Literature DB >> 15923145

SAGE and the quantitative analysis of gene expression in parasites.

David P Knox1, Philip J Skuce.   

Abstract

The nature of an organism is defined by the genes that it expresses. Genome- and expressed-sequence-tag (EST) sequencing projects are underway for many of the major parasites of humans and animals. These provide essential datasets that delineate the genes present in an organism and, in the case of ESTs, some quantitative information on gene expression. The temporal and quantitative analysis of gene expression is essential to fully exploit these datasets and define the biology of the parasite at the molecular level. Here, we discuss the application of serial analysis of gene expression (SAGE) for this purpose. SAGE is a technique that allows the rapid, quantitative analysis of thousands of transcripts. It complements microarray analysis with the advantage that it is affordable for standard laboratories. It provides a platform to define complete metabolic pathways and has been applied to study responses to drug treatment and the molecular events that are associated with arrested larval development.

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Year:  2005        PMID: 15923145     DOI: 10.1016/j.pt.2005.05.011

Source DB:  PubMed          Journal:  Trends Parasitol        ISSN: 1471-4922


  3 in total

1.  Transcriptome analyses of the Giardia lamblia life cycle.

Authors:  Shanda R Birkeland; Sarah P Preheim; Barbara J Davids; Michael J Cipriano; Daniel Palm; David S Reiner; Staffan G Svärd; Frances D Gillin; Andrew G McArthur
Journal:  Mol Biochem Parasitol       Date:  2010-06-04       Impact factor: 1.759

2.  A gene expression atlas of adult Schistosoma mansoni and their gonads.

Authors:  Zhigang Lu; Florian Sessler; Nancy Holroyd; Steffen Hahnel; Thomas Quack; Matthew Berriman; Christoph G Grevelding
Journal:  Sci Data       Date:  2017-08-22       Impact factor: 6.444

3.  Serial Analysis of Gene Expression in Plasmodium berghei salivary gland sporozoites.

Authors:  Isabelle Rosinski-Chupin; Thomas Chertemps; Bertrand Boisson; Sylvie Perrot; Emmanuel Bischoff; Jérôme Briolay; Pierre Couble; Robert Ménard; Paul Brey; Patricia Baldacci
Journal:  BMC Genomics       Date:  2007-12-19       Impact factor: 3.969

  3 in total

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