mirTools: microRNA profiling and discovery based on high-throughput sequencing

microRNA Isolation, Expression Profiling, and Target Identification for Neuroprotection in Alzheimer's Disease

Millions of people throughout the world are affected by neurodegenerative disorders like Alzheimer's disease (AD), making them a major public health concern. To create successful medicines, early diagnosis and illness monitoring are required. Emerging as possible diagnostic and treatment tools for neurodegenerative illnesses are biomarkers such as microRNAs (miRNAs). In the realm of neuroscience, miRNAs have been discovered to function as essential regulators of gene expression, with roles spanning development, differentiation, and illness. Several neurodegenerative diseases, including AD, have been linked to miRNA dysregulation. As high-throughput methods have been developed for monitoring miRNA expression and identifying miRNA targets, miRNAs have become a prime candidate for use in diagnostics and therapy. The techniques for isolating miRNAs and the most up-to-date computational methods for finding miRNA target transcripts are both described in this chapter. This chapter will be a helpful reference for anyone investigating the role of miRNAs in AD and related neurodegenerative illnesses.

Functional role of microRNA in the regulation of biotic and abiotic stress in agronomic plants

The increasing demand for food is the result of an increasing population. It is crucial to enhance crop yield for sustainable production. Recently, microRNAs (miRNAs) have gained importance because of their involvement in crop productivity by regulating gene transcription in numerous biological processes, such as growth, development and abiotic and biotic stresses. miRNAs are small, non-coding RNA involved in numerous other biological functions in a plant that range from genomic integrity, metabolism, growth, and development to environmental stress response, which collectively influence the agronomic traits of the crop species. Additionally, miRNA families associated with various agronomic properties are conserved across diverse plant species. The miRNA adaptive responses enhance the plants to survive environmental stresses, such as drought, salinity, cold, and heat conditions, as well as biotic stresses, such as pathogens and insect pests. Thus, understanding the detailed mechanism of the potential response of miRNAs during stress response is necessary to promote the agronomic traits of crops. In this review, we updated the details of the functional aspects of miRNAs as potential regulators of various stress-related responses in agronomic plants.

Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets

Human diseases have been a critical threat from the beginning of human history. Knowing the origin, course of action and treatment of any disease state is essential. A microscopic approach to the molecular field is a more coherent and accurate way to explore the mechanism, progression, and therapy with the introduction and evolution of technology than a macroscopic approach. Non-coding RNAs (ncRNAs) play increasingly important roles in detecting, developing, and treating all abnormalities related to physiology, pathology, genetics, epigenetics, cancer, and developmental diseases. Noncoding RNAs are becoming increasingly crucial as powerful, multipurpose regulators of all biological processes. Parallel to this, a rising amount of scientific information has revealed links between abnormal noncoding RNA expression and human disorders. Numerous non-coding transcripts with unknown functions have been found in addition to advancements in RNA-sequencing methods. Non-coding linear RNAs come in a variety of forms, including circular RNAs with a continuous closed loop (circRNA), long non-coding RNAs (lncRNA), and microRNAs (miRNA). This comprises specific information on their biogenesis, mode of action, physiological function, and significance concerning disease (such as cancer or cardiovascular diseases and others). This study review focuses on non-coding RNA as specific biomarkers and novel therapeutic targets.

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.

Bioinformatics and Machine Learning Approaches to Understand the Regulation of Mobile Genetic Elements

Simple Summary

Transposable elements (TEs) are DNA sequences that are, or were, able to move (transpose) within the genome of a single cell. They were first discovered by Barbara McClintock while working on maize, and they make up a large fraction of the genome. Transpositions can result in mutations and they can alter the genome size. Cells regulate the activity of TEs using a variety of mechanisms, such as chemical modifications of DNA and small RNAs. Machine learning (ML) is an interdisciplinary subject that studies computer algorithms that can improve through experience and by the use of data. ML has been successfully applied to a variety of problems in bioinformatics and has exhibited favorable precision and speed. Here, we provide a systematic and guided review on the ML and bioinformatic methods and tools that are used for the analysis of the regulation of TEs.

Abstract

Transposable elements (TEs, or mobile genetic elements, MGEs) are ubiquitous genetic elements that make up a substantial proportion of the genome of many species. The recent growing interest in understanding the evolution and function of TEs has revealed that TEs play a dual role in genome evolution, development, disease, and drug resistance. Cells regulate TE expression against uncontrolled activity that can lead to developmental defects and disease, using multiple strategies, such as DNA chemical modification, small RNA (sRNA) silencing, chromatin modification, as well as sequence-specific repressors. Advancements in bioinformatics and machine learning approaches are increasingly contributing to the analysis of the regulation mechanisms. A plethora of tools and machine learning approaches have been developed for prediction, annotation, and expression profiling of sRNAs, for methylation analysis of TEs, as well as for genome-wide methylation analysis through bisulfite sequencing data. In this review, we provide a guided overview of the bioinformatic and machine learning state of the art of fields closely associated with TE regulation and function.

Investigation of the miRNA and mRNA Coexpression Network and Their Prognostic Value in Hepatocellular Carcinoma

Purpose

To identify pivotal differentially expressed miRNAs and genes and construct their regulatory network in hepatocellular carcinoma.

Methods

mRNA (GSE101728) and microRNA (GSE108724) microarray datasets were obtained from the NCBI Gene Expression Omnibus (GEO) database. Then, we identified the differentially expressed miRNAs and mRNAs. Sequentially, transcription factor enrichment and gene ontology (GO) enrichment analysis for miRNA were performed. Target genes of these differential miRNAs were obtained using packages in R language (R package multiMiR). After that, downregulated miRNAs were matched with target mRNAs which were upregulated, while upregulated miRNAs were paired with downregulated target mRNA using scripts written in Perl. An miRNA-mRNA network was constructed and visualized in Cytoscape software. For miRNAs in the network, survival analysis was performed. And for genes in the network, we did gene ontology (GO) and KEGG pathway enrichment analysis.

Results

A total of 35 miRNAs and 295 mRNAs were involved in the network. These differential genes were enriched in positive regulation of cell-cell adhesion, positive regulation of leukocyte cell-cell adhesion, and so on. Eight differentially expressed miRNAs were found to be associated with the OS of patients with HCC. Among which, miR-425 and miR-324 were upregulated while the other six, including miR-99a, miR-100, miR-125b, miR-145, miR-150, and miR-338, were downregulated.

Conclusion

In conclusion, these results can provide a potential research direction for further studies about the mechanisms of how miRNA affects malignant behavior in hepatocellular carcinoma.

Plasma Hsa-miR-92a-3p in correlation with lipocalin-2 is associated with sepsis-induced coagulopathy

BACKGROUND

Sepsis is a life-threatening situation, and it can be rendered more severe by coagulopathy. We here examine a novel plasma biomarker for sepsis-induced coagulopathy.

