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Recent advances in RNA-sequencing technologies have led to the discovery of thousands of previously unannotated noncoding transcripts, including many long noncoding RNAs (lncRNAs) whose functions remain largely unknown. Here, the authors discuss considerations and best practices when identifying and annotating lncRNAs that should aid their functional and mechanistic exploration. Recent advances in RNA-sequencing technologies have led to the discovery of thousands of previously unannotated noncoding transcripts, including many long noncoding RNAs (lncRNAs) whose functions remain largely unknown. Here we discuss considerations and best practices in lncRNA identification and annotation, which we hope will foster functional and mechanistic exploration.

Long noncoding RNAs (lncRNAs) fulfill a variety of regulatory roles in gene expression, which are dictated by their RNA structure, chemistry and modular domain structure. In this Review, the focus is on the well-characterized ability for lncRNAs to function as epigenetic modulators as part of a broad epigenetic regulatory network. Genomes of complex organisms encode an abundance and diversity of long noncoding RNAs (lncRNAs) that are expressed throughout the cell and fulfill a wide variety of regulatory roles at almost every stage of gene expression. These roles, which encompass sensory, guiding, scaffolding and allosteric capacities, derive from folded modular domains in lncRNAs. In this diverse functional repertoire, we focus on the well-characterized ability for lncRNAs to function as epigenetic modulators. Many lncRNAs bind to chromatin-modifying proteins and recruit their catalytic activity to specific sites in the genome, thereby modulating chromatin states and impacting gene expression. Considering this regulatory potential in combination with the abundance of lncRNAs suggests that lncRNAs may be part of a broad epigenetic regulatory network.

The majority of the genome in animals and plants is transcribed in a developmentally regulated manner to produce large numbers of non-protein-coding RNAs (ncRNAs), whose incidence increases with developmental complexity. There is growing evidence that these transcripts are functional, particularly in the regulation of epigenetic processes, leading to the suggestion that they compose a hitherto hidden layer of genomic programming in humans and other complex organisms. However, to date, very few have been identified in genetic screens. Here I show that this is explicable by an historic emphasis, both phenotypically and technically, on mutations in protein-coding sequences, and by presumptions about the nature of regulatory mutations. Most variations in regulatory sequences produce relatively subtle phenotypic changes, in contrast to mutations in protein-coding sequences that frequently cause catastrophic component failure. Until recently, most mapping projects have focused on protein-coding sequences, and the limited number of identified regulatory mutations have been interpreted as affecting conventional cis-acting promoter and enhancer elements, although these regions are often themselves transcribed. Moreover, ncRNA-directed regulatory circuits underpin most, if not all, complex genetic phenomena in eukaryotes, including RNA interference-related processes such as transcriptional and post-transcriptional gene silencing, position effect variegation, hybrid dysgenesis, chromosome dosage compensation, parental imprinting and allelic exclusion, paramutation, and possibly transvection and transinduction. The next frontier is the identification and functional characterization of the myriad sequence variations that influence quantitative traits, disease susceptibility, and other complex characteristics, which are being shown by genome-wide association studies to lie mostly in noncoding, presumably regulatory, regions. There is every possibility that many of these variations will alter the interactions between regulatory RNAs and their targets, a prospect that should be borne in mind in future functional analyses.

