Small RNA transcriptome investigation based on next-generation sequencing technology

Optimized miR-124 reporters uncover differences in miR-124 expression among neuronal populations in vitro

Introduction

Although intensively studied in the last decades, how microRNAs (miRNAs) are expressed across different cell types in the brain remains largely unknown.

Materials

To address this issue, we sought to develop optimized fluorescence reporters that could be expressed in precise cellular subsets and used to accurately quantify miR contents in vivo.

Results

Focusing on miR-124, we tested different reporter designs whose efficiency was confirmed in different in vitro settings including cell lines and primary neuronal cultures from different brain structures. Unlike previous reporters, we provide experimental evidence that our optimized designs can faithfully translate miR levels in vitro.

Discussion

Tools developed here would enable assessing miRNA expression at the single cell resolution and are expected to significantly contribute to future miRNA research in vivo.

Plasma tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 as novel diagnostic biomarkers for lung adenocarcinoma

Objective

TRNA-derived fragments (tRFs) and tRNA-derived stress-induced RNAs (tiRNAs) are recognized as novel and potential types of non-coding RNAs (ncRNAs), and several tRF/tiRNA signatures are closely associated with tumor diagnosis. This study aimed to analyze the expression profiles of plasma tRFs/tiRNAs and to clarify their diagnostic value in lung adenocarcinoma (LUAD).

Methods

The differential expression profiles of plasma tRFs/tiRNAs in patients with four patients with early LUAD, four patients with advanced LUAD, and four healthy controls were analyzed using high-throughput sequencing technology. Then, plasma tRFs/tiRNAs were validated by quantitative real-time polymerase chain reaction (qRT-PCR), and their diagnostic efficiency was appraised by receiver operating characteristic curve analysis. The correlation of candidate plasma tRFs/tiRNAs with clinicopathological features was also analyzed. Finally, bioinformatics analysis was performed to explore and identify the potential biological pathways induced by tRFs/tiRNAs.

Results

The sequencing results revealed that tRFs/tiRNAs from plasma samples in patients with LUAD were differently expressed, supporting the necessity of exploring their potential as biomarkers. The validation results of qRT-PCR demonstrated that the expression level of tRF-1:29-Pro-AGG-1-M6 was downregulated in LUAD, while that of tRF-55:76-Tyr-GTA-1-M2 was upregulated, which was consistent with the sequencing data. The areas under the receiver operating characteristic curve of tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 were 0.882 and 0.896, respectively, which have significant values in the diagnosis of LUAD. The expressions of tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 in LUAD were obviously correlated with various clinicopathological features such as tumor–node–metastasis stage, node stage, and the expression levels of carcinoembryonic antigen. In addition, their expression was significantly altered from before to after tumor resection in LUAD patients. The results of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses further indicated that tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 are widely distributed and apparently enriched in several tumor-related signaling pathways.

Conclusions

Plasma tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 may be promising components in the development of highly sensitive and non-invasive biomarkers for LUAD diagnosis.

tRNA-Derived Small RNAs: Novel Epigenetic Regulators

Simple Summary

Cells must synthesize new proteins to maintain its life and tRNA (transfer RNA) is an essential component of the translation process. tRNA-derived small RNA (tsRNA) is a relatively uncharacterized small RNA, derived from enzymatic cleavage of the tRNAs. Accumulating evidences suggest that tsRNA is an abundant, highly modified, dynamically regulated small-RNA and interacts with other types of RNAs or proteins. Moreover, it is abnormally expressed in multiple human diseases including systemic lupus, neurological disorder, metabolic disorder and cancer, implying its diverse function in the initiation or progression of such diseases. In this review, we summarize the classification of tsRNA and its role focused on the epigenetic regulation. Further, we discuss the limitation of current knowledge about the tsRNA and its potential applications.

