Mapping of conserved RNA secondary structures predicts thousands of functional noncoding RNAs in the human genome

Non-coding RNAs and neuroinflammation: implications for neurological disorders

Neuroinflammation is considered a balanced inflammatory response important in the intrinsic repair process after injury or infection. Under chronic states of disease, injury, or infection, persistent neuroinflammation results in a heightened presence of cytokines, chemokines, and reactive oxygen species that result in tissue damage. In the CNS, the surrounding microglia normally contain macrophages and other innate immune cells that perform active immune surveillance. The resulting cytokines produced by these macrophages affect the growth, development, and responsiveness of the microglia present in both white and gray matter regions of the CNS. Controlling the levels of these cytokines ultimately improves neurocognitive function and results in the repair of lesions associated with neurologic disease. MicroRNAs (miRNAs) are master regulators of the genome and subsequently control the activity of inflammatory responses crucial in sustaining a robust and acute immunological response towards an acute infection while dampening pathways that result in heightened levels of cytokines and chemokines associated with chronic neuroinflammation. Numerous reports have directly implicated miRNAs in controlling the abundance and activity of interleukins, TGF-B, NF-kB, and toll-like receptor-signaling intrinsically linked with the development of neurological disorders such as Parkinson's, ALS, epilepsy, Alzheimer's, and neuromuscular degeneration. This review is focused on discussing the role miRNAs play in regulating or initiating these chronic neurological states, many of which maintain the level and/or activity of neuron-specific secondary messengers. Dysregulated miRNAs present in the microglia, astrocytes, oligodendrocytes, and epididymal cells, contribute to an overall glial-specific inflammatory niche that impacts the activity of neuronal conductivity, signaling action potentials, neurotransmitter robustness, neuron-neuron specific communication, and neuron-muscular connections. Understanding which miRNAs regulate microglial activation is a crucial step forward in developing non-coding RNA-based therapeutics to treat and potentially correct the behavioral and cognitive deficits typically found in patients suffering from chronic neuroinflammation.

Comparative RNA Genomics

Over the last quarter of a century it has become clear that RNA is much more than just a boring intermediate in protein expression. Ancient RNAs still appear in the core information metabolism and comprise a surprisingly large component in bacterial gene regulation. A common theme with these types of mostly small RNAs is their reliance of conserved secondary structures. Large-scale sequencing projects, on the other hand, have profoundly changed our understanding of eukaryotic genomes. Pervasively transcribed, they give rise to a plethora of large and evolutionarily extremely flexible non-coding RNAs that exert a vastly diverse array of molecule functions. In this chapter we provide a-necessarily incomplete-overview of the current state of comparative analysis of non-coding RNAs, emphasizing computational approaches as a means to gain a global picture of the modern RNA world.

Thirteen dubious ways to detect conserved structural RNAs

Covariation induced by compensatory base substitutions in RNA alignments is a great way to deduce conserved RNA structure, in principle. In practice, success depends on many factors, importantly the quality and depth of the alignment and the choice of covariation statistic. Measuring covariation between pairs of aligned positions is easy. However, using covariation to infer evolutionarily conserved RNA structure is complicated by other extraneous sources of covariation such as that resulting from homologous sequences having evolved from a common ancestor. In order to provide evidence of evolutionarily conserved RNA structure, a method to distinguish covariation due to sources other than RNA structure is necessary. Moreover, there are several sorts of artifactually generated covariation signals that can further confound the analysis. Additionally, some covariation signal is difficult to detect due to incomplete comparative data. Here, we investigate and critically discuss the practice of inferring conserved RNA structure by comparative sequence analysis. We provide new methods on how to approach and decide which of the numerous long non-coding RNAs (lncRNAs) have biologically relevant structures.

Evolutionary Conservation of RNA Secondary Structure

Noncoding RNAs, ncRNAs, naturally fold into structures, which allow them to perform their functions in the cell. Evolutionarily close species share structures and functions. This occurs because of shared selective pressures, resulting in conserved groups. Previous efforts in finding functional RNAs have been made in detecting conserved structures in genomes or alignments. It may occur that, within a conserved group, species-specific structures arise after species split due to positive selection. Detecting positive selection in ncRNAs is a hard problem in biology as well as bioinformatics. To detect positive selection, one should find species-specific structures within a conserved set. This chapter provides protocols to detect and analyze positive selection in ncRNA structures with the SSS-test and other free software.

Navigating the Multiverse of Antisense RNAs: The Transcription- and RNA-Dependent Dimension

Evidence accumulated over the past decades shows that the number of identified antisense transcripts is continuously increasing, promoting them from transcriptional noise to real genes with specific functions. Indeed, recent studies have begun to unravel the complexity of the antisense RNA (asRNA) world, starting from the multidimensional mechanisms that they can exert in physiological and pathological conditions. In this review, we discuss the multiverse of the molecular functions of asRNAs, describing their action through transcription-dependent and RNA-dependent mechanisms. Then, we report the workflow and methodologies to study and functionally characterize single asRNA candidates.

Genome-Wide Analysis of Human Long Noncoding RNAs: A Provocative Review

Do long noncoding RNAs (lncRNAs) contribute little or substantively to human biology? To address how lncRNA loci and their transcripts, structures, interactions, and functions contribute to human traits and disease, we adopt a genome-wide perspective. We intend to provoke alternative interpretation of questionable evidence and thorough inquiry into unsubstantiated claims. We discuss pitfalls of lncRNA experimental and computational methods as well as opposing interpretations of their results. The majority of evidence, we argue, indicates that most lncRNA transcript models reflect transcriptional noise or provide minor regulatory roles, leaving relatively few human lncRNAs that contribute centrally to human development, physiology, or behavior. These important few tend to be spliced and better conserved but lack a simple syntax relating sequence to structure and mechanism, and so resist simple categorization. This genome-wide view should help investigators prioritize individual lncRNAs based on their likely contribution to human biology.

Small and intermediate size structural RNAs in the unicellular parasite Cryptosporidium parvum as revealed by sRNA-seq and comparative genomics

Small and intermediate-size noncoding RNAs (sRNAs and is-ncRNAs) have been shown to play important regulatory roles in the development of several eukaryotic organisms. However, they have not been thoroughly explored in Cryptosporidium parvum, an obligate zoonotic protist parasite responsible for the diarrhoeal disease cryptosporidiosis. Using Illumina sequencing of a small RNA library, a systematic identification of novel small and is-ncRNAs was performed in C. parvum excysted sporozoites. A total of 79 novel is-ncRNA candidates, including antisense, intergenic and intronic is-ncRNAs, were identified, including 7 new small nucleolar RNAs (snoRNAs). Expression of select novel is-ncRNAs was confirmed by RT-PCR. Phylogenetic conservation was analysed using covariance models (CMs) in related Cryptosporidium and apicomplexan parasite genome sequences. A potential new type of small ncRNA derived from tRNA fragments was observed. Overall, a deep profiling analysis of novel is-ncRNAs in C. parvum and related species revealed structural features and conservation of these novel is-ncRNAs. Covariance models can be used to detect is-ncRNA genes in other closely related parasites. These findings provide important new sequences for additional functional characterization of novel is-ncRNAs in the protist pathogen C. parvum.