Background Long non-protein-coding RNAs (ncRNAs) are emerging as important regulators of cellular differentiation and are widely expressed in the brain. Results Here we show that many long ncRNAs exhibit dynamic expression patterns during neuronal and oligodendrocyte (OL) lineage specification, neuronal-glial fate transitions, and progressive stages of OL lineage elaboration including myelination. Consideration of the genomic context of these dynamically regulated ncRNAs showed they were part of complex transcriptional loci that encompass key neural developmental protein-coding genes, with which they exhibit concordant expression profiles as indicated by both microarray and in situ hybridization analyses. These included ncRNAs associated with differentiation-specific nuclear subdomains such as Gomafu and Neat1 , and ncRNAs associated with developmental enhancers and genes encoding important transcription factors and homeotic proteins. We also observed changes in ncRNA expression profiles in response to treatment with trichostatin A, a histone deacetylase inhibitor that prevents the progression of OL progenitors into post-mitotic OLs by altering lineage-specific gene expression programs. Conclusion This is the first report of long ncRNA expression in neuronal and glial cell differentiation and of the modulation of ncRNA expression by modification of chromatin architecture. These observations explicitly link ncRNA dynamics to neural stem cell fate decisions, specification and epigenetic reprogramming and may have important implications for understanding and treating neuropsychiatric diseases.

Genes specifying long non-coding RNAs (lncRNAs) occupy a large fraction of the genomes of complex organisms. The term ‘lncRNAs’ encompasses RNA polymerase I (Pol I), Pol II and Pol III transcribed RNAs, and RNAs from processed introns. The various functions of lncRNAs and their many isoforms and interleaved relationships with other genes make lncRNA classification and annotation difficult. Most lncRNAs evolve more rapidly than protein-coding sequences, are cell type specific and regulate many aspects of cell differentiation and development and other physiological processes. Many lncRNAs associate with chromatin-modifying complexes, are transcribed from enhancers and nucleate phase separation of nuclear condensates and domains, indicating an intimate link between lncRNA expression and the spatial control of gene expression during development. lncRNAs also have important roles in the cytoplasm and beyond, including in the regulation of translation, metabolism and signalling. lncRNAs often have a modular structure and are rich in repeats, which are increasingly being shown to be relevant to their function. In this Consensus Statement, we address the definition and nomenclature of lncRNAs and their conservation, expression, phenotypic visibility, structure and functions. We also discuss research challenges and provide recommendations to advance the understanding of the roles of lncRNAs in development, cell biology and disease.This Consensus Statement addresses the definition, nomenclature and classification of long non-coding RNAs, and provides a shared viewpoint on their features and functions. The authors also discuss research challenges and provide recommendations to advance our understanding of long non-coding RNAs.

The epitranscriptomics field has undergone an enormous expansion in the last few years; however, a major limitation is the lack of generic methods to map RNA modifications transcriptome-wide. Here, we show that using direct RNA sequencing, N 6 -methyladenosine (m 6 A) RNA modifications can be detected with high accuracy, in the form of systematic errors and decreased base-calling qualities. Specifically, we find that our algorithm, trained with m 6 A-modified and unmodified synthetic sequences, can predict m 6 A RNA modifications with ~90% accuracy. We then extend our findings to yeast data sets, finding that our method can identify m 6 A RNA modifications in vivo with an accuracy of 87%. Moreover, we further validate our method by showing that these ‘errors’ are typically not observed in yeast ime4 -knockout strains, which lack m 6 A modifications. Our results open avenues to investigate the biological roles of RNA modifications in their native RNA context. We currently lack generic methods to map RNA modifications across the entire transcriptome. Here, the authors demonstrate that m 6 A RNA modifications can be detected with high accuracy using nanopore direct RNA sequencing.

Convolutional Neural Networks (CNNs) have been central to the Deep Learning revolution and played a key role in initiating the new age of Artificial Intelligence. However, in recent years newer architectures such as Transformers have dominated both research and practical applications. While CNNs still play critical roles in many of the newer developments such as Generative AI, they are far from being thoroughly understood and utilised to their full potential. Here we show that CNNs can recognise patterns in images with scattered pixels and can be used to analyse complex datasets by transforming them into pseudo images with minimal processing for any high dimensional dataset, representing a more general approach to the application of CNNs to datasets such as in molecular biology, text, and speech. We introduce a pipeline called DeepMapper , which allows analysis of very high dimensional datasets without intermediate filtering and dimension reduction, thus preserving the full texture of the data, enabling detection of small variations normally deemed ‘noise’. We demonstrate that DeepMapper can identify very small perturbations in large datasets with mostly random variables, and that it is superior in speed and on par in accuracy to prior work in processing large datasets with large numbers of features.

