Computational Prediction of miRNA Genes from Small RNA Sequencing Data

Description Generation Using Variational Auto-Encoders for Precursor microRNA

Micro RNAs (miRNA) are a type of non-coding RNA involved in gene regulation and can be associated with diseases such as cancer, cardiovascular, and neurological diseases. As such, identifying the entire genome of miRNA can be of great relevance. Since experimental methods for novel precursor miRNA (pre-miRNA) detection are complex and expensive, computational detection using Machine Learning (ML) could be useful. Existing ML methods are often complex black boxes that do not create an interpretable structural description of pre-miRNA. In this paper, we propose a novel framework that makes use of generative modeling through Variational Auto-Encoders to uncover the generative factors of pre-miRNA. After training the VAE, the pre-miRNA description is developed using a decision tree on the lower dimensional latent space. Applying the framework to miRNA classification, we obtain a high reconstruction and classification performance while also developing an accurate miRNA description.

Bladder cancer: non-coding RNAs and exosomal non-coding RNAs

Bladder cancer (BCa) is a highly prevalent type of cancer worldwide, and it is responsible for numerous deaths and cases of disease. Due to the diverse nature of this disease, it is necessary to conduct significant research that delves deeper into the molecular aspects, to potentially discover novel diagnostic and therapeutic approaches. Lately, there has been a significant increase in the focus on non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), due to their growing recognition for their involvement in the progression and manifestation of BCa. The interest in exosomes has greatly grown due to their potential for transporting a diverse array of active substances, including proteins, nucleic acids, carbohydrates, and lipids. The combination of these components differs based on the specific cell and its condition. Research indicates that using exosomes could have considerable advantages in identifying and forecasting BCa, offering a less invasive alternative. The distinctive arrangement of the lipid bilayer membrane found in exosomes is what makes them particularly effective for administering treatments aimed at managing cancer. In this review, we have tried to summarize different ncRNAs that are involved in BCa pathogenesis. Moreover, we highlighted the role of exosomal ncRNAs in BCa.

Distinct small RNAs are expressed at different stages of Phytophthora capsici and play important roles in development and pathogenesis

Small RNAs (sRNAs) are important non-coding RNA regulators that play key roles in the development and pathogenesis of plant pathogens, as well as in other biological processes. However, whether these abundant and varying sRNAs are involved in Phytophthora development or infection remains enigmatic. In this study, sRNA sequencing of 4 asexual stages of Phytophthora capsici (P. capsici), namely, as mycelia (HY), sporangia (SP), zoospores (ZO), cysts (CY), and pepper infected with P. capsici (IN), were performed, followed by sRNA analysis, microRNA (miRNA) identification, and miRNA target prediction. sRNAs were mainly distributed at 25-26 nt in HY, SP, and ZO but distributed at 18-34 nt in CY and IN. 92, 42, 176, 39, and 148 known miRNAs and 15, 19, 54, 13, and 1 novel miRNA were identified in HY, SP, ZO, CY, and IN, respectively. It was found that the expression profiles of known miRNAs vary greatly at different stages and could be divided into 4 categories. Novel miRNAs mostly belong to part I. Gene ontology (GO) analysis of known miRNA-targeting genes showed that they are involved in the catalytic activity pathway, binding function, and other biological processes. Kyoto Encyclopedia of Gene and Genome (KEGG) analysis of novel miRNA-targeting genes showed that they are involved in the lysine degradation pathway. The expression of candidate miRNAs was validated using quantitative reverse transcription-polymerase chain reaction (qRT-PCR), and miRNAs were downregulated in PcDCL1 or PcAGO1 mutants. To further explore the function of the detected miRNAs, the precursor of a novel miRNA, miR91, was knockout by CRISPR-Cas9, the mutants displayed decreased mycelial growth, sporangia production, and zoospore production. It was found that 503142 (Inositol polyphosphate 5-phosphatase and related proteins) can be predicted as a target of miR91, and the interaction between miR91 and 503142 was verified using the tobacco transient expression system. Overall, our results indicate that the diverse and differentially expressed sRNAs are involved in the development and pathogenesis of P. capsici.