OUP accepted manuscript

Accelerated evolution of any portion of the genome is of significant interest, potentially signaling positive selection of phenotypic traits and adaptation. Accelerated evolution remains understudied for structured RNAs, despite the fact that an RNA’s structure is often key to its function. RNA structures are typically characterized by compensatory (structure-preserving) basepair changes that are unexpected given the underlying sequence variation, i.e., they have evolved through negative selection on structure. We address the question of how fast the primary sequence of an RNA can change through evolution while conserving its structure. Specifically, we consider predicted and known structures in vertebrate genomes. After careful control of false discovery rates, we obtain 13 de novo structures (and three known Rfam structures) that we predict to have rapidly evolving sequences—defined as structures where the primary sequences of human and mouse have diverged at least twice as fast (1.5 times for Rfam) as nearby neutrally evolving sequences. Two of the three known structures function in translation inhibition related to infection and immune response. We conclude that rapid sequence divergence does not preclude RNA structure conservation in vertebrates, although these events are relatively rare.

An RNA-Based Theory of Natural Universal Computation

Life is confronted with computation problems in a variety of domains including animal behavior, single-cell behavior, and embryonic development. Yet we currently do not know of a naturally existing biological system that is capable of universal computation, i.e., Turing-equivalent in scope. Generic finite-dimensional dynamical systems (which encompass most models of neural networks, intracellular signaling cascades, and gene regulatory networks) fall short of universal computation, but are assumed to be capable of explaining cognition and development. I present a class of models that bridge two concepts from distant fields: combinatory logic (or, equivalently, lambda calculus) and RNA molecular biology. A set of basic RNA editing rules can make it possible to compute any computable function with identical algorithmic complexity to that of Turing machines. The models do not assume extraordinarily complex molecular machinery or any processes that radically differ from what we already know to occur in cells. Distinct independent enzymes can mediate each of the rules and RNA molecules solve the problem of parenthesis matching through their secondary structure. In the most plausible of these models all of the editing rules can be implemented with merely cleavage and ligation operations at fixed positions relative to predefined motifs. This demonstrates that universal computation is well within the reach of molecular biology. It is therefore reasonable to assume that life has evolved - or possibly began with - a universal computer that yet remains to be discovered. The variety of seemingly unrelated computational problems across many scales can potentially be solved using the same RNA-based computation system. Experimental validation of this theory may immensely impact our understanding of memory, cognition, development, disease, evolution, and the early stages of life.

Long noncoding RNA#45 exerts broad inhibitory effect on influenza a virus replication via its stem ring arms

A growing body of evidence suggests the pivotal role of long non-coding RNA (lncRNA) in influenza virus infection. Based on next-generation sequencing, we previously demonstrated that Lnc45 was distinctively stimulated by H5N1 influenza virus in mice. In this study, we systematically investigated the specific role of Lnc45 during influenza A virus (IAV) infection. Through qRT-PCR, we first demonstrated that Lnc45 is highly up-regulated by different subtypes of IAV strains, including H5N1, H7N9, and H1N1 viruses. Using RNA-FISH and qRT-PCR, we then found that Lnc45 can translocate from nuclear to cytoplasm during H5N1 virus infection. In addition, forced Lnc45 expression dramatically impeded viral replication of H1N1, H5N1, and H7N9 virus, while abolish of Lnc45 expression by RNA interference favored replication of these viruses, highlighting the potential broad antiviral activity of Lnc45 to IAV. Correspondingly, overexpression of Lnc45 inhibited viral polymerase activity and suppressed IAV-induced cell apoptosis. Moreover, Lnc45 significantly restrained nuclear aggregation of viral NP and PA proteins during H5N1 virus infection. Further functional study revealed that the stem ring arms of Lnc45 mainly mediated the antiviral effect. Therefore, we here demonstrated that Lnc45 functions as a broad-spectrum antiviral factor to inhibit influenza virus replication probably through inhibiting polymerase activity and NP and PA nuclear accumulation via its stem ring arms. Our study not only advances our understanding of the complexity of the IAV pathogenesis but also lays the foundation for developing novel anti-IAV therapeutics targeting the host lncRNA.

In Vivo Silencing/Overexpression of lncRNAs by CRISPR/Cas System

Long noncoding RNAs (lncRNAs) are implicated in several biological processes and it has been observed that their expression is altered in several diseases. The generation of animal models where selective silencing or overexpression of lncRNAs can be attained is crucial for their biological characterization, since it offers the opportunity to analyze their function at the tissue specific or organismal level. CRISPR/Cas technology is a newly developed tool that allows to easily manipulate the mouse genome, in turn allowing to discover lncRNAs functions in an in vivo context. Here, we provide an overview of how CRISPR/Cas technology can be used to generate transgenic mouse models in which lncRNAs can be studied.

LncRNA LncHrt preserves cardiac metabolic homeostasis and heart function by modulating the LKB1-AMPK signaling pathway

Metabolic modulation is a promising therapeutic approach to prevent adverse remodeling of the ischemic heart. Because little is known about the involvement of long non-coding RNAs (lncRNAs) in regulating cardiac metabolism, we used unbiased transcriptome profiling in a mouse model of myocardial infarction (MI). We identified a novel cardiomyocyte-enriched lncRNA, called LncHrt, which regulates metabolism and the pathophysiological processes that lead to heart failure. AAV-based LncHrt overexpression protects the heart from MI as demonstrated by improved contractile function, preserved metabolic homeostasis, and attenuated maladaptive remodeling responses. RNA-pull down followed by mass spectrometry and RNA immunoprecipitation (RIP) identified SIRT2 as a LncHrt-interacting protein involved in cardiac metabolic regulation. Mechanistically, we established that LncHrt interacts with SIRT2 to preserve SIRT2 deacetylase activity by interfering with the CDK5 and SIRT2 interaction. This increases downstream LKB1-AMPK kinase signaling, which ameliorates functional and metabolic deficits. Importantly, we found the expression of the human homolog of mouse LncHrt was decreased in patients with dilated cardiomyopathy. Together, these studies identify LncHrt as a cardiac metabolic regulator that plays an essential role in preserving heart function by regulating downstream metabolic signaling pathways. Consequently, LncHrt is a potentially novel RNA-based therapeutic target for ischemic heart disease.

