Many lncRNAs, 5'UTRs, and pseudogenes are translated and some are likely to express functional proteins

Ferroptosis contributes to the progression of female-specific neoplasms, from breast cancer to gynecological malignancies in a manner regulated by non-coding RNAs: Mechanistic implications

Ferroptosis, a recently identified type of non-apoptotic cell death, triggers the elimination of cells in the presence of lipid peroxidation and in an iron-dependent manner. Indeed, ferroptosis-stimulating factors have the ability of suppressing antioxidant capacity, leading to the accumulation of reactive oxygen species (ROS) and the subsequent oxidative death of the cells. Ferroptosis is involved in the pathophysiological basis of different maladies, such as multiple cancers, among which female-oriented malignancies have attracted much attention in recent years. In this context, it has also been unveiled that non-coding RNA transcripts, including microRNAs, long non-coding RNAs, and circular RNAs have regulatory interconnections with the ferroptotic flux, which controls the pathogenic development of diseases. Furthermore, the potential of employing these RNA transcripts as therapeutic targets during the onset of female-specific neoplasms to modulate ferroptosis has become a research hotspot; however, the molecular mechanisms and functional alterations of ferroptosis still require further investigation. The current review comprehensively highlights ferroptosis and its association with non-coding RNAs with a focus on how this crosstalk affects the pathogenesis of female-oriented malignancies, from breast cancer to ovarian, cervical, and endometrial neoplasms, suggesting novel therapeutic targets to decelerate and even block the expansion and development of these tumors.

Biochemical targets of the micropeptides encoded by lncRNAs

Long non-coding RNAs (lncRNAs) are a group of transcripts longer than 200 nucleotides, which play important roles in regulating various cellular activities by the action of the RNA itself. However, about 40% of lncRNAs in human cells are potentially translated into micropeptides (also referred to as microproteins) usually shorter than 100 amino acids. Thus, these lncRNAs may function by both RNAs directly and their encoded micropeptides. The micropeptides encoded by lncRNAs may regulate transcription, translation, protein phosphorylation or degradation, or subcellular membrane functions. This review attempts to summarize the biochemical targets of the micropeptides-encoded by lncRNAs, which function by both RNAs and micropeptides, and discuss their associations with various diseases and their potentials as drug targets.

Rp3: Ribosome profiling-assisted proteogenomics improves coverage and confidence during microprotein discovery

There has been a dramatic increase in the identification of non-canonical translation and a significant expansion of the protein-coding genome. Among the strategies used to identify unannotated small Open Reading Frames (smORFs) that encode microproteins, Ribosome profiling (Ribo-Seq) is the gold standard for the annotation of novel coding sequences by reporting on smORF translation. In Ribo-Seq, ribosome-protected footprints (RPFs) that map to multiple genomic sites are removed since they cannot be unambiguously assigned to a specific genomic location. Furthermore, RPFs necessarily result in short (25-34 nucleotides) reads, increasing the chance of multi-mapping alignments, such that smORFs residing in these regions cannot be identified by Ribo-Seq. Moreover, it has been challenging to identify protein evidence for Ribo-Seq. To solve this, we developed Rp3, a pipeline that integrates proteogenomics and Ribosome profiling to provide unambiguous evidence for a subset of microproteins missed by current Ribo-Seq pipelines. Here, we show that Rp3 maximizes proteomics detection and confidence of microprotein-encoding smORFs.

Targeting ROS in cancer: rationale and strategies

Reactive oxygen species (ROS) in biological systems are transient but essential molecules that are generated and eliminated by a complex set of delicately balanced molecular machineries. Disruption of redox homeostasis has been associated with various human diseases, especially cancer, in which increased ROS levels are thought to have a major role in tumour development and progression. As such, modulation of cellular redox status by targeting ROS and their regulatory machineries is considered a promising therapeutic strategy for cancer treatment. Recently, there has been major progress in this field, including the discovery of novel redox signalling pathways that affect the metabolism of tumour cells as well as immune cells in the tumour microenvironment, and the intriguing ROS regulation of biomolecular phase separation. Progress has also been made in exploring redox regulation in cancer stem cells, the role of ROS in determining cell fate and new anticancer agents that target ROS. This Review discusses these research developments and their implications for cancer therapy and drug discovery, as well as emerging concepts, paradoxes and future perspectives.

Exploring the Dark Matter of Human Proteome: The Emerging Role of Non-Canonical Open Reading Frame (ncORF) in Cancer Diagnosis, Biology, and Therapy

Cancer develops from abnormal cell growth in the body, causing significant mortalities every year. To date, potent therapeutic approaches have been developed to eradicate tumor cells, but intolerable toxicity and drug resistance can occur in treated patients, limiting the efficiency of existing treatment strategies. Therefore, searching for novel genes critical for cancer progression and therapeutic response is urgently needed for successful cancer therapy. Recent advances in bioinformatics and proteomic techniques have allowed the identification of a novel category of peptides encoded by non-canonical open reading frames (ncORFs) from historically non-coding genomic regions. Surprisingly, many ncORFs express functional microproteins that play a vital role in human cancers. In this review, we provide a comprehensive description of different ncORF types with coding capacity and technological methods in discovering ncORFs among human genomes. We also summarize the carcinogenic role of ncORFs such as pTINCR and HOXB-AS3 in regulating hallmarks of cancer, as well as the roles of ncORFs such as HOXB-AS3 and CIP2A-BP in cancer diagnosis and prognosis. We also discuss how ncORFs such as AKT-174aa and DDUP are involved in anti-cancer drug response and the underestimated potential of ncORFs as therapeutic targets.

Current understanding of functional peptides encoded by lncRNA in cancer

Dysregulated gene expression and imbalance of transcriptional regulation are typical features of cancer. RNA always plays a key role in these processes. Human transcripts contain many RNAs without long open reading frames (ORF, > 100 aa) and that are more than 200 bp in length. They are usually regarded as long non-coding RNA (lncRNA) which play an important role in cancer regulation, including chromatin remodeling, transcriptional regulation, translational regulation and as miRNA sponges. With the advancement of ribosome profiling and sequencing technologies, increasing research evidence revealed that some ORFs in lncRNA can also encode peptides and participate in the regulation of multiple organ tumors, which undoubtedly opens a new chapter in the field of lncRNA and oncology research. In this review, we discuss the biological function of lncRNA in tumors, the current methods to evaluate their coding potential and the role of functional small peptides encoded by lncRNA in cancers. Investigating the small peptides encoded by lncRNA and understanding the regulatory mechanisms of these functional peptides may contribute to a deeper understanding of cancer and the development of new targeted anticancer therapies.

