Literature DB >> 17595311

Big results from small samples: evaluation of amplification protocols for gene expression profiling.

Agnes Viale1, Juan Li, Jay Tiesman, Susan Hester, Aldo Massimi, Chandi Griffin, George Grills, Greg Khitrov, Kathryn Lilley, Kevin Knudtson, Bill Ward, Karl Kornacker, Chin-Yi Chu, Herbert Auer, Andrew I Brooks.   

Abstract

Microarrays have revolutionized many areas of biology due to our technical ability to quantify tens of thousands of transcripts within a single experiment. However, there are still many areas that cannot benefit from this technology due to the amount of biological material needed for microarray analysis. In response to this demand, chemistries have been developed that boast the capability of generating targets from nanogram amounts of total RnA, reflecting minimal amounts of biological material, on the order of several hundred or thousand cells. Herein, we describe the evaluation of four chemistries for RnA amplification in terms of reproducibility, sensitivity, accuracy, and comparability to results from a single round of T7 amplification. No evidence for false-positive measurements of differential expression was observed. In contrast, clear differences between chemistries in sensitivity and accuracy were detected. PCR validation showed an interaction of probe sequence on the array and target labeling chemistry, resulting in a chemistry-dependent probe set sensitivity varying over an order of magnitude.

Mesh:

Year:  2007        PMID: 17595311      PMCID: PMC2062549     

Source DB:  PubMed          Journal:  J Biomol Tech        ISSN: 1524-0215


  11 in total

1.  A high-density probe array sample preparation method using 10- to 100-fold fewer cells.

Authors:  M Mahadevappa; J A Warrington
Journal:  Nat Biotechnol       Date:  1999-11       Impact factor: 54.908

2.  Gene expression profiles of human breast cancer progression.

Authors:  Xiao-Jun Ma; Ranelle Salunga; J Todd Tuggle; Justin Gaudet; Edward Enright; Philip McQuary; Terry Payette; Maria Pistone; Kimberly Stecker; Brian M Zhang; Yi-Xiong Zhou; Heike Varnholt; Barbara Smith; Michelle Gadd; Erica Chatfield; Jessica Kessler; Thomas M Baer; Mark G Erlander; Dennis C Sgroi
Journal:  Proc Natl Acad Sci U S A       Date:  2003-04-24       Impact factor: 11.205

3.  A comparison of normalization methods for high density oligonucleotide array data based on variance and bias.

Authors:  B M Bolstad; R A Irizarry; M Astrand; T P Speed
Journal:  Bioinformatics       Date:  2003-01-22       Impact factor: 6.937

4.  Linear mRNA amplification from as little as 5 ng total RNA for global gene expression analysis.

Authors:  Alan Dafforn; Pengchin Chen; Glenn Deng; Michael Herrler; Dawn Iglehart; Sriveda Koritala; Susan Lato; Susheela Pillarisetty; Reshma Purohit; Martin Wang; Shenglong Wang; Nurith Kurn
Journal:  Biotechniques       Date:  2004-11       Impact factor: 1.993

5.  Amplified RNA synthesized from limited quantities of heterogeneous cDNA.

Authors:  R N Van Gelder; M E von Zastrow; A Yool; W C Dement; J D Barchas; J H Eberwine
Journal:  Proc Natl Acad Sci U S A       Date:  1990-03       Impact factor: 11.205

6.  Laser capture microdissection.

Authors:  M R Emmert-Buck; R F Bonner; P D Smith; R F Chuaqui; Z Zhuang; S R Goldstein; R A Weiss; L A Liotta
Journal:  Science       Date:  1996-11-08       Impact factor: 47.728

7.  Antisense RNA Amplification: A Linear Amplification Method for Analyzing the mRNA Population from Single Living Cells

Authors: 
Journal:  Methods       Date:  1996-12       Impact factor: 3.608

8.  Microdissection is essential for gene expression profiling of clinically resected cancer tissues.

Authors:  Yuko Sugiyama; Kazuo Sugiyama; Yasuo Hirai; Futoshi Akiyama; Katsuhiko Hasumi
Journal:  Am J Clin Pathol       Date:  2002-01       Impact factor: 2.493

9.  Gene-expression profiles predict survival of patients with lung adenocarcinoma.

Authors:  David G Beer; Sharon L R Kardia; Chiang-Ching Huang; Thomas J Giordano; Albert M Levin; David E Misek; Lin Lin; Guoan Chen; Tarek G Gharib; Dafydd G Thomas; Michelle L Lizyness; Rork Kuick; Satoru Hayasaka; Jeremy M G Taylor; Mark D Iannettoni; Mark B Orringer; Samir Hanash
Journal:  Nat Med       Date:  2002-07-15       Impact factor: 53.440

Review 10.  High density synthetic oligonucleotide arrays.

