Though Illumina has largely dominated the RNA-Seq field, the simultaneous availability of Ion Torrent has left scientists wondering which platform is most effective for differential gene expression (DGE) analysis. Previous investigations of this question have typically used reference samples derived from cell lines and brain tissue, and do not involve biological variability. While these comparisons might inform studies of tissue-specific expression, marked by large-scale transcriptional differences, this is not the common use case.
University of Pennsylvania researchers employed a standard treatment/control experimental design, which enabled them to evaluate these platforms in the context of the expression differences common in differential gene expression experiments. Specifically, they assessed the hepatic inflammatory response of mice by assaying liver RNA from control and IL-1β treated animals with both the Illumina HiSeq and the Ion Torrent Proton sequencing platforms. They found the greatest difference between the platforms at the level of read alignment, a moderate level of concordance at the level of DGE analysis, and nearly identical results at the level of differentially affected pathways. Interestingly, the researchers also observed a strong interaction between sequencing platform and choice of aligner. By aligning both real and simulated Illumina and Ion Torrent data with the twelve most commonly-cited aligners in the literature, they observed that different aligner and platform combinations were better suited to probing different genomic features; for example, disentangling the source of expression in gene-pseudogene pairs.
A treatment/control experimental design
Ten mice were treated with IL-1β (n = 5), or saline (n = 5; referred to as untreated). Four hours after treatment, the mice were sacrificed, liver samples were collected, and total RNA was extracted from the tissue. At this point, aliquots of the same RNA sample were sequenced on both an Illumina HiSeq 2500 and an Ion Torrent Proton. Next, RNA-Seq reads from each platform were aligned using three alignment algorithms: 1) GSNAP, 2) STAR, and 3) STAR, followed by Bowtie2 to align reads not mapped by STAR (STAR + Bowtie2). Lastly, all aligned data were normalized using the Pipeline Of RNA-Seq Transformations (PORT)
Taken together, these results indicate that while Illumina and Ion Torrent have similar capacities to detect changes in biology from a treatment/control experiment, these platforms may be tailored to interrogate different transcriptional phenomena through careful selection of alignment software.