Recent development of bioinformatics tools for microRNA target prediction

MicroRNAs (miRNAs) are central players that regulate the post-transcriptional processes of gene expression. Binding of miRNAs to target mRNAs can repress their translation by inducing the degradation or by inhibiting the translation of the target mRNAs. High-throughput experimental approaches for miRNA target identification are costly and time-consuming, depending on various factors. It is vitally important to develop the bioinformatics methods for accurately predicting miRNA targets. With the increase of RNA sequences in the post-genomic era, bioinformatics methods are being developed for miRNA studies specially for miRNA target prediction. This review summarizes the current development of state-of-the-art bioinformatics tools for miRNA target prediction, points out the progress and limitations of the available miRNA databases, and their working principles. Finally, we discuss the caveat and perspectives of the next-generation algorithms for the prediction of miRNA targets.

Physical Laws Shape Up HOX Gene Collinearity

Hox gene collinearity (HGC) is a multi-scalar property of many animal phyla particularly important in embryogenesis. It relates entities and events occurring in Hox clusters inside the chromosome DNA and in embryonic tissues. These two entities differ in linear size by more than four orders of magnitude. HGC is observed as spatial collinearity (SC), where the Hox genes are located in the order (Hox1, Hox2, Hox3 …) along the 3′ to 5′ direction of DNA in the genome and a corresponding sequence of ontogenetic units (E1, E2, E3, …) located along the Anterior—Posterior axis of the embryo. Expression of Hox1 occurs in E1, Hox2 in E2, Hox3 in E3, etc. Besides SC, a temporal collinearity (TC) has been also observed in many vertebrates. According to TC, first Hox1 is expressed in E1; later, Hox2 is expressed in E2, followed by Hox3 in E3, etc. Lately, doubt has been raised about whether TC really exists. A biophysical model (BM) was formulated and tested during the last 20 years. According to BM, physical forces are created which pull the Hox genes one after the other, driving them to a transcription factory domain where they are transcribed. The existing experimental data support this BM description. Symmetry is a physical–mathematical property of matter that was explored in depth by Noether who formulated a ground-breaking theory (NT) that applies to all sizes of matter. NT may be applied to biology in order to explain the origin of HGC in animals developing not only along the A/P axis, but also to animals with circular symmetry.

Biological relevance and therapeutic potential of G-quadruplex structures in the human noncoding transcriptome

Noncoding RNAs are functional transcripts that are not translated into proteins. They represent the largest portion of the human transcriptome and have been shown to regulate gene expression networks in both physiological and pathological cell conditions. Research in this field has made remarkable progress in the comprehension of how aberrations in noncoding RNA drive relevant disease-associated phenotypes; however, the biological role and mechanism of action of several noncoding RNAs still need full understanding. Besides fulfilling its function through sequence-based mechanisms, RNA can form complex secondary and tertiary structures which allow non-canonical interactions with proteins and/or other nucleic acids. In this context, the presence of G-quadruplexes in microRNAs and long noncoding RNAs is increasingly being reported. This evidence suggests a role for RNA G-quadruplexes in controlling microRNA biogenesis and mediating noncoding RNA interaction with biological partners, thus ultimately regulating gene expression. Here, we review the state of the art of G-quadruplexes in the noncoding transcriptome, with their structural and functional characterization. In light of the existence and further possible development of G-quadruplex binders that modulate G-quadruplex conformation and protein interactions, we also discuss the therapeutic potential of G-quadruplexes as targets to interfere with disease-associated noncoding RNAs.

Functional and structural basis of extreme conservation in vertebrate 5' untranslated regions

The lack of knowledge about extreme conservation in genomes remains a major gap in our understanding of the evolution of gene regulation. Here, we reveal an unexpected role of extremely conserved 5' untranslated regions (UTRs) in noncanonical translational regulation that is linked to the emergence of essential developmental features in vertebrate species. Endogenous deletion of conserved elements within these 5' UTRs decreased gene expression, and extremely conserved 5' UTRs possess cis-regulatory elements that promote cell-type-specific regulation of translation. We further developed in-cell mutate-and-map (icM²), a new methodology that maps RNA structure inside cells. Using icM², we determined that an extremely conserved 5' UTR encodes multiple alternative structures and that each single nucleotide within the conserved element maintains the balance of alternative structures important to control the dynamic range of protein expression. These results explain how extreme sequence conservation can lead to RNA-level biological functions encoded in the untranslated regions of vertebrate genomes.

Functional long non-coding and circular RNAs in zebrafish

The utility of model organisms to understand the function of a novel transcript/genes has allowed us to delineate their molecular mechanisms in maintaining cellular homeostasis. Organisms such as zebrafish have contributed a lot in the field of developmental and disease biology. Attributable to advancement and deep transcriptomics, many new transcript isoforms and non-coding RNAs such as long noncoding RNA (lncRNA) and circular RNAs (circRNAs) have been identified and cataloged in multiple databases and many more are yet to be identified. Various methods and tools have been utilized to identify lncRNAs/circRNAs in zebrafish using deep sequencing of transcriptomes as templates. Functional analysis of a few candidates such as tie1-AS, ECAL1 and CDR1as in zebrafish provides a prospective outline to approach other known or novel lncRNA/circRNA. New genetic alteration tools like TALENS and CRISPRs have helped in probing for the molecular function of lncRNA/circRNA in zebrafish. Further latest improvements in experimental and computational techniques offer the identification of lncRNA/circRNA counterparts in humans and zebrafish thereby allowing easy modeling and analysis of function at cellular level.

Evolutionary conservation of RNA sequence and structure

An RNA structure prediction from a single‐sequence RNA folding program is not evidence for an RNA whose structure is important for function. Random sequences have plausible and complex predicted structures not easily distinguishable from those of structural RNAs. How to tell when an RNA has a conserved structure is a question that requires looking at the evolutionary signature left by the conserved RNA. This question is important not just for long noncoding RNAs which usually lack an identified function, but also for RNA binding protein motifs which can be single stranded RNAs or structures. Here we review recent advances using sequence and structural analysis to determine when RNA structure is conserved or not. Although covariation measures assess structural RNA conservation, one must distinguish covariation due to RNA structure from covariation due to independent phylogenetic substitutions. We review a statistical test to measure false positives expected under the null hypothesis of phylogenetic covariation alone (specificity). We also review a complementary test that measures power, that is, expected covariation derived from sequence variation alone (sensitivity). Power in the absence of covariation signals the absence of a conserved RNA structure. We analyze artifacts that falsely identify conserved RNA structure such as the misuse of programs that do not assess significance, the use of inappropriate statistics confounded by signals other than covariation, or misalignments that induce spurious covariation. Among artifacts that obscure the signal of a conserved RNA structure, we discuss the inclusion of pseudogenes in alignments which increase power but destroy covariation.