Microproteins encoded by noncanonical ORFs are a major source of tumor-specific antigens in a liver cancer patient meta-cohort

The expression of tumor-specific antigens during cancer progression can trigger an immune response against the tumor. Here, we investigate if microproteins encoded by noncanonical open reading frames (ncORFs) are a relevant source of tumor-specific antigens. We analyze RNA sequencing data from 117 hepatocellular carcinoma (HCC) tumors and matched healthy tissue together with ribosome profiling and immunopeptidomics data. Combining human leukocyte antigen-epitope binding predictions and experimental validation experiments, we conclude that around 40% of the tumor-specific antigens in HCC are likely to be derived from ncORFs, including two peptides that can trigger an immune response in humanized mice. We identify a subset of 33 tumor-specific long noncoding RNAs expressing novel cancer antigens shared by more than 10% of the HCC samples analyzed, which, when combined, cover a large proportion of the patients. The results of the study open avenues for extending the range of anticancer vaccines.

CyCoNP lncRNA establishes cis and trans RNA-RNA interactions to supervise neuron physiology

The combination of morphogenetic and transcription factors together with the synergic aid of noncoding RNAs and their cognate RNA binding proteins contribute to shape motor neurons (MN) identity. Here, we extend the noncoding perspective of human MN, by detailing the molecular and biological activity of CyCoNP (as Cytoplasmic Coordinator of Neural Progenitors) a highly expressed and MN-enriched human lncRNA. Through in silico prediction, in vivo RNA purification and loss of function experiments followed by RNA-sequencing, we found that CyCoNP sustains a specific neuron differentiation program, required for the physiology of both neuroblastoma cells and hiPSC-derived MN, which mainly involves miR-4492 and NCAM1 mRNA. We propose a novel lncRNA-mediated 'dual mode' of action, in which CyCoNP acts in trans as a classical RNA sponge by sequestering miR-4492 from its pro-neuronal targets, including NCAM1 mRNA, and at the same time it plays an additional role in cis by interacting with NCAM1 mRNA and regulating the availability and localization of the miR-4492 in its proximity. These data highlight novel insights into the noncoding RNA-mediated control of human neuron physiology and point out the importance of lncRNA-mediated interactions for the spatial distribution of regulatory molecules.

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.

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.

Shedding light on function of long non-coding RNAs (lncRNAs) in glioblastoma

The brain tumors and especially glioblastoma, are affecting life of many people worldwide and due to their high mortality and morbidity, their treatment is of importance and has gained attention in recent years. The abnormal expression of genes is commonly observed in GBM and long non-coding RNAs (lncRNAs) have demonstrated dysregulation in this tumor. LncRNAs have length more than 200 nucleotides and they have been located in cytoplasm and nucleus. The current review focuses on the role of lncRNAs in GBM. There two types of lncRNAs in GBM including tumor-promoting and tumor-suppressor lncRNAs and overexpression of oncogenic lncRNAs increases progression of GBM. LncRNAs can regulate proliferation, cell cycle arrest and metastasis of GBM cells. Wnt, STAT3 and EZH2 are among the molecular pathways affected by lncRNAs in GBM and for regulating metastasis of GBM cells, these RNA molecules mainly affect EMT mechanism. LncRNAs are involved in drug resistance and can induce resistance of GBM cells to temozolomide chemotherapy. Furthermore, lncRNAs stimulate radio-resistance in GBM cells. LncRNAs increase PD-1 expression to mediate immune evasion. LncRNAs can be considered as diagnostic and prognostic tools in GBM and researchers have developed signature from lncRNAs in GBM.

Comparison of software packages for detecting unannotated translated small open reading frames by Ribo-seq

Accurate and comprehensive annotation of microprotein-coding small open reading frames (smORFs) is critical to our understanding of normal physiology and disease. Empirical identification of translated smORFs is carried out primarily using ribosome profiling (Ribo-seq). While effective, published Ribo-seq datasets can vary drastically in quality and different analysis tools are frequently employed. Here, we examine the impact of these factors on identifying translated smORFs. We compared five commonly used software tools that assess open reading frame translation from Ribo-seq (RibORFv0.1, RibORFv1.0, RiboCode, ORFquant, and Ribo-TISH) and found surprisingly low agreement across all tools. Only ~2% of smORFs were called translated by all five tools, and ~15% by three or more tools when assessing the same high-resolution Ribo-seq dataset. For larger annotated genes, the same analysis showed ~74% agreement across all five tools. We also found that some tools are strongly biased against low-resolution Ribo-seq data, while others are more tolerant. Analyzing Ribo-seq coverage revealed that smORFs detected by more than one tool tend to have higher translation levels and higher fractions of in-frame reads, consistent with what was observed for annotated genes. Together these results support employing multiple tools to identify the most confident microprotein-coding smORFs and choosing the tools based on the quality of the dataset and the planned downstream characterization experiments of the predicted smORFs.

Ribosome decision graphs for the representation of eukaryotic RNA translation complexity

The application of ribosome profiling has revealed an unexpected abundance of translation in addition to that responsible for the synthesis of previously annotated protein-coding regions. Multiple short sequences have been found to be translated within single RNA molecules, within both annotated protein-coding and noncoding regions. The biological significance of this translation is a matter of intensive investigation. However, current schematic or annotation-based representations of mRNA translation generally do not account for the apparent multitude of translated regions within the same molecules. They also do not take into account the stochasticity of the process that allows alternative translations of the same RNA molecules by different ribosomes. There is a need for formal representations of mRNA complexity that would enable the analysis of quantitative information on translation and more accurate models for predicting the phenotypic effects of genetic variants affecting translation. To address this, we developed a conceptually novel abstraction that we term ribosome decision graphs (RDGs). RDGs represent translation as multiple ribosome paths through untranslated and translated mRNA segments. We termed the latter "translons." Nondeterministic events, such as initiation, reinitiation, selenocysteine insertion, or ribosomal frameshifting, are then represented as branching points. This representation allows for an adequate representation of eukaryotic translation complexity and focuses on locations critical for translation regulation. We show how RDGs can be used for depicting translated regions and for analyzing genetic variation and quantitative genome-wide data on translation for characterization of regulatory modulators of translation.

