Detecting and comparing non-coding RNAs in the high-throughput era

Exploring ncRNA-mediated regulation of EGFR signalling in glioblastoma: From mechanisms to therapeutics

Glioblastoma (GBM) is the most prevalent and deadly primary brain tumor type, with a discouragingly low survival rate and few effective treatments. An important function of the EGFR signalling pathway in the development of GBM is to affect tumor proliferation, persistence, and treatment resistance. Advances in molecular biology in the last several years have shown how important ncRNAs are for controlling a wide range of biological activities, including cancer progression and development. NcRNAs have become important post-transcriptional regulators of gene expression, and they may affect the EGFR pathway by either directly targeting EGFR or by modifying important transcription factors and downstream signalling molecules. The EGFR pathway is aberrantly activated in response to the dysregulation of certain ncRNAs, which has been linked to GBM carcinogenesis, treatment resistance, and unfavourable patient outcomes. We review the literature on miRNAs, circRNAs and lncRNAs that are implicated in the regulation of EGFR signalling in GBM, discussing their mechanisms of action, interactions with the signalling pathway, and implications for GBM therapy. Furthermore, we explore the potential of ncRNA-based strategies to overcome resistance to EGFR-targeted therapies, including the use of ncRNA mimics or inhibitors to modulate the activity of key regulators within the pathway.

LINC00839 in Human Disorders: Insights into its Regulatory Roles and Clinical Impact, with a Special Focus on Cancer

LINC00839 has captured significant attention within a spectrum of human disorders, including acute lung injury, osteoarthritis, and childhood obesity. Notably, aberrant expression patterns of LINC00839 have been observed across diverse cancer tissues and cell lines. LINC00839 emerges as an oncogenic factor in tumorigenesis and exerts a positive influence on tumor-associated behaviors. Its therapeutic potential for various cancers is underscored by its modulatory impact on pivotal signaling pathways, such as PI3K/AKT, OXPHOS, and Wnt/β-catenin. Additionally, LINC00839's role in reducing sensitivity to drug and radiotherapy interventions presents opportunities for targeted intervention. Furthermore, elevated LINC00839 expression indicates advanced clinicopathological features and foretells unfavorable prognoses, as validated by publications and comprehensive analyses of tumor types using TCGA datasets. This review elucidates the multiple regulatory mechanisms and functional implications of LINC00839 in various diseases, especially malignancies, emphasizing its potential as a predictive biomarker and therapeutic target across multiple disease domains in humans.

Another lesson from unmapped reads: in-depth analysis of RNA-Seq reads from various horse tissues

In recent years, a vast amount of sequencing data has been generated and large improvements have been made to reference genome sequences. Despite these advances, significant portions of reads still do not map to reference genomes and these reads have been considered as junk or artificial sequences. Recent studies have shown that these reads can be useful, e.g., for refining reference genomes or detecting contaminating microorganisms present in the analyzed biological samples. A special case of this is RNA sequencing (RNA-Seq) reads that come from tissue transcriptomes. Unmapped reads from RNA-Seq have received much less attention than those from whole-genome sequencing. In particular, in the horse, an analysis of unmapped RNA reads has not been performed yet. Thus, in this study, we analyzed the unmapped reads originating from the RNA-Seq performed through the Functional Annotation of Animal Genomes (FAANG) project in the horse, using eight different tissues from two mares. We demonstrated that unmapped reads from RNA-Seq could be easily assembled into transcripts relating to many important genes present in the sequences of other mammals. Large portions of these transcripts did not have coding potential and, thus, can be considered as non-coding RNA. Moreover, reads that were not mapped to the reference genome but aligned to the entries in NCBI database of horse proteins were enriched for biological processes that largely correspond to the functions of organ from which RNA was isolated and thus are presumably true transcripts of genes associated with cell metabolism in those tissues. In addition, a portion of reads aligned to the common pathogenic or neutral microbiota, of which the most common was Brucella spp. These data suggest that unmapped reads can be an important target for in-depth analysis that may substantially enrich results of initial RNA-Seq experiments for various tissues and organs.

