Genomic tiling array transcriptomics and RNA-seq are two powerful and rapidly developing approaches for unbiased transcriptome analysis. Providing comprehensive identification and quantification of transcripts with an unprecedented resolution, they are leading to major breakthroughs in systems biology. Here we review each step of the analysis from library preparation to the interpretation of the data, with particular attention paid to the possible sources of artifacts. Methodological requirements and statistical frameworks are often similar in both the approaches despite differences in the nature of the data. Tiling array analysis does not require rRNA depletion and benefits from a more mature computational workflow, whereas RNA-Seq has a clear lead in terms of background noise and dynamic range with a considerable potential for evolution with the improvements of sequencing technologies. Being independent of prior sequence knowledge, RNA-seq will boost metatranscriptomics and evolutionary transcriptomics applications.
%0 Journal Article
%1 Mader2011Comprehensive
%A Mäder, Ulrike
%A Nicolas, Pierre
%A Richard, Hugues
%A Bessières, Philippe
%A Aymerich, Stéphane
%D 2011
%J Current Opinion in Biotechnology
%K transcriptomics
%N 1
%P 32--41
%R 10.1016/j.copbio.2010.10.003
%T Comprehensive identification and quantification of microbial transcriptomes by genome-wide unbiased methods
%U http://dx.doi.org/10.1016/j.copbio.2010.10.003
%V 22
%X Genomic tiling array transcriptomics and RNA-seq are two powerful and rapidly developing approaches for unbiased transcriptome analysis. Providing comprehensive identification and quantification of transcripts with an unprecedented resolution, they are leading to major breakthroughs in systems biology. Here we review each step of the analysis from library preparation to the interpretation of the data, with particular attention paid to the possible sources of artifacts. Methodological requirements and statistical frameworks are often similar in both the approaches despite differences in the nature of the data. Tiling array analysis does not require rRNA depletion and benefits from a more mature computational workflow, whereas RNA-Seq has a clear lead in terms of background noise and dynamic range with a considerable potential for evolution with the improvements of sequencing technologies. Being independent of prior sequence knowledge, RNA-seq will boost metatranscriptomics and evolutionary transcriptomics applications.
@article{Mader2011Comprehensive,
abstract = {Genomic tiling array transcriptomics and {RNA}-seq are two powerful and rapidly developing approaches for unbiased transcriptome analysis. Providing comprehensive identification and quantification of transcripts with an unprecedented resolution, they are leading to major breakthroughs in systems biology. Here we review each step of the analysis from library preparation to the interpretation of the data, with particular attention paid to the possible sources of artifacts. Methodological requirements and statistical frameworks are often similar in both the approaches despite differences in the nature of the data. Tiling array analysis does not require {rRNA} depletion and benefits from a more mature computational workflow, whereas {RNA}-Seq has a clear lead in terms of background noise and dynamic range with a considerable potential for evolution with the improvements of sequencing technologies. Being independent of prior sequence knowledge, {RNA}-seq will boost metatranscriptomics and evolutionary transcriptomics applications.},
added-at = {2018-12-02T16:09:07.000+0100},
author = {M\"{a}der, Ulrike and Nicolas, Pierre and Richard, Hugues and Bessi\`{e}res, Philippe and Aymerich, St\'{e}phane},
biburl = {https://www.bibsonomy.org/bibtex/21107ea02d4bd870ecd3186c3ee00a38f/karthikraman},
citeulike-article-id = {8276011},
citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.copbio.2010.10.003},
day = 10,
doi = {10.1016/j.copbio.2010.10.003},
interhash = {d97b7de5c67ea21b6e993ff3032c0895},
intrahash = {1107ea02d4bd870ecd3186c3ee00a38f},
issn = {09581669},
journal = {Current Opinion in Biotechnology},
keywords = {transcriptomics},
month = feb,
number = 1,
pages = {32--41},
posted-at = {2010-11-23 09:55:42},
priority = {2},
timestamp = {2018-12-02T16:09:07.000+0100},
title = {Comprehensive identification and quantification of microbial transcriptomes by genome-wide unbiased methods},
url = {http://dx.doi.org/10.1016/j.copbio.2010.10.003},
volume = 22,
year = 2011
}