Literature DB >> 17487157

Serial analysis of gene expression.

Min Hu1, Kornelia Polyak.   

Abstract

Serial analysis of gene expression (SAGE) is a method used to obtain comprehensive, unbiased and quantitative gene-expression profiles. Its major advantage over arrays is that it does not require a priori knowledge of the genes to be analyzed and reflects absolute mRNA levels. Since the original SAGE protocol was developed in a short-tag (10-bp) format, several modifications have been made to produce longer SAGE tags for more precise gene identification and to decrease the amount of starting material necessary. Several SAGE-like methods have also been developed for the genome-wide analysis of DNA copy-number changes and methylation patterns, chromatin structure and transcription factor targets. In this protocol, we describe the 17-bp longSAGE method for transcriptome profiling optimized for a small amount of starting material. The generation of such libraries can be completed in 7-10 d, whereas sequencing and data analysis require an additional 2-3 wk.

Mesh:

Year:  2006        PMID: 17487157     DOI: 10.1038/nprot.2006.269

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  8 in total

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Journal:  Theory Biosci       Date:  2012-05-17       Impact factor: 1.919

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Authors:  Stefan Siebert; Mark D Robinson; Sophia C Tintori; Freya Goetz; Rebecca R Helm; Stephen A Smith; Nathan Shaner; Steven H D Haddock; Casey W Dunn
Journal:  PLoS One       Date:  2011-07-29       Impact factor: 3.240

3.  Gene network reconstruction from transcriptional dynamics under kinetic model uncertainty: a case for the second derivative.

Authors:  David R Bickel; Zahra Montazeri; Pei-Chun Hsieh; Mary Beatty; Shai J Lawit; Nicholas J Bate
Journal:  Bioinformatics       Date:  2009-02-13       Impact factor: 6.937

4.  The most common technologies and tools for functional genome analysis.

Authors:  Evelina Gasperskaja; Vaidutis Kučinskas
Journal:  Acta Med Litu       Date:  2017

Review 5.  A Brief Overview of lncRNAs in Endothelial Dysfunction-Associated Diseases: From Discovery to Characterization.

Authors:  Rashidul Islam; Christopher Lai
Journal:  Epigenomes       Date:  2019-09-13

6.  High throughput transcriptome analysis of lipid metabolism in Syrian hamster liver in absence of an annotated genome.

Authors:  Roland Schmucki; Marco Berrera; Erich Küng; Serene Lee; Wolfgang E Thasler; Sabine Grüner; Martin Ebeling; Ulrich Certa
Journal:  BMC Genomics       Date:  2013-04-10       Impact factor: 3.969

Review 7.  Jellyfish Bioactive Compounds: Methods for Wet-Lab Work.

Authors:  Bárbara Frazão; Agostinho Antunes
Journal:  Mar Drugs       Date:  2016-04-12       Impact factor: 5.118

8.  Single-cell RNA sequencing reveals gene expression signatures of breast cancer-associated endothelial cells.

Authors:  Zhengda Sun; Chih-Yang Wang; Devon A Lawson; Serena Kwek; Hugo Gonzalez Velozo; Mark Owyong; Ming-Derg Lai; Lawrence Fong; Mark Wilson; Hua Su; Zena Werb; Daniel L Cooke
Journal:  Oncotarget       Date:  2017-12-29
  8 in total

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