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Consistent errors in first strand cDNA due to random hexamer mispriming.

Thomas P van Gurp1, Lauren M McIntyre2, Koen J F Verhoeven1

  • 1Netherlands Institute of Ecology (NIOO-KNAW), Department of Terrestrial Ecology, Wageningen, The Netherlands.

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|January 4, 2014
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Summary
This summary is machine-generated.

Random hexamer priming in RNA sequencing (RNA-seq) can introduce sequence errors. Mismatches during this process, particularly in the first seven nucleotides, are linked to specific biases, impacting downstream analyses.

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Random hexamer priming is a common method for complementary DNA (cDNA) synthesis in RNA sequencing (RNA-seq).
  • Previous studies have noted sequence bias associated with random hexamers.
  • Emerging evidence suggests mispriming events may contribute to sequence discrepancies between RNA and cDNA reads.

Purpose of the Study:

  • To investigate random hexamer mispriming as a potential source of errors in RNA-seq data.
  • To analyze sequence mismatch patterns in relation to random hexamer priming.

Main Methods:

  • Analysis of two independent RNA-seq datasets derived from synthetic External RNA Controls Consortium (ERCC) spike-in sequences.
  • Examination of first-strand cDNA synthesis using random hexamer priming on RNA templates.
  • Characterization of mismatch errors in terms of position, nucleotide specificity, and thermodynamic stability.

Main Results:

  • Consistent, position- and nucleotide-specific mismatch errors were observed in the first seven nucleotides of cDNA synthesized from RNA.
  • Mismatch error distributions were similar across both analyzed datasets.
  • Thermodynamically stable mismatches were found to be more prevalent, indicating a non-random error source.

Conclusions:

  • RNA-DNA mispriming by specific random hexamers is strongly indicated as the cause of observed sequence errors in RNA-seq.
  • The consistency and specificity of these mispriming errors necessitate careful consideration in downstream RNA-seq data analysis.
  • Failure to account for mispriming errors may have significant implications for the accuracy of various biological applications.