Population and Functional Genomics of Neisseria Revealed with Gene-by-Gene Approaches.
Rapid low-cost whole-genome sequencing (WGS) is revolutionizing microbiology; however, complementary advances in accessible, reproducible, and rapid analysis techniques are required to realize the potential of these data. Here, investigations of the genus Neisseria illustrated the gene-by-gene conceptual approach to the organization and analysis of WGS data. Using the gene and its link to phenotype as a starting point, the BIGSdb database, which powers the PubMLST databases, enables the assembly of large open-access collections of annotated genomes that provide insight into the evolution of the Neisseria, the epidemiology of meningococcal and gonococcal disease, and mechanisms of Neisseria pathogenicity.
Department of Zoology, University of Oxford, Oxford, United KingdomEmory University martin.maiden@zoo.ox.ac.uk.
Martin C J
MC
Maiden
Department of Zoology, University of Oxford, Oxford, United KingdomEmory University.
Odile B
OB
Harrison
D019295:Computational Biology / Q000379:methods; D023281:Genomics / Q000379:methods*; D006069:Gonorrhea / Q000453:epidemiology / Q000382:microbiology* / Q000473:pathology; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D006801:Humans; D008589:Meningococcal Infections / Q000453:epidemiology / Q000382:microbiology* / Q000473:pathology; D009343:Neisseria / Q000145:classification / Q000235:genetics* / Q000472:pathogenicity