METHODS

A total of 116 patients diagnosed with sepsis were recruited and divided into two groups by whether they also had coagulopathy. Plasma samples were collected on arrival at the intensive care unit. Fifteen sepsis-alone and 15 sepsis-induced coagulopathy plasma samples were mixed and sent for microRNA sequencing. Differently expressed microRNAs were then validated by quantitative reverse transcriptase polymerase chain reaction in 52 sepsis-alone and 34 sepsis-induced coagulopathy patients; plasma lipocalin-2 was measured as well.

RESULTS

Four microRNAs were selected from microRNA sequencing. Only hsa-mir-92a-3p was differently expressed in the validation set. Its level of expression was significantly lower in sepsis-induced coagulopathy group. Hsa-mir-92a-3p had an area under a receiver operating characteristic curve of 0.660 (95% confidence interval, 0.537, 0.782). The plasma Hsa-mir-92a-3p level was related to activated partial thromboplastin time, prothrombin activity, and plasma lipocalin-2 level. A binary logistic model showed an association between hsa-mir-92a-3p and fibrinogen with SIC.

CONCLUSIONS

The utility of hsa-mir-92a-3p as a biomarker for sepsis-induced coagulopathy needs more verification, and the regulatory mechanism of hsa-mir-92a-3p in coagulation disorder and its potency as a therapeutic target must be confirmed.

Small noncoding RNA discovery and profiling with sRNAtools based on high-throughput sequencing

Small noncoding RNAs (sRNA/sncRNAs) are generated from different genomic loci and play important roles in biological processes, such as cell proliferation and the regulation of gene expression. Next-generation sequencing (NGS) has provided an unprecedented opportunity to discover and quantify diverse kinds of sncRNA, such as tRFs (tRNA-derived small RNA fragments), phasiRNAs (phased, secondary, small-interfering RNAs), Piwi-interacting RNA (piRNAs) and plant-specific 24-nt short interfering RNAs (siRNAs). However, currently available web-based tools do not provide approaches to comprehensively analyze all of these diverse sncRNAs. This study presents a novel integrated platform, sRNAtools (https://bioinformatics.caf.ac.cn/sRNAtools), that can be used in conjunction with high-throughput sequencing to identify and functionally annotate sncRNAs, including profiling microRNAss, piRNAs, tRNAs, small nuclear RNAs, small nucleolar RNAs and rRNAs and discovering isomiRs, tRFs, phasiRNAs and plant-specific 24-nt siRNAs for up to 21 model organisms. Different modules, including single case, batch case, group case and target case, are developed to provide users with flexible ways of studying sncRNA. In addition, sRNAtools supports different ways of uploading small RNA sequencing data in a very interactive queue system, while local versions based on the program package/Docker/virtureBox are also available. We believe that sRNAtools will greatly benefit the scientific community as an integrated tool for studying sncRNAs.

MicroRNA dataset of normal and Nosema ceranae-infected midguts of Apis cerana cerana workers

Nosema ceranae is a widespread fungal pathogen of honeybees, which is infective to all castes in the colony, including queens, drones and workers. Nosemosis caused by N. ceranae poses a big challenge for apiculture all over the world. Here, midguts of normal and N. ceranae-infected Apis cerana cerana workers at 7 and 10 days post infection were sequenced utilizing small RNA sequencing (sRNA-seq) technology. Totally, more than 150.54 Mb raw reads were produced in this article, and over 144.26 Mb high-quality clean reads with a mean ratio of 95.83% were obtained after strict filtering and quality control. For more insight please see "Comparative identification of microRNAs in Apis cerana cerana workers' midguts responding to Nosema ceranae invasion" (Chen et al., 2019). Raw data are available in NCBI Sequence Read Archive (SRA) database under the BioProject number PRJNA487111. Our data can be used for investigating differentially expressed microRNAs (miRNAs) and piRNAs and their regulatory roles engaged in A. c. cerana response to N. ceranae infection, and for offering potential candidates for uncovering the molecular mechanisms regulating eastern honeybee-microsporidian interactions.

Comparative Identification of MicroRNAs in Apis cerana cerana Workers' Midguts in Responseto Nosema ceranae Invasion

Here, the expression profiles and differentially expressed miRNAs (DEmiRNAs) in the midguts of Apis cerana cerana workers at 7 d and 10 d post-inoculation (dpi) with N. ceranae were investigated via small RNA sequencing and bioinformatics. Five hundred and twenty nine (529) known miRNAs and 25 novel miRNAs were identified in this study, and the expression of 16 predicted miRNAs was confirmed by Stem-loop RT-PCR. A total of 14 DEmiRNAs were detected in the midgut at 7 dpi, including eight up-regulated and six down-regulated miRNAs, while 12 DEmiRNAs were observed in the midgut at 10 dpi, including nine up-regulated and three down-regulated ones. Additionally, five DEmiRNAs were shared, while nine and seven DEmiRNAs were specifically expressed in midguts at 7 dpi and 10 dpi. Gene ontology analysis suggested some DEmiRNAs and corresponding target mRNAs were involved in various functions including immune system processes and response to stimulus. KEGG pathway analysis shed light on the potential functions of some DEmiRNAs in regulating target mRNAs engaged in material and energy metabolisms, cellular immunity and the humoral immune system. Further investigation demonstrated a complex regulation network between DEmiRNAs and their target mRNAs, with miR-598-y, miR-252-y, miR-92-x and miR-3654-y at the center. Our results can facilitate future exploration of the regulatory roles of miRNAs in host responses to N. ceranae, and provide potential candidates for further investigation of the molecular mechanisms underlying eastern honeybee-microsporidian interactions.

Comparative profile analysis reveals differentially expressed microRNAs regulate anther and pollen development in kenaf cytoplasmic male sterility line

Cytoplasmic male sterility (CMS) is advantageous in extensive crop breeding and represents a perfect model for understanding anther and pollen development research. MicroRNAs (miRNAs) play key roles in regulating various biological processes. However, the miRNA-mediated regulatory network in kenaf CMS occurrence remains largely unknown. In the present study, a comparative deep sequencing approach was used to investigate the miRNAs and their roles in regulating anther and pollen development during CMS occurrence. We identified 283 known and 46 new candidate miRNAs in kenaf anther. A total of 67 differentially expressed miRNAs (DEMs) were discovered between CMS and its maintainer line. Among them, 40 and 27 miRNAs were up- and downregulated, respectively. These 67 DEMs were predicted to target 189 genes. Validation of DEMs and putative target genes were confirmed by using real-time quantitative PCR. In addition, a potential miRNA-mediated regulatory network, which mainly involves the auxin signaling pathway, signal transduction, glycolysis and energy metabolism, gene expression, transmembrane transport, protein modification and metabolism, and floral development, that mediates anther development during CMS occurrence was proposed. Taken together, our findings provide a better understanding of the molecular mechanism of miRNA regulation in pollen development and CMS occurrence in kenaf.

