Literature DB >> 15808310

Validation and application of a high fidelity mRNA linear amplification procedure for profiling gene expression.

Osman V Patel1, Steve P Suchyta, Sue S Sipkovsky, Jianbo Yao, James J Ireland, Paul M Coussens, George W Smith.   

Abstract

The need for microgram quantities of RNA for microarray experiments has hindered application of this novel technology in cell types/tissue samples with limited abundance of RNA. In this study, potential application of T7-based linear RNA amplification was investigated for use in gene expression profiling experiments where starting material is limited. Yield and integrity of amplified antisense RNA (aaRNA), microarray hybridization intensities, and fidelity of differential gene expression detected were determined for arrays generated for unamplified versus amplified RNA from the same homogenous starting pools. Total RNA was extracted from bovine spleen and fetal ovary, serially diluted to concentrations ranging from 2 microg to 500 pg and amplified. Quality and quantity of total input RNA and aaRNA were assessed by spectrophotometry, gel electrophoresis and bioanalyzer. In experiment 1, we determined the optimal amounts of aaRNA generated from 20, 40, 200 ng and 2 microg input total RNA for use in cDNA synthesis, labeling and array hybridization that would yield robust and consistent hybridization signals on a bovine oocyte cDNA microarray. In experiment 2, comparison of microarray hybridization intensities and fidelity of differential gene expression between aaRNA generated from 2, 20 and 40 ng input total RNA versus unamplified RNA (uRNA) were conducted. The hybridization intensities for each of the 7000 spots per slide for microarrays conducted using aaRNA versus uRNA were highly correlated (2 ng = 0.84, 20 ng = 0.88, 40 ng = 0.90; P < 0.01). The false positive rate was low and similar (4.0% versus 4.4%) for arrays done with uRNA and aaRNA. Ninety-seven ESTs were detected as differentially expressed in the fetal ovary versus spleen at > 1.5- or < 0.5-fold using uRNA (P < 0.05). However, the number of genes detected in arrays using aaRNA was approximately 1.5-2.5 times greater than with uRNA. Approximately, 65-70% of differentially expressed genes were common between uRNA and aaRNA arrays. Relative fold-expression (Cy3/Cy5 ratios) for 25 overlapping abundant genes was comparable for uRNA versus aaRNA arrays with 2 and 20 ng total RNA as input. Results demonstrate that T7-based linear amplification of small amounts of input RNA and use of aaRNA in microarray experiments retains fidelity of detection of differential gene expression that is relatively comparable to experiments done with uRNA and provides a potentially viable approach to facilitate gene expression profiling using limited amounts of starting material.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 15808310     DOI: 10.1016/j.vetimm.2005.02.018

Source DB:  PubMed          Journal:  Vet Immunol Immunopathol        ISSN: 0165-2427            Impact factor:   2.046


  13 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

Review 2.  Single-cell analysis of the transcriptome and its application in the characterization of stem cells and early embryos.

Authors:  Na Liu; Lin Liu; Xinghua Pan
Journal:  Cell Mol Life Sci       Date:  2014-03-21       Impact factor: 9.261

3.  Subcellular profiling reveals distinct and developmentally regulated repertoire of growth cone mRNAs.

Authors:  Krishna H Zivraj; Yi Chun Loraine Tung; Michael Piper; Laura Gumy; James W Fawcett; Giles S H Yeo; Christine E Holt
Journal:  J Neurosci       Date:  2010-11-17       Impact factor: 6.167

4.  Method to isolate polyribosomal mRNA from scarce samples such as mammalian oocytes and early embryos.

Authors:  Sara Scantland; Jean-Philippe Grenon; Marie-Hélène Desrochers; Marc-André Sirard; Edward W Khandjian; Claude Robert
Journal:  BMC Dev Biol       Date:  2011-02-15       Impact factor: 1.978

5.  Limitations of mRNA amplification from small-size cell samples.

Authors:  Vigdis Nygaard; Marit Holden; Anders Løland; Mette Langaas; Ola Myklebost; Eivind Hovig
Journal:  BMC Genomics       Date:  2005-10-27       Impact factor: 3.969

6.  Gene expression signatures of morphologically normal breast tissue identify basal-like tumors.

Authors:  Greg Finak; Svetlana Sadekova; Francois Pepin; Michael Hallett; Sarkis Meterissian; Fawaz Halwani; Karim Khetani; Margarita Souleimanova; Brent Zabolotny; Atilla Omeroglu; Morag Park
Journal:  Breast Cancer Res       Date:  2006       Impact factor: 6.466

7.  Development and validation of a bovine macrophage specific cDNA microarray.

Authors:  Kirsty Jensen; Richard Talbot; Edith Paxton; David Waddington; Elizabeth J Glass
Journal:  BMC Genomics       Date:  2006-09-01       Impact factor: 3.969

8.  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

Review 9.  Options available for profiling small samples: a review of sample amplification technology when combined with microarray profiling.

Authors:  Vigdis Nygaard; Eivind Hovig
Journal:  Nucleic Acids Res       Date:  2006-02-09       Impact factor: 16.971

10.  Comparative evaluation of linear and exponential amplification techniques for expression profiling at the single-cell level.

Authors:  Tatiana Subkhankulova; Frederick J Livesey
Journal:  Genome Biol       Date:  2006-03-07       Impact factor: 13.583

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.