Literature DB >> 17109989

Understanding SAGE data.

San Ming Wang1.   

Abstract

Serial analysis of gene expression (SAGE) is a method for identifying and quantifying transcripts from eukaryotic genomes. Since its invention, SAGE has been widely applied to analyzing gene expression in many biological and medical studies. Vast amounts of SAGE data have been collected and more than a thousand SAGE-related studies have been published since the mid-1990s. The principle of SAGE has been developed to address specific issues such as determination of normal gene structure and identification of abnormal genome structural changes. This review focuses on the general features of SAGE data, including the specificity of SAGE tags with respect to their original transcripts, the quantitative nature of SAGE data for differentially expressed genes, the reproducibility, the comparability of SAGE with microarray and the future potential of SAGE. Understanding these basic features should aid the proper interpretation of SAGE data to address biological and medical questions.

Mesh:

Year:  2006        PMID: 17109989     DOI: 10.1016/j.tig.2006.11.001

Source DB:  PubMed          Journal:  Trends Genet        ISSN: 0168-9525            Impact factor:   11.639


  33 in total

1.  Detection of low-abundant novel transcripts in mouse hematopoietic stem cells.

Authors:  Hyeng-Soo Kim; Junmo Hwang; Young-Hun Kim; Seonggon Kim; Jae-Woong Lee; Hyung-Sik Kang; Kil Soo Kim; Ji-Hong Ha; Jin Woong Chung; Kyu-Tae Chang; Zae Young Ryoo; Sanggyu Lee
Journal:  Mol Genet Genomics       Date:  2009-07-08       Impact factor: 3.291

Review 2.  Deeply dissecting stemness: making sense to non-coding RNAs in stem cells.

Authors:  Shizuka Uchida; Pascal Gellert; Thomas Braun
Journal:  Stem Cell Rev Rep       Date:  2012-03       Impact factor: 5.739

3.  Global gene expression reveals a set of new genes involved in the modification of cells during erythroid differentiation.

Authors:  A F da Cunha; A F Brugnerotto; A S Duarte; C Lanaro; G G L Costa; S T O Saad; F F Costa
Journal:  Cell Prolif       Date:  2010-06       Impact factor: 6.831

4.  An NGF-responsive element targets myo-inositol monophosphatase-1 mRNA to sympathetic neuron axons.

Authors:  Catia Andreassi; Carola Zimmermann; Richard Mitter; Salvatore Fusco; Serena De Vita; Serena Devita; Adolfo Saiardi; Antonella Riccio
Journal:  Nat Neurosci       Date:  2010-01-31       Impact factor: 24.884

5.  Transcriptome sequencing and comparative analysis of cucumber flowers with different sex types.

Authors:  Shaogui Guo; Yi Zheng; Je-Gun Joung; Shiqiang Liu; Zhonghua Zhang; Oswald R Crasta; Bruno W Sobral; Yong Xu; Sanwen Huang; Zhangjun Fei
Journal:  BMC Genomics       Date:  2010-06-17       Impact factor: 3.969

6.  Interrogating global gene expression in rat neuronal cultures using SAGE.

Authors:  Adriano Sebollela; Emmanuel Dias-Neto; Sérgio T Ferreira
Journal:  Neurotox Res       Date:  2007-12       Impact factor: 3.911

7.  Serial analysis of gene expression reveals differential expression between endometriosis and normal endometrium. Possible roles for AXL and SHC1 in the pathogenesis of endometriosis.

Authors:  Hiroshi Honda; Fermin F Barrueto; Jean Gogusev; Dwight D Im; Patrice J Morin
Journal:  Reprod Biol Endocrinol       Date:  2008-12-02       Impact factor: 5.211

8.  Large-scale transcriptome data reveals transcriptional activity of fission yeast LTR retrotransposons.

Authors:  Tobias Mourier; Eske Willerslev
Journal:  BMC Genomics       Date:  2010-03-12       Impact factor: 3.969

9.  Identification of genes expressed in the hermaphrodite germ line of C. elegans using SAGE.

Authors:  Xin Wang; Yongjun Zhao; Kim Wong; Peter Ehlers; Yuji Kohara; Steven J Jones; Marco A Marra; Robert A Holt; Donald G Moerman; Dave Hansen
Journal:  BMC Genomics       Date:  2009-05-09       Impact factor: 3.969

10.  An integrated strategy to study muscle development and myofilament structure in Caenorhabditis elegans.

Authors:  Barbara Meissner; Adam Warner; Kim Wong; Nicholas Dube; Adam Lorch; Sheldon J McKay; Jaswinder Khattra; Teresa Rogalski; Aruna Somasiri; Iasha Chaudhry; Rebecca M Fox; David M Miller; David L Baillie; Robert A Holt; Steven J M Jones; Marco A Marra; Donald G Moerman
Journal:  PLoS Genet       Date:  2009-06-26       Impact factor: 5.917

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