Degradome Assisted Plant MicroRNA Prediction Under Alternative Annotation Criteria

Current microRNA (miRNA) prediction methods are generally based on annotation criteria that tend to miss potential functional miRNAs. Recently, new miRNA annotation criteria have been proposed that could lead to improvements in miRNA prediction methods in plants. Here, we investigate the effect of the new criteria on miRNA prediction in Arabidopsis thaliana and present a new degradome assisted functional miRNA prediction approach. We investigated the effect by applying the new criteria, and a more permissive criteria on miRNA prediction using existing miRNA prediction tools. We also developed an approach to miRNA prediction that is assisted by the functional information extracted from the analysis of degradome sequencing. We demonstrate the improved performance of degradome assisted miRNA prediction compared to unassisted prediction and evaluate the approach using miRNA differential expression analysis. We observe how the miRNA predictions fit under the different criteria and show a potential novel miRNA that has been missed within Arabidopsis thaliana. Additionally, we introduce a freely available software 'PAREfirst' that employs the degradome assisted approach. The study shows that some miRNAs could be missed due to the stringency of the former annotation criteria, and combining a degradome assisted approach with more permissive miRNA criteria can expand confident miRNA predictions.

Analysis of circulating microRNA during early gestation in Japanese black cattle

Circulating microRNAs (miRNAs) have been used as biomarkers for various diseases and physiological conditions in humans and mice; studies in domestic animals, particularly cattle, are limited. The importance of early pregnancy diagnosis (especially within the 21-d cow estrous cycle) in the livestock industry is extremely high. This study compared the circulating miRNAs in bred non-pregnant and pregnant Japanese Black cows, explored miRNAs as biomarkers for early pregnancy diagnosis, and established a measurement system that included selecting an appropriate reference miRNA and determining the effect of hemolysis on miRNA quantification in plasma. miRNA was extracted from the plasma of Japanese Black cows on day 21 after artificial insemination and subjected to a customized bovine oligonucleotide microarray for expression analysis. Differentially expressed miRNAs and reference miRNA candidates were selected and validated using reverse transcription-quantitative PCR (RT-qPCR). An appropriate endogenous reference miRNA for normalization was selected using NormFinder software. To evaluate the effect of hemolysis on miRNA quantification, hemolyzed samples were prepared using plasma from four cows in the estrous cycle and subjected to RT-qPCR. A total of 124 miRNAs were detected in bovine plasma by microarray analysis in bred non-pregnant and pregnant cows. The levels of five circulating miRNAs were significantly higher in pregnant cows than in bred non-pregnant cows, and 24 miRNAs were detected only in the pregnant group. NormFinder analysis and RT-qPCR validation showed that miR-2455 was an appropriate reference miRNA in the plasma of bred non-pregnant and pregnant Japanese Black cows, and miR-19b, miR-25, miR-29a, and miR-148a were significantly higher in the pregnant group. These four circulating miRNAs did not change during the estrous cycle and were less affected by hemolysis. In the current study, we found four miRNAs, miR-19b, miR-25, miR-29a, and miR-148a, which were present at high levels in the plasma of pregnant Japanese Black cows. Since these miRNAs are less affected by hemolysis, they may potentially be used as biomarkers for early pregnancy diagnosis in cattle.

MicroRNA and Hemophilia-A Disease: Bioinformatics Prediction and Experimental Analysis

Objective

Hemophilia-A is a common genetic abnormality resulted from decreased or lack of factor VIII (FVIII) pro-coagulant protein function caused by mutations in the F8 gene. Majority of molecular studies consider screening of mutations and their relevant impacts on the quality and expression levels of FVIII. Interestingly, some of the functions in FVIII suggest a probable involvement of small non-coding RNAs embedded within the sequence of F8 gene. Therefore, microRNAs which are encoded within the F8 gene might have a role in hemophilia development. In this study, miRNAs production in the F8 gene was investigated by bioinformatics prediction and experimental validation.

