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Nucleic Acids Research Advance Access originally published online on April 9, 2009
Nucleic Acids Research 2009 37(11):3588-3601; doi:10.1093/nar/gkp213
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Nucleic Acids Research, 2009, Vol. 37, No. 11 3588-3601
© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Molecular Biology

Protein-coding gene promoters in Methanocaldococcus (Methanococcus) jannaschii

Jian Zhang1, Enhu Li2 and Gary J. Olsen1,3,*

1Department of Microbiology, 2Department of Biochemistry and 3Institute for Genomic Biology, University of Illinois at Urbana-Champaign, 601 South Goodwin Avenue, Urbana, IL 61801, USA

*To whom correspondence should be addressed. Tel: +1 217 244 0616; Fax: +1 217 244 6697; Email: gary{at}life.illinois.edu

Received June 24, 2008. Revised March 13, 2009. Accepted March 16, 2009.

Although Methanocaldococcus (Methanococcus) jannaschii was the first archaeon to have its genome sequenced, little is known about the promoters of its protein-coding genes. To expand our knowledge, we have experimentally identified 131 promoters for 107 protein-coding genes in this genome by mapping their transcription start sites. Compared to previously identified promoters, more than half of which are from genes for stable RNAs, the protein-coding gene promoters are qualitatively similar in overall sequence pattern, but statistically different at several positions due to greater variation among their sequences. Relative binding affinity for general transcription factors was measured for 12 of these promoters by competition electrophoretic mobility shift assays. These promoters bind the factors less tightly than do most tRNA gene promoters. When a position weight matrix (PWM) was constructed from the protein gene promoters, factor binding affinities correlated with corresponding promoter PWM scores. We show that the PWM based on our data more accurately predicts promoters in the genome and transcription start sites than could be done with the previously available data. We also introduce a PWM logo, which visually displays the implications of observing a given base at a position in a sequence.

Present address: Enhu Li, Division of Biology, California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125, USA


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