Evolutionary analysis across mammals reveals distinct classes of long non-coding RNAs

Genome-wide cataloging and orthology analysis of long noncoding RNA expression in three species of Anopheles mosquito

BACKGROUND

Long noncoding RNAs (lncRNAs) are versatile regulatory molecules that affect cellular phenotypes through context-specific expression. While their role in controlling cellular pathways is well-established in insects, investigating lncRNA expression in Anopheles in a tissue- and species-specific manner could add to our understanding of malaria transmission by this important vector.

METHODOLOGY

We performed de novo transcriptome assembly of Anopheles minimus, Anopheles albimanus, and Anopheles arabiensis utilising publicly available RNA-Seq datasets of male reproductive tissues, male carcasses, female reproductive tissues, and female carcasses. Various bioinformatics tools were subsequently used for lncRNA identification, conservation analysis, and differential expression analysis across sexes and tissues.

RESULTS

We identified 9331, 5372, and 5256 lncRNA transcripts in An. albimanus, An. arabiensis, and An. minimus, respectively. Compared with An. albimanus lncRNAs, conservation analysis revealed that a total of 1964 and 1400 lncRNAs were conserved in An. arabiensis and An. minimus; however, only 283 and 253 lncRNAs presented sequence-level conservation. Differential expression (DE) analysis revealed that the carcasses presented the lowest difference in lncRNA expression, whereas in each comparison, the reproductive tissues (whether male or female) presented relatively high levels of differential expression. Additionally, 69 lncRNAs were found to be conserved at the sequence level in all 3 species. These lncRNAs were almost exclusively upregulated in males (reproductive tissue as well as carcasses) and exclusively downregulated in female carcasses.

CONCLUSIONS

The genes in the vicinity of differentially expressed, conserved lncRNAs were found to be involved in critical pathways such as nuclear structure, chromatin remodelling, protein and RNA metabolism, and cell cycle in each of these species. Future studies on these lncRNAs can provide useful insights into how these functions control sexually-dimorphic physiological phenomena such as host-seeking and biting behaviour of female mosquitoes, blood meal metabolism, reproductive behaviour, and disease-carrying capacity.

Syntenic lncRNA locus exhibits DNA regulatory functions with sequence evolution

Syntenic long non-coding RNAs (lncRNAs) often show limited sequence conservation across species, prompting concern in the field. This study delves into functional signatures of syntenic lncRNAs between humans and zebrafish. Syntenic lncRNAs are highly expressed in zebrafish, with ∼90 % located near protein-coding genes, either in sense or antisense orientation. During early zebrafish development and in human embryonic stem cells (H1-hESC), syntenic lncRNA loci are enriched with cis-regulatory repressor signatures, influencing the expression of development-associated genes. In later zebrafish developmental stages and specific human cell lines, these syntenic lncRNA loci function as enhancers or transcription start sites (TSS) for protein-coding genes. Analysis of transposable elements (TEs) in syntenic lncRNA sequences revealed intriguing patterns: human lncRNAs are enriched in simple repeat elements, while their zebrafish counterparts show enrichment in LTR elements. This sequence evolution likely arises from post-rearrangement mutations that enhance DNA elements or cis-regulatory functions. It may also contribute to vertebrate innovation by creating novel transcription factor binding sites within the locus. This study highlights the conserved functionality of syntenic lncRNA loci through DNA elements, emphasizing their conserved roles across species despite sequence divergence.

Epigenetic Role of Long Non-coding RNAs in Multiple Myeloma

PURPOSE OF THE REVIEW

This review aims to explore the pivotal role of long non-coding RNAs (lncRNAs) as epigenetic regulators in the pathogenesis of multiple myeloma (MM). Additionally, we have portrayed the dual role of lncRNAs in the epigenetic landscape of MM pathobiology.

RECENT FINDINGS

In MM, lncRNAs are pivotal for proliferation, progression, and drug resistance by acting as miRNA sponges, regulating mRNA activity through microRNA recognition elements (MREs). Epigenetic modifications in lncRNAs influence gene expression, with some like MEG3, GAS5, CRNDE, and H19 showing promoter hypermethylation, while MALAT1 exhibits hypomethylation. Targeting lncRNAs using siRNA, ASO, CRISPR-Cas9, or small molecule inhibitors shows promise in preclinical studies, alongside the potential benefits of epigenetic-based therapies such as DNMTi and HDACi. Clinical trials combining epigenetic modifiers with standard chemotherapy show encouraging results, especially in relapsed/refractory MM. The key finding of the studies highlighted in the review paves the way for understanding the epigenetic role of lncRNAs in MM disease progression and biology. In addition, the novel therapeutic strategies that have shown promising results have been highlighted. The adoption of the epigenetic landscape into therapeutics in addition to existing treatment strategies may increase the efficacy of treatment approaches.

Computational Resources for lncRNA Functions and Targetome

Long non-coding RNAs (lncRNAs) are a type of non-coding RNA molecules exceeding 200 nucleotides in length and that do not encode proteins. The dysregulated expression of lncRNAs has been identified in various diseases, holding therapeutic significance. Over the past decade, numerous computational resources have been published in the field of lncRNA. In this chapter, we have provided a comprehensive review of the databases as well as predictive tools, that is, lncRNA databases, machine learning based algorithms, and tools predicting lncRNAs utilizing different techniques. The chapter will focus on the importance of lncRNA resources developed for different organisms specifically for humans, mouse, plants, and other model organisms. We have enlisted important databases, primarily focusing on comprehensive information related to lncRNA registries, associations with diseases, differential expression, lncRNA transcriptome, target regulations, and all-in-one resources. Further, we have also included the updated version of lncRNA resources. Additionally, computational identification of lncRNAs using algorithms like Deep learning, Support Vector Machine (SVM), and Random Forest (RF) was also discussed. In conclusion, this comprehensive overview concludes by summarizing vital in silico resources, empowering biologists to choose the most suitable tools for their lncRNA research endeavors. This chapter serves as a valuable guide, emphasizing the significance of computational approaches in understanding lncRNAs and their implications in various biological contexts.

Evolutionary comparison of lncRNAs in four cotton species and functional identification of LncR4682-PAS2-KCS19 module in fiber elongation

Long non-coding RNAs (lncRNAs) play an important role in various biological processes in plants. However, there have been few reports on the evolutionary signatures of lncRNAs in closely related cotton species. The lncRNA transcription patterns in two tetraploid cotton species and their putative diploid ancestors were compared in this paper. By performing deep RNA sequencing, we identified 280 429 lncRNAs from 21 tissues in four cotton species. lncRNA transcription evolves more rapidly than mRNAs, and exhibits more severe turnover phenomenon in diploid species compared to that in tetraploid species. Evolutionarily conserved lncRNAs exhibit higher expression levels, and lower tissue specificity compared with species-specific lncRNAs. Remarkably, tissue expression of homologous lncRNAs in Gossypium hirsutum and G. barbadense exhibited similar patterns, suggesting that these lncRNAs may be functionally conserved and selectively maintained during domestication. An orthologous lncRNA, lncR4682, was identified and validated in fibers of G. hirsutum and G. barbadense with the highest conservatism and expression abundance. Through virus-induced gene silencing in upland cotton, we found that lncR4682 and its target genes GHPAS2 and GHKCS19 positively regulated fiber elongation. In summary, the present study provides a systematic analysis of lncRNAs in four closely related cotton species, extending the understanding of transcriptional conservation of lncRNAs across cotton species. In addition, LncR4682-PAS2-KCS19 contributes to cotton fiber elongation by participating in the biosynthesis of very long-chain fatty acids.