DNA Methylation and Non-Coding RNAs during Tissue-Injury Associated Pain

While about half of the population experience persistent pain associated with tissue damages during their lifetime, current symptom-based approaches often fail to reduce such pain to a satisfactory level. To provide better patient care, mechanism-based analgesic approaches must be developed, which necessitates a comprehensive understanding of the nociceptive mechanism leading to tissue injury-associated persistent pain. Epigenetic events leading the altered transcription in the nervous system are pivotal in the maintenance of pain in tissue injury. However, the mechanisms through which those events contribute to the persistence of pain are not fully understood. This review provides a summary and critical evaluation of two epigenetic mechanisms, DNA methylation and non-coding RNA expression, on transcriptional modulation in nociceptive pathways during the development of tissue injury-associated pain. We assess the pre-clinical data and their translational implication and evaluate the potential of controlling DNA methylation and non-coding RNA expression as novel analgesic approaches and/or biomarkers of persistent pain.

Long Non-Coding RNAs Involved in Progression of Non-Alcoholic Fatty Liver Disease to Steatohepatitis

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease and is characterized by different stages varying from benign fat accumulation to non-alcoholic steatohepatitis (NASH) that may progress to cirrhosis and liver cancer. In recent years, a regulatory role of long non-coding RNAs (lncRNAs) in NAFLD has emerged. Therefore, we aimed to characterize the still poorly understood lncRNA contribution to disease progression. Transcriptome analysis in 60 human liver samples with various degrees of NAFLD/NASH was combined with a functional genomics experiment in an in vitro model where we exposed HepG2 cells to free fatty acids (FFA) to induce steatosis, then stimulated them with tumor necrosis factor alpha (TNFα) to mimic inflammation. Bioinformatics analyses provided a functional prediction of novel lncRNAs. We further functionally characterized the involvement of one novel lncRNA in the nuclear-factor-kappa B (NF-κB) signaling pathway by its silencing in Hepatoma G2 (HepG2) cells. We identified 730 protein-coding genes and 18 lncRNAs that responded to FFA/TNFα and associated with human NASH phenotypes with consistent effect direction, with most being linked to inflammation. One novel intergenic lncRNA, designated lncTNF, was 20-fold up-regulated upon TNFα stimulation in HepG2 cells and positively correlated with lobular inflammation in human liver samples. Silencing lncTNF in HepG2 cells reduced NF-κB activity and suppressed expression of the NF-κB target genes A20 and NFKBIA. The lncTNF we identified in the NF-κB signaling pathway may represent a novel target for controlling liver inflammation.

RNAconTest: comparing tools for noncoding RNA multiple sequence alignment based on structural consistency

The importance of noncoding RNA sequences has become increasingly clear over the past decade. New RNA families are often detected and analyzed using comparative methods based on multiple sequence alignments. Accordingly, a number of programs have been developed for aligning and deriving secondary structures from sets of RNA sequences. Yet, the best tools for these tasks remain unclear because existing benchmarks contain too few sequences belonging to only a small number of RNA families. RNAconTest (RNA consistency test) is a new benchmarking approach relying on the observation that secondary structure is often conserved across highly divergent RNA sequences from the same family. RNAconTest scores multiple sequence alignments based on the level of consistency among known secondary structures belonging to reference sequences in their output alignment. Similarly, consensus secondary structure predictions are scored according to their agreement with one or more known structures in a family. Comparing the performance of 10 popular alignment programs using RNAconTest revealed that DAFS, DECIPHER, LocARNA, and MAFFT created the most structurally consistent alignments. The best consensus secondary structure predictions were generated by DAFS and LocARNA (via RNAalifold). Many of the methods specific to noncoding RNAs exhibited poor scalability as the number or length of input sequences increased, and several programs displayed substantial declines in score as more sequences were aligned. Overall, RNAconTest provides a means of testing and improving tools for comparative RNA analysis, as well as highlighting the best available approaches. RNAconTest is available from the DECIPHER website (http://DECIPHER.codes/Downloads.html).

MicroRNAs Associated With Colon Cancer: New Potential Prognostic Markers and Targets for Therapy

MicroRNAs (miRNAs) are a kind of non-coding RNA (ncRNA) that regulate the expression of target genes and play a role in the occurrence and development of cancers. Colon cancer (COAD) is the second most common cause of cancer-related mortality. However, the prognostic value of miRNAs in COAD is still confusing. In this study, we obtain miRNAs and messenger RNAs (mRNAs) expression profiles of COAD from the Cancer Genome Atlas (TCGA) database. After preliminary data screening and preprocessing, we acquire the expression data of 894 miRNAs and 17,019 mRNAs. Then, compared with the normal samples, 39 upregulated miRNAs and 54 downregulated miRNAs are identified by differential expression analysis. Furthermore, we obtain 1,487 upregulated mRNAs and 2,847 downregulated mRNAs. We confirm nine key miRNAs related to the survival rate of COAD patients. Moreover, by using bioinformatics methods, we get 461 common genes from both the target genes of these nine key miRNAs and differentially expressed mRNAs. Through analyzing the protein-protein interaction (PPI) network of these 461 common genes and survival analysis, we confirm five hub genes as promising biomarkers for COAD prognosis. It is worth mentioning that no previous reports have found that PGR and KCNB1 are related to COAD. We expect these key miRNAs and hub genes will provide a new way for the study of COAD.

