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Evaluation of alternative RNA labeling protocols for transcript profiling with Arabidopsis AGRONOMICS1 tiling arrays

Overview of attention for article published in Plant Methods, June 2012
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Title
Evaluation of alternative RNA labeling protocols for transcript profiling with Arabidopsis AGRONOMICS1 tiling arrays
Published in
Plant Methods, June 2012
DOI 10.1186/1746-4811-8-18
Pubmed ID
Authors

Marlen Müller, Andrea Patrignani, Hubert Rehrauer, Wilhelm Gruissem, Lars Hennig

Abstract

Microarrays are routine tools for transcript profiling, and genomic tiling arrays such as the Arabidopsis AGRONOMICS1 arrays have been found to be highly suitable for such experiments because changes in genome annotation can be easily integrated at the data analysis level. In a transcript profiling experiment, RNA labeling is a critical step, most often initiated by oligo-dT-primed reverse transcription. Although this has been found to be a robust and reliable method, very long transcripts or non-polyadenylated transcripts might be labeled inefficiently. In this study, we first provide data handling methods to analyze AGRONOMICS1 tiling microarrays based on the TAIR10 genome annotation. Second, we describe methods to easily quantify antisense transcripts on such tiling arrays. Third, we test a random-primed RNA labeling method, and find that on AGRONOMICS1 arrays this method has similar general performance as the conventional oligo-dT-primed method. In contrast to the latter, however, the former works considerably better for long transcripts and for non-polyadenylated transcripts such as found in mitochondria and plastids. We propose that researchers interested in organelle function use the random-primed method to unleash the full potential of genomic tiling arrays.

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The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 6%
Mexico 1 6%
Portugal 1 6%
Unknown 13 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 31%
Student > Ph. D. Student 3 19%
Professor 2 13%
Student > Bachelor 1 6%
Student > Master 1 6%
Other 3 19%
Unknown 1 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 69%
Biochemistry, Genetics and Molecular Biology 2 13%
Social Sciences 1 6%
Chemistry 1 6%
Unknown 1 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 June 2012.
All research outputs
#20,159,700
of 22,668,244 outputs
Outputs from Plant Methods
#1,038
of 1,070 outputs
Outputs of similar age
#151,238
of 167,239 outputs
Outputs of similar age from Plant Methods
#4
of 6 outputs
Altmetric has tracked 22,668,244 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
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