SRA

Pesticides are widely used to protect growth of crops and prevent the spread of diseases. However, more and more pest insects have developed resistance to chemical pesticides along with the long-term application of the pesticides. It is very important to explore the molecular mechanisms of insecticide resistance not only for reversing the resistance in insects, but also for finding out new function targets of the insecticides. Recently, the next-generation sequence technique has become an effective tool to screen resistance genes and has developed transcriptome profiles of various species. However, a comprehensive database to collect these transcriptome data remains poorly developed. In this study, we constructed a database for insect resistance called IRdb, which contains gene count data from various insect species analyzed by a unified process. In addition to the gene data, IRdb also contains 430 unique resistance proteins (experimentally verified proteins manually extracted from literature). Users can discriminate the resistance proteins by submitting fasta sequence of proteins of interest, which can provide clues to detect resistance proteins. The application of resistance protein part in IRdb indicates the accuracy of prediction of IRdb by extracting CTD features and employing random forest. The database IRdb online web server (http://120.27.24.199:20609/) was provided for users to download the transcriptome and protein data for resistance of insects to insecticides and to predict potential resistance proteins. Overall design: Compare the RNA-seq between sensitive and resistance in third-instar larva and adult Drosophila melanogaster