RNAdetect: efficient computational detection of novel non-coding RNAs

MOTIVATION

Non-coding RNAs (ncRNAs) are known to play crucial roles in various biological processes, and there is a pressing need for accurate computational detection methods that could be used to efficiently scan genomes to detect novel ncRNAs. However, unlike coding genes, ncRNAs often lack distinctive sequence features that could be used for recognizing them. Although many ncRNAs are known to have a well conserved secondary structure, which provides useful cues for computational prediction, it has been also shown that a structure-based approach alone may not be sufficient for detecting ncRNAs in a single sequence. Currently, the most effective ncRNA detection methods combine structure-based techniques with a comparative genome analysis approach to improve the prediction performance.

RESULTS

In this paper, we propose RNAdetect, a computational method incorporating novel features for accurate detection of ncRNAs in combination with comparative genome analysis. Given a sequence alignment, RNAdetect can accurately detect the presence of functional ncRNAs by incorporating novel predictive features based on the concept of generalized ensemble defect (GED), which assesses the degree of structure conservation across multiple related sequences and the conformation of the individual folding structures to a common consensus structure. Furthermore, n-gram models (NGMs) are used to extract features that can effectively capture sequence homology to known ncRNA families. Utilization of NGMs can enhance the detection of ncRNAs that have sparse folding structures with many unpaired bases. Extensive performance evaluation based on the Rfam database and bacterial genomes demonstrate that RNAdetect can accurately and reliably detect novel ncRNAs, outperforming the current state-of-the-art methods.

AVAILABILITY AND IMPLEMENTATION

The source code for RNAdetect and the benchmark data used in this paper can be downloaded at https://github.com/bjyoontamu/RNAdetect.

Manatee: detection and quantification of small non-coding RNAs from next-generation sequencing data

Small non-coding RNAs (sncRNAs) play important roles in health and disease. Next Generation Sequencing (NGS) technologies are considered as the most powerful and versatile methodologies to explore small RNA (sRNA) transcriptomes in diverse experimental and clinical studies. Small RNA-Seq (sRNA-Seq) data analysis proved to be challenging due to non-unique genomic origin, short length, and abundant post-transcriptional modifications of sRNA species. Here, we present Manatee, an algorithm for the quantification of sRNA classes and the detection of novel expressed non-coding loci. Manatee combines prior annotation of sRNAs with reliable alignment density information and extensive rescue of usually neglected multimapped reads to provide accurate transcriptome-wide sRNA expression quantification. Comparison of Manatee against state-of-the-art implementations using real and simulated data demonstrates its high accuracy across diverse sRNA classes. Manatee also goes beyond common pipelines by identifying and quantifying expression from unannotated loci and microRNA isoforms (isomiRs). It is user-friendly, can be easily incorporated in pipelines, and provides a simplified output suitable for direct usage in downstream analyses and functional studies.

Clinical significance of microRNA-449a in hepatocellular carcinoma with microarray data mining together with initial bioinformatics analysis

Increasing evidence has demonstrated that microRNA (miR)-449a expression is reduced in various types of tumors and that it serves as a tumor suppressor. However, the molecular mechanism of miR-449a in hepatocellular carcinoma (HCC) has not been thoroughly elucidated and is disputed. Therefore, the aim of the present work was to systematically review the current literature and to utilize the public Gene Expression Omnibus database to determine the role of miR-449a and its significance in HCC. A total of eight original papers and seven microarrays were included in the present study. Based on the evidence, miR-449a was reduced in HCC. miR-449a is likely involved in various signaling pathways and is targeted to multiple mRNA as part of its function in HCC. In addition, a preliminary bioinformatic analysis was conducted for miR-449a to investigate the novel potential pathways that miR-449a may participate in regarding HCC.

