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A Complete Set of Nascent Transcription Rates for Yeast Genes

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Title
A Complete Set of Nascent Transcription Rates for Yeast Genes
Published in
PLOS ONE, November 2010
DOI 10.1371/journal.pone.0015442
Pubmed ID
Authors

Vicent Pelechano, Sebastián Chávez, José E. Pérez-Ortín

Abstract

The amount of mRNA in a cell is the result of two opposite reactions: transcription and mRNA degradation. These reactions are governed by kinetics laws, and the most regulated step for many genes is the transcription rate. The transcription rate, which is assumed to be exercised mainly at the RNA polymerase recruitment level, can be calculated using the RNA polymerase densities determined either by run-on or immunoprecipitation using specific antibodies. The yeast Saccharomyces cerevisiae is the ideal model organism to generate a complete set of nascent transcription rates that will prove useful for many gene regulation studies. By combining genomic data from both the GRO (Genomic Run-on) and the RNA pol ChIP-on-chip methods we generated a new, more accurate nascent transcription rate dataset. By comparing this dataset with the indirect ones obtained from the mRNA stabilities and mRNA amount datasets, we are able to obtain biological information about posttranscriptional regulation processes and a genomic snapshot of the location of the active transcriptional machinery. We have obtained nascent transcription rates for 4,670 yeast genes. The median RNA polymerase II density in the genes is 0.078 molecules/kb, which corresponds to an average of 0.096 molecules/gene. Most genes have transcription rates of between 2 and 30 mRNAs/hour and less than 1% of yeast genes have >1 RNA polymerase molecule/gene. Histone and ribosomal protein genes are the highest transcribed groups of genes and other than these exceptions the transcription of genes is an infrequent phenomenon in a yeast cell.

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Geographical breakdown

Country Count As %
Germany 2 1%
United States 2 1%
Chile 1 <1%
Canada 1 <1%
France 1 <1%
Spain 1 <1%
Poland 1 <1%
Unknown 182 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 61 32%
Researcher 39 20%
Student > Master 18 9%
Professor 15 8%
Student > Bachelor 11 6%
Other 27 14%
Unknown 20 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 87 46%
Biochemistry, Genetics and Molecular Biology 55 29%
Physics and Astronomy 5 3%
Computer Science 3 2%
Chemistry 3 2%
Other 16 8%
Unknown 22 12%