The use of molecular indexing technology (unique molecular labels, UMIs, stochastic labels, molecular labels) can be an important tool for identifying and correcting PCR duplicates in NGS data analysis.

While small RNA sequencing is known to suffer from substantial bias, it has been shown by multiple groups that this bias is the result of ligation steps, rather than PCR amplification (1-3). We also demonstrated this independently in this whitepaper, Reduced-Bias Small RNA Library Preparation with Gel-Free or Low-Input Options. The following quotes are from research articles that demonstrate negligible bias in the PCR step of small RNA library preparation:

 

“We also established in this experiment that the bias was not PCR-dependent, by reducing the number of PCR cycles down from 25 to 18, without any significant effect on the results.”

Jayaprakash et al., NAR 2011

 

“…RT and PCR steps did not have a significant impact on read frequencies.”

Hafner et al., RNA 2011

 

“These results suggest that the amplification steps in library construction and the downstream steps to prepare the samples for sequencing are not responsible for the bias seen…”

Fuchs et al., PLOS One 2015

 

Common findings of these papers were that all of the bias seen stemmed from the ligation steps. Two of these papers, and additional papers (4-6), also show that the use of adapters containing randomized bases is effective in reducing this ligation bias. Thus, in order to reduce bias in small RNA libraries, the use of randomized adapters is a more effective strategy than the use of UMIs, which provide little benefit as there is little bias in the PCR step of small library preparation. The NEXTflex® Small RNA-Seq Kit v3 is the only small RNA library preparation kit on the market that features randomized adapters to reduce bias, a strategy proven to be effective time and again in the published, peer-reviewed literature.

NEXTflex Small RNA Seq Kit v3 detects more miRNAs in an equimolar mixture of 963 miRNAs  Libraries were prepared in triplicate from the Miltenyi® miRXplore® Universal Reference sample and the average number of miRNAs detected at the indicated thresholds was calculated. QIAGEN® libraries were analyzed with and without UMI correction, with the almost identical results demonstrating that UMIs no not effectively reduce bias in small RNA library preparation.

 

  1. Jayaprakash, A. D., Jabado O., Brown, B. D. and Sachidanandam, R. (Sept 2, 2011). Identification and remediation of biases in the activity of RNA ligases in small-RNA deep sequencing Nuc Acid Res, 1–12. doi:10.1093/nar/gkr693
  2. Hafner, M., et al. (2011). RNA-ligase-dependent biases in miRNA representation in deep-sequenced small RNA cDNA libraries. RNA, 17(9), 1697–1712. http://doi.org/10.1261/rna.2799511
  3. Fuchs, R. T., Sun, Z., Zhuang, F., & Robb, G. B. (2015). Bias in Ligation-Based Small RNA Sequencing Library Construction Is Determined by Adaptor and RNA Structure. PLoS ONE, 10(5), e0126049. http://doi.org/10.1371/journal.pone.0126049
  4. Sun, G., et al. (2011). A bias-reducing strategy in profiling small RNAs using Solexa. RNA, 17(12), 2256–2262. http://doi.org/10.1261/rna.028621.111.
  5. Sorefan, K., et al. (2012). Reducing ligation bias of small RNAs in libraries for next generation sequencing. Silence, 3, 4. http://doi.org/10.1186/1758-907X-3-4.
  6. Zhang, Z., Lee, J. E., Riemondy, K., Anderson, E. M., & Yi, R. (2013). High-efficiency RNA cloning enables accurate quantification of miRNA expression by deep sequencing. Genome Biology, 14(10), R109. http://doi.org/10.1186/gb-2013-14-10-r109.

For research use only. Not for use in diagnostic procedures.