Novel targets for engineering Physostegia chlorotic mottle and tomato brown rugose fruit virus-resistant tomatoes: in silico prediction of tomato microRNA targets

Background Physostegia chlorotic mottle virus (PhCMoV; genus: Alphanucleorhabdovirus, family: Rhabdoviridae) and tomato brown rugose fruit virus (ToBRFV; genus: Tobamovirus, family: Virgaviridae) are newly emerging plant viruses that have a dramatic effect on tomato production. Among various known virus-control strategies, RNAi-mediated defence has shown the potential to protect plants against various pathogens including viral infections. Micro(mi)RNAs play a major role in RNAi-mediated defence. Methods Using in silico analyses, we investigated the possibility of tomato-encoded miRNAs (TomiRNA) to target PhCMoV and ToBRFV genomes using five different algorithms, i.e., miRanda, RNAhybrid, RNA22, Tapirhybrid and psRNATarget. Results The results revealed that 14 loci on PhCMoV and 10 loci on ToBRFV can be targeted by the TomiRNAs based on the prediction of at least three algorithms. Interestingly, one TomiRNA, miR6026, can target open reading frames from both viruses, i.e., the phosphoprotein encoding gene of PhCMoV, and the two replicase components of ToBRFV. There are currently no commercially available PhCMoV- or ToBRFV-resistant tomato varieties, therefore the predicted data provide useful information for the development of PhCMoV- and ToBFRV-resistant tomato plants

Comparative study on three viral enrichment approaches based on RNA extraction for plant virus/viroid detection using high-throughput sequencing.

High-throughput sequencing (HTS) has become increasingly popular as virus diagnostic tool. It has been used to detect and identify plant viruses and viroids in different types of matrices and tissues. A viral sequence enrichment method prior to HTS is required to increase the viral reads in the generated data to ease the bioinformatic analysis of generated sequences. In this study, we compared the sensitivity of three viral enrichment approaches, i.e. double stranded RNA (dsRNA), ribosomal RNA depleted total RNA (ribo-depleted totRNA) and small RNA (sRNA) for plant virus/viroid detection, followed by sequencing on MiSeq and NextSeq Illumina platforms. The three viral enrichment approaches used here enabled the detection of all viruses/viroid used in this study. When the data was normalised, the recovered viral/viroid nucleotides and depths were depending on the viral genome and the enrichment method used. Both dsRNA and ribo-depleted totRNA approaches detected a divergent strain of Wuhan aphid virus 2 that was not expected in this sample. Additionally, Vicia cryptic virus was detected in the data of dsRNA and sRNA approaches only. The results suggest that dsRNA enrichment has the highest potential to detect and identify plant viruses and viroids. The dsRNA approach used here detected all viruses/viroid, consumed less time, was lower in cost, and required less starting material. Therefore, this approach appears to be suitable for diagnostics laboratories