Conserved regions in long non-coding RNAs contain abundant translation and protein-RNA interaction signatures

Alzheimer's disease and microorganisms: the non-coding RNAs crosstalk

Alzheimer's disease (AD) is a complex, multifactorial disorder, influenced by a multitude of variables ranging from genetic factors, age, and head injuries to vascular diseases, infections, and various other environmental and demographic determinants. Among the environmental factors, the role of the microbiome in the genesis of neurodegenerative disorders (NDs) is gaining increased recognition. This paradigm shift is substantiated by an extensive body of scientific literature, which underscores the significant contributions of microorganisms, encompassing viruses and gut-derived bacteria, to the pathogenesis of AD. The mechanism by which microbial infection exerts its influence on AD hinges primarily on inflammation. Neuroinflammation, activated in response to microbial infections, acts as a defense mechanism for the brain but can inadvertently lead to unexpected neuropathological perturbations, ultimately contributing to NDs. Given the ongoing uncertainty surrounding the genetic factors underpinning ND, comprehensive investigations into environmental factors, particularly the microbiome and viral agents, are imperative. Recent advances in neuroscientific research have unveiled the pivotal role of non-coding RNAs (ncRNAs) in orchestrating various pathways integral to neurodegenerative pathologies. While the upstream regulators governing the pathological manifestations of microorganisms remain elusive, an in-depth exploration of the nuanced role of ncRNAs holds promise for the development of prospective therapeutic interventions. This review aims to elucidate the pivotal role of ncRNAs as master modulators in the realm of neurodegenerative conditions, with a specific focus on Alzheimer's disease.

Functional inference of long non-coding RNAs through exploration of highly conserved regions

Background: Long non-coding RNAs (lncRNAs), which are generally less functionally characterized or less annotated, evolve more rapidly than mRNAs and substantially possess fewer sequence conservation patterns than protein-coding genes across divergent species. People assume that the functional inference could be conducted on the evolutionarily conserved long non-coding RNAs as they are most likely to be functional. In the past decades, substantial progress has been made in discussions on the evolutionary conservation of non-coding genomic regions from multiple perspectives. However, understanding their conservation and the functions associated with sequence conservation in relation to further corresponding phenotypic variability or disorders still remains incomplete. Results: Accordingly, we determined a highly conserved region (HCR) to verify the sequence conservation among long non-coding RNAs and systematically profiled homologous long non-coding RNA clusters in humans and mice based on the detection of highly conserved regions. Moreover, according to homolog clustering, we explored the potential function inference via highly conserved regions on representative long non-coding RNAs. On lncRNA XACT, we investigated the potential functional competence between XACT and lncRNA XIST by recruiting miRNA-29a, regulating the downstream target genes. In addition, on lncRNA LINC00461, we examined the interaction relationship between LINC00461 and SND1. This interaction or association may be perturbed during the progression of glioma. In addition, we have constructed a website with user-friendly web interfaces for searching, analyzing, and downloading to present the homologous clusters of humans and mice. Conclusion: Collectively, homolog clustering via the highly conserved region definition and detection on long non-coding RNAs, as well as the functional explorations on representative sequences in our research, would provide new evidence for the potential function of long non-coding RNAs. Our results on the remarkable roles of long non-coding RNAs would presumably provide a new theoretical basis and candidate diagnostic indicators for tumors.

A proinflammatory long noncoding RNA Lncenc1 regulates inflammasome activation in macrophage

Mammalian genomes encode thousands of long noncoding RNAs (lncRNAs). LncRNAs are extensively expressed in various immune cells. The lncRNAs have been reported to be involved in diverse biological processes, including the regulation of gene expression, dosage compensation, and genomic imprinting. However, very little research has been conducted to explore how they alter innate immune responses during host-pathogen interactions. In this study, we found that a lncRNA, named long noncoding RNA, embryonic stem cells expressed 1 (Lncenc1), was strikingly increased in mouse lungs after gram-negative (G-) bacterial infection or exposure to lipopolysaccharides (LPS). Interestingly, our data indicated that Lncenc1 was upregulated in macrophages but not in primary epithelial cells (PECs) or polymorphonuclear leukocytes (PMN). The upregulation was also observed in human THP-1 and U937 macrophages. Besides, Lncenc1 was highly induced during ATP-induced inflammasome activation. Functionally, Lncenc1 showed proinflammatory effects in macrophages as demonstrated by increased expressions of cytokine and chemokines, as well as enhanced NF-κB promoter activity. Overexpression of Lncenc1 promoted the releases of IL-1β and IL-18, and Caspase-1 activity in macrophages, suggesting a role in inflammasome activation. Consistently, knockdown of Lncenc1 inhibited inflammasome activation in LPS-treated macrophages. Moreover, knockdown of Lncenc1 using antisense oligo (ASO)-loaded exosomes (EXO) attenuated LPS-induced lung inflammation in mice. Similarly, Lncenc1 deficiency protects mice from bacteria-induced lung injury and inflammasome activation. Taken together, our work identified Lncenc1 as a modulator of inflammasome activation in macrophages during bacterial infection. Our study suggested that Lncenc1 could serve as a therapeutic target for lung inflammation and injury.

