Computational Identification of MicroRNAs and Their Targets in Perennial Ryegrass (Lolium perenne)

MicroRNAs (miRNAs) are small non-coding RNA molecules of 22 nucleotides in length that have been characterized as regulators of messenger RNA (mRNA) regulating a number of developmental processes in plants and animals by silencing genes using multiple mechanisms. miRNAs have been extensively studied in various plant species; however, few information are available about miRNAs in perennial ryegrass, animal feed, and industrial raw materials. In this study, the 12 potential perennial ryegrass miRNAs were identified for the first time by computational approach. Using the newly identified miRNA sequences, the perennial ryegrass mRNA database was further used for BLAST search and detected 33 potential targets of miRNAs. Prediction of potential miRNA target genes revealed their functions involved in various important plant biological processes. Our result should be useful for further investigation into the biological functions of miRNAs in perennial ryegrass. The selected miRNAs representing four families were verified by RT-PCR experiment, indicating that the prediction method that we used to identify the miRNAs was effective.     

Computational identification of novel microRNA homologs in the chimpanzee genome

MicroRNAs are important negative regulators of gene expression in higher eukaryotes. The miRNA repertoire of the closest human animal relative, the chimpanzee (Pan troglodytes), is largely unknown. In this study, we focused on computational search of novel miRNA homologs in chimpanzee. We have searched and analyzed the chimp homologs of the human pre-miRNA and mature miRNA sequences. Based on a homology search of the chimpanzee genome with human miRNA precursor sequences as queries, we identified 639 chimp miRNA genes, including 529 novel chimp miRNAs. 91.8% of chimp mature miRNAs and 60.3% of precursors are 100% identical to their human orthologs. The pre-miRNA secondary structures, miRNA families, and clusters are also highly conserved. We also found certain sequence differences in pre-miRNAs and even mature miRNAs that occurred after the divergence of the two species. Some of these differences (especially in mature miRNAs) could have caused species-specific changes in the expression levels of their target genes which in turn could have resulted in phenotypic variation between human and chimp.     

基于miRNA-靶位点配对的序列特征研究

miRNA与其靶基因的作用机制十分复杂,因此,miRNA靶基因识别问题一直是miRNA研究领域的热点难题。该文基于CLASH数据集,提出了miRNA-靶位点配对序列特征,并使用随机森林建模。实验结果表明,本模型的Acc,Sen,Spe,Pre以及Mcc分别达到90.05%,89.47%,90.56%,90.43%和0.799 8;ROC和PRC的AUC分别为0.954,0.958。相比已有方法,该方法表现出更加良好的性能,说明新引入的miRNA-靶位点配对序列特征对miRNA靶基因识别有很重大的影响。     

Identification of evolutionarily conserved Momordica charantia microRNAs using computational approach and its utility in phylogeny analysis

Momordica charantia (bitter gourd, bitter melon) is a monoecious Cucurbitaceae with anti-oxidant, anti-microbial, anti-viral and anti-diabetic potential. Molecular studies on this economically valuable plant are very essential to understand its phylogeny and evolution. MicroRNAs (miRNAs) are conserved, small, non-coding RNA with ability to regulate gene expression by bind the 3′ UTR region of target mRNA and are evolved at different rates in different plant species. In this study we have utilized homology based computational approach and identified 27 mature miRNAs for the first time from this bio-medically important plant. The phylogenetic tree developed from binary data derived from the data on presence/absence of the identified miRNAs were noticed to be uncertain and biased. Most of the identified miRNAs were highly conserved among the plant species and sequence based phylogeny analysis of miRNAs resolved the above difficulties in phylogeny approach using miRNA. Predicted gene targets of the identified miRNAs revealed their importance in regulation of plant developmental process. Reported miRNAs held sequence conservation in mature miRNAs and the detailed phylogeny analysis of pre-miRNA sequences revealed genus specific segregation of clusters.     

