Identification of MicroRNAs in Helicoverpa armigera and Spodoptera litura Based on Deep Sequencing and Homology Analysis

The current identification of microRNAs (miRNAs) in insects is largely dependent on genome sequences. However, the lack of available genome sequences inhibits the identification of miRNAs in various insect species. In this study, we used a miRNA database of the silkworm Bombyx mori as a reference to identify miRNAs in Helicoverpa armigera and Spodoptera litura using deep sequencing and homology analysis. Because all three species belong to the Lepidoptera, the experiment produced reliable results. Our study identified 97 and 91 conserved miRNAs in H. armigera and S. litura, respectively. Using the genome of B. mori and BAC sequences of H. armigera as references, 1 novel miRNA and 8 novel miRNA candidates were identified in H. armigera, and 4 novel miRNA candidates were identified in S. litura. An evolutionary analysis revealed that most of the identified miRNAs were insect-specific, and more than 20 miRNAs were Lepidoptera-specific. The investigation of the expression patterns of miR-2a, miR-34, miR-2796-3p and miR-11 revealed their potential roles in insect development. miRNA target prediction revealed that conserved miRNA target sites exist in various genes in the 3 species. Conserved miRNA target sites for the Hsp90 gene among the 3 species were validated in the mammalian 293T cell line using a dual-luciferase reporter assay. Our study provides a new approach with which to identify miRNAs in insects lacking genome information and contributes to the functional analysis of insect miRNAs.     

Recovery of dicer-like 1-late flowering phenotype by miR172 expressed by the noncanonical DCL4-dependent biogenesis pathway

MicroRNAs (miRNAs) act as down-regulators of gene expression, and play a dominant role in eukaryote development. In Arabidopsis thaliana, DICER-LIKE 1 (DCL1) is the main processor in miRNA biogenesis, and dcl1 mutants show various developmental defects at the early stage of embryogenesis or at gamete formation. However, miRNAs responsible for the respective developmental stages of the dcl1 defects have not been identified. Here, we developed a DCL1-independent miRNA expression system using the unique DCL4-dependent miRNA, miR839. By replacing the mature sequence in the miR839 precursor sequence with that of miR172, one of the most widely conserved miRNAs in angiosperms, we succeeded in expressing miR172 from a chimeric miR839 precursor in dcl1-7 plants and observed the repression of miR172 target gene expression. In parallel, the DCL4-dependent miR172 expression rescued the late flowering phenotype of dcl1-7 by acceleration of flowering. We established the DCL1-independent miRNA expression system, and revealed that the reduction of miR172 expression is responsible for the dcl1-7 late flowering phenotype.     

miRTar Hunter: A prediction system for identifying human microRNA target sites

MicroRNAs (miRNAs) are important regulators of gene expression and play crucial roles in many biological processes including apoptosis, differentiation, development, and tumorigenesis. Recent estimates suggest that more than 50% of human protein coding genes may be regulated by miRNAs and that each miRNA may bind to 300–400 target genes. Approximately 1,000 human miRNAs have been identified so far with each having up to hundreds of unique target mRNAs. However, the targets for a majority of these miRNAs have not been identified due to the lack of large-scale experimental detection techniques. Experimental detection of miRNA target sites is a costly and time-consuming process, even though identification of miRNA targets is critical to unraveling their functions in various biological processes. To identify miRNA targets, we developed miRTar Hunter, a novel computational approach for predicting target sites regardless of the presence or absence of a seed match or evolutionary sequence conservation. Our approach is based on a dynamic programming algorithm that incorporates more sequence-specific features and reflects the properties of various types of target sites that determine diverse aspects of complementarities between miRNAs and their targets. We evaluated the performance of our algorithm on 532 known human miRNA:target pairs and 59 experimentally-verified negative miRNA:target pairs, and also compared our method with three popular programs for 481 miRNA:target pairs. miRTar Hunter outperformed three popular existing algorithms in terms of recall and precision, indicating that our unique scheme to quantify the determinants of complementary sites is effective at detecting miRNA targets. miRTar Hunter is now available at http://203.230.194.162/~kbkim.     

Expression profiles of precursor and mature microRNAs under dehydration and high salinity shock in Populus euphratica

MicroRNAs (miRNAs) are small non-coding RNAs that play vital roles in plant abiotic stress responses via cleavage or translational inhibition of their target mRNAs. Populus euphratica is a typical stress-resistant sessile organism that grows in desert areas. Here, we identified sequences of 12 miRNA precursors from 11 families and 13 mature miRNAs from 12 families by PCR amplification in P. euphratica. To detect expression differences in mature miRNAs and their precursors under dehydration and high salinity shock in P. euphratica, we examined 14 miRNA precursors from 13 miRNA families and 17 mature miRNAs from 17 miRNA families using the SYBR Green RT–PCR assay. This is the first report of expression profiles for both precursor and mature miRNAs in P. euphratica. By profiling both the mature miRNAs and the precursors under abiotic stress shock, it was possible to identify miRNA whose processing is regulated during stress shock environments. A majority of the genes predicted to be targets for plant miRNAs are involved in development, stress resistance and metabolic processes. We have cloned and experimentally identified in vivo five of the predicted target genes and quantified the five target mRNAs from the same RNA sample simultaneously. Based on this study, we propose some regulatory pathways that illustrate the important role that miRNAs play in response to abiotic stress shock in P. euphratica.     

