Correction: Haegeman et al. Looking beyond Virus Detection in RNA Sequencing Data: Lessons Learned from a Community-Based Effort to Detect Cellular Plant Pathogens and Pests. Plants 2023, 12, 2139.

In the original publication [...].

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

Cassava Brown Streak Disease (CBSD), which is caused by cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV), represents one of the most devastating threats to cassava production in Africa, including in Rwanda where a dramatic epidemic in 2014 dropped cassava yield from 3.3 million to 900,000 tonnes (1). Studying viral genetic diversity at the genome level is essential in disease management, as it can provide valuable information on the origin and dynamics of epidemic events. To fill the current lack of genome-based diversity studies of UCBSV, we performed a nationwide survey of cassava ipomovirus genomic sequences in Rwanda by high-throughput sequencing (HTS) of pools of plants sampled from 130 cassava fields in thirteen cassava-producing districts, spanning seven agro-ecological zones with contrasting climatic conditions and different cassava cultivars. HTS allowed the assembly of a nearly complete consensus genome of UCBSV in twelve districts. The phylogenetic analysis revealed high homology between UCBSV genome sequences, with a maximum of 0.8 per cent divergence between genomes at the nucleotide level. An in-depth investigation based on Single Nucleotide Polymorphisms (SNPs) was conducted to explore the genome diversity beyond the consensus sequences. First, to ensure the validity of the result, a panel of SNPs was confirmed by independent reverse transcription polymerase chain reaction (RT-PCR) and Sanger sequencing. Furthermore, the combination of fixation index (FST) calculation and Principal Component Analysis (PCA) based on SNP patterns identified three different UCBSV haplotypes geographically clustered. The haplotype 2 (H2) was restricted to the central regions, where the NAROCAS 1 cultivar is predominantly farmed. RT-PCR and Sanger sequencing of individual NAROCAS1 plants confirmed their association with H2. Haplotype 1 was widely spread, with a 100 per cent occurrence in the Eastern region, while Haplotype 3 was only found in the Western region. These haplotypes' associations with specific cultivars or regions would need further confirmation. Our results prove that a much more complex picture of genetic diversity can be deciphered beyond the consensus sequences, with practical implications on virus epidemiology, evolution, and disease management. Our methodology proposes a high-resolution analysis of genome diversity beyond the consensus between and within samples. It can be used at various scales, from individual plants to pooled samples of virus-infected plants. Our findings also showed how subtle genetic differences could be informative on the potential impact of agricultural practices, as the presence and frequency of a virus haplotype could be correlated with the dissemination and adoption of improved cultivars.

Detection of single nucleotide polymorphisms in virus genomes assembled from high-throughput sequencing data: large-scale performance testing of sequence analysis strategies.

Recent developments in high-throughput sequencing (HTS) technologies and bioinformatics have drastically changed research in virology, especially for virus discovery. Indeed, proper monitoring of the viral population requires information on the different isolates circulating in the studied area. For this purpose, HTS has greatly facilitated the sequencing of new genomes of detected viruses and their comparison. However, bioinformatics analyses allowing reconstruction of genome sequences and detection of single nucleotide polymorphisms (SNPs) can potentially create bias and has not been widely addressed so far. Therefore, more knowledge is required on the limitations of predicting SNPs based on HTS-generated sequence samples. To address this issue, we compared the ability of 14 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 21 variants of pepino mosaic virus (PepMV) in three samples through large-scale performance testing (PT) using three artificially designed datasets. To evaluate the impact of bioinformatics analyses, they were divided into three key steps: reads pre-processing, virus-isolate identification, and variant calling. Each step was evaluated independently through an original, PT design including discussion and validation between participants at each step. Overall, this work underlines key parameters influencing SNPs detection and proposes recommendations for reliable variant calling for plant viruses. The identification of the closest reference, mapping parameters and manual validation of the detection were recognized as the most impactful analysis steps for the success of the SNPs detections. Strategies to improve the prediction of SNPs are also discussed.