Background The cancer transcriptome is difficult to explore due to the heterogeneity of quantitative and qualitative changes in gene expression linked to the disease status. An increasing number of \"unconventional\" transcripts, such as novel isoforms, non-coding RNAs, somatic gene fusions and deletions have been associated with the tumoral state. Massively parallel sequencing techniques provide a framework for exploring the transcriptional complexity inherent to cancer with a limited laboratory and financial effort. We developed a deep sequencing and bioinformatics analysis protocol to investigate the molecular composition of a breast cancer poly(A) + transcriptome. This method utilizes a cDNA library normalization step to diminish the representation of highly expressed transcripts and biology-oriented bioinformatic analyses to facilitate detection of rare and novel transcripts. Results We analyzed over 132,000 Roche 454 high-confidence deep sequencing reads from a primary human lobular breast cancer tissue specimen, and detected a range of unusual transcriptional events that were subsequently validated by RT-PCR in additional eight primary human breast cancer samples. We identified and validated one deletion, two novel ncRNAs (one intergenic and one intragenic), ten previously unknown or rare transcript isoforms and a novel gene fusion specific to a single primary tissue sample. We also explored the non-protein-coding portion of the breast cancer transcriptome, identifying thousands of novel non-coding transcripts and more than three hundred reads corresponding to the non-coding RNA MALAT1 , which is highly expressed in many human carcinomas. Conclusion Our results demonstrate that combining 454 deep sequencing with a normalization step and careful bioinformatic analysis facilitates the discovery and quantification of rare transcripts or ncRNAs, and can be used as a qualitative tool to characterize transcriptome complexity, revealing many hitherto unknown transcripts, splice isoforms, gene fusion events and ncRNAs, even at a relatively low sequence sampling.

Touchdown (TD) PCR offers a simple and rapid means to optimize PCRs, increasing specificity, sensitivity and yield, without the need for lengthy optimizations and/or the redesigning of primers. TD-PCR employs an initial annealing temperature above the projected melting temperature ( T m ) of the primers being used, then progressively transitions to a lower, more permissive annealing temperature over the course of successive cycles. Any difference in T m between correct and incorrect annealing will produce an exponential advantage of twofold per cycle. TD-PCR has found wide applicability in standard PCR protocols, including reverse transcriptase-dependent PCR, as well as in the generation of cDNA libraries and single nucleotide polymorphism screening. TD-PCR is particularly useful for templates that are difficult to amplify but can also be standardly used to enhance specificity and product formation. The procedure takes between 90 and 120 min, depending on the template length.

Transcriptomic studies have demonstrated that the vast majority of the genomes of mammals and other complex organisms is expressed in highly dynamic and cell-specific patterns to produce large numbers of intergenic, antisense and intronic long non-protein-coding RNAs (lncRNAs). Despite well characterized examples, their scaling with developmental complexity, and many demonstrations of their association with cellular processes, development and diseases, lncRNAs are still to be widely accepted as major players in gene regulation. This may reflect an underappreciation of the extent and precision of the epigenetic control of differentiation and development, where lncRNAs appear to have a central role, likely as organizational and guide molecules: most lncRNAs are nuclear-localized and chromatin-associated, with some involved in the formation of specialized subcellular domains. I suggest that a reassessment of the conceptual framework of genetic information and gene expression in the 4-dimensional ontogeny of spatially organized multicellular organisms is required. Together with this and further studies on their biology, the key challenges now are to determine the structure–function relationships of lncRNAs, which may be aided by emerging evidence of their modular structure, the role of RNA editing and modification in enabling epigenetic plasticity, and the role of RNA signaling in transgenerational inheritance of experience.