UC Riverside

Female Aedes aegypti mosquitoes spread pathogens for various vector-borne diseases while feeding on vertebrate blood. Being anautogenous, these mosquitoes require a blood meal for vitellogenesis, the process of yolk formation during the maturation of eggs. A clear understanding of the molecular mechanism of reproduction, such as detailed transcription mechanisms, should contribute significantly to the vector control strategies. The aim of this project is to decipher how complex transcription programs govern genes that are differentially expressed during female mosquito reproduction. We have identified 89 putative transcription factor biding sites (TFBSs) using bioinformatics tools, on the promoter regions of more then 1K differentially regulated genes. The putative TFBSs were screened for positional bias, orientation bias and evolutionary conservation, properties that are often associated with real TFBSs. Promoters from orthologous genes in closely related species Anopheles gambiae and Culex quinquefascitus, were used to check for evolutionary conservation. The above-mentioned screens were used to increase the accuracy of the in-silico predictions. JASPAR database was searched to identity the known TFBSs and their corresponding TFs. GeneMANIA webtool was used for the construction of putative regulatory networks. Molecular biology techniques such as RNA-interference mediated depletion of selected TFs and quantitative reverse-transcription polymerase chain reaction have been used for verifying and evaluating the functionality of some of these putative TFBSs.

In addition to identifying cis-regulatory elements this dissertation also describes an approach developed for prediction of miRNA targets involved in mosquito reproduction. miRNAs are 21 to 24 nucleotide long non-coding RNAs that degrade or inhibit by coupling with target sites on mRNAs. Since the discovery huge numbers of miRNAs have been reported. However, the functions of only a few of these miRNAs are well understood. The study of miRNA targets is critical step for determining the functionality of miRNAs. There are many miRNA target prediction tools that are readily available, but almost all of these have a problem of producing huge number of false-positive results. Here, we have developed a new approach for computational target prediction that involves five different target prediction programs, the results have been experimentally verified in separate studies and found to be highly reliable.

Overall we have been able to identify binding sites for TFs and targets for miRNAs that are involved in female mosquito reproduction. We realize that future work remains, for a complete understanding of the complex molecular mechanisms, during the reproductive period. However this study can be regarded as a significant step towards the accomplishment of that goal.