Noncanonical microprotein regulation of immunity

The immune system is highly regulated but, when dysregulated, suboptimal protective or overly robust immune responses can lead to immune-mediated disorders. The genetic and molecular mechanisms of immune regulation are incompletely understood, impeding the development of more precise diagnostics and therapeutics for immune-mediated disorders. Recently, thousands of previously unrecognized noncanonical microprotein genes encoded by small open reading frames have been identified. Many of these microproteins perform critical functions, often in a cell- and context-specific manner. Several microproteins are now known to regulate immunity; however, the vast majority are uncharacterized. Therefore, illuminating what is often referred to as the "dark proteome," may present opportunities to tune immune responses more precisely. Here, we review noncanonical microprotein biology, highlight recently discovered examples regulating immunity, and discuss the potential and challenges of modulating dysregulated immune responses by targeting microproteins.

Microscale marvels: unveiling the macroscopic significance of micropeptides in human health

Non-coding RNA encodes micropeptides from small open reading frames located within the RNA. Interestingly, these micropeptides are involved in a variety of functions within the body. They are emerging as the resolving piece of the puzzle for complex biomolecular signaling pathways within the body. Recent studies highlight the pivotal role of small peptides in regulating important biological processes like DNA repair, gene expression, muscle regeneration, immune responses, etc. On the contrary, altered expression of micropeptides also plays a pivotal role in the progression of various diseases like cardiovascular diseases, neurological disorders and several types of cancer, including colorectal cancer, hepatocellular cancer, lung cancer, etc. This review delves into the dual impact of micropeptides on health and pathology, exploring their pivotal role in preserving normal physiological homeostasis and probing their involvement in the triggering and progression of diseases.

Rules and impacts of nonsense-mediated mRNA decay in the degradation of long noncoding RNAs

Nonsense-mediated mRNA decay (NMD) is a quality-control process that selectively degrades mRNAs having premature termination codon, upstream open reading frame, or unusually long 3'UTR. NMD detects such mRNAs and rapidly degrades them during initial rounds of translation in the eukaryotic cells. Since NMD is a translation-dependent cytoplasmic mRNA surveillance process, the noncoding RNAs were initially believed to be NMD-resistant. The sequence feature-based analysis has revealed that many putative long noncoding RNAs (lncRNAs) have short open reading frames, most of which have translation potential. Subsequent transcriptome-based molecular studies showed an association of a large set of such putative lncRNAs with translating ribosomes, and some of them produce stable and functionally active micropeptides. The translationally active lncRNAs typically have relatively longer and unprotected 3'UTR, which can induce their NMD-dependent degradation. This review defines the mechanism and regulation of NMD-dependent degradation of lncRNAs and its impact on biological processes related to the functions of lncRNAs or their encoded micropeptides. This article is categorized under: RNA Turnover and Surveillance > Turnover/Surveillance Mechanisms RNA Turnover and Surveillance > Regulation of RNA Stability RNA in Disease and Development > RNA in Disease.

Downregulated PDIA3P1 lncRNA Impairs Trophoblast Phenotype by Regulating Snail and SFRP1 in PE

Preeclampsia (PE) manifests as a pregnancy-specific complication arising from compromised placentation characterized by inadequate trophoblast invasion. A growing body of evidence underscores the pivotal involvement of pseudogenes, a subset of long noncoding RNAs, in the pathological processes of PE. This study presents a novel finding, demonstrating a significant downregulation of the pseudogene PDIA3P1 in PE placental tissues compared to normal tissues. In vitro functional assays revealed that suppressing PDIA3P1 hindered trophoblast proliferation, invasion, and migration, concurrently upregulating the expression of secreted frizzled-related protein 1 (SFRP1). Further exploration of the regulatory role of PDIA3P1 in PE, utilizing human trophoblasts, established that PDIA3P1 exerts its function by binding to HuR, thereby enhancing the stability of Snail expression in trophoblasts. Overall, our findings suggest a crucial role for PDIA3P1 in regulating trophoblast properties and contributing to the pathogenesis of PE, offering potential targets for prognosis and therapeutic intervention.

Emerging potential of immunopeptidomics by mass spectrometry in cancer immunotherapy

With significant advances in analytical technologies, research in the field of cancer immunotherapy, such as adoptive T cell therapy, cancer vaccine, and immune checkpoint blockade (ICB), is currently gaining tremendous momentum. Since the efficacy of cancer immunotherapy is recognized only by a minority of patients, more potent tumor-specific antigens (TSAs, also known as neoantigens) and predictive markers for treatment response are of great interest. In cancer immunity, immunopeptides, presented by human leukocyte antigen (HLA) class I, play a role as initiating mediators of immunogenicity. The latest advancement in the interdisciplinary multiomics approach has rapidly enlightened us about the identity of the "dark matter" of cancer and the associated immunopeptides. In this field, mass spectrometry (MS) is a viable option to select because of the naturally processed and actually presented TSA candidates in order to grasp the whole picture of the immunopeptidome. In the past few years the search space has been enlarged by the multiomics approach, the sensitivity of mass spectrometers has been improved, and deep/machine-learning-supported peptide search algorithms have taken immunopeptidomics to the next level. In this review, along with the introduction of key technical advancements in immunopeptidomics, the potential and further directions of immunopeptidomics will be reviewed from the perspective of cancer immunotherapy.

Upstream open reading frames may contain hundreds of novel human exons

Several recent studies have presented evidence that the human gene catalogue should be expanded to include thousands of short open reading frames (ORFs) appearing upstream or downstream of existing protein-coding genes, each of which would comprise an additional bicistronic transcript in humans. Here we explore an alternative hypothesis that would explain the translational and evolutionary evidence for these upstream ORFs without the need to create novel genes or bicistronic transcripts. We examined 2,199 upstream ORFs that have been proposed as high-quality candidates for novel genes, to determine if they could instead represent protein-coding exons that can be added to existing genes. We checked for the conservation of these ORFs in four recently sequenced, high-quality human genomes, and found a large majority (87.8%) to be conserved in all four as expected. We then looked for splicing evidence that would connect each upstream ORF to the downstream protein-coding gene at the same locus, thus creating a novel splicing variant using the upstream ORF as its first exon. These protein coding exon candidates were further evaluated using protein structure predictions of the protein sequences that included the proposed new exons. We determined that 582 out of 2,199 upstream ORFs have strong evidence that they can form protein coding exons that are part of an existing gene, and that the resulting protein is predicted to have similar or better structural quality than the currently annotated isoform.

