Metatranscriptomics reveals unique microbial small RNAs in the ocean’s water column


Microbial gene expression in the environment has recently been assessed via pyrosequencing of total RNA extracted directly from natural microbial assemblages. Several such ‘metatranscriptomic’ studies1,2 have reported that many complementary DNA sequences shared no significant homology with known peptide sequences, and so might represent transcripts from uncharacterized proteins. Here we report that a large fraction of cDNA sequences detected in microbial metatranscriptomic data sets are comprised of well-known small RNAs (sRNAs)3, as well as new groups of previously unrecognized putative sRNAs (psRNAs). These psRNAs mapped specifically to intergenic regions of microbial genomes recovered from similar habitats, displayed characteristic conserved secondary structures and were frequently flanked by genes that indicated potential regulatory functions. Depth-dependent variation of psRNAs generally reflected known depth distributions of broad taxonomic groups4, but fine-scale differences in the psRNAs within closely related populations indicated potential roles in niche adaptation. Genome-specific mapping of a subset of psRNAs derived from predominant planktonic species such as Pelagibacter revealed recently discovered as well as potentially new regulatory elements. Our analyses show that metatranscriptomic data sets can reveal new information about the diversity, taxonomic distribution and abundance of sRNAs in naturally occurring microbial communities, and indicate their involvement in environmentally relevant processes including carbon metabolism and nutrient acquisition.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Inventory of RNAs from each depth in the microbial metatranscriptomic datasets.
Figure 2: Abundance, distribution and features of the top twenty most abundant sRNA and psRNA groups identified in the metatranscriptomic data.
Figure 3: Characteristics of psRNA groups consistent with known sRNAs.
Figure 4: Normalized cDNA/DNA ratios of expressed IGRs (eIGRs) on the P. ubique HTCC7211 genome at all four depths.

Accession codes

Data deposits

The sequences reported here have been deposited in GenBank under accession numbers SRA007802.3, SRA000263, SRA007804.3 and SRA007806.3 corresponding to cDNA sequences, and SRA007801.5, SRA000262, SRA007803.3 and SRA007805.4 corresponding to DNA sequences, for 25 m, 75 m, 125 m and 500 m samples, respectively.


  1. 1

    Frias-Lopez, J. et al. Microbial community gene expression in ocean surface waters. Proc. Natl Acad. Sci. USA 105, 3805–3810 (2008)

    ADS  CAS  Article  Google Scholar 

  2. 2

    Gilbert, J. A. et al. Detection of large numbers of novel sequences in the metatranscriptomes of complex marine microbial communities. PLoS ONE 3, e3042 (2008)

    ADS  Article  Google Scholar 

  3. 3

    Storz, G. & Haas, D. A guide to small RNAs in microorganisms. Curr. Opin. Microbiol. 10, 93–95 (2007)

    Article  Google Scholar 

  4. 4

    DeLong, E. F. et al. Community genomics among stratified microbial assemblages in the ocean’s interior. Science 311, 496–503 (2006)

    ADS  CAS  Article  Google Scholar 

  5. 5

    Gottesman, S. Stealth regulation: biological circuits with small RNA switches. Genes Dev. 16, 2829–2842 (2002)

    CAS  Article  Google Scholar 

  6. 6

    Lenz, D. H. et al. The small RNA chaperone Hfq and multiple small RNAs control quorum sensing in Vibrio harveyi and Vibrio cholerae . Cell 118, 69–82 (2004)

    CAS  Article  Google Scholar 

  7. 7

    Duehring, U., Axmann, I. M., Hess, W. R. & Wilde, A. An internal antisense RNA regulates expression of the photosynthesis gene isiA . Proc. Natl Acad. Sci. USA 103, 7054–7058 (2006)

    ADS  CAS  Article  Google Scholar 

  8. 8

    Steglich, C. et al. The challenge of regulation in a minimal photoautotroph: non-coding RNAs in Prochlorococcus . PLoS Genet. 4, e1000173 (2008)

    Article  Google Scholar 

  9. 9

    Vogel, J. et al. RNomics in Escherichia coli detects new sRNA species and indicates parallel transcriptional output in bacteria. Nucleic Acids Res. 31, 6435–6443 (2003)

    CAS  Article  Google Scholar 

  10. 10

    Silvaggi, J. M., Perkins, J. B. & Losick, R. Genes for small, noncoding RNAs under sporulation control in Bacillus subtilis . J. Bacteriol. 188, 532–541 (2006)

    CAS  Article  Google Scholar 

  11. 11

    Karl, D. M. & Lukas, R. The Hawaii Ocean Time-series (HOT) program: Background, rationale and field implementation. Deep-Sea Res. II 43, 129–156 (1996)

