Detection of Banana Mild Mosaic Virus in Musa In Vitro Plants: High-Throughput Sequencing Presents Higher Diagnostic Sensitivity Than (IC)-RT-PCR and Identifies a New Betaflexiviridae Species

Abstract

: The banana mild mosaic virus (BanMMV) (Betaflexiviridae, Quinvirinae, unassigned species) is a filamentous virus that infects Musa spp. and has a very wide geographical distribution. The current BanMMV indexing process for an accession requires the testing of no less than four plants cultivated in a greenhouse for at least 6 months and causes a significant delay for the distribution of the germplasm. We evaluated the sensitivity of different protocols for BanMMV detection from in vitro plants to accelerate the testing process. We first used corm tissues from 137 in vitro plants and obtained a diagnostic sensitivity (DSE) of only 61% when testing four plants per accession. After thermotherapy was carried out to eliminate BanMMV infection, the meristem was recovered and further grown in vitro. The same protocol was evaluated in parallel on the corm tissue surrounding the meristem, as a rapid screening to evaluate virus therapy success, and was compared to the results obtained following the standard protocol. The obtained results showed 28% false negatives when conducting testing from corm tissues, making this protocol unsuitable in routine processes. Furthermore, RT-PCR and high-throughput sequencing (HTS) tests were applied on tissues from the base (n = 39) and the leaves (n = 36). For RT-PCR, the average DSE per sample reached 65% from either the base or leaves. HTS was applied on 36 samples and yielded 100% diagnostic specificity (DSP) and 100% DSE, whatever the sampled tissue, allowing the identification of a new Betaflexiviridae species infecting Musa. These results suggest that a reliable diagnostic of BanMMV from in vitro plants using RT-PCR or HTS technologies might represent an efficient alternative for testing after greenhouse cultivation.

Viroscope: Plant viral diagnosis from high-throughput sequencing data using biologically-informed genome assembly coverage

“…(Adams et al, 2018;Gauthier et al, 2022). Due to its untargeted nature, HTS is capable of detecting multiple viruses (known as well as novel ones) in infected material even when viruses are present in very low concentrations (Hanafi et al, 2022). In addition, it has proved to be a major advance for crops, imported plants and germplasm in which disease symptoms are absent, unspecific or only triggered by multiple viruses (Massart et al, 2017;Mehetre et al, 2021).…”

“…Although the vast majority of virus diagnostic tools have been focused on human clinical samples -VirusFinder and VERSE (Wang et al, 2013(Wang et al, , 2015, VIP (Li et al, 2016), VirusSeeker (Zhao et al, 2017)-some efforts have been focused specifically on plants -VirFind (Ho and Tzanetakis, 2014), VSD toolkit (Barrero et al, 2017), Virtool (Rott et al, 2017) and PVDP (Gutiérrez et al, 2021). However, bioinformatic pipelines have presented challenges for standardization and incongruences in frequently used metrics such as read counts, genome coverage or a combination of both criteria are common (Visser et al, 2016;Rott et al, 2017;Malapi-Wight et al, 2021;Soltani et al, 2021;Hanafi et al, 2022). Also, threshold harmonization is required to establish virus detection using HTS (Ruiz-García et al, 2021), particularly in cases with low sequencing coverage.…”

Viroscope: plant viral diagnosis from NGS data using biologically-informed genome assembly coverage

“…In the last two decades, NGS methods have become a reliable tool for plant virus diagnostics including managing disease risk, emergence, and the adoption of novel phytosanitary rules (Adams et al, 2018; Gauthier et al, 2022). Due to its untargeted nature, NGS is capable of detecting multiple viruses (known as well as emergent ones) in infected material also when viruses are present in very low concentrations (Hanafi et al, 2022). In addition, it has proved to be a major advance for crops, imported plants and germplasm in which disease symptoms are absent, unspecific or only triggered by multiple viruses (Massart et al, 2017; Mehetre et al, 2021).…”

“…Although the vast majority of virus diagnostic tools have been focused on human clinical samples – VirusFinder and VERSE (Wang et at., 2013; 2015), VIP (Li et al, 2016), VirusSeeker (Zhao et al, 2017)– some efforts have been focused specifically on plants – VirFind (Ho and Tzanetakis, 2014), VSD toolkit (Barrero et al, 2017), Virtool (Rott et al, 2017) and PVDP (Gutierrez et al, 2021). However, bioinformatic pipelines have presented challenges for standardization and incongruences in frequently used metrics such as read counts, genome coverage or a combination of both criteria are common (Visser et al, 2016, Rott et al, 2017, Malapi-Wight et al, 2021, Soltani et al, 2021, Hanafi et al 2022). Also, threshold harmonization is required to establish virus detection using NGS (Ruiz-García, et al, 2021), particularly in cases with low sequencing coverage.…”

Going beyond consensus genome sequences: An innovative SNP-based methodology reconstructs different Ugandan cassava brown streak virus haplotypes at a nationwide scale in Rwanda

“…at least 5–10 per cent of divergence, their consensus genome sequence reconstruction is possible using classical de novo assembly ( Winter et al. 2010 ; Hanafi et al 2022 ; Kim et al 2022 ), and several consensus sequences can be obtained. The presence and frequency of SNPs can be further studied for each genome sequence.…”