MiniSAGE: Gene Expression Profiling Using Serial Analysis of Gene Expression from 1 μg Total RNA

Ye, Shui Qing; Zhang, Li Q.; Zheng, Fang; Virgil, Donna G.; Kwiterovich, Peter O.

doi:10.1006/abio.2000.4846

Cited by 46 publications

(22 citation statements)

References 22 publications

(19 reference statements)

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“…NlaIII was used as the anchoring enzyme and BsmFI as the tagging enzyme. In addition, Phase Lock Gel (Eppendorf) was used at every phenol-chloroform extraction step to increase the recovery and purity of DNA (Ye et al 2000). During library construction, ditags were amplified by 27-29 cycles of PCR.…”

Section: Generation Of Sage Tags and Librariesmentioning

confidence: 99%

Analysis of long-lived C. elegans daf-2 mutants using serial analysis of gene expression

Halaschek-Wiener

Khattra²,

McKay³

et al. 2005

Genome Res.

191

174

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We have identified longevity-associated genes in a long-lived Caenorhabditis elegans daf-2 (insulin/IGF receptor) mutant using serial analysis of gene expression (SAGE), a method that efficiently quantifies large numbers of mRNA transcripts by sequencing short tags. Reduction of daf-2 signaling in these mutant worms leads to a doubling in mean lifespan. We prepared C. elegans SAGE libraries from 1, 6, and 10-d-old adult daf-2 and from 1 and 6-d-old control adults. Differences in gene expression between daf-2 libraries representing different ages and between daf-2 versus control libraries identified not only single genes, but whole gene families that were differentially regulated. These gene families are part of major metabolic pathways including lipid, protein, and energy metabolism, stress response, and cell structure. Similar expression patterns of closely related family members emphasize the importance of these genes in aging-related processes. Global analysis of metabolism-associated genes showed hypometabolic features in mid-life daf-2 mutants that diminish with advanced age. Comparison of our results to recent microarray studies highlights sets of overlapping genes that are highly conserved throughout evolution and thus represent strong candidate genes that control aging and longevity.

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Section: Generation Of Sage Tags and Librariesmentioning

confidence: 99%

Analysis of long-lived C. elegans daf-2 mutants using serial analysis of gene expression

Halaschek-Wiener

Khattra²,

McKay³

et al. 2005

Genome Res.

191

174

View full text Add to dashboard Cite

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“…Since the discovery of SAGE technology, a number of modifications have been reported in the technique. Some of the important modifications include 'SAGE-lite', (15) micro-SAGE, (16) mini-SAGE, (17) a SAGE adaptation for downsized extracts (SADE) (18) and generation of longer cDNA fragments from SAGE tags for gene identification (GLGI). (19) SAGE bioinformatics Fig.…”

Section: Sage-the Methodsmentioning

confidence: 99%

Serial analysis of gene expression (SAGE): unraveling the bioinformatics tools

Tuteja

2004

BioEssays

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Serial analysis of gene expression (SAGE) is a powerful technique that can be used for global analysis of gene expression. Its chief advantage over other methods is that it does not require prior knowledge of the genes of interest and provides qualitative and quantitative data of potentially every transcribed sequence in a particular cell or tissue type. This is a technique of expression profiling, which permits simultaneous, comparative and quantitative analysis of gene-specific, 9- to 13-basepair sequences. These short sequences, called SAGE tags, are linked together for efficient sequencing. The sequencing data are then analyzed to identify each gene expressed in the cell and the levels at which each gene is expressed. The main benefit of SAGE includes the digital output and the identification of novel genes. In this review, we present an outline of the method, various bioinformatics methods for data analysis and general applications of this important technology.

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“…However, SAGE analysis of nephron segments, glomeruli, or kidney cells, which can be obtained by laser capture microdissection of biopsy specimens [14, 15], is only practical, if significantly smaller amounts of mRNA can be used for cDNA synthesis. To address this problem, several groups have developed ‘miniaturized’ protocols that require 500- to 5,000-fold less input RNA, i.e., from as few as 15,000–50,000 cells [16, 17, 18]. In addition, quantitative techniques for RNA amplification from small samples have been published [15]which allow expression libraries to be generated from considerably fewer cells.…”

Section: Sage: Methodological Outlinementioning

confidence: 99%

Generation of Kidney Transcriptomes Using Serial Analysis of Gene Expression

Schelling¹,

El-Meanawy²,

Barathan³

et al. 2002

Nephron Exp Nephrol

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Chronic renal disease initiation and progression remain incompletely understood. Genomewide expression monitoring should clarify the mechanisms which cause progressive renal disease by determining how clusters of genes coordinately change their activity. Serial analysis of gene expression (SAGE) is a technique of expression profiling which permits simultaneous and quantitative analysis of 9- to 13-bp sequence tags that correspond to unique mRNAs. Key principles of the technique are use of PCR in a manner to minimize distortion and serial concatenation of tags which facilitates sequencing and permits identification of many expressed genes in a single cDNA molecule. Tags are extracted from many concatenated sequences, counted using software, and identified by comparison with existing gene databases. In aggregate, gene expression profiles generated from a tag library comprise a transcriptome which represents a comprehensive and quantitative profile of genes expressed at the time of analysis. These global snapshots of gene expression patterns can better define basic cell biology and provide insights into disease pathogenesis by simultaneously determining the net consequences of gene-gene and gene-environment interactions on expression of thousands of genes. Rather than applying a priori assumptions (i.e., hypothesis testing), transcriptome analysis is hypothesis generating and requires no prior knowledge of gene expression. SAGE kidney transcriptomes, from normal animals and animals with progressive kidney disease, are being produced and can be analyzed for novel pathogenetic mechanisms. The use of SAGE and other genomic and proteomic tools should result in a better understanding of kidney disease pathogenesis and in identification of new therapeutic targets.

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MiniSAGE: Gene Expression Profiling Using Serial Analysis of Gene Expression from 1 μg Total RNA

Cited by 46 publications

References 22 publications

Analysis of long-lived C. elegans daf-2 mutants using serial analysis of gene expression

Analysis of long-lived C. elegans daf-2 mutants using serial analysis of gene expression

Serial analysis of gene expression (SAGE): unraveling the bioinformatics tools

Generation of Kidney Transcriptomes Using Serial Analysis of Gene Expression

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