Quest for Orthologs in the Era of Biodiversity Genomics

The era of biodiversity genomics is characterized by large-scale genome sequencing efforts that aim to represent each living taxon with an assembled genome. Generating knowledge from this wealth of data has not kept up with this pace. We here discuss major challenges to integrating these novel genomes into a comprehensive functional and evolutionary network spanning the tree of life. In summary, the expanding datasets create a need for scalable gene annotation methods. To trace gene function across species, new methods must seek to increase the resolution of ortholog analyses, e.g. by extending analyses to the protein domain level and by accounting for alternative splicing. Additionally, the scope of orthology prediction should be pushed beyond well-investigated proteomes. This demands the development of specialized methods for the identification of orthologs to short proteins and noncoding RNAs and for the functional characterization of novel gene families. Furthermore, protein structures predicted by machine learning are now readily available, but this new information is yet to be integrated with orthology-based analyses. Finally, an increasing focus should be placed on making orthology assignments adhere to the findable, accessible, interoperable, and reusable (FAIR) principles. This fosters green bioinformatics by avoiding redundant computations and helps integrating diverse scientific communities sharing the need for comparative genetics and genomics information. It should also help with communicating orthology-related concepts in a format that is accessible to the public, to counteract existing misinformation about evolution.

CANTATAdb 3.0: An Updated Repository of Plant Long Non-Coding RNAs

CANTATAdb 3.0 is an updated database of plant long non-coding RNAs (lncRNAs), containing 571,688 lncRNAs identified across 108 species, including 100 Magnoliopsida (flowering plants), a significant expansion from the previous version. A notable feature is the inclusion of 112,980 lncRNAs that are expressed specifically in certain plant organs or embryos, indicating their potential role in development and organ-specific processes. In addition, CANTATAdb 3.0 includes 74,886 pairs of evolutionarily conserved lncRNAs found across 47 species and inferred from genome-genome alignments as well as conserved lncRNAs obtained using a similarity search approach in 5,479 species pairs, which would further aid in the selection of lncRNAs for functional studies. Interestingly, we find that conserved lncRNAs with tissue-specific expression patterns tend to occupy the same plant organ across different species, pointing toward conserved biological roles. The database now offers extended search capabilities and downloadable data in popular formats, further facilitating research on plant lncRNAs.

AMPFLDAP: Adaptive Message Passing and Feature Fusion on Heterogeneous Network for LncRNA-Disease Associations Prediction

Exploration of the intricate connections between long noncoding RNA (lncRNA) and diseases, referred to as lncRNA-disease associations (LDAs), plays a pivotal and indispensable role in unraveling the underlying molecular mechanisms of diseases and devising practical treatment approaches. It is imperative to employ computational methods for predicting lncRNA-disease associations to circumvent the need for superfluous experimental endeavors. Graph-based learning models have gained substantial popularity in predicting these associations, primarily because of their capacity to leverage node attributes and relationships within the network. Nevertheless, there remains much room for enhancing the performance of these techniques by incorporating and harmonizing the node attributes more effectively. In this context, we introduce a novel model, i.e., Adaptive Message Passing and Feature Fusion (AMPFLDAP), for forecasting lncRNA-disease associations within a heterogeneous network. Firstly, we constructed a heterogeneous network involving lncRNA, microRNA (miRNA), and diseases based on established associations and employing Gaussian interaction profile kernel similarity as a measure. Then, an adaptive topological message passing mechanism is suggested to address the information aggregation for heterogeneous networks. The topological features of nodes in the heterogeneous network were extracted based on the adaptive topological message passing mechanism. Moreover, an attention mechanism is applied to integrate both topological and semantic information to achieve the multimodal features of biomolecules, which are further used to predict potential LDAs. The experimental results demonstrated that the performance of the proposed AMPFLDAP is superior to seven state-of-the-art methods. Furthermore, to validate its efficacy in practical scenarios, we conducted detailed case studies involving three distinct diseases, which conclusively demonstrated AMPFLDAP's effectiveness in the prediction of LDAs.

Exploring the Utility of Long Non-Coding RNAs for Assessing the Health Consequences of Vaping

Electronic cigarette (e-cig) use, otherwise known as "vaping", is widespread among adolescent never-smokers and adult smokers seeking a less-harmful alternative to combustible tobacco products. To date, however, the long-term health consequences of vaping are largely unknown. Many toxicants and carcinogens present in e-cig vapor and tobacco smoke exert their biological effects through epigenetic changes that can cause dysregulation of disease-related genes. Long non-coding RNAs (lncRNAs) have emerged as prime regulators of gene expression in health and disease states. A large body of research has shown that lncRNAs regulate genes involved in the pathogenesis of smoking-associated diseases; however, the utility of lncRNAs for assessing the disease-causing potential of vaping remains to be fully determined. A limited but growing number of studies has shown that lncRNAs mediate dysregulation of disease-related genes in cells and tissues of vapers as well as cells treated in vitro with e-cig aerosol extract. This review article provides an overview of the evolution of e-cig technology, trends in use, and controversies on the safety, efficacy, and health risks or potential benefits of vaping relative to smoking. While highlighting the importance of lncRNAs in cell biology and disease, it summarizes the current and ongoing research on the modulatory effects of lncRNAs on gene regulation and disease pathogenesis in e-cig users and in vitro experimental settings. The gaps in knowledge are identified, priorities for future research are highlighted, and the importance of empirical data for tobacco products regulation and public health is underscored.

Targeting and engineering long non-coding RNAs for cancer therapy

RNA therapeutics (RNATx) aim to treat diseases, including cancer, by targeting or employing RNA molecules for therapeutic purposes. Amongst the most promising targets are long non-coding RNAs (lncRNAs), which regulate oncogenic molecular networks in a cell type-restricted manner. lncRNAs are distinct from protein-coding genes in important ways that increase their therapeutic potential yet also present hurdles to conventional clinical development. Advances in genome editing, oligonucleotide chemistry, multi-omics and RNA engineering are paving the way for efficient and cost-effective lncRNA-focused drug discovery pipelines. In this Review, we present the emerging field of lncRNA therapeutics for oncology, with emphasis on the unique strengths and challenges of lncRNAs within the broader RNATx framework. We outline the necessary steps for lncRNA therapeutics to deliver effective, durable, tolerable and personalized treatments for cancer.

MicroProteinDB: A database to provide knowledge on sequences, structures and function of ncRNA-derived microproteins

Omics-based technologies have revolutionized our comprehension of microproteins encoded by ncRNAs, revealing their abundant presence and pivotal roles within complex functional landscapes. Here, we developed MicroProteinDB (http://bio-bigdata.hrbmu.edu.cn/MicroProteinDB), which offers and visualizes the extensive knowledge to aid retrieval and analysis of computationally predicted and experimentally validated microproteins originating from various ncRNA types. Employing prediction algorithms grounded in diverse deep learning approaches, MicroProteinDB comprehensively documents the fundamental physicochemical properties, secondary and tertiary structures, interactions with functional proteins, family domains, and inter-species conservation of microproteins. With five major analytical modules, it will serve as a valuable knowledge for investigating ncRNA-derived microproteins.

Genome-scale pan-cancer interrogation of lncRNA dependencies using CasRx

Although long noncoding RNAs (lncRNAs) dominate the transcriptome, their functions are largely unexplored. The extensive overlap of lncRNAs with coding and regulatory sequences restricts their systematic interrogation by DNA-directed perturbation. Here we developed genome-scale lncRNA transcriptome screening using Cas13d/CasRx. We show that RNA targeting overcomes limitations inherent to other screening methods, thereby considerably expanding the explorable space of the lncRNAome. By evolving the screening system toward pan-cancer applicability, it supports molecular and phenotypic data integration to contextualize screening hits or infer lncRNA function. We thereby addressed challenges posed by the enormous transcriptome size and tissue specificity through a size-reduced multiplexed gRNA library termed Albarossa, targeting 24,171 lncRNA genes. Its rational design incorporates target prioritization based on expression, evolutionary conservation and tissue specificity, thereby reconciling high discovery power and pan-cancer representation with scalable experimental throughput. Applied across entities, the screening platform identified numerous context-specific and common essential lncRNAs. Our work sets the stage for systematic exploration of lncRNA biology in health and disease.

