# Sympatric Populations of Crop and Wild Carrots (Daucus carota subsp.) Have Distinct Viromes, with Shared Core Species More Prevalent in Farm-Grown Populations

Deborah Schönegger, Armelle Marais, Fernando Garcia Arenal, Carolyn Malmstrom, Marcos Martinez Jimenez, Michael Mcleish, Marie Lefebvre, Chantal Faure, Laurence Svanella-Dumas, Thierry Candresse

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Deborah Schönegger, Armelle Marais, Fernando Garcia Arenal, Carolyn Malmstrom, Marcos Martinez Jimenez, et al.. Sympatric Populations of Crop and Wild Carrots (Daucus carota subsp.) Have Distinct Viromes, with Shared Core Species More Prevalent in Farm-Grown Populations. Phytobiomes Journal, 2025, 9 (1), pp.8-20. 10.1094/PBIOMES-06-24-0062-R. hal-05125724

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RESEARCH

# Sympatric Populations of Crop and Wild Carrots (*Daucus carota* subsp.) Have Distinct Viromes, with Shared Core Species More Prevalent in Farm-Grown Populations

Deborah Schönegger,<fnref n="1" /> Armelle Marais,<fnref n="1" /> ID Fernando Garcia Arenal,<fnref n="2" /> Carolyn M. Malmstrom,<fnref n="3" /> Marcos Martinez Jimenez,<fnref n="2" />

Michael McLeish,<fnref n="2" /> Marie Lefebvre,<fnref n="1" /> Chantal Faure,<fnref n="1" /> Laurence Svanella-Dumas,<fnref n="1" /> and Thierry Candresse<fnref n="1" />,† ID

Accepted for publication 26 October 2024.

Abstract

Viral exchanges between crops and wild plants are important considerations in virus ecology and epidemiology but remain poorly understood. To investigate such exchanges, we compared the viromes of wild and farmed carrots (Daucus carota subsp.) growing near each other in France. Farm populations included cultivated varieties and off-type carrots (resembling wild ones) growing among them. This crop-wild relative pathosystem offers notable opportunities for virus exchange due to the hosts' genetic closeness and geographic proximity. High-throughput sequencing found that viral taxonomic richness was greatest in wild carrots. However, hierarchical clustering and bipartite network analyses revealed that wild and farm carrot viromes differed in their seedborne and vector-borne components. About 50% of viral taxa were shared among population types, whereas others were uniquely associated with either wild or farm carrots. Individual-plant RT-PCR testing of 16 aphid-borne agents from the shared core virome found that their prevalence was generally

greatest in farm populations, with some geographic variability in virus pressure. The viromes of off-type and cultivated carrots were most similar, suggesting that proximity and/or management practices influence virome properties. For some aphid-borne viruses, similar isolates were found in wild and cultivated carrots, suggesting exchanges between them or with a shared source. However, isolates of other aphid-borne viruses clustered by carrot type, indicating barriers to viral fluxes that might involve differential susceptibility of populations, vector preferences, or unidentified factors. To improve virus management, we need better understanding of how specific facilitators and barriers of viral exchange can be manipulated to reduce negative viral impacts.

**Keywords:** dsRNA, high-throughput sequencing, reservoir, viral fluxes, virome

Viruses are widespread biological entities that depend on their hosts to maintain their life cycles and are often transmitted by vectors. Their role is mainly regarded as that of disease-causing agents in humans, animals, and plants. However, in wild plants, viruses are often considered asymptomatic or associated with mild or indistinct abnormalities (Cooper and Jones 2006), which may be due to a long co-evolution between host plants and viruses (Lefeuvre et al. 2019). Besides natural resistance or tolerance to pests and pathogens, a number of mechanisms are theoretically able to limit the impact of pathogens in wild plant communities, including high plant species

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<footnote n="1">¹ University of Bordeaux, INRAE, UMR BFP, CS20032, 33882, Villenave d'Ornon Cedex, France</footnote>

<footnote n="2">²Centro de Biotecnología y Genómica de Plantas (CBGP), Universidad Politécnica de Madrid (UPM) and E.T.S.I. Agronómica, Alimentaria y de Biosistemas, Campus de Montegancedo, UPM, 28223 Pozuelo de Alarcón, Madrid, Spain</footnote>

