Novel insight into the non-coding repertoire through deep sequencing analysis

MicroRNAs Regulating Autophagy in Neurodegeneration

Social and economic impacts of neurodegenerative diseases (NDs) become more prominent in our constantly aging population. Currently, due to the lack of knowledge about the aetiology of most NDs, only symptomatic treatment is available for patients. Hence, researchers and clinicians are in need of solid studies on pathological mechanisms of NDs. Autophagy promotes degradation of pathogenic proteins in NDs, while microRNAs post-transcriptionally regulate multiple signalling networks including autophagy. This chapter will critically discuss current research advancements in the area of microRNAs regulating autophagy in NDs. Moreover, we will introduce basic strategies and techniques used in microRNA research. Delineation of the mechanisms contributing to NDs will result in development of better approaches for their early diagnosis and effective treatment.

A comprehensive annotation and differential expression analysis of short and long non-coding RNAs in 16 bat genomes

Although bats are increasingly becoming the focus of scientific studies due to their unique properties, these exceptional animals are still among the least studied mammals. Assembly quality and completeness of bat genomes vary a lot and especially non-coding RNA (ncRNA) annotations are incomplete or simply missing. Accordingly, standard bioinformatics pipelines for gene expression analysis often ignore ncRNAs such as microRNAs or long antisense RNAs. The main cause of this problem is the use of incomplete genome annotations. We present a complete screening for ncRNAs within 16 bat genomes. NcRNAs affect a remarkable variety of vital biological functions, including gene expression regulation, RNA processing, RNA interference and, as recently described, regulatory processes in viral infections. Within all investigated bat assemblies, we annotated 667 ncRNA families including 162 snoRNAs and 193 miRNAs as well as rRNAs, tRNAs, several snRNAs and lncRNAs, and other structural ncRNA elements. We validated our ncRNA candidates by six RNA-Seq data sets and show significant expression patterns that have never been described before in a bat species on such a large scale. Our annotations will be usable as a resource (rna.uni-jena.de/supplements/bats) for deeper studying of bat evolution, ncRNAs repertoire, gene expression and regulation, ecology and important host–virus interactions.

lncRNA FOXD3-AS1 is associated with clinical progression and regulates cell migration and invasion in breast cancer

For women, breast cancer is the most commonly diagnosed cancer and the leading cause of women deaths due to cancer. In recent years, increasing long noncoding RNA (lncRNA) has been discovered to be related to tumorigenesis, progression, and prognosis. FOXD3-AS1 is a lncRNA and has been identified as a cancer-promoting gene in glioma. By analysing the FOXD3-AS1 expression in The Cancer Genome Atlas (TCGA) database, we found that FOXD3-AS1 has significantly high expression in breast cancer tumour comparing with the normal tissue. And patients with low FOXD3-AS1 expression had greater survival probability, smaller tumour size, and less distant metastasis. This leads us to peep inquisitively biological function of FOXD3-AS1 in breast cancer. Biological assays demonstrated that silenced FOXD3-AS1 impaired cell proliferation and inhibited cell migration and invasion in breast cancer cell lines (BT549, MDA-MB-231). These results suggest that FOXD3-AS1 could play a potential diagnostics or prognostic biomarker for patients with breast cancer. SIGNIFICANCE OF THE STUDY: We demonstrated that lncRNA FOXD3-AS1 has significantly high expression in breast cancer cell lines comparing with the normal tissue. Besides, our findings suggested that lncRNA FOXD3-AS1 could play a potential diagnostics or prognostic biomarker for patients with breast cancer.

HIV-1 infection increases microRNAs that inhibit Dicer1, HRB and HIV-EP2, thereby reducing viral replication

HIV-1 is the causative agent of AIDS (Autoimmune Deficiency Syndrome). HIV-1 infection results in systemic CD4⁺ T cell depletion, thereby impairing cell-mediated immunity. MicroRNAs are short (~22 nucleotides long), endogenous single-stranded RNA molecules that regulate gene expression by binding to the 3' untranslated regions (3' UTR) of mRNA transcripts. The relation between HIV-1 infection and human miRNA expression profile has been previously investigated, and studies have shown that the virus can alter miRNA expression and vice versa. Here, we broaden the understanding of the HIV-1 infection process, and show that miRNA-186, 210 and 222 are up-regulated following HIV-1 infection of human Sup-T1 cells. As a result, the host miRNA target genes: Dicer1 (Double-Stranded RNA-Specific Endoribonuclease), HRB (HIV-1 Rev-binding protein) and HIV-EP2 (Human Immunodeficiency Virus Type I Enhancer Binding Protein 2), are down-regulated. Moreover, testing the miRNA-gene anti- correlation on the Jurkat and the HeLa-MAGI cell lines demonstrated the ability of the miRNAs to down-regulate viral expression as well. To conclude, we found that human miR-186, 210 and 222 directly regulate the human genes Dicer1, HRB and HIV-EP2, thus may be filling key roles during HIV-1 replication and miRNA biogenesis. This finding may contribute to the development of new therapeutic strategies.

