Re-analysis of mobile mRNA datasets highlights challenges in the detection of mobile transcripts from short-read RNA-Seq data

Abstract

Short-read RNA-Seq analyses of grafted plants have led to the proposal that large numbers of mRNAs move over long distances between plant tissues, acting as potential signals. The detection of transported transcripts by RNA-Seq is both experimentally and computationally challenging, requiring successful grafting, delicate harvesting, rigorous contamination controls and data processing approaches that can identify rare events in inherently noisy data. Here, we perform a meta-analysis of existing datasets and examine the associated bioinformatic pipelines. Our analysis reveals that technological noise, biological variation and incomplete genome assemblies give rise to features in the data that can distort the interpretation. Taking these considerations into account, we find that a substantial number of transcripts that are currently annotated as mobile are left without support from the available RNA-Seq data. Whilst several annotated mobile mRNAs have been validated, we cannot exclude that others may be false positives. The identified issues may also impact other RNA-Seq studies, in particular those using single nucleotide polymorphisms (SNPs) to detect variants.