Looking beyond Virus Detection in RNA Sequencing Data: Lessons Learned from a Community-Based Effort to Detect Cellular Plant Pathogens and Pests.

High-throughput sequencing (HTS), more specifically RNA sequencing of plant tissues, has become an indispensable tool for plant virologists to detect and identify plant viruses. During the data analysis step, plant virologists typically compare the obtained sequences to reference virus databases. In this way, they are neglecting sequences without homologies to viruses, which usually represent the majority of sequencing reads. We hypothesized that traces of other pathogens might be detected in this unused sequence data. In the present study, our goal was to investigate whether total RNA-seq data, as generated for plant virus detection, is also suitable for the detection of other plant pathogens and pests. As proof of concept, we first analyzed RNA-seq datasets of plant materials with confirmed infections by cellular pathogens in order to check whether these non-viral pathogens could be easily detected in the data. Next, we set up a community effort to re-analyze existing Illumina RNA-seq datasets used for virus detection to check for the potential presence of non-viral pathogens or pests. In total, 101 datasets from 15 participants derived from 51 different plant species were re-analyzed, of which 37 were selected for subsequent in-depth analyses. In 29 of the 37 selected samples (78%), we found convincing traces of non-viral plant pathogens or pests. The organisms most frequently detected in this way were fungi (15/37 datasets), followed by insects (13/37) and mites (9/37). The presence of some of the detected pathogens was confirmed by independent (q)PCRs analyses. After communicating the results, 6 out of the 15 participants indicated that they were unaware of the possible presence of these pathogens in their sample(s). All participants indicated that they would broaden the scope of their bioinformatic analyses in future studies and thus check for the presence of non-viral pathogens. In conclusion, we show that it is possible to detect non-viral pathogens or pests from total RNA-seq datasets, in this case primarily fungi, insects, and mites. With this study, we hope to raise awareness among plant virologists that their data might be useful for fellow plant pathologists in other disciplines (mycology, entomology, bacteriology) as well.

Long-Term Anthropogenic Management and Associated Loss of Plant Diversity Deeply Impact Virome Richness and Composition of Poaceae Communities.

Modern agriculture has influenced plant virus emergence through ecosystem simplification, introduction of new host species, and reduction in crop genetic diversity. Therefore, it is crucial to better understand virus distributions across cultivated and uncultivated communities in agro-ecological interfaces, as well as virus exchange among them. Here, we advance fundamental understanding in this area by characterizing the virome of three co-occurring replicated Poaceae community types that represent a gradient of grass species richness and management intensity, from highly managed crop monocultures to little-managed, species-rich grasslands. We performed a large-scale study on 950 wild and cultivated Poaceae over 2 years, combining untargeted virome analysis down to the virus species level with targeted detection of three plant viruses. Deep sequencing revealed (i) a diversified and largely unknown Poaceae virome (at least 51 virus species or taxa), with an abundance of so-called persistent viruses; (ii) an increase of virome richness with grass species richness within the community; (iii) stability of virome richness over time but a large viral intraspecific variability; and (iv) contrasting patterns of virus prevalence, coinfections, and spatial distribution among plant communities and species. Our findings highlight the complex structure of plant virus communities in nature and suggest the influence of anthropogenic management on viral distribution and prevalence. IMPORTANCE Because viruses have been mostly studied in cultivated plants, little is known about virus diversity and ecology in less-managed vegetation or about the influence of human management and agriculture on virome composition. Poaceae (grass family)-dominated communities provide invaluable opportunities to examine these ecological issues, as they are distributed worldwide across agro-ecological gradients, are essential for food security and conservation, and can be infected by numerous viruses. Here, we used multiple levels of analysis that considered plant communities, individual plants, virus species, and haplotypes to broaden understanding of the Poaceae virome and to evaluate host-parasite richness relationships within agro-ecological landscapes in our study area. We emphasized the influence of grass diversity and land use on the composition of viral communities and their life history strategies, and we demonstrated the complexity of plant-virus interactions in less-managed grass communities, such as the higher virus prevalence and overrepresentation of mixed virus infection compared to theoretical predictions.

