Validation of two ribosomal RNA removal methods for microbial metatranscriptomics

Journal name:
Nature Methods
Year published:
Published online


The predominance of rRNAs in the transcriptome is a major technical challenge in sequence-based analysis of cDNAs from microbial isolates and communities. Several approaches have been applied to deplete rRNAs from (meta)transcriptomes, but no systematic investigation of potential biases introduced by any of these approaches has been reported. Here we validated the effectiveness and fidelity of the two most commonly used approaches, subtractive hybridization and exonuclease digestion, as well as combinations of these treatments, on two synthetic five-microorganism metatranscriptomes using massively parallel sequencing. We found that the effectiveness of rRNA removal was a function of community composition and RNA integrity for these treatments. Subtractive hybridization alone introduced the least bias in relative transcript abundance, whereas exonuclease and in particular combined treatments greatly compromised mRNA abundance fidelity. Illumina sequencing itself also can compromise quantitative data analysis by introducing a G+C bias between runs.

At a glance


  1. Technical reproducibility.
    Figure 1: Technical reproducibility.

    (ad) In the correlation plots, each point indicates the abundance of an individual mRNA transcript in two technical replicates. Analysis of technical replicates (i and ii) of Hyb in Illumina run 1 (a), Exo between runs 1 and 2 (b), Hyb between runs 3 and 4 (c; color-coded by source organisms) and Hyb between runs 3 and 4 after normalizing for G+C content by organism (d). Pearson's product moment correlation coefficient, r, for all data points regardless of source organism is shown. Slopes from linear regression of data points for each organism are indicated in c and d.

  2. Effectiveness of bulk rRNA removal.
    Figure 2: Effectiveness of bulk rRNA removal.

    (a,b) Distribution of reads between rRNAs (divided by community member) and total non-rRNAs for each treatment in experiments 1 (a) and 2 (b). (c) Observed and actual rRNA percentage removals for the three and five treatments in experiments 1 and 2. Dashed lines are simulations of observed and actual rRNA percentage removals, when starting rRNA (in controls, rRNA0) accounted for 94.9% (community 1) and 96.9% (community 2) of total RNA. (d) Actual rRNA percentage removal for each organism. Error bars, s.d. There was no net rRNA removal for Spirochaeta by Exo in experiment 1, indicated by an arbitrary negative value.

  3. Enrichment of mRNA in the synthetic communities.
    Figure 3: Enrichment of mRNA in the synthetic communities.

    (a) Fold enrichment of total mRNA abundance. (b) Percentage improvement in mRNA detection sensitivity.

  4. Fidelity of mRNA relative abundance.
    Figure 4: Fidelity of mRNA relative abundance.

    (a,b) Analysis of all seven samples in experiment 1 (a) and the seven samples from run 3 in experiment 2 (b). Bray Curtis similarities between samples are indicated by a dendrogram showing increasing loss of mRNA fidelity with distance from controls. Increasing loss of fidelity between treatments (y axes) and corresponding controls (x axes) is also visually shown using scatter plots. The average percentage and s.d. of mRNAs in treatments exhibiting greater than twofold difference from respective controls (indicated by diagonal dashed lines) is shown in each scatter plot.


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Author information

  1. These authors contributed equally to this work.

    • Shaomei He &
    • Omri Wurtzel


  1. Department of Energy Joint Genome Institute, Walnut Creek, California, USA.

    • Shaomei He,
    • Kanwar Singh,
    • Jeff L Froula,
    • Suzan Yilmaz,
    • Susannah G Tringe,
    • Zhong Wang,
    • Feng Chen,
    • Erika A Lindquist &
    • Philip Hugenholtz
  2. Energy Biosciences Institute, University of California-Berkeley, Berkeley, California, USA.

    • Shaomei He &
    • Philip Hugenholtz
  3. Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.

    • Omri Wurtzel &
    • Rotem Sorek
  4. Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia.

    • Philip Hugenholtz


S.H., K.S., S.G.T., F.C., E.A.L. and P.H. planned the experiments, S.H., K.S. and S.Y. executed the experiments, S.H., O.W., J.L.F., Z.W., R.S. and P.H. performed the data analysis and S.H. and P.H. wrote the manuscript.

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The authors declare no competing financial interests.

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