Materials and Methods

In this experimental study, bioinformatics tools have been utilized to seek the novel microRNAs inserted within human F8 gene. The ability to express new microRNAs in F8 locus was studied through reliable bioinformatics databases such as SSCProfiler, RNA fold, miREval, miR-FIND, UCSC genome browser and miRBase. Then, expression and processing of the predicted microRNAs were examined based on bioinformatics methods, in the HEK293 cell lines.

Results

We are unable to confirm existence of the considered mature microRNAs in the transfected cells.

Conclusion

We hope that through changing experimental conditions, designing new primers or altering cell lines as well as the expression of vectors, exogenous and endogenous expressions of the predicted miRNA will be confirmed.

Filtering the Junk: Assigning Function to the Mosquito Non-Coding Genome

The portion of the mosquito genome that does not code for proteins contains regulatory elements that likely underlie variation for important phenotypes including resistance and susceptibility to infection with arboviruses and Apicomplexan parasites. Filtering the non-coding genome to uncover these functional elements is an expanding area of research, though identification of non-coding regulatory elements is challenging due to the lack of an amino acid-like code for the non-coding genome and a lack of sequence conservation across species. This review focuses on three types of non-coding regulatory elements: (1) microRNAs (miRNAs), (2) long non-coding RNAs (lncRNAs), and (3) enhancers, and summarizes current advances in technical and analytical approaches for measurement of each of these elements on a genome-wide scale. The review also summarizes and highlights novel findings following application of these techniques in mosquito-borne disease research. Looking beyond the protein-coding genome is essential for understanding the complexities that underlie differential gene expression in response to arboviral or parasite infection in mosquito disease vectors. A comprehensive understanding of the regulation of gene and protein expression will inform transgenic and other vector control methods rooted in naturally segregating genetic variation.

MicroRNAs and target molecules in bladder cancer

Bladder cancer (BC) is considered as one of the most common malignant tumors in humans with complex pathogenesis including gene expression variation, protein degradation, and changes in signaling pathways. Many studies on involved miRNAs in BC have demonstrated that they could be used as potential biomarkers in the prognosis, response to treatment, and screening before the cancerous phenotype onset. MicroRNAs (miRNAs) regulate many cellular processes through their different effects on special targets along with modifying signaling pathways, apoptosis, cell growth, and differentiation. The diverse expression of miRNAs in cancerous tissues could mediate procedures leading to the oncogenic or suppressor behavior of certain genes in cancer cells. Since a specific miRNA may have multiple targets, an mRNA could also be regulated by multiple miRNAs which further demonstrates the actual role of miRNAs in cancer. In addition, miRNAs can be utilized as biomarkers in some cancers that cannot be screened in the early stages. Hence, finding blood, urine, or tissue miRNA biomarkers by novel or routine gene expression method could be an essential step in the prognosis and control of cancer. In the present review, we have thoroughly evaluated the recent findings on different miRNAs in BC which can provide comprehensive information on better understanding the role of diverse miRNAs and better decision making regarding the new approaches in the diagnosis, prognosis, prevention, and treatment of BC.