Temporal dynamics in meta longitudinal RNA-Seq data

Identification of differentially expressed genes has been a high priority task of downstream analyses to further advances in biomedical research. Investigators have been faced with an array of issues in dealing with more complicated experiments and metadata, including batch effects, normalization, temporal dynamics (temporally differential expression), and isoform diversity (isoform-level quantification and differential splicing events). To date, there are currently no standard approaches to precisely and efficiently analyze these moderate or large-scale experimental designs, especially with combined metadata. In this report, we propose comprehensive analytical pipelines to precisely characterize temporal dynamics in differential expression of genes and other genomic features, i.e., the variability of transcripts, isoforms and exons, by controlling batch effects and other nuisance factors that could have significant confounding effects on the main effects of interest in comparative models and may result in misleading interpretations.

Long noncoding RNA FOXD3-AS1 regulates oxidative stress-induced apoptosis via sponging microRNA-150

The function of most human long noncoding RNAs (lncRNAs) remains unclear. Our studies identified a highly up-regulated mammalian lncRNA, FOXD3-AS1, known as linc1623 in mice, in the setting of hyperoxia/reactive oxygen species (ROS)-induced lung injury. We found that ROS induced a robust expression of FOXD3-AS1 in mouse lung tissue. Functionally, FOXD3-AS1 promoted oxidative stress-induced lung epithelial cell death. In human lung epithelial cells, the microRNA-150 (miR-150) was identified to interact with FOXD3-AS1; this finding was confirmed using the luciferase reporter assays. Consistently, mutation on the miR-150 pairing sequence in FOXD3-AS1 abolished the interactions between FOXD3-AS1 and miR-150. Additionally, miR-150 mimics suppressed the level of FOXD3-AS1. The antisense oligos of FOXD3-AS1 significantly augmented the intracellular level of miR-150, supporting the theory of sponging effects of FOXD3-AS1 on miR-150. We further investigated the cellular function of miR-150 in our lung injury models. MiR-150 conferred a cytoprotective role in lung epithelial cells after oxidative stress, whereas FOXD3-AS1 promoted cell death. Taken together, our studies indicated that FOXD3-AS1 serves as a sponge or as a competing endogenous noncoding RNA for miR-150, restricting its capability to promote cell growth and thereby exaggerating hyperoxia-induced lung epithelial cell death.-Zhang, D., Lee, H., Haspel, J. A., Jin, Y. Long noncoding RNA FOXD3-AS1 regulates oxidative stress-induced apoptosis via sponging microRNA-150.

Noncoding RNA: Current Deep Sequencing Data Analysis Approaches and Challenges

One of the most significant biological discoveries of the last decade is represented by the reality that the vast majority of the transcribed genomic output comprises diverse classes of noncoding RNAs (ncRNAs) that may play key roles and/or be affected by many biochemical cellular processes (i.e., RNA editing), with implications in human health and disease. With 90% of the human genome being transcribed and novel classes of ncRNA emerging (tRNA-derived small RNAs and circular RNAs among others), the great majority of the human transcriptome suggests that many important ncRNA functions/processes are yet to be discovered. An approach to filling such vast void of knowledge has been recently provided by the increasing application of next-generation sequencing (NGS), offering the unprecedented opportunity to obtain a more accurate profiling with higher resolution, increased throughput, sequencing depth, and low experimental complexity, concurrently posing an increasing challenge in terms of efficiency, accuracy, and usability of data analysis software. This review provides an overview of ncRNAs, NGS technology, and the most recent/popular computational approaches and the challenges they attempt to solve, which are essential to a more sensitive and comprehensive ncRNA annotation capable of furthering our understanding of this still vastly uncharted genomic territory.

