Progress in miRNA target prediction and identification

Recently, the identification of miRNA targets has received much attention. The strategies to determine miRNA targets include bioinformatic prediction and experimental assays. The bioinformatic prediction methods are mainly based on the confirmed rules of interaction between miRNAs and their targets, and are carried out by programs, such as miRanda, TargetScan, TargetScanS, RNAhybrid, DIANA-microT, PicTar, RNA22 and FindTar, which follow well-known principles. The experimental assays to find miRNA targets employ immunoprecipitation of AGO proteins to identify interacting mRNAs, or the analysis of mRNA or protein levels to identify genes which can be regulated by miRNAs. The improvement of current bioinformatic and experimental assays and the development of novel assays will enable greater efficiency in the identification of miRNA targets and thus facilitate miRNA research. This paper describes progress in the prediction and identification of miRNA targets.     

miRTour: Plant miRNA and target prediction tool

MicroRNAs (miRNAs) are important negative regulators of gene expression in plant and animals, which are endogenously produced from their own genes. Computational comparative approach based on evolutionary conservation of mature miRNAs has revealed a number of orthologs of known miRNAs in different plant species. The homology-based plant miRNA discovery, followed by target prediction, comprises several steps, which have been done so far manually. Here, we present the bioinformatics pipeline miRTour which automates all the steps of miRNA similarity search, miRNA precursor selection, target prediction and annotation, each of them performed with the same set of input sequences. AVAILABILITY: The database is available for free at http://bio2server.bioinfo.uni-plovdiv.bg/miRTour/     

通过miRNA基因表达谱的基因共表达网络构建对星形细胞瘤的基因靶标进行预测

星形细胞瘤为浸润性生长肿瘤,生长缓慢,多为隐形症状,难以早期发现。多数肿瘤切除后有复发可能,且复发后肿瘤可演变成间变性星形细胞瘤或多形性胶质母细胞瘤。因此寻找其生物标志物早期诊断,并研究新的治疗方法就十分重要。方法:通过选用GEO数据库的星形细胞瘤miRNA表达谱数据,进行差异分析以及靶基因预测,通过2者共表达网络的构建对筛选出的miRNA的研究价值进行探讨。结果:得出hsa-miR-29b-2-5p;hsa-miR-339-5p与hsa-miR-362-3p3个较为关键的miRNA及与3者关系密切的8个mRNA。结论:通过对8个mRNA在癌症中的作用的讨论,肯定了这3个关键miRNA作为潜在靶点的研究价值。     

埃博拉病毒来源miRNA的研究综述

近年来,随着对microRNA（miRNA）的广泛研究,人们发现,不仅有细胞结构的生物具有产生miRNA的能力,无细胞结构的病毒同样具有产生miRNA从而影响自身复制及调控宿主基因表达和信号通路的能力。埃博拉病毒（Ebola virus,EBOV）已经多次导致一定规模的流行,病毒的高致死率和复杂的致病机制引起了人们的高度重视,多项研究指出EBOV具有产生miRNA的能力,且在其感染过程中发挥一定的作用。本文对埃博拉病毒来源miRNA的预测、证实及检测相关研究进行综述,以期为全面了解EBOV来源的miRNA提供参考。     

A database for allergenic proteins and tools for allergenicity prediction

The AllergenPro database has developed a web-based system that will provide information about allergen in microbes, animals and plants. The database has three major parts and functions:(i) database list; (ii) allergen search; and (iii) allergenicity prediction. The database contains 2,434 allergens related information readily available in the database such as on allergens in rice microbes (712 records), animals (617 records) and plants (1,105 records). Furthermore, this database provides bioinformatics tools for allergenicity prediction. Users can search for specific allergens by various methods and can run tools for allergenicity prediction using three different methods.

Availability

The database is available for free at http://www.niab.go.kr/nabic/     

High performance separation technologies and spectroscopic tools for plant extract characterization in phytomics

The review is concerned with fast analytical methods for the qualitative and quantitative determination of plant constituents and phytopharmaceutical products. Emphasis is put on the determination of leading compounds, the role of the stationary phase in the analysis of sugars, phenolic compounds, proteins or DNA-mutations and the use of non-standard analytical tools such as micro high performance liquid chromatography (μ-LC) or near infrared reflectance spectroscopy (NIR) next to conventional high performance liquid chromatography (HPLC). Finally the importance of spectroscopic methods such as mass spectrometry (MS) in phytomics will be discussed giving examples for HPLC-MS and μ-HPLC-MS hyphenation. This revised version was published online in June 2006 with corrections to the Cover Date.     

Functional combination strategy for prioritization of human miRNA target

MicroRNAs (miRNAs) are a class of non-coding RNAs known to play important regulatory roles through targets, which can affect human cell proliferation, differentiation, and metabolism. Overlaps between different miRNA target prediction algorithms (MTPAs) are small, which limit the understanding of miRNA's biological functions. However, the overlaps increase on functional levels, such as Gene Ontology (GO), Protein–Protein Interaction Network (PPIN) and pathways. Here, we performed prioritization on existing predicted target sets for each miRNA by considering all the possible combinations of 7 functional levels. After analyzing the results of both single and multiple functional levels, we found that functional combination strategies including pathways and GO performed better in the prioritization of human miRNA target. The combination which performed best was “Pathway + GO BP + GO MF + GO CC + Target + PPIN”. For the prioritized result of this combination, the valid target had top ranking, and our method performed better than the MTPAs after comparison adopting the validated ranking levels. Top genes in ranking lists generated by this strategy were either validated by experiments or share same functions with the corresponding miRNA/its validated genes in disease related biological processes.     

