Bioinformatics of high-throughput insertional mutagenesis

Bioinformatics plays critical roles to handle large amount of sequence data from insertional mutagenesis. First, computational approaches are used to develop rapid sequence analysis pipelines and biological databases. Millions of reads from an insertion mutagenesis screening are mapped to genomic locations and be annotated to their target genes rapidly by pipeline, and such sequence-based data is stored and managed in database to share the information in the scientific community. Second, statistical techniques are used to distinguish true common insertion sites (loci that have been hit by insertions in multiple tumors: candidate loci for cancer genes) from background insertions in large-scale screenings. Finally, the advanced data mining techniques, pathway and network analysis, are used to give further biological meaning to insertion sites by identifying the interaction of genes in cancer. In this chapter, we discuss features of these three topics and address their future roles: (1) development of sequence analysis pipeline and database, (2) detection of common insertion sites, and (3) network and pathway analysis of insertion sites.