Computational Approaches for the Analysis of ncRNA through Deep Sequencing Techniques

The majority of the human transcriptome is defined as non-coding RNA (ncRNA), since only a small fraction of human DNA encodes for proteins, as reported by the ENCODE project. Several distinct classes of ncRNAs, such as transfer RNA, microRNA, and long non-coding RNA, have been classified, each with its own three-dimensional folding and specific function. As ncRNAs are highly abundant in living organisms and have been discovered to play important roles in many biological processes, there has been an ever increasing need to investigate the entire ncRNAome in further unbiased detail. Recently, the advent of next-generation sequencing (NGS) technologies has substantially increased the throughput of transcriptome studies, allowing an unprecedented investigation of ncRNAs, as regulatory pathways and novel functions involving ncRNAs are now also emerging. The huge amount of transcript data produced by NGS has progressively required the development and implementation of suitable bioinformatics workflows, complemented by knowledge-based approaches, to identify, classify, and evaluate the expression of hundreds of ncRNAs in normal and pathological conditions, such as cancer. In this mini-review, we present and discuss current bioinformatics advances in the development of such computational approaches to analyze and classify the ncRNA component of human transcriptome sequence data obtained from NGS technologies.

MicroRNA-mediated regulation of p21 and TASK1 cellular restriction factors enhances HIV-1 infection

MicroRNAs (miRNAs) are short non-coding RNAs that play a central role in the regulation of gene expression by binding to target mRNAs. Several studies have revealed alterations in cellular miRNA profiles following HIV-1 infection, mostly for miRNAs involved in inhibiting viral infection. These miRNA expression modifications might also serve to block the innate HIV-1 inhibition mechanism. As a result, it is expected that during HIV-1 infection miRNAs target genes that hinder or prevent the progression of the HIV-1 replication cycle. One of the major sets of genes known to inhibit the progression of HIV-1 infection are cellular restriction factors. In this study, we identified a direct miRNA target gene that modulates viral spread in T-lymphocytes and HeLa-CCR5 cell lines. Following infection, let-7c, miR-34a or miR-124a were upregulated, and they targeted and downregulated p21 and TASK1 (also known as CDKN1A and KCNK3, respectively) cellular proteins. This eventually led to increased virion release and higher copy number of viral genome transcripts in infected cells. Conversely, by downregulating these miRNAs, we could suppress viral replication and spread. Our data suggest that HIV-1 exploits the host miRNA cellular systems in order to block the innate inhibition mechanism, allowing a more efficient infection process.

Changing genetic paradigms: creating next-generation genetic databases as tools to understand the emerging complexities of genotype/phenotype relationships

Understanding genotype/phenotype relationships has become more complicated as increasing amounts of inter- and intra-tissue genetic heterogeneity have been revealed through next-generation sequencing and evidence showing that factors such as epigenetic modifications, non-coding RNAs and RNA editing can play an important role in determining phenotype. Such findings have challenged a number of classic genetic assumptions including (i) analysis of genomic sequence obtained from blood is an accurate reflection of the genotype responsible for phenotype expression in an individual; (ii) that significant genetic alterations will be found only in diseased individuals, in germline tissues in inherited diseases, or in specific diseased tissues in somatic diseases such as cancer; and (iii) that mutation rates in putative disease-associated genes solely determine disease phenotypes. With the breakdown of our traditional understanding of genotype to phenotype relationships, it is becoming increasingly apparent that new analytical tools will be required to determine the relationship between genotype and phenotypic expression. To this end, we are proposing that next-generation genetic database (NGDB) platforms be created that include new bioinformatics tools based on algorithms that can evaluate genetic heterogeneity, as well as powerful systems biology analysis tools to actively process and evaluate the vast amounts of both genomic and genomic-modifying information required to reveal the true relationships between genotype and phenotype.

iMir: an integrated pipeline for high-throughput analysis of small non-coding RNA data obtained by smallRNA-Seq

BACKGROUND

Qualitative and quantitative analysis of small non-coding RNAs by next generation sequencing (smallRNA-Seq) represents a novel technology increasingly used to investigate with high sensitivity and specificity RNA population comprising microRNAs and other regulatory small transcripts. Analysis of smallRNA-Seq data to gather biologically relevant information, i.e. detection and differential expression analysis of known and novel non-coding RNAs, target prediction, etc., requires implementation of multiple statistical and bioinformatics tools from different sources, each focusing on a specific step of the analysis pipeline. As a consequence, the analytical workflow is slowed down by the need for continuous interventions by the operator, a critical factor when large numbers of datasets need to be analyzed at once.

RESULTS

We designed a novel modular pipeline (iMir) for comprehensive analysis of smallRNA-Seq data, comprising specific tools for adapter trimming, quality filtering, differential expression analysis, biological target prediction and other useful options by integrating multiple open source modules and resources in an automated workflow. As statistics is crucial in deep-sequencing data analysis, we devised and integrated in iMir tools based on different statistical approaches to allow the operator to analyze data rigorously. The pipeline created here proved to be efficient and time-saving than currently available methods and, in addition, flexible enough to allow the user to select the preferred combination of analytical steps. We present here the results obtained by applying this pipeline to analyze simultaneously 6 smallRNA-Seq datasets from either exponentially growing or growth-arrested human breast cancer MCF-7 cells, that led to the rapid and accurate identification, quantitation and differential expression analysis of ~450 miRNAs, including several novel miRNAs and isomiRs, as well as identification of the putative mRNA targets of differentially expressed miRNAs. In addition, iMir allowed also the identification of ~70 piRNAs (piwi-interacting RNAs), some of which differentially expressed in proliferating vs growth arrested cells.