Identification of coordinately regulated microRNA-gene networks that differ in baboons discordant for LDL-cholesterol

RATIONALE

Plasma low-density lipoprotein cholesterol (plasma LDL-C), vascular endothelial cells and peripheral blood mononuclear cells (PBMCs), particularly monocytes, play key roles in initiating atherosclerosis, the primary cause of cardiovascular disease (CVD). Although the mechanisms underlying development of atherosclerosis are not well understood, LDL-C is known to influence expression of endothelial microRNAs (miRNAs) and gene-targets of miRNAs to promote cell senescence. However, the impact of LDL-C on expression of PBMC miRNAs and miRNA targeted genes in response to an atherogenic diet is not known. In this study, we used unbiased methods to identify coordinately responsive PBMC miRNA- gene networks that differ between low and high LDL-C baboons when fed a high-cholesterol, high-fat (HCHF) diet.

METHODS AND RESULTS

Using RNA Seq, we quantified PBMC mRNAs and miRNAs from half-sib baboons discordant for LDL-C plasma concentrations (low LDL-C, n = 3; high LDL-C, n = 3) before and after a 7-week HCHF diet challenge. For low LDL-C baboons, 626 genes exhibited significant change in expression (255 down-regulated, 371 up-regulated) in response to the HCHF diet, and for high LDL-C baboons 379 genes exhibited significant change in expression (162 down-regulated, 217 up-regulated) in response to the HCHF diet. We identified 494 miRNAs identical to human miRNAs and 47 novel miRNAs. Fifty miRNAs were differentially expressed in low LDL-C baboons (21 up- and 29 down-regulated) and 20 in high LDL-C baboons (11 up- and 9 down-regulated) in response to the HCHF diet. Among the differentially expressed miRNAs were miR-221/222 and miR-34a-3p, which were down-regulated, and miR-148a/b-5p, which was up-regulated. In addition, gene-targets of these miRNAs, VEGFA, MAML3, SPARC, and DMGDH, were inversely expressed and are central hub genes in networks and signaling pathways that differ between low and high LDL-C baboon HCHF diet response.

CONCLUSIONS

We have identified coordinately regulated HCHF diet-responsive PBMC miRNA-gene networks that differ between baboons discordant for LDL-C concentrations. Our findings provide potential insights into molecular mechanisms underlying initiation of atherosclerosis where LDL-C concentrations influence expression of specific miRNAs, which in turn regulate expression of genes that play roles in initiation of lesions.

Black phosphorus nanosheets for rapid microRNA detection

Herein, for the first time, a sensitive sensing platform for rapid detection of microRNA was developed by employing black phosphorus nanosheets as the fluorescence quenching material. The biosensor displayed a good linear response to microRNA ranging from 10 nM to 1000 nM. Moreover, the biosensor could distinguish triple nucleotide polymorphism.

Evaluation of Bioinformatics Approaches for Next-Generation Sequencing Analysis of microRNAs with a Toxicogenomics Study Design

MicroRNAs (miRNAs) are key post-transcriptional regulators that affect protein translation by targeting mRNAs. Their role in disease etiology and toxicity are well recognized. Given the rapid advancement of next-generation sequencing techniques, miRNA profiling has been increasingly conducted with RNA-seq, namely miRNA-seq. Analysis of miRNA-seq data requires several steps: (1) mapping the reads to miRBase, (2) considering mismatches during the hairpin alignment (windowing), and (3) counting the reads (quantification). The choice made in each step with respect to the parameter settings could affect miRNA quantification, differentially expressed miRNAs (DEMs) detection and novel miRNA identification. Furthermore, these parameters do not act in isolation and their joint effects impact miRNA-seq results and interpretation. In toxicogenomics, the variation associated with parameter setting should not overpower the treatment effect (such as the dose/time-dependent effect). In this study, four commonly used miRNA-seq analysis tools (i.e., miRDeep2, miRExpress, miRNAkey, sRNAbench) were comparatively evaluated with a standard toxicogenomics study design. We tested 30 different parameter settings on miRNA-seq data generated from thioacetamide-treated rat liver samples for three dose levels across four time points, followed by four normalization options. Because both miRExpress and miRNAkey yielded larger variation than that of the treatment effects across multiple parameter settings, our analyses mainly focused on the side-by-side comparison between miRDeep2 and sRNAbench. While the number of miRNAs detected by miRDeep2 was almost the subset of those detected by sRNAbench, the number of DEMs identified by both tools was comparable under the same parameter settings and normalization method. Change in the number of nucleotides out of the mature sequence in the hairpin alignment (window option) yielded the largest variation for miRNA quantification and DEMs detection. However, such a variation is relatively small compared to the treatment effect when the study focused on DEMs that are more critical to interpret the toxicological effect. While the normalization methods introduced a large variation in DEMs, toxic behavior of thioacetamide showed consistency in the trend of time-dose responses. Overall, miRDeep2 was found to be preferable over other choices when the window option allowed up to three nucleotides from both ends.

Bioinformatic Analysis of MicroRNA Sequencing Data

The vital role of microRNAs (miRNAs) involved in gene expression regulation has been confirmed in many biological processes. With the growing power and reducing cost of next-generation sequencing, more and more researchers turn to apply this high-throughput method to solve their biological problems. For miRNAs with known sequences, their expression profiles can be generated from the sequencing data. It also allows us to identify some novel miRNAs and explore the sequence variations under different conditions. Currently, there are a handful of tools available to analyze the miRNA sequencing data with separated or combined features, such as reads preprocessing, mapping and differential expression analysis. However, to our knowledge, a hands-on guideline for miRNA sequencing data analysis covering all steps is not available. Here we will utilize a set of published tools to perform the miRNA analysis with detailed explanation. Particularly, the miRNA target prediction and annotation may provide useful information for further experimental verification.

Integrative analysis of the Pekin duck (Anas anas) MicroRNAome during feather follicle development

BACKGROUND

The quality and yield of duck feathers are very important economic traits that might be controlled by miRNA regulation. The aim of the present study was to investigate the mechanism underlying the crosstalk between individual miRNAs and the activity of signaling pathways that control the growth of duck feathers during different periods. We therefore conducted a comprehensive investigation using Solexa sequencing technology on the Pekin duck microRNAome over six stages of feather development at days 11, 15, and 20 of embryonic development (during the hatching period), and at 1 day and 4 and 10 weeks posthatch.

RESULTS

There were a total of 354 known miRNAs and 129 novel candidate miRNAs found based on comparisons with known miRNAs in the Gallus gallus miRBase. The series of miRNAs related to feather follicle formation as summarized in the present study showed two expression patterns, with primary follicle developed during embryonic stage and secondary follicle developed mainly at early post hatch stage. Analysis of miRNA expression profiles identified 18 highly expressed miRNAs, which might be directly responsible for regulation of feather development. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis suggested that in addition to Wnt and transforming growth factor (TGFβ) signaling pathways, which were widely reported in response to follicle formation, another group of signaling pathways that regulate lipid synthesis and metabolism, such as the phosphatidylinositol signaling system and glycerolipid metabolism and signaling, are also responsible for follicle formation.

CONCLUSION

The highly expressed miRNAs provide a valuable reference for further investigation into the functional miRNAs important for feather development. Lipid synthesis and metabolism related signaling pathways might be responsible for lipid formation on the surface of feather, and should be paid much more attention for their relation to feather quality.

