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Effects of Globin MRNA Reduction Methods on Gene Expression Profiles from Whole Blood

Overview
Journal J Mol Diagn
Publisher Elsevier
Date 2006 Oct 27
PMID 17065423
Citations 46
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Abstract

Excessive globin mRNA in whole blood RNA decreases transcript detection sensitivity and increases signal variation on microarrays. Hence, methods based on peptide nucleic acid inhibitory oligos and biotinylated DNA capture oligos have been developed to reduce globin mRNA. However, there is limited information about the effects of these two methods on gene expression profiles. Thus, we systematically compared the facility and effects of the two globin reduction methods on profile measurements from Jurkat cell line RNA with or without spiked globin mRNA and human blood RNA isolated using PAXgene collection tubes. We showed that the methods were efficient at increasing the sensitivity of transcript detection without loss of specificity, but neither method could recover a profile equivalent to that of an identical RNA sample without globin mRNA excesses. The capture oligo method had slightly better transcript detection sensitivity for cell line RNA, lowered signal variation for PAXgene RNA, and more similar profiles to controls than the inhibitory method. However, the capture method required larger amounts of initial high-quality RNA to yield sufficient cRNA amounts, and its procedures were more complex and time consuming than the inhibitory method. These results inform the selection of methods suitable for multicenter surveillance of gene expression profiles.

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References
1.
Li C, Wong W . Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection. Proc Natl Acad Sci U S A. 2001; 98(1):31-6. PMC: 14539. DOI: 10.1073/pnas.98.1.31. View

2.
Li C, Hung Wong W . Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application. Genome Biol. 2001; 2(8):RESEARCH0032. PMC: 55329. DOI: 10.1186/gb-2001-2-8-research0032. View

3.
Debey S, Zander T, Brors B, Popov A, Eils R, Schultze J . A highly standardized, robust, and cost-effective method for genome-wide transcriptome analysis of peripheral blood applicable to large-scale clinical trials. Genomics. 2006; 87(5):653-64. DOI: 10.1016/j.ygeno.2005.11.010. View

4.
Thach D, Lin B, Walter E, Kruzelock R, Rowley R, Tibbetts C . Assessment of two methods for handling blood in collection tubes with RNA stabilizing agent for surveillance of gene expression profiles with high density microarrays. J Immunol Methods. 2003; 283(1-2):269-79. DOI: 10.1016/j.jim.2003.10.004. View

5.
Thach D, Agan B, Olsen C, Diao J, Lin B, Gomez J . Surveillance of transcriptomes in basic military trainees with normal, febrile respiratory illness, and convalescent phenotypes. Genes Immun. 2005; 6(7):588-95. DOI: 10.1038/sj.gene.6364244. View