Evolutionary origins and interactomes of human, young microproteins and small peptides translated from short open reading frames

All species continuously evolve short open reading frames (sORFs) that can be templated for protein synthesis and may provide raw materials for evolutionary adaptation. We analyzed the evolutionary origins of 7,264 recently cataloged human sORFs and found that most were evolutionarily young and had emerged de novo. We additionally identified 221 previously missed sORFs potentially translated into peptides of up to 15 amino acids-all of which are smaller than the smallest human microprotein annotated to date. To investigate the bioactivity of sORF-encoded small peptides and young microproteins, we subjected 266 candidates to a mass-spectrometry-based interactome screen with motif resolution. Based on these interactomes and additional cellular assays, we can associate several candidates with mRNA splicing, translational regulation, and endocytosis. Our work provides insights into the evolutionary origins and interaction potential of young and small proteins, thereby helping to elucidate this underexplored territory of the human proteome.

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.

Many Functions of Telomerase Components: Certainties, Doubts, and Inconsistencies

A growing number of studies have evidenced non-telomeric functions of "telomerase". Almost all of them, however, investigated the non-canonical effects of the catalytic subunit TERT, and not the telomerase ribonucleoprotein holoenzyme. These functions mainly comprise signal transduction, gene regulation and the increase of anti-oxidative systems. Although less studied, TERC (the RNA component of telomerase) has also been shown to be involved in gene regulation, as well as other functions. All this has led to the publication of many reviews on the subject, which, however, are often disseminating personal interpretations of experimental studies of other researchers as original proofs. Indeed, while some functions such as gene regulation seem ascertained, especially because mechanistic findings have been provided, other ones remain dubious and/or are contradicted by other direct or indirect evidence (e.g., telomerase activity at double-strand break site, RNA polymerase activity of TERT, translation of TERC, mitochondrion-processed TERC). In a critical study of the primary evidence so far obtained, we show those functions for which there is consensus, those showing contradictory results and those needing confirmation. The resulting picture, together with some usually neglected aspects, seems to indicate a link between TERT and TERC functions and cellular stemness and gives possible directions for future research.

Integrated lncRNA function upon genomic and epigenomic regulation

Although some long noncoding (lnc)RNAs are known since the 1950s, the past 25 years have uncovered myriad lncRNAs with diverse sequences, structures, and functions. The advent of high-throughput and sensitive technologies has further uncovered the vast heterogeneity of lncRNA-interacting molecules and patterns of expressed lncRNAs. We propose a unifying functional theme for the expansive family of lncRNAs. At an elementary level, the genomic program of gene expression is elicited via canonical transcription and post-transcriptional mRNA assembly, turnover, and translation. Building upon this regulation, an epigenomic program refines the basic genomic control by modifying chromatin architecture as well as DNA and RNA chemistry. Superimposed over the genomic and epigenomic programs, lncRNAs create an additional regulatory dimension: by interacting with the proteins and nucleic acids that regulate gene expression in the nucleus and cytoplasm, lncRNAs help establish robust, nimble, and specific transcriptional and post-transcriptional control. We describe our present understanding of lncRNA-coordinated control of protein programs and cell fate and discuss challenges and opportunities as we embark on the next 25 years of lncRNA discovery.