This article is categorized under:

RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry

RNA Evolution and Genomics > Computational Analyses of RNA

RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution

Specificity of RNA Folding and Its Association with Evolutionarily Adaptive mRNA Secondary Structures

The secondary structure is a fundamental feature of both noncoding and messenger RNAs. However, our understanding of the secondary structure of mRNA, especially that of the coding regions, remains elusive, likely due to translation and the lack of RNA-binding proteins that sustain the consensus structure, such as those that bind to noncoding RNA. Indeed, mRNA has recently been found to adopt diverse alternative structures, the overall functional significance of which remains untested. We hereby approached this problem by estimating the folding specificity, i.e., the probability that a fragment of RNA folds back to the same partner once refolded. We showed that the folding specificity of mRNA is lower than that of noncoding RNA and exhibits moderate evolutionary conservation. Notably, we found that specific rather than alternative folding is likely evolutionarily adaptive since specific folding is frequently associated with functionally important genes or sites within a gene. Additional analysis in combination with ribosome density suggests the ability to modulate ribosome movement as one potential functional advantage provided by specific folding. Our findings revealed a novel facet of the RNA structurome with important functional and evolutionary implications and indicated a potential method for distinguishing the mRNA secondary structures maintained by natural selection from molecular noise.

Lithium Chloride Sensitivity in Yeast and Regulation of Translation

For decades, lithium chloride (LiCl) has been used as a treatment option for those living with bipolar disorder (BD). As a result, many studies have been conducted to examine its mode of action, toxicity, and downstream cellular responses. We know that LiCl is able to affect cell signaling and signaling transduction pathways through protein kinase C and glycogen synthase kinase-3, which are considered to be important in regulating gene expression at the translational level. However, additional downstream effects require further investigation, especially in translation pathway. In yeast, LiCl treatment affects the expression, and thus the activity, of PGM2, a phosphoglucomutase involved in sugar metabolism. Inhibition of PGM2 leads to the accumulation of intermediate metabolites of galactose metabolism causing cell toxicity. However, it is not fully understood how LiCl affects gene expression in this matter. In this study, we identified three genes, NAM7, PUS2, and RPL27B, which increase yeast LiCl sensitivity when deleted. We further demonstrate that NAM7, PUS2, and RPL27B influence translation and exert their activity through the 5′-Untranslated region (5′-UTR) of PGM2 mRNA in yeast.

Principles and innovative technologies for decrypting noncoding RNAs: from discovery and functional prediction to clinical application

Noncoding RNAs (ncRNAs) are a large segment of the transcriptome that do not have apparent protein-coding roles, but they have been verified to play important roles in diverse biological processes, including disease pathogenesis. With the development of innovative technologies, an increasing number of novel ncRNAs have been uncovered; information about their prominent tissue-specific expression patterns, various interaction networks, and subcellular locations will undoubtedly enhance our understanding of their potential functions. Here, we summarized the principles and innovative methods for identifications of novel ncRNAs that have potential functional roles in cancer biology. Moreover, this review also provides alternative ncRNA databases based on high-throughput sequencing or experimental validation, and it briefly describes the current strategy for the clinical translation of cancer-associated ncRNAs to be used in diagnosis.

Sensitivity of yeast to lithium chloride connects the activity of YTA6 and YPR096C to translation of structured mRNAs

Lithium Chloride (LiCl) toxicity, mode of action and cellular responses have been the subject of active investigations over the past decades. In yeast, LiCl treatment is reported to reduce the activity and alters the expression of PGM2, a gene that encodes a phosphoglucomutase involved in sugar metabolism. Reduced activity of phosphoglucomutase in the presence of galactose causes an accumulation of intermediate metabolites of galactose metabolism leading to a number of phenotypes including growth defect. In the current study, we identify two understudied yeast genes, YTA6 and YPR096C that when deleted, cell sensitivity to LiCl is increased when galactose is used as a carbon source. The 5’-UTR of PGM2 mRNA is structured. Using this region, we show that YTA6 and YPR096C influence the translation of PGM2 mRNA.

A Novel Integrative Approach for Non-coding RNA Classification Based on Deep Learning

Background:

Molecular biomarkers show new ways to understand many disease processes. Noncoding RNAs as biomarkers play a crucial role in several cellular activities, which are highly correlated to many human diseases especially cancer. The classification and the identification of ncRNAs have become a critical issue due to their application, such as biomarkers in many human diseases.

Objective:

Most existing computational tools for ncRNA classification are mainly used for classifying only one type of ncRNA. They are based on structural information or specific known features. Furthermore, these tools suffer from a lack of significant and validated features. Therefore, the performance of these methods is not always satisfactory.

Methods:

We propose a novel approach named imCnC for ncRNA classification based on multisource deep learning, which integrates several data sources such as genomic and epigenomic data to identify several ncRNA types. Also, we propose an optimization technique to visualize the extracted features pattern from the multisource CNN model to measure the epigenomics features of each ncRNA type.

Results:

The computational results using a dataset of 16 human ncRNA classes downloaded from RFAM show that imCnC outperforms the existing tools. Indeed, imCnC achieved an accuracy of 94,18%. In addition, our method enables to discover new ncRNA features using an optimization technique to measure and visualize the features pattern of the imCnC classifier.

Genomic and Transcriptomic Analysis Identified Novel Putative Cassava lncRNAs Involved in Cold and Drought Stress

Long non-coding RNAs (lncRNAs) play important roles in the regulation of complex cellular processes, including transcriptional and post-transcriptional regulation of gene expression relevant for development and stress response, among others. Compared to other important crops, there is limited knowledge of cassava lncRNAs and their roles in abiotic stress adaptation. In this study, we performed a genome-wide study of ncRNAs in cassava, integrating genomics- and transcriptomics-based approaches. In total, 56,840 putative ncRNAs were identified, and approximately half the number were verified using expression data or previously known ncRNAs. Among these were 2229 potential novel lncRNA transcripts with unmatched sequences, 250 of which were differentially expressed in cold or drought conditions, relative to controls. We showed that lncRNAs might be involved in post-transcriptional regulation of stress-induced transcription factors (TFs) such as zinc-finger, WRKY, and nuclear factor Y gene families. These findings deepened our knowledge of cassava lncRNAs and shed light on their stress-responsive roles.

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.

SSS-test: a novel test for detecting positive selection on RNA secondary structure

BACKGROUND

Long non-coding RNAs (lncRNAs) play an important role in regulating gene expression and are thus important for determining phenotypes. Most attempts to measure selection in lncRNAs have focused on the primary sequence. The majority of small RNAs and at least some parts of lncRNAs must fold into specific structures to perform their biological function. Comprehensive assessments of selection acting on RNAs therefore must also encompass structure. Selection pressures acting on the structure of non-coding genes can be detected within multiple sequence alignments. Approaches of this type, however, have so far focused on negative selection. Thus, a computational method for identifying ncRNAs under positive selection is needed.