Structural Features and Physiological Associations of Human 14-3-3ζ Pseudogenes

There are about 14,000 pseudogenes that are mutated or truncated sequences resembling functional parent genes. About two-thirds of pseudogenes are processed, while others are duplicated. Although initially thought dead, emerging studies indicate they have functional and regulatory roles. We study 14-3-3ζ, an adaptor protein that regulates cytokine signaling and inflammatory diseases, including rheumatoid arthritis, cancer, and neurological disorders. To understand how 14-3-3ζ (gene symbol YWHAZ) performs diverse functions, we examined the human genome and identified nine YWHAZ pseudogenes spread across many chromosomes. Unlike the 32 kb exon-to-exon sequence in YWHAZ, all pseudogenes are much shorter and lack introns. Out of six, four YWHAZ exons are highly conserved, but the untranslated region (UTR) shows significant diversity. The putative amino acid sequence of pseudogenes is 78-97% homologous, resulting in striking structural similarities with the parent protein. The OMIM and Decipher database searches revealed chromosomal loci containing pseudogenes are associated with human diseases that overlap with the parent gene. To the best of our knowledge, this is the first report on pseudogenes of the 14-3-3 family protein and their implications for human health. This bioinformatics-based study introduces a new insight into the complexity of 14-3-3ζ's functions in biology.

Widespread stable noncanonical peptides identified by integrated analyses of ribosome profiling and ORF features

Studies have revealed dozens of functional peptides in putative 'noncoding' regions and raised the question of how many proteins are encoded by noncanonical open reading frames (ORFs). Here, we comprehensively annotate genome-wide translated ORFs across five eukaryotes (human, mouse, zebrafish, worm, and yeast) by analyzing ribosome profiling data. We develop a logistic regression model named PepScore based on ORF features (expected length, encoded domain, and conservation) to calculate the probability that the encoded peptide is stable in humans. Systematic ectopic expression validates PepScore and shows that stable complex-associating microproteins can be encoded in 5'/3' untranslated regions and overlapping coding regions of mRNAs besides annotated noncoding RNAs. Stable noncanonical proteins follow conventional rules and localize to different subcellular compartments. Inhibition of proteasomal/lysosomal degradation pathways can stabilize some peptides especially those with moderate PepScores, but cannot rescue the expression of short ones with low PepScores suggesting they are directly degraded by cellular proteases. The majority of human noncanonical peptides with high PepScores show longer lengths but low conservation across species/mammals, and hundreds contain trait-associated genetic variants. Our study presents a statistical framework to identify stable noncanonical peptides in the genome and provides a valuable resource for functional characterization of noncanonical translation during development and disease.

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.

Variants in the first methionine of RAD51C are homologous recombination proficient due to an alternative start site

In the 20+ years since the discovery of RAD51C, scientists have been perplexed as to how missense variants in this tumor suppressor gene impacts its function and pathogenicity. With a strong connection to breast and ovarian cancer, classifying these variants as pathogenic or benign aids in the diagnosis and treatment of patients with RAD51C variants. In particular, variants at translational starts sites are disruptive as they prevent protein expression. These variants are often classified as pathogenic, unless an alternative translational start is shown to produce a functional isoform to rescue protein expression. In this study, we utilized the ribosome profiling database GWIPS-VIZ to identify two active translational start sites in human RAD51C at methionine one and methionine ten. This second translational start at methionine ten is both conserved in 97 % of mammals and is the sole translational start in 80 % of mammals. Missense variants at either methionine have been identified in 47 individuals, preventing expression from one of these two start sites. Therefore, we stably expressed both wildtype isoforms, as well as the RAD51C M1 and M10 variants in a RAD51C CRISPR/Cas9 knockout U2OS cell and compared their homologous recombination function. Surprisingly, we find that expression of human RAD51C from either start site can equivalently rescue homologous recombination of RAD51C CRISPR/Cas9 knockout U2OS cells through a sister chromatid recombination assay. Similarly, each of our RAD51C CRISPR/Cas9 KO cells stably complemented with RAD51C missense variants at either M1 or M10 are homologous recombination proficient. Together, our data demonstrate that RAD51C has two translational start sites and that variants in either methionine result in homologous recombination proficiency. With this critical discovery, individuals with variants at M1 will be more accurately informed of their cancer risk upon reclassification of these variants.

The Ribosome Hypothesis: Decoding Mood Disorder Complexity

Several types of mood disorders lie along a continuum, with nebulous boundaries between them. Understanding the mechanisms that contribute to mood disorder complexity is critical for effective treatment. However, present treatments are largely centered around neurotransmission and receptor-based hypotheses, which, given the high instance of treatment resistance, fail to adequately explain the complexities of mood disorders. In this opinion piece, based on our recent results, we propose a ribosome hypothesis of mood disorders. We suggest that any hypothesis seeking to explain the diverse nature of mood disorders must incorporate infrastructure diversity that results in a wide range of effects. Ribosomes, with their mobility across neurites and complex composition, have the potential to become specialized during stress; thus, ribosome diversity and dysregulation are well suited to explaining mood disorder complexity. Here, we first establish a framework connecting ribosomes to the current state of knowledge associated with mood disorders. Then, we describe the potential mechanisms through which ribosomes could homeostatically regulate systems to manifest diverse mood disorder phenotypes and discuss approaches for substantiating the ribosome hypothesis. Investigating these mechanisms as therapeutic targets holds promise for transdiagnostic avenues targeting mood disorders.

Single-cell profiling and functional screening reveal crucial roles for lncRNAs in the epidermal re-epithelialization of human acute wounds

Objectives

Re-epithelialization is an important physiological process for repairing skin barrier function during wound healing. It is primarily mediated by coordinated migration, proliferation, and differentiation of keratinocytes. Long noncoding RNAs (lncRNAs) are essential components of the noncoding genome and participate in various biological processes; however, their expression profiles and function in re-epithelialization during wound healing have not been established.

Methods

We investigated the distribution of lncRNAs during wound re-epithelialization by comparing the genomic profiles of uninjured skin and acute wound (AW) from healthy donors. We performed functional screening of differentially expressed lncRNAs to identify the important lncRNAs for re-epithelialization.

Results

The expression of multiple lncRNAs is changed during human wound re-epithelialization process. We identified VIM-AS1, SMAD5-AS1, and LINC02581 as critical regulators involved in keratinocyte migration, proliferation, and differentiation, respectively.

Conclusion

LncRNAs play crucial regulatory roles in wound re-epithelialization. We established lncRNA expression profile in human acute wounds compared with intact skin, offering valuable insights into the physiological mechanisms underlying wound healing and potential therapeutic targets.

