LNCipedia 5: towards a reference set of human long non-coding RNAs

LncRNAs (long non-coding RNAs) are pervasively transcribed in the human genome and also extensively involved in a variety of essential biological processes and human diseases. The comprehensive annotation of human lncRNAs is of great significance in navigating the functional landscape of the human genome and deepening the understanding of the multi-featured RNA world. However, the unique characteristics of lncRNAs as well as their enormous quantity have complicated and challenged the annotation of lncRNAs. Advances in high-throughput sequencing technologies give rise to a large volume of omics data that are generated at an unprecedented rate and scale, providing possibilities in the identification, characterization and functional annotation of lncRNAs. Here, we review the recent important discoveries of human lncRNAs through analysis of various omics data and summarize specialized lncRNA database resources. Moreover, we highlight the multi-omics integrative analysis as a powerful strategy to efficiently discover and characterize the functional lncRNAs and elucidate their potential molecular mechanisms.

The lncRNA DEANR1 facilitates human endoderm differentiation by activating FOXA2 expression.

In the past decade, significant resources have been invested in long noncoding RNA (lncRNA) research. Despite the knowledge available, we are far from incorporation of lncRNA into clinical practice. Here, we emphasize the technical challenges in the field, hoping to provoke a response leading to new consensus and guidelines.

High-throughput long noncoding RNA profiling for diagnostic and prognostic markers in cancer: opportunities and challenges.

The mammalian imprinted Dlk1-Dio3 locus produces multiple long non-coding RNAs (lncRNAs) from the maternally inherited allele, including Meg3 (i.e., Gtl2) in the mammalian genome. Although this locus has well-characterized functions in stem cell and tumor contexts, its role during neural development is unknown. By profiling cell types at each stage of embryonic stem cell-derived motor neurons (ESC~MNs) that recapitulate spinal cord development, we uncovered that lncRNAs expressed from the Dlk1-Dio3 locus are predominantly and gradually enriched in rostral motor neurons (MNs). Mechanistically, Meg3 and other Dlk1-Dio3 locus-derived lncRNAs facilitate Ezh2/Jarid2 interactions. Loss of these lncRNAs compromises the H3K27me3 landscape, leading to aberrant expression of progenitor and caudal Hox genes in postmitotic MNs. Our data thus illustrate that these lncRNAs in the Dlk1-Dio3 locus, particularly Meg3, play a critical role in maintaining postmitotic MN cell fate by repressing progenitor genes and they shape MN subtype identity by regulating Hox genes.

Long non-coding RNAs in humans: Classification, genomic organization and function.

Pan-cancer analysis of non-coding transcripts reveals the prognostic onco-lncRNA HOXA10-AS in gliomas.

Ischemic stroke is a leading cause of long-term disability and death, making it crucial to understand the underlying cellular and molecular mechanisms. Research into these mechanisms has gained significant attention, with a particular focus on long noncoding RNAs, which are greater than 200 nucleotides in length. Recent studies using RNA sequencing, deep sequencing, and microarrays have identified numerous long non-coding RNAs that are aberrantly expressed in both patients with ischemic stroke and animal models of ischemic injury. In recent years, research on long non-coding RNAs has identified various types that exhibit both vascular protective effects and harmful effects, which are related to the regulation of vascular regeneration in the nervous system. These findings offer new targets for the study of ischemic stroke. The purpose of this review is to summarize the current research progress on the role of long non-coding RNAs in angiogenesis after ischemic stroke and to explore their potential clinical significance and new technologies. With advances in new technologies, such as RNA sequencing and deep sequencing, researchers can gain deeper insights into the functions and mechanisms of long noncoding RNAs. The application of these technologies has not only enhanced the understanding of the role of long non-coding RNAs in stroke but also opened up possibilities for the development of new therapeutic strategies. This review highlights the critical roles of long non-coding RNAs such as MALAT1, XIST, and MEG3 in angiogenesis after ischemic stroke and discusses how they participate in this process through different molecular mechanisms. These findings provide new molecular targets for the treatment of ischemic stroke and pave the way for future research. As new technological advancements emerge, there is hope for a deeper understanding of long non-coding RNAs in ischemic stroke, which could assist in the development of more precise tools for clinical diagnosis and treatment. Although there are still challenges to overcome, the prospects for long non-coding RNA research are encouraging, and they are anticipated to play a crucial role in the study and management of ischemic stroke.

Mitochondria currently appear to be a major destination for the RNA trafficking and localization processes that control and coordinate gene expression in living cells. A large set of messenger RNAs derived from the nuclear genome is translated at the mitochondrial surface, while an increasing series of noncoding RNAs has been reported to localize in the organelles, including microRNAs, additional small noncoding RNAs, transfer RNAs, and long noncoding RNAs. These RNA species contribute to mitochondrial functions and control of organellar gene expression, but mitochondria might also store and release noncoding RNAs of nuclear origin having cytosolic targets. Conversely, data have emerged implying that small and long noncoding regulatory RNAs are generated within the organelles from the mitochondrial genome. Some of them nevertheless appeared to localize to the nucleus or were recovered in body fluids. Integrating all reported data leads to an intricate picture of multidirectional RNA trafficking and intercompartment communication that can be related to cellular homeostasis, cell differentiation, pathogenesis, or disease. However, a number of facets in this amazing picture are still a matter of debate, as the mechanisms underlying nucleic acid translocation through the mitochondrial membranes remain difficult to assess and the widespread presence of mitochondrial DNA pseudo-sequences in the nuclear genome can make the origin of some transcripts confusing. A detailed panorama of the reported mitochondrial noncoding RNAs and of the questions raised by the data is developed here in relation to major mitochondrial processes.