Regulatory activity is the default DNA state in eukaryotes

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

Genome-wide analysis of RNA-chromatin interactions in lizards as a mean for functional lncRNA identification

BACKGROUND

Long non-coding RNAs (lncRNAs) are defined as transcribed molecules longer than 200 nucleotides with little to no protein-coding potential. LncRNAs can regulate gene expression of nearby genes (cis-acting) or genes located on other chromosomes (trans-acting). Several methodologies have been developed to capture lncRNAs associated with chromatin at a genome-wide level. Analysis of RNA-DNA contacts can be combined with epigenetic and RNA-seq data to define potential lncRNAs involved in the regulation of gene expression.

RESULTS

We performed Chromatin Associated RNA sequencing (ChAR-seq) in Anolis carolinensis to obtain the genome-wide map of the associations that RNA molecules have with chromatin. We analyzed the frequency of DNA contacts for different classes of RNAs and were able to define cis- and trans-acting lncRNAs. We integrated the ChAR-seq map of RNA-DNA contacts with epigenetic data for the acetylation of lysine 16 on histone H4 (H4K16ac), a mark connected to actively transcribed chromatin in lizards. We successfully identified three trans-acting lncRNAs significantly associated with the H4K16ac signal, which are likely involved in the regulation of gene expression in A. carolinensis.

CONCLUSIONS

We show that the ChAR-seq method is a powerful tool to explore the RNA-DNA map of interactions. Moreover, in combination with epigenetic data, ChAR-seq can be applied in non-model species to establish potential roles for predicted lncRNAs that lack functional annotations.

Dysregulation of murine long noncoding single-cell transcriptome in nonalcoholic steatohepatitis and liver fibrosis

LncRNAs comprise a heterogeneous class of RNA-encoding genes typified by low expression, nuclear enrichment, high tissue-specificity, and functional diversity, but the vast majority remain uncharacterized. Here, we assembled the mouse liver noncoding transcriptome from >2000 bulk RNA-seq samples and discovered 48,261 liver-expressed lncRNAs, a majority novel. Using these lncRNAs as a single-cell transcriptomic reference set, we elucidated lncRNA dysregulation in mouse models of high fat diet-induced nonalcoholic steatohepatitis and carbon tetrachloride-induced liver fibrosis. Trajectory inference analysis revealed lncRNA zonation patterns across the liver lobule in each major liver cell population. Perturbations in lncRNA expression and zonation were common in several disease-associated liver cell types, including nonalcoholic steatohepatitis-associated macrophages, a hallmark of fatty liver disease progression, and collagen-producing myofibroblasts, a central feature of liver fibrosis. Single-cell-based gene regulatory network analysis using bigSCale2 linked individual lncRNAs to specific biological pathways, and network-essential regulatory lncRNAs with disease-associated functions were identified by their high network centrality metrics. For a subset of these lncRNAs, promoter sequences of the network-defined lncRNA target genes were significantly enriched for lncRNA triplex formation, providing independent mechanistic support for the lncRNA-target gene linkages predicted by the gene regulatory networks. These findings elucidate liver lncRNA cell-type specificities, spatial zonation patterns, associated regulatory networks, and temporal patterns of dysregulation during hepatic disease progression. A subset of the liver disease-associated regulatory lncRNAs identified have human orthologs and are promising candidates for biomarkers and therapeutic targets.

Single-cell profiling of lncRNA expression during Ebola virus infection in rhesus macaques

Long non-coding RNAs (lncRNAs) are involved in numerous biological processes and are pivotal mediators of the immune response, yet little is known about their properties at the single-cell level. Here, we generate a multi-tissue bulk RNAseq dataset from Ebola virus (EBOV) infected and not-infected rhesus macaques and identified 3979 novel lncRNAs. To profile lncRNA expression dynamics in immune circulating single-cells during EBOV infection, we design a metric, Upsilon, to estimate cell-type specificity. Our analysis reveals that lncRNAs are expressed in fewer cells than protein-coding genes, but they are not expressed at lower levels nor are they more cell-type specific when expressed in the same number of cells. In addition, we observe that lncRNAs exhibit similar changes in expression patterns to those of protein-coding genes during EBOV infection, and are often co-expressed with known immune regulators. A few lncRNAs change expression specifically upon EBOV entry in the cell. This study sheds light on the differential features of lncRNAs and protein-coding genes and paves the way for future single-cell lncRNA studies.

Multidimensional conservation analysis decodes the expression of conserved long noncoding RNAs

Although long noncoding RNAs (lncRNAs) experience weaker evolutionary constraints and exhibit lower sequence conservation than coding genes, they can still conserve their features in various aspects. Here, we used multiple approaches to systemically evaluate the conservation between human and mouse lncRNAs from various dimensions including sequences, promoter, global synteny, and local synteny, which led to the identification of 1,731 conserved lncRNAs with 427 high-confidence ones meeting multiple criteria. Conserved lncRNAs, compared with non-conserved ones, generally have longer gene bodies, more exons and transcripts, stronger connections with human diseases, and are more abundant and widespread across different tissues. Transcription factor (TF) profile analysis revealed a significant enrichment of TF types and numbers in the promoters of conserved lncRNAs. We further identified a set of TFs that preferentially bind to conserved lncRNAs and exert stronger regulation on conserved than non-conserved lncRNAs. Our study has reconciled some discrepant interpretations of lncRNA conservation and revealed a new set of transcriptional factors ruling the expression of conserved lncRNAs.

RUNX2 stabilization by long non-coding RNAs contributes to hypertrophic changes in human chondrocytes

Background: Chondrocyte hypertrophy has been implicated in endochondral ossification and osteoarthritis (OA). In OA, hypertrophic chondrocytes contribute to the destruction and focal calcification of the joint cartilage. Although studies in this field have remarkably developed the modulation of joint inflammation using gene therapy and regeneration of damaged articular cartilage using cell therapy, studies that can modulate or prevent hypertrophic changes in articular chondrocytes are still lacking. Methods: In vitro hypertrophic differentiation and inflammation assays were conducted using human normal chondrocyte cell lines, TC28a2 cells. Human cartilage tissues and primary articular chondrocytes were obtained from OA patients undergoing total knee arthroplasty. Long non-coding RNAs (lncRNAs), LINC02035 and LOC100130207, were selected through RNA-sequencing analysis using RNAs extracted from TC28a2 cells cultured in hypertrophic medium. The regulatory mechanism was evaluated using western blotting, real-time quantitative polymerase chain reaction, osteocalcin reporter assay, RNA-immunoprecipitation (RNA-IP), RNA-in situ hybridization, and IP. Results: LncRNAs are crucial regulators of various biological processes. In this study, we identified two important lncRNAs, LINC02035 and LOC100130207, which play important roles in hypertrophic changes in normal chondrocytes, through RNA sequencing. Interestingly, the expression level of RUNX2, a master regulator of chondrocyte hypertrophy, was regulated at the post-translational level during hypertrophic differentiation of the normal human chondrocyte cell line, TC28a2. RNA-immunoprecipitation proved the potential interaction between RUNX2 protein and both lncRNAs. Knockdown (KD) of LINC02035 or LOC100130207 promoted ubiquitin-mediated proteasomal degradation of RUNX2 and prevented hypertrophic differentiation of normal chondrocyte cell lines, whereas overexpression of both lncRNAs stabilized RUNX2 protein and generated hypertrophic changes. Furthermore, the KD of the two lncRNAs mitigated the destruction of important cartilage matrix proteins, COL2A1 and ACAN, by hypertrophic differentiation or inflammatory conditions. We also confirmed that the phenotypic changes raised by the two lncRNAs could be rescued by modulating RUNX2 expression. In addition, the KD of these two lncRNAs suppressed hypertrophic changes during chondrogenic differentiation of mesenchymal stem cells. Conclusion: Therefore, this study suggests that LINC02035 and LOC100130207 contribute to hypertrophic changes in normal chondrocytes by regulating RUNX2, suggesting that these two novel lncRNAs could be potential therapeutic targets for delaying or preventing OA development, especially for preventing chondrocyte hypertrophy.