Authors:  R J Lipshutz; S P Fodor; T R Gingeras; D J Lockhart
Journal:  Nat Genet       Date:  1999-01       Impact factor: 38.330

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  16 in total

1.  Influence of RNA labeling on expression profiling of microRNAs.

Authors:  John S Kaddis; Daniel H Wai; Jessica Bowers; Nicole Hartmann; Lukas Baeriswyl; Sheetal Bajaj; Michael J Anderson; Robert C Getts; Timothy J Triche
Journal:  J Mol Diagn       Date:  2011-11-07       Impact factor: 5.568

2.  Ontogeny of erythroid gene expression.

Authors:  Paul D Kingsley; Emily Greenfest-Allen; Jenna M Frame; Timothy P Bushnell; Jeffrey Malik; Kathleen E McGrath; Christian J Stoeckert; James Palis
Journal:  Blood       Date:  2012-12-12       Impact factor: 22.113

Review 3.  A Review of the Scientific Rigor, Reproducibility, and Transparency Studies Conducted by the ABRF Research Groups.

Authors:  Sheenah M Mische; Nancy C Fisher; Susan M Meyn; Katia Sol-Church; Rebecca L Hegstad-Davies; Frances Weis-Garcia; Marie Adams; John M Ashton; Kym M Delventhal; Julie A Dragon; Laura Holmes; Pratik Jagtap; Kristopher E Kubow; Christopher E Mason; Magnus Palmblad; Brian C Searle; Christoph W Turck; Kevin L Knudtson
Journal:  J Biomol Tech       Date:  2020-04

4.  T7-based linear amplification of low concentration mRNA samples using beads and microfluidics for global gene expression measurements.

Authors:  Jason G Kralj; Audrey Player; Hope Sedrick; Matthew S Munson; David Petersen; Samuel P Forry; Paul Meltzer; Ernest Kawasaki; Laurie E Locascio
Journal:  Lab Chip       Date:  2008-12-15       Impact factor: 6.799

5.  Rhombomere-specific analysis reveals the repertoire of genetic cues expressed across the developing hindbrain.

Authors:  David Chambers; Leigh Jane Wilson; Fabienne Alfonsi; Ewan Hunter; Uma Saxena; Eric Blanc; Andrew Lumsden
Journal:  Neural Dev       Date:  2009-02-10       Impact factor: 3.842

6.  Evaluation of methods for amplification of picogram amounts of total RNA for whole genome expression profiling.

Authors:  Mathieu Clément-Ziza; David Gentien; Stanislas Lyonnet; Jean-Paul Thiery; Claude Besmond; Charles Decraene
Journal:  BMC Genomics       Date:  2009-05-26       Impact factor: 3.969

7.  Whole genome transcript profiling from fingerstick blood samples: a comparison and feasibility study.

Authors:  Elizabeth H Robison; Tony S Mondala; Adam R Williams; Steven R Head; Daniel R Salomon; Sunil M Kurian
Journal:  BMC Genomics       Date:  2009-12-17       Impact factor: 3.969

8.  Statistical evaluation of transcriptomic data generated using the Affymetrix one-cycle, two-cycle and IVT-Express RNA labelling protocols with the Arabidopsis ATH1 microarray.

Authors:  Tara J Holman; Michael H Wilson; Kim Kenobi; Ian L Dryden; T Charlie Hodgman; Andrew Ta Wood; Michael J Holdsworth
Journal:  Plant Methods       Date:  2010-03-15       Impact factor: 4.993

9.  Gene expression profiling of whole blood: comparison of target preparation methods for accurate and reproducible microarray analysis.

Authors:  Kristina Vartanian; Rachel Slottke; Timothy Johnstone; Amanda Casale; Stephen R Planck; Dongseok Choi; Justine R Smith; James T Rosenbaum; Christina A Harrington
Journal:  BMC Genomics       Date:  2009-01-05       Impact factor: 3.969

10.  Estimating RNA-quality using GeneChip microarrays.

Authors:  Mario Fasold; Hans Binder
Journal:  BMC Genomics       Date:  2012-05-14       Impact factor: 3.969

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