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We read with interest the recent article by Roth and colleagues [1] reporting the findings of altered tumorspecific microRNAs (miRNAs) in sera of breast cancer patients. This report further substantiates emerging data suggesting that blood-based miRNAs have immense potential as novel non-invasive cancer biomarkers. However, we have several concerns regarding the authors' study. Roth and colleagues claim this article to be the first evidence that circulating miRNAs have potential as breast cancer biomarkers, yet refer to previous reports of similar findings [2,3]. This aside, other claims in the study are unsubstantiated. Firstly, the finding that total RNA levels were significantly higher in M0 patients compared to controls and M1 breast cancer patients most likely reflects the quality of RNA extraction techniques and is not clinically relevant. We have previously demonstrated that total RNA levels differ significantly depending on the RNA isolation method and starting blood medium [2]. The authors have not adequately discussed their finding that patients with metastatic disease had significantly lower total RNA levels compared to M0 patients; if their claim that total RNA concentration indicated tumour progression held truth, then one would expect a sequential increase in total RNA concentration from controls, to M0 and M1 patients. The four candidate miRNAs (miR-10b, miR-34a, miR-141, and miR-155) selected by Roth and colleagues for analysis is contentious. Evidence demonstrating consistent differential expression of this miRNA panel in breast tumours, and functionality in breast tumour genesis and progression, is lacking. Given that currently 1,212 mature human miRNAs have been identified (miRBase, release 16 September 2010 [4]), and others strongly associated with breast cancer, there are more appropriate miRNAs worthy of consideration as breast cancer biomarkers. Another concerning issue is the time-point at which serum samples were obtained from patients. Our group has previously demonstrated that circulating miRNAs that are elevated in breast cancer patients when the tumour is in situ (miR-195 and let-7a) decrease to basal levels by 2 weeks post-tumour resection. Whilst the half-life of tumour-associated miRNAs in blood is undefined, ours and other studies would suggest that it is less than 14 days [5]. The authors' samples were obtained from M0 patients as late as 4 weeks post-operatively, at which time there would have been no disease, or at most microscopic foci, remaining. As the authors' primary aim was to evaluate the feasibility of using circulating miRNAs for detection and staging of breast cancer, it would have been prudent to obtain blood samples pre-operatively. We do believe that blood-based miRNA analysis has imminent clinical utility as tumour markers. However, if this concept is to translate readily from bench to bedside, then supporting data demonstrating feasibility and validity of this novel approach must stem from carefully planned and well-designed studies. If the current momentum in miRNA translational research can be maintained, then an era of non-invasive rapid diagnostics and individualized care for breast cancer patients is rapidly forthcoming.

Common fragile sites (CFSs) are regions of the genome with a predisposition to DNA double-strand breaks in response to intrinsic (oncogenic) or extrinsic replication stress. CFS breakage is a common feature in carcinogenesis from its earliest stages. Given that a number of oncogenes and tumor suppressors are located within CFSs, a question that emerges is whether fragility in these regions is only a structural "passive" incident or an event with a profound biological effect. Furthermore, there is sparse evidence that other elements, like non-coding RNAs, are positioned with them. By analyzing data from various libraries, like miRbase and ENCODE, we show a prevalence of various cancer-related genes, miRNAs, and regulatory binding sites, such as CTCF within CFSs. We propose that CFSs are not only susceptible structural domains, but highly organized "functional" entities that when targeted, severe repercussion for cell homeostasis occurs.

