Identification of mirtrons in rice using MirtronPred: a tool for predicting plant mirtrons.

article i nfo Studies from flies and insects have reported the existence of a special class of miRNA, called mirtrons that are produced from spliced-out introns in a DROSHA-independent manner. The spliced-out lariat is debranched and refolded into a stem-loop structure resembling the pre-miRNA, which can then be processed by DICER into mature ~21 nt species. The mirtrons have not been reported from plants. In this study, we present Mir- tronPred, a web based server to predict mirtrons from intronic sequences. We have used the server to predict 70 mirtrons in rice introns that were put through a stringent selection filter to shortlist 16 best sequences. The prediction accuracy was subsequently validated by northern analysis and RT-PCR of a predicted Os- mirtron-109. The target sequences for this mirtron were also found in the rice degradome database. The pos- sible role of the mirtron in rice regulon is discussed. The MirtronPred web server is available at http://bioinfo. icgeb.res.in/mirtronPred

CyclinPred: A SVM-Based Method for Predicting Cyclin Protein Sequences

Functional annotation of protein sequences with low similarity to well characterized protein sequences is a major challenge of computational biology in the post genomic era. The cyclin protein family is once such important family of proteins which consists of sequences with low sequence similarity making discovery of novel cyclins and establishing orthologous relationships amongst the cyclins, a difficult task. The currently identified cyclin motifs and cyclin associated domains do not represent all of the identified and characterized cyclin sequences. We describe a Support Vector Machine (SVM) based classifier, CyclinPred, which can predict cyclin sequences with high efficiency. The SVM classifier was trained with features of selected cyclin and non cyclin protein sequences. The training features of the protein sequences include amino acid composition, dipeptide composition, secondary structure composition and PSI-BLAST generated Position Specific Scoring Matrix (PSSM) profiles. Results obtained from Leave-One-Out cross validation or jackknife test, self consistency and holdout tests prove that the SVM classifier trained with features of PSSM profile was more accurate than the classifiers based on either of the other features alone or hybrids of these features. A cyclin prediction server- CyclinPred has been setup based on SVM model trained with PSSM profiles. CyclinPred prediction results prove that the method may be used as a cyclin prediction tool, complementing conventional cyclin prediction methods

compendiumdb: an R package for retrieval and storage of functional genomics data

Currently, the Gene Expression Omnibus (GEO) contains public data of over 1 million samples from more than 40 000 microarray-based functional genomics experiments. This provides a rich source of information for novel biological discoveries. However, unlocking this potential often requires retrieving and storing a large number of expression profiles from a wide range of different studies and platforms. The compendiumdb R package provides an environment for downloading functional genomics data from GEO, parsing the information into a local or remote database and interacting with the database using dedicated R functions, thus enabling seamless integration with other tools available in R/Bioconductor. The compendiumdb package is written in R, MySQL and Perl. Source code and binaries are available from CRAN (http://cran.r-project.org/web/packages/compendiumdb/) for all major platforms (Linux, MS Windows and OS X) under the GPLv3 license. [email protected] Supplementary data are available at Bioinformatics onlin

Inference of the oxidative stress network in Anopheles stephensi upon Plasmodium infection.

Ookinete invasion of Anopheles midgut is a critical step for malaria transmission; the parasite numbers drop drastically and practically reach a minimum during the parasite's whole life cycle. At this stage, the parasite as well as the vector undergoes immense oxidative stress. Thereafter, the vector undergoes oxidative stress at different time points as the parasite invades its tissues during the parasite development. The present study was undertaken to reconstruct the network of differentially expressed genes involved in oxidative stress in Anopheles stephensi during Plasmodium development and maturation in the midgut. Using high throughput next generation sequencing methods, we generated the transcriptome of the An. stephensi midgut during Plasmodium vinckei petteri oocyst invasion of the midgut epithelium. Further, we utilized large datasets available on public domain on Anopheles during Plasmodium ookinete invasion and Drosophila datasets and arrived upon clusters of genes that may play a role in oxidative stress. Finally, we used support vector machines for the functional prediction of the un-annotated genes of An. stephensi. Integrating the results from all the different data analyses, we identified a total of 516 genes that were involved in oxidative stress in An. stephensi during Plasmodium development. The significantly regulated genes were further extracted from this gene cluster and used to infer an oxidative stress network of An. stephensi. Using system biology approaches, we have been able to ascertain the role of several putative genes in An. stephensi with respect to oxidative stress. Further experimental validations of these genes are underway

Mapping summary of RNA-seq data.

<p>*RNA-seq libraries were mapped to <i>Anopheles stephensi</i> genome using TopHat and Cufflinks tools.</p><p>Mapping summary of RNA-seq data.</p

Venn diagram representing data summary of differentially expressed <i>Anopheles</i> genes from RNA-seq data.

<p>Venn diagram representing data summary of differentially expressed <i>Anopheles</i> genes from RNA-seq data.</p

Figure representing the hypothetical model of oxidative stress pathway.

<p>This model includes 3 predicted proteins namely, FOXRED1, SCMC3 and SQR represented by red star.</p

Expression pattern of the RNA-seq and microarray predicted genes related to oxidative stress.

<p>These genes were selected on the basis of GO terms, and microarray analysis. RPKM values of all the genes are also shown in the table.</p><p>*The analysis was performed using <i>Anopheles gambiae</i> genes. <i>Anopheles gambiae</i> IDs were then converted into <i>Anopheles stephensi</i> IDs using BioMart tool of VectorBase.</p><p>Expression pattern of the RNA-seq and microarray predicted genes related to oxidative stress.</p

KOBAS analysis of differentially expressed genes.

<p>Graph represents the significant pathways predicted after KOBAS analysis.</p