Popular Computational Tools Used for miRNA Prediction and Their Future Development Prospects

MicroRNAs (miRNAs) are 19-24 nucleotide (nt)-long noncoding, single-stranded RNA molecules that play significant roles in regulating the gene expression, growth, and development of plants and animals. From the year that miRNAs were first discovered until the beginning of the twenty-first century, researchers used experimental methods such as cloning and sequencing to identify new miRNAs and their roles in the posttranscriptional regulation of protein synthesis. Later, in the early 2000s, informatics approaches to the discovery of new miRNAs began to be implemented. With increasing knowledge about miRNA, more efficient algorithms have been developed for computational miRNA prediction. The miRNA research community, hoping for greater coverage and faster results, has shifted from cumbersome and expensive traditional experimental approaches to computational approaches. These computational methods started with homology-based comparisons of known miRNAs with orthologs in the genomes of other species; this method could identify a known miRNA in new species. Second-generation sequencing and next-generation sequencing of mRNA at different developmental stages and in specific tissues, in combination with a better search and alignment algorithm, have accelerated the process of predicting novel miRNAs in a particular species. Using the accumulated annotated miRNA sequence information, researchers have been able to design ab initio algorithms for miRNA prediction independent of genome sequence knowledge. Here, the methods recently used for miRNA computational prediction are summarized and classified into the following four categories: homology-based, target-based, scoring-based, and machine-learning-based approaches. Finally, the future developmental directions of miRNA prediction methods are discussed.

Elucidating the Functional Role of Predicted miRNAs in Post- Transcriptional Gene Regulation Along with Symbiosis in Medicago truncatula

Background:

microRNAs are small non-coding RNAs which inhibit translational and post-transcriptional processes whereas long non-coding RNAs are found to regulate both transcriptional and post-transcriptional gene expression. Medicago truncatula is a well-known model plant for studying legume biology and is also used as a forage crop. In spite of its importance in nitrogen fixation and soil fertility improvement, little information is available about Medicago non-coding RNAs that play important role in symbiosis.

Objective:

In this study we have tried to understand the role of Medicago ncRNAs in symbiosis and regulation of transcription factors.

Methods:

We have identified novel miRNAs by computational methods considering various parameters like length, MFEI, AU content, SSR signatures and tried to establish an interaction model with their targets obtained through psRNATarget server.

Results:

149 novel miRNAs are predicted along with their 770 target proteins. We have also shown that 51 of these novel miRNAs are targeting 282 lncRNAs.

Conclusion:

In this study role of Medicago miRNAs in the regulation of various transcription factors are elucidated. Knowledge gained from this study will have a positive impact on the nitrogen fixing ability of this important model plant, which in turn will improve the soil fertility.

Identification, Prediction and Data Analysis of Noncoding RNAs: A Review

BACKGROUND

Noncoding RNAs (ncRNAs) which play an important role in various cellular processes are important in medicine as well as in drug design strategies. Different studies have shown that ncRNAs are dis-regulated in cancer cells and play an important role in human tumorigenesis. Therefore, it is important to identify and predict such molecules by experimental and computational methods, respectively. However, to avoid expensive experimental methods, computational algorithms have been developed for accurately and fast prediction of ncRNAs.

OBJECTIVE

The aim of this review was to introduce the experimental and computational methods to identify and predict ncRNAs structure. Also, we explained the ncRNA's roles in cellular processes and drugs design, briefly.

METHOD

In this survey, we will introduce ncRNAs and their roles in biological and medicinal processes. Then, some important laboratory techniques will be studied to identify ncRNAs. Finally, the state-of-the-art models and algorithms will be introduced along with important tools and databases.

RESULTS

The results showed that the integration of experimental and computational approaches improves to identify ncRNAs. Moreover, the high accurate databases, algorithms and tools were compared to predict the ncRNAs.

CONCLUSION

ncRNAs prediction is an exciting research field, but there are different difficulties. It requires accurate and reliable algorithms and tools. Also, it should be mentioned that computational costs of such algorithm including running time and usage memory are very important. Finally, some suggestions were presented to improve computational methods of ncRNAs gene and structural prediction.