Virus Evolution Faced to Multiple Host Targets: The Potyvirus-Pepper Case Study.

The wealth of variability amongst genes controlling immunity against potyviruses in pepper (Capsicum spp.) has been instrumental in understanding plant-virus co-evolution and major determinants of plant resistance durability. Characterization of the eukaryotic initiation factor 4E1 (eIF4E1), involved in mRNA translation, as the basis of potyvirus resistance in pepper initiated a large body of work that showed that recessive resistance to potyviruses and other single-stranded positive-sense RNA viruses resulted from mutations in eukaryotic initiation factors in many plant crop species. Combining mutations in different eIF4Es in the same pepper genotype had complex effects on the breadth of the resistance spectrum and on resistance durability, revealing a trade-off between these two traits. In addition, combining eIF4E1 mutations with a quantitatively resistant genetic background had a strong positive effect on resistance durability. Analysing the evolutionary forces imposed by pepper genotypes onto virus populations allowed identifying three key factors improving plant resistance durability: the complexity of mutational pathways involved in virus adaptation to the plant resistance, the decrease of competitivity induced by these mutations on the virus and the intensity of genetic drift imposed by plant genotypes on the virus during its infection cycle.

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.

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.

Concurrent evolution of resistance and tolerance to potato virus Y in Capsicum annuum revealed by genome-wide association.

We performed a genome-wide association study of pepper (Capsicum annuum) tolerance to potato virus Y (PVY). For 254 pepper accessions, we estimated the tolerance to PVY as the coefficient of regression of the fresh weight (or height) of PVY-infected and mock-inoculated plants against within-plant virus load. Small (strongly negative) coefficients of regression indicate low tolerance because plant biomass or growth decreases sharply as virus load increases. The tolerance level varied largely, with some pepper accessions showing no symptoms or fairly mild mosaics, whereas about half (48%) of the accessions showed necrotic symptoms. We found two adjacent single-nucleotide polymorphisms (SNPs) at one extremity of chromosome 9 that were significantly associated with tolerance to PVY. Similarly, in three biparental pepper progenies, we showed that the induction of necrosis on PVY systemic infection segregated as a monogenic trait determined by a locus on chromosome 9. Our results also demonstrate the existence of a negative correlation between resistance and tolerance among the cultivated pepper accessions at both the phenotypic and genetic levels. By comparing the distributions of the tolerance-associated SNP alleles and previously identified PVY resistance-associated SNP alleles, we showed that cultivated pepper accessions possess favourable alleles for both resistance and tolerance less frequently than expected under random associations, while the minority of wild pepper accessions frequently combined resistance and tolerance alleles. This divergent evolution of PVY resistance and tolerance could be related to pepper domestication or farmer's selection.

Corrigendum: A Survey Using High-Throughput Sequencing Suggests That the Diversity of Cereal and Barley Yellow Dwarf Viruses Is Underestimated.

[This corrects the article DOI: 10.3389/fmicb.2021.673218.].

A Survey Using High-Throughput Sequencing Suggests That the Diversity of Cereal and Barley Yellow Dwarf Viruses Is Underestimated.