Designing libraries for pooled CRISPR functional screens of long noncoding RNAs

Human and other genomes encode tens of thousands of long noncoding RNAs (lncRNAs), the vast majority of which remain uncharacterised. High-throughput functional screening methods, notably those based on pooled CRISPR-Cas perturbations, promise to unlock the biological significance and biomedical potential of lncRNAs. Such screens are based on libraries of single guide RNAs (sgRNAs) whose design is critical for success. Few off-the-shelf libraries are presently available, and lncRNAs tend to have cell-type-specific expression profiles, meaning that library design remains in the hands of researchers. Here we introduce the topic of pooled CRISPR screens for lncRNAs and guide readers through the three key steps of library design: accurate annotation of transcript structures, curation of optimal candidate sets, and design of sgRNAs. This review is a starting point and reference for researchers seeking to design custom CRISPR screening libraries for lncRNAs.

Native RNA sequencing in fission yeast reveals frequent alternative splicing isoforms

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

A novel binary k-mer approach for classification of coding and non-coding RNAs across diverse species

Classification among coding sequences (CDS) and non-coding RNA (ncRNA) sequences is a challenge and several machine learning models have been developed for the same. Since the frequency of curated CDS is many-folds as compared to that of the ncRNAs, we devised a novel approach to work with the complete datasets from fifteen diverse species. In our proposed binary approach, we replaced all the 'A's and 'T's with '0's and 'G's and 'C's with '1's to obtain a binary form of CDS and ncRNAs. The k-mer analysis of these binary sequences revealed that the frequency of binary patterns among the CDS and ncRNAs can be used as features to distinguish among them. Using insights from these distinguishing frequencies, we used k-nearest neighbor classifier to classify among them. Our strategy is not only time-efficient but leads to significantly increased performance metrics in terms of Matthews Correlation Coefficient (MCC), Accuracy, F1 score, Precision, Recall and AUC-ROC, for species like P. paniscus, M. mulatta, M. lucifugus, G. gallus, C. japonica, C. abingdonii, A. carolinensis, D. melanogaster and C. elegans when compared with the conventional ATGC approach. Additionally, we also show that the performance obtained for diverse species tested on the model based on H. sapiens, correlated with the geological evolutionary timeline, thereby further strengthening our approach. Therefore, we propose that CDS and ncRNAs can be efficiently classified using "2-character" binary frequency as compared to "4-character" frequency of ATGC approach. Thus, our highly efficient binary approach can replace the more complex ATGC approach successfully.

Optimization of Ribosome Footprinting Conditions for Ribo-Seq in Human and Drosophila melanogaster Tissue Culture Cells

Our understanding of mRNA translation and its regulation has been transformed by the development of ribosome profiling. This approach relies upon RNase footprinting of translating ribosomes in a precise manner to generate an accurate snapshot of ribosome positions with nucleotide resolution. Here we tested a variety of conditions, which contribute to the preciseness of ribosome footprinting and therefore the success of ribosome profiling. We found that NaCl concentration, RNaseI source, RNaseI amount, and temperature of footprinting all contributed to the quality of ribosome footprinting in human neuroblastoma SH-SY5Y cells. These ideal conditions for footprinting also improved footprint quality when used with Drosophila melanogaster S2 cells. Footprinting under the same conditions generated different footprints sizes and framing patterns in human and D. melanogaster cells. We also found that treatment of S2 cells with cycloheximide prior to footprinting impacted the distribution of footprints across ORFs, without affecting overall read length distribution and framing pattern, as previously found in other organisms. Together our results indicate that a variety of factors affect ribosome footprint quality and the nature of precise footprinting varies across species.

The evolutionary landscape and expression pattern of plant lincRNAs

Long intergenic non-coding RNAs (lincRNAs) are important regulators of cellular processes, including development and stress response. Many lincRNAs have been bioinformatically identified in plants, but their evolutionary dynamics and expression characteristics are still elusive. Here, we systematically identified thousands of lincRNAs in 26 plant species, including 6 non-flowering plants, investigated the conservation of the identified lincRNAs in different levels of plant lineages based on sequence and/or synteny homology and explored characteristics of the conserved lincRNAs during plant evolution and their co-expression relationship with protein-coding genes (PCGs). In addition to confirmation of the features well documented in literature for lincRNAs, such as species-specific, fewer exons, tissue-specific expression patterns and less abundantly expressed, we revealed that histone modification signals and/or binding sites of transcription factors were enriched in the conserved lincRNAs, implying their biological functionalities, as demonstrated by identifying conserved lincRNAs related to flower development in both the Brassicaceae and grass families and ancient lincRNAs potentially functioning in meristem development of non-flowering plants. Compared to PCGs, lincRNAs are more likely to be associated with transposable elements (TEs), but with different characteristics in different evolutionary lineages, for instance, the types of TEs and the variable level of association in lincRNAs with different conservativeness. Together, these results provide a comprehensive view on the evolutionary landscape of plant lincRNAs and shed new insights on the conservation and functionality of plant lincRNAs.

