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Quantitative Bias in Illumina TruSeq and a Novel Post Amplification Barcoding Strategy for Multiplexed DNA and Small RNA Deep Sequencing

Overview of attention for article published in PLOS ONE, October 2011
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Title
Quantitative Bias in Illumina TruSeq and a Novel Post Amplification Barcoding Strategy for Multiplexed DNA and Small RNA Deep Sequencing
Published in
PLOS ONE, October 2011
DOI 10.1371/journal.pone.0026969
Pubmed ID
Authors

Filip Van Nieuwerburgh, Sandra Soetaert, Katie Podshivalova, Eileen Ay-Lin Wang, Lana Schaffer, Dieter Deforce, Daniel R. Salomon, Steven R. Head, Phillip Ordoukhanian

Abstract

Here we demonstrate a method for unbiased multiplexed deep sequencing of RNA and DNA libraries using a novel, efficient and adaptable barcoding strategy called Post Amplification Ligation-Mediated (PALM). PALM barcoding is performed as the very last step of library preparation, eliminating a potential barcode-induced bias and allowing the flexibility to synthesize as many barcodes as needed. We sequenced PALM barcoded micro RNA (miRNA) and DNA reference samples and evaluated the quantitative barcode-induced bias in comparison to the same reference samples prepared using the Illumina TruSeq barcoding strategy. The Illumina TruSeq small RNA strategy introduces the barcode during the PCR step using differentially barcoded primers, while the TruSeq DNA strategy introduces the barcode before the PCR step by ligation of differentially barcoded adaptors. Results show virtually no bias between the differentially barcoded miRNA and DNA samples, both for the PALM and the TruSeq sample preparation methods. We also multiplexed miRNA reference samples using a pre-PCR barcode ligation. This barcoding strategy results in significant bias.

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Mendeley readers

The data shown below were compiled from readership statistics for 171 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 5%
United Kingdom 4 2%
Spain 2 1%
Czechia 1 <1%
Cuba 1 <1%
Germany 1 <1%
Denmark 1 <1%
Netherlands 1 <1%
Canada 1 <1%
Other 1 <1%
Unknown 150 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 56 33%
Student > Ph. D. Student 40 23%
Student > Master 21 12%
Professor > Associate Professor 9 5%
Other 9 5%
Other 22 13%
Unknown 14 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 98 57%
Biochemistry, Genetics and Molecular Biology 28 16%
Medicine and Dentistry 11 6%
Environmental Science 5 3%
Computer Science 3 2%
Other 8 5%
Unknown 18 11%