TLSEA: a tool for lncRNA set enrichment analysis based on multi-source heterogeneous information fusion

Long non-coding RNAs (lncRNAs) play an important regulatory role in gene transcription and post-transcriptional modification, and lncRNA regulatory dysfunction leads to a variety of complex human diseases. Hence, it might be beneficial to detect the underlying biological pathways and functional categories of genes that encode lncRNA. This can be carried out by using gene set enrichment analysis, which is a pervasive bioinformatic technique that has been widely used. However, accurately performing gene set enrichment analysis of lncRNAs remains a challenge. Most conventional enrichment analysis methods have not exhaustively included the rich association information among genes, which usually affects the regulatory functions of genes. Here, we developed a novel tool for lncRNA set enrichment analysis (TLSEA) to improve the accuracy of the gene functional enrichment analysis, which extracted the low-dimensional vectors of lncRNAs in two functional annotation networks with the graph representation learning method. A novel lncRNA-lncRNA association network was constructed by merging lncRNA-related heterogeneous information obtained from multiple sources with the different lncRNA-related similarity networks. In addition, the random walk with restart method was adopted to effectively expand the lncRNAs submitted by users according to the lncRNA-lncRNA association network of TLSEA. In addition, a case study of breast cancer was performed, which demonstrated that TLSEA could detect breast cancer more accurately than conventional tools. The TLSEA can be accessed freely at http://www.lirmed.com:5003/tlsea.

Selective RNA Labeling by RNA-Compatible Type II Restriction Endonuclease and RNA-Extending DNA Polymerase

RNAs not only offer valuable information regarding our bodies but also regulate cellular functions, allowing for their specific manipulations to be extensively explored for many different biological and clinical applications. In particular, rather than temporary hybridization, permanent labeling is often required to introduce functional tags to target RNAs; however, direct RNA labeling has been revealed to be challenging, as native RNAs possess unmodifiable chemical moieties or indefinable dummy sequences at the ends of their strands. In this work, we demonstrate the combinatorial use of RNA-compatible restriction endonucleases (REs) and RNA-extending polymerases for sequence-specific RNA cleavage and subsequent RNA functionalization. Upon the introduction of complementary DNAs to target RNAs, Type II REs, such as AvrII and AvaII, could precisely cut the recognition site in the RNA-DNA heteroduplexes with exceptionally high efficiency. Subsequently, the 3′ ends of the cleaved RNAs were selectively and effectively modified when Therminator DNA polymerase template-dependently extended the RNA primers with a variety of modified nucleotides. Based on this two-step RNA labeling, only the target RNA could be chemically labeled with the desired moieties, such as bioconjugation tags or fluorophores, even in a mixture of various RNAs, demonstrating the potential for efficient and direct RNA modifications.

Flnc: Machine Learning Improves the Identification of Novel Long Noncoding RNAs from Stand-Alone RNA-Seq Data

Long noncoding RNAs (lncRNAs) play critical regulatory roles in human development and disease. Although there are over 100,000 samples with available RNA sequencing (RNA-seq) data, many lncRNAs have yet to be annotated. The conventional approach to identifying novel lncRNAs from RNA-seq data is to find transcripts without coding potential but this approach has a false discovery rate of 30-75%. Other existing methods either identify only multi-exon lncRNAs, missing single-exon lncRNAs, or require transcriptional initiation profiling data (such as H3K4me3 ChIP-seq data), which is unavailable for many samples with RNA-seq data. Because of these limitations, current methods cannot accurately identify novel lncRNAs from existing RNA-seq data. To address this problem, we have developed software, Flnc, to accurately identify both novel and annotated full-length lncRNAs, including single-exon lncRNAs, directly from RNA-seq data without requiring transcriptional initiation profiles. Flnc integrates machine learning models built by incorporating four types of features: transcript length, promoter signature, multiple exons, and genomic location. Flnc achieves state-of-the-art prediction power with an AUROC score over 0.92. Flnc significantly improves the prediction accuracy from less than 50% using the conventional approach to over 85%. Flnc is available via GitHub platform.

ortho2align: a sensitive approach for searching for orthologues of novel lncRNAs

Background

Many novel long noncoding RNAs have been discovered in recent years due to advances in high-throughput sequencing experiments. Finding orthologues of these novel lncRNAs might facilitate clarification of their functional role in living organisms. However, lncRNAs exhibit low sequence conservation, so specific methods for enhancing the signal-to-noise ratio were developed. Nevertheless, current methods such as transcriptomes comparison approaches or searches for conserved secondary structures are not applicable to novel, previously unannotated lncRNAs by design.

Results

We present ortho2align—a versatile sensitive synteny-based lncRNA orthologue search tool with statistical assessment of sequence conservation. This tool allows control of the specificity of the search process and optional annotation of found orthologues. ortho2align shows similar performance in terms of sensitivity and resource usage as the state-of-the-art method for aligning orthologous lncRNAs but also enables scientists to predict unannotated orthologous sequences for lncRNAs in question. Using ortho2align, we predicted orthologues of three distinct classes of novel human lncRNAs in six Vertebrata species to estimate their degree of conservation.

Conclusions

Being designed for the discovery of unannotated orthologues of novel lncRNAs in distant species, ortho2align is a versatile tool applicable to any genomic regions, especially weakly conserved ones. A small amount of input files makes ortho2align easy to use in orthology studies as a single tool or in bundle with other steps that researchers will consider sensible. ortho2align is available as an Anaconda package with its source code hosted at https://github.com/dmitrymyl/ortho2align.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04929-y.

High temporal resolution RNA-seq time course data reveals widespread synchronous activation between mammalian lncRNAs and neighboring protein-coding genes

The advent of massively parallel sequencing revealed extensive transcription beyond protein-coding genes, identifying tens of thousands of long noncoding RNAs (lncRNAs). Selected functional examples raised the possibility that lncRNAs, as a class, may maintain broad regulatory roles. Expression of lncRNAs is strongly linked with adjacent protein-coding gene expression, suggesting potential cis-regulatory functions. A more detailed understanding of these regulatory roles may be obtained through careful examination of the precise timing of lncRNA expression relative to adjacent protein-coding genes. Despite the diversity of reported lncRNA regulatory mechanisms, where causal cis-regulatory relationships exist, lncRNA transcription is expected to precede changes in target gene expression. Using a high temporal resolution RNA-seq time course, we profiled the expression dynamics of several thousand lncRNAs and protein-coding genes in synchronized, transitioning human cells. Our findings reveal that lncRNAs are expressed synchronously with adjacent protein-coding genes. Analysis of lipopolysaccharide-activated mouse dendritic cells revealed the same temporal relationship observed in transitioning human cells. Our findings suggest broad-scale cis-regulatory roles for lncRNAs are not common. The strong association between lncRNAs and adjacent genes may instead indicate an origin as transcriptional by-products from active protein-coding gene promoters and enhancers.