High-Throughput Evolutionary Comparative Analysis of Long Intergenic Noncoding RNAs in Multiple Organisms

Comparative genomic and transcriptomic analyses can help prioritize and facilitate the functional analysis of long noncoding RNAs (lncRNAs). Evolinc-II is a bioinformatic pipeline that automates comparative analyses, searching for sequence and structural conservation for thousands of lncRNAs at once. In addition, Evolinc-II takes a phylogenetic approach to infer key evolutionary events that may have occurred during the emergence of each query lncRNA. Here, we describe how to use command line or GUI (CyVerse's Discovery Environment) versions of Evolinc-II to identify lncRNA homologs and prioritize them for functional analysis.

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

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

Non-coding RNAs and their bioengineering applications for neurological diseases

Engineering of cellular biomolecules is an emerging landscape presenting creative therapeutic opportunities. Recently, several strategies such as biomimetic materials, drug-releasing scaffolds, stem cells, and dynamic culture systems have been developed to improve specific biological functions, however, have been confounded with fundamental and technical roadblocks. Rapidly emerging investigations on the bioengineering prospects of mammalian ribonucleic acid (RNA) is expected to result in significant biomedical advances. More specifically, the current trend focuses on devising non-coding (nc) RNAs as therapeutic candidates for complex neurological diseases. Given the pleiotropic and regulatory role, ncRNAs such as microRNAs and long non-coding RNAs are deemed as attractive therapeutic candidates. Currently, the list of non-coding RNAs in mammals is evolving, which presents the plethora of hidden possibilities including their scope in biomedicine. Herein, we critically review on the emerging repertoire of ncRNAs in neurological diseases such as Alzheimer’s disease, Parkinson’s disease, neuroinflammation and drug abuse disorders. Importantly, we present the advances in engineering of ncRNAs to improve their biocompatibility and therapeutic feasibility as well as provide key insights into the applications of bioengineered non-coding RNAs that are investigated for neurological diseases.

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

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

Exploring Evidence of Non-coding RNA Translation With Trips-Viz and GWIPS-Viz Browsers

Detection of translation in so-called non-coding RNA provides an opportunity for identification of novel bioactive peptides and microproteins. The main methods used for these purposes are ribosome profiling and mass spectrometry. A number of publicly available datasets already exist for a substantial number of different cell types grown under various conditions, and public data mining is an attractive strategy for identification of translation in non-coding RNAs. Since the analysis of publicly available data requires intensive data processing, several data resources have been created recently for exploring processed publicly available data, such as OpenProt, GWIPS-viz, and Trips-Viz. In this work we provide a detailed demonstration of how to use the latter two tools for exploring experimental evidence for translation of RNAs hitherto classified as non-coding. For this purpose, we use a set of transcripts with substantially different patterns of ribosome footprint distributions. We discuss how certain features of these patterns can be used as evidence for or against genuine translation. During our analysis we concluded that the MTLN mRNA, previously misannotated as lncRNA LINC00116, likely encodes only a short proteoform expressed from shorter RNA transcript variants.

Computational analysis of sense-antisense chimeric transcripts reveals their potential regulatory features and the landscape of expression in human cells

Many human genes are transcribed from both strands and produce sense-antisense gene pairs. Sense-antisense (SAS) chimeric transcripts are produced upon the coalescing of exons/introns from both sense and antisense transcripts of the same gene. SAS chimera was first reported in prostate cancer cells. Subsequently, numerous SAS chimeras have been reported in the ChiTaRS-2.1 database. However, the landscape of their expression in human cells and functional aspects are still unknown. We found that longer palindromic sequences are a unique feature of SAS chimeras. Structural analysis indicates that a long hairpin-like structure formed by many consecutive Watson-Crick base pairs appears because of these long palindromic sequences, which possibly play a similar role as double-stranded RNA (dsRNA), interfering with gene expression. RNA-RNA interaction analysis suggested that SAS chimeras could significantly interact with their parental mRNAs, indicating their potential regulatory features. Here, 267 SAS chimeras were mapped in RNA-seq data from 16 healthy human tissues, revealing their expression in normal cells. Evolutionary analysis suggested the positive selection favoring sense-antisense fusions that significantly impacted the evolution of their function and structure. Overall, our study provides detailed insight into the expression landscape of SAS chimeras in human cells and identifies potential regulatory features.

