Literature DB >> 10748532

High-fidelity mRNA amplification for gene profiling.

E Wang1, L D Miller, G A Ohnmacht, E T Liu, F M Marincola.   

Abstract

The completion of the Human Genome Project has made possible the comprehensive analysis of gene expression, and cDNA microarrays are now being employed for expression analysis in cancer cell lines or excised surgical specimens. However, broader application of cDNA microarrays is limited by the amount of RNA required: 50-200 microg of total RNA (T-RNA) and 2-5 microg poly(A) RNA. To broaden the use of cDNA microarrays, some methods aiming at intensifying fluorescence signal have resulted in modest improvement. Methods devoted to amplifying starting poly(A) RNA or cDNA show promise, in that detection can be increased by orders of magnitude. However, despite the common use of these amplification procedures, no systematic assessment of their limits and biases has been documented. We devised a procedure that optimizes amplification of low-abundance RNA samples by combining antisense RNA (aRNA) amplification with a template-switching effect (Clonetech, Palo Alto, CA). The fidelity of aRNA amplified from 1:10,000 to 1:100,000 of commonly used input RNA was comparable to expression profiles observed with conventional poly(A) RNA- or T-RNA-based arrays.

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Year:  2000        PMID: 10748532     DOI: 10.1038/74546

Source DB:  PubMed          Journal:  Nat Biotechnol        ISSN: 1087-0156            Impact factor:   54.908


  204 in total

1.  Quantitative analysis of mRNA amplification by in vitro transcription.

Authors:  L R Baugh; A A Hill; E L Brown; C P Hunter
Journal:  Nucleic Acids Res       Date:  2001-03-01       Impact factor: 16.971

2.  Stereotyped and specific gene expression programs in human innate immune responses to bacteria.

Authors:  Jennifer C Boldrick; Ash A Alizadeh; Maximilian Diehn; Sandrine Dudoit; Chih Long Liu; Christopher E Belcher; David Botstein; Louis M Staudt; Patrick O Brown; David A Relman
Journal:  Proc Natl Acad Sci U S A       Date:  2002-01-22       Impact factor: 11.205

3.  Core biopsies can be used to distinguish differences in expression profiling by cDNA microarrays.

Authors:  Christos Sotiriou; Chand Khanna; Amir A Jazaeri; David Petersen; Edison T Liu
Journal:  J Mol Diagn       Date:  2002-02       Impact factor: 5.568

4.  mRNA expression profiling of laser microbeam microdissected cells from slender embryonic structures.

Authors:  Stefan J Scheidl; Sven Nilsson; Mattias Kalén; Mats Hellström; Minoru Takemoto; Joakim Håkansson; Per Lindahl
Journal:  Am J Pathol       Date:  2002-03       Impact factor: 4.307

5.  A highly reproducible, linear, and automated sample preparation method for DNA microarrays.

Authors:  David R Dorris; Ramesh Ramakrishnan; Dionisios Trakas; Frank Dudzik; Richard Belval; Connie Zhao; Allen Nguyen; Marc Domanus; Abhijit Mazumder
Journal:  Genome Res       Date:  2002-06       Impact factor: 9.043

6.  Small amplified RNA-SAGE: an alternative approach to study transcriptome from limiting amount of mRNA.

Authors:  Catheline Vilain; Frederick Libert; David Venet; Sabine Costagliola; Gilbert Vassart
Journal:  Nucleic Acids Res       Date:  2003-03-15       Impact factor: 16.971

7.  A new strategy to amplify degraded RNA from small tissue samples for microarray studies.

Authors:  Charlie C Xiang; Mei Chen; Li Ma; Quang N Phan; Jason M Inman; Olga A Kozhich; Michael J Brownstein
Journal:  Nucleic Acids Res       Date:  2003-05-01       Impact factor: 16.971

8.  Optimizing gene expression analysis in archival brain tissue.

Authors:  Vivianna M D Van Deerlin; Lisa H Gill; Peter T Nelson
Journal:  Neurochem Res       Date:  2002-10       Impact factor: 3.996

9.  Validation of cDNA microarray gene expression data obtained from linearly amplified RNA.

Authors:  S D Jenson; R S Robetorye; S D Bohling; J A Schumacher; J W Morgan; M S Lim; K S J Elenitoba-Johnson
Journal:  Mol Pathol       Date:  2003-12

10.  Combined analysis of transcriptome and proteome data as a tool for the identification of candidate biomarkers in renal cell carcinoma.

Authors:  Barbara Seliger; Sven P Dressler; Ena Wang; Roland Kellner; Christian V Recktenwald; Friedrich Lottspeich; Francesco M Marincola; Maja Baumgärtner; Derek Atkins; Rudolf Lichtenfels
Journal:  Proteomics       Date:  2009-03       Impact factor: 3.984

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