Worldwide, barley/cereal yellow dwarf viruses (YDVs) are the most widespread and damaging group of cereal viruses. In this study, we applied high-throughput sequencing technologies (HTS) to perform a virus survey on symptomatic plants from 47 cereal fields in Estonia. HTS allowed the assembly of complete genome sequences for 22 isolates of cereal yellow dwarf virus RPS, barley yellow dwarf virus GAV, barley yellow dwarf virus PAS (BYDV-PAS), barley yellow dwarf virus PAV (BYDV-PAV), and barley yellow dwarf virus OYV (BYDV-OYV). We also assembled a near-complete genome of the putative novel species BYDV-OYV from Swedish samples of meadow fescue. Previously, partial sequencing of the central part of the coat protein gene indicated that BYDV-OYV represented a putative new species closely related to BYDV-PAV-CN, which currently is recognized as a subtype of BYDV-PAV. The present study found that whereas the 3'gene block of BYDV-OYV shares the closest relationship with BYDV-PAV-CN, the 5'gene block of BYDV-OYV shows the closest relationships to that of BYDV-PAS. Recombination detection analysis revealed that BYDV-OYV is a parental virus for both. Analysis of complete genome sequence data indicates that both BYDV-OYV and BYDV-PAV-CN meet the species criteria of genus Luteovirus. The study discusses BYDV phylogeny, and through a systematic in silico analysis of published primers for YDV detection, the existing gaps in current diagnostic practices for detection of YDVs, proposing primer pairs based on the most recent genomic information for the detection of different BYDV species. Thanks to the rising number of sequences available in databases, continuous updating of diagnostic primers can improve test specificity, e.g., inclusivity and exclusivity at species levels. This is needed to properly survey the geographical and host distribution of the different species of the YDV complex and their prevalence in cereal/barley yellow dwarf disease epidemics.

A Primer on the Analysis of High-Throughput Sequencing Data for Detection of Plant Viruses.

High-throughput sequencing (HTS) technologies have become indispensable tools assisting plant virus diagnostics and research thanks to their ability to detect any plant virus in a sample without prior knowledge. As HTS technologies are heavily relying on bioinformatics analysis of the huge amount of generated sequences, it is of utmost importance that researchers can rely on efficient and reliable bioinformatic tools and can understand the principles, advantages, and disadvantages of the tools used. Here, we present a critical overview of the steps involved in HTS as employed for plant virus detection and virome characterization. We start from sample preparation and nucleic acid extraction as appropriate to the chosen HTS strategy, which is followed by basic data analysis requirements, an extensive overview of the in-depth data processing options, and taxonomic classification of viral sequences detected. By presenting the bioinformatic tools and a detailed overview of the consecutive steps that can be used to implement a well-structured HTS data analysis in an easy and accessible way, this paper is targeted at both beginners and expert scientists engaging in HTS plant virome projects.

Molecular and biological characterization of a new mulberry idaeovirus.

A virus-like disease with symptoms including mosaic structure, deformation, vein clearing and necrosis on the leaves and deformation, crumbling, and scab on the fruits was detected in black mulberry trees (Morus nigra L.) in Kayseri province of Turkey. A novel positive single-stranded RNA virus with a bipartite genome and the mulberry badnavirus 1 (MBV-1) were detected in the black mulberry trees by high throughput sequencing and bioinformatic analyses. The novel virus RNA1 (5,796/7 nt) encodes a polyprotein (1,808 aa, 204.31 kDa) with three conserved domains, [MTR (aa 294-705), Hel (aa 971-1,226) and RdRp (aa 1,348-1,788)], whereas RNA2 (2,243 nt) encodes two putative proteins, MP (374 aa, 40.98 kDa), and CP (272 aa, 30.59 kDa), separated by an intergenic region of 97 nt. The highest amino acids identities were 70, 57 and 70 % with raspberry bushy dwarf virus (RBDV) for ORF1, MP and CP genes, respectively. The genome organization and phylogenetic analyses suggested that the novel virus is likely a putative new member of the genus Idaeovirus and it has been tentatively named black mulberry idaeovirus (BMIV). Virus survey showed both the BMIV and MBV-1 are likely prevalent in the region. Seven complete (six Turkish and one Iranian) and 41 partial genome sequences of the BMIV isolates revealed moderate genetic diversity (0.033 ± 0.001 %, 0.020 ± 0.002 % and 0.016 ± 0.002 % for RNA1, RNA2, and partial genomes, respectively). Both the BMIV and MBV-1 were detected in all tested pollens (n = 24, 100 %), in seed-borne balck mulberry saplings (n = 96, 100 %).This situation clearly revealed the potential spread risk of both viruses in black mulberry plantations and the necessity of taking precautions.

