on the challenges and potential solutions in identifying and validating sORFs and their microproteins. The novelty of this review lies within its validation for the functional role of microproteins, which could contribute towards the future landscape of microproteomics.

The microprotein Nrs1 rewires the G1/S transcriptional machinery during nitrogen limitation in budding yeast

Commitment to cell division at the end of G1 phase, termed Start in the budding yeast Saccharomyces cerevisiae, is strongly influenced by nutrient availability. To identify new dominant activators of Start that might operate under different nutrient conditions, we screened a genome-wide ORF overexpression library for genes that bypass a Start arrest caused by absence of the G1 cyclin Cln3 and the transcriptional activator Bck2. We recovered a hypothetical gene YLR053c, renamed NRS1 for Nitrogen-Responsive Start regulator 1, which encodes a poorly characterized 108 amino acid microprotein. Endogenous Nrs1 was nuclear-localized, restricted to poor nitrogen conditions, induced upon TORC1 inhibition, and cell cycle-regulated with a peak at Start. NRS1 interacted genetically with SWI4 and SWI6, which encode subunits of the main G1/S transcription factor complex SBF. Correspondingly, Nrs1 physically interacted with Swi4 and Swi6 and was localized to G1/S promoter DNA. Nrs1 exhibited inherent transactivation activity, and fusion of Nrs1 to the SBF inhibitor Whi5 was sufficient to suppress other Start defects. Nrs1 appears to be a recently evolved microprotein that rewires the G1/S transcriptional machinery under poor nitrogen conditions.

Commitment to cell division at the end of G1 phase in the budding yeast Saccharomyces cerevisiae is strongly influenced by nutrient availability. This study identifies a micro-protein that promotes G1/S transcription activation and cell cycle entry in yeast under nitrogen-limited conditions.

Mosquito long non-coding RNAs are enriched with Transposable Elements

Long non-coding RNAs (lncRNAs) lack coding capacity and mounting evidence suggests that they have a regulatory role in diverse organisms. Most knowledge about lncRNAs comes from studies on vertebrates, including a structural association between lncRNAs and transposable elements (TEs). TE sequences are genomic parasites found in all branches of life and are particularly active and abundant in insect genomes. Here we investigate the contribution of TEs to lncRNA biogenesis in Aedes albopictus and Culex quinquefasciatus. We found that a large fraction of lncRNA loci co-occurs with TE loci in both species. Around 40% of A. albopictus and 52% of C. quinquefasciatus lncRNAs show some association with TEs. Most of the lncRNA/TE associations are represented by TE-derived sequences that are expressed as one or all exons of lncRNAs, including five lncRNAs that seem to influence immune-related genes involved in antiviral response. The contribution of TEs to lncRNAs also varies among the different types of TEs. The Gypsi superfamily is particularly enriched in lncRNAs sequences. In sum, this study demonstrates that transposable elements substantially contribute to lncRNAs biogenesis in A. albopictus and C. quinquefasciatus and may have an impact on regulatory modulation in these species.

Overlapping genes in natural and engineered genomes

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

Effects of the Expression of Random Sequence Clones on Growth and Transcriptome Regulation in Escherichia coli

Comparative genomic analyses have provided evidence that new genetic functions can emerge out of random nucleotide sequences. Here, we apply a direct experimental approach to study the effects of plasmids harboring random sequence inserts under the control of an inducible promoter. Based on data from previously described experiments dealing with the growth of clones within whole libraries, we extracted specific clones that had shown either negative, neutral or positive effects on relative cell growth. We analyzed these individually with respect to growth characteristics and the impact on the transcriptome. We find that candidate clones for negative peptides lead to growth arrest by eliciting a general stress response. Overexpression of positive clones, on the other hand, does not change the exponential growth rates of hosts, and they show a growth advantage over a neutral clone when tested in direct competition experiments. Transcriptomic changes in positive clones are relatively moderate and specific to each clone. We conclude from our experiments that random sequence peptides are indeed a suitable source for the de novo evolution of genetic functions.

Long Non-Coding RNAs Associated with Ribosomes in Human Adipose-Derived Stem Cells: From RNAs to Microproteins

Ribosome profiling reveals the translational dynamics of mRNAs by capturing a ribosomal footprint snapshot. Growing evidence shows that several long non-coding RNAs (lncRNAs) contain small open reading frames (smORFs) that are translated into functional peptides. The difficulty in identifying bona-fide translated smORFs is a constant challenge in experimental and bioinformatics fields due to their unconventional characteristics. This motivated us to isolate human adipose-derived stem cells (hASC) from adipose tissue and perform a ribosome profiling followed by bioinformatics analysis of transcriptome, translatome, and ribosome-protected fragments of lncRNAs. Here, we demonstrated that 222 lncRNAs were associated with the translational machinery in hASC, including the already demonstrated lncRNAs coding microproteins. The ribosomal occupancy of some transcripts was consistent with the translation of smORFs. In conclusion, we were able to identify a subset of 15 lncRNAs containing 35 smORFs that likely encode functional microproteins, including four previously demonstrated smORF-derived microproteins, suggesting a possible dual role of these lncRNAs in hASC self-renewal.

