Integration of Genetic Analysis and Map Generation with the E. coli Genetic Stock Center Database

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The objective of this project is to add advanced features to the E. coli Genetic Stock Center database and to extend the current database to include additional genetic information currently available at the Center. Special emphasis will be put on developing and handling representation, computation, and analysis of mapping information; on the use and handling of pedigree data; and on exploration of interaction and possible integrations with other databases that specialize in information relevant to an E. coli database. The proposed work will involve extending the current design and the current database and developing plans for integration with other databases. The design and structure of the current system were developed with these expanded functions in mind, so that the necessary additions can be accomplished without requiring that any of the earlier work be discarded or redesigned. This project is significant in developing a database management system for a large strain collection involving complex genetic descriptions with as many as 20 genetic markers per strain; providing a means to query (in a database format) types and positions of mutations ranging from base pair changes in tRNA (suppressor) loci to insertion of transposons or sex factors between genes, to intragenic or intergenic deletions, to inversions, transpositions, or episome-integration of regions of the chromosome; developing representations of uncertainties inherent in genetic data; providing retrieval capability for virtually any combination of genetic or strain traits, including specific mutation types, mutations in specific genes or within specific regions, plasmids with or without markers, and strain attributes such as sex or lab of origin; and providing, in relational format, critical genome information at both the organismal and subcellular level, with capability of integration with sequence and other physical databases. Much of the value of our approach to the mapping function lies in the ability to store, analyze, and integrate data from many experimental sources as well as summary map data, and to have the map data tied to our extensive and accurate database of genes, alleles, and strains. This should facilitate detecting, for example, map anomalies that are strain specific, or allele- specific, or that consistently differ according to experimental procedure.