In Silico Mining of Conserved miRNAs of Indian Catfish <Emphasis Type="Italic">Clarias batrachus</Emphasis> (Linnaeus, 1758) from the Contigs,ESTs, and BAC End Sequences

MicroRNAs are small non-coding RNAs which play significant role in RNA interference. The present work deals with mining of the conserved miRNA and their target genes from the contigs, ESTs, and BAC end sequences of commercially important catfish, Clarias batrachus, from India. A total of 138, 1 and 1 conserved pre-miRNA sequences, were mined from the contigs, ESTs, and BAC end sequences, respectively. The analysis of families of the conserved pre-miRNA revealed conservation of the fish-specific family mir-430 and other important families, such as mir-455, let-7, mir-133, and mir-137. The mir-455 is involved in hypoxia signaling, let-7 family represents potential anti-tumor molecules involved in human cancer therapy, whereas mir-133 and mir-137 have high therapeutic potentials. Using an alternate computational in silico approach, mining of mature miRNAs resulted in identification of 210 mature miRNAs from contigs, 1 from EST, and 2 each from forward as well as reverse BAC end sequences. Target prediction of these putative miRNAs resulted in the identification of 66,758 and 18,747 target genes in C. batrachus and Danio rerio, respectively. Functional annotation of these miRNAs indicated their involvement in diverse biological functions. The findings of the present study can serve as a valuable resource for further functional genomics studies in C. batrachus.     

Predicting microRNA biological functions based on genes discriminant analysis

Although thousands of microRNAs (miRNAs) have been identified in recent experimental efforts, it remains a challenge to explore their specific biological functions through molecular biological experiments. Since those members from same family share same or similar biological functions, classifying new miRNAs into their corresponding families will be helpful for their further functional analysis. In this study, we initially built a vector space by characterizing the features from miRNA sequences and structures according to their miRBase family organizations. Then we further assigned miRNAs into its specific miRNA families by developing a novel genes discriminant analysis (GDA) approach in this study. As can be seen from the results of new families from GDA, in each of these new families, there was a high degree of similarity among all members of nucleotide sequences. At the same time, we employed 10-fold cross-validation machine learning to achieve the accuracy rates of 68.68%, 80.74%, and 83.65% respectively for the original miRNA families with no less than two, three, and four members. The encouraging results suggested that the proposed GDA could not only provide a support in identifying new miRNAs’ families, but also contributing to predicting their biological functions.     

Silencing lung cancer genes using miRNAs identified by 7mer-seed matching

Lung cancer (LC) is the main cause of cancer-associated deaths in both men and women globally with a very high mortality rate. The microRNAs (miRNAs) are a class of noncoding RNAs consisting of 18–25 nucleotides. They inhibit translation of protein through binding to complementary target mRNAs. The non-coding miRNAs are recognized as potent biomarkers for detection, development and treatment of malignancy. In this study, we screened a set of 12 genes over expressed in small cell lung cancer, non small cell lung cancer and the genes involved in both categories and their binding sites for human miRNAs as no work was reported yet. Screening of human miRNAs revealed that a few genes showed numerous miRNA binding sites. Free energy values of mRNA sequences revealed that they might acquire compact folded structure causing complexity for miRNAs to interact. GC content in the target site was relatively higher than that of their flanks. It was observed through analysis of cosine similarity metric and compAI parameters that the genes related to lung cancer were encoded with non optimal codons and thus might be translationally less efficient for producing polypeptides. Gene ontology analysis was carried out to understand the diverse functions of these 12 genes.     

In silico prediction of human genes as potential targets for rice miRNAs

BackgroundExogenous microRNAs (miRNAs) enter the human body through food, and their effects on metabolic processes can be considerable. It is important to determine which miRNAs from plants affect the expression of human genes and the extent of their influence.MethodThe binding sites of 738Oryza sativa miRNAs (osa-miRNAs) that interact with 17 508 mRNAs of human genes were determined using the MirTarget program.ResultThe characteristics of the binding of 46 single osa-miRNAs to 86 mRNAs of human genes with a value of free energy (ΔG) interaction equal 94%–100% from maximum ΔG were established. The findings showed that osa-miR2102-5p, osa-miR5075-3p, osa-miR2097-5p, osa-miR2919 targeted the largest number of genes at 38, 36, 23, 19 sites, respectively. mRNAs of 86 human genes were identified as targets for 93 osa-miRNAs of all family osa-miRNAs with ΔG values equal 94%–98% from maximum ΔG. Each miRNA of the osa-miR156-5p, osa-miR164-5p, osa-miR168-5p, osa-miR395-3p, osa-miR396-3p, osa-miR396-5p, osa-miR444-3p, osa-miR529-3p, osa-miR1846-3p, osa-miR2907-3p families had binding sites in mRNAs of several human target genes. The binding sites of osa-miRNAs in mRNAs of the target genes for each family of osa-miRNAs were conserved when compared to flanking nucleotide sequences.ConclusionTarget mRNA human genes of osa-miRNAs are also candidate genes of cancer, cardiovascular and neurodegenerative diseases.     

