Email updates

Keep up to date with the latest news and content from Genome Biology and BioMed Central.

Open Access Research

Short RNA half-lives in the slow-growing marine cyanobacterium Prochlorococcus

Claudia Steglich12, Debbie Lindell13, Matthias Futschik45, Trent Rector67, Robert Steen6 and Sallie W Chisholm1*

Author Affiliations

1 Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Cambridge, MA 02139, USA

2 University of Freiburg, Faculty of Biology, D-79104 Freiburg, Germany

3 Technion - Israel Institute of Technology, Faculty of Biology, Haifa 32000, Israel

4 University of Algarve, Institute for Biotechnology and Bioengineering, Centre for Molecular and Structural Biomedicine, 8005-139 Faro, Portugal

5 Humboldt University, Institute for Theoretical Biology, Charité, 10115 Berlin, Germany

6 Harvard Medical School, Department of Genetics, Biopolymers Facility, Boston, MA 02115, USA

7 PerkinElmer Life and Analytical Sciences, Waltham, MA 02451, USA

For all author emails, please log on.

Genome Biology 2010, 11:R54  doi:10.1186/gb-2010-11-5-r54

Published: 19 May 2010

Additional files

Additional file 1:

Table listing RNA half-lives and decay times for the whole transcriptome of P. marinus strain MED4. Standard errors for half-lives and decay times are presented in columns H and J. For the decay times the lower (column K) and upper (column L) bounds of error intervals are also given.

Format: PPT Size: 134KB Download file

This file can be viewed with: Microsoft PowerPoint Viewer

Open Data

Additional file 2:

Figure comparing microarray and quantitative RT-PCR expression profiles for 17 selected genes. The top panel compares microarray expression signals (MA; [microarray signal intensity of expression]) and quantitative RT-PCR expression signals (qPCR; [normalized to 100% at maximum]) of biological triplicates. The lower panel shows expression profiles for biological triplicates determined by microarrays (red line) and quantitative RT-PCR (black lines; note for series B two samples at time point 2.5 minutes (in grey) are illustrated).

Format: PPT Size: 82KB Download file

This file can be viewed with: Microsoft PowerPoint Viewer

Open Data

Additional file 3:

Table with estimates of half-lives and decay rates of genes organized in operons and their cluster membership.

Format: PPT Size: 147KB Download file

This file can be viewed with: Microsoft PowerPoint Viewer

Open Data

Additional file 4:

Figure displaying the relationship between the gene position within an operon and (a) half-life or (b) decay rate.

Format: PPT Size: 446KB Download file

This file can be viewed with: Microsoft PowerPoint Viewer

Open Data

Additional file 5:

Figure showing the relationship between single probe positions of genes with a size of at least 2 kb (monocistrons and first genes in operons) and (a) half-life or (b) decay rate.

Format: XLS Size: 539KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional file 6:

Table that compares computationally predicted operons from [41] with operon assignment based on this study.

Format: XLS Size: 47KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional file 7:

Figure comparing transcript profiles of cells treated with rifampicin dissolved in water or DMSO. RNA expression levels were determined by quantitative real-time PCR and compared to microarray data (MA) for transcripts with the regular exponential decay profiles (representing the majority of the transcriptome) that have very short half-lives: (a) recA and (b) PMM1077 and (c-e) transcripts from the type II atp operon.

Format: XLS Size: 34KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional file 8:

Table with information on oligonucleotides used for quantitative RT-PCR.

Format: XLS Size: 26KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data