Investigating miRNA-lncRNA Interactions: Computational Tools and Resources

In the last two decades noncoding RNAs have been the recipients of increasing scientific interest. In particular, miRNAs, short (~22 nts) noncoding transcripts, have been thoroughly investigated since their essential role in posttranscriptional gene expression regulation had been established in the early 2000s. With the advent and the advancements of high-throughput sequencing technologies in recent years, long noncoding RNAs have also started to emerge as important actors in cellular functions and processes. Such transcripts, on average longer than 200 nt, whose functions have yet to be fully characterized, have recently been identified as regulatory elements of the RNAi pathway, harboring several miRNA response elements, uncovering the phenomena of competing endogenous RNAs (ceRNAs), or "sponge RNAs." The present chapter aims to provide a brief update on the actual biomedical relevance of ceRNAs, together with a summary of resources, tools, and practical examples of their application to aid researchers in the discovery and further elucidation of lncRNA-miRNA interactions.

Small RNA-Seq reveals novel miRNAs shaping the transcriptomic identity of rat brain structures

Small RNA-Seq of the rat central nervous system reveals known and novel miRNAs specifically regulated in brain structures and correlated with the expression of their predicted target genes, suggesting a critical role in the transcriptomic identity of brain structures.

In the central nervous system (CNS), miRNAs are involved in key functions, such as neurogenesis and synaptic plasticity. Moreover, they are essential to define specific transcriptomes in tissues and cells. However, few studies were performed to determine the miRNome of the different structures of the rat CNS, although a major model in neuroscience. Here, we determined by small RNA-Seq, the miRNome of the olfactory bulb, the hippocampus, the cortex, the striatum, and the spinal cord and showed the expression of 365 known miRNAs and 90 novel miRNAs. Differential expression analysis showed that several miRNAs were specifically enriched/depleted in these CNS structures. Transcriptome analysis by mRNA-Seq and correlation based on miRNA target predictions suggest that the specifically enriched/depleted miRNAs have a strong impact on the transcriptomic identity of the CNS structures. Altogether, these results suggest the critical role played by these enriched/depleted miRNAs, in particular the novel miRNAs, in the functional identities of CNS structures.

miRmine: a database of human miRNA expression profiles

Motivation

MicroRNAs (miRNAs) are small non-coding RNAs that are involved in post-transcriptional regulation of gene expression. In this high-throughput sequencing era, a tremendous amount of RNA-seq data is accumulating, and full utilization of publicly available miRNA data is an important challenge. These data are useful to determine expression values for each miRNA, but quantification pipelines are in a primitive stage and still evolving; there are many factors that affect expression values significantly.

Results

We used 304 high-quality microRNA sequencing (miRNA-seq) datasets from NCBI-SRA and calculated expression profiles for different tissues and cell-lines. In each miRNA-seq dataset, we found an average of more than 500 miRNAs with higher than 5x coverage, and we explored the top five highly expressed miRNAs in each tissue and cell-line. This user-friendly miRmine database has options to retrieve expression profiles of single or multiple miRNAs for a specific tissue or cell-line, either normal or with disease information. Results can be displayed in multiple interactive, graphical and downloadable formats.

Availability and Implementation

http://guanlab.ccmb.med.umich.edu/mirmine.

Contact

bharatpa@umich.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

FLI1 and PKC co-activation promote highly efficient differentiation of human embryonic stem cells into endothelial-like cells