No country for old methods: New tools for studying microproteins

Microproteins encoded by small open reading frames (sORFs) have emerged as a fascinating frontier in genomics. Traditionally overlooked due to their small size, recent technological advancements such as ribosome profiling, mass spectrometry-based strategies and advanced computational approaches have led to the annotation of more than 7000 sORFs in the human genome. Despite the vast progress, only a tiny portion of these microproteins have been characterized and an important challenge in the field lies in identifying functionally relevant microproteins and understanding their role in different cellular contexts. In this review, we explore the recent advancements in sORF research, focusing on the new methodologies and computational approaches that have facilitated their identification and functional characterization. Leveraging these new tools hold great promise for dissecting the diverse cellular roles of microproteins and will ultimately pave the way for understanding their role in the pathogenesis of diseases and identifying new therapeutic targets.

Making sense of mRNA translational "noise"

The importance of translation fidelity has been apparent since the discovery of genetic code. It is commonly believed that translation deviating from the main coding region is to be avoided at all times inside cells. However, ribosome profiling and mass spectrometry have revealed pervasive noncanonical translation. Both the scope and origin of translational "noise" are just beginning to be appreciated. Although largely overlooked, those translational "noises" are associated with a wide range of cellular functions, such as producing unannotated protein products. Furthermore, the dynamic nature of translational "noise" is responsive to stress conditions, highlighting the beneficial effect of translational "noise" in stress adaptation. Mechanistic investigation of translational "noise" will provide better insight into the mechanisms of translational regulation. Ultimately, they are not "noise" at all but represent a signature of cellular activities under pathophysiological conditions. Deciphering translational "noise" holds the therapeutic and diagnostic potential in a wide spectrum of human diseases.

A method for evaluating of RNA's coding potential using the interaction effects of open reading frames and high-energy scalograms

The identification and function determination of long non-coding RNAs (lncRNAs) can help to better understand the transcriptional regulation in both normal development and disease pathology, thereby demanding methods to distinguish them from protein-coding (pcRNAs) after obtaining sequencing data. Many algorithms based on the statistical, structural, physical, and chemical properties of the sequences have been developed for evaluating the coding potential of RNA to distinguish them. In order to design common features that do not rely on hyperparameter tuning and optimization and are evaluated accurately, we designed a series of features from the effects of open reading frames (ORFs) on their mutual interactions and with the electrical intensity of sequence sites to further improve the screening accuracy. Finally, the single model constructed from our designed features meets the strong classifier criteria, where the accuracy is between 82% and 89%, and the prediction accuracy of the model constructed after combining the auxiliary features equal to or exceed some best classification tools. Moreover, our method does not require special hyper-parameter tuning operations and is species insensitive compared to other methods, which means this method can be easily applied to a wide range of species. Also, we find some correlations between the features, which provides some reference for follow-up studies.

Comparison of software packages for detecting unannotated translated small open reading frames by Ribo-seq

Accurate and comprehensive annotation of microprotein-coding small open reading frames (smORFs) is critical to our understanding of normal physiology and disease. Empirical identification of translated smORFs is carried out primarily using ribosome profiling (Ribo-seq). While effective, published Ribo-seq datasets can vary drastically in quality and different analysis tools are frequently employed. Here, we examine the impact of these factors on identifying translated smORFs. We compared five commonly used software tools that assess ORF translation from Ribo-seq (RibORFv0.1, RibORFv1.0, RiboCode, ORFquant, and Ribo-TISH), and found surprisingly low agreement across all tools. Only ~2% of smORFs were called translated by all five tools and ~15% by three or more tools when assessing the same high-resolution Ribo-seq dataset. For larger annotated genes, the same analysis showed ~72% agreement across all five tools. We also found that some tools are strongly biased against low-resolution Ribo-seq data, while others are more tolerant. Analyzing Ribo-seq coverage as a proxy for translation levels revealed that highly translated smORFs are more likely to be detected by more than one tool. Together these results support employing multiple tools to identify the most confident microprotein-coding smORFs, and choosing the tools based on the quality of the dataset and planned downstream characterization experiments of predicted smORFs.

Integrated workflow for discovery of microprotein-coding small open reading frames

Small open reading frame (smORF)-encoded microproteins, proteins containing less than 100-150 amino acids, are an emerging class of functional biomolecules. Here, we present a protocol for identifying translated smORFs in mammalian systems genome wide. We describe steps for generation of ribosome profiling (Ribo-seq) data, in silico translation of a transcriptome assembly to create an ORF database, and computational analysis of Ribo-seq to score individual smORFs for translation. Identification of translated smORFs is the first step to studying the functions of microproteins. For complete details on the use and execution of this protocol, please refer to Martinez et al.1.

Micropeptides: origins, identification, and potential role in metabolism-related diseases

With the development of modern sequencing techniques and bioinformatics, genomes that were once thought to be noncoding have been found to encode abundant functional micropeptides (miPs), a kind of small polypeptides. Although miPs are difficult to analyze and identify, a number of studies have begun to focus on them. More and more miPs have been revealed as essential for energy metabolism homeostasis, immune regulation, and tumor growth and development. Many reports have shown that miPs are especially essential for regulating glucose and lipid metabolism and regulating mitochondrial function. MiPs are also involved in the progression of related diseases. This paper reviews the sources and identification of miPs, as well as the functional significance of miPs for metabolism-related diseases, with the aim of revealing their potential clinical applications.

Protein-coding potential of non-canonical open reading frames in human transcriptome

In recent years, proteogenomics and ribosome profiling studies have identified a large number of proteins encoded by noncoding regions in the human genome. They are encoded by small open reading frames (sORFs) in the untranslated regions (UTRs) of mRNAs and long non-coding RNAs (lncRNAs). These sORF encoded proteins (SEPs) are often <150AA and show poor evolutionary conservation. A subset of them have been functionally characterized and shown to play an important role in fundamental biological processes including cardiac and muscle function, DNA repair, embryonic development and various human diseases. How many novel protein-coding regions exist in the human genome and what fraction of them are functionally important remains a mystery. In this review, we discuss current progress in unraveling SEPs, approaches used for their identification, their limitations and reliability of these identifications. We also discuss functionally characterized SEPs and their involvement in various biological processes and diseases. Lastly, we provide insights into their distinctive features compared to canonical proteins and challenges associated with annotating these in protein reference databases.

