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Gene Expression Profiling: Metatranscriptomics

  • Jack A. GilbertEmail author
  • Margaret Hughes
Part of the Methods in Molecular Biology book series (MIMB, volume 733)

Abstract

Metatranscriptomics has been developed to help understand how communities respond to changes in their environment. Metagenomic studies provided a snapshot of the genetic composition of the community at any given time. However, short-timescale studies investigating the response of communities to rapid environmental changes (e.g. pollution events or diurnal light availability) require analysis of changes in the abundance and composition of the active fraction of the community. Metatranscriptomics enables researchers to investigate the actively transcribed ribosomal and messenger RNA from a community. It has been applied to environments as diverse as soil and seawater. This chapter outlines sampling protocols and RNA extraction techniques from these two ecosystems, as well as details a method to enrich mRNA in the extracted nucleic acid. Also, a section is dedicated for outlining a bioinformatic procedure for the analysis of metatranscriptomic datasets.

Key words

Metatranscriptomics Marine Soil Expression 

Notes

Acknowledgements

The author would like to thank Margaret Hughes and Neil Hall from the NERC/University of Liverpool Advanced Genomics Facility.

References

  1. 1.
    DeLong EF, Preston CM, Mincer T, Rich V, Hallam SJ, et al. (2006) Community genomics among stratified microbial assemblages in the ocean’s interior. Science 311, 496  –503.PubMedCrossRefGoogle Scholar
  2. 2.
    Rusch DB, Halpern AL, Sutton G, Heidelberg KB, Williamson S, et al. (2007) The Sorcerer II Global Ocean Sampling expedition: northwest Atlantic through eastern tropical Pacific. PLoS Biol. 5, 398  –  431CrossRefGoogle Scholar
  3. 3.
    Yooseph S, Sutton G, Rusch DB, Halpern AL, Williamson SJ, et al. (2007) The Sorcerer II Global Ocean Sampling expedition: expanding the universe of protein families. PLoS Biol. 5, 432–  466.CrossRefGoogle Scholar
  4. 4.
    Handelsman J, Tiedje J, Alvarez-Cohen L, Ashburner M, Cann IKO, et al. (2007) The New Science of metagenomics: revealing the secrets of our microbial planet, Washington, DC: The National Academies Press.Google Scholar
  5. 5.
    Parro V, Moreno-Paz M, Gonzalez-Toril E (2007) Analysis of environmental transcriptomes by DNA microarrays. Environ. Microbiol. 9, 453–  464.PubMedCrossRefGoogle Scholar
  6. 6.
    Poretsky RS, Bano N, Buchan A, LeCleir G, Kleikemper J, et al. (2005) Analysis of microbial gene transcripts in environmental samples. Appl. Environ. Microbiol. 71, 4121–  4126.PubMedCrossRefGoogle Scholar
  7. 7.
    Leininger S, Urich T, Schloter M, Schwark L, Qi J, et al. (2006) Archaea predominate among ammonia-oxidizing prokaryotes in soils. Nature 442, 806  –  809.PubMedCrossRefGoogle Scholar
  8. 8.
    Urich T, Lanzén A, Qi J, Huson DH, Schleper C, et al. (2008) Simultaneous Assessment of Soil Microbial Community Structure and Function through Analysis of the Meta-Transcriptome. PLoS ONE 3: e2527. doi: 10.1371/journal.pone.0002527
  9. 9.
    Frias-Lopez J, Shi Y, Tyson GW, Coleman ML, Schuster SC, et al. (2008) Microbial community gene expression in ocean surface waters. Proc. Natl. Acad. Sci. USA 105, 3805  –10.PubMedCrossRefGoogle Scholar
  10. 10.
    Gilbert JA, Field D, Huang Y, Edwards R, Li W, et al. (2008) Detection of Large Numbers of Novel Sequences in the Metatranscriptomes of Complex Marine Microbial Communities. PLoS ONE 3(8): e3042. doi: 10.1371/journal.pone.0003042
  11. 11.
    Poretsky R.S., Hewson I, Sun S, Allen A. E., Zehr J.P. and Moran, M.A. 2009a. Comparative day/night metatranscriptomic analysis of microbial communities in the North Pacific subtropical gyre. Environ. Microbiol. 11, 1358  –1375.PubMedCrossRefGoogle Scholar
  12. 12.
    Poretsky R.S., Gifford S., Rinta-Kanto J., Vila-Costa M., Moran M.A. 2009b. Analyzing Gene Expression from Marine Microbial Communities using Environmental Transcriptomics. JoVE. 24. http://www.jove.com/index/Details.stp?ID=1086, doi:  10.3791/1086
  13. 13.
    Li W & Godzik A (2006) Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658  –1659.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Plymouth Marine Laboratory, The HoePlymouthUK

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