Background: Recently, regulatory T (Treg) cells have gained interest in the fields of immunopathology, transplantation and oncoimmunology. Here, we investigated the microRNA expression profile of human natural CD8+CD25+ Treg cells and the impact of microRNAs on molecules associated with immune regulation.Methods: We purified human natural CD8+ Treg cells and assessed the expression of FOXP3 and CTLA-4 by flow cytometry. We have also tested the ex vivo suppressive capacity of these cells in mixed leukocyte reactions. Using TaqMan low-density arrays and microRNA qPCR for validation, we could identify a microRNA 'signature' for CD8+CD25+FOXP3+CTLA-4+ natural Treg cells. We used the 'TargetScan' and 'miRBase' bioinformatics programs to identify potential target sites for these microRNAs in the 3′-UTR of important Treg cell-associated genes.Results: The human CD8+CD25+ natural Treg cell microRNA signature includes 10 differentially expressed microRNAs. We demonstrated an impact of this signature on Treg cell biology by showing specific regulation of FOXP3, CTLA-4 and GARP gene expression by microRNA using site-directed mutagenesis and a dual-luciferase reporter assay. Furthermore, we used microRNA transduction experiments to demonstrate that these microRNAs impacted their target genes in human primary Treg cells ex vivo.Conclusions: We are examining the biological relevance of this 'signature' by studying its impact on other important Treg cell-associated genes. These efforts could result in a better understanding of the regulation of Treg cell function and might reveal new targets for immunotherapy in immune disorders and cancer., SCOPUS: ar.j, info:eu-repo/semantics/published

Background Although miRNAs are reportedly involved in the salt stress tolerance of plants, miRNA profiling in plants has largely remained restricted to glycophytes, including certain crop species that do not exhibit any tolerance to salinity. Hence, this manuscript describes the results from the miRNA profiling of the halophyte Suaeda maritima, which is used worldwide to study salt tolerance in plants. Results A total of 134 conserved miRNAs were identified from unique sRNA reads, with 126 identified using miRBase 21.0 and an additional eight identified using the Plant Non-coding RNA Database. The presence of the precursors of seven conserved miRNAs was validated in S. maritima. In addition, 13 novel miRNAs were predicted using the ESTs of two mangrove plants, Rhizophora mangle and Heritiera littoralis, and the precursors of seven miRNAs were found in S. maritima. Most of the miRNAs considered for characterization were responsive to NaCl application, indicating their importance in the regulation of metabolic activities in plants exposed to salinity. An expression study of the novel miRNAs in plants of diverse ecological and taxonomic groups revealed that two of the miRNAs, sma-miR6 and sma-miR7, were also expressed in Oryza sativa, whereas another two, sma-miR2 and sma-miR5, were only expressed in plants growing under the influence of seawater, similar to S. maritima. Conclusion The distribution of conserved miRNAs among only 25 families indicated the possibility of identifying a greater number of miRNAs with increase in knowledge of the genomes of more halophytes. The expression of two novel miRNAs, sma-miR2 and sma-miR5, only in plants growing under the influence of seawater suggested their metabolic regulatory roles specific to saline environments, and such behavior might be mediated by alterations in the expression of certain genes, modifications of proteins leading to changes in their activity and production of secondary metabolites as revealed by the miRNA target predictions. Moreover, the auxin responsive factor targeted by sma-miR7 could also be involved in salt tolerance because the target is conserved between species. This study also indicated that the transcriptome of one species can be successfully used to computationally predict the miRNAs in other species, especially those that have similar metabolism, even if they are taxonomically separated. Electronic supplementary material The online version of this article (doi:10.1186/s12870-015-0682-3) contains supplementary material, which is available to authorized users.

