A comparative analysis of data generated using two different target preparation methods for hybridization to high-density oligonucleotide microarrays.
BACKGROUND
To generate specific transcript profiles, one must isolate homogenous cell populations using techniques that often yield small amounts of RNA, requiring researchers to employ RNA amplification methods. The data generated by using these methods must be extensively evaluated to determine any technique dependent distortion of the expression profiles.


RESULTS
High-density oligonucleotide microarrays were used to perform experiments for comparing data generated by using two protocols, an in vitro transcription (IVT) protocol that requires 5 microg of total RNA and a double in vitro transcription (dIVT) protocol that requires 200 ng of total RNA for target preparation from RNA samples extracted from a normal and a cancer cell line. In both cell lines, about 10% more genes were detected with IVT than with dIVT. Genes were filtered to exclude those that were undetected on all arrays. Hierarchical clustering using the 9,482 genes that passed the filter showed that the variation attributable to biological differences between samples was greater than that introduced by differences in the protocols. We analyzed the behavior of these genes separately for each protocol by using a statistical model to estimate the posterior probability of various levels of fold change. At each level, more differentially expressed genes were detected with IVT than with dIVT. When we checked for genes that had a posterior probability greater than 99% of fold change greater than 2, in data generated by IVT but not dIVT, more than 60% of these genes had posterior probabilities greater than 90% in data generated by dIVT. Both protocols identified the same functional gene categories to be differentially expressed. Differential expression of selected genes was confirmed using quantitative real-time PCR.


CONCLUSIONS
Using nanogram quantities on total RNA, the usage of dIVT protocol identified differentially expressed genes and functional categories consistent with those detected by the IVT protocol. There was a loss in sensitivity of about 10% when detecting differentially expressed genes using the dIVT protocol. However, the lower amount of RNA required for this protocol, as compared to the IVT protocol, renders this methodology a highly desirable one for biological systems where sample amounts are limiting.
Gold
David
D
Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA. dgold@odin.mdacc.tmc.edu
Coombes
Kevin
K
Medhane
Dina
D
Ramaswamy
Anitha
A
Ju
Zhenlin
Z
Strong
Louise
L
Koo
Ja Seok
JS
Kapoor
Mini
M
D000465:Algorithms; D002460:Cell Line; D045744:Cell Line, Tumor; D016000:Cluster Analysis; D004587:Electrophoresis, Agar Gel; D020869:Gene Expression Profiling; D006801:Humans; D009693:Nucleic Acid Hybridization / Q000379:methods; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000592:standards; D012313:RNA / Q000235:genetics / Q000302:isolation & purification / Q000378:metabolism; D012334:RNA, Neoplasm / Q000235:genetics / Q000302:isolation & purification / Q000378:metabolism
D012334:RNA, Neoplasm; D012313:RNA