RESULTS

We introduce the SSS-test (test for Selection on Secondary Structure) to identify positive selection and thus adaptive evolution. Benchmarks with biological as well as synthetic controls yield coherent signals for both negative and positive selection, demonstrating the functionality of the test. A survey of a lncRNA collection comprising 15,443 families resulted in 110 candidates that appear to be under positive selection in human. In 26 lncRNAs that have been associated with psychiatric disorders we identified local structures that have signs of positive selection in the human lineage.

CONCLUSIONS

It is feasible to assay positive selection acting on RNA secondary structures on a genome-wide scale. The detection of human-specific positive selection in lncRNAs associated with cognitive disorder provides a set of candidate genes for further experimental testing and may provide insights into the evolution of cognitive abilities in humans.

AVAILABILITY

The SSS-test and related software is available at: https://github.com/waltercostamb/SSS-test . The databases used in this work are available at: http://www.bioinf.uni-leipzig.de/Software/SSS-test/ .

Evolutionary Patterns of Non-Coding RNA in Cardiovascular Biology

Cardiovascular diseases (CVDs) affect the heart and the vascular system with a high prevalence and place a huge burden on society as well as the healthcare system. These complex diseases are often the result of multiple genetic and environmental risk factors and pose a great challenge to understanding their etiology and consequences. With the advent of next generation sequencing, many non-coding RNA transcripts, especially long non-coding RNAs (lncRNAs), have been linked to the pathogenesis of CVD. Despite increasing evidence, the proper functional characterization of most of these molecules is still lacking. The exploration of conservation of sequences across related species has been used to functionally annotate protein coding genes. In contrast, the rapid evolutionary turnover and weak sequence conservation of lncRNAs make it difficult to characterize functional homologs for these sequences. Recent studies have tried to explore other dimensions of interspecies conservation to elucidate the functional role of these novel transcripts. In this review, we summarize various methodologies adopted to explore the evolutionary conservation of cardiovascular non-coding RNAs at sequence, secondary structure, syntenic, and expression level.

lncRNA MIR503HG functioned as a tumor suppressor and inhibited cell proliferation, metastasis and epithelial-mesenchymal transition in bladder cancer

Bladder cancer is the most common malignancy with high recurrence. Currently, the long noncoding RNAs (lncRNAs) have been suggested to play vital roles in the pathogenesis of bladder cancer. The present study investigated the role of lncRNA MIR503 host gene (MIR503HG) in the pathogenesis of bladder cancer by using both in vitro and in vivo functional assays. The expression of MIR503HG was downregulated in bladder cancer tissues and cell lines. Low expression of MIR503HG was associated with advanced tumor stage, advanced histological grade, and lymph node metastasis. Ectopic expression of MIR503HG inhibited cell proliferation, cell growth, cell invasion, and migration, and also promoted cell apoptosis and inhibited cell cycle progression in SW780 cells. In parallel, T24 cells were used for loss-of-function studies. Knockdown of MIR503HG promoted the cancer cell proliferation and increased the migration and invasion abilities of T24 cells. In addition, knockdown of MIR503HG reduced the cell apoptotic rate in cancer cells and promoted cell cycle progression. Furthermore, MIR503HG overexpression decreased the epithelial-mesenchymal transition-related mRNA and protein levels of ZEB1, Snail, N-cadherin, and vimentin, with an increase in E-cadherin level. Consistently, knockdown of MIR503HG showed the opposite effects. In vivo xenograft, nude mice results showed that overexpression of MIR503HG suppressed the tumor growth and tumor metastasis. In conclusion, our results identified a novel lncRNA MIR503HG that exhibited significant antiproliferation, antimigration/invasion effects on bladder cancer cells both in vitro and in vivo, which may hold a therapeutic promise to treat bladder cancer.

ScanFold: an approach for genome-wide discovery of local RNA structural elements-applications to Zika virus and HIV

In addition to encoding RNA primary structures, genomes also encode RNA secondary and tertiary structures that play roles in gene regulation and, in the case of RNA viruses, genome replication. Methods for the identification of functional RNA structures in genomes typically rely on scanning analysis windows, where multiple partially-overlapping windows are used to predict RNA structures and folding metrics to deduce regions likely to form functional structure. Separate structural models are produced for each window, where the step size can greatly affect the returned model. This makes deducing unique local structures challenging, as the same nucleotides in each window can be alternatively base paired. We are presenting here a new approach where all base pairs from analysis windows are considered and weighted by favorable folding. This results in unique base pairing throughout the genome and the generation of local regions/structures that can be ranked by their propensity to form unusually thermodynamically stable folds. We applied this approach to the Zika virus (ZIKV) and HIV-1 genomes. ZIKV is linked to a variety of neurological ailments including microcephaly and Guillain-Barré syndrome and its (+)-sense RNA genome encodes two, previously described, functionally essential structured RNA regions. HIV, the cause of AIDS, contains multiple functional RNA motifs in its genome, which have been extensively studied. Our approach is able to successfully identify and model the structures of known functional motifs in both viruses, while also finding additional regions likely to form functional structures. All data have been archived at the RNAStructuromeDB (www.structurome.bb.iastate.edu), a repository of RNA folding data for humans and their pathogens.

The RNA Base-Pairing Problem and Base-Pairing Solutions

RNA molecules are folded into structures and complexes to perform a wide variety of functions. Determination of RNA structures and their interactions is a fundamental problem in RNA biology. Most RNA molecules in living cells are large and dynamic, posing unique challenges to structure analysis. Here we review progress in RNA structure analysis, focusing on methods that use the "cross-link, proximally ligate, and sequence" principle for high-throughput detection of base-pairing interactions in living cells. Beginning with a comparison of commonly used methods in structure determination and a brief historical account of psoralen cross-linking studies, we highlight the important features of cross-linking methods and new biological insights into RNA structures and interactions from recent studies. Further improvement of these cross-linking methods and application to previously intractable problems will shed new light on the mechanisms of the "modern RNA world."

The ensemble diversity of non-coding RNA structure is lower than random sequence

In addition to energetically optimal structures, RNAs can fold into near energy suboptimal conformations that may be populated and play functional roles. The diversity of this structural ensemble can be estimated using a metric derived from the calculated RNA partition function: the ensemble diversity. In this report, 10 classes of functional RNAs were analyzed: the 5.8S and 5S rRNAs, ribozyme, RNase P, snoRNA, snRNA, SRP RNA, tmRNA, Vault RNA and Y RNA. Representative sequences from each class were mutagenized in two ways: firstly, all possible point mutations were generated and secondly, wild type sequences were randomized to generate multiple scrambled mutants. Compared to the mutants, the native RNA ensemble diversity was predicted to be lower. This finding held true when all available sequences (378,455 sequences) for each RNA class (archived in the RNAcentral database) were analyzed. This suggests that a compact structural ensemble is an evolved characteristic of functional RNAs.