Identification, molecular and biological characterization of two novel secovirids in wild grass species in Belgium.

High throughput sequencing was performed on virion-associated nucleic acids (VANA) from a pool of fifty asymptomatic rough bluegrasses (Poa trivialis L.) collected in a Belgian grazed pasture. Bioinformatics analyses produced some contigs presenting similarities with secovirid genomes, in particular nepoviruses and waikaviruses. Three distinct positive-sense single-stranded RNAs including 5' and 3' UTR were reconstructed and they represented two novel viruses infecting rough bluegrass, for which the provisional names poaceae Liege nepovirus A (PoLNVA, 7298 nt for RNA1 and 4263 nt for RNA2) and poaceae Liege virus 1 (PoLV1, 11,623 nt) were proposed. Compared to other Secoviridae members, the highest amino acid identity reached 90.7 % and 66.7 % between PoLNVA and nepoviruses for the Pro-Pol and CP regions respectively, while PoLV1 presented the highest amino acid identity with waikaviruses but with lower identities, i.e. 41.2 % for Pro-Pol and 25.8 % for CP regions, far below the ICTV demarcation criteria for novel secovirid. Based on sequence identity and phylogenetic analyses, PoLNVA was proposed to belong to the genus Nepovirus and PoLV1 as an unclassified secovirids. Detection of the two novel viruses was confirmed in high prevalence in rough bluegrass and ten other wild Poaceae species (Agropyron repens, Agrostis capillaris, Apera spica-venti, Anthoxanthum odoratum, Cynosorus cristatus, Festuca rubra, Holcus lanatus, Lolium perenne, Phleum bertolini and Phleum pratense) by RT-PCR and Sanger sequencing, revealing a diverse host range within Poaceae for these novel secovirids. Seed transmission was evaluated and confirmed for PoLNVA.

Identification of Divergent Isolates of Banana Mild Mosaic Virus and Development of a New Diagnostic Primer to Improve Detection.

Banana mild mosaic virus (BanMMV) (Betaflexiviridae, Quinvirinae, unassigned species) is a filamentous virus belonging to the Betaflexiviridae family. It infects Musa spp. with a very wide geographic distribution. The genome variability of plant viruses, including the members of the Betaflexiviridae family, makes their molecular detection by specific primers particularly challenging. During routine indexing of the Musa germplasm accessions, a discrepancy was observed between electron microscopy and immunocapture (IC) reverse transcription (RT) polymerase chain reaction (PCR) test results for one asymptomatic accession. Filamentous viral particles were observed while molecular tests failed to amplify any fragment. The accession underwent high-throughput sequencing and two complete genomes of BanMMV with 75.3% of identity were assembled. Based on these sequences and on the 54 coat protein sequences available from GenBank, a new forward primer, named BanMMV CP9, compatible with Poty1, an oligodT reverse primer already used in diagnostics, was designed. A retrospective analysis of 110 different germplasm accessions from diverse origins was conducted, comparing BanMMCP2 and BanMMV CP9 primers. Of these 110 accessions, 16 tested positive with both BanMMCP2 and BanMMV CP9, 3 were positive with only BanMMCP2 and 2 tested positive with only BanMMV CP9. Otherwise, 89 were negative with the two primers and free of flexuous virions. Sanger sequencing was performed from purified PCR products in order to confirm the amplification of the BanMMV sequence for the five accessions with contrasting results. It is highly recommended to use the two primers successively to improve the inclusiveness of the protocol.

Complete Sequence, Genome Organization and Molecular Detection of Grapevine Line Pattern Virus, a New Putative Anulavirus Infecting Grapevine.

