A computational model for non-conserved mature miRNAs from the rice genome

Several computational approaches employ the high complementarity of plant miRNAs to target mRNAs as a filter to recognize miRNA. Numerous non-conserved miRNAs are known with more recent evolutionary origin as a result of target gene duplication events. We present here a computational model with knowledge inputs from reported non-conserved mature miRNAs of Oryza sativa (rice). Sequence- and structure-based approaches were used to retrieve miRNA features based on rice Argonaute protein and develop a multiple linear regression (MLR) model (r² = 0.996, q²_cv = 0.989) which scored mature miRNAs as predicted by the MaturePred program. The model was validated by scoring test set (q² = 0.990) and computationally predicted mature miRNAs as external test set (q²_test = 0.895). This strategy successfully enhanced the confidence of retrieving most probable non-conserved miRNAs from the rice genome. We anticipate that this computational model would recognize unknown non-conserved miRNA candidates and nurture the current mechanistic understanding of miRNA sorting to unveil the role of non-conserved miRNAs in gene silencing.     

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.     

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.     

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.     

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.     

Target prediction of candidate miRNAs from Oryza sativa for silencing the RYMV genome

In order to maintain a consistent supply of rice globally, control of pathogens affecting crop production is a matter of due concern. Rice yellow mottle virus(RYMV) is known to cause a variety of symptoms which can result in reduced yield. Four ORFs can be identified in the genome of RYMV encoding for P1 (ORF1), Polyprotein (processed to produce VPg, protease, helicase, RdRp4) (ORF2), putative RdRp (ORF3) and capsid/coat protein (ORF4). This research was aimed at identifying genome encoded miRNAs of O. sativa that are targeted to the genome of Rice Yellow Mottle Virus (RYMV). A consensus of four miRNA target prediction algorithms (RNA22, miRanda, TargetFinder and psRNATarget) was computed, followed by calculation of free energies of miRNA-mRNA duplex formation. A phylogenetic tree was constructed to portray the evolutionary relationships between RYMV strains isolated to date. From the consensus of algorithms used, a total of seven O. sativa miRNAs were predicted and conservation of target site was finally evaluated. Predicted miRNAs can be further evaluated by experiments involving the testing of the success of in vitro gene silencing of RYMV genome; this can pave the way for development of RYMV resistant rice varieties in the future.     

<Emphasis Type="Italic">Insilco</Emphasis> Prediction and Characterization of microRNAs from <Emphasis Type="Italic">Oncopeltus fasciatus</Emphasis> (Hemiptera: Lygaeidae) Genome

For studies on functional genomics, small RNAs, especially microRNAs (miRNAs), have emerged as a hot topic due to their importance in cellular and developmental processes. Identification of insect miRNAs largely depends on the availability of genomic sequences in the public domain. The large milkweed bug, Oncopeltus fasciatus (Dallas) is a hemimetabolous insect which has become a model hemipteran system for various molecular studies. In this study, we identified 96 candidate mature miRNAs from O. fasciatus genome using a blast search with the previously reported animal miRNAs. The secondary structure of predicted miRNA sequences was determined online using “mfold” web server and verified by calculating the minimal free energy index (MFEI). Six miRNAs let-7e, miR-133c, miR-219b, mir-466d, mir-669f, and mir-669l are reported for the first time in Insecta. Comparison of O. fasciatus mir-2 and mir-71 family clusters to those of diverse insect species showed that they are highly conserved. The phylogenetic analysis of miRNAs revealed the evolutionary relationship of conserved miRNAs of O. fasciatus with other insect species. Using a classical rule-based algorithm method, we predicted the possible targets of the new miRNAs. Our study not only identified the list of miRNAs in O. fasciatus but also provides a basic platform for developing novel pest management strategies based on artificial miRNAs.     

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.     

Computational Approach for Identification of Anopheles gambiae miRNA Involved in Modulation of Host Immune Response

MicroRNAs (miRNAs) are small, noncoding RNAs that play key roles in regulating gene expression in animals, plants, and viruses, which involves in biological processes including development, cancer, immunity, and host–microorganism interactions. In this present study, we have used the computational approach to identify potent miRNAs involved in Anopheles gambiae immune response. Analysis of 217,261 A. gambiae ESTs and further study of RNA folding revealed six new miRNAs. The minimum free energy of the predicted miRNAs ranged from ?27.2 to ?62.63 kcal/mol with an average of ?49.38 kcal/mol. While its A + U % ranges from 50 to 65 % with an average value of 57.37 %. Phylogenetic analysis of the predicted miRNAs revealed that aga-miR-277 was evolutionary highly conserved with more similarity with other mosquito species. Observing further the target identification of the predicted miRNA, it was noticed that the aga-miR-2304 and aga-miR-2390 are involved in modulation of immune response by targeting the gene encoding suppressin and protein prophenoloxidase. Further detailed studies of these miRNAs will help in revealing its function in modulation of A. gambiae immune response with respect to its parasite.     

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 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.     

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.