RNA Structure Elements Conserved between Mouse and 59 Other Vertebrates

In this work, we present a computational screen conducted for functional RNA structures, resulting in over 100,000 conserved RNA structure elements found in alignments of mouse (mm10) against 59 other vertebrates. We explicitly included masked repeat regions to explore the potential of transposable elements and low-complexity regions to give rise to regulatory RNA elements. In our analysis pipeline, we implemented a four-step procedure: (i) we screened genome-wide alignments for potential structure elements using RNAz-2, (ii) realigned and refined candidate loci with LocARNA-P, (iii) scored candidates again with RNAz-2 in structure alignment mode, and (iv) searched for additional homologous loci in mouse genome that were not covered by genome alignments. The 3'-untranslated regions (3'-UTRs) of protein-coding genes and small noncoding RNAs are enriched for structures, while coding sequences are depleted. Repeat-associated loci make up about 95% of the homologous loci identified and are, as expected, predominantly found in intronic and intergenic regions. Nevertheless, we report the structure elements enriched in specific genome elements, such as 3'-UTRs and long noncoding RNAs (lncRNAs). We provide full access to our results via a custom UCSC genome browser trackhub freely available on our website (http://rna.tbi.univie.ac.at/trackhubs/#RNAz).

A current view on long noncoding RNAs in yeast and filamentous fungi

Long noncoding RNAs (lncRNAs) are crucial players in epigenetic regulation. They were initially discovered in human, yet they emerged as common factors involved in a number of central cellular processes in several eukaryotes. For example, in the past decade, research on lncRNAs in yeast has steadily increased. Several examples of lncRNAs were described in Saccharomyces cerevisiae and Schizosaccharomyces pombe. Also, screenings for lncRNAs in ascomycetes were performed and, just recently, the first full characterization of a lncRNA was performed in the filamentous fungus Trichoderma reesei. In this review, we provide a broad overview about currently known fugal lncRNAs. We make an attempt to categorize them according to their functional context, regulatory strategies or special properties. Moreover, the potential of lncRNAs as a biotechnological tool is discussed.

Genome-wide identification and analysis of A-to-I RNA editing events in bovine by transcriptome sequencing

RNA editing increases the diversity of the transcriptome and proteome. Adenosine-to-inosine (A-to-I) editing is the predominant type of RNA editing in mammals and it is catalyzed by the adenosine deaminases acting on RNA (ADARs) family. Here, we used a largescale computational analysis of transcriptomic data from brain, heart, colon, lung, spleen, kidney, testes, skeletal muscle and liver, from three adult animals in order to identify RNA editing sites in bovine. We developed a computational pipeline and used a rigorous strategy to identify novel editing sites from RNA-Seq data in the absence of corresponding DNA sequence information. Our methods take into account sequencing errors, mapping bias, as well as biological replication to reduce the probability of obtaining a false-positive result. We conducted a detailed characterization of sequence and structural features related to novel candidate sites and found 1,600 novel canonical A-to-I editing sites in the nine bovine tissues analyzed. Results show that these sites 1) occur frequently in clusters and short interspersed nuclear elements (SINE) repeats, 2) have a preference for guanines depletion/enrichment in the flanking 5′/3′ nucleotide, 3) occur less often in coding sequences than other regions of the genome, and 4) have low evolutionary conservation. Further, we found that a positive correlation exists between expression of ADAR family members and tissue-specific RNA editing. Most of the genes with predicted A-to-I editing in each tissue were significantly enriched in biological terms relevant to the function of the corresponding tissue. Lastly, the results highlight the importance of the RNA editome in nervous system regulation. The present study extends the list of RNA editing sites in bovine and provides pipelines that may be used to investigate the editome in other organisms.

Deep sequencing of the mouse lung transcriptome reveals distinct long non-coding RNAs expression associated with the high virulence of H5N1 avian influenza virus in mice

Long non-coding RNAs (lncRNAs) play multiple key regulatory roles in various biological processes. However, their function in influenza A virus (IAV) pathogenicity remains largely unexplored. Here, using next generation sequencing, we systemically compared the whole-transcriptome response of the mouse lung infected with either the highly pathogenic (A/Chicken/Jiangsu/k0402/2010, CK10) or the nonpathogenic (A/Goose/Jiangsu/k0403/2010, GS10) H5N1 virus. A total of 126 significantly differentially expressed (SDE) lncRNAs from three replicates were identified to be associated with the high virulence of CK10, whereas 94 SDE lncRNAs were related with GS10. Functional category analysis suggested that the SDE lncRNAs-coexpressed mRNAs regulated by CK10 were highly related with aberrant and uncontrolled inflammatory responses. Further canonical pathway analysis also confirmed that these targets were highly enriched for inflammatory-related pathways. Moreover, 9 lncRNAs and 17 lncRNAs-coexpressed mRNAs associated with a large number of targeted genes were successfully verified by qRT-PCR. One targeted lncRNA (NONMMUT011061) that was markedly activated and correlated with a great number of mRNAs was selected for further in-depth analysis, including predication of transcription factors, potential interacting proteins, genomic location, coding ability and construction of the secondary structure. More importantly, NONMMUT011061 was also distinctively stimulated during the highly pathogenic H5N8 virus infection in mice, suggesting a potential universal role of NONMMUT011061 in the pathogenesis of different H5 IAV. Altogether, these results provide a subset of lncRNAs that might play important roles in the pathogenesis of influenza virus and add the lncRNAs to the vast repertoire of host factors utilized by IAV for infection and persistence.

Comparative RNA Genomics

Over the last two decades it has become clear that RNA is much more than just a boring intermediate in protein expression. Ancient RNAs still appear in the core information metabolism and comprise a surprisingly large component in bacterial gene regulation. A common theme with these types of mostly small RNAs is their reliance of conserved secondary structures. Large scale sequencing projects, on the other hand, have profoundly changed our understanding of eukaryotic genomes. Pervasively transcribed, they give rise to a plethora of large and evolutionarily extremely flexible noncoding RNAs that exert a vastly diverse array of molecule functions. In this chapter we provide a-necessarily incomplete-overview of the current state of comparative analysis of noncoding RNAs, emphasizing computational approaches as a means to gain a global picture of the modern RNA world.

Roles of miRNAs and long noncoding RNAs in the progression of diabetic retinopathy

Diabetic retinopathy (DR) is the leading cause of blindness in working-age adults across the world. The pathogenesis of DR is multifactorial and the molecular mechanisms are still not fully understood. Accumulating evidence has demonstrated that noncoding RNAs (ncRNAs) may be aberrantly expressed and may play vital roles in the development of DR. Amongst ncRNAs, miRNAs and long ncRNAs (lncRNAs) are known for their regulatory functions. Here, we summarize the functions and mechanisms of known aberrantly expressed miRNAs and lncRNAs in DR. Additionally, a novel lncRNA–mRNA–miRNA network is included in this review. We highlight original studies that provide detailed data about the mechanisms of miRNAs and lncRNAs, their applications as diagnostic or prognostic biomarkers, and their potential therapeutic targets. In conclusion, this review will help us gain a better understanding of the molecular mechanisms by which miRNAs and lncRNAs perform their functions in DR, and provide general strategies and directions for future research.