Discovering functional motifs in long noncoding RNAs

Long noncoding RNAs (lncRNAs) are products of pervasive transcription that closely resemble messenger RNAs on the molecular level, yet function through largely unknown modes of action. The current model is that the function of lncRNAs often relies on specific, typically short, conserved elements, connected by linkers in which specific sequences and/or structures are less important. This notion has fueled the development of both computational and experimental methods focused on the discovery of functional elements within lncRNA genes, based on diverse signals such as evolutionary conservation, predicted structural elements, or the ability to rescue loss-of-function phenotypes. In this review, we outline the main challenges that the different methods need to overcome, describe the recently developed approaches, and discuss their respective limitations. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

Emerging Functions of lncRNA Loci beyond the Transcript Itself

Thousands of long noncoding RNAs (lncRNAs) are actively transcribed in mammalian genomes. This class of RNAs has important regulatory functions in a broad range of cellular processes and diseases. Numerous lncRNAs have been demonstrated to mediate gene regulation through RNA-based mechanisms. Simultaneously, non-functional lncRNA transcripts derived from the activity of lncRNA loci have been identified, which underpin the notion that a considerable fraction of lncRNA loci exert regulatory functions through mechanisms associated with the production or the activity of lncRNA loci beyond the synthesized transcripts. We particularly distinguish two main RNA-independent components associated with regulatory effects; the act of transcription and the activity of DNA regulatory elements. We describe the experimental approaches to distinguish and understand the functional mechanisms derived from lncRNA loci. These scenarios reveal emerging mechanisms important to understanding the lncRNA implications in genome biology.

Assessing and assuring interoperability of a genomics file format

Motivation

Bioinformatics software tools operate largely through the use of specialized genomics file formats. Often these formats lack formal specification, making it difficult or impossible for the creators of these tools to robustly test them for correct handling of input and output. This causes problems in interoperability between different tools that, at best, wastes time and frustrates users. At worst, interoperability issues could lead to undetected errors in scientific results.

Results

We developed a new verification system, Acidbio, which tests for correct behavior in bioinformatics software packages. We crafted tests to unify correct behavior when tools encounter various edge cases—potentially unexpected inputs that exemplify the limits of the format. To analyze the performance of existing software, we tested the input validation of 80 Bioconda packages that parsed the Browser Extensible Data (BED) format. We also used a fuzzing approach to automatically perform additional testing. Of 80 software packages examined, 75 achieved less than 70% correctness on our test suite. We categorized multiple root causes for the poor performance of different types of software. Fuzzing detected other errors that the manually designed test suite could not. We also created a badge system that developers can use to indicate more precisely which BED variants their software accepts and to advertise the software’s performance on the test suite.

Availability and implementation

Acidbio is available at https://github.com/hoffmangroup/acidbio.

Supplementary information

Supplementary data are available at Bioinformatics online.

The Role of Non-Coding RNAs in the Human Placenta

Non-coding RNAs (ncRNAs) play a central and regulatory role in almost all cells, organs, and species, which has been broadly recognized since the human ENCODE project and several other genome projects. Nevertheless, a small fraction of ncRNAs have been identified, and in the placenta they have been investigated very marginally. To date, most examples of ncRNAs which have been identified to be specific for fetal tissues, including placenta, are members of the group of microRNAs (miRNAs). Due to their quantity, it can be expected that the fairly larger group of other ncRNAs exerts far stronger effects than miRNAs. The syncytiotrophoblast of fetal origin forms the interface between fetus and mother, and releases permanently extracellular vesicles (EVs) into the maternal circulation which contain fetal proteins and RNA, including ncRNA, for communication with neighboring and distant maternal cells. Disorders of ncRNA in placental tissue, especially in trophoblast cells, and in EVs seem to be involved in pregnancy disorders, potentially as a cause or consequence. This review summarizes the current knowledge on placental ncRNA, their transport in EVs, and their involvement and pregnancy pathologies, as well as their potential for novel diagnostic tools.

Identification and Characterization of a Novel Long Noncoding RNA that Regulates Osteogenesis in Diet-Induced Obesity Mice

As a precursor to type 2 diabetes mellitus (T2D), obesity adversely alters bone cell functions, causing decreased bone quality. Currently, the mechanisms leading to alterations in bone quality in obesity and subsequently T2D are largely unclear. Emerging evidence suggests that long noncoding RNAs (lncRNAs) participate in a vast repertoire of biological processes and play essential roles in gene expression and posttranscriptional processes. Mechanistically, the expression of lncRNAs is implicated in pathogenesis surrounding the aggregation or alleviation of human diseases. To investigate the functional link between specific lncRNA and obesity-associated poor bone quality and elucidate the molecular mechanisms underlying the interaction between the two, we first assessed the structure of the bones in a diet-induced obese (DIO) mouse model. We found that bone microarchitecture markedly deteriorated in the DIO mice, mainly because of aberrant remodeling in the bone structure. The results of in vitro mechanistic experiments supported these observations. We then screened mRNAs and lncRNAs from DIO bones and functionally identified a specific lncRNA, Gm15222. Further analyses demonstrated that Gm15222 promotes osteogenesis and inhibits the expression of adipogenesis-related genes in DIO via recruitment of lysine demethylases KDM6B and KDM4B, respectively. Through this epigenetic pathway, Gm15222 modulates histone methylation of osteogenic genes. In addition, Gm15222 showed a positive correlation with the expression of a neighboring gene, BMP4. Together, the results of this study identified and provided initial characterization of Gm15222 as a critical epigenetic modifier that regulates osteogenesis and has potential roles in targeting the pathophysiology of bone disease in obesity and potential T2D.

Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level

Endothelial cells (ECs) are crucial for vascular and whole-body function through their dynamic response to environmental cues. Elucidating the transcriptome and epigenome of ECs is paramount to understanding their roles in development, health, and disease, but is limited in the availability of isolated primary cells. Recent technologies have enabled the high-throughput profiling of EC transcriptome and epigenome, leading to the identification of previously unknown EC cell subpopulations and developmental trajectories. While EC cultures are a useful tool in the exploration of EC function and dysfunction, the culture conditions and multiple passages can introduce external variables that alter the properties of native EC, including morphology, epigenetic state, and gene expression program. To overcome this limitation, the present paper demonstrates a method of isolating human primary ECs from donor mesenteric arteries aiming to capture their native state. ECs in the intimal layer are dissociated mechanically and biochemically with the use of particular enzymes. The resultant cells can be directly used for bulk RNA or single-cell RNA-sequencing or plated for culture. In addition, a workflow is described for the preparation of human arterial tissue for spatial transcriptomics, specifically for a commercially available platform, although this method is also suitable for other spatial transcriptome profiling techniques. This methodology can be applied to different vessels collected from a variety of donors in health or disease states to gain insights into EC transcriptional and epigenetic regulation, a pivotal aspect of endothelial cell biology.

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.