Upregulation of Circulating miR-195-3p in Heart Failure

OBJECTIVES

Many circulating microRNAs (miRs) have been shown to have potential biomarker effects in cardiovascular disease. We studied the dysregulation of circulating miR-195-3p in patients with heart failure (HF) to elucidate its value as a potential biomarker for HF.

METHODS

Eight ischemic HF (IHF) patients, 8 nonischemic HF patients (NIHF), and 8 healthy volunteers (matched by age and sex - normal controls [NCs]) were chosen for miR sequencing. The plasma RNA was extracted, and a small RNA library of HF was established and then sequenced using next-generation sequencing (NGS) technology. The miR-195-3p was selected for a second clinical study in 60 IHF, 48 NIHF patients, and 35 NCs for qRT-PCR validation.

RESULTS

The expression of circulating miR-195-3p in the IHF group was increased 69.5-fold compared with the NC group using NGS technique, and it was the most elevated in all upregulated miRs. MiR-195-3p was ranked in the top 1 of all upregulated miRs in contribution to HF based on a random forest model analysis. The upregulation of circulating miR-195-3p was also validated with the qRT-PCR method, and receiver operating characteristic curve analysis showed that the area under the curve (AUC) was 0.831.

CONCLUSIONS

The circulating miR-195-3p was upregulated in IHF and NIHF patients and could be a potential biomarker for HF.

Dynamic regulation of small RNAome during the early stage of cardiac differentiation from pluripotent embryonic stem cells

Embryonic stem cells (mESCs), having potential to differentiate into three germ-layer cells including cardiomyocytes, shall be a perfect model to help understanding heart development. Here, using small RNA deep sequencing, we studied the small RNAome in the early stage of mouse cardiac differentiation. We found that the expression pattern of most microRNA (miRNA) were highly enriched at the beginning and declined thereafter, some were still insufficiently expressed on day 6, and most miRNAs recovered in the following days. When pluripotent embryonic stem cells are differentiating to cardiomyocytes, targeted genes are concentrated on TGF, WNT and cytoskeletal remodeling pathway. The pathway and network of dynamically changed target genes of the miRNAs at different time points were also investigated. Furthermore, we demonstrated that small rDNA-derived RNAs (srRNAs) were significantly up-regulated during differentiation, especially in stem cells. The pathways of srRNAs targeted genes were also presented. We described the existence and the differential expression of transfer RNA (tRNA), Piwi-interacting RNA (piRNA) and Endogenous siRNAs (endo-siRNAs) in this process. This study reports the genome-wide small RNAome profile, and provides a uniquely comprehensive view of the small RNA regulatory network that governs embryonic stem cell differentiation and cardiac development.

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.

Effects of exposure to Streptococcus iniae on microRNA expression in the head kidney of genetically improved farmed tilapia (Oreochromis niloticus)

Background

Genetically improved farmed tilapia (GIFT, Oreochromis niloticus) are susceptible to infection by Streptococcus iniae when maintained in modern intensive culture systems. GIFT are commercially important fishes that are cultured widely in southern China. The role of microRNAs (miRNAs) in the regulatory response of GIFT to S. iniae infection has been underestimated and has not yet been well studied. Head kidney has an important immune function in teleost fishes. The main aim of this study was to determine the possible function of miRNAs in head kidney of S. iniae-infected GIFT. MiRNAs are small, non-coding RNAs that regulate gene expression by binding to the 3’-untranslated regions of their target mRNAs. MiRNAs are known to regulate immune-regulated signaling and inflammatory response pathways.

Results

High-throughput deep sequencing of two libraries (control group [CO] and infected group [IN]) of RNA extracted from GIFT head kidney tissues generated 12,089,630 (CO) and 12,624,975 (IN) clean reads. Bioinformatics analysis identified 1736 and 1729 conserved miRNAs and 164 and 165 novel miRNAs in the CO and IN libraries, respectively. Three miRNAs (miR-310-3p, miR-92, and miR-127) were found to be up-regulated and four miRNAs (miR-92d-3p, miR-375-5p, miR-146-3p, and miR-694) were found to be down-regulated in the S. iniae-infected GIFT. The expressions of these miRNAs were verified by quantitative real-time PCR. RNAhybrid and TargetScan were used to identify complementary miRNA and mRNA target sites, and the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases were used to annotate and predict potential downstream regulation of biological pathways. Seven target genes, which encode immune-related proteins (complement C3, cytidine deaminase, regulator of G-protein Rgs22, mitogen-activated protein kinase Mapk1, metabotropic glutamate receptorm GluR8, calcium-sensing receptor CaSR, and microtubule-associated protein Map1S) were predicted to play crucial roles in the GIFT response to S. iniae infection.

Conclusions

S. iniae outbreaks have hindered the development of the tilapia industry in China. Understanding the miRNA transcriptome of S. iniae-infected GIFT is important for exploring the immune responses regulated by miRNAs as well as for studying novel regulated networks to prevent and treat S. iniae infections in the future.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3591-z) contains supplementary material, which is available to authorized users.

Considerations and complications of mapping small RNA high-throughput data to transposable elements

BACKGROUND

High-throughput sequencing (HTS) has revolutionized the way in which epigenetic research is conducted. When coupled with fully-sequenced genomes, millions of small RNA (sRNA) reads are mapped to regions of interest and the results scrutinized for clues about epigenetic mechanisms. However, this approach requires careful consideration in regards to experimental design, especially when one investigates repetitive parts of genomes such as transposable elements (TEs), or when such genomes are large, as is often the case in plants.

RESULTS

Here, in an attempt to shed light on complications of mapping sRNAs to TEs, we focus on the 2,300 Mb maize genome, 85% of which is derived from TEs, and scrutinize methodological strategies that are commonly employed in TE studies. These include choices for the reference dataset, the normalization of multiply mapping sRNAs, and the selection among sRNA metrics. We further examine how these choices influence the relationship between sRNAs and the critical feature of TE age, and contrast their effect on low copy genomic regions and other popular HTS data.

CONCLUSIONS

Based on our analyses, we share a series of take-home messages that may help with the design, implementation, and interpretation of high-throughput TE epigenetic studies specifically, but our conclusions may also apply to any work that involves analysis of HTS data.

miR-29a modulates SCD expression and is regulated in response to a saturated fatty acid diet in juvenile genetically improved farmed tilapia (Oreochromis niloticus)

MicroRNAs (miRNAs) are small non-coding RNAs that regulate target gene expression by binding to the 3′ untranslated region (3′ UTR) of the target mRNA. MiRNAs regulate a large variety of genes, including those involved in liver biology and disease. Here, we report for the first time that miR-29a post-transcriptionally regulates stearoyl-CoA desaturase (SCD) by binding to its 3′ UTR in genetically improved farmed tilapia (GIFT), Oreochromis niloticus, as shown by a 3′ UTR luciferase reporter assay. miR-29a antagomir treatment in vivo resulted in significant upregulation of SCD expression. We found that miR-29a expression was negatively correlated with SCD expression in GIFT liver. Inhibition of miR-29a led to a significant increase in SCD expression on day 60 induced by a saturated fatty acid diet, thereby increasing conversion of 16:0 and 18:0 to 16:1 and 18:1, respectively, and activating serum insulin, which would favor glucose and lipid uptake by the liver. These results indicate that miR-29a regulates SCD levels by binding to its 3′ UTR, and this interaction affects saturated fatty acid stress induction and insulin and lipid accumulation in serum. Our results suggest that miR-29a is critical in regulating lipid metabolism homeostasis in GIFT liver, and this might provide a basis for understanding the biological processes and therapeutic intervention encountered in fatty liver.

