Raw fluorescence intensities show chemistry-dependent probe sensitivities. Fluorescence intensities of all 11 probes of probe sets 213945_s_at (upper panel) and 220035_at, both measuring NUP210. Triangles show signal intensity of RR and squares of MDA; (a) and (c) signals from NuGEN chemistry, (b) and (d) from standard protocol.

Intra-chemistry correlation by signal intensity. Probe sets were divided into quartiles based on average signal intensity for each chemistry. Six correlation measurements for each chemistry at each quartile were based on three RR samples compared to themselves and three MDA samples compared to themselves. These six correlations were averaged and the coefficient of variation was computed. The coefficient of variation for any average did not exceed 5%.

3′ bias of Affymetrix Genechip Arrays—Affymetrix probe arrays (human U133 array depicted here) represent a severe 3′ bias which has a direct effect on array peformance as a function of the “size” of labeled product being hyrbridized to the array. Labeled target sequences over 600 bp represent a very small number of Affymetrix transcripts on any given array.

Sensitivity of labeling chemistries to detect differential expression and comparability of results to the standard protocol. (a) Number of probe sets detecting >2-fold differential expression; white bars show probe sets up-regulated in MDA, black bars show down-regulated. (b) Sensitivity discordances in measurements of differential expression between amplification chemistries and standard protocol; a discordance between an amplification chemistry and the standard protocol was counted when one chemistry measured strong differential expression (black bars >64-fold, gray bars >16-fold, white bars >4-fold) while the other chemistry measured < 1.5-fold differential expression. A discordance is counted as negative (e.g., NG_pos for NuGEN) when the amplification chemistry measured strong differential expression while the standard protocol gave < 1.5-fold differential expression.

Confirmability of array results by qPCR and internal consistency of array results. (a) Differential gene expression measured by qPCR (white bars), by NuGEN (gray bars) and by the standard protocol (black bars) for nine transcripts where at least one probe set indicated sensitivity discordance between the two chemistries. (b) Measurement of differential expression of ApoE by five probe sets (white bars show results from Affymetrix chemistry, gray bars from Ambion, diagonally striped bars from Enzo, horizontally striped bars from NuGEN, and black bars from standard protocol chemistry).

Hierarchical clustering of all hybridization groups. All genes were clustered using a Pearson correlation following a filter based on signal intensity (100 cutoff). All samples clustered correctly within amplification technology, and the genes highlighted by the yellow box constitute the roughly 1500 additional differentially expressed genes in NuGEN amplified samples. Closer evaluation of all hybridization groups shows important differences between technologies, but most importantly demonstrates the overall comparability (on a gene-by-gene level) of all technologies evaluated. Std: 1x Affy; En: 2x Enzo; Af: 2x Affy; Am: 2x Ambion; Ng: NuGEN Ovation; RR: reference RNA; MDA: tumor RNA.

Pathway analysis was performed on the best- and worst-performing protocols to determine whether the biological implications of differentially expressed genes was compromised. The most differentially expressed genes from the Enzo two-round and NuGEN Ovation protocols were used in this comparison. PathwayAssist was used to generate direct (and indirect) interactions of differentially expressed genes between the two processing protocols. The gene products circled in blue represent hits from the Enzo analysis and demonstrate that the core biological mediators in this analysis are the same when comparing differentially expressed genes between NuGEN and Enzo. It is also clear that the NuGEN approach (in this comparison) yielded a significant increase in the number of genes identified in the pathways that correlate to the core sets of genes identified by both approaches. The main point is that even in the absence of a true biological model (as in this comparison with a reference gene) the core set of biologically interacting genes in this pathway are preserved between both small-sample amplification methods; however, a more sensitive amplification approach can lead to the detection of a larger set of differentially expressed genes within a pathway.