Background The begomoviruses are the largest and most economically important group of plant viruses exclusively vectored by whitefly (Bemisia tabaci) in a circulative, persistent manner. During this process, begomoviruses and whitefly vectors have developed close relationships and complex interactions. However, the molecular mechanisms underlying these interactions remain largely unknown, and the microRNA profiles for viruliferous and nonviruliferous whiteflies have not been studied. Methods Sequences of Argonaute 1(Ago1) and Dicer 1 (Dcr1) genes were cloned from B. tabaci MEAM1 cDNAs. Subsequently, deep sequencing of small RNA libraries from uninfected and Tomato yellow leaf curl China virus (TYLCCNV)-infected whiteflies was performed. The conserved and novel miRNAs were identified using the release of miRBase Version 19.0 and the prediction software miRDeep2, respectively. The sequencing results of selected deregulated and novel miRNAs were further confirmed using quantitative reverse transcription-PCR. Moreover, the previously published B. tabaci MEAM1 transcriptome database and the miRNA target prediction algorithm miRanda 3.1 were utilized to predict potential targets for miRNAs. Gene Ontology (GO) analysis was also used to classify the potential enriched functional groups of their putative targets. Results Ago1 and Dcr1orthologs with conserved domains were identified from B. tabaci MEAM1. BLASTn searches and sequence analysis identified 112 and 136 conserved miRNAs from nonviruliferous and viruliferous whitefly libraries respectively, and a comparison of the conserved miRNAs of viruliferous and nonviruliferous whiteflies revealed 15 up- and 9 down-regulated conserved miRNAs. 7 novel miRNA candidates with secondary pre-miRNA hairpin structures were also identified. Potential targets of conserved and novel miRNAs were predicted using GO analysis, for the targets of up- and down-regulated miRNAs, eight and nine GO terms were significantly enriched. Conclusions We identified Ago1 and Dcr1 orthologs from whiteflies, which indicated that miRNA-mediated silencing is present in whiteflies. Our comparative analysis of miRNAs from TYLCCNV viruliferous and nonviruliferous whiteflies revealed the relevance of deregulated miRNAs for the post-transcriptional gene regulation in these whiteflies. The potential targets of all expressed miRNAs were also predicted. These results will help to acquire a better understanding of the molecular mechanism underlying the complex interactions between begomoviruses and whiteflies. Electronic supplementary material The online version of this article (doi:10.1186/s12985-016-0469-7) contains supplementary material, which is available to authorized users.

Background microRNA166 (miR166) is a highly conserved family of miRNAs implicated in a wide range of cellular and physiological processes in plants. miR166 family generally comprises multiple miR166 members in plants, which might exhibit functional redundancy and specificity. The soybean miR166 family consists of 21 members according to the miRBase database. However, the evolutionary conservation and functional diversification of miR166 family members in soybean remain poorly understood. Results We identified five novel miR166s in soybean by data mining approach, thus enlarging the size of miR166 family from 21 to 26 members. Phylogenetic analyses of the 26 miR166s and their precursors indicated that soybean miR166 family exhibited both evolutionary conservation and diversification, and ten pairs of miR166 precursors with high sequence identity were individually grouped into a discrete clade in the phylogenetic tree. The analysis of genomic organization and evolution of MIR166 gene family revealed that eight segmental duplications and four tandem duplications might occur during evolution of the miR166 family in soybean. The cis-elements in promoters of MIR166 family genes and their putative targets pointed to their possible contributions to the functional conservation and diversification. The targets of soybean miR166s were predicted, and the cleavage of ATHB14-LIKE transcript was experimentally validated by RACE PCR. Further, the expression patterns of the five newly identified MIR166s and 12 target genes were examined during seed development and in response to abiotic stresses, which provided important clues for dissecting their functions and isoform specificity. Conclusion This study enlarged the size of soybean miR166 family from 21 to 26 members, and the 26 soybean miR166s exhibited evolutionary conservation and diversification. These findings have laid a foundation for elucidating functional conservation and diversification of miR166 family members, especially during seed development or under abiotic stresses. Electronic supplementary material The online version of this article (doi:10.1186/s12870-017-0983-9) contains supplementary material, which is available to authorized users.

Background MicroRNAs (miRNAs) are small ~22 nucleotide non-coding RNAs that function as post-transcriptional regulators of messenger RNA (mRNA) through base-pairing to 6–8 nucleotide long target sites, usually located within the mRNA 3’ untranslated region. A common approach to validate and probe microRNA-mRNA interactions is to mutate predicted target sites within the mRNA and determine whether it affects miRNA-mediated activity. The introduction of miRNA target site mutations, however, is potentially problematic as it may generate new, “illegitimate sites” target sites for other miRNAs, which may affect the experimental outcome. While it is possible to manually generate and check single miRNA target site mutations, this process can be time consuming, and becomes particularly onerous and error prone when multiple sites are to be mutated simultaneously. We have developed a modular Java-based system called ImiRP (Illegitimate miRNA Predictor) to solve this problem and to facilitate miRNA target site mutagenesis. Results The ImiRP interface allows users to input a sequence of interest, specify the locations of multiple predicted target sites to mutate, and set parameters such as species, mutation strategy, and disallowed illegitimate target site types. As mutant sequences are generated, ImiRP utilizes the miRBase high confidence miRNA dataset to identify illegitimate target sites in each mutant sequence by comparing target site predictions between input and mutant sequences. ImiRP then assembles a final mutant sequence in which all specified target sites have been mutated. Conclusions ImiRP is a mutation generator program that enables selective disruption of specified miRNA target sites while ensuring predicted target sites for other miRNAs are not inadvertently created. ImiRP supports mutagenesis of single and multiple miRNA target sites within a given sequence, including sites that overlap. This software will be particularly useful for studies looking at microRNA cooperativity, where mutagenesis of multiple microRNA target sites may be desired. The software is available at imirp.org and is available open source for download through GitHub (https://github.com/imirp). Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1057-y) contains supplementary material, which is available to authorized users.