Regulatory Non-coding RNAs in Atherosclerosis

Regulatory RNAs like microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) control vascular and immune cells' phenotype and thus play a crucial role in atherosclerosis. Moreover, the mutual interactions between miRNAs and lncRNAs link both types of regulatory RNAs in a functional network that affects lesion formation. In this review, we deduce novel concepts of atherosclerosis from the analysis of the current data on regulatory RNAs' role in endothelial cells (ECs) and macrophages. In contrast to arterial ECs, which adopt a stable phenotype by adaptation to high shear stress, macrophages are highly plastic and quickly change their activation status. At predilection sites of atherosclerosis, such as arterial bifurcations, ECs are exposed to disturbed laminar flow, which generates a dysadaptive stress response mediated by miRNAs. Whereas the highly abundant miR-126-5p promotes regenerative proliferation of dysadapted ECs, miR-103-3p stimulates inflammatory activation and impairs endothelial regeneration by aberrant proliferation and micronuclei formation. In macrophages, miRNAs are essential in regulating energy and lipid metabolism, which affects inflammatory activation and foam cell formation.Moreover, lipopolysaccharide-induced miR-155 and miR-146 shape inflammatory macrophage activation through their oppositional effects on NF-kB. Most lncRNAs are not conserved between species, except a small group of very long lncRNAs, such as MALAT1, which blocks numerous miRNAs by providing non-functional binding sites. In summary, regulatory RNAs' roles are highly context-dependent, and therapeutic approaches that target specific functional interactions of miRNAs appear promising against cardiovascular diseases.

LncRNAs in domesticated animals: from dog to livestock species

Animal genomes are pervasively transcribed into multiple RNA molecules, of which many will not be translated into proteins. One major component of this transcribed non-coding genome is the long non-coding RNAs (lncRNAs), which are defined as transcripts longer than 200 nucleotides with low coding-potential capabilities. Domestic animals constitute a unique resource for studying the genetic and epigenetic basis of phenotypic variations involving protein-coding and non-coding RNAs, such as lncRNAs. This review presents the current knowledge regarding transcriptome-based catalogues of lncRNAs in major domesticated animals (pets and livestock species), covering a broad phylogenetic scale (from dogs to chicken), and in comparison with human and mouse lncRNA catalogues. Furthermore, we describe different methods to extract known or discover novel lncRNAs and explore comparative genomics approaches to strengthen the annotation of lncRNAs. We then detail different strategies contributing to a better understanding of lncRNA functions, from genetic studies such as GWAS to molecular biology experiments and give some case examples in domestic animals. Finally, we discuss the limitations of current lncRNA annotations and suggest research directions to improve them and their functional characterisation.

Genome Instability and Long Noncoding RNA Reveal Biomarkers for Immunotherapy and Prognosis and Novel Competing Endogenous RNA Mechanism in Colon Adenocarcinoma

Background: Long noncoding RNAs (lncRNAs) crucially modulate DNA damage responses/repair in cancer cells. However, the underlying regulatory role of genome integrity and its clinical value in colon adenocarcinoma (COAD) remains unclear. This study links genome instability to lncRNA using computational biology techniques, in attempt to propose novel biomarkers of immunotherapy outcome, and investigated a potential competing endogenous RNA (ceRNA) as a molecular regulatory mechanism.

Methods: TCGA-COAD patients were divided into genome unstable (GU)-like and genome stable (GS)-like clusters via hierarchical clustering to predict immunotherapy outcomes. Multivariate Cox model was established to predict the overall survival rate in COAD patients. Additionally, SVM and LASSO algorithms were applied to obtain hub lncRNAs. A novel genome instability-related ceRNA network was predicted with the Starbase 2.0 database. To better understand how these genes fundamentally interact during tumor progression and development, the mutation analysis and single-gene analysis for each gene was performed.

Results: In contrast to those in the GS-like cluster, GU-like-cluster patients demonstrated a higher tumor mutational burden (TMB)/microsatellite instability (MSI), DNA polymerase epsilon (POLE) mutation rate, and immune checkpoint expression, all indicate a greater predictive power for response rate for immunotherapy. The novel prognostic signature demonstrated an outstanding predictive performance (AUC > 0.70). The genes in the genome insatiability-related ceRNA network (including four axes: AL161772.1-has-miR-671-5p (hsa-miR-181d-5p, has-miR-106a-5p)-NINL, AL161772.1-has-miR-106a-5p-TNFSF11, AC124067.4-hsa-miR-92b-3p (hsa-miR-589-5p)-PHYHIPL, and BOLA3-AS1-has-miR-130b-3p-SALL4) were identified as critical regulators of tumor microenvironment infiltration, cancer stemness, and drug resistance. qPCR was performed to validate the expression patterns of these genes. Furthermore, the MSI-high proportion was greater in patients with mutated type than in those with the wild type according to all four target genes, indicating that these four genes modulate genomic integrity and could serve as novel immunotherapy biomarkers.

Conclusion: We demonstrated that genome instability-related lncRNA is a novel biomarker for immunotherapy outcomes and prognosis. A novel ceRNA network that modulates genomic integrity, including four lncRNA-miRNA-mRNA axes, was proposed.

SVDNVLDA: predicting lncRNA-disease associations by Singular Value Decomposition and node2vec

Background

Numerous studies on discovering the roles of long non-coding RNAs (lncRNAs) in the occurrence, development and prognosis progresses of various human diseases have drawn substantial attentions. Since only a tiny portion of lncRNA-disease associations have been properly annotated, an increasing number of computational methods have been proposed for predicting potential lncRNA-disease associations. However, traditional predicting models lack the ability to precisely extract features of biomolecules, it is urgent to find a model which can identify potential lncRNA-disease associations with both efficiency and accuracy.

Results

In this study, we proposed a novel model, SVDNVLDA, which gained the linear and non-linear features of lncRNAs and diseases with Singular Value Decomposition (SVD) and node2vec methods respectively. The integrated features were constructed from connecting the linear and non-linear features of each entity, which could effectively enhance the semantics contained in ultimate representations. And an XGBoost classifier was employed for identifying potential lncRNA-disease associations eventually.

Conclusions

We propose a novel model to predict lncRNA-disease associations. This model is expected to identify potential relationships between lncRNAs and diseases and further explore the disease mechanisms at the lncRNA molecular level.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04457-1.

Data integration and evolutionary analysis of long non-coding RNAs in 25 flowering plants

Background

Long non-coding RNAs (lncRNAs) play vital roles in many important biological processes in plants. Currently, a large fraction of plant lncRNA studies center at lncRNA identification and functional analysis. Only a few plant lncRNA studies focus on understanding their evolutionary history, which is crucial for an in-depth understanding of lncRNAs. Therefore, the integration of large volumes of plant lncRNA data is required to deeply investigate the evolution of lncRNAs.

Results

We present a large-scale evolutionary analysis of lncRNAs in 25 flowering plants. In total, we identified 199,796 high-confidence lncRNAs through data integration analysis, and grouped them into 5497 lncRNA orthologous families. Then, we divided the lncRNAs into groups based on the degree of sequence conservation, and quantified the various characteristics of 756 conserved Arabidopsis thaliana lncRNAs. We found that compared with non-conserved lncRNAs, conserved lncRNAs might have more exons, longer sequence length, higher expression levels, and lower tissue specificities. Functional annotation based on the A. thaliana coding-lncRNA gene co-expression network suggested potential functions of conserved lncRNAs including autophagy, locomotion, and cell cycle. Enrichment analysis revealed that the functions of conserved lncRNAs were closely related to the growth and development of the tissues in which they were specifically expressed.

Conclusions

Comprehensive integration of large-scale lncRNA data and construction of a phylogenetic tree with orthologous lncRNA families from 25 flowering plants was used to provide an oversight of the evolutionary history of plant lncRNAs including origin, conservation, and orthologous relationships. Further analysis revealed a differential characteristic profile for conserved lncRNAs in A. thaliana when compared with non-conserved lncRNAs. We also examined tissue specific expression and the potential functional roles of conserved lncRNAs. The results presented here will further our understanding of plant lncRNA evolution, and provide the basis for further in-depth studies of their functions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08047-6.