Summary: miR-29a targets SCD 3′ UTR directly. Inhibition of miR-29a could mediate conversion of C16:0 and C18:0 to C16:1 and C18:1, respectively, and activate serum insulin and glucose uptake in GIFT by increasing SCD.

miR-122 promotes hepatic antioxidant defense of genetically improved farmed tilapia (GIFT, Oreochromis niloticus) exposed to cadmium by directly targeting a metallothionein gene

MicroRNAs (miRNAs) are small, non-coding RNAs that regulate target gene expression by binding to the 3'untranslated region (3'UTR) of the target mRNA. MiRNAs regulate a large variety of genes, including those involved in liver homeostasis and energy metabolism. Down-regulated levels of hepatic miR-122 were found in genetically improved farmed tilapia (GIFT, Oreochromis niloticus) exposed to cadmium (Cd) stress. Here, we report for the first time that reduction of miR-122 post-transcriptionally increased metallothionein (MT) mRNA levels by binding to its 3'UTR, as shown by a 3' UTR luciferase reporter assay. The expression levels of miR-122 were negatively related to MT levels in GIFT under Cd stress. We performed in vivo functional analysis of miR-122 by injecting the fish with a miR-122 antagomir. Inhibition of miR-122 levels in GIFT liver caused a significant increase in MT expression, affected white blood cell and red blood cell counts, and serum alanine and aspartate aminotransferase activities, and glucose levels, all of which may help to relieve Cd stress-related liver stress. miR-122 silencing modulated oxidative stress and stimulated the activity of antioxidant enzymes. Our findings indicate that miR-122 regulated MT levels by binding to the 3'UTR of MT mRNA, and this interaction affected Cd stress induction and the resistance response in GIFT. We concluded that miR-122 plays an important role in regulating the stress response in GIFT liver. Our findings may contribute to understanding the mechanisms of miRNA-mediated gene regulation in tilapia in response to environmental stresses.

Analysis of liver and gill miRNAs of Larimichthys crocea against Cryptocryon irritans challenge

The white-spot disease caused by marine ciliate Cryptocryon irritans hindered the sustainable development of large yellow croaker Larimichthys crocea industry. Better understandings about the parasite-host interactions in the molecular level will facilitate the prevention of mass mortality of the L. crocea caused by white-spot disease. MicroRNAs (miRNAs) are a class of small RNA molecules about 20-22 nucleotides which post-transcriptionally regulated many protein-coding genes and involved in many biological processes, especially in host-pathogen responses. In this study, we identified known and novel miRNAs in the gill and liver of L. crocea challenged by C. irritans by high throughput sequencing using Solexa technology. The data were further studied to screen differentially expressed miRNAs, and predict their target genes. The differential expression (p < 0.05) between libraries was observed in 103 miRNAs in liver tissue, among which 65 and 38 were conserved and novel miRNAs, 67 and 36 were up- and down-regulated miRNAs. While in gill tissue, 122 significant differentially expressed miRNAs were identified, among which 83 and 39 were conserved and novel miRNAs, 79 and 43 were up- and down-regulated miRNAs. In addition, these differentially expressed miRNAs target a series of genes which involved in many important biological processes including immune response. Here via deep sequencing, we for the first time characterize L. crocea miRNAs in response to C. irritans challenge, the results should help for better understandings about the immune response of the L. crocea under C. irritans challenge.

Chicken cecal microRNAs in the response to Campylobacter jejuni inoculation by Solexa sequencing

Campylobacter jejuni (C. jejuni) is one of major foodborne pathogen that cause human diarrhea by consuming C. jejuni contaminated chicken products. MicroRNAs play an integral role in many different biological processes including bacteria and virus inoculation in chickens. In this study, we identified chicken miRNAs responding to C. jejuni inoculation through Solexa sequencing in the cecum. As a result, four miRNAs were significantly differentially expressed between inoculated and non-inoculated groups. There were 1,114 putative target genes regulated by those differentially expressed miRNAs predicted by miRanda, TargetScan, and miRTarget softwares. Functional analysis of those target genes showed that 113 gene ontology biological process terms and 14 pathways were significantly enriched. Hedgehog signaling pathway may contribute to chicken C. jejuni inoculation. MiR-155 played vital role in the C. jejuni inoculation. The result herein will lay the foundation for the further study of regulatory mechanism of chicken miRNAs in the response to C. jejuni inoculation.

The transcriptome of nitrofen-induced pulmonary hypoplasia in the rat model of congenital diaphragmatic hernia

BACKGROUND

We currently do not know how the herbicide nitrofen induces lung hypoplasia and congenital diaphragmatic hernia in rats. Our aim was to compare the differentially expressed transcriptome of nitrofen-induced hypoplastic lungs to control lungs in embryonic day 13 rat embryos before the development of embryonic diaphragmatic defects.

METHODS

Using next-generation sequencing technology, we identified the expression profile of microRNA (miRNA) and mRNA genes. Once the dataset was validated by both RT-qPCR and digital-PCR, we conducted gene ontology, miRNA target analysis, and orthologous miRNA sequence matching for the deregulated miRNAs in silico.

RESULTS

Our study identified 186 known mRNA and 100 miRNAs which were differentially expressed in nitrofen-induced hypoplastic lungs. Sixty-four rat miRNAs homologous to known human miRNAs were identified. A subset of these genes may promote lung hypoplasia in rat and/or human, and we discuss their associations. Potential miRNA pathways relevant to nitrofen-induced lung hypoplasia include PI3K, TGF-β, and cell cycle kinases.

CONCLUSION

Nitrofen-induced hypoplastic lungs have an abnormal transcriptome that may lead to impaired development.

isomiR-SEA: an RNA-Seq analysis tool for miRNAs/isomiRs expression level profiling and miRNA-mRNA interaction sites evaluation

Background

Massive parallel sequencing of transcriptomes, revealed the presence of many miRNAs and miRNAs variants named isomiRs with a potential role in several cellular processes through their interaction with a target mRNA. Many methods and tools have been recently devised to detect and quantify miRNAs from sequencing data. However, all of them are implemented on top of general purpose alignment methods, thus providing poorly accurate results and no information concerning isomiRs and conserved miRNA-mRNA interaction sites.