<footnote n="3">³Department of Plant Biology and Program in Ecology, Evolution & Behavior, Michigan State University, East Lansing, MI, U.S.A.</footnote>

<footnote>†Corresponding author: T. Candresse; thierry.candresse@inrae.fr</footnote>

<footnote>**Data availability:** The sequence datasets for the various carrot populations are available at https://doi.org/10.57745/42WNRJ.</footnote>

<footnote>**Funding:** This study was funded by the European Union through a Horizon 2020 Marie Skłodowska-Curie Actions Innovative Training Network (H2020 MSCA- 60 ITN) project "INEXTVIR" (GA 813542). C. M. Malmstrom was supported by Michigan State University AgBioResearch (Hatch MICL 02582) and the Michigan Vegetable Council.</footnote>

<footnote>**e-Xtra:** Supplementary material is available online.</footnote>
diversity with ensuing host dilution effects by non-host species, lower host population densities, the presence of natural predators, and parasites that may limit vector populations (Cooper and Jones 2006).

Major milestones in history, such as the domestication of wild plant species and the advent of agriculture around 10,000 years ago, or, more recently, global warming and the globalization of markets, have changed the dynamics between hosts, pathogens, and their environment (Cooper and Jones 2006; Jones 2014). These changes have likely led to more encounters between otherwise separated hosts and pathogens, facilitating virus emergence and disease epidemics (Elena et al. 2014). In modern agriculture, crops are usually part of complex agro-ecosystems and lie adjacent to natural plant communities. This so-called agro-ecological interface plays an important role in virus interactions between cultivated and wild environments (Haňcinský et al. 2020). Wild plants can serve as reservoirs for viruses that can then spread to neighboring crops, and, conversely, wild plant communities are increasingly exposed to plant viruses that can spill over from agroecosystems (Malmstrom and Alexander 2016; Roossinck and García-Arenal 2015). The way the wild and cultivated plant populations interact through such viral fluxes contributes to the shaping of viral populations.

Given their biodiversity, wild plants are likely to host a considerable proportion of plant virus diversity (Cooper and Jones 2006). In addition, host biodiversity is predicted to alter disease risk by either increasing (amplification effect) or decreasing (dilution effect) pathogen diversity and prevalence (Pagán et al. 2012). To test assumptions about the composition and structure of virus communities and of viral fluxes between wild plants and crops, it is thus important to analyze virus communities across agro-ecological interfaces.

Innovative genomic tools introduced in the twenty-first century, such as high-throughput sequencing (HTS), allow for less biased analyses of the structure of microbial communities, including viral populations, in different ecosystems and the discovery of new viruses without any prior knowledge. During the last decade, a number of studies have looked at viral diversity in natural ecosystems (Bernardo et al. 2018; Fraile et al. 2017; Mahlanza et al. 2022; Muthukumar et al. 2009; Roossinck 2011; Roossinck et al. 2010, 2015; Susi et al. 2019; Thapa et al. 2015) and at the likelihood of virus movement between wild and cultivated hosts and the potential role of wild plants as virus reservoirs (Ma et al. 2020; Maachi et al. 2022; Rivarez et al. 2023; Tugume et al. 2016). Some of these studies considered the taxonomic relatedness of either viruses or host plants and found variable influences of taxonomy on virus overlap. For example, Ma et al. (2020) reported that tomato and its wild relative *Solanum nigrum* share a relatively low proportion of operational taxonomic units (a proxy for viral taxa) and, while identifying shared viruses between these two plants, also highlighted unexplained cases where an expected sharing of viruses appeared limited. Similarly, Maachi et al. (2022) observed virome overlap exclusively between crops and weeds of the same family but also showed differentiation of some viral populations, suggesting that at least for one virus, there were few exchanges between a crop and weeds belonging to the same botanical family. Overall, intrinsic plant and virus characteristics, such as overall diversity or taxonomic relatedness, are expected to strongly influence the potential for viral exchange at the agroecological interface. As highlighted by Moury et al. (2017), phylogenetic distance between plant species is an important barrier to infection of new hosts and strongly contributes to virus host range. Similarly, Sallinen et al. (2020) showed that host genotype plays a key role in the composition of virus communities. Host genetics and ecol-

ogy thus influence virus communities and their circulation in the environment.