CRISPR-Cas9-based functional interrogation of unconventional translatome reveals human cancer dependency on cryptic non-canonical open reading frames

Emerging evidence suggests that cryptic translation beyond the annotated translatome produces proteins with developmental or physiological functions. However, functions of cryptic non-canonical open reading frames (ORFs) in cancer remain largely unknown. To fill this gap and systematically identify colorectal cancer (CRC) dependency on non-canonical ORFs, we apply an integrative multiomic strategy, combining ribosome profiling and a CRISPR-Cas9 knockout screen with large-scale analysis of molecular and clinical data. Many such ORFs are upregulated in CRC compared to normal tissues and are associated with clinically relevant molecular subtypes. We confirm the in vivo tumor-promoting function of the microprotein SMIMP, encoded by a primate-specific, long noncoding RNA, the expression of which is associated with poor prognosis in CRC, is low in normal tissues and is specifically elevated in CRC and several other cancer types. Mechanistically, SMIMP interacts with the ATPase-forming domains of SMC1A, the core subunit of the cohesin complex, and facilitates SMC1A binding to cis-regulatory elements to promote epigenetic repression of the tumor-suppressive cell cycle regulators encoded by CDKN1A and CDKN2B. Thus, our study reveals a cryptic microprotein as an important component of cohesin-mediated gene regulation and suggests that the 'dark' proteome, encoded by cryptic non-canonical ORFs, may contain potential therapeutic or diagnostic targets.

Interchromosomal Colocalization with Parental Genes Is Linked to the Function and Evolution of Mammalian Retrocopies

Retrocopies are gene duplicates arising from reverse transcription of mature mRNA transcripts and their insertion back into the genome. While long being regarded as processed pseudogenes, more and more functional retrocopies have been discovered. How the stripped-down retrocopies recover expression capability and become functional paralogs continually intrigues evolutionary biologists. Here, we investigated the function and evolution of retrocopies in the context of 3D genome organization. By mapping retrocopy-parent pairs onto sequencing-based and imaging-based chromatin contact maps in human and mouse cell lines and onto Hi-C interaction maps in 5 other mammals, we found that retrocopies and their parental genes show a higher-than-expected interchromosomal colocalization frequency. The spatial interactions between retrocopies and parental genes occur frequently at loci in active subcompartments and near nuclear speckles. Accordingly, colocalized retrocopies are more actively transcribed and translated and are more evolutionarily conserved than noncolocalized ones. The active transcription of colocalized retrocopies may result from their permissive epigenetic environment and shared regulatory elements with parental genes. Population genetic analysis of retroposed gene copy number variants in human populations revealed that retrocopy insertions are not entirely random in regard to interchromosomal interactions and that colocalized retroposed gene copy number variants are more likely to reach high frequencies, suggesting that both insertion bias and natural selection contribute to the colocalization of retrocopy-parent pairs. Further dissection implies that reduced selection efficacy, rather than positive selection, contributes to the elevated allele frequency of colocalized retroposed gene copy number variants. Overall, our results hint a role of interchromosomal colocalization in the "resurrection" of initially neutral retrocopies.

Ribosome Decision Graphs for the Representation of Eukaryotic RNA Translation Complexity

The application of ribosome profiling has revealed an unexpected abundance of translation in addition to that responsible for the synthesis of previously annotated protein-coding regions. Multiple short sequences have been found to be translated within single RNA molecules, both within annotated protein-coding and non-coding regions. The biological significance of this translation is a matter of intensive investigation. However, current schematic or annotation-based representations of mRNA translation generally do not account for the apparent multitude of translated regions within the same molecules. They also do not take into account the stochasticity of the process that allows alternative translations of the same RNA molecules by different ribosomes. There is a need for formal representations of mRNA complexity that would enable the analysis of quantitative information on translation and more accurate models for predicting the phenotypic effects of genetic variants affecting translation. To address this, we developed a conceptually novel abstraction that we term Ribosome Decision Graphs (RDGs). RDGs represent translation as multiple ribosome paths through untranslated and translated mRNA segments. We termed the later 'translons'. Non-deterministic events, such as initiation, re-initiation, selenocysteine insertion or ribosomal frameshifting are then represented as branching points. This representation allows for an adequate representation of eukaryotic translation complexity and focuses on locations critical for translation regulation. We show how RDGs can be used for depicting translated regions, analysis of genetic variation and quantitative genome-wide data on translation for characterisation of regulatory modulators of translation.

LncRNA-encoded peptides: unveiling their significance in cardiovascular physiology and pathology-current research insights

Long non-coding RNAs (lncRNAs), which are RNA transcripts exceeding 200 nucleotides were believed to lack any protein-coding capacity. But advancements in -omics technology have revealed that some lncRNAs have small open reading frames (sORFs) that can be translated by ribosomes to encode peptides, some of which have important biological functions. These encoded peptides subserve important biological functions by interacting with their targets to modulate transcriptional or signalling axes, thereby enhancing or suppressing cardiovascular disease (CVD) occurrence and progression. In this review, we summarize what is known about the research strategy of lncRNA-encoded peptides, mainly comprising predictive websites/tools and experimental methods that have been widely used for prediction, identification, and validation. More importantly, we have compiled a list of lncRNA- encoded peptides, with a focus on those that play significant roles in cardiovascular physiology and pathology, including ENSRNOT (RNO)-sORF6/RNO-sORF7/RNO-sORF8, dwarf open reading frame (DOWRF), myoregulin (NLN), etc. Additionally, we have outlined the functions and mechanisms of these peptides in cardiovascular physiology and pathology, such as cardiomyocyte hypertrophy, myocardial contraction, myocardial infarction, and vascular remodelling. Finally, an overview of the existing challenges and potential future developments in the realm of lncRNA-encoded peptides was provided, with consideration given to prospective avenues for further research. Given that many lncRNA-encoded peptides have not been functionally annotated yet, their application in CVD diagnosis and treatment still requires further research.

Readthrough isoform of aquaporin-4 (AQP4) as a therapeutic target for Alzheimer's disease and other proteinopathies

The glymphatic system is a crucial component in preserving brain homeostasis by facilitating waste clearance from the central nervous system (CNS). Aquaporin-4 (AQP4) water channels facilitate the continuous interchange between cerebrospinal fluid and brain interstitial fluid by convective flow movement. This flow is responsible for guiding proteins and metabolites away from the CNS. Proteinopathies are neurological conditions characterized by the accumulation of aggregated proteins or peptides in the brain. In Alzheimer's disease (AD), the deposition of amyloid-β (Aβ) peptides causes the formation of senile plaques. This accumulation has been hypothesized to be a result of the imbalance between Aβ production and clearance. Recent studies have shown that an extended form of AQP4 increases Aβ clearance from the brain. In this mini-review, we present a summary of these findings and explore the potential for future therapeutic strategies aiming to boost waste clearance in AD.