Results

To overcome these limitations we present a novel algorithm named isomiR-SEA, that is able to provide users with very accurate miRNAs expression levels and both isomiRs and miRNA-mRNA interaction sites precise classifications. Tags are mapped on the known miRNAs sequences thanks to a specialized alignment algorithm developed on top of biological evidence concerning miRNAs structure. Specifically, isomiR-SEA checks for miRNA seed presence in the input tags and evaluates, during all the alignment phases, the positions of the encountered mismatches, thus allowing to distinguish among the different isomiRs and conserved miRNA-mRNA interaction sites.

Conclusions

isomiR-SEA performances have been assessed on two public RNA-Seq datasets proving that the implemented algorithm is able to account for more reliable and accurate miRNAs expression levels with respect to those provided by two compared state of the art tools. Moreover, differently from the few methods currently available to perform isomiRs detection, the proposed algorithm implements the evaluation of isomiRs and conserved miRNA-mRNA interaction sites already in the first alignment phases, thus avoiding any additional filtering stages potentially responsible for the loss of useful information.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0958-0) contains supplementary material, which is available to authorized users.

iSRAP - a one-touch research tool for rapid profiling of small RNA-seq data

Small non-coding RNAs have been significantly recognized as the key modulators in many biological processes, and are emerging as promising biomarkers for several diseases. These RNA species are transcribed in cells and can be packaged in extracellular vesicles, which are small vesicles released from many biotypes, and are involved in intercellular communication. Currently, the advent of next-generation sequencing (NGS) technology for high-throughput profiling has further advanced the biological insights of non-coding RNA on a genome-wide scale and has become the preferred approach for the discovery and quantification of non-coding RNA species. Despite the routine practice of NGS, the processing of large data sets poses difficulty for analysis before conducting downstream experiments. Often, the current analysis tools are designed for specific RNA species, such as microRNA, and are limited in flexibility for modifying parameters for optimization. An analysis tool that allows for maximum control of different software is essential for drawing concrete conclusions for differentially expressed transcripts. Here, we developed a one-touch integrated small RNA analysis pipeline (iSRAP) research tool that is composed of widely used tools for rapid profiling of small RNAs. The performance test of iSRAP using publicly and in-house available data sets shows its ability of comprehensive profiling of small RNAs of various classes, and analysis of differentially expressed small RNAs. iSRAP offers comprehensive analysis of small RNA sequencing data that leverage informed decisions on the downstream analyses of small RNA studies, including extracellular vesicles such as exosomes.

Non-coding RNAs deregulation in oral squamous cell carcinoma: advances and challenges

Oral squamous cell carcinoma (OSCC) is a common cause of cancer death. Despite decades of improvements in exploring new treatments and considerable advance in multimodality treatment, satisfactory curative rates have not yet been reached. The difficulty of early diagnosis and the high prevalence of metastasis associated with OSCC contribute to its dismal prognosis. In the last few decades the emerging data from both tumor biology and clinical trials led to growing interest in the research for predictive biomarkers. Non-coding RNAs (ncRNAs) are promising biomarkers. Among numerous kinds of ncRNAs, short ncRNAs, such as microRNAs (miRNAs), have been extensively investigated with regard to their biogenesis, function, and importance in carcinogenesis. In contrast to miRNAs, long non-coding RNAs (lncRNAs) are much less known concerning their functions in human cancers especially in OSCC. The present review highlighted the roles of miRNAs and newly discovered lncRNAs in oral tumorigenesis, metastasis, and their clinical implication.

miFRame: analysis and visualization of miRNA sequencing data in neurological disorders

Background

While in the past decades nucleic acid analysis has been predominantly carried out using quantitative low- and high-throughput approaches such as qRT-PCR and microarray technology, next-generation sequencing (NGS) with its single base resolution is now frequently applied in DNA and RNA testing. Especially for small non-coding RNAs such as microRNAs there is a need for analysis and visualization tools that facilitate interpretation of the results also for clinicians.

Methods

We developed miFRame, which supports the analysis of human small RNA NGS data. Our tool carries out different data analyses for known as well as predicted novel mature microRNAs from known precursors and presents the results in a well interpretable manner. Analyses include among others expression analysis of precursors and mature miRNAs, detection of novel precursors and detection of potential iso-microRNAs. Aggregation of results from different users moreover allows for evaluation whether remarkable results, such as novel mature miRNAs, are indeed specific for the respective experimental set-up or are frequently detected across a broad range of experiments.

Results

We demonstrate the capabilities of miFRame, which is freely available at http://www.ccb.uni-saarland.de/miframe on two studies, circulating biomarker screening for Multiple Sclerosis (cohort includes clinically isolated syndrome, relapse remitting MS, matched controls) as well as Alzheimer Disease (cohort includes Alzheimer Disease, Mild Cognitive Impairment, matched controls). Here, our tool allowed for an improved biomarker discovery by identifying likely false positive marker candidates.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-015-0594-x) contains supplementary material, which is available to authorized users.

Use of RNA sequencing to evaluate rheumatic disease patients

Studying the factors that control gene expression is of substantial importance for rheumatic diseases with poorly understood etiopathogenesis. In the past, gene expression microarrays have been used to measure transcript abundance on a genome-wide scale in a particular cell, tissue or organ. Microarray analysis has led to gene signatures that differentiate rheumatic diseases, and stages of a disease, as well as response to treatments. Nowadays, however, with the advent of next-generation sequencing methods, massive parallel sequencing of RNA tends to be the technology of choice for gene expression profiling, due to several advantages over microarrays, as well as for the detection of non-coding transcripts and alternative splicing events. In this review, we describe how RNA sequencing enables unbiased interrogation of the abundance and complexity of the transcriptome, and present a typical experimental workflow and bioinformatics tools that are often used for RNA sequencing analysis. We also discuss different uses of this next-generation sequencing technology to evaluate rheumatic disease patients and investigate the pathogenesis of rheumatic diseases such as rheumatoid arthritis, systemic lupus erythematosus, juvenile idiopathic arthritis and Sjögren’s syndrome.

Optimization of miRNA-seq data preprocessing

The past two decades of microRNA (miRNA) research has solidified the role of these small non-coding RNAs as key regulators of many biological processes and promising biomarkers for disease. The concurrent development in high-throughput profiling technology has further advanced our understanding of the impact of their dysregulation on a global scale. Currently, next-generation sequencing is the platform of choice for the discovery and quantification of miRNAs. Despite this, there is no clear consensus on how the data should be preprocessed before conducting downstream analyses. Often overlooked, data preprocessing is an essential step in data analysis: the presence of unreliable features and noise can affect the conclusions drawn from downstream analyses. Using a spike-in dilution study, we evaluated the effects of several general-purpose aligners (BWA, Bowtie, Bowtie 2 and Novoalign), and normalization methods (counts-per-million, total count scaling, upper quartile scaling, Trimmed Mean of M, DESeq, linear regression, cyclic loess and quantile) with respect to the final miRNA count data distribution, variance, bias and accuracy of differential expression analysis. We make practical recommendations on the optimal preprocessing methods for the extraction and interpretation of miRNA count data from small RNA-sequencing experiments.

