A bias-reducing strategy in profiling small RNAs using Solexa

Guihua Sun, Xiwei Wu, Jinhui Wang, Haiqing Li, Xuejun Li, Hanlin Gao, John Rossi, Yun Yen

Research output: Contribution to journalArticlepeer-review

39 Citations (Scopus)

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 workaround solution to reveal the "true" small RNAome. Published by Cold Spring Harbor Laboratory Press.

Original languageEnglish
Pages (from-to)2256-2262
Number of pages7
JournalRNA
Volume17
Issue number12
DOIs
Publication statusPublished - Dec 2011

Keywords

  • Deep sequencing
  • Small RNA
  • Solexa
  • microRNA

ASJC Scopus subject areas

  • Molecular Biology

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