Long Non-Coding RNAs as Functional Codes for Oral Cancer: Translational Potential, Progress and Promises

Oral cancer is one of the leading malignant tumors worldwide. Despite the advent of multidisciplinary approaches, the overall prognosis of patients with oral cancer is poor, mainly due to late diagnosis. There is an urgent need to develop valid biomarkers for early detection and effective therapies. Long non-coding RNAs (lncRNAs) are recognized as key elements of gene regulation, with pivotal roles in various physiological and pathological processes, including cancer. Over the past few years, an exponentially growing number of lncRNAs have been identified and linked to tumorigenesis and prognosis outcomes in oral cancer, illustrating their emerging roles in oral cancer progression and the associated signaling pathways. Herein, we aim to summarize the most recent advances made concerning oral cancer-associated lncRNA, and their expression, involvement, and potential clinical impact, reported to date, with a specific focus on the lncRNA-mediated molecular regulation in oncogenic signaling cascades and oral malignant progression, while exploring their potential, and challenges, for clinical applications as biomarkers or therapeutic targets for oral cancer.

The largely unexplored biology of small proteins in pro- and eukaryotes

The large abundance of small open reading frames (smORFs) in prokaryotic and eukaryotic genomes and the plethora of smORF-encoded small proteins became only apparent with the constant advancements in bioinformatic, genomic, proteomic, and biochemical tools. Small proteins are typically defined as proteins of < 50 amino acids in prokaryotes and of less than 100 amino acids in eukaryotes, and their importance for cell physiology and cellular adaptation is only beginning to emerge. In contrast to antimicrobial peptides, which are secreted by prokaryotic and eukaryotic cells for combatting pathogens and competitors, small proteins act within the producing cell mainly by stabilizing protein assemblies and by modifying the activity of larger proteins. Production of small proteins is frequently linked to stress conditions or environmental changes, and therefore, cells seem to use small proteins as intracellular modifiers for adjusting cell metabolism to different intra- and extracellular cues. However, the size of small proteins imposes a major challenge for the cellular machinery required for protein folding and intracellular trafficking and recent data indicate that small proteins can engage distinct trafficking pathways. In the current review, we describe the diversity of small proteins in prokaryotes and eukaryotes, highlight distinct and common features, and illustrate how they are handled by the protein trafficking machineries in prokaryotic and eukaryotic cells. Finally, we also discuss future topics of research on this fascinating but largely unexplored group of proteins.

Characterization of novel pollen-expressed transcripts reveals their potential roles in pollen heat stress response in Arabidopsis thaliana

Arabidopsis pollen transcriptome analysis revealed new intergenic transcripts of unknown function, many of which are long non-coding RNAs, that may function in pollen-specific processes, including the heat stress response. The male gametophyte is the most heat sensitive of all plant tissues. In recent years, long noncoding RNAs (lncRNAs) have emerged as important components of cellular regulatory networks involved in most biological processes, including response to stress. While examining RNAseq datasets of developing and germinating Arabidopsis thaliana pollen exposed to heat stress (HS), we identified 66 novel and 246 recently annotated intergenic expressed loci (XLOCs) of unknown function, with the majority encoding lncRNAs. Comparison with HS in cauline leaves and other RNAseq experiments indicated that 74% of the 312 XLOCs are pollen-specific, and at least 42% are HS-responsive. Phylogenetic analysis revealed that 96% of the genes evolved recently in Brassicaceae. We found that 50 genes are putative targets of microRNAs and that 30% of the XLOCs contain small open reading frames (ORFs) with homology to protein sequences. Finally, RNAseq of ribosome-protected RNA fragments together with predictions of periodic footprint of the ribosome P-sites indicated that 23 of these ORFs are likely to be translated. Our findings indicate that many of the 312 unknown genes might be functional and play a significant role in pollen biology, including the HS response.

Functional Long Non-coding RNAs Evolve from Junk Transcripts

Transcriptome studies reveal pervasive transcription of complex genomes, such as those of mammals. Despite popular arguments for functionality of most, if not all, of these transcripts, genome-wide analysis of selective constraints indicates that most of the produced RNA are junk. However, junk is not garbage. On the contrary, junk transcripts provide the raw material for the evolution of diverse long non-coding (lnc) RNAs by non-adaptive mechanisms, such as constructive neutral evolution. The generation of many novel functional entities, such as lncRNAs, that fuels organismal complexity does not seem to be driven by strong positive selection. Rather, the weak selection regime that dominates the evolution of most multicellular eukaryotes provides ample material for functional innovation with relatively little adaptation involved.