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Explaining the correlations among properties of mammalian promoters

Overview of attention for article published in Nucleic Acids Research, March 2014
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Title
Explaining the correlations among properties of mammalian promoters
Published in
Nucleic Acids Research, March 2014
DOI 10.1093/nar/gku115
Pubmed ID
Authors

Martin C. Frith

Abstract

Proximal promoters are fundamental genomic elements for gene expression. They vary in terms of GC percentage, CpG abundance, presence of TATA signal, evolutionary conservation, chromosomal spread of transcription start sites and breadth of expression across cell types. These properties are correlated, and it has been suggested that there are two classes of promoters: one class with high CpG, widely spread transcription start sites and broad expression, and another with TATA signals, narrow spread and restricted expression. However, it has been unclear why these properties are correlated in this way. We reexamined these features using the deep FANTOM5 CAGE data from hundreds of cell types. First, we point out subtle but important biases in previous definitions of promoters and of expression breadth. Second, we show that most promoters are rather nonspecifically expressed across many cell types. Third, promoters' expression breadth is independent of maximum expression level, and therefore correlates with average expression level. Fourth, the data show a more complex picture than two classes, with a network of direct and indirect correlations among promoter properties. By tentatively distinguishing the direct from the indirect correlations, we reveal simple explanations for them.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 4%
United Kingdom 3 4%
Canada 1 1%
Denmark 1 1%
Chile 1 1%
Russia 1 1%
Korea, Republic of 1 1%
Japan 1 1%
Spain 1 1%
Other 0 0%
Unknown 69 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 33%
Student > Ph. D. Student 24 29%
Student > Master 6 7%
Student > Bachelor 5 6%
Professor 4 5%
Other 13 16%
Unknown 3 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 46 56%
Biochemistry, Genetics and Molecular Biology 18 22%
Medicine and Dentistry 4 5%
Computer Science 3 4%
Engineering 3 4%
Other 3 4%
Unknown 5 6%