Exploring Consensus RNA Substructural Patterns Using Subgraph Mining

Frequently recurring RNA structural motifs play important roles in RNA folding process and interaction with other molecules. Traditional index-based and shape-based schemas are useful in modeling RNA secondary structures but ignore the structural discrepancy of individual RNA family member. Further, the in-depth analysis of underlying substructure pattern is insufficient due to varied and unnormalized substructure data. This prevents us from understanding RNAs functions and their inherent synergistic regulation networks. This article thus proposes a novel labeled graph-based algorithm RnaGraph to uncover frequently RNA substructure patterns. Attribute data and graph data are combined to characterize diverse substructures and their correlations, respectively. Further, a top-k graph pattern mining algorithm is developed to extract interesting substructure motifs by integrating frequency and similarity. The experimental results show that our methods assist in not only modelling complex RNA secondary structures but also identifying hidden but interesting RNA substructure patterns.

Long noncoding RNAs coordinate functions between mitochondria and the nucleus

In animal cells, mitochondria are the primary powerhouses and metabolic factories. They also contain genomes and can produce mitochondrial-specific nucleic acids and proteins. To maintain homeostasis of the entire cell, an intense cross-talk between mitochondria and the nucleus, mediated by encoded noncoding RNAs (ncRNAs), as well as proteins, is required. Long ncRNAs (lncRNAs) contain characteristic structures, and they are involved in the regulation of almost every stage of gene expression, as well as being implicated in a variety of disease states, such as cancer. In the coordinated signaling system, several lncRNAs, transcribed in the nucleus but residing in mitochondria, play a key role in regulating mitochondrial functions or dynamics. For example, RMRP, a component of the mitochondrial RNase MRP, is important for mitochondrial DNA replication and RNA processing, and the steroid receptor RNA activator, SRA, is a key modulator of hormone signaling and is present in both the nucleus and mitochondria. Some RNA-binding proteins maybe play a role in the lncRNAs transport system, such as HuR, GRSF1, SHARP, SLIRP, PPR, and PNPASE. Furthermore, a series of nuclear DNA-encoded lncRNAs were implicated in mitochondria-mediated apoptosis, mitochondrial bioenergetics and biosynthesis, and glutamine metabolism. The mitochondrial genome can also encode a set of lncRNAs, and they are divided into three categories: (1) lncND5, lncND6, and lncCyt b RNA; (2) chimeric mitochondrial DNA-encoded lncRNAs; and (3) putative mitochondrial DNA-encoded lncRNAs. It has been reported that the mitochondrial DNA-encoded lncRNAs appear to operate in the nucleus. The molecular mechanisms underlying trafficking of the mitochondrial DNA-encoded lncRNAs to the nucleus in mammals are only now beginning to emerge. In conclusion, both nuclear- and mitochondrial DNA-encoded lncRNAs mediate an intense intercompartmental cross-talk, which opens a rich field for investigation of the mechanism underlying the intercompartmental coordination and the maintenance of whole cell homeostasis.

Non-coding RNAs as a new dawn in tumor diagnosis

The current knowledge about non-coding RNAs (ncRNAs) as important regulators of gene expression in both physiological and pathological conditions, has been the main engine for the design of innovative platforms to finalize the pharmacological application of ncRNAs as either therapeutic tools or as molecular biomarkers in cancer. Biochemical alterations of cancer cells are, in fact, largely supported by ncRNA disregulation in the tumor site, which, in turn, reflects the cancer-associated specific modification of circulating ncRNA expression pattern. The aim of this review is to describe the state of the art of pre-clinical and clinical studies that analyze the involvement of miRNAs and lncRNAs in cancer-related processes, such as proliferation, invasion and metastases, giving emphasis to their functional role. A central node of our work has been also the examination of advantages and criticisms correlated with the clinical use of ncRNAs, taking into account the pressing need to refine the profiling methods aimed at identify novel diagnostic and prognostic markers and the request to optimize the delivery of such nucleic acids for a therapeutic use in an imminent future.

Whole transcriptome analysis reveals dysregulated oncogenic lncRNAs in natural killer/T-cell lymphoma and establishes MIR155HG as a target of PRDM1

Natural killer/T-cell lymphoma is a rare but aggressive neoplasm with poor prognosis. Despite previous reports that showed potential tumor suppressors, such as PRDM1 or oncogenes associated with the etiology of this malignancy, the role of long non-coding RNAs in natural killer/T-cell lymphoma pathobiology has not been addressed to date. Here, we aim to identify cancer-associated dysregulated long non-coding RNAs and signaling pathways or biological processes associated with these long non-coding RNAs in natural killer/T-cell lymphoma cases and to identify the long non-coding RNAs transcriptionally regulated by PRDM1. RNA-Seq analysis revealed 166 and 66 long non-coding RNAs to be significantly overexpressed or underexpressed, respectively, in natural killer/T-cell lymphoma cases compared with resting or activated normal natural killer cells. Novel long non-coding RNAs as well as the cancer-associated ones such as SNHG5, ZFAS1, or MIR155HG were dysregulated. Interestingly, antisense transcripts of many growth-regulating genes appeared to be transcriptionally deregulated. Expression of ZFAS1, which is upregulated in natural killer/T-cell lymphoma cases, showed association with growth-regulating pathways such as stabilization of P53, regulation of apoptosis, cell cycle, or nuclear factor-kappa B signaling in normal and neoplastic natural killer cell samples. Consistent with the tumor suppressive role of PRDM1, we identified MIR155HG and TERC to be transcriptionally downregulated by PRDM1 in two PRDM1-null NK-cell lines when it is ectopically expressed. In conclusion, this is the first study that identified long non-coding RNAs whose expression is dysregulated in natural killer/T-cell lymphoma cases. These findings suggest that ZFAS1 and other dysregulated long non-coding RNAs may be involved in natural killer/T-cell lymphoma pathobiology through regulation of cancer-related genes, and loss-of-PRDM1 expression in natural killer/T-cell lymphomas may contribute to overexpression of MIR155HG; thereby promoting tumorigenesis.