NAIL: an evolutionarily conserved lncRNA essential for licensing coordinated activation of p38 and NFκB in colitis

OBJECTIVE

NFκB is the key modulator in inflammatory disorders. However, the key regulators that activate, fine-tune or shut off NFκB activity in inflammatory conditions are poorly understood. In this study, we aim to investigate the roles that NFκB-specific long non-coding RNAs (lncRNAs) play in regulating inflammatory networks.

DESIGN

Using the first genetic-screen to identify NFκB-specific lncRNAs, we performed RNA-seq from the p65^-/- and Ikkβ^-/- mouse embryonic fibroblasts and report the identification of an evolutionary conserved lncRNA designated mNAIL (mice) or hNAIL (human). hNAIL is upregulated in human inflammatory disorders, including UC. We generated mNAIL^ΔNFκB mice, wherein deletion of two NFκB sites in the proximal promoter of mNAIL abolishes its induction, to study its function in colitis.

RESULTS

NAIL regulates inflammation via sequestering and inactivating Wip1, a known negative regulator of proinflammatory p38 kinase and NFκB subunit p65. Wip1 inactivation leads to coordinated activation of p38 and covalent modifications of NFκB, essential for its genome-wide occupancy on specific targets. NAIL enables an orchestrated response for p38 and NFκB coactivation that leads to differentiation of precursor cells into immature myeloid cells in bone marrow, recruitment of macrophages to inflamed area and expression of inflammatory genes in colitis.

CONCLUSION

NAIL directly regulates initiation and progression of colitis and its expression is highly correlated with NFκB activity which makes it a perfect candidate to serve as a biomarker and a therapeutic target for IBD and other inflammation-associated diseases.

TransLnc: a comprehensive resource for translatable lncRNAs extends immunopeptidome

LncRNAs are not only well-known as non-coding elements, but also serve as templates for peptide translation, playing important roles in fundamental cellular processes and diseases. Here, we describe a database, TransLnc (http://bio-bigdata.hrbmu.edu.cn/TransLnc/), which aims to provide comprehensive experimentally supported and predicted lncRNA peptides in multiple species. TransLnc currently documents approximate 583 840 peptides encoded by 33 094 lncRNAs. Six types of direct and indirect evidences supporting the coding potential of lncRNAs were integrated, and 65.28% peptides entries were with at least one type of evidence. Considering the strong tissue-specific expression of lncRNAs, TransLnc allows users to access lncRNA peptides in any of the 34 tissues involved in. In addition, both the unique characteristic and homology relationship were also predicted and provided. Importantly, TransLnc provides computationally predicted tumour neoantigens from peptides encoded by lncRNAs, which would provide novel insights into cancer immunotherapy. There were 220 791 and 237 915 candidate neoantigens binding by major histocompatibility complex (MHC) class I or II molecules, respectively. Several flexible tools were developed to aid retrieve and analyse, particularly lncRNAs tissue expression patterns, clinical relevance across cancer types. TransLnc will serve as a valuable resource for investigating the translation capacity of lncRNAs and greatly extends the cancer immunopeptidome.

A comprehensive method protocol for annotation and integrated functional understanding of lncRNAs

Long non-coding RNAs (lncRNAs) are of fundamental biological importance; however, their functional role is often unclear or loosely defined as experimental characterization is challenging and bioinformatic methods are limited. We developed a novel integrated method protocol for the annotation and detailed functional characterization of lncRNAs within the genome. It combines annotation, normalization and gene expression with sequence-structure conservation, functional interactome and promoter analysis. Our protocol allows an analysis based on the tissue and biological context, and is powerful in functional characterization of experimental and clinical RNA-Seq datasets including existing lncRNAs. This is demonstrated on the uncharacterized lncRNA GATA6-AS1 in dilated cardiomyopathy.

Evolutionarily conserved transcriptional landscape of the heart defining the chamber specific physiology

Cardiovascular disease (CVD) remains the leading cause of death worldwide. A deeper characterization of regional transcription patterns within different heart chambers may aid to improve our understanding of the molecular mechanisms involved in myocardial function and further, our ability to develop novel therapeutic strategies. Here, we used RNA sequencing to determine differentially expressed protein coding (PC) and long non-coding (lncRNA) transcripts within the heart chambers across seven vertebrate species and identified evolutionarily conserved chamber specific genes, lncRNAs and pathways. We investigated lncRNA homologs based on sequence, secondary structure, synteny and expressional conservation and found most lncRNAs to be conserved by synteny. Regional co-expression patterns of transcripts are modulated by multiple factors, including genomic overlap, strandedness and transcript biotype. Finally, we provide a community resource designated EvoACTG, which informs researchers on the conserved yet intertwined nature of the coding and non-coding cardiac transcriptome across popular model organisms in CVD research.

Evolutionary conservation in noncoding genomic regions

Humans may share more genomic commonalities with other species than previously thought. According to current estimates, ~5% of the human genome is functionally constrained, which is a much larger fraction than the ~1.5% occupied by annotated protein-coding genes. Hence, ~3.5% of the human genome comprises likely functional conserved noncoding elements (CNEs) preserved among organisms, whose common ancestors existed throughout hundreds of millions of years of evolution. As whole-genome sequencing emerges as a standard procedure in genetic analyses, interpretation of variations in CNEs, including the elucidation of mechanistic and functional roles, becomes a necessity. Here, we discuss the phenomenon of noncoding conservation via four dimensions (sequence, regulatory conservation, spatiotemporal expression, and structure) and the potential significance of CNEs in phenotype variation and disease.

Identification of a Genome Instability-Associated LncRNA Signature for Prognosis Prediction in Colon Cancer

Long non-coding RNAs (lncRNAs) were reported to have the potential in maintaining genome instability, but the identification of lncRNAs related to genome instability and their prognostic value have not been largely explored in colon cancer. In this study, we obtained 155 genome instability-associated lncRNAs based on somatic mutation profiles in colon cancer from The Cancer Genome Atlas (TCGA) database. Functional enrichment analysis revealed the possible roles of genes co-expressed with those lncRNAs involved in some cancer, genome instability and immune related biological processes. Combined with overall survival data, a seven-lncRNA signature was established for prognosis prediction. According to the risk score calculated by this signature, high-risk patients characterized by high somatic mutation count, high microsatellite instability, significantly poorer clinical outcomes and specific tumor immune infiltration status compared with low-risk patients. The lncRNA signature was validated to be an independent prognostic indicator with good predictive performance in TCGA cohort. Furthermore, the prognostic value of the ZNF503-AS1 in lncRNA signature was confirmed in another independent dataset from Gene Expression Omnibus database. In summary, the genome instability-associated lncRNA signature in this study could be a promising tool for effectively predicting survival outcomes in colon cancer.

Targeting Human lncRNAs for Treating Cardiometabolic Diseases

BACKGROUND

Long non-coding RNAs (lncRNAs) have evolved as a critical regulatory mechanism for almost all biological processes. By dynamically interacting with their molecular partners, lncRNAs regulate gene activity at multiple levels ranging from transcription, pre-mRNA splicing, RNA transporting, RNA decay, and translation of mRNA.

RESULTS AND CONCLUSIONS

Dysregulation of lncRNAs has been associated with human diseases, including cancer, neurodegenerative, and cardiometabolic diseases. However, as lncRNAs are usually much less conserved than mRNAs at the sequence level, most human lncRNAs are either primate or human specific. The pathophysiological significance of human lncRNAs is still mostly unclear due to the persistent limitations in studying human-specific genes. This review will focus on recent discoveries showing human lncRNAs' roles in regulating metabolic homeostasis and the potential of targeting this unique group of genes for treatment of cardiometabolic diseases.