Analysis of the NCI-60 dataset for cancer-related microRNA and mRNA using expression profiles

BackgroundRecent studies have indicated that microRNA (miRNA) may play an oncogenic or tumor suppressor role in human cancer. To study the regulatory role of miRNAs in tumorigenesis, an integrated platform has been set up to provide a user friendly interface for query. The main advantage of the present platform is that all the miRNA target genes’ information and disease records are drawn from experimentally verified or high confidence records.ResultsMiRNA target gene results are annotated with reference to the disease gene as well as the pathway database. The correlation strength between miRNA and target gene expression profile is quantified by computing the correlation coefficient using the NCI-60 expression profiling data. Comprehensive analysis of the NCI-60 data found that the cumulative percentage of negative correlation coefficients for cleavage regulation is slightly higher than its positive counterpart; which indicated that the mRNA degradation mechanism is slightly dominant. In addition, the RNAHybrid and TargetScans scores are computed which potentially served as quantitative estimators for miRNA–mRNA binding events.Three scores are defined for each miRNA–mRNA pair, which are based on the disease gene and pathway information. These three scores allow user to sort out high confidence cancer-related miRNA–mRNA pairs.Statistical tests were applied to investigate the relations of three chromosomal features, i.e., CpG island, fragile site, and miRNA cluster, with cancer-related miRNAs. A web-based interface has been set up for query, which can be accessed at: http://ppi.bioinfo.asia.edu.tw/mirna_target/ConclusionsThe main advantage of the present platform on miRNA–mRNA targeting information is that all the target genes’ information and disease records are experimentally verified. Although this may limit the number of miRNA–mRNA relationships, the results provided here are more solid and have fewer false positive events. Certain novel cancer-related miRNA–mRNA pairs are identified and confirmed in the literature. Fisher's exact test suggests that CpG island and fragile site associated miRNAs tend to associate with cancer formation. In summary, the present platform provides an easy means of investigating cancer-related miRNAs.     

Genome-wide computational analyses of microRNAs and their targets from Canis familiaris

By computational analyses, we identified 357 miRNA candidates from Canis familiaris genome, among which 300 are homology of characterized human miRNAs, the remains are not reported in any other animal. Of the 357 miRNA genes, 142 are organized into 53 clusters, and two clusters locate in the paternally imprinted region. These dog miRNAs may regulate more than 800 possible targets, which are involved in a wide range of cellular processes. Remarkably, miR-186 resides in the eighth intron of its target gene in the same orientation, suggesting a feedback regulation of miRNA on its host gene.     

Genome-wide computational identification of microRNAs and their targets in the deep-branching eukaryote Giardia lamblia

Using a combined computational program, we identified 50 potential microRNAs (miRNAs) in Giardia lamblia, one of the most primitive unicellular eukaryotes. These miRNAs are unique to G. lamblia and no homologues have been found in other organisms; miRNAs, currently known in other species, were not found in G. lamblia. This suggests that miRNA biogenesis and miRNA-mediated gene regulation pathway may evolve independently, especially in evolutionarily distant lineages. A majority (43) of the predicted miRNAs are located at one single locus; however, some miRNAs have two or more copies in the genome. Among the 58 miRNA genes, 28 are located in the intergenic regions whereas 30 are present in the anti-sense strands of the protein-coding sequences. Five predicted miRNAs are expressed in G. lamblia trophozoite cells evidenced by expressed sequence tags or RT-PCR. Thirty-seven identified miRNAs may target 50 protein-coding genes, including seven variant-specific surface proteins (VSPs). Our findings provide a clue that miRNA-mediated gene regulation may exist in the early stage of eukaryotic evolution, suggesting that it is an important regulation system ubiquitous in eukaryotes.