: Grapevine line pattern virus (GLPV) was first described 30 years ago in Hungary. The lack of its genomic sequences and of an available antiserum made its detection impossible in other parts of the world. Three different high-throughput sequencing (HTS) protocols applied on a GLPV-infected vine allowed the construction of the full genome sequence of this virus. It includes three RNA segments, encoding four proteins: methyltransferase-helicase (1a), RNA-dependent RNA polymerase (2a), movement protein (3a) and coat protein (3b). The obtained sequences were used to design specific primers for its detection by RT-PCR and Northern blot hybridization, respectively. These diagnostic methods were used to test the presence of GLPV in graft-inoculated plants and in 220 grapevine accessions of different Mediterranean origins. The three RNAs-encoding proteins of GLPV shared a very high amino acid identity with those of hop yellow virus, a tentative member of the Anulavirus genus, leaving no doubt that both are two isolates of the same viral species. A circular RNA originating from the RNA2 was found, for which an alternative silencing suppressor role is hypothesized. Further investigation is needed to determine this possibility and also the host range and pathological significance of the virus.

Genome-wide association mapping of QTLs implied in potato virus Y population sizes in pepper: evidence for widespread resistance QTL pyramiding.

In this study, we looked for genetic factors in the pepper (Capsicum annuum) germplasm that control the number of potato virus Y (PVY) particles entering the plant (i.e. effective population size at inoculation) and the PVY accumulation at the systemic level (i.e. census population size). Using genotyping-by-sequencing (GBS) in a core collection of 256 pepper accessions, we obtained 10 307 single nucleotide polymorphisms (SNPs) covering the whole genome. Genome-wide association studies (GWAS) detected seven SNPs significantly associated with the virus population size at inoculation and/or systemic level on chromosomes 4, 6, 9 and 12. Two SNPs on chromosome 4 associated with both PVY population sizes map closely to the major resistance gene pvr2 encoding the eukaryotic initiation factor 4E. No obvious candidates for resistance were identified in the confidence intervals for the other chromosomes. SNPs detected on chromosomes 6 and 12 colocalized with resistance quantitative trait loci (QTLs) previously identified with a biparental population. These results show the efficiency of GBS and GWAS in C. annuum, indicate highly consistent results between GWAS and classical QTL mapping, and suggest that resistance QTLs identified with a biparental population are representative of a much larger collection of pepper accessions. Moreover, the resistance alleles at these different loci were more frequently combined than expected by chance in the core collection, indicating widespread pyramiding of resistance QTLs and widespread combination of resistance QTLs and major effect genes. Such pyramiding may increase resistance efficiency and/or durability.

Sixty Years After the First Description: Genome Sequence and Biological Characterization of European Wheat Striate Mosaic Virus Infecting Cereal Crops.

High-throughput sequencing technologies were used to identify plant viruses in cereal samples surveyed from 2012 to 2017. Fifteen genome sequences of a tenuivirus infecting wheat, oats, and spelt in Estonia, Norway, and Sweden were identified and characterized by their distances to other tenuivirus sequences. Like most tenuiviruses, the genome of this tenuivirus contains four genomic segments. The isolates found from different countries shared at least 92% nucleotide sequence identity at the genome level. The planthopper Javesella pellucida was identified as a vector of the virus. Laboratory transmission tests using this vector indicated that wheat, oats, barley, rye, and triticale, but none of the tested pasture grass species (Alopecurus pratensis, Dactylis glomerata, Festuca rubra, Lolium multiflorum, Phleum pratense, and Poa pratensis), are susceptible. Taking into account the vector and host range data, the tenuivirus we have found most probably represents European wheat striate mosaic virus first identified about 60 years ago. Interestingly, whereas we were not able to infect any of the tested cereal species mechanically, Nicotiana benthamiana was infected via mechanical inoculation in laboratory conditions, displaying symptoms of yellow spots and vein clearing evolving into necrosis, eventually leading to plant death. Surprisingly, one of the virus genome segments (RNA2) encoding both a putative host systemic movement enhancer protein and a putative vector transmission factor was not detected in N. benthamiana after several passages even though systemic infection was observed, raising fundamental questions about the role of this segment in the systemic spread in several hosts.

Impact of genetic drift, selection and accumulation level on virus adaptation to its host plants.

