Log on / register
BioMed Central home | Journals A-Z | Feedback | Support | My details
.refereed research
 |  |  |  |  | 


Open AccessMethod

Quantification of global transcription patterns in prokaryotes using spotted microarrays

Ben Sidders1 email, Mike Withers1 email, Sharon L Kendall1 email, Joanna Bacon3 email, Simon J Waddell4 email, Jason Hinds4 email, Paul Golby5 email, Farahnaz Movahedzadeh1,6 email, Robert A Cox7 email, Rosangela Frita1 email, Annemieke MC ten Bokum8 email, Lorenz Wernisch2 email and Neil G Stoker1 email

Department of Pathology and Infectious Diseases, Royal Veterinary College, Royal College Street, London, NW1 0TU, UK

School of Crystallography, Birkbeck College, London, WC1E 7HX, UK

TB Research, CEPR, Health Protection Agency, Porton Down, Salisbury, SP4 0JG, UK

Medical Microbiology, Division of Cellular and Molecular Medicine, St George's University of London, Cranmer Terrace, Tooting, London, SW17 0RE, UK

Veterinary Laboratories Agency, Woodham Lane, New Haw, Addlestone, Surrey, KT15 3NB, UK

Institute for Tuberculosis Research College of Pharmacy, University of Illinois at Chicago, Chicago, Illinois, 60612-7231, USA

Division of Mycobacterial Research, National Institute for Medical Research, The Ridgeway, Mill Hill, London, NW7 1AA, UK

Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK

author email corresponding author email

Genome Biology 2007, 8:R265doi:10.1186/gb-2007-8-12-r265

Published: 13 December 2007

Subject areas: Bioinformatics, Genome studies, Microbiology and parasitology

Abstract

We describe an analysis, applicable to any spotted microarray dataset produced using genomic DNA as a reference, that quantifies prokaryotic levels of mRNA on a genome-wide scale. Applying this to Mycobacterium tuberculosis, we validate the technique, show a correlation between level of expression and biological importance, define the complement of invariant genes and analyze absolute levels of expression by functional class to develop ways of understanding an organism's biology without comparison to another growth condition.


© 1999-2010 BioMed Central Ltd unless otherwise stated. Part of Springer Science+Business Media.