Rationale-endothelial cells (ECs) play important roles in various regeneration processes and can be used in a variety of therapeutic applications, such as cardiac regeneration, gene therapy, tissue-engineered vascular grafts and prevascularized tissue transplants. ECs can be acquired from pluripotent and adult stem cells. To acquire ECs from human embryonic stem cells (hESCs) in a fast, efficient and economic manner. We established a conditional overexpression system in hESCs based on 15 transcription factors reported to be responsible for hematopoiesis lineage. Among them, only overexpression of FLI1 could induce hESCs to a hematopoietic lineage. Moreover, simultaneous overexpression of FLI1 and activation of PKC rapidly and efficiently induced differentiation of hESCs into induced endothelial cells (iECs) within 3 days, while neither FLI1 overexpression nor PKC activation alone could derive iECs from hESCs. During induction, hESCs differentiated into spindle-like cells that were consistent in appearance with ECs. Flow cytometric analysis revealed that 92.2-98.9% and 87.2-92.6% of these cells were CD31+ and CD144+, respectively. Expression of vascular-specific genes dramatically increased, while the expression of pluripotency genes gradually decreased during induction. iECs incorporated acetylated low-density lipoproteins, strongly expressed vWF and bound UEA-1. iECs also formed capillary-like structures both in vitro and in vivo. RNA-seq analysis verified that these cells closely resembled their in vivo counterparts. Our results showed that co-activation of FLI1 and PKC could induce differentiation of hESCs into iECs in a fast, efficient and economic manner.

Detecting Agotrons in Ago CLIPseq Data

Timely and accurate regulation of gene expression is essential to all organisms. MicroRNAs (miRNAs) are a well-characterized and important class of gene expression regulators. We recently identified a novel class of gene regulators, the agotrons. Agotrons derive from short introns and associate with Argonaute (Ago) proteins much similar to miRNAs. However, agotrons completely bypass the conventional miRNA biogenesis pathway and thus exist as full-length introns, which disobey the classical rules on Ago-substrate requirements. As a class, agotrons are conserved in mammals, and despite the non-canonical biogenesis pathway, agotrons maintain the ability to deregulate mRNAs with seed-matches in the 3'UTR. While several pipelines exist for the detection of miRNAs, no bioinformatics toolkit has yet been developed to specifically identify agotrons. Here, we describe a simple approach, termed agotron_detector ( https://github.com/ncrnalab/agotron_detector ), to identify and quantify agotrons in Ago CLIPseq datasets. Hopefully, this allows researchers worldwide to characterize agotrons in more detail and to reveal the biological relevance of these fascinating RNA species.

Small RNA Sequencing: A Technique for miRNA Profiling

Identifying microRNA (miRNA) signatures in animal tissues is an essential first step in studies assessing post-transcriptional regulation of gene expression in health or disease. Small RNA sequencing (sRNA-Seq) is a next-generation sequencing-based technology that is currently considered the most powerful and versatile tool for miRNA profiling. Here, we describe a sRNA-Seq protocol including RNA purification from mammalian tissues, library preparation, and raw data analysis.

A comprehensive, cell specific microRNA catalogue of human peripheral blood

With this study, we provide a comprehensive reference dataset of detailed miRNA expression profiles from seven types of human peripheral blood cells (NK cells, B lymphocytes, cytotoxic T lymphocytes, T helper cells, monocytes, neutrophils and erythrocytes), serum, exosomes and whole blood. The peripheral blood cells from buffy coats were typed and sorted using FACS/MACS. The overall dataset was generated from 450 small RNA libraries using high-throughput sequencing. By employing a comprehensive bioinformatics and statistical analysis, we show that 3′ trimming modifications as well as composition of 3′ added non-templated nucleotides are distributed in a lineage-specific manner—the closer the hematopoietic progenitors are, the higher their similarities in sequence variation of the 3′ end. Furthermore, we define the blood cell-specific miRNA and isomiR expression patterns and identify novel cell type specific miRNA candidates. The study provides the most comprehensive contribution to date towards a complete miRNA catalogue of human peripheral blood, which can be used as a reference for future studies. The dataset has been deposited in GEO and also can be explored interactively following this link: http://134.245.63.235/ikmb-tools/bloodmiRs.

miRCat2: accurate prediction of plant and animal microRNAs from next-generation sequencing datasets

MOTIVATION

MicroRNAs are a class of ∼21-22 nt small RNAs which are excised from a stable hairpin-like secondary structure. They have important gene regulatory functions and are involved in many pathways including developmental timing, organogenesis and development in eukaryotes. There are several computational tools for miRNA detection from next-generation sequencing datasets. However, many of these tools suffer from high false positive and false negative rates. Here we present a novel miRNA prediction algorithm, miRCat2. miRCat2 incorporates a new entropy-based approach to detect miRNA loci, which is designed to cope with the high sequencing depth of current next-generation sequencing datasets. It has a user-friendly interface and produces graphical representations of the hairpin structure and plots depicting the alignment of sequences on the secondary structure.