CID-miRNA: a web server for prediction of novel miRNA precursors in human genome

microRNAs (miRNA) are a class of non-protein coding functional RNAs that are thought to regulate expression of target genes by direct interaction with mRNAs. miRNAs have been identified through both experimental and computational methods in a variety of eukaryotic organisms. Though these approaches have been partially successful, there is a need to develop more tools for detection of these RNAs as they are also thought to be present in abundance in many genomes. In this report we describe a tool and a web server, named CID-miRNA, for identification of miRNA precursors in a given DNA sequence, utilising secondary structure-based filtering systems and an algorithm based on stochastic context free grammar trained on human miRNAs. CID-miRNA analyses a given sequence using a web interface, for presence of putative miRNA precursors and the generated output lists all the potential regions that can form miRNA-like structures. It can also scan large genomic sequences for the presence of potential miRNA precursors in its stand-alone form. The web server can be accessed at http://mirna.jnu.ac.in/cidmirna/.     

miRPlant: an integrated tool for identification of plant miRNA from RNA sequencing data

Background

Small RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction.

Result

We have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram.

Conclusions

We have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills.miRPlant and its manual are freely available at http://www.australianprostatecentre.org/research/software/mirplant or http://sourceforge.net/projects/mirplant/.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-275) contains supplementary material, which is available to authorized users.     

Multiplexing RT-PCR for the detection of multiple miRNA species in small samples

MicroRNAs are short (approximately 22 nucleotides), non-coding RNAs that play critical roles in gene regulation and may be used as rapid precise diagnostic indicators of early stages of cancer. The small size of these RNAs makes detection of multiple microRNA species in very small samples problematic. Here we investigate the parameters associated with multiplexing RT-PCR to obtain relative abundance profiles of multiple microRNAs in small sample sizes down to the amount of RNA found in a single cell.     

The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease

Recent studies have established that mutations or deletions in microRNA (miRNA) processing enzymes resulting in a global decrease of miRNA expression are frequent across cancers and can be associated with a poorer prognosis. While very popular in miRNA profiling studies, it remains unclear whether miRNA microarrays are suited or not to accurately detecting global miRNA decreases seen in cancers. In this work, we analyzed the miRNA profiles of samples with global miRNA decreases using Affymetrix miRNA microarrays following the inducible genetic deletion of Dicer1. Surprisingly, up to a third of deregulated miRNAs identified upon Dicer1 depletion were found to be up-regulated following standard robust multichip average (RMA) background correction and quantile normalization, indicative of normalization bias. Our comparisons of five preprocess steps performed at the probe level demonstrated that the use of cyclic loess relying on non-miRNA small RNAs present on the Affymetrix platform significantly improved specificity and sensitivity of detection of decreased miRNAs. These findings were validated in samples from patients with prostate cancer, where conjugation of robust normal-exponential background correction with cyclic loess normalization and array weights correctly identified the greatest number of decreased miRNAs, and the lowest amount of false-positive up-regulated miRNAs. These findings highlight the importance of miRNA microarray normalization for the detection of miRNAs that are truly differentially expressed and suggest that the use of cyclic loess based on non-miRNA small RNAs can help to improve the sensitivity and specificity of miRNA profiling in cancer samples with global miRNA decrease.     

一种利用分泌型荧光素酶基因表达变化监测活细胞中miRNA活性的新方法

建立了一种以分泌型的荧光素酶Gluc为报告基因的miRNA传感器质粒(命名为Gsensor)监测活细胞中miRNA(microRNA)活性的方法。首先构建了pAAV2neo-Gluc-MCS-polyA质粒作为Gsensor的空载体,同时其中的MCS位点可供插入miRNA的靶序列。以miR142-3p为检测对象,将1个和3个拷贝的与miR142-3p完全互补靶序列分别插入pAAV2neo-Gluc-MCS-polyA中,构建成miR142-3p Gsensor和miR142-3p Gsensor-3。将它们分别转染至U937细胞中,检测培养上清中Gluc的表达水平。结果显示二者均可有效反映U937细胞中miR142-3p的抑制活性(分别与Gsensor空载体相比),提示Gsensor中采用一个拷贝的miRNA靶序列即可满足检测要求。并且miR142-3p Gsensor也能有效地反映出Anti-miR142对miR142-3p活性的抑制作用。随后,分析了时间、转染剂量对Gsensor检测结果的影响。结果表明,在U937细胞中miR142-3p Gsensor表现的miR142-3p活性在48h后趋于稳定;Gsensor转染剂量在0.001~0.05pg/cell范围内不影响其功能。最后,利用miR142-3p Gsensor检测了HEK293、U937、K562、SP2/0和P815细胞内miR142-3p活性,结果发现miR142-3p活性在U937、K562、SP2/0和P815细胞中均较高,而在HEK293中几乎没有活性。用QRT-PCR方法检测miR142-3p的相对拷贝数。结果表明,在HEK293、U937和K562细胞中,miR142-3p活性与其相对拷贝数呈正相关。本研究表明Gsensor可作为一种有效的miRNA活性检测工具,为体外实时动态监测miRNA活性提供了一种新方法。