The efficiency of plant major resistance genes is limited by the emergence and spread of resistance-breaking mutants. Modulation of the evolutionary forces acting on pathogen populations constitutes a promising way to increase the durability of these genes. We studied the effect of four plant traits affecting these evolutionary forces on the rate of resistance breakdown (RB) by a virus. Two of these traits correspond to virus effective population sizes (Ne ) at either plant inoculation or during infection. The third trait corresponds to differential selection exerted by the plant on the virus population. Finally, the fourth trait corresponds to within-plant virus accumulation (VA). These traits were measured experimentally on Potato virus Y (PVY) inoculated to a set of 84 pepper doubled-haploid lines, all carrying the same pvr23 resistance gene, but having contrasting genetic backgrounds. The lines showed extensive variation for the rate of pvr23 RB by PVY and for the four other traits of interest. A generalized linear model showed that three of these four traits, with the exception of Ne at inoculation, and several pairwise interactions between them had significant effects on RB. RB increased with increasing values of Ne during plant infection or VA. The effect of differential selection was more complex because of a strong interaction with VA. When VA was high, RB increased as the differential selection increased. An opposite relationship between RB and differential selection was observed when VA was low. This study provides a framework to select plants with appropriate virus evolution-related traits to avoid or delay RB.

Ecological and sanitary impacts of bacterial communities associated to biological invasions in African commensal rodent communities.

Changes in host-parasite ecological interactions during biological invasion events may affect both the outcome of invasions and the dynamics of exotic and/or endemic infections. We tested these hypotheses, by investigating ongoing house mouse (Mus musculus domesticus) and black rat (Rattus rattus) invasions in Senegal (West Africa). We used a 16S gene rRNA amplicon sequencing approach to study potentially zoonotic bacterial communities in invasive and native rodents sampled along two well-defined independent invasion routes. We found that individual host factors (body mass and sex) were important drivers of these bacterial infections in rodents. We observed that the bacterial communities varied along invasion routes and differed between invasive and native rodents, with native rodents displaying higher overall bacterial diversity than invasive rodents. Differences in prevalence levels for some bacterial Operational Taxonomic Units (OTUs) provided support for ecological processes connecting parasitism and invasion success. Finally, our results indicated that rodent invasions may lead to the introduction of exotic bacterial genera and/or to changes in the prevalence of endemic ones. This study illustrates the difficulty of predicting the relationship between biodiversity and disease risks, and advocate for public health prevention strategies based on global pathogen surveillance followed by accurate characterization of potential zoonotic agents.

Quantitative trait loci in pepper control the effective population size of two RNA viruses at inoculation.

Infection of plants by viruses is a complex process involving several steps: inoculation into plant cells, replication in inoculated cells and plant colonization. The success of the different steps depends, in part, on the viral effective population size (Ne), defined as the number of individuals passing their genes to the next generation. During infection, the virus population will undergo bottlenecks, leading to drastic reductions in Ne and, potentially, to the loss of the fittest variants. Therefore, it is crucial to better understand how plants affect Ne. We aimed to (i) identify the plant genetic factors controlling Ne during inoculation, (ii) understand the mechanisms used by the plant to control Ne and (iii) compare these genetic factors with the genes controlling plant resistance to viruses. Ne was measured in a doubled-haploid population of Capsicum annuum. Plants were inoculated with either a Potato virus Y (PVY) construct expressing the green fluorescent protein or a necrotic variant of Cucumber mosaic virus (CMV). Newas assessed by counting the number of primary infection foci on cotyledons for PVY or the number of necrotic local lesions on leaves for CMV. The number of foci and lesions was correlated (r=0.57) and showed a high heritability (h2=0.93 for PVY and h2=0.98 for CMV). The Ne of the two viruses was controlled by both common quantitative trait loci (QTLs) and virus-specific QTLs, indicating the contribution of general and specific mechanisms. The PVY-specific QTL colocalizes with a QTL that reduces PVY accumulation and the capacity to break down a major-effect resistance gene.