A bioinformatics-based update on microRNAs and their targets in rainbow trout (Oncorhynchus mykiss)

MicroRNAs (miRNAs) participate in various vitally biological processes via controlling target genes activity and thousands of miRNAs have been identified in many species to date, including 18,698 known animal miRNA in miRBase. However, there are only limited studies reported in rainbow trout (Oncorhynchus mykiss) especially via the computational-based approaches. In present study, we systematically investigated the miRNAs in rainbow trout using a well-developed comparative genome-based homologue search. A total of 196 potential miRNAs, belonging to 124 miRNA families, were identified, most of which were firstly reported in rainbow trout. The length of miRNAs ranged from 17 to 24 nt with an average of 20 nt while the length of their precursors varied from 47 to 152 nt with an average of 85 nt. The identified miRNAs were not evenly distributed in each miRNA family, with only one member per family for a majority, and multiple members were also identified for several families. Nucleotide U was dominant in the pre-miRNAs with a percentage of 30.04%. The rainbow trout pre-miRNAs had relatively high negative minimal folding free energy (MFE) and adjusted MFE (AMFE). Not only the mature miRNAs but their precursor sequences are conserved among the living organisms. About 2466 O. mykiss genes were predicted as potential targets for 189 miRNAs. Gene Ontology (GO) analysis showed that nearly 2093, 2107, and 2081 target genes are involved in cellular component, molecular function, and biological processes respectively. KEGG pathway enrichment analysis illuminated that these miRNAs targets might regulate 105 metabolic pathways, including those of purine metabolism, nitrogen metabolism, and oxidative phosphorylation. This study has provided an update on rainbow trout miRNAs and their targets, which represents a foundation for future studies.     

RNA-binding protein AUF1 represses Dicer expression

MicroRNA (miRNA) biogenesis is tightly regulated by numerous proteins. Among them, Dicer is required for the processing of the precursor (pre-)miRNAs into the mature miRNA. Despite its critical function, the mechanisms that regulate Dicer expression are not well understood. Here we report that the RNA-binding protein (RBP) AUF1 (AU-binding factor 1) associates with the endogenous DICER1 mRNA and can interact with several segments of DICER1 mRNA within the coding region (CR) and the 3′-untranslated region (UTR). Through these interactions, AUF1 lowered DICER1 mRNA stability, since silencing AUF1 lengthened DICER1 mRNA half-life and increased Dicer expression, while overexpressing AUF1 lowered DICER1 mRNA and Dicer protein levels. Given that Dicer is necessary for the synthesis of mature miRNAs, the lowering of Dicer levels by AUF1 diminished the levels of miRNAs tested, but not the levels of the corresponding pre-miRNAs. In summary, AUF1 suppresses miRNA production by reducing Dicer production.     

Tissue and Process Specific microRNA–mRNA Co-Expression in Mammalian Development and Malignancy

An association between enrichment and depletion of microRNA (miRNA) binding sites, 3′ UTR length, and mRNA expression has been demonstrated in various developing tissues and tissues from different mature organs; but functional, context-dependent miRNA regulations have yet to be elucidated. Towards that goal, we examined miRNA–mRNA interactions by measuring miRNA and mRNA in the same tissue during development and also in malignant conditions. We identified significant miRNA-mediated biological process categories in developing mouse cerebellum and lung using non-targeted mRNA expression as the negative control. Although miRNAs in general suppress target mRNA messages, many predicted miRNA targets demonstrate a significantly higher level of co-expression than non-target genes in developing cerebellum. This phenomenon is tissue specific since it is not observed in developing lungs. Comparison of mouse cerebellar development and medulloblastoma demonstrates a shared miRNA–mRNA co-expression program for brain-specific neurologic processes such as synaptic transmission and exocytosis, in which miRNA target expression increases with the accumulation of multiple miRNAs in developing cerebellum and decreases with the loss of these miRNAs in brain tumors. These findings demonstrate the context-dependence of miRNA–mRNA co-expression.     

Identification of Wolbachia-responsive microRNAs in the two-spotted spider mite,Tetranychus urticae

Background

The two-spotted spider mite, Tetranychus urticae, is infected with Wolbachia, which have the ability to manipulate host reproduction and fitness. MicroRNAs (miRNAs) are small non-coding RNAs that are involved in many biological processes such as development, reproduction and host-pathogen interactions. Although miRNA was observed to involve in Wolbachia-host interactions in the other insect systems, its roles have not been fully deciphered in the two-spotted spider mite.