Previous studies also indicate that environmental factors, such as plant growth conditions and soil nutrient status, can affect pathogen community structure and disease dynamics (Susi and Laine 2021). In another example, Bernardo et al. (2018), using a landscape-scale geometagenomic approach, found higher virus prevalence in cultivated areas and preferential association of some virus families with agriculture. Likewise, for viruses circulating through the action of vectors, changes in host density or physiology can alter vector feeding behavior and population densities, leading to increased frequency of inoculum transmission and consequent disease incidence (Burdon and Chilvers 1982).

Whereas previous metagenomic studies have compared virus communities' diversity and potential transfer between host plants within genera or broader taxonomic groups (Ma et al. 2020; Maachi et al. 2022; Rivarez et al. 2023), here, we set out to compare the virome of a crop and its same-species wild relative. Cultivated carrots (*Daucus carota* subsp. *sativus*) and wild carrots (*Daucus carota* subsp. *carota*) represent a comparison with the least botanical and genetic distance between a crop and a frequent wild weed that could act as a reservoir. Thus, wild and cultivated carrots represent a particularly interesting pathosystem for the analysis of the potential for viral fluxes between the wild and cultivated plant populations or compartments at the agroecological interface because the absence of a species barrier is expected to impose fewer constraints on virus fluxes.

Carrot is the most widely cultivated crop in the Apiaceae family and grown on 1.1 million ha worldwide (FAO 2020). The history of carrot domestication is relatively short; early domestication likely occurred in southwestern Asia (Afghanistan) only about 1,100 years ago (Iorizzo et al. 2013; Rong et al. 2014). Cultivated carrots are derived from the biennial conspecific wild carrot, which is native to Europe, southwestern Asia, and North Africa and now established broadly in temperate regions worldwide (Praciak 2022). The tendency of crop plants to show increased susceptibility to pathogens relative to wild relatives is generally attributed to a loss of genetic variability resulting from the bottleneck(s) associated with domestication (Gaut et al. 2015; Gross and Olsen 2010). Indeed, recent results demonstrate a sequential reduction of genetic diversity with carrot domestication (Coe et al. 2023). In France, the Nouvelle-Aquitaine region represents the largest carrot-growing area, with 99% of the regional production area concentrated in the Gironde and Landes departments (Anonymous 2018), where carrot cultivation benefits from deep, sandy soils. At the same time, these particular local pedoclimatic conditions have the consequence that wild carrots are in many places the only Apiaceae species present.

Carrots are susceptible to a wide range of viruses, some horizontally transmitted (primarily by aphid vectors) and others vertically transmitted by seeds. In the past, more than 30 viruses from 12 different families were identified in carrots (Brunt et al. 1996; Mihara et al. 2016; Wu et al. 2022). The viral families *Tombusviridae*, *Solemoviridae*, *Closteroviridae*, *Secoviridae*, and *Potyviridae* contain well-known carrot-infecting species that are horizontally transmitted and can cause severe damage to carrot production worldwide (Adams et al. 2014; Latham and Jones 2004; Rozado-Aguirre et al. 2016; Yoshida 2020).

Carrot motley dwarf disease (CMD) is a particularly widespread and impactful disease (Stubbs 1948) caused by a mixed infection of carrot red leaf virus (CtRLV, genus *Polerovirus*, family *Solemoviridae*) with either of two umbraviruses (family *Tombusviridae*), carrot mottle virus (CMoV) or carrot mottle mimic virus (CMoMV) (Yoshida 2020). Umbraviruses are capable of replication and movement within hosts but lack a gene for the capsid protein essential
for aphid transmission; umbraviruses can thus be considered dependent viruses that rely on fully autonomous helper viruses, such as poleroviruses, for their encapsidation and vector transmission. Subviral agents that likewise depend on helper viruses may also be involved in the CMD complex; these agents include satellite RNAs (satRNAs) or tombusvirus-like associated RNAs (tlaRNAs) (Menzel et al. 2009; Yoshida 2020). Plants with CMD exhibit chlorotic mottling and yellowing of foliage and often severe stunting (Menzel et al. 2009; Stubbs 1948; Yoshida 2020). The helper and dependent CMD agents are transmitted by the willow carrot aphid (*Cavariella aegopodii*) in a persistent, non-propagative way (Stubbs 1948; Yoshida 2020). *C. aegopodii* is a heteroecious species alternating between primary woody overwintering hosts (*Salix* spp.) and secondary herbaceous Apiaceae hosts colonized during the growing season (Dunn 1965; Williams and Dixon 2007). The aphid *Myzus persicae* can also transmit the CMD agents to Apiaceae family hosts under laboratory conditions (Naseem et al. 2016).