Abstract

An epigenetic change is a heritable genetic alteration that does not involve any nucleotide changes. While the methylation of specific DNA regions such as CpG islands or histone modifications, including acetylation or methylation, have been investigated in detail, the role of small RNAs in epigenetic regulation is largely unknown. Among the many types of small RNAs, tRNA-derived small RNAs (tsRNAs) represent a class of noncoding small RNAs with multiple roles in diverse physiological processes, including neovascularization, sperm maturation, immune modulation, and stress response. Regarding these roles, several pioneering studies have revealed that dysregulated tsRNAs are associated with human diseases, such as systemic lupus, neurological disorder, metabolic disorder, and cancer. Moreover, recent findings suggest that tsRNAs regulate the expression of critical genes linked with these diseases by a variety of mechanisms, including epigenetic regulation. In this review, we will describe different classes of tsRNAs based on their biogenesis and will focus on their role in epigenetic regulation.

snoRNA and piRNA expression levels modified by tobacco use in women with lung adenocarcinoma

Lung cancer is one of the most frequent types of cancer worldwide. Most patients are diagnosed at advanced stage and thus have poor prognosis. Smoking is a risk factor for lung cancer, however most smokers do not develop lung cancer while 20% of women with lung adenocarcinoma are non-smokers. Therefore, it is possible that these two groups present differences besides the smoking status, including differences in their gene expression signature. The altered expression patterns of non-coding RNAs in complex diseases make them potential biomarkers for diagnosis and treatment. We analyzed data from differentially and constitutively expressed PIWI-interacting RNAs and small nucleolar RNAs from publicly available small RNA high-throughput sequencing data in search of an expression pattern of non-coding RNA that could differentiate these two groups. Here, we report two sets of differentially expressed small non-coding RNAs identified in normal and tumoral tissues of women with lung adenocarcinoma, that discriminate between smokers and non-smokers. Our findings may offer new insights on metabolic alterations caused by tobacco and may be used for early diagnosis of lung cancer.

dbDEMC 2.0: updated database of differentially expressed miRNAs in human cancers

MicroRNAs (miRNAs) are often deregulated in cancer and are thought to play an important role in cancer development. Large amount of differentially expressed miRNAs have been identified in various cancers by using high-throughput methods. It is therefore quite important to make a comprehensive collection of these miRNAs and to decipher their roles in oncogenesis and tumor progression. In 2010, we presented the first release of dbDEMC, representing a database for collection of differentially expressed miRNAs in human cancers obtained from microarray data. Here we describe an update of the database. dbDEMC 2.0 documents 209 expression profiling data sets across 36 cancer types and 73 subtypes, and a total of 2224 differentially expressed miRNAs were identified. An easy-to-use web interface was constructed that allows users to make a quick search of the differentially expressed miRNAs in certain cancer types. In addition, a new function of ‘meta-profiling’ was added to view differential expression events according to user-defined miRNAs and cancer types. We expect this database to continue to serve as a valuable source for cancer investigation and potential clinical application related to miRNAs. dbDEMC 2.0 is freely available at http://www.picb.ac.cn/dbDEMC.

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.

In NMR tube transcription for rapid screening of RNA conformation

A simple method for rapid structure screening for RNA by NMR is proposed. Target RNA is transcribed in a NMR tube and its spectra are measured without purification. The proposed method, in NMR tube transcription or INTT, was applied for three RNAs for which NMR spectra have been measured by using the conventionally purified samples. By the real-time measuring, increase of imino proton signals and decrease of NTP signals can be observed. It was confirmed that INTT spectra are in general similar to those obtained by the conventional method. INTT can be used for the first-step screening of RNA folding.

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.

Recent developments in epigenetics of acute and chronic kidney diseases

The growing epidemic of obesity and diabetes, the aging population as well as prevalence of drug abuse has led to significant increases in the rates of the closely associated acute and chronic kidney diseases, including diabetic nephropathy. Furthermore, evidence shows that parental behavior and diet can affect the phenotype of subsequent generations via epigenetic transmission mechanisms. These data suggest a strong influence of the environment on disease susceptibility and that, apart from genetic susceptibility, epigenetic mechanisms need to be evaluated to gain critical new information about kidney diseases. Epigenetics is the study of processes that control gene expression and phenotype without alterations in the underlying DNA sequence. Epigenetic modifications, including cytosine DNA methylation and covalent post translational modifications of histones in chromatin are part of the epigenome, the interface between the stable genome and the variable environment. This dynamic epigenetic layer responds to external environmental cues to influence the expression of genes associated with disease states. The field of epigenetics has seen remarkable growth in the past few years with significant advances in basic biology, contributions to human disease, as well as epigenomics technologies. Further understanding of how the renal cell epigenome is altered by metabolic and other stimuli can yield novel new insights into the pathogenesis of kidney diseases. In this review, we have discussed the current knowledge on the role of epigenetic mechanisms (primarily DNA me and histone modifications) in acute and chronic kidney diseases, and their translational potential to identify much needed new therapies.