Cytoplasmic long noncoding RNAs are differentially regulated and translated during human neuronal differentiation

The expression of long noncoding RNAs is highly enriched in the human nervous system. However, the function of neuronal lncRNAs in the cytoplasm and their potential translation remains poorly understood. Here we performed Poly-Ribo-Seq to understand the interaction of lncRNAs with the translation machinery and the functional consequences during neuronal differentiation of human SH-SY5Y cells. We discovered 237 cytoplasmic lncRNAs up-regulated during early neuronal differentiation, 58%-70% of which are associated with polysome translation complexes. Among these polysome-associated lncRNAs, we find 45 small ORFs to be actively translated, 17 specifically upon differentiation. Fifteen of 45 of the translated lncRNA-smORFs exhibit sequence conservation within Hominidea, suggesting they are under strong selective constraint in this clade. The profiling of publicly available data sets revealed that 8/45 of the translated lncRNAs are dynamically expressed during human brain development, and 22/45 are associated with cancers of the central nervous system. One translated lncRNA we discovered is LINC01116, which is induced upon differentiation and contains an 87 codon smORF exhibiting increased ribosome profiling signal upon differentiation. The resulting LINC01116 peptide localizes to neurites. Knockdown of LINC01116 results in a significant reduction of neurite length in differentiated cells, indicating it contributes to neuronal differentiation. Our findings indicate cytoplasmic lncRNAs interact with translation complexes, are a noncanonical source of novel peptides, and contribute to neuronal function and disease. Specifically, we demonstrate a novel functional role for LINC01116 during human neuronal differentiation.

Long Noncoding RNAs and Human Liver Disease

Long noncoding RNAs (lncRNAs) are pervasively transcribed in the genome, exhibit a diverse range of biological functions, and exert effects through a variety of mechanisms. The sheer number of lncRNAs in the human genome has raised important questions about their potential biological significance and roles in human health and disease. Technological and computational advances have enabled functional annotation of a large number of lncRNAs. Though the number of publications related to lncRNAs has escalated in recent years, relatively few have focused on those involved in hepatic physiology and pathology. We provide an overview of evolving lncRNA classification systems and characteristics and highlight important advances in our understanding of the contribution of lncRNAs to liver disease, with a focus on nonalcoholic steatohepatitis, hepatocellular carcinoma, and cholestatic liver disease. Expected final online publication date for the Annual Review of Pathology: Mechanisms of Disease, Volume 17 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A trans locus causes a ribosomopathy in hypertrophic hearts that affects mRNA translation in a protein length-dependent fashion

BACKGROUND

Little is known about the impact of trans-acting genetic variation on the rates with which proteins are synthesized by ribosomes. Here, we investigate the influence of such distant genetic loci on the efficiency of mRNA translation and define their contribution to the development of complex disease phenotypes within a panel of rat recombinant inbred lines.

RESULTS

We identify several tissue-specific master regulatory hotspots that each control the translation rates of multiple proteins. One of these loci is restricted to hypertrophic hearts, where it drives a translatome-wide and protein length-dependent change in translational efficiency, altering the stoichiometric translation rates of sarcomere proteins. Mechanistic dissection of this locus across multiple congenic lines points to a translation machinery defect, characterized by marked differences in polysome profiles and misregulation of the small nucleolar RNA SNORA48. Strikingly, from yeast to humans, we observe reproducible protein length-dependent shifts in translational efficiency as a conserved hallmark of translation machinery mutants, including those that cause ribosomopathies. Depending on the factor mutated, a pre-existing negative correlation between protein length and translation rates could either be enhanced or reduced, which we propose to result from mRNA-specific imbalances in canonical translation initiation and reinitiation rates.

CONCLUSIONS

We show that distant genetic control of mRNA translation is abundant in mammalian tissues, exemplified by a single genomic locus that triggers a translation-driven molecular mechanism. Our work illustrates the complexity through which genetic variation can drive phenotypic variability between individuals and thereby contribute to complex disease.

