A bias-reducing strategy in profiling small RNAs using Solexa

  1. Yun Yen1,5
  1. 1Department of Molecular Pharmacology, Beckman Research Institute of the City of Hope, Duarte, California 91010-3000, USA
  2. 2Bioinformatics Core, Beckman Research Institute of the City of Hope, Duarte, California 91010-3000, USA
  3. 3Solexa Sequencing Core, Beckman Research Institute of the City of Hope, Duarte, California 91010-3000, USA
  4. 4Department of Molecular and Cellular Biology, Beckman Research Institute of the City of Hope, Duarte, California 91010-3000, USA

    Abstract

    Small RNAs (smRNAs) encompass several different classes of short noncoding RNAs. Progress in smRNA research and applications has coincided with the advance of techniques to detect them. Next-generation sequencing technologies are becoming the preferred smRNA profiling method because of their high-throughput capacity and digitized results. In our small RNA profiling study using Solexa, we observed serious biases introduced by the 5′ adaptors in small RNA species coverage and abundance; therefore, the results cannot reveal the accurate composition of the small RNAome. We found that the profiling results can be significantly optimized by using an index pool of 64 customized 5′ adaptors. This pool of 64 adaptors can be further reduced to four smaller index pools, each containing 16 adaptors, to minimize profiling bias and facilitate multiplexing. It is plausible that this type of bias exists in other deep-sequencing technologies, and adaptor pooling could be an easy work-around solution to reveal the “true” small RNAome.

    Keywords

    Footnotes

    • Received June 4, 2011.
    • Accepted September 15, 2011.
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