RESULTS

We test miRCat2 on a number of animal and plant datasets and present a comparative analysis with miRCat, miRDeep2, miRPlant and miReap. We also use mutants in the miRNA biogenesis pathway to evaluate the predictions of these tools. Results indicate that miRCat2 has an improved accuracy compared with other methods tested. Moreover, miRCat2 predicts several new miRNAs that are differentially expressed in wild-type versus mutants in the miRNA biogenesis pathway.

AVAILABILITY AND IMPLEMENTATION

miRCat2 is part of the UEA small RNA Workbench and is freely available from http://srna-workbench.cmp.uea.ac.uk/.

CONTACT

v.moulton@uea.ac.uk or s.moxon@uea.ac.uk.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

SMARTER De-Stressed Cereal Breeding

In cereal breeding programs, improved yield potential and stability are ultimate goals when developing new varieties. To facilitate achieving these goals, reproductive success under stressful growing conditions is of the highest priority. In recent times, small RNA (sRNA)-mediated pathways have been associated with the regulation of genes involved in stress adaptation and reproduction in both model plants and several cereals. Reproductive and physiological traits such as flowering time, reproductive branching, and root architecture can be manipulated by sRNA regulatory modules. We review sRNA-mediated pathways that could be exploited to expand crop diversity with adaptive traits and, in particular, the development of high-yielding stress-tolerant cereals: SMARTER cereal breeding through 'Small RNA-Mediated Adaptation of Reproductive Targets in Epigenetic Regulation'.

Investigating miRNA-mRNA regulatory networks using crosslinking immunoprecipitation methods for biomarker and target discovery in cancer

INTRODUCTION

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression at the post-transcriptional level. Recently, different experimental approaches, such as RNA Sequencing, crosslinking immunoprecipitation (CLIP) methods and its variations, together with computational approaches have been developed to elucidate the miRNA-mRNA targetome. Areas covered: This report focuses on comparing the different experimental and computational approaches, describing their advantages and disadvantages and providing several examples of preclinical (in vitro and in vivo) and clinical studies that have identified miRNA target genes in various tumour types, including breast, ovary, colorectal and pancreas. Expert commentary: The combination of CLIP methods with bioinformatic analyses is essential to better predict miRNA-mRNA interactions and associate their specific pathways within the extensive regulatory network. Nevertheless, further studies are needed to overcome the difficulties these methods have, in order to find a gold standard method that identifies, without any bias, the regulatory association between miRNAs and their target mRNAs.

Novel microRNA discovery using small RNA sequencing in post-mortem human brain

BACKGROUND

MicroRNAs (miRNAs) are short, non-coding RNAs that regulate gene expression mainly through translational repression of target mRNA molecules. More than 2700 human miRNAs have been identified and some are known to be associated with disease phenotypes and to display tissue-specific patterns of expression.

METHODS

We used high-throughput small RNA sequencing to discover novel miRNAs in 93 human post-mortem prefrontal cortex samples from individuals with Huntington's disease (n = 28) or Parkinson's disease (n = 29) and controls without neurological impairment (n = 36). A custom miRNA identification analysis pipeline was built, which utilizes miRDeep* miRNA identification and result filtering based on false positive rate estimates.

RESULTS

Ninety-nine novel miRNA candidates with a false positive rate of less than 5 % were identified. Thirty-four of the candidate miRNAs show sequence similarity with known mature miRNA sequences and may be novel members of known miRNA families, while the remaining 65 may constitute previously undiscovered families of miRNAs. Nineteen of the 99 candidate miRNAs were replicated using independent, publicly-available human brain RNA-sequencing samples, and seven were experimentally validated using qPCR.

