Abstract
Dual RNA-Seq is the simultaneous retrieval and analysis of host and pathogen transcriptomes. It follows the rationale that cross-species interactions determine both pathogen virulence and host tolerance, resistance or susceptibility. Correlated gene expression might help identify interlinked signaling, metabolic or gene regulatory pathways in addition to potentially physically interacting proteins. Numerous studies have used RNA-Seq to investigate Plasmodium infection with a focus on only one organism, either the host or the parasite.
Here we propose a meta-analysis approach for dual RNA-Seq. We screened malaria transcriptome experiments for gene expression data from both Plasmodium and its host. Out of 105 malaria studies in Homo sapiens, Macaca mulatta and Mus musculus, we identified 56 studies with the potential to provide host and parasite data. While 15 studies (1,935 total samples) of these 56 explicitly aimed to generate dual RNA-Seq data, 41 (1,129 samples) had an original focus on either the host or the parasite. We show that a total of up to 2,530 samples are suitable for dual RNA-Seq analysis providing an unexplored potential for meta-analysis.
We argue that the multitude of variations in experimental conditions should help narrow down a conserved core of cross-species interactions. Different hosts are infected by evolutionarily diverse species of the genus Plasmodium. We propose to overlay interaction networks of different host-parasite systems based on orthologous genes. This might allow us to gauge the applicability of model systems for different pathways in malaria infection and to address the evolution of parasite-host interactions.