The human genome contains many thousands of long noncoding RNAs (lncRNAs). While several studies have demonstrated compelling biological and disease roles for individual examples, analytical and experimental approaches to investigate these genes have been hampered by the lack of comprehensive lncRNA annotation. Here, we present and analyze the most complete human lncRNA annotation to date, produced by the GENCODE consortium within the framework of the ENCODE project and comprising 9277 manually annotated genes producing 14,880 transcripts. Our analyses indicate that lncRNAs are generated through pathways similar to that of protein-coding genes, with similar histone-modification profiles, splicing signals, and exon/intron lengths. In contrast to protein-coding genes, however, lncRNAs display a striking bias toward two-exon transcripts, they are predominantly localized in the chromatin and nucleus, and a fraction appear to be preferentially processed into small RNAs. They are under stronger selective pressure than neutrally evolving sequences—particularly in their promoter regions, which display levels of selection comparable to protein-coding genes. Importantly, about one-third seem to have arisen within the primate lineage. Comprehensive analysis of their expression in multiple human organs and brain regions shows that lncRNAs are generally lower expressed than protein-coding genes, and display more tissue-specific expression patterns, with a large fraction of tissue-specific lncRNAs expressed in the brain. Expression correlation analysis indicates that lncRNAs show particularly striking positive correlation with the expression of antisense coding genes. This GENCODE annotation represents a valuable resource for future studies of lncRNAs.

Related studies showed that the protein PSF represses proto-oncogene transcription, and VL30-1 RNA, a mouse noncoding retroelement RNA, binds and releases PSF from a proto-oncogene, activating transcription. Here we show that this mechanism regulates tumorigenesis in human cells, with human RNAs replacing VL30-1 RNA. A library of human RNA fragments was used to isolate, by affinity chromatography, 5 noncoding RNA fragments that bind to human PSF (hPSF), releasing hPSF from a proto-oncogene and activating transcription. Each of the 5 RNA fragments maps to a different human gene. The tumorigenic function of the hPSF-binding RNAs was tested in a human melanoma line and mouse fibroblast line, by determining the effect of the RNAs on formation of colonies in agar and tumors in mice. (i) Expressing in human melanoma cells the RNA fragments individually promoted tumorigenicity. (ii) Expressing in human melanoma cells a shRNA, which causes degradation of the endogenous RNA from which an RNA fragment was derived, suppressed tumorigenicity. (iii) Expressing in mouse NIH/3T3 cells the RNA fragments individually resulted in transformation to tumorigenic cells. (iv) A screen of 9 human tumor lines showed that each line expresses high levels of several hPSF-binding RNAs, relative to the levels in human fibroblast cells. We conclude that human hPSF-binding RNAs drive transformation and tumorigenesis by reversing PSF-mediated repression of proto-oncogene transcription and that dysfunctional regulation of human hPSF-binding RNA expression has a central role in the etiology of human cancer.

Long non-coding RNAs (lncRNAs) are important transcripts that are more than 200 nucleotides in length, and distribute extensively in animal and plant genomes. Accumulated studies demonstrate that lncRNAs play critical roles in biological processes related to embryogenesis, muscle development, lipid deposition and immune responses. They assist protein complexes in translocating to appropriate locations and participate in regulating gene activation and inactivation. Recently, rapid progress of lncRNA research is emerging, largely due to molecular biological technologies and information developed in the human genome project and the Encyclopedia of DNA Elements (ENCODE) project. For example, a dwarf open reading frame (DWORF) encoded by an annotated lncRNA was reported to activate the SERCA pump. Moreover, small regulatory polypeptide of amino acid response (SPAR) encoded by lncRNA LINC00961 was found to regulate muscle regeneration. These new results have revealed a novel model that lncRNA regulates biological processes using its small peptide product. In this review, we summarize the characteristics, databases, biological functions and molecular regulatory models, as well as research interests of lncRNAs in the future.

As the biological roles and disease implications of non-coding RNAs continue to emerge, the need to thoroughly characterize previously unexplored non-coding RNAs becomes increasingly urgent. These molecules hold potential as biomarkers and therapeutic targets. However, the vast and complex nature of non-coding RNAs data presents a challenge. We introduce MMnc, an interpretable deep-learning approach designed to classify non-coding RNAs into functional groups. MMnc leverages multiple data sources-such as the sequence, secondary structure, and expression-using attention-based multi-modal data integration. This ensures the learning of meaningful representations while accounting for missing sources in some samples. Our findings demonstrate that MMnc achieves high classification accuracy across diverse non-coding RNA classes. The method's modular architecture allows for the consideration of multiple types of modalities, whereas other tools only consider one or two at most. MMnc is resilient to missing data, ensuring that all available information is effectively utilized. Importantly, the generated attention scores offer interpretable insights into the underlying patterns of the different non-coding RNA classes, potentially driving future non-coding RNA research and applications. Data and source code can be found at EvryRNA.ibisc.univ-evry.fr/EvryRNA/MMnc.

Visiting “Noncodarnia”

Protein-translated mRNA analysis has been extensively used to determine the function of various traits in animals. The non-coding RNA (ncRNA), which was known to be non-functional because it was not encoded as a protein, was re-examined as it was studied to actually function. One of the ncRNAs, long non-coding RNA (lncRNA), is known to have a function of regulating mRNA expression, and its importance is emerging. Therefore, lncRNAs are currently being used to understand the traits of various animals as well as human diseases. However, studies on lncRNA annotation and its functions are still lacking in most animals except humans and mice. lncRNAs have unique characteristics of lncRNAs and interact with mRNA through various mechanisms. In order to make lncRNA annotations in animals in the future, it is essential to understand the characteristics of lncRNAs and the mechanisms by which lncRNAs function. In addition, this will allow lncRNAs to be used for a wider variety of traits in a wider range of animals, and it is expected that integrated analysis using other biological information will be possible.