CONCLUSIONS

We have used small RNA sequencing to identify 99 putative novel miRNAs that are present in human brain samples.

Tools4miRs - one place to gather all the tools for miRNA analysis

Summary: MiRNAs are short, non-coding molecules that negatively regulate gene expression and thereby play several important roles in living organisms. Dozens of computational methods for miRNA-related research have been developed, which greatly differ in various aspects. The substantial availability of difficult-to-compare approaches makes it challenging for the user to select a proper tool and prompts the need for a solution that will collect and categorize all the methods. Here, we present tools4miRs, the first platform that gathers currently more than 160 methods for broadly defined miRNA analysis. The collected tools are classified into several general and more detailed categories in which the users can additionally filter the available methods according to their specific research needs, capabilities and preferences. Tools4miRs is also a web-based target prediction meta-server that incorporates user-designated target prediction methods into the analysis of user-provided data.

Availability and Implementation: Tools4miRs is implemented in Python using Django and is freely available at tools4mirs.org.

Contact: piotr@ibb.waw.pl

Supplementary information:Supplementary data are available at Bioinformatics online.

A Comprehensive Prescription for Plant miRNA Identification

microRNAs (miRNAs) are tiny ribo-regulatory molecules involved in various essential pathways for persistence of cellular life, such as development, environmental adaptation, and stress response. In recent years, miRNAs have become a major focus in molecular biology because of their functional and diagnostic importance. This interest in miRNA research has resulted in the development of many specific software and pipelines for the identification of miRNAs and their specific targets, which is the key for the elucidation of miRNA-modulated gene expression. While the well-recognized importance of miRNAs in clinical research pushed the emergence of many useful computational identification approaches in animals, available software and pipelines are fewer for plants. Additionally, existing approaches suffers from mis-identification and annotation of plant miRNAs since the miRNA mining process for plants is highly prone to false-positives, particularly in cereals which have a highly repetitive genome. Our group developed a homology-based in silico miRNA identification approach for plants, which utilizes two Perl scripts "SUmirFind" and "SUmirFold" and since then, this method helped identify many miRNAs particularly from crop species such as Triticum or Aegliops. Herein, we describe a comprehensive updated guideline by the implementation of two new scripts, "SUmirPredictor" and "SUmirLocator," and refinements to our previous method in order to identify genuine miRNAs with increased sensitivity in consideration of miRNA identification problems in plants. Recent updates enable our method to provide more reliable and precise results in an automated fashion in addition to solutions for elimination of most false-positive predictions, miRNA naming and miRNA mis-annotation. It also provides a comprehensive view to genome/transcriptome-wide location of miRNA precursors as well as their association with transposable elements. The "SUmirPredictor" and "SUmirLocator" scripts are freely available together with a reference high-confidence plant miRNA list.

Applications of Next-generation Sequencing in Systemic Autoimmune Diseases

Systemic autoimmune diseases are a group of heterogeneous disorders caused by both genetic and environmental factors. Although numerous causal genes have been identified by genome-wide association studies (GWAS), these susceptibility genes are correlated to a relatively low disease risk, indicating that environmental factors also play an important role in the pathogenesis of disease. The intestinal microbiome, as the main symbiotic ecosystem between the host and host-associated microorganisms, has been demonstrated to regulate the development of the body’s immune system and is likely related to genetic mutations in systemic autoimmune diseases. Next-generation sequencing (NGS) technology, with high-throughput capacity and accuracy, provides a powerful tool to discover genomic mutations, abnormal transcription and intestinal microbiome identification for autoimmune diseases. In this review, we briefly outlined the applications of NGS in systemic autoimmune diseases. This review may provide a reference for future studies in the pathogenesis of systemic autoimmune diseases.