Prediction of MicroRNA Precursors Using Parsimonious Feature Sets

MicroRNAs (miRNAs) are a class of short noncoding RNAs that regulate gene expression through base pairing with messenger RNAs. Due to the interest in studying miRNA dysregulation in disease and limits of validated miRNA references, identification of novel miRNAs is a critical task. The performance of different models to predict novel miRNAs varies with the features chosen as predictors. However, no study has systematically compared published feature sets. We constructed a comprehensive feature set using the minimum free energy of the secondary structure of precursor miRNAs, a set of nucleotide-structure triplets, and additional extracted sequence and structure characteristics. We then compared the predictive value of our comprehensive feature set to those from three previously published studies, using logistic regression and random forest classifiers. We found that classifiers containing as few as seven highly predictive features are able to predict novel precursor miRNAs as well as classifiers that use larger feature sets. In a real data set, our method correctly identified the holdout miRNAs relevant to renal cancer.

Genome-wide discovery and differential regulation of conserved and novel microRNAs in chickpea via deep sequencing

MicroRNAs (miRNAs) are essential components of complex gene regulatory networks that orchestrate plant development. Although several genomic resources have been developed for the legume crop chickpea, miRNAs have not been discovered until now. For genome-wide discovery of miRNAs in chickpea (Cicer arietinum), we sequenced the small RNA content from seven major tissues/organs employing Illumina technology. About 154 million reads were generated, which represented more than 20 million distinct small RNA sequences. We identified a total of 440 conserved miRNAs in chickpea based on sequence similarity with known miRNAs in other plants. In addition, 178 novel miRNAs were identified using a miRDeep pipeline with plant-specific scoring. Some of the conserved and novel miRNAs with significant sequence similarity were grouped into families. The chickpea miRNAs targeted a wide range of mRNAs involved in diverse cellular processes, including transcriptional regulation (transcription factors), protein modification and turnover, signal transduction, and metabolism. Our analysis revealed several miRNAs with differential spatial expression. Many of the chickpea miRNAs were expressed in a tissue-specific manner. The conserved and differential expression of members of the same miRNA family in different tissues was also observed. Some of the same family members were predicted to target different chickpea mRNAs, which suggested the specificity and complexity of miRNA-mediated developmental regulation. This study, for the first time, reveals a comprehensive set of conserved and novel miRNAs along with their expression patterns and putative targets in chickpea, and provides a framework for understanding regulation of developmental processes in legumes.

Methods of quantifying microRNAs for hypoxia research: classic and next generation

SIGNIFICANCE

Recent evidence is uncovering the ever-increasing importance of microribonucleic acids (miRNAs) in the hypoxia response. In order to investigate the important roles that these small RNAs play, methods of quantification whether using classic single-gene methods or genome-wide technologies are necessary to obtain a global picture of the differential expression of miRNAs in hypoxia and their interplay with protein coding genes.

RECENT ADVANCES

Building on the groundwork of classic quantitative polymerase chain reaction (qPCR) and microarrays, the advent of next-generation sequencing technology has revolutionized how small RNAs can be detected and quantified on a genome-wide scale and without a priori knowledge of the small RNA sequence. This method delivers accurate and comprehensive data on the expression and sequence of all expressed small RNAs, and the data can be further combined with other sequencing modalities to better understand miRNAs via integrated genomic analyses.

CRITICAL ISSUES

Advancing technology has increased the need for better methods of sample and library preparation and for bioinformatics tools. Speed, cost, sample input, and analysis expertise remain the mainstay critical issues of small RNA sequencing.

FUTURE DIRECTIONS

Future hypoxia research will benefit from the application of genome-wide sequencing technologies. Analyses that combine genomic, transcriptomic, chromosome conformation, DNA/RNA-protein binding, and proteomics will help greatly advance hypoxia miRNA research.

Identification and characterization of novel serum microRNA candidates from deep sequencing in cervical cancer patients

Small non-coding microRNAs (miRNAs) are involved in cancer development and progression, and serum profiles of cervical cancer patients may be useful for identifying novel miRNAs. We performed deep sequencing on serum pools of cervical cancer patients and healthy controls with 3 replicates and constructed a small RNA library. We used MIREAP to predict novel miRNAs and identified 2 putative novel miRNAs between serum pools of cervical cancer patients and healthy controls after filtering out pseudo-pre-miRNAs using Triplet-SVM analysis. The 2 putative novel miRNAs were validated by real time PCR and were significantly decreased in cervical cancer patients compared with healthy controls. One novel miRNA had an area under curve (AUC) of 0.921 (95% CI: 0.883, 0.959) with a sensitivity of 85.7% and a specificity of 88.2% when discriminating between cervical cancer patients and healthy controls. Our results suggest that characterizing serum profiles of cervical cancers by Solexa sequencing may be a good method for identifying novel miRNAs and that the validated novel miRNAs described here may be cervical cancer-associated biomarkers.

miRSeq: a user-friendly standalone toolkit for sequencing quality evaluation and miRNA profiling

MicroRNAs (miRNAs) present diverse regulatory functions in a wide range of biological activities. Studies on miRNA functions generally depend on determining miRNA expression profiles between libraries by using a next-generation sequencing (NGS) platform. Currently, several online web services are developed to provide small RNA NGS data analysis. However, the submission of large amounts of NGS data, conversion of data format, and limited availability of species bring problems. In this study, we developed miRSeq to provide alternatives. To test the performance, we had small RNA NGS data from four species, including human, rat, fly, and nematode, analyzed with miRSeq. The alignments results indicate that miRSeq can precisely evaluate the sequencing quality of samples regarding percentage of self-ligation read, read length distribution, and read category. miRSeq is a user-friendly standalone toolkit featuring a graphical user interface (GUI). After a simple installation, users can easily operate miRSeq on a PC or laptop by using a mouse. Within minutes, miRSeq yields useful miRNA data, including miRNA expression profiles, 3′ end modification patterns, and isomiR forms. Moreover, miRSeq supports the analysis of up to 105 animal species, providing higher flexibility.

MAGI: a Node.js web service for fast microRNA-Seq analysis in a GPU infrastructure

Summary: MAGI is a web service for fast MicroRNA-Seq data analysis in a graphics processing unit (GPU) infrastructure. Using just a browser, users have access to results as web reports in just a few hours—>600% end-to-end performance improvement over state of the art. MAGI’s salient features are (i) transfer of large input files in native FASTA with Qualities (FASTQ) format through drag-and-drop operations, (ii) rapid prediction of microRNA target genes leveraging parallel computing with GPU devices, (iii) all-in-one analytics with novel feature extraction, statistical test for differential expression and diagnostic plot generation for quality control and (iv) interactive visualization and exploration of results in web reports that are readily available for publication.

Availability and implementation: MAGI relies on the Node.js JavaScript framework, along with NVIDIA CUDA C, PHP: Hypertext Preprocessor (PHP), Perl and R. It is freely available at http://magi.ucsd.edu.

