Refining dual RNA-seq mapping: sequential and combined approaches in host-parasitic plant dynamics

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Abstract

Transcriptional profiling in host plant-parasitic plant interactions is challenging due to the tight interface between host and parasitic plants and the percentage of homologous sequences shared. Dual RNA-seq offers a solution by enabling in silico separation of mixed transcripts from the interface region. However, it has to deal with issues related to multiple mapping and cross-mapping of reads in host and parasite genomes, particularly as evolutionary divergence decreases. In this paper, we evaluated the feasibility of this technique by simulating interactions between parasitic and host plants and refining the mapping process. More specifically, we merged host plant with parasitic plant transcriptomes and compared two alignment approaches: sequential mapping of reads to the two separate reference genomes and combined mapping of reads to a single concatenated genome. We considered Cuscuta campestris as parasitic plant and two host plants of interest such as Arabidopsis thaliana and Solanum lycopersicum. Both tested approaches achieved a mapping rate of ~90%, with only about 1% of cross-mapping reads. This suggests the effectiveness of the method in accurately separating mixed transcripts in silico. The combined approach proved slightly more accurate and less time consuming than the sequential approach. The evolutionary distance between parasitic and host plants did not significantly impact the accuracy of read assignment to their respective genomes since enough polymorphisms were present to ensure reliable differentiation. This study demonstrates the reliability of dual RNA-seq for studying host-parasite interactions within the same taxonomic kingdom, paving the way for further research into the key genes involved in plant parasitism.

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Fruggiero, C., Aufiero, G., D’Angelo, D., Pasolli, E., & D’Agostino, N. (2024). Refining dual RNA-seq mapping: sequential and combined approaches in host-parasitic plant dynamics. Frontiers in Plant Science, 15. https://doi.org/10.3389/fpls.2024.1483717

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