Next-generation sequencing and epigenomics research: a hammer in search of nails

After the initial enthusiasm of the human genome project, it became clear that without additional data pertaining to the epigenome, i.e., how the genome is marked at specific developmental periods, in different tissues, as well as across individuals and species-the promise of the genome sequencing project in understanding biology cannot be fulfilled. This realization prompted several large-scale efforts to map the epigenome, most notably the Encyclopedia of DNA Elements (ENCODE) project. While there is essentially a single genome in an individual, there are hundreds of epigenomes, corresponding to various types of epigenomic marks at different developmental times and in multiple tissue types. Unprecedented advances in next-generation sequencing (NGS) technologies, by virtue of low cost and high speeds that continue to improve at a rate beyond what is anticipated by Moore's law for computer hardware technologies, have revolutionized molecular biology and genetics research, and have in turn prompted innovative ways to reduce the problem of measuring cellular events involving DNA or RNA into a sequencing problem. In this article, we provide a brief overview of the epigenome, the various types of epigenomic data afforded by NGS, and some of the novel discoveries yielded by the epigenomics projects. We also provide ample references for the reader to get in-depth information on these topics.

Human cytomegalovirus latent infection alters the expression of cellular and viral microRNA

BACKGROUND

MicroRNAs (miRNAs) play important roles in regulating gene expression of plants, animals and viruses. Comprehensive characterization of host and viral miRNA will help uncover the molecular mechanisms that underlie the progression of human cytomegalovirus (HCMV) latent infection. To investigate the miRNA expression profile of HCMV and host cells during latent infection, we performed deep-sequencing analysis of the small RNAs isolated from HCMV-infected and mock-infected human monocytic leukemia cell line, THP-1.

RESULTS

We established a HCMV latent infection cell model using the THP-1 cells. High-throughput sequencing technology was used to sequence small RNA libraries of the HCMV-infected and mock-infected THP-1 and to investigate their small RNA transcriptomes. We found eight miRNAs including miR-US25-1, miR-US25-2-5p and miR-UL112 that were expressed by HCMV during latent infection. The expressions of the host miRNAs were also affected by HCMV latent infection. At least 49 cellular miRNAs were differentially expressed: 39 were up-regulated and 10 were down-regulated upon HCMV latent infection. The expression of the human miRNA hsa-miR-124-3p was significantly up-regulated in the HCMV latent infection library. In addition, we found 14 cellular novel miRNAs in the HCMV-infected and mock-infected THP-1 libraries. Functional annotation of the target genes of the differentially expressed miRNAs suggested that the majority of the genes are involved in melanogenesis, pathways in cancer, endocytosis and wnt signaling pathway.

CONCLUSIONS

The small RNA transcriptomes obtained in this study demonstrate the usefulness of the deep-sequencing combined with bioinformatics approach in understanding of the expression and function of host and viral small RNAs in HCMV latent infection. This approach can also be applied to the study of other kinds of viruses.

MicroRNAs as biomarkers for CNS disease

For many neurological diseases, the efficacy and outcome of treatment depend on early detection. Diagnosis is currently based on the detection of symptoms and neuroimaging abnormalities, which appear at relatively late stages in the pathogenesis. However, the underlying molecular responses to genetic and environmental insults begin much earlier and non-coding RNA networks are critically involved in these cellular regulatory mechanisms. Profiling RNA expression patterns could thus facilitate presymptomatic disease detection. Obtaining indirect readouts of pathological processes is particularly important for brain disorders because of the lack of direct access to tissue for molecular analyses. Living neurons and other CNS cells secrete microRNA and other small non-coding RNA into the extracellular space packaged in exosomes, microvesicles, or lipoprotein complexes. This discovery, together with the rapidly evolving massive sequencing technologies that allow detection of virtually all RNA species from small amounts of biological material, has allowed significant progress in the use of extracellular RNA as a biomarker for CNS malignancies, neurological, and psychiatric diseases. There is also recent evidence that the interactions between external stimuli and brain pathological processes may be reflected in peripheral tissues, facilitating their use as potential diagnostic markers. In this review, we explore the possibilities and challenges of using microRNA and other small RNAs as a signature for neurodegenerative and other neuropsychatric conditions.