CONCLUSION

The integrated data analysis pipeline described here is based on a reliable, flexible and fully automated workflow, useful to rapidly and efficiently analyze high-throughput smallRNA-Seq data, such as those produced by the most recent high-performance next generation sequencers. iMir is available at http://www.labmedmolge.unisa.it/inglese/research/imir.

The involvement of microRNAs in major depression, suicidal behavior, and related disorders: a focus on miR-185 and miR-491-3p

Major depressive disorders are common and disabling conditions associated with significant psychosocial impairment and suicide risk. At least 3-4 % of all depressive individuals die by suicide. Evidence suggests that small non-coding RNAs, in particular microRNAs (miRNAs), play a critical role in major affective disorders as well as suicide. We performed a detailed review of the current literature on miRNAs and their targets in major depression and related disorders as well as suicidal behavior, with a specific focus on miR-185 and miR-491-3p, which have been suggested to participate in the pathogenesis of major depression and/or suicide. miRNAs play a fundamental role in the development of the brain. Several miRNAs are reported to influence neuronal and circuit formation by negatively regulating gene expression. Global miRNA reduced expression was found in the prefrontal cortex of depressed suicide completers when compared to that of nonpsychiatric controls who died of other causes. One particular miRNA, miR-185, was reported to regulate TrkB-T1, which has been associated with suicidal behavior upon truncation. Furthermore, cAMP response element-binding protein-brain-derived neurotrophic factor pathways may regulate, through miRNAs, the homeostasis of neural and synaptic pathways playing a crucial role in major depression. miRNAs have gained attention as key players involved in nervous system development, physiology, and disease. Further evidence is needed to clarify the exact role that miRNAs play in major depression and related disorders and suicidal behavior.

miRNAs and long noncoding RNAs as biomarkers in human diseases

Noncoding RNAs (ncRNAs) are transcripts that have no apparent protein-coding capacity; however, many ncRNAs have been found to play a major biological role in human physiology. Their deregulation is implicated in many human diseases, but their exact roles are only beginning to be elucidated. Nevertheless, ncRNAs are extensively studied as a novel source of biomarkers, and the fact that they can be detected in body fluids makes them extremely suitable for this purpose. The authors mainly focus on ncRNAs as biomarkers in cancer, but also touch on other human diseases such as cardiovascular diseases, autoimmune diseases, neurological disorders and infectious diseases. The authors discuss the established methods and provide a selection of emerging new techniques that can be used to detect and quantify ncRNAs. Finally, the authors discuss ncRNAs as a new strategy for therapeutic interventions.

Species-specific microRNA regulation influences phenotypic variability: perspectives on species-specific microRNA regulation

Phenotypic divergence among animal species may be due in part to species-specific (SS) regulation of gene expression by small, non-coding regulatory RNAs termed "microRNAs". This phenomenon can be modulated by several variables. First, microRNA genes vary by their level of conservation, many of them being SS, or unique to a particular evolutionary lineage. Second, microRNA expression levels vary spatially and temporally in different species. Lastly, while microRNAs bind the 3'UTR of target genes in order to silence their expression, the binding sites themselves are often non-conserved. The variability of the miRNA-target paradigm between different species is thus multifactorial, and this paradigm has only just started to gain attention from researchers in various fields. Here we present and discuss recent findings regarding the characteristics and implications of SS microRNA regulation.

Bioinformatics of Cancer ncRNA in High Throughput Sequencing: Present State and Challenges

The numerous genome sequencing projects produced unprecedented amount of data providing significant information to the discovery of novel non-coding RNA (ncRNA). Several ncRNAs have been described to control gene expression and display important role during cell differentiation and homeostasis. In the last decade, high throughput methods in conjunction with approaches in bioinformatics have been used to identify, classify, and evaluate the expression of hundreds of ncRNA in normal and pathological states, such as cancer. Patient outcomes have been already associated with differential expression of ncRNAs in normal and tumoral tissues, providing new insights in the development of innovative therapeutic strategies in oncology. In this review, we present and discuss bioinformatics advances in the development of computational approaches to analyze and discover ncRNA data in oncology using high throughput sequencing technologies.