Open Access Open Badges Method

Quantification of global transcription patterns in prokaryotes using spotted microarrays

Ben Sidders1, Mike Withers1, Sharon L Kendall1, Joanna Bacon3, Simon J Waddell4, Jason Hinds4, Paul Golby5, Farahnaz Movahedzadeh16, Robert A Cox7, Rosangela Frita1, Annemieke MC ten Bokum8, Lorenz Wernisch2 and Neil G Stoker1*

Author Affiliations

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

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

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

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

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

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

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

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

For all author emails, please log on.

Genome Biology 2007, 8:R265  doi:10.1186/gb-2007-8-12-r265

Published: 13 December 2007


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.