Background MicroRNAs (miRNAs) are endogenous small RNAs that play a key role in post-transcriptional regulation of gene expression in animals and plants. The number of known miRNAs has increased rapidly over the years. The current release (version 14.0) of miRBase, the central online repository for miRNA annotation, comprises over 10.000 miRNA precursors from 115 different species. Furthermore, a large number of decentralized online resources are now available, each contributing with important miRNA annotation and information. Results We have developed a software framework, designated here as miRMaid, with the goal of integrating miRNA data resources in a uniform web service interface that can be accessed and queried by researchers and, most importantly, by computers. miRMaid is built around data from miRBase and is designed to follow the official miRBase data releases. It exposes miRBase data as inter-connected web services. Third-party miRNA data resources can be modularly integrated as miRMaid plugins or they can loosely couple with miRMaid as individual entities in the World Wide Web. miRMaid is available as a public web service but is also easily installed as a local application. The software framework is freely available under the LGPL open source license for academic and commercial use. Conclusion miRMaid is an intuitive and modular software platform designed to unify miRBase and independent miRNA data resources. It enables miRNA researchers to computationally address complex questions involving the multitude of miRNA data resources. Furthermore, miRMaid constitutes a basic framework for further programming in which microRNA-interested bioinformaticians can readily develop their own tools and data sources.

Background Micro RNAs (miRNAs) are a class of small (~21 nucleotide) non-coding RNAs that recently gained much attention due to their perceived role as master regulators of gene expression in Eukaryotes, responsible for fine tuning gene expression regulation and, in plants, has been shown to be involved in a diverse range of biological processes such as plant development and architecture, flowering, cell differentiation and response to biotic and abiotic stresses [1]. The repertoire of expressed miRNAs differs among cell types, tissues, development, environmental condition, etc [2]. Notwithstanding, the exact function of thousands miRNAs sequences present in miRBase [http://www.mirbase.org/] is not elucidated. At this point, discovery and profiling of new and conserved miRNAs are critical in the attempt to understand their function and mechanism. Deep sequencing through next generation sequencing is the methodology of choice for this purpose as its ultra high throughput permits a comprehensive interrogation of the small RNA transcriptome, permitting de novo identification and relative quantification of different small RNA species [3]. Due to its economic importance the Eucalyptus grandis genome has been sequenced by JGI and the annotation of miRNAs is pivotal. In order to provide the first large scale experimental characterization of Eucalyptus miRNAs we performed an Illumina deep sequencing run that allowed us to discover and quantify the miRNA levels in two different tissues – xylem and leaves. Additionally, to get insights of the observed phenotypic differences in wood quality among Eucalyptus species, we characterized the xylem small RNA transcriptome of two different E. globulus individuals and

