Strategy in wheat-Fusarium dual-genome RNA-seq data processing

Abstract

In RNA-seq data processing, short read alignments are usually of one species against its own genome; however, in plant-microbe interaction systems, reads from both host and pathogen samples are blended together. In contrast to single-genome, both pathogen and host reference genomes are involved in the alignment process. In such circumstances, the order of alignment to the host, the pathogen, or simultaneously to both genomes results in differences in read counts of certain genes, especially at the advanced infection stage. It is crucial to have an appropriate strategy for aligning the reads to their respective genomes, yet the existing strategies of either sequential or parallel alignment become a problem when mapping mixed reads to their corresponding reference genomes. The challenge lies in the determination of which reads belong to which species, especially when homology exists between the two genomes. This study proposes a combo-genome alignment strategy after comparing three alignment scenarios. Simulation results demonstrated that the degree of discrepancy in the results is correlated with phylogenetic distance of the two species in the mixture which was attributable to the extent of homology between the two genomes involved. This correlation was also found in the analysis using two real RNA-seq datasets of Fusarium-challenged wheat plants. Comparisons of the three RNA-seq processing strategies on three simulation datasets and two real Fusarium-infected wheat datasets showed that an alignment to a combo-genome, consisting of both host and pathogen genomes, improves mapping quality as compared to sequential alignment procedures.