Noncanonical open reading frames encode functional proteins essential for cancer cell survival

Although genomic analyses predict many noncanonical open reading frames (ORFs) in the human genome, it is unclear whether they encode biologically active proteins. Here we experimentally interrogated 553 candidates selected from noncanonical ORF datasets. Of these, 57 induced viability defects when knocked out in human cancer cell lines. Following ectopic expression, 257 showed evidence of protein expression and 401 induced gene expression changes. Clustered regularly interspaced short palindromic repeat (CRISPR) tiling and start codon mutagenesis indicated that their biological effects required translation as opposed to RNA-mediated effects. We found that one of these ORFs, G029442-renamed glycine-rich extracellular protein-1 (GREP1)-encodes a secreted protein highly expressed in breast cancer, and its knockout in 263 cancer cell lines showed preferential essentiality in breast cancer-derived lines. The secretome of GREP1-expressing cells has an increased abundance of the oncogenic cytokine GDF15, and GDF15 supplementation mitigated the growth-inhibitory effect of GREP1 knockout. Our experiments suggest that noncanonical ORFs can express biologically active proteins that are potential therapeutic targets.

The Roles of Host Noncoding RNAs in Mycobacterium tuberculosis Infection

Tuberculosis remains a major health problem. Mycobacterium tuberculosis, the causative agent of tuberculosis, can replicate and persist in host cells. Noncoding RNAs (ncRNAs) widely participate in various biological processes, including Mycobacterium tuberculosis infection, and play critical roles in gene regulation. In this review, we summarize the latest reports on ncRNAs (microRNAs, piRNAs, circRNAs and lncRNAs) that regulate the host response against Mycobacterium tuberculosis infection. In the context of host-Mycobacterium tuberculosis interactions, a broad and in-depth understanding of host ncRNA regulatory mechanisms may lead to potential clinical prospects for tuberculosis diagnosis and the development of new anti-tuberculosis therapies.

Long noncoding RNA-dependent methylation of nonhistone proteins

In the last decade, an intriguing new paradigm of regulation has emerged in which some transcripts longer than 200 nucleotides and no coding potential, long noncoding RNA (lncRNAs), exhibit the capability to control posttranslational modifications of nonhistone proteins in both invertebrates and vertebrates. The extent of such a regulation is still largely unknown. We performed a systematic review to identify and evaluate the potential impact of lncRNA-dependent methylation of nonhistone proteins. Collectively, these lncRNAs primarily act as scaffolds upon which methyltransferases (MTases) and targets are brought in proximity. In this manner, the N-MTase activity of EZH2, protein arginine-MTase 1/4/5, and SMYD2 is exploited to modulate the stability or the compartmentalization of several nonhistone proteins with roles in cell signaling, gene expression, and RNA processing. Moreover, these lncRNAs can indirectly affect the methylation of nonhistone proteins by transcriptional or posttranscriptional regulation of MTases. Strikingly, the lncRNAs/MTases/nonhistone proteins networking seem to be relevant to carcinogenesis and neurological disorders. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

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.

lncRNA SNHG9 Promotes Cell Proliferation, Migration, and Invasion in Human Hepatocellular Carcinoma Cells by Increasing GSTP1 Methylation, as Revealed by CRISPR-dCas9

Hepatocellular carcinoma (HCC) is among the major causes of cancer-related mortalities globally. Long non-coding RNAs (LncRNAs), as epigenetic molecules, contribute to malignant tumor incidences and development, including HCC. Although LncRNA SNHG9 is considered an oncogene in many cancers, the biological function and molecular mechanism of SNHG9 in HCC are still unclear. We investigated the effects of lncRNA SNHG9 on the methylation of glutathione S-transferase P1 (GSTP1) and the progression of HCC. Histological data analysis, CRISPR-dCas9, and cytological function experiment were used to study the expression level and biological function of SNHG9 in HCC. There was an upregulated expression of SNHG9 in HCC, which was associated with shorter disease-free survival. Knockdown of SNHG9 can inhibit cell proliferation, block cell cycle progression, and inhibit cell migration and invasion by upregulating GSTP1. LncRNA SNHG9 recruits methylated enzymes (DNMT1, DNMT3A, and DNMT3B) to increase GSTP1 promoter methylation, a common event in the development of HCC. Inhibition of lncRNA SNHG9 demethylates GSTP1, which prevents HCC progression, presents a promising therapeutic approach for HCC patients.

Long noncoding RNAs-a new dimension in the molecular architecture of the bile acid/FXR pathway

Bile acids, regarded as the body's detergent for digesting lipids, also function as critical signaling molecules that regulate cholesterol and triglyceride levels in the body. Bile acids are the natural ligands of the nuclear receptor, FXR, which controls an intricate network of cellular pathways to maintain metabolic homeostasis. In recent years, growing evidence supports that many cellular actions of the bile acid/FXR pathway are mediated by long non-coding RNAs (lncRNAs), and lncRNAs are in turn powerful regulators of bile acid levels and FXR activities. In this review, we highlight the substantial progress made in the understanding of the functional and mechanistic role of lncRNAs in bile acid metabolism and how lncRNAs connect bile acid activity to additional metabolic processes. We also discuss the potential of lncRNA studies in elucidating novel molecular mechanisms of the bile acid/FXR pathway and the promise of lncRNAs as potential diagnostic markers and therapeutic targets for diseases associated with altered bile acid metabolism.

Characterization of Long Non-Coding RNA Profiles in Porcine Granulosa Cells of Healthy and Atretic Antral Follicles: Implications for a Potential Role in Apoptosis

Long non-coding RNAs (lncRNAs) play important roles in multiple biological processes including ovarian follicular development. Here we aimed to gain novel information regarding lncRNAs transcriptome profiles in porcine granulosa cells of advanced atretic antral (AA) and healthy antral (HA) follicles using RNA-seq. A total of 11,321 lncRNAs including 10,813 novel and 508 annotated lncRNAs were identified, of which 173 lncRNAs were differentially expressed (DE-lncRNAs); ten of these were confirmed by qRT-PCR. Gene Ontology indicated that DE-lncRNAs associated with developmental processes were highly enriched. Pathway analysis demonstrated predicted cis- and trans-targets of DE-lncRNAs. Potential mRNA targets of up-regulated DE-lncRNAs were mainly enriched in apoptosis related pathways, while targeted genes of downregulated DE-lncRNAs were primarily enriched in metabolism and ovarian steroidogenesis pathways. Linear regression analyses showed that expression of upregulated DE-lncRNAs was significantly associated with apoptosis related genes. NOVEL_00001850 is the most-downregulated DE-lncRNA (FDR = 0.04, FC = -6.53), of which miRNA binding sites were predicted. KEGG analysis of its downregulated target genes revealed that ovarian steroidogenesis was the second most highlighted pathway. qRT-PCR and linear regression analysis confirmed the expression and correlation of its potential targeted gene, CYP19A1, a key gene involved in estradiol synthesis. Our results indicate that lncRNAs may participate in granulosa cells apoptosis and thus antral follicular atresia.

Long Noncoding RNAs in Human Stemness and Differentiation

There is increasing evidence that long noncoding RNAs (lncRNAs) are among the main regulatory factors of stem cell maintenance and differentiation. They act through various mechanisms and interactions with proteins, DNA, and RNA. This heterogeneity in function increases the capabilities of the lncRNome toolkit but also makes it difficult to predict the function of novel lncRNAs or even rely on biological information produced in animal models. As lncRNAs are species- and tissue-specific, the recent technical advances in self-renewal and differentiation of human embryonic stem cells (ESCs) make these cells the ideal system to identify key regulatory lncRNAs and study their molecular functions. Here we provide an overview of the functional versatility of lncRNA mechanistic heterogeneity in regulating pluripotency maintenance and human differentiation.