The Integration of Proteogenomics and Ribosome Profiling Circumvents Key Limitations to Increase the Coverage and Confidence of Novel Microproteins

There has been a dramatic increase in the identification of non-conical translation and a significant expansion of the protein-coding genome and proteome. Among the strategies used to identify novel small ORFs (smORFs), Ribosome profiling (Ribo-Seq) is the gold standard for the annotation of novel coding sequences by reporting on smORF translation. In Ribo-Seq, ribosome-protected footprints (RPFs) that map to multiple sites in the genome are computationally removed since they cannot unambiguously be assigned to a specific genomic location, or to a specific transcript in the case of multiple isoforms. Furthermore, RPFs necessarily result in short (25-34 nucleotides) reads, increasing the chance of ambiguous and multi-mapping alignments, such that smORFs that reside in these regions cannot be identified by Ribo-Seq. Here, we show that the inclusion of proteogenomics to create a Ribosome Profiling and Proteogenomics Pipeline (RP3) bypasses this limitation to identify a group of microprotein-encoding smORFs that are missed by current Ribo-Seq pipelines. Moreover, we show that the microproteins identified by RP3 have different sequence compositions from the ones identified by Ribo-Seq-only pipelines, which can affect proteomics identification. In aggregate, the development of RP3 maximizes the detection and confidence of protein-encoding smORFs and microproteins.

Current perspectives on mass spectrometry-based immunopeptidomics: the computational angle to tumor antigen discovery

Identification of tumor antigens presented by the human leucocyte antigen (HLA) molecules is essential for the design of effective and safe cancer immunotherapies that rely on T cell recognition and killing of tumor cells. Mass spectrometry (MS)-based immunopeptidomics enables high-throughput, direct identification of HLA-bound peptides from a variety of cell lines, tumor tissues, and healthy tissues. It involves immunoaffinity purification of HLA complexes followed by MS profiling of the extracted peptides using data-dependent acquisition, data-independent acquisition, or targeted approaches. By incorporating DNA, RNA, and ribosome sequencing data into immunopeptidomics data analysis, the proteogenomic approach provides a powerful means for identifying tumor antigens encoded within the canonical open reading frames of annotated coding genes and non-canonical tumor antigens derived from presumably non-coding regions of our genome. We discuss emerging computational challenges in immunopeptidomics data analysis and tumor antigen identification, highlighting key considerations in the proteogenomics-based approach, including accurate DNA, RNA and ribosomal sequencing data analysis, careful incorporation of predicted novel protein sequences into reference protein database, special quality control in MS data analysis due to the expanded and heterogeneous search space, cancer-specificity determination, and immunogenicity prediction. The advancements in technology and computation is continually enabling us to identify tumor antigens with higher sensitivity and accuracy, paving the way toward the development of more effective cancer immunotherapies.

Precision medicine in the era of multi-omics: can the data tsunami guide rational treatment decision?

Precision medicine for cancer is rapidly moving to an approach that integrates multiple dimensions of the biology in order to model mechanisms of cancer progression in each patient. The discovery of multiple drivers per tumor challenges medical decision that faces several treatment options. Drug sensitivity depends on the actionability of the target, its clonal or subclonal origin and coexisting genomic alterations. Sequencing has revealed a large diversity of drivers emerging at treatment failure, which are potential targets for clinical trials or drug repurposing. To effectively prioritize therapies, it is essential to rank genomic alterations based on their proven actionability. Moving beyond primary drivers, the future of precision medicine necessitates acknowledging the intricate spatial and temporal heterogeneity inherent in cancer. The advent of abundant complex biological data will make artificial intelligence algorithms indispensable for thorough analysis. Here, we will discuss the advancements brought by the use of high-throughput genomics, the advantages and limitations of precision medicine studies and future perspectives in this field.

Improving deep models of protein-coding potential with a Fourier-transform architecture and machine translation task

Ribosomes are information-processing macromolecular machines that integrate complex sequence patterns in messenger RNA (mRNA) transcripts to synthesize proteins. Studies of the sequence features that distinguish mRNAs from long noncoding RNAs (lncRNAs) may yield insight into the information that directs and regulates translation. Computational methods for calculating protein-coding potential are important for distinguishing mRNAs from lncRNAs during genome annotation, but most machine learning methods for this task rely on previously known rules to define features. Sequence-to-sequence (seq2seq) models, particularly ones using transformer networks, have proven capable of learning complex grammatical relationships between words to perform natural language translation. Seeking to leverage these advancements in the biological domain, we present a seq2seq formulation for predicting protein-coding potential with deep neural networks and demonstrate that simultaneously learning translation from RNA to protein improves classification performance relative to a classification-only training objective. Inspired by classical signal processing methods for gene discovery and Fourier-based image-processing neural networks, we introduce LocalFilterNet (LFNet). LFNet is a network architecture with an inductive bias for modeling the three-nucleotide periodicity apparent in coding sequences. We incorporate LFNet within an encoder-decoder framework to test whether the translation task improves the classification of transcripts and the interpretation of their sequence features. We use the resulting model to compute nucleotide-resolution importance scores, revealing sequence patterns that could assist the cellular machinery in distinguishing mRNAs and lncRNAs. Finally, we develop a novel approach for estimating mutation effects from Integrated Gradients, a backpropagation-based feature attribution, and characterize the difficulty of efficient approximations in this setting.

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."

Shining in the dark: the big world of small peptides in plants

Small peptides represent a subset of dark matter in plant proteomes. Through differential expression patterns and modes of action, small peptides act as important regulators of plant growth and development. Over the past 20 years, many small peptides have been identified due to technical advances in genome sequencing, bioinformatics, and chemical biology. In this article, we summarize the classification of plant small peptides and experimental strategies used to identify them as well as their potential use in agronomic breeding. We review the biological functions and molecular mechanisms of small peptides in plants, discuss current problems in small peptide research and highlight future research directions in this field. Our review provides crucial insight into small peptides in plants and will contribute to a better understanding of their potential roles in biotechnology and agriculture.

Pseudogenes in Cancer: State of the Art

Pseudogenes are duplicates of protein-coding genes that have accumulated multiple detrimental alterations, rendering them unable to produce the protein they encode. Initially disregarded as "junk DNA" due to their perceived lack of functionality, research on their biological roles has been hindered by this assumption. Nevertheless, recent focus has shifted towards these molecules due to their abnormal expression in cancer phenotypes. In this review, our objective is to provide a thorough overview of the current understanding of pseudogene formation, the mechanisms governing their expression, and the roles they may play in promoting tumorigenesis.