Results

Small RNA libraries of infected and uninfected T. urticae for both sexes (in total four libraries) were constructed. By integrating the mRNA data originated from the same samples, the target genes of the differentially expressed miRNAs were predicted. Then, GO and pathway analyses were performed for the target genes. Comparison of libraries showed that Wolbachia infection significantly regulated 91 miRNAs in females and 20 miRNAs in males, with an overall suppression of miRNAs in Wolbachia-infected libraries. A comparison of the miRNA and mRNA data predicted that the differentially expressed miRNAs negatively regulated 90 mRNAs in females and 9 mRNAs in males. An analysis of target genes showed that Wolbachia-responsive miRNAs regulated genes with function in sphingolipid metabolism, lysosome function, apoptosis and lipid transporting in both sexes, as well as reproduction in females.

Conclusion

Comparisons of the miRNA and mRNA data can help to identify miRNAs and miRNA target genes involving in Wolbachia-host interactions. The molecular targets identified in this study should be useful in further functional studies.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1122) contains supplementary material, which is available to authorized users.     

MicroRNAs are tightly associated with RNA-induced gene silencing complexes in vivo

Previous work has shown that synthesized siRNA/miRNA is tightly associated with RNA-induced Gene Silencing Complexes (RISCs) in vitro. However, it is unknown if the endogenous miRNAs are also stably bound to RISC complexes in vivo in cells under physiological conditions. Here we describe the use of the looped real-time PCR-based method to trace the location of endogenous miRNAs in intact cells. We found that most of the endogenous miRNAs are tightly bound to RISC complexes, and only a very small proportion of them are free in cells. Furthermore, synthesized single-stranded mature miRNA or hairpin miRNA precursor cannot replace endogenous miRNAs already present in RISC complexes. However, we found that modified 2-O-Methyl-ribonucleotides were able to dissociate the target miRNA specifically from the RISC complex. These findings have important implications for understanding the basis for the stability and metabolism of miRNAs in living cells.     

miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs

miRDeepFinder is a software package developed to identify and functionally analyze plant microRNAs (miRNAs) and their targets from small RNA datasets obtained from deep sequencing. The functions available in miRDeepFinder include pre-processing of raw data, identifying conserved miRNAs, mining and classifying novel miRNAs, miRNA expression profiling, predicting miRNA targets, and gene pathway and gene network analysis involving miRNAs. The fundamental design of miRDeepFinder is based on miRNA biogenesis, miRNA-mediated gene regulation and target recognition, such as perfect or near perfect hairpin structures, different read abundances of miRNA and miRNA*, and targeting patterns of plant miRNAs. To test the accuracy and robustness of miRDeepFinder, we analyzed a small RNA deep sequencing dataset of Arabidopsis thaliana published in the GEO database of NCBI. Our test retrieved 128 of 131 (97.7%) known miRNAs that have a more than 3 read count in Arabidopsis. Because many known miRNAs are not associated with miRNA*s in small RNA datasets, miRDeepFinder was also designed to recover miRNA candidates without the presence of miRNA*. To mine as many miRNAs as possible, miRDeepFinder allows users to compare mature miRNAs and their miRNA*s with other small RNA datasets from the same species. Cleaveland software package was also incorporated into miRDeepFinder for miRNA target identification using degradome sequencing analysis. Using this new computational tool, we identified 13 novel miRNA candidates with miRNA*s from Arabidopsis and validated 12 of them experimentally. Interestingly, of the 12 verified novel miRNAs, a miRNA named AC1 spans the exons of two genes (UTG71C4 and UGT71C3). Both the mature AC1 miRNA and its miRNA* were also found in four other small RNA datasets. We also developed a tool, ??miRNA primer designer?? to design primers for any type of miRNAs. miRDeepFinder provides a powerful tool for analyzing small RNA datasets from all species, with or without the availability of genome information. miRDeepFinder and miRNA primer designer are freely available at http://www.leonxie.com/DeepFinder.php and at http://www.leonxie.com/miRNAprimerDesigner.php, respectively. A program (called RefFinder: http://www.leonxie.com/referencegene.php) was also developed for assessing the reliable reference genes for gene expression analysis, including miRNAs.     

Data mining for miRNAs and their targets in the Triticeae.

MicroRNAs (miRNAs) and the mRNA targets of miRNAs were identified by sequence complementarity within a DNA sequence database for species of the Triticeae. Data screening identified 28 miRNA precursor sequences from 15 miRNA families that contained conserved mature miRNA sequences within predicted stem-loop structures. In addition, the identification of 337 target sequences among Triticeae genes provided further evidence of the existence of 26 miRNA families in the cereals. MicroRNA targets included genes that are homologous to known targets in diverse model species as well as novel targets. MicroRNA precursors and targets were identified in 10 related species, though the great majority of them were identified in bread wheat, Triticum aestivum, and barley, Hordeum vulgare, the two species with the largest EST data sets among the Triticeae.