Contact:j5kim@ucsd.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

CAP-miRSeq: a comprehensive analysis pipeline for microRNA sequencing data

Background

miRNAs play a key role in normal physiology and various diseases. miRNA profiling through next generation sequencing (miRNA-seq) has become the main platform for biological research and biomarker discovery. However, analyzing miRNA sequencing data is challenging as it needs significant amount of computational resources and bioinformatics expertise. Several web based analytical tools have been developed but they are limited to processing one or a pair of samples at time and are not suitable for a large scale study. Lack of flexibility and reliability of these web applications are also common issues.

Results

We developed a Comprehensive Analysis Pipeline for microRNA Sequencing data (CAP-miRSeq) that integrates read pre-processing, alignment, mature/precursor/novel miRNA detection and quantification, data visualization, variant detection in miRNA coding region, and more flexible differential expression analysis between experimental conditions. According to computational infrastructure, users can install the package locally or deploy it in Amazon Cloud to run samples sequentially or in parallel for a large number of samples for speedy analyses. In either case, summary and expression reports for all samples are generated for easier quality assessment and downstream analyses. Using well characterized data, we demonstrated the pipeline’s superior performances, flexibility, and practical use in research and biomarker discovery.

Conclusions

CAP-miRSeq is a powerful and flexible tool for users to process and analyze miRNA-seq data scalable from a few to hundreds of samples. The results are presented in the convenient way for investigators or analysts to conduct further investigation and discovery.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-423) contains supplementary material, which is available to authorized users.

eRNA: a graphic user interface-based tool optimized for large data analysis from high-throughput RNA sequencing

BACKGROUND

RNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers.

RESULTS

We developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification" includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module "mRNA identification" includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module "Target screening" provides expression profiling analyses and graphic visualization. The module "Self-testing" offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program's functionality.

CONCLUSIONS

eRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory.

Computational developments in microRNA-regulated protein-protein interactions

Protein-protein interaction (PPI) is one of the most important functional components of a living cell. Recently, researchers have been interested in investigating the correlation between PPI and microRNA, which has been found to be a regulator at the post-transcriptional level. Studies on miRNA-regulated PPI networks will not only facilitate an understanding of the fine tuning role that miRNAs play in PPI networks, but will also provide potential candidates for tumor diagnosis. This review describes basic studies on the miRNA-regulated PPI network in the way of bioinformatics which includes constructing a miRNA-target protein network, describing the features of miRNA-regulated PPI networks and overviewing previous findings based on analysing miRNA-regulated PPI network features.

Computational approaches in detecting non- coding RNA

The important role of non coding RNAs (ncRNAs) in the cell has made their identification a critical issue in the biological research. However, traditional approaches such as PT-PCR and Northern Blot are costly. With recent progress in bioinformatics and computational prediction technology, the discovery of ncRNAs has become realistically possible. This paper aims to introduce major computational approaches in the identification of ncRNAs, including homologous search, de novo prediction and mining in deep sequencing data. Furthermore, related software tools have been compared and reviewed along with a discussion on future improvements.

Sequencing small RNA: introduction and data analysis fundamentals

Small RNAs are important transcriptional regulators within cells. With the advent of powerful Next Generation Sequencing platforms, sequencing small RNAs seems to be an obvious choice to understand their expression and its downstream effect. Additionally, sequencing provides an opportunity to identify novel and polymorphic miRNA. However, the biggest challenge is the appropriate data analysis pipeline, which is still in phase of active development by various academic groups. This chapter describes basic and advanced steps for small RNA sequencing analysis including quality control, small RNA alignment and quantification, differential expression analysis, novel small RNA identification, target prediction, and downstream analysis. We also provide a list of various resources for small RNA analysis.

Computational prediction of microRNA genes

The computational identification of novel microRNA (miRNA) genes is a challenging task in bioinformatics. Massive amounts of data describing unknown functional RNA transcripts have to be analyzed for putative miRNA candidates with automated computational pipelines. Beyond those miRNAs that meet the classical definition, high-throughput sequencing techniques have revealed additional miRNA-like molecules that are derived by alternative biogenesis pathways. Exhaustive bioinformatics analyses on such data involve statistical issues as well as precise sequence and structure inspection not only of the functional mature part but also of the whole precursor sequence of the putative miRNA. Apart from a considerable amount of species-specific miRNAs, the majority of all those genes are conserved at least among closely related organisms. Some miRNAs, however, can be traced back to very early points in the evolution of eukaryotic species. Thus, the investigation of the conservation of newly found miRNA candidates comprises an important step in the computational annotation of miRNAs.Topics covered in this chapter include a review on the obvious problem of miRNA annotation and family definition, recommended pipelines of computational miRNA annotation or detection, and an overview of current computer tools for the prediction of miRNAs and their limitations. The chapter closes discussing how those bioinformatic approaches address the problem of faithful miRNA prediction and correct annotation.

High-throughput approaches for microRNA expression analysis

Profiling microRNA (miRNA) expression is of widespread interest due to their critical roles in diverse biological processes, including development, cell proliferation, differentiation, and apoptosis. Profiling can be achieved via three major methods: amplification-based (real-time quantitative PCR, qRT-PCR), hybridization-based (microarrays), and sequencing-based (next-generation sequencing (NGS)) technologies. The gold standard is qRT-PCR and serves as a platform for single reverse PCR amplification experiments and for a large number of miRNAs in parallel, both by multiplexing and plate based arrays. Currently, qRT-PCR is used for the validation of miRNA profiling results from other platforms. Hybridization based miRNA profiling by microarrays has become a widely used method especially for biomarker and therapeutic target identification. The data obtained from microarrays also enables functional prediction of miRNAs by correlating miRNA expression patterns to corresponding mRNA and protein profiles. Additionally, miRNA profiling strategies based on deep sequencing allow both the identification of novel miRNAs and relative quantification of miRNAs. Each miRNA profiling strategy has specific strengths and challenges that have to be considered depending on the nature of the research context.In this chapter the high-throughput approaches that can be applied to microRNA profiling are discussed starting from small-scale qRT-PCR technology to a wider one, NGS.

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.

ISRNA: an integrative online toolkit for short reads from high-throughput sequencing data

Integrative Short Reads NAvigator (ISRNA) is an online toolkit for analyzing high-throughput small RNA sequencing data. Besides the high-speed genome mapping function, ISRNA provides statistics for genomic location, length distribution and nucleotide composition bias analysis of sequence reads. Number of reads mapped to known microRNAs and other classes of short non-coding RNAs, coverage of short reads on genes, expression abundance of sequence reads as well as some other analysis functions are also supported. The versatile search functions enable users to select sequence reads according to their sub-sequences, expression abundance, genomic location, relationship to genes, etc. A specialized genome browser is integrated to visualize the genomic distribution of short reads. ISRNA also supports management and comparison among multiple datasets.

AVAILABILITY

ISRNA is implemented in Java/C++/Perl/MySQL and can be freely accessed at http://omicslab.genetics.ac.cn/ISRNA/.