Bovine Leukemia Virus (BLV), a delta-retrovirus related to humanT-cell leukemia virus-1 (HTLV-1), is associated with the development of B-cell leukemia in experimentally-infected sheep. Using this outbred animal model of B-cell transformation, oncogenic modifications reflected in altered microRNA expression can be identified and compared as the disease progresses. We have analyzed the miRNome of transformed B-cells isolated from leukemic sheep. Using Taqman Low Density Array (TLDA) assays and High-Throughput (HT) sequencing of small RNA libraries, we identified differentially-expressed microRNAs associated with B-cell transformation. For miRBase database-matched sheep orthologs there was a good overall quantitative correlation between data generated with both techniques. Furthermore, deep sequencing identified variants of mature microRNA transcripts, indicating that isomir distribution might be of biological significance. Finally, HT sequencing revealed unknown candidate microRNAs which were confirmed both in silico using miRDeep and experimentally using stem-loop RT-QPCR methods. Target prediction tools (miRanda, targetscan) suggest that these microRNAs might target both cellular and viral mRNAs. Down-regulation of viral mRNAs might contribute to tumor-associated virus silencing and play a role in immune escape mechanisms. Ongoing work aims at the validation of bioinformatics predictions of microRNA targets. Altogether, this work should lead to a better understanding of the microRNA-mRNA regulation network associated with leukemia progression.

Background Worldwide, but especially in developing countries, coenurosis of sheep and other livestock is caused by Taenia multiceps larvae, and zoonotic infections occur in humans. Infections frequently lead to host death, resulting in huge socioeconomic losses. MicroRNAs (miRNAs) have important roles in the post-transcriptional regulation of a large number of animal genes by imperfectly binding target mRNAs. To date, there have been no reports of miRNAs in T. multiceps. Results In this study, we obtained 12.8 million high quality raw reads from adult T. multiceps small RNA library using Illumina sequencing technology. A total of 796 conserved miRNA families (containing 1,006 miRNAs) from 170,888 unique miRNAs were characterized using miRBase (Release 17.0). Here, we selected three conserved miRNA/miRNA* (antisense strand) duplexes at random and amplified their corresponding precursors using a PCR-based method. Furthermore, 20 candidate novel miRNA precursors were verified by genomic PCR. Among these, six corresponding T. multiceps miRNAs are considered specific for Taeniidae because no homologs were found in other species annotated in miRBase. In addition, 181,077 target sites within T. multiceps transcriptome were predicted for 20 candidate newly miRNAs. Conclusions Our large-scale investigation of miRNAs in adult T. multiceps provides a substantial platform for improving our understanding of the molecular regulation of T. multiceps and other cestodes development.

Background MicroRNAs (miRNAs) are small non-coding RNAs affecting the expression of target genes via translational repression or mRNA degradation mechanisms. With the increasing availability of mRNA and miRNA expression data, it might be possible to assess functional targets using the fact that a miRNA might down-regulate its target mRNAs. In this work we computed the correlation of expression profiles between miRNAs and target mRNAs using the NCI-60 expression data. The aim is to investigate whether the correlations between miRNA and mRNA expression profiles, either positive or negative, can be used to assist the identification of functional miRNA-mRNA relationships. Results Predicted miRNA-mRNA interactions were taken from TargetScan 4.1 and miRBase release 5. Pearson correlation coefficients between the miRNA and the mRNA expression profiles were computed using NCI-60 data. The correlation coefficients were then subject to the Benjamini and Hochberg correction. Our results show that the percentage of TargetScan-predicted miRNA-mRNA interactions having negative correlation in expression profiles is higher than that of miRBase-predicted pairs. Using the experimentally validated miRNA targets listed in TarBase, genes involved in mRNA degradation show more negative correlations between miRNA and mRNA expression profiles, comparing with genes involved in translational repression. Furthermore, correlation analysis for miRNAs and mRNAs transcribed from the same genes shows that correlations of expression profiles between intronic miRNAs and host genes tend to be positive. Finally we found that a target gene might be down-regulated by more than one miRNAs sharing the same seed region. Conclusion Our results suggest that expression profiles can be used in the computational identification of functional miRNA-target associations. One can expect a higher chance of finding negatively correlated expression profiles for TargetScan-predicted interactions than for miRBase-predicted ones. With limited experimentally validated miRNA-target interactions, expression profiles can only serve as a supplementary role in finding interactions between miRNAs and mRNAs.