HAfTs are novel lncRNA transcripts from aflatoxin exposure

The transcriptome can reveal insights into precancer biology. We recently conducted RNA-Seq analysis on liver RNA from male rats exposed to the carcinogen, aflatoxin B1 (AFB1), for 90 days prior to liver tumor onset. Among >1,000 differentially expressed transcripts, several novel, unannotated Cufflinks-assembled transcripts, or HAfTs (Hepatic Aflatoxin Transcripts) were found. We hypothesized PCR-cloning and RACE (rapid amplification of cDNA ends) could further HAfT identification. Sanger data was obtained for 6 transcripts by PCR and 16 transcripts by 5’- and 3’-RACE. BLAST alignments showed, with two exceptions, HAfT transcripts were lncRNAs, >200nt without apparent long open reading frames. Six rat HAfT transcripts were classified as ‘novel’ without RefSeq annotation. Sequence alignment and genomic synteny showed each rat lncRNA had a homologous locus in the mouse genome and over half had homologous loci in the human genome, including at least two loci (and possibly three others) that were previously unannotated. While HAfT functions are not yet clear, coregulatory roles may be possible from their adjacent orientation to known coding genes with altered expression that include 8 HAfT-gene pairs. For example, a unique rat HAfT, homologous to Pvt1, was adjacent to known genes controlling cell proliferation. Additionally, PCR and RACE Sanger sequencing showed many alternative splice variants and refinements of exon sequences compared to Cufflinks assembled transcripts and gene prediction algorithms. Presence of multiple splice variants and short tandem repeats found in some HAfTs may be consequential for secondary structure, transcriptional regulation, and function. In summary, we report novel, differentially expressed lncRNAs after exposure to the genotoxicant, AFB1, prior to neoplastic lesions. Complete cloning and sequencing of such transcripts could pave the way for a new set of sensitive and early prediction markers for chemical hepatocarcinogens.

Therapeutic Approaches and Role of ncRNAs in Cardiovascular Disorders and Insulin Resistance

Diseases resulting from alterations in gene expressions through mutations in the genes or through changes in the gene expression regulation could be identified through the analysis of RNA expressions. ncRNAs play a significant role in regulation of the gene expression by controlling the expression levels of the coding RNAs and other cellular processes. Discoveries have shown that the human genome is encoded with sequences responsible for the transcription of thousands of ncRNAs. Even though the studies conducted on ncRNAs are still at initial stages, facts established so far display biomarkers that confirm their relationship with certain diseases such as cancers, cardiovascular diseases, and insulin resistance. These studies have been facilitated with high throughput modern sequencing techniques such as microarrays and RNA sequencing. The data obtained through the above analysis are processed with the aid of existing databases, to deduce conclusions on different diagnostic biomarkers and therapeutic targets for specific diseases. This review focuses on the association of ncRNAs in disease prediction, focusing mainly on cardiovascular diseases and disorders caused by insulin resistance. The report also analyzes regulatory functions of ncRNAs and novel approaches used in disease therapeutics.

Improved definition of the mouse transcriptome via targeted RNA sequencing

Targeted RNA sequencing (CaptureSeq) uses oligonucleotide probes to capture RNAs for sequencing, providing enriched read coverage, accurate measurement of gene expression, and quantitative expression data. We applied CaptureSeq to refine transcript annotations in the current murine GRCm38 assembly. More than 23,000 regions corresponding to putative or annotated long noncoding RNAs (lncRNAs) and 154,281 known splicing junction sites were selected for targeted sequencing across five mouse tissues and three brain subregions. The results illustrate that the mouse transcriptome is considerably more complex than previously thought. We assemble more complete transcript isoforms than GENCODE, expand transcript boundaries, and connect interspersed islands of mapped reads. We describe a novel filtering pipeline that identifies previously unannotated but high-quality transcript isoforms. In this set, 911 GENCODE neighboring genes are condensed into 400 expanded gene models. Additionally, 594 GENCODE lncRNAs acquire an open reading frame (ORF) when their structure is extended with CaptureSeq. Finally, we validate our observations using current FANTOM and Mouse ENCODE resources.

