水稻MicroRNA的预测及实验验证

根据已报道水稻pre-miRNA的序列与结构信息,利用支持向量机（support vector machine, SVM）方法在miRNA前体上预测成熟区,产生一个模型——mature-SVM.它预测水稻成熟区的敏感性和特异性分别为86.7% 和100%;然后,用这个模型对从水稻基因组中筛选出的46.501条pre-miRNA进行成熟链预测,此外再根据miRNA的作用原理用blast程序所进一步的筛选,得到了127条pre-miRNA及成熟miRNA;除去其中已知的21条,最后得到106条候选的新的水稻miRNA. 从中随机挑取10条进行Northern验证,结果有4条miRNA得到确认.     

SNPs in human miRNA genes affect biogenesis and function

MicroRNAs (miRNAs) are 21–25-nucleotide-long, noncoding RNAs that are involved in translational regulation. Most miRNAs derive from a two-step sequential processing: the generation of pre-miRNA from pri-miRNA by the Drosha/DGCR8 complex in the nucleus, and the generation of mature miRNAs from pre-miRNAs by the Dicer/TRBP complex in the cytoplasm. Sequence variation around the processing sites, and sequence variations in the mature miRNA, especially the seed sequence, may have profound affects on miRNA biogenesis and function. In the context of analyzing the roles of miRNAs in Schizophrenia and Autism, we defined at least 24 human X-linked miRNA variants. Functional assays were developed and performed on these variants. In this study we investigate the affects of single nucleotide polymorphisms (SNPs) on the generation of mature miRNAs and their function, and report that naturally occurring SNPs can impair or enhance miRNA processing as well as alter the sites of processing. Since miRNAs are small functional units, single base changes in both the precursor elements as well as the mature miRNA sequence may drive the evolution of new microRNAs by altering their biological function. Finally, the miRNAs examined in this study are X-linked, suggesting that the mutant alleles could be determinants in the etiology of diseases.     

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.     

Global profiling of miRNAs and the hairpin precursors: insights into miRNA processing and novel miRNA discovery

MicroRNAs (miRNAs) constitute an important class of small regulatory RNAs that are derived from distinct hairpin precursors (pre-miRNAs). In contrast to mature miRNAs, which have been characterized in numerous genome-wide studies of different organisms, research on global profiling of pre-miRNAs is limited. Here, using massive parallel sequencing, we have performed global characterization of both mouse mature and precursor miRNAs. In total, 87 369 704 and 252 003 sequencing reads derived from 887 mature and 281 precursor miRNAs were obtained, respectively. Our analysis revealed new aspects of miRNA/pre-miRNA processing and modification, including eight Ago2-cleaved pre-miRNAs, eight new instances of miRNA editing and exclusively 5′ tailed mirtrons. Furthermore, based on the sequences of both mature and precursor miRNAs, we developed a miRNA discovery pipeline, miRGrep, which does not rely on the availability of genome reference sequences. In addition to 239 known mouse pre-miRNAs, miRGrep predicted 41 novel ones with high confidence. Similar as known ones, the mature miRNAs derived from most of these novel loci showed both reduced abundance following Dicer knockdown and the binding with Argonaute2. Evaluation on data sets obtained from Caenorhabditis elegans and Caenorhabditis sp.11 demonstrated that miRGrep could be widely used for miRNA discovery in metazoans, especially in those without genome reference sequences.     

Identification and Comparative Analysis of the Tegillarca granosa Haemocytes MicroRNA Transcriptome in Response to Cd Using a Deep Sequencing Approach

Background

MicroRNAs (miRNAs) are endogenous non-coding small RNAs (sRNAs) that can base pair with their target mRNAs, which represses their translation or induces their degradation in various biological processes. To identify miRNAs regulated by heavy metal stress, we constructed two sRNA libraries for the blood clam Tegillarca granosa: one for organisms exposed to toxic levels of cadmium (Cd) and one for a control group.

Results

Sequencing of the two libraries and subsequent analysis revealed 215 conserved and 39 new miRNAs. Most of the new miRNAs in T. granosa were up- or down-regulated in response to Cd exposure. There were significant differences in expression between the Cd and control groups for 16 miRNAs. Of these, five miRNAs were significantly up-regulated and 11 were significantly down-regulated in the Cd stress library. Potential targets were predicted for the 16 differential miRNAs in pre-miRNAs identified according to sequence homology. Some of the predicted miRNA targets are associated with regulation of the response to stress induced by heavy metals. Five differentially expressed miRNAs (Tgr-nmiR-8, Tgr-nmiR-21, Tgr-miR-2a, Tgr-miR-10a-5p, and Tgr-miR-184b) were validated by qRT-PCR.

Conclusion

Our study is the first large-scale identification of miRNAs in T. granosa haemocytes. Our findings suggest that some miRNAs and their target genes and pathways may play critical roles in the responses of this species to environmental heavy metal stresses.