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    • Feb 2008
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    PubMed: Analyzing Gene Expression from Marine Microbial Communities using Environment

    Syndicated from PubMed RSS Feeds

    Related Articles Analyzing Gene Expression from Marine Microbial Communities using Environmental Transcriptomics.

    J Vis Exp. 2009;(24):

    Authors: Poretsky RS, Gifford S, Rinta-Kanto J, Vila-Costa M, Moran MA

    Analogous to metagenomics, environmental transcriptomics (metatranscriptomics) retrieves and sequences environmental mRNAs from a microbial assemblage without prior knowledge of what genes the community might be expressing. Thus it provides the most unbiased perspective on community gene expression in situ. Environmental transcriptomics protocols are technically difficult since prokaryotic mRNAs generally lack the poly(A) tails that make isolation of eukaryotic messages relatively straightforward (1) and because of the relatively short half lives of mRNAs (2). In addition, mRNAs are much less abundant than rRNAs in total RNA extracts, thus an rRNA background often overwhelms mRNA signals. However, techniques for overcoming some of these difficulties have recently been developed. A procedure for analyzing environmental transcriptomes by creating clone libraries using random primers to reverse-transcribe and amplify environmental mRNAs was recently described was successful in two different natural environments, but results were biased by selection of the random primers used to initiate cDNA synthesis (3). Advances in linear amplification of mRNA obviate the need for random primers in the amplification step and make it possible to use less starting material decreasing the collection and processing time of samples and thereby minimizing RNA degradation (4). In vitro transcription methods for amplifying mRNA involve polyadenylating the mRNA and incorporating a T7 promoter onto the 3' end of the transcript. Amplified RNA (aRNA) can then be converted to double stranded cDNA using random hexamers and directly sequenced by pyrosequencing (5). A first use of this method at Station ALOHA demonstrated its utility for characterizing microbial community gene expression (6).

    PMID: 19229184 [PubMed - in process]



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