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Article: Serial Analysis of Gene Expression (SAGE): A useful tool to analyze the cardiac transcriptome

TitleSerial Analysis of Gene Expression (SAGE): A useful tool to analyze the cardiac transcriptome
Authors
KeywordsFunctional genomics
Gene expression
Heart
mRNA
SAGE
Sequencing
Transcriptome
Issue Date2007
Citation
Methods in Molecular Biology, 2007, v. 366, p. 41-59 How to Cite?
AbstractSerial analysis of gene expression (SAGE), a functional genomics technique, can be used for global profiling of gene transcripts. It relies on the preparation and sequencing of cDNA concatemers, but it does not require prior knowledge of the genes to be assayed (as with microarrays). Once analyzed, SAGE data provide both a qualitative and quantitative assessment of potentially every transcript present in a particular cell or tissue type. In this chapter, we describe the fundamental principles of SAGE, describe a complete protocol for the generation of SAGE libraries, and show how it has been employed to generate the first SAGE reference data set of the mouse myocardium. Following the protocols described here, investigators should be able to generate unique mouse heart SAGE libraries, which can be directly compared with our reference library. This permits the identification of transcripts that are differentially expressed as a function of time, age, genetic background or transgenic state, among other factors. SAGE is thus a powerful technique that permits a comprehensive analysis of changes in mRNA abundance. The results provide a snapshot of altered patterns of gene expression in response to any genetic or environmental stimulus that can be used to generate new biological hypotheses or test existing paradigms. © Humana Press Inc.
Persistent Identifierhttp://hdl.handle.net/10722/195184
ISSN
2023 SCImago Journal Rankings: 0.399

 

DC FieldValueLanguage
dc.contributor.authorTarasov, KV-
dc.contributor.authorBrugh, SA-
dc.contributor.authorTarasova, YS-
dc.contributor.authorBoheler, KR-
dc.date.accessioned2014-02-25T01:40:17Z-
dc.date.available2014-02-25T01:40:17Z-
dc.date.issued2007-
dc.identifier.citationMethods in Molecular Biology, 2007, v. 366, p. 41-59-
dc.identifier.issn1064-3745-
dc.identifier.urihttp://hdl.handle.net/10722/195184-
dc.description.abstractSerial analysis of gene expression (SAGE), a functional genomics technique, can be used for global profiling of gene transcripts. It relies on the preparation and sequencing of cDNA concatemers, but it does not require prior knowledge of the genes to be assayed (as with microarrays). Once analyzed, SAGE data provide both a qualitative and quantitative assessment of potentially every transcript present in a particular cell or tissue type. In this chapter, we describe the fundamental principles of SAGE, describe a complete protocol for the generation of SAGE libraries, and show how it has been employed to generate the first SAGE reference data set of the mouse myocardium. Following the protocols described here, investigators should be able to generate unique mouse heart SAGE libraries, which can be directly compared with our reference library. This permits the identification of transcripts that are differentially expressed as a function of time, age, genetic background or transgenic state, among other factors. SAGE is thus a powerful technique that permits a comprehensive analysis of changes in mRNA abundance. The results provide a snapshot of altered patterns of gene expression in response to any genetic or environmental stimulus that can be used to generate new biological hypotheses or test existing paradigms. © Humana Press Inc.-
dc.languageeng-
dc.relation.ispartofMethods in Molecular Biology-
dc.subjectFunctional genomics-
dc.subjectGene expression-
dc.subjectHeart-
dc.subjectmRNA-
dc.subjectSAGE-
dc.subjectSequencing-
dc.subjectTranscriptome-
dc.titleSerial Analysis of Gene Expression (SAGE): A useful tool to analyze the cardiac transcriptome-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1385/1-59745-030-8:41-
dc.identifier.pmid17568118-
dc.identifier.scopuseid_2-s2.0-34447278348-
dc.identifier.volume366-
dc.identifier.spage41-
dc.identifier.epage59-
dc.identifier.issnl1064-3745-

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