mirTools 2.0 for non-coding RNA discovery, profiling, and functional annotation based on high-throughput sequencing

Next-generation sequencing has been widely applied to understand the complexity of non-coding RNAs (ncRNAs) in a cost-effective way. In this study, we developed mirTools 2.0, an updated version of mirTools 1.0, which includes the following new features. (1) From miRNA discovery in mirTools 1.0, mirTools 2.0 allows users to detect and profile various types of ncRNAs, such as miRNA, tRNA, snRNA, snoRNA, rRNA, and piRNA. (2) From miRNA profiling in mirTools 1.0, mirTools 2.0 allows users to identify miRNA-targeted genes and performs detailed functional annotation of miRNA targets, including Gene Ontology, KEGG pathway and protein-protein interaction. (3) From comparison of two samples for differentially expressed miRNAs in mirTools 1.0, mirTools 2.0 allows users to detect differentially expressed ncRNAs between two experimental groups or among multiple samples. (4) Other significant improvements include strategies used to detect novel miRNAs and piRNAs, more taxonomy categories to discover more known miRNAs and a stand-alone version of mirTools 2.0. In conclusion, we believe that mirTools 2.0 (122.228.158.106/mr2_dev and centre.bioinformatics.zj.cn/mr2_dev) will provide researchers with more detailed insight into small RNA transcriptomes.

A user-friendly chromatographic method to purify small regulatory RNAs

The discovery of the small regulatory RNAs has changed our vision of cellular regulations. Indeed, when loaded on Argonaute proteins they form ribonucleoprotein complexes (RNPs) that target complementary sequences to achieve widespread silencing mechanisms conserved in most eukaryotes. The recent development of deep sequencing approaches highly contributed to their detection. Small RNA isolation from cells and/or tissues remains a crucial stage to generate robust and relevant sequencing data. In 2006, a novel strategy based on anion-exchange chromatography has been proposed as an alternative to the standard size-isolation purification procedure. Using bioinformatic comparative analysis, we here demonstrate that anion-exchange chromatographic RNP purification prior to small RNA extraction unbiasedly enriches datasets in bona fide reads (small regulatory RNA sequences) and depletes endogenous contaminants (ribosomal RNAs and degradation RNA products). The resulting increase in sequencing depth provides a major benefit to study rare populations. We then developed a fast and basic manual procedure to purify such small non-coding RNAs using anion-exchange chromatography at the bench. We validated the efficiency of this new method and used this strategy to purify small RNAs from various tissues and organisms. We moreover determined that our manual purification increases the output of the previously described anion-exchange chromatography procedure.

MicroRNAs and their cross-talks in plant development

Plant development is a complex process influenced by exogenous and endogenous elements. A series of postembryonic developmental events is involved to form the final architecture and contend with the changing environment. MicroRNA (miRNA) is one of endogenous non-coding RNAs, which plays an important role in plant developmental regulation. In this review, we summarized 34 miRNA families that are closely associated with plant development. Among these families, nine are expressed only in specific organs, whereas 20 families are expressed in at least two different organs. It is known that some miRNAs are expressed across most processes of plant growth, while some appear only at particular developmental stages or under special environmental conditions such as drought, waterlogging and short-day time. These miRNAs execute their diverse functions by regulating developmental gene expression levels, interacting with phytohormone signaling response, participating in the biogenesis of ta-siRNAs and affecting the production of miRNAs.

Rat mir-155 generated from the lncRNA Bic is 'hidden' in the alternate genomic assembly and reveals the existence of novel mammalian miRNAs and clusters

