Development of maternal blood transcriptomic markers to monitor placental function and risk of obstetrical complications throughout pregnancy requires accurate quantification of gene expression.
PRB researchers benchmarked three state-of-the-art expression profiling techniques to assess in maternal circulation the expression of cell type-specific gene sets previously discovered by single-cell genomics studies of the placenta. The team compared Affymetrix Human Transcriptome Arrays, Illumina RNA-Seq, and sequencing-based targeted expression profiling (DriverMap™) to assess transcriptomic changes with gestational age and labor status at term, and tested 86 candidate genes by qRT-PCR.
DriverMap™ identified twice as many significant genes (q<0.1) than RNA-Seq and five times more than microarrays. The gap in the number of significant genes remained when testing only protein-coding genes detected by all platforms. qRT-PCR validation statistics (positive predictive value and area under the curve) were high and similar among platforms; yet dynamic ranges were higher for sequencing-based platforms than microarrays. DriverMap™ provided the strongest evidence for the association of B-cell and T-cell gene signatures with gestational age, while T-cell expression was increased with spontaneous labor at term according to all three platforms.
The team concluded that sequencing-based techniques are more suitable to quantify whole-blood gene expression compared to microarrays, as they have an expanded dynamic range and identify more true positives. Targeted expression profiling achieved higher coverage of protein-coding genes with fewer total sequenced reads, and it is especially suited to track cell type-specific signatures discovered in the placenta. The T-cell gene expression signature was increased in women who underwent spontaneous labor at term, mimicking immunological processes at the maternal-fetal interface and placenta.