Background MicroRNAs (miRNAs) are a set of small non-coding RNAs serving as important negative gene regulators. In animals, miRNAs turn down protein translation by binding to the 3' UTR regions of target genes with imperfect complementary pairing. The identification of microRNA targets has become one of the major challenges of miRNA research. Bioinformatics investigations on miRNA target have resulted in a number of target prediction tools. Although these tools are capable of predicting hundreds of targets for a given miRNA, many of them suffer from high false positive rates, indicating the need for a post-processing filter for the predicted targets. Once trained with experimentally validated true and false targets, machine learning methods appear to be ideal approaches to distinguish the true targets from the false ones. Results We present a miRNA target filtering system named MiRTif (miRNA:target interaction filter). The system is a support vector machine (SVM) classifier trained with 195 positive and 38 negative miRNA:target interaction pairs, all experimentally validated. Each miRNA:target interaction pair is divided into a seed and a non-seed region. The encoded feature vector contains various k-gram frequencies in the seed, the non-seed and the entire regions. Informative features are selected based on their discriminating abilities. Prediction accuracies are assessed using 10-fold cross-validation experiments. Our system achieves AUC (area under the ROC curve) of 0.86, sensitivity of 83.59%, and specificity of 73.68%. More importantly, the system correctly predicts majority of the false positive miRNA:target interactions (28 out of 38). The possibility of over-fitting due to the relatively small negative sample set has also been investigated using a set of non-validated and randomly selected targets (from miRBase). Conclusion MiRTif is designed as a post-processing filter that takes miRNA:target interactions predicted by other target prediction softwares such as TargetScanS, PicTar and miRanda as inputs, and determines how likely the given interaction is a real or a pseudo one. MiRTif can be accessed from http://bsal.ym.edu.tw/mirtif.

Background Micro(mi)RNAs are short RNA sequences, ranging from 16 to 35 nucleotides (miRBase; http://www.mirbase.org). The majority of the identified sequences are 21 or 22 nucleotides in length. Despite the range of sequence lengths for different miRNAs, individual miRNAs were thought to have a specific sequence of a particular length. A recent report describing a longer variant of a previously identified miRNA in Arabidopsis thaliana prompted this investigation for variations in the length of other miRNAs. Results In this paper, we demonstrate that a fifth of annotated A. thaliana miRNAs recorded in miRBase V.14 have stable miRNA isoforms that are one or two nucleotides longer than their respective recorded miRNA. Further, we demonstrate that miRNA isoforms are co-expressed and often show differential argonaute complex association. We postulate that these extensions are caused by differential cleavage of the parent precursor miRNA. Conclusions Our systematic analysis of A. thaliana miRNAs reveals that miRNA length isoforms are relatively common. This finding not only has implications for miRBase and miRNA annotation, but also extends to miRNA validation experiments and miRNA localization studies. Further, we predict that miRNA isoforms are present in other plant species also.

Background MicroRNAs (miRNAs) are small RNAs (21-24 bp) providing an RNA-based system of gene regulation highly conserved in plants and animals. In plants, miRNAs control mRNA degradation or restrain translation, affecting development and responses to stresses. Plant miRNAs show imperfect but extensive complementarity to mRNA targets, making their computational prediction possible, useful when data mining is applied on different species. In this study we used a comparative approach to identify both miRNAs and their targets, in artichoke and safflower. Results Two complete expressed sequence tags (ESTs) datasets from artichoke (3.6·104 entries) and safflower (4.2·104), were analysed with a bioinformatic pipeline and in vitro experiments, identifying 17 potential miRNAs. For each EST, using RNAhybrid program and 953 non redundant miRNA mature sequences, available in mirBase as reference, we searched matching putative targets. 8730 out of 42011 ESTs from safflower and 7145 of 36323 ESTs from artichoke showed at least one predicted miRNA target. BLAST analysis showed that 75% of all ESTs shared at least a common homologous region (E-value < 10-4) and about 50% of these displayed 400 bp or longer aligned sequences as conserved homologous/orthologous (COS) regions. 960 and 890 ESTs of safflower and artichoke organized in COS shared 79 different miRNA targets, considered functionally conserved, and statistically significant when compared with random sequences (signal to noise ratio > 2 and specificity ≥ 0.85). Four highly significant miRNAs selected from in silico data were experimentally validated in globe artichoke leaves. Conclusions Mature miRNAs and targets were predicted within EST sequences of safflower and artichoke. Most of the miRNA targets appeared highly/moderately conserved, highlighting an important and conserved function. In this study we introduce a stringent parameter for the comparative sequence analysis, represented by the identification of the same target in the COS region. After statistical analysis 79 targets, found on the COS regions and belonging to 60 miRNA families, have a signal to noise ratio > 2, with ≥ 0.85 specificity. The putative miRNAs identified belong to 55 dicotyledon plants and to 24 families only in monocotyledon.