Comparative genomics in the search for conserved long noncoding RNAs

Long noncoding RNAs (lncRNAs) have emerged as prominent regulators of gene expression in eukaryotes. The identification of lncRNA orthologs is essential in efforts to decipher their roles across model organisms, as homologous genes tend to have similar molecular and biological functions. The relatively high sequence plasticity of lncRNA genes compared with protein-coding genes, makes the identification of their orthologs a challenging task. This is why comparative genomics of lncRNAs requires the development of specific and, sometimes, complex approaches. Here, we briefly review current advancements and challenges associated with four levels of lncRNA conservation: genomic sequences, splicing signals, secondary structures and syntenic transcription.

lncEvo: automated identification and conservation study of long noncoding RNAs

BACKGROUND

Long noncoding RNAs represent a large class of transcripts with two common features: they exceed an arbitrary length threshold of 200 nt and are assumed to not encode proteins. Although a growing body of evidence indicates that the vast majority of lncRNAs are potentially nonfunctional, hundreds of them have already been revealed to perform essential gene regulatory functions or to be linked to a number of cellular processes, including those associated with the etiology of human diseases. To better understand the biology of lncRNAs, it is essential to perform a more in-depth study of their evolution. In contrast to protein-encoding transcripts, however, they do not show the strong sequence conservation that usually results from purifying selection; therefore, software that is typically used to resolve the evolutionary relationships of protein-encoding genes and transcripts is not applicable to the study of lncRNAs.

RESULTS

To tackle this issue, we developed lncEvo, a computational pipeline that consists of three modules: (1) transcriptome assembly from RNA-Seq data, (2) prediction of lncRNAs, and (3) conservation study-a genome-wide comparison of lncRNA transcriptomes between two species of interest, including search for orthologs. Importantly, one can choose to apply lncEvo solely for transcriptome assembly or lncRNA prediction, without calling the conservation-related part.

CONCLUSIONS

lncEvo is an all-in-one tool built with the Nextflow framework, utilizing state-of-the-art software and algorithms with customizable trade-offs between speed and sensitivity, ease of use and built-in reporting functionalities. The source code of the pipeline is freely available for academic and nonacademic use under the MIT license at https://gitlab.com/spirit678/lncrna_conservation_nf .

The Role of cis- and trans-Acting RNA Regulatory Elements in Leukemia

RNA molecules are a source of phenotypic diversity and an operating system that connects multiple genetic and metabolic processes in the cell. A dysregulated RNA network is a common feature of cancer. Aberrant expression of long non-coding RNA (lncRNA), micro RNA (miRNA), and circular RNA (circRNA) in tumors compared to their normal counterparts, as well as the recurrent mutations in functional regulatory cis-acting RNA motifs have emerged as biomarkers of disease development and progression, opening avenues for the design of novel therapeutic approaches. This review looks at the progress, challenges and future prospects of targeting cis-acting and trans-acting RNA elements for leukemia diagnosis and treatment.

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

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

Mitochondrial noncoding RNA-regulatory network in cardiovascular disease

Mitochondrial function and integrity are vital for the maintenance of cellular homeostasis, particularly in high-energy demanding cells. Cardiomyocytes have a large number of mitochondria, which provide a continuous and bulk supply of the ATP necessary for cardiac mechanical function. More than 90% of the ATP consumed by the heart is derived from the mitochondrial oxidative metabolism. Decreased energy supply as the main consequence of mitochondrial dysfunction is closely linked to cardiovascular disease (CVD). The discovery of noncoding RNA (ncRNAs) in the mitochondrial compartment has changed the traditional view of molecular pathways involved in the regulatory network of CVD. Mitochondrial ncRNAs participate in controlling cardiovascular pathogenesis by regulating glycolysis, mitochondrial energy status, and the expression of genes involved in mitochondrial metabolism. Understanding the underlying mechanisms of the association between impaired mitochondrial function resulting from fluctuation in expression levels of ncRNAs and specific disease phenotype can aid in preventing and treating CVD. This review presents an overview of the role of mitochondrial ncRNAs in the complex regulatory network of the cardiovascular pathology. We will summarize and discuss (1) mitochondrial microRNAs (mitomiRs) and long noncoding RNAs (lncRNAs) encoded either by nuclear or mitochondrial genome which are involved in the regulation of mitochondrial metabolism; (2) the role of mitomiRs and lncRNAs in the pathogenesis of several CVD such as hypertension, cardiac hypertrophy, acute myocardial infarction and heart failure; (3) the biomarker and therapeutic potential of mitochondrial ncRNAs in CVD; (4) and the challenges inherent to their translation into clinical application.