    ADS  CAS  Article  Google Scholar 

  12. 12

    Kawano, M., Reynolds, A. A., Miranda-Rios, J. & Storz, G. Detection of 5′- and 3′-UTR-derived small RNAs and cis-encoded antisense RNAs in Escherichia coli . Nucleic Acids Res. 33, 1040–1050 (2005)

    CAS  Article  Google Scholar 

  13. 13

    Eddy, S. INFERNAL User’s Guide, Version 0. 72〉 (2007)

    Google Scholar 

  14. 14

    Griffiths-Jones, S. et al. Rfam: annotating non-coding RNAs in complete genomes. Nucleic Acids Res. 33, D121–D124 (2005)

    CAS  Article  Google Scholar 

  15. 15

    Brantl, S. Bacterial gene regulation: from transcription attenuation to riboswitches and ribozymes. Trends Microbiol. 12, 473–475 (2004)

    CAS  Article  Google Scholar 

  16. 16

    Schattner, P. Searching for RNA genes using base-composition statistics. Nucleic Acids Res. 30, 2076–2082 (2002)

    CAS  Article  Google Scholar 

  17. 17

    Ré, M. & Pavesi, G. in Applications of Fuzzy Sets Theory (eds Masulli, F., Mitra, S. & Pasi, G.) 544–550 (Springer, 2007)

    Google Scholar 

  18. 18

    Konstantinidis, K. T. & DeLong, E. F. Genomic patterns of recombination, clonal divergence and environment in marine microbial populations. ISME J. 2, 1052–1065 (2008)

    CAS  Article  Google Scholar 

  19. 19

    Rusch, D. B. et al. The Sorcerer II Global Ocean Sampling expedition: Northwest Atlantic through eastern tropical Pacific. PLoS Biol. 5, 398–431 (2007)

    ADS  CAS  Article  Google Scholar 

  20. 20

    Vogel, J. & Wagner, E. G. H. Target identification of small noncoding RNAs in bacteria. Curr. Opin. Microbiol. 10, 262–270 (2007)

    CAS  Article  Google Scholar 

  21. 21

    Hershberg, R., Altuvia, S. & Margalit, H. A survey of small RNA-encoding genes in Escherichia coli . Nucleic Acids Res. 31, 1813–1820 (2003)

    CAS  Article  Google Scholar 

  22. 22

    Yao, Z. et al. A computational pipeline for high-throughput discovery of cis-regulatory noncoding RNA in prokaryotes. PLoS Comp. Biol. 3, 1212–1223 (2007)

    CAS  Article  Google Scholar 

  23. 23

    Trotochaud, A. E. & Wassarman, K. M. A highly conserved 6S RNA structure is required for regulation of transcription. Nature Struct. Mol. Biol. 12, 313–319 (2005)

    CAS  Article  Google Scholar 

  24. 24

    Bruttin, A. & Brüssow, H. Site-specific spontaneous deletions in three genome regions of a temperate Streptococcus thermophilus phage. Virology 219, 96–104 (1996)

    CAS  Article  Google Scholar 

  25. 25

    Abreu-Goodger, C. & Merino, E. RibEx: a web server for locating riboswitches and other conserved bacterial regulatory elements. Nucleic Acids Res. 33, W690–W692 (2005)

    CAS  Article  Google Scholar 

  26. 26

    Martiny, A. C., Coleman, M. L. & Chisholm, S. W. Phosphate acquisition genes in Prochlorococcus ecotypes: evidence for genome-wide adaptation. Proc. Natl Acad. Sci. USA 103, 12552–12557 (2006)

    ADS  CAS  Article  Google Scholar 

  27. 27

    Tripp, H. J. et al. Unique glycine-activated riboswitch linked to glycine-serine auxotrophy in SAR11. Environ. Microbiol. 11, 230–238 (2008)

    Article  Google Scholar 

  28. 28

    Hofacker, I. L. Vienna RNA secondary structure server. Nucleic Acids Res. 31, 3429–3431 (2003)

    CAS  Article  Google Scholar 

  29. 29

    Washietl, S., Hofacker, I. L. & Stadler, P. F. Fast and reliable prediction of noncoding RNAs. Proc. Natl Acad. Sci. USA 102, 2454–2459 (2005)

    ADS  CAS  Article  Google Scholar 

  30. 30

    Wendisch, V. F. et al. Isolation of Escherichia coli mRNA and comparison of expression using mRNA and total RNA on DNA microarrays. Anal. Biochem. 290, 205–213 (2001)

    CAS  Article  Google Scholar 

  31. 31

    Vangelder, R. N. et al. Amplified RNA synthesized from limited quantities of heterogeneous cDNA. Proc. Natl Acad. Sci. USA 87, 1663–1667 (1990)