The identification and functional annotation of RNA structures conserved in vertebrates

Structured elements of RNA molecules are essential in, e.g., RNA stabilization, localization, and protein interaction, and their conservation across species suggests a common functional role. We computationally screened vertebrate genomes for conserved RNA structures (CRSs), leveraging structure-based, rather than sequence-based, alignments. After careful correction for sequence identity and GC content, we predict ∼516,000 human genomic regions containing CRSs. We find that a substantial fraction of human–mouse CRS regions (1) colocalize consistently with binding sites of the same RNA binding proteins (RBPs) or (2) are transcribed in corresponding tissues. Additionally, a CaptureSeq experiment revealed expression of many of our CRS regions in human fetal brain, including 662 novel ones. For selected human and mouse candidate pairs, qRT-PCR and in vitro RNA structure probing supported both shared expression and shared structure despite low abundance and low sequence identity. About 30,000 CRS regions are located near coding or long noncoding RNA genes or within enhancers. Structured (CRS overlapping) enhancer RNAs and extended 3′ ends have significantly increased expression levels over their nonstructured counterparts. Our findings of transcribed uncharacterized regulatory regions that contain CRSs support their RNA-mediated functionality.

A Review on Recent Computational Methods for Predicting Noncoding RNAs

Noncoding RNAs (ncRNAs) play important roles in various cellular activities and diseases. In this paper, we presented a comprehensive review on computational methods for ncRNA prediction, which are generally grouped into four categories: (1) homology-based methods, that is, comparative methods involving evolutionarily conserved RNA sequences and structures, (2) de novo methods using RNA sequence and structure features, (3) transcriptional sequencing and assembling based methods, that is, methods designed for single and pair-ended reads generated from next-generation RNA sequencing, and (4) RNA family specific methods, for example, methods specific for microRNAs and long noncoding RNAs. In the end, we summarized the advantages and limitations of these methods and pointed out a few possible future directions for ncRNA prediction. In conclusion, many computational methods have been demonstrated to be effective in predicting ncRNAs for further experimental validation. They are critical in reducing the huge number of potential ncRNAs and pointing the community to high confidence candidates. In the future, high efficient mapping technology and more intrinsic sequence features (e.g., motif and k-mer frequencies) and structure features (e.g., minimum free energy, conserved stem-loop, or graph structures) are suggested to be combined with the next- and third-generation sequencing platforms to improve ncRNA prediction.

Transcriptomic responses to environmental temperature by turtles with temperature-dependent and genotypic sex determination assessed by RNAseq inform the genetic architecture of embryonic gonadal development

Vertebrate sexual fate is decided primarily by the individual's genotype (GSD), by the environmental temperature during development (TSD), or both. Turtles exhibit TSD and GSD, making them ideal to study the evolution of sex determination. Here we analyze temperature-specific gonadal transcriptomes (RNA-sequencing validated by qPCR) of painted turtles (Chrysemys picta TSD) before and during the thermosensitive period, and at equivalent stages in soft-shell turtles (Apalone spinifera-GSD), to test whether TSD's and GSD's transcriptional circuitry is identical but deployed differently between mechanisms. Our data show that most elements of the mammalian urogenital network are active during turtle gonadogenesis, but their transcription is generally more thermoresponsive in TSD than GSD, and concordant with their sex-specific function in mammals [e.g., upregulation of Amh, Ar, Esr1, Fog2, Gata4, Igf1r, Insr, and Lhx9 at male-producing temperature, and of β-catenin, Foxl2, Aromatase (Cyp19a1), Fst, Nf-kb, Crabp2 at female-producing temperature in Chrysemys]. Notably, antagonistic elements in gonadogenesis (e.g., β-catenin and Insr) were thermosensitive only in TSD early-embryos. Cirbp showed warm-temperature upregulation in both turtles disputing its purported key TSD role. Genes that may convert thermal inputs into sex-specific development (e.g., signaling and hormonal pathways, RNA-binding and heat-shock) were differentially regulated. Jak-Stat, Nf-κB, retinoic-acid, Wnt, and Mapk-signaling (not Akt and Ras-signaling) potentially mediate TSD thermosensitivity. Numerous species-specific ncRNAs (including Xist) were differentially-expressed, mostly upregulated at colder temperatures, as were unannotated loci that constitute novel TSD candidates. Cirbp showed warm-temperature upregulation in both turtles. Consistent transcription between turtles and alligator revealed putatively-critical reptilian TSD elements for male (Sf1, Amh, Amhr2) and female (Crabp2 and Hspb1) gonadogenesis. In conclusion, while preliminary, our data helps illuminate the regulation and evolution of vertebrate sex determination, and contribute genomic resources to guide further research into this fundamental biological process.

Emerging roles for long noncoding RNAs in skeletal biology and disease

Normal skeletal development requires tight coordination of transcriptional networks, signaling pathways, and biomechanical cues, and many of these pathways are dysregulated in pathological conditions affecting cartilage and bone. Recently, a significant role has been identified for long noncoding RNAs (lncRNAs) in developing and maintaining cellular phenotypes, and improvements in sequencing technologies have led to the identification of thousands of lncRNAs across diverse cell types, including the cells within cartilage and bone. It is clear that lncRNAs play critical roles in regulating gene expression. For example, they can function as epigenetic regulators in the nucleus via chromatin modulation to control gene transcription, or in the cytoplasm, where they can function as scaffolds for protein-binding partners or modulate the activity of other coding and noncoding RNAs. In this review, we discuss the growing list of lncRNAs involved in normal development and/or homeostasis of the skeletal system, the potential mechanisms by which these lncRNAs might function, and recent improvements in the methodologies available to study lncRNA functions in vitro and in vivo. Finally, we address the likely utility of lncRNAs as biomarkers and therapeutic targets for diseases of the skeletal system, including osteoarthritis, osteoporosis, and in cancers of the skeletal system.

Mycoplasma non-coding RNA: identification of small RNAs and targets

Background

Bacterial non-coding RNAs act by base-pairing as regulatory elements in crucial biological processes. We performed the identification of trans-encoded small RNAs (sRNA) from the genomes of Mycoplama hyopneumoniae, Mycoplasma flocculare and Mycoplasma hyorhinis, which are Mycoplasma species that have been identified in the porcine respiratory system.

Results

A total of 47, 15 and 11 putative sRNAs were predicted in M. hyopneumoniae, M. flocculare and M. hyorhinis, respectively. A comparative genomic analysis revealed the presence of species or lineage specific sRNA candidates. Furthermore, the expression profile of some M. hyopneumoniae sRNAs was determined by a reverse transcription amplification approach, in three different culture conditions. All tested sRNAs were transcribed in at least one condition. A detailed investigation revealed a differential expression profile for two M. hyopneumoniae sRNAs in response to oxidative and heat shock stress conditions, suggesting that their expression is influenced by environmental signals. Moreover, we analyzed sRNA-mRNA hybrids and accessed putative target genes for the novel sRNA candidates. The majority of the sRNAs showed interaction with multiple target genes, some of which could be linked to pathogenesis and cell homeostasis activity.

Conclusion

This study contributes to our knowledge of Mycoplasma sRNAs and their response to environmental changes. Furthermore, the mRNA target prediction provides a perspective for the characterization and comprehension of the function of the sRNA regulatory mechanisms.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3061-z) contains supplementary material, which is available to authorized users.