Study strategies for long non-coding RNAs and their roles in regulating gene expression

Long non-coding RNAs (lncRNAs) have attracted considerable attention recently due to their involvement in numerous key cellular processes and in the development of various disorders. New high-throughput methods enable their study on a genome-wide scale. Numerous lncRNAs have been identified and characterized as important members of the biological regulatory network, with significant roles in regulating gene expression at the epigenetic, transcriptional and post-transcriptional levels. This paper summarizes the diverse mechanisms of action of these lncRNAs and looks at the study strategies in this field. A major challenge in future study is to establish more effective bioinformatics and experimental methods to explore the functions, detailed mechanisms of action and structures deciding the functional diversity of lncRNAs, since the vast majority remain unresolved.

Rapid evolutionary turnover underlies conserved lncRNA-genome interactions

Many long noncoding RNAs (lncRNAs) can regulate chromatin states, but the evolutionary origin and dynamics driving lncRNA-genome interactions are unclear. We adapted an integrative strategy that identifies lncRNA orthologs in different species despite limited sequence similarity, which is applicable to mammalian and insect lncRNAs. Analysis of the roX lncRNAs, which are essential for dosage compensation of the single X chromosome in Drosophila males, revealed 47 new roX orthologs in diverse Drosophilid species across ∼40 million years of evolution. Genetic rescue by roX orthologs and engineered synthetic lncRNAs showed that altering the number of focal, repetitive RNA structures determines roX ortholog function. Genomic occupancy maps of roX RNAs in four species revealed conserved targeting of X chromosome neighborhoods but rapid turnover of individual binding sites. Many new roX-binding sites evolved from DNA encoding a pre-existing RNA splicing signal, effectively linking dosage compensation to transcribed genes. Thus, dynamic change in lncRNAs and their genomic targets underlies conserved and essential lncRNA-genome interactions.

Chromosomal polymorphism in mammals: an evolutionary perspective

Although chromosome rearrangements (CRs) are central to studies of genome evolution, our understanding of the evolutionary consequences of the early stages of karyotypic differentiation (i.e. polymorphism), especially the non-meiotic impacts, is surprisingly limited. We review the available data on chromosomal polymorphisms in mammals so as to identify taxa that hold promise for developing a more comprehensive understanding of chromosomal change. In doing so, we address several key questions: (i) to what extent are mammalian karyotypes polymorphic, and what types of rearrangements are principally involved? (ii) Are some mammalian lineages more prone to chromosomal polymorphism than others? More specifically, do (karyotypically) polymorphic mammalian species belong to lineages that are also characterized by past, extensive karyotype repatterning? (iii) How long can chromosomal polymorphisms persist in mammals? We discuss the evolutionary implications of these questions and propose several research avenues that may shed light on the role of chromosome change in the diversification of mammalian populations and species.

Long Intergenic Non-Coding RNAs: Novel Drivers of Human Lymphocyte Differentiation

Upon recognition of a foreign antigen, CD4(+) naïve T lymphocytes proliferate and differentiate into subsets with distinct functions. This process is fundamental for the effective immune system function, as CD4(+) T cells orchestrate both the innate and adaptive immune response. Traditionally, this differentiation event has been regarded as the acquisition of an irreversible cell fate so that memory and effector CD4(+) T subsets were considered terminally differentiated cells or lineages. Consequently, these lineages are conventionally defined thanks to their prototypical set of cytokines and transcription factors. However, recent findings suggest that CD4(+) T lymphocytes possess a remarkable phenotypic plasticity, as they can often re-direct their functional program depending on the milieu they encounter. Therefore, new questions are now compelling such as which are the molecular determinants underlying plasticity and stability and how the balance between these two opposite forces drives the cell fate. As already mentioned, in some cases, the mere expression of cytokines and master regulators could not fully explain lymphocytes plasticity. We should consider other layers of regulation, including epigenetic factors such as the modulation of chromatin state or the transcription of non-coding RNAs, whose high cell-specificity give a hint on their involvement in cell fate determination. In this review, we will focus on the recent advances in understanding CD4(+) T lymphocytes subsets specification from an epigenetic point of view. In particular, we will emphasize the emerging importance of non-coding RNAs as key players in these differentiation events. We will also present here new data from our laboratory highlighting the contribution of long non-coding RNAs in driving human CD4(+) T lymphocytes differentiation.

Editorial on the Special Issue: Regulation by non-coding RNAs

This Special Issue of IJMS is devoted to regulation by non-coding RNAs and contains both original research and review articles. An attempt is made to provide an up-to-date analysis of this very fast moving field and cover regulatory roles of both microRNAs and long non-coding RNAs. Multifaceted functions of these RNAs in normal cellular processes, as well as in disease progression, are highlighted.