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A Quantitative Comparison of Cell-Type-Specific Microarray Gene Expression Profiling Methods in the Mouse Brain

Overview of attention for article published in PLOS ONE, January 2011
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Title
A Quantitative Comparison of Cell-Type-Specific Microarray Gene Expression Profiling Methods in the Mouse Brain
Published in
PLOS ONE, January 2011
DOI 10.1371/journal.pone.0016493
Pubmed ID
Authors

Benjamin W. Okaty, Ken Sugino, Sacha B. Nelson

Abstract

Expression profiling of restricted neural populations using microarrays can facilitate neuronal classification and provide insight into the molecular bases of cellular phenotypes. Due to the formidable heterogeneity of intermixed cell types that make up the brain, isolating cell types prior to microarray processing poses steep technical challenges that have been met in various ways. These methodological differences have the potential to distort cell-type-specific gene expression profiles insofar as they may insufficiently filter out contaminating mRNAs or induce aberrant cellular responses not normally present in vivo. Thus we have compared the repeatability, susceptibility to contamination from off-target cell-types, and evidence for stress-responsive gene expression of five different purification methods--Laser Capture Microdissection (LCM), Translating Ribosome Affinity Purification (TRAP), Immunopanning (PAN), Fluorescence Activated Cell Sorting (FACS), and manual sorting of fluorescently labeled cells (Manual). We found that all methods obtained comparably high levels of repeatability, however, data from LCM and TRAP showed significantly higher levels of contamination than the other methods. While PAN samples showed higher activation of apoptosis-related, stress-related and immediate early genes, samples from FACS and Manual studies, which also require dissociated cells, did not. Given that TRAP targets actively translated mRNAs, whereas other methods target all transcribed mRNAs, observed differences may also reflect translational regulation.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 175 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 14 8%
United Kingdom 2 1%
Netherlands 2 1%
Canada 2 1%
Switzerland 1 <1%
Israel 1 <1%
Portugal 1 <1%
Germany 1 <1%
Japan 1 <1%
Other 1 <1%
Unknown 149 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 55 31%
Student > Ph. D. Student 52 30%
Professor > Associate Professor 10 6%
Student > Bachelor 8 5%
Student > Doctoral Student 8 5%
Other 26 15%
Unknown 16 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 90 51%
Neuroscience 26 15%
Biochemistry, Genetics and Molecular Biology 14 8%
Medicine and Dentistry 13 7%
Engineering 8 5%
Other 7 4%
Unknown 17 10%