    ADS  CAS  Article  Google Scholar 

  32. 32

    Margulies, M. et al. Genome sequencing in microfabricated high-density picolitre reactors. Nature 437, 376–380 (2005)

    ADS  CAS  Article  Google Scholar 

  33. 33

    Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990)

    CAS  Article  Google Scholar 

  34. 34

    Eddy, S. R. & Durbin, R. RNA sequence-analysis using covariance-models. Nucleic Acids Res. 22, 2079–2088 (1994)

    CAS  Article  Google Scholar 

  35. 35

    Rudd, K. E. EcoGene: a genome sequence database for Escherichia coli K-12. Nucleic Acids Res. 28, 60–64 (2000)

    CAS  Article  Google Scholar 

  36. 36

    Huson, D. H., Auch, A. F., Qi, J. & Schuster, S. C. MEGAN analysis of metagenomic data. Genome Res. 17, 377–386 (2007)

    CAS  Article  Google Scholar 

  37. 37

    Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004)

    CAS  Article  Google Scholar 

  38. 38

    Holste, D., Weiss, O., Grosse, I. & Herzel, H. Are noncoding sequences of Rickettsia prowazekii remnants of “neutralized” genes? J. Mol. Evol. 51, 353–362 (2000)

    ADS  CAS  Article  Google Scholar 

  39. 39

    Mincer, T. J. et al. Quantitative distribution of presumptive archaeal and bacterial nitrifiers in Monterey Bay and the North Pacific subtropical gyre. Environ. Microbiol. 9, 1162–1175 (2007)

    CAS  Article  Google Scholar 

  40. 40

    Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2-[Delta][Delta]CT Method. Methods 25, 402–408 (2001)

    CAS  Article  Google Scholar 

  41. 41

    Noguchi, H., Park, J. & Takagi, T. MetaGene: prokaryotic gene finding from environmental genome shotgun sequences. Nucleic Acids Res. 34, 5623–5630 (2006)

    CAS  Article  Google Scholar 

  42. 42

    Kanehisa, M. & Goto, S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27–30 (2000)

    CAS  Article  Google Scholar 

  43. 43

    Tatusov, R. L., Galperin, M. Y., Natale, D. A. & Koonin, E. V. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 28, 33–36 (2000)

    CAS  Article  Google Scholar 

  44. 44

    Hofacker, I. L., Fekete, M. & Stadler, P. F. Secondary structure prediction for aligned RNA sequences. J. Mol. Biol. 319, 1059–1066 (2002)

    CAS  Article  Google Scholar 

  45. 45

    Axmann, I. M. et al. Identification of cyanobacterial non-coding RNAs by comparative genome analysis. Genome Biol. 6, R73 (2005)

    Article  Google Scholar 

  46. 46

    Jason, S. & Ewan, B. The Bioperl project: motivation and usage. SIGBIO Newsl. 20, 13–14 (2000)

    Google Scholar 

Download references


We are grateful to the University of Hawaii HOT team, and the captain and crew of the RV Kilo Moana for their expert assistance at sea. We also thank S. Schuster for collaboration and advice on pyrosequencing, J. Eppley for help with computational analyses and discussion, and J. Maresca, A. Martinez, J. McCarren and V. Rich for their comments on this manuscript. We thank S. Giovannoni, J. Tripp and M. Schwalbach for sharing their in press manuscript on Pelagibacter riboswitches, and S. Giovannoni, U. Stingl, the J. Craig Venter Institute and the Gordon and Betty Moore Foundation for the genome sequence of Pelagibacter strain HTCC7211. This work was supported by the Gordon and Betty Moore Foundation, National Science Foundation Microbial Observatory Award MCB-0348001, the Department of Energy Genomics GTL Program, the Department of Energy Microbial Genomics Program, and an NSF Science and Technology award, C-MORE. This article is a contribution from the NSF Science and Technology Center for Microbial Oceanography: Research and Education (C-MORE).

Author Contributions E.F.D. conceived and directed the research, coordinated the sequencing effort and collected the samples. Y.S. prepared samples for sequencing, and made the initial observation of sRNA sequences. E.F.D., Y.S. and G.W.T. developed the concept of the paper together. Y.S. and G.W.T. performed the data analysis. Y.S. wrote the first draft of the paper, which was completed by G.W.T. and E.F.D. together.

Author information



Corresponding author

Correspondence to Edward F. DeLong.

Supplementary information

Supplementary Information

This file contains Supplementary Figures 1-6 with Legends, Supplementary Tables 1-3 and Supplementary References. (PDF 5587 kb)

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Shi, Y., Tyson, G. & DeLong, E. Metatranscriptomics reveals unique microbial small RNAs in the ocean’s water column. Nature 459, 266–269 (2009).

Download citation

Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing