Gene expression profiling of human whole blood samples with the Illumina WG-DASL assay

Abstract

Background: Microarray-based gene expression analysis of peripheral whole blood is a common strategy in the development of clinically relevant biomarker panels for a variety of human diseases. However, the results of such an analysis are often plagued by decreased sensitivity and reliability due to the effects of relatively high levels of globin mRNA in whole blood. Globin reduction assays have been shown to overcome such effects, but they require large amounts of total RNA and may induce distinct gene expression profiles. The Illumina whole genome DASL assay can detect gene expression levels using partially degraded RNA samples and has the potential to detect rare transcripts present in highly heterogeneous whole blood samples without the need for globin reduction. We assessed the utility of the whole genome DASL assay in an analysis of peripheral whole blood gene expression profiles.

Results: We find that gene expression detection is significantly increased with the use of whole genome DASL compared to the standard IVT-based direct hybridization. Additionally, globin-probe negative whole genome DASL did not exhibit significant improvements over globin-probe positive whole genome DASL. Globin reduction further increases the detection sensitivity and reliability of both whole genome DASL and IVT-based direct hybridization with little effect on raw intensity correlations. Raw intensity correlations between total RNA and globin reduced RNA were 0.955 for IVT-based direct hybridization and 0.979 for whole genome DASL.

Conclusions: Overall, the detection sensitivity of the whole genome DASL assay is higher than the IVT-based direct hybridization assay, with or without globin reduction, and should be considered in conjunction with globin reduction methods for future blood-based gene expression studies.

Figure 1

Flow diagram of study design. A PAXGene blood tube was collected from 8 individuals then frozen and stored for later processing. RNA was isolated and microarray targets prepared by one of five different methods: IVT-based direct hybridization with total RNA (WB IVT), IVT-based direct hybridization with globin-reduced RNA (GR IVT), whole-genome DAP+ DASL with total RNA (WB DAP+), whole-genome DAP- DASL with total RNA (WB DAP-), and whole-genome DAP+ DASL with globin-reduced RNA (GR DAP+).

Figure 2

Box plots of present calls. The number of detected probes (detection p-value < 0.05) per target preparation method are shown. The boxes represent the lower quartile through the upper quartile, while the whiskers extend to 1.5 times the interquartile range. A bold line denotes the median. WB IVT and GR IVT (n = 8). WB DASL+, WB DASL-, and GR DAP+ (n = 16).

Figure 3

Overlap of detected probes. Probes detected as present across all eight samples per target preparation method are compared. WB IVT: IVT-based direct hybridization with total RNA, GR IVT: IVT-based direct hybridization with globin-reduced RNA, WB DAP+: whole-genome DAP+ DASL with total RNA, WB DAP-: whole-genome DAP- DASL with total RNA, and GR DAP+: whole-genome DAP+ DASL with globin-reduced RNA.

Figure 4

Raw intensity scatter plots. Raw intensities for all probes (n = 24526) were compared for (A) whole blood RNA and globin reduced RNA with IVT, (B) whole blood RNA with DAP+ and whole blood RNA with DAP-, (C) whole blood RNA and globin reduced RNA with DAP+, and (D) whole blood RNA with DAP- and globin reduced RNA with DAP-. Correlations for sample 1 are depicted. Average correlations for paired WB IVT versus GR IVT, WB DAP+ versus WB DAP-, WB DAP+ versus GR DAP+, and WB DAP- versus GR DAP- samples are 0.955, 0.992, 0.976, and 0.979, respectively. All 8 hemoglobin genes assayed on Illumina BeadChip Human-Ref v3.0 are labelled: HBA2, HBB, HBD, HBE1, HBG1, HBG2, HBM, HBQ, and HBZ. GLOBINclear specifically targets only HBA2 and HBB for reduction.

Figure 5

Sample relations as assessed by unsupervised hierarchical clustering. Dendrogram reflecting the clustering of the individual samples and the different sample preparation methods. The dendrogram was constructed using hierarchical clustering methods as implemented in the Bioconductor lumi package.