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Article: SAGE analysis to identify embryonic stem cell-predominant transcripts.

TitleSAGE analysis to identify embryonic stem cell-predominant transcripts.
Authors
Issue Date2006
Citation
Methods in molecular biology (Clifton, N.J.), 2006, v. 329, p. 195-221 How to Cite?
AbstractThe Human Genome Consortium has successfully sequenced the entire human genome (http://www.genome.gov/11006945), but an unfinished goal remains the identification of specific genes responsible for unique cellular processes. With respect to embryonic stem (ES) cells, this includes the identification of factors that govern self-renewal and pluripotentiality. One technique that facilitates this last goal is serial analysis of gene expression (SAGE), a functional genomics technique that identifies and quantifies mRNA transcripts. This technique relies on the preparation and sequencing of complementary DNA concatemers to rapidly generate a comprehensive profile of gene expression within a cell, and unlike microarrays, it does not require prior knowledge of the genes to be assayed. Because SAGE is a sequence-based technique, it can be used to search for ES-restricted genes (i.e., markers) by sequence comparisons among stem cells, differentiated cells, and tissues. These markers can then be genetically manipulated to understand the molecular basis for stem cell biology to help define how transcriptional mechanisms distinguish ES cells from other, less-pluripotent cell types. SAGE is, thus, a powerful technique that permits a comprehensive analysis of mRNA abundance that can define, at a molecular level, fundamental characteristics of ES cells. In this chapter, we illustrate the basic principles of SAGE, describe a complete protocol for the generation of SAGE libraries, and show how this technique can be employed to analyze embryonic stem cells.
Persistent Identifierhttp://hdl.handle.net/10722/195181
ISSN
2015 SCImago Journal Rankings: 0.549

 

DC FieldValueLanguage
dc.contributor.authorBoheler, KR-
dc.contributor.authorTarasov, KV-
dc.date.accessioned2014-02-25T01:40:16Z-
dc.date.available2014-02-25T01:40:16Z-
dc.date.issued2006-
dc.identifier.citationMethods in molecular biology (Clifton, N.J.), 2006, v. 329, p. 195-221-
dc.identifier.issn1064-3745-
dc.identifier.urihttp://hdl.handle.net/10722/195181-
dc.description.abstractThe Human Genome Consortium has successfully sequenced the entire human genome (http://www.genome.gov/11006945), but an unfinished goal remains the identification of specific genes responsible for unique cellular processes. With respect to embryonic stem (ES) cells, this includes the identification of factors that govern self-renewal and pluripotentiality. One technique that facilitates this last goal is serial analysis of gene expression (SAGE), a functional genomics technique that identifies and quantifies mRNA transcripts. This technique relies on the preparation and sequencing of complementary DNA concatemers to rapidly generate a comprehensive profile of gene expression within a cell, and unlike microarrays, it does not require prior knowledge of the genes to be assayed. Because SAGE is a sequence-based technique, it can be used to search for ES-restricted genes (i.e., markers) by sequence comparisons among stem cells, differentiated cells, and tissues. These markers can then be genetically manipulated to understand the molecular basis for stem cell biology to help define how transcriptional mechanisms distinguish ES cells from other, less-pluripotent cell types. SAGE is, thus, a powerful technique that permits a comprehensive analysis of mRNA abundance that can define, at a molecular level, fundamental characteristics of ES cells. In this chapter, we illustrate the basic principles of SAGE, describe a complete protocol for the generation of SAGE libraries, and show how this technique can be employed to analyze embryonic stem cells.-
dc.languageeng-
dc.relation.ispartofMethods in molecular biology (Clifton, N.J.)-
dc.titleSAGE analysis to identify embryonic stem cell-predominant transcripts.-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.pmid16845993-
dc.identifier.scopuseid_2-s2.0-33747587443-
dc.identifier.volume329-
dc.identifier.spage195-
dc.identifier.epage221-

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