MicroRNAs (miRNAs) are a class of small noncoding RNAs acting as post-transcriptional gene expression regulators in many physiological and pathological conditions. During the last few years, many novel mammalian miRNAs have been predicted experimentally with bioinformatics approaches and validated by next-generation sequencing. Although these strategies have prompted the discovery of several miRNAs, the total number of these genes still seems larger. Here, by exploiting the species conservation of human, mouse, and rat hairpin miRNAs, we discovered a novel rat microRNA, mir-155. We found that mature miR-155 is overexpressed in rat spleen myeloid cells treated with LPS, similarly to humans and mice. Rat mir-155 is annotated only on the alternate genome, suggesting the presence of other "hidden" miRNAs on this assembly. Therefore, we comprehensively extended the homology search also to mice and humans, finally validating 34 novel mammalian miRNAs (two in humans, five in mice, and up to 27 in rats). Surprisingly, 15 of these novel miRNAs (one for mice and 14 for rats) were found only on the alternate and not on the reference genomic assembly. To date, our findings indicate that the choice of genomic assembly, when mapping small RNA reads, is an important option that should be carefully considered, at least for these animal models. Finally, the discovery of these novel mammalian miRNA genes may contribute to a better understanding of already acquired experimental data, thereby paving the way to still unexplored investigations and to unraveling the function of miRNAs in disease models.

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.

YM500: a small RNA sequencing (smRNA-seq) database for microRNA research

MicroRNAs (miRNAs) are small RNAs ∼22 nt in length that are involved in the regulation of a variety of physiological and pathological processes. Advances in high-throughput small RNA sequencing (smRNA-seq), one of the next-generation sequencing applications, have reshaped the miRNA research landscape. In this study, we established an integrative database, the YM500 (http://ngs.ym.edu.tw/ym500/), containing analysis pipelines and analysis results for 609 human and mice smRNA-seq results, including public data from the Gene Expression Omnibus (GEO) and some private sources. YM500 collects analysis results for miRNA quantification, for isomiR identification (incl. RNA editing), for arm switching discovery, and, more importantly, for novel miRNA predictions. Wetlab validation on >100 miRNAs confirmed high correlation between miRNA profiling and RT-qPCR results (R = 0.84). This database allows researchers to search these four different types of analysis results via our interactive web interface. YM500 allows researchers to define the criteria of isomiRs, and also integrates the information of dbSNP to help researchers distinguish isomiRs from SNPs. A user-friendly interface is provided to integrate miRNA-related information and existing evidence from hundreds of sequencing datasets. The identified novel miRNAs and isomiRs hold the potential for both basic research and biotech applications.

The success of pharmacogenomics in moving genetic association studies from bench to bedside: study design and implementation of precision medicine in the post-GWAS era

Pharmacogenomics is emerging as a popular type of study for human genetics in recent years. This is primarily due to the many success stories and high potential for translation to clinical practice. In this review, the strengths and limitations of pharmacogenomics are discussed as well as the primary epidemiologic, clinical trial, and in vitro study designs implemented. A brief discussion of molecular and analytic approaches will be reviewed. Finally, several examples of bench-to-bedside clinical implementations of pharmacogenetic traits will be described. Pharmacogenomics continues to grow in popularity because of the important genetic associations identified that drive the possibility of precision medicine.

CPSS: a computational platform for the analysis of small RNA deep sequencing data

Next generation sequencing (NGS) techniques have been widely used to document the small ribonucleic acids (RNAs) implicated in a variety of biological, physiological and pathological processes. An integrated computational tool is needed for handling and analysing the enormous datasets from small RNA deep sequencing approach. Herein, we present a novel web server, CPSS (a computational platform for the analysis of small RNA deep sequencing data), designed to completely annotate and functionally analyse microRNAs (miRNAs) from NGS data on one platform with a single data submission. Small RNA NGS data can be submitted to this server with analysis results being returned in two parts: (i) annotation analysis, which provides the most comprehensive analysis for small RNA transcriptome, including length distribution and genome mapping of sequencing reads, small RNA quantification, prediction of novel miRNAs, identification of differentially expressed miRNAs, piwi-interacting RNAs and other non-coding small RNAs between paired samples and detection of miRNA editing and modifications and (ii) functional analysis, including prediction of miRNA targeted genes by multiple tools, enrichment of gene ontology terms, signalling pathway involvement and protein-protein interaction analysis for the predicted genes. CPSS, a ready-to-use web server that integrates most functions of currently available bioinformatics tools, provides all the information wanted by the majority of users from small RNA deep sequencing datasets.

AVAILABILITY

CPSS is implemented in PHP/PERL+MySQL+R and can be freely accessed at http://mcg.ustc.edu.cn/db/cpss/index.html or http://mcg.ustc.edu.cn/sdap1/cpss/index.html.