title: A comparison of RNA amplification techniques at sub-nanogram input concentration.
abstract: BACKGROUND
  Gene expression profiling of small numbers of cells requires high-fidelity amplification of sub-nanogram amounts of RNA. Several methods for RNA amplification are available; however, there has been little consideration of the accuracy of these methods when working with very low-input quantities of RNA as is often required with rare clinical samples. Starting with 250 picograms-3.3 nanograms of total RNA, we compared two linear amplification methods 1) modified T7 and 2) Arcturus RiboAmp HS and a logarithmic amplification, 3) Balanced PCR. Microarray data from each amplification method were validated against quantitative real-time PCR (QPCR) for 37 genes.
  
  
  RESULTS
  For high intensity spots, mean Pearson correlations were quite acceptable for both total RNA and low-input quantities amplified with each of the 3 methods. Microarray filtering and data processing has an important effect on the correlation coefficient results generated by each method. Arrays derived from total RNA had higher Pearson's correlations than did arrays derived from amplified RNA when considering the entire unprocessed dataset, however, when considering a gene set of high signal intensity, the amplified arrays had superior correlation coefficients than did the total RNA arrays.
  
  
  CONCLUSIONS
  Gene expression arrays can be obtained with sub-nanogram input of total RNA. High intensity spots showed better correlation on array-array analysis than did unfiltered data, however, QPCR validated the accuracy of gene expression array profiling from low-input quantities of RNA with all 3 amplification techniques. RNA amplification and expression analysis at the sub-nanogram input level is both feasible and accurate if data processing is used to focus attention to high intensity genes for microarrays or if QPCR is used as a gold standard for validation.
authors.affiliation: Department of Surgery, UCSF Comprehensive Cancer Center, 1500 Divisadero Street, San Francisco, CA 94143, USA. jlang@azcc.arizona.edu
authors.forename: Julie E
authors.initials: JE
authors.lastname: Lang
authors.forename: Mark Jesus M
authors.initials: MJ
authors.lastname: Magbanua
authors.forename: Janet H
authors.initials: JH
authors.lastname: Scott
authors.forename: G Mike
authors.initials: GM
authors.lastname: Makrigiorgos
authors.forename: Gang
authors.initials: G
authors.lastname: Wang
authors.forename: Scot
authors.initials: S
authors.lastname: Federman
authors.forename: Laura J
authors.initials: LJ
authors.lastname: Esserman
authors.forename: John W
authors.initials: JW
authors.lastname: Park
authors.forename: Christopher M
authors.initials: CM
authors.lastname: Haqq
mesh_terms: D002460:Cell Line; D020869:Gene Expression Profiling / Q000379:methods; D006801:Humans; D021141:Nucleic Acid Amplification Techniques / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D016133:Polymerase Chain Reaction / Q000379:methods; D012313:RNA / Q000737:chemistry*; D012680:Sensitivity and Specificity
chemical_list: D012313:RNA