Discovery of putative long non-coding RNAs expressed in the eyes of Astyanax mexicanus (Actinopterygii: Characidae)

Astyanax mexicanus is a well-known model species, that has two morphotypes, cavefish, from subterranean rivers and surface fish, from surface rivers. They are morphologically distinct due to many troglomorphic traits in the cavefish, such as the absence of eyes. Most studies on A. mexicanus are focused on eye development and protein-coding genes involved in the process. However, lncRNAs did not get the same attention and very little is known about them. This study aimed to fill this knowledge gap, identifying, describing, classifying, and annotating lncRNAs expressed in the embryo's eye tissue of cavefish and surface fish. To do so, we constructed a concise workflow to assemble and evaluate transcriptomes, annotate protein-coding genes, ncRNAs families, predict the coding potential, identify putative lncRNAs, map them and predict interactions. This approach resulted in the identification of 33,069 and 19,493 putative lncRNAs respectively mapped in cavefish and surface fish. Thousands of these lncRNAs were annotated and identified as conserved in human and several species of fish. Hundreds of them were validated in silico, through ESTs. We identified lncRNAs associated with genes related to eye development. This is the case of a few lncRNAs associated with sox2, which we suggest being isomorphs of the SOX2-OT, a lncRNA that can regulate the expression of sox2. This work is one of the first studies to focus on the description of lncRNAs in A. mexicanus, highlighting several lncRNA targets and opening an important precedent for future studies focusing on lncRNAs expressed in A. mexicanus.

Autonomous action and cooperativity between the ONECUT2 transcription factor and its 3' untranslated region

The transcription factor ONECUT2 (OC2) is a master transcriptional regulator operating in metastatic castration-resistant prostate cancer that suppresses androgen receptor activity and promotes neural differentiation and tumor cell survival. OC2 mRNA possesses an unusually long (14,575 nt), evolutionarily conserved 3' untranslated region (3' UTR) with many microRNA binding sites, including up to 26 miR-9 sites. This is notable because miR-9 targets many of the same genes regulated by the OC2 protein. Paradoxically, OC2 expression is high in tissues with high miR-9 expression. The length and complex secondary structure of OC2 mRNA suggests that it is a potent master competing endogenous RNA (ceRNA) capable of sequestering miRNAs. Here, we describe a novel role for OC2 3' UTR in lethal prostate cancer consistent with a function as a ceRNA. A plausible ceRNA network in OC2-driven tumors was constructed computationally and then confirmed in prostate cancer cell lines. Genes regulated by OC2 3' UTR exhibited high overlap (up to 45%) with genes driven by the overexpression of the OC2 protein in the absence of 3' UTR, indicating a cooperative functional relationship between the OC2 protein and its 3' UTR. These overlapping networks suggest an evolutionarily conserved mechanism to reinforce OC2 transcription by protection of OC2-regulated mRNAs from miRNA suppression. Both the protein and 3' UTR showed increased polycomb-repressive complex activity. The expression of OC2 3' UTR mRNA alone (without protein) dramatically increased the metastatic potential by in vitro assays. Additionally, OC2 3' UTR increased the expression of Aldo-Keto reductase and UDP-glucuronyl transferase family genes responsible for altering the androgen synthesis pathway. ONECUT2 represents the first-described dual-modality transcript that operates as both a key transcription factor driving castration-resistant prostate cancer and a master ceRNA that promotes and protects the same transcriptional network.

Principles, mechanisms, and biological implications of translation termination-reinitiation

The gene expression pathway from DNA sequence to functional protein is not as straightforward as simple depictions of the central dogma might suggest. Each step is highly regulated, with complex and only partially understood molecular mechanisms at play. Translation is one step where the "one gene-one protein" paradigm breaks down, as often a single mature eukaryotic mRNA leads to more than one protein product. One way this occurs is through translation reinitiation, in which a ribosome starts making protein from one initiation site, translates until it terminates at a stop codon, but then escapes normal recycling steps and subsequently reinitiates at a different downstream site. This process is now recognized as both important and widespread, but we are only beginning to understand the interplay of factors involved in termination, recycling, and initiation that cause reinitiation events. There appear to be several ways to subvert recycling to achieve productive reinitiation, different types of stresses or signals that trigger this process, and the mechanism may depend in part on where the event occurs in the body of an mRNA. This perspective reviews the unique characteristics and mechanisms of reinitiation events, highlights the similarities and differences between three major scenarios of reinitiation, and raises outstanding questions that are promising avenues for future research.

The Talented LncRNAs: Meshing into Transcriptional Regulatory Networks in Cancer

As a group of diseases characterized by uncontrollable cell growth, cancer is highly multifaceted in how it overrides checkpoints controlling proliferation. Amongst the regulators of these checkpoints, long non-coding RNAs (lncRNAs) can have key roles in why natural biological processes go haywire. LncRNAs represent a large class of regulatory transcripts that can localize anywhere in cells. They were found to affect gene expression on many levels from transcription to mRNA translation and even protein stability. LncRNA participation in such control mechanisms can depend on cell context, with given transcripts sometimes acting as oncogenes or tumor suppressors. Importantly, the tissue-specificity and low expression levels of lncRNAs make them attractive therapeutic targets or biomarkers. Here, we review the various cellular processes affected by lncRNAs and outline molecular strategies they use to control gene expression, particularly in cancer and in relation to transcription factors.

CrypticProteinDB: an integrated database of proteome and immunopeptidome derived non-canonical cancer proteins

Translated non-canonical proteins derived from noncoding regions or alternative open reading frames (ORFs) can contribute to critical and diverse cellular processes. In the context of cancer, they also represent an under-appreciated source of targets for cancer immunotherapy through their tumor-enriched expression or by harboring somatic mutations that produce neoantigens. Here, we introduce the largest integration and proteogenomic analysis of novel peptides to assess the prevalence of non-canonical ORFs (ncORFs) in more than 900 patient proteomes and 26 immunopeptidome datasets across 14 cancer types. The integrative proteogenomic analysis of whole-cell proteomes and immunopeptidomes revealed peptide support for a nonredundant set of 9760 upstream, downstream, and out-of-frame ncORFs in protein coding genes and 12811 in noncoding RNAs. Notably, 6486 ncORFs were derived from differentially expressed genes and 340 were ubiquitously translated across eight or more cancers. The analysis also led to the discovery of thirty-four epitopes and eight neoantigens from non-canonical proteins in two cohorts as novel cancer immunotargets. Collectively, our analysis integrated both bottom-up proteogenomic and targeted peptide validation to illustrate the prevalence of translated non-canonical proteins in cancer and to provide a resource for the prioritization of novel proteins supported by proteomic, immunopeptidomic, genomic and transcriptomic data, available at https://www.maherlab.com/crypticproteindb.