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A Versatile Method for Cell-Specific Profiling of Translated mRNAs in Drosophila

Overview of attention for article published in PLOS ONE, July 2012
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Title
A Versatile Method for Cell-Specific Profiling of Translated mRNAs in Drosophila
Published in
PLOS ONE, July 2012
DOI 10.1371/journal.pone.0040276
Pubmed ID
Authors

Amanda Thomas, Pei-Jung Lee, Justin E. Dalton, Krystle J. Nomie, Loredana Stoica, Mauro Costa-Mattioli, Peter Chang, Sergey Nuzhdin, Michelle N. Arbeitman, Herman A. Dierick

Abstract

In Drosophila melanogaster few methods exist to perform rapid cell-type or tissue-specific expression profiling. A translating ribosome affinity purification (TRAP) method to profile actively translated mRNAs has been developed for use in a number of multicellular organisms although it has only been implemented to examine limited sets of cell- or tissue-types in these organisms. We have adapted the TRAP method for use in the versatile GAL4/UAS system of Drosophila allowing profiling of almost any tissue/cell-type with a single genetic cross. We created transgenic strains expressing a GFP-tagged ribosomal protein, RpL10A, under the control of the UAS promoter to perform cell-type specific translatome profiling. The GFP::RpL10A fusion protein incorporates efficiently into ribosomes and polysomes. Polysome affinity purification strongly enriches mRNAs from expected genes in the targeted tissues with sufficient sensitivity to analyze expression in small cell populations. This method can be used to determine the unique translatome profiles in different cell-types under varied physiological, pharmacological and pathological conditions.

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Mendeley readers

The data shown below were compiled from readership statistics for 245 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 2%
United Kingdom 3 1%
Japan 2 <1%
Portugal 1 <1%
Turkey 1 <1%
Spain 1 <1%
Unknown 232 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 59 24%
Student > Ph. D. Student 58 24%
Student > Master 24 10%
Professor > Associate Professor 17 7%
Student > Bachelor 13 5%
Other 38 16%
Unknown 36 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 120 49%
Biochemistry, Genetics and Molecular Biology 49 20%
Neuroscience 28 11%
Medicine and Dentistry 4 2%
Mathematics 3 1%
Other 9 4%
Unknown 32 13%