Journal Article

BIGSdb: Scalable analysis of bacterial genome variation at the population level

Jolley, Keith A, Maiden, Martin CJ

2010

Overview

Background The opportunities for bacterial population genomics that are being realised by the application of parallel nucleotide sequencing require novel bioinformatics platforms. These must be capable of the storage, retrieval, and analysis of linked phenotypic and genotypic information in an accessible, scalable and computationally efficient manner. Results The Bacterial Isolate Genome Sequence Database (BIGS DB ) is a scalable, open source, web-accessible database system that meets these needs, enabling phenotype and sequence data, which can range from a single sequence read to whole genome data, to be efficiently linked for a limitless number of bacterial specimens. The system builds on the widely used mlstdbNet software, developed for the storage and distribution of multilocus sequence typing (MLST) data, and incorporates the capacity to define and identify any number of loci and genetic variants at those loci within the stored nucleotide sequences. These loci can be further organised into 'schemes' for isolate characterisation or for evolutionary or functional analyses. Isolates and loci can be indexed by multiple names and any number of alternative schemes can be accommodated, enabling cross-referencing of different studies and approaches. LIMS functionality of the software enables linkage to and organisation of laboratory samples. The data are easily linked to external databases and fine-grained authentication of access permits multiple users to participate in community annotation by setting up or contributing to different schemes within the database. Some of the applications of BIGS DB are illustrated with the genera Neisseria and Streptococcus . The BIGS DB source code and documentation are available at http://pubmlst.org/software/database/bigsdb/ . Conclusions Genomic data can be used to characterise bacterial isolates in many different ways but it can also be efficiently exploited for evolutionary or functional studies. BIGS DB represents a freely available resource that will assist the broader community in the elucidation of the structure and function of bacteria by means of a population genomics approach.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Algorithms / Bacteria / Bacterial genetics / Base Sequence / Bioinformatics / Biomedical and Life Sciences / Community involvement / Computational Biology/Bioinformatics / Computer Appl. in Life Sciences / Computer programs / Data processing / Database management systems / Databases, Genetic / Epidemiology / Evolution / Genetic variance / Genetic Variation / Genome, Bacterial / Genomics / Genomics - methods / Information management / Life Sciences / Microarrays / multilocus sequence typing / Neisseria / Nucleotide sequence / Nucleotides / Population genetics / Population levels / Sequence analysis (applications) / Sequence Analysis, DNA / Software / Streptococcus / Structure-function relationships / Studies