Computational identification of novel microRNAs and targets in Brassica napus

MicroRNAs (miRNAs) are a newly discovered class of non-protein-coding small RNAs with roughly 22 nucleotide-long. Increasing evidence has shown that miRNAs play multiple roles in biological processes, including development, cell proliferation and apoptosis and stress responses. In this research, several approaches were combined to make computational prediction of potential miRNAs and their targets in Brassica napus. We used previously known miRNAs from Arabidopsis, rice and other plant species against both expressed sequence tags (EST) and genomic survey sequence (GSS) databases to search for potential miRNAs in B. napus. A total of 21 potential miRNAs were detected following a range of strict filtering criteria. Using these potential miRNA sequences, we could further blast the mRNA database and found 67 potential targets in this species. According to the mRNA target information provided by NCBI (http://www.ncbi.nlm.nih.gov/), most of the target mRNAs appeared to be involved in plant growth, development and stress responses. To validate the prediction of miRNAs in B. napus, we performed a RT-PCR based assay of mature miRNA expression. Five miRNAs were identified in response to auxin, cadmium stress and phosphate starvation. So far, little is known about experimental or computational identification of miRNA in B. napus species. To improve efficiency for blast search, we developed an implementation (miRNAassist) that can identify homologs of miRNAs and their targets, with high sensitivity and specificity. The program is allowed to be run on Windows Operation System platform. miRNAassist is freely available if required.     

Computational identification of conserved microRNAs and their putative targets in the Hypericum perforatum L. flower transcriptome

MicroRNAs (miRNAs) have recently emerged as important regulators of gene expression in plants. Many miRNA families and their targets have been extensively studied in model species and major crops. We have characterized mature miRNAs along with their precursors and potential targets in Hypericum to generate a comprehensive list of conserved miRNA families and to investigate the regulatory role of selected miRNAs in biological processes that occur in the flower. St. John’s wort (Hypericum perforatum L., 2n = 4x = 32), a medicinal plant that produces pharmaceutically important metabolites with therapeutic activities, was chosen because it is regarded as an attractive model system for the study of apomixis. A computational in silico prediction of structure, in combination with an in vitro validation, allowed us to identify 7 pre-miRNAs, including miR156, miR166, miR390, miR394, miR396, and miR414. We demonstrated that H. perforatum flowers share highly conserved miRNAs and that these miRNAs potentially target dozens of genes with a wide range of molecular functions, including metabolism, response to stress, flower development, and plant reproduction. Our analysis paves the way toward identifying flower-specific miRNAs that may differentiate the sexual and apomictic reproductive pathways.     

Computational identification of microRNA targets

Recent experiments have shown that the genomes of organisms such as worm, fly, human, and mouse encode hundreds of microRNA genes. Many of these microRNAs are thought to regulate the translational expression of other genes by binding to partially complementary sites in messenger RNAs. Phenotypic and expression analysis suggests an important role of microRNAs during development. Therefore, it is of fundamental importance to identify microRNA targets. However, no experimental or computational high-throughput method for target site identification in animals has been published yet. Our main result is a new computational method that is designed to identify microRNA target sites. This method recovers with high specificity known microRNA target sites that have previously been defined experimentally. Based on these results, we present a simple model for the mechanism of microRNA target site recognition. Our model incorporates both kinetic and thermodynamic components of target recognition. When we applied our method to a set of 74 Drosophila melanogaster microRNAs, searching 3'UTR sequences of a predefined set of fly mRNAs for target sites which were evolutionary conserved between D. melanogaster and Drosophila pseudoobscura, we found that many key developmental body patterning genes such as hairy and fushi-tarazu are likely to be translationally regulated by microRNAs.     

Genome-wide identification of Brassica napus microRNAs and their targets in response to cadmium

MicroRNAs (miRNAs) are a distinct class of small RNAs in plants that not only regulate biological processes but also regulate response to environmental stresses. The toxic heavy metal cadmium (Cd) induces expression of several miRNAs in rapeseed (Brassica napus), but it is not known on a genome-wide scale how the expression of miRNAs and their target genes, is regulated by Cd. In this study, four small RNA libraries and four degradome libraries were constructed from Cd-treated and non-Cd-treated roots and shoots of B. napus seedlings. Using high-throughput sequencing, the study identified 84 conserved and non-conserved miRNAs (belonging to 37 miRNA families) from Cd-treated and non-treated B. napus, including 19 miRNA members that were not identified before. Some of the miRNAs were validated by RNA gel blotting. Most of the identified miRNAs were found to be differentially expressed in roots/shoots or regulated by Cd exposure. The study simultaneously identified 802 targets for the 37 (24 conserved and 13 non-conserved) miRNA families, from which there are 200, 537, and 65 targets, belonging to categories I, II, and III, respectively. In category I alone, many novel targets for miRNAs were identified and shown to be involved in plant response to Cd.     

Computational prediction of microRNAs and their targets from three unicellular algae species with complete genome sequences

The genome sequences of Phaeodactylum tricornutum, Thalassiosira pseudonana, and Cyanidioschyzon merolae have provided significant evidence for the secondary endosymbiosis of diatoms in regard to the genome. Yet little about their relationships in regard to gene regulation pattern, such as microRNA (miRNA), has been reported. Using a homology search based on genomic sequences, 13, 3, and 7 predicted miRNA genes were found in genomes from P. tricornutum, T. pseudonana, and C. merolae, respectively. Of the 23 miRNA genes, 18 had homology with animal miRNAs, implying that they are ancestral miRNAs. A phylogenetic tree based on common miRNA families shared by these three unicellular algae, higher plants, and animals showed that P. tricornutum shared most miRNAs with animals. The phylogenetic tree also showed that C. merolae shared more miRNAs with plants than did the two diatoms, and the majority of its miRNAs were shared with the two diatoms. Our results were consistent with diatoms originating from a secondary endosymbiosis.     

Prediction and validation of microRNAs and their targets

MicroRNAs are short non-coding RNAs that inhibit translation of target genes by binding to their mRNAs, and have been shown to play a central role in gene regulation in health and disease. Sophisticated computer-based prediction approaches of microRNAs and of their targets, and effective biological validation techniques for validating these predictions, now play a central role in discovery of microRNAs and elucidating their functions.     

Computational and experimental identification of C. elegans microRNAs

MicroRNAs (miRNAs) constitute an extensive class of noncoding RNAs that are thought to regulate the expression of target genes via complementary base-pair interactions. To date, cloning has identified over 200 miRNAs from diverse eukaryotic organisms. Despite their success, such biochemical approaches are skewed toward identifying abundant miRNAs, unlike genome-wide, sequence-based computational predictions. We developed informatic methods to predict miRNAs in the C. elegans genome using sequence conservation and structural similarity to known miRNAs and generated 214 candidates. We confirmed the expression of four new miRNAs by Northern blotting and used a more sensitive PCR approach to verify the expression of ten additional candidates. Based on hypotheses underlying our computational methods, we estimate that the C. elegans genome may encode between 140 and 300 miRNAs and potentially many more.