Background MicroRNAs (miRNAs) play critical roles in a wide spectrum of biological processes and have been shown to be important effectors in the intricate host-pathogen interaction networks. Avian influenza virus (AIV) not only causes significant economic losses in poultry production, but also is of great concern to human health. The objective of this study was to identify miRNAs associated with AIV infections in chickens. Results Total RNAs were isolated from lung and trachea of low pathogenic H5N3 infected and non-infected SPF chickens at 4 days post-infection. A total of 278,398 and 340,726 reads were obtained from lung and trachea, respectively. And 377 miRNAs were detected in lungs and 149 in tracheae from a total of 474 distinct chicken miRNAs available at the miRBase, respectively. Seventy-three and thirty-six miRNAs were differentially expressed between infected and non-infected chickens in lungs and tracheae, respectively. There were more miRNAs highly expressed in non-infected tissues than in infected tissues. Interestingly, some of these differentially expressed miRNAs, including miR-146, have been previously reported to be associated with immune-related signal pathways in mammals. Conclusion To our knowledge, this is the first study on miRNA gene expression in AIV infected chickens using a deep sequencing approach. During AIV infection, many host miRNAs were differentially regulated, supporting the hypothesis that certain miRNAs might be essential in the host-pathogen interactions. Elucidation of the mechanism of these miRNAs on the regulation of host-AIV interaction will lead to the development of new control strategies to prevent or treat AIV infections in poultry.

Background MicroRNAs (miRNAs) are endogenous ∼22 nt RNAs that are identified in many species as powerful regulators of gene expressions. Experimental identification of miRNAs is still slow since miRNAs are difficult to isolate by cloning due to their low expression, low stability, tissue specificity and the high cost of the cloning procedure. Thus, computational identification of miRNAs from genomic sequences provide a valuable complement to cloning. Different approaches for identification of miRNAs have been proposed based on homology, thermodynamic parameters, and cross-species comparisons. Results The present paper focuses on the integration of miRNA classifiers in a meta-classifier and the identification of miRNAs from metagenomic sequences collected from different environments. An ensemble of classifiers is proposed for miRNA hairpin prediction based on four well-known classifiers (Triplet SVM, Mipred, Virgo and EumiR), with non-identical features, and which have been trained on different data. Their decisions are combined using a single hidden layer neural network to increase the accuracy of the predictions. Our ensemble classifier achieved 89.3% accuracy, 82.2% f–measure, 74% sensitivity, 97% specificity, 92.5% precision and 88.2% negative predictive value when tested on real miRNA and pseudo sequence data. The area under the receiver operating characteristic curve of our classifier is 0.9 which represents a high performance index. The proposed classifier yields a significant performance improvement relative to Triplet-SVM, Virgo and EumiR and a minor refinement over MiPred. The developed ensemble classifier is used for miRNA prediction in mine drainage, groundwater and marine metagenomic sequences downloaded from the NCBI sequence reed archive. By consulting the miRBase repository, 179 miRNAs have been identified as highly probable miRNAs. Our new approach could thus be used for mining metagenomic sequences and finding new and homologous miRNAs. Conclusions The paper investigates a computational tool for miRNA prediction in genomic or metagenomic data. It has been applied on three metagenomic samples from different environments (mine drainage, groundwater and marine metagenomic sequences). The prediction results provide a set of extremely potential miRNA hairpins for cloning prediction methods. Among the ensemble prediction obtained results there are pre-miRNA candidates that have been validated using miRbase while they have not been recognized by some of the base classifiers.