Recently, we reported the results of a large metagenomic survey of viruses in 45 wild and cultivated French and Spanish carrot populations (Schönegger et al. 2023a). This work identified 45 viruses among these populations (of which 25 were novel) and allowed us to assemble nearly complete genomic contigs for most of the newly discovered viruses. Although not delving into this aspect in detail, this work also provided the first indications of differential associations of some of the identified viruses with either cultivated or wild carrot populations (Schönegger et al. 2023a). Here, we build on this virus discovery effort to examine in-depth viral associations within and among host populations, focusing on a subset of the French sampling sites (Nouvelle-Aquitaine region) where cultivated and wild carrots grow in sympatry near each other. For these sites, we analyzed the previously produced HTS data within a community context to explore relationships among viruses and virus-like agents. To complement this, the prevalence and diversity of 16 aphid-borne viruses were assessed using virus-specific RT-PCR assays or HTS analyses on single plants of, respectively, eight and two of the Nouvelle-Aquitaine carrot populations. Taken together, this work enables a holistic virome analysis at the agro-ecological interface and provides insight into virus circulation between sympatric populations of a crop and its wild relative.

Based on previous reports from wild- agricultural comparisons, we expected to find lower viral species richness and greater virus prevalence in cultivated carrots than in their wild relatives. Specifically, we asked the following questions: (i) How similar are virus species richness, virus prevalence, and the species composition of viral communities found in cultivated and wild carrots growing near each other? (ii) Does phylogenetic analysis suggest exchange

or separation of viral isolates between wild and cultivated carrots?
(iii) Are co-occurrence patterns of aphid-borne viruses and dependent viruses and virus-like agents consistent with the known helper/dependency relationships linking them?

Materials and Methods

Overview of the study design

This study focuses on and expands the analysis of 31 of the 45 French and Spanish carrot populations evaluated in an initial virome discovery effort (Schönegger et al. 2023a). These 31 populations were sampled within a radius of approximately 50 km in the Landes and Gironde departments of Nouvelle-Aquitaine (France) over 2019 and 2020. They were selected for the present study to allow for a direct comparison of the virome of cultivated and wild carrots growing in sympatry near each other (Fig. 1; Supplementary Table S1). The carrot populations analyzed in this study were sampled at the end of July, providing time for the spring aphid flights to introduce the virus inoculum into carrot populations and for further local spread by wingless aphids. To capture any potential asymptomatic infections and to permit estimates of viral prevalence, carrot plants were sampled regardless of the presence of viral symptoms; however, plants with evident fungal infection or necrosis were excluded to avoid over-representation of fungifying viruses and because such damaged tissue is less likely to sequence well (see Schönegger et al. 2023a for details). The HTS sequencing data (https://doi.org/10.57745/42WNRJ) generated by Schönegger et al. (2023a) on 50-plant pools, each representing one carrot population sampled at a given site, were used here to contrast their viromes through detailed clustering and network analyses. Stored samples of individual plants of eight of these populations were analyzed here by HTS and/or specific RT-PCR assays to generate information on the prevalence, diversity, and co-occurrence of individual viruses and virus-like agents.

The sampling strategy of Schönegger et al. (2023a) reflected agricultural practices and grower permission for access. In the Nouvelle-Aquitaine region of France, carrots are grown as an annual crop with long (>10 year) rotations to limit the impact of soilborne pathogens and pests, so multiyear sampling of any single cultivated plot was not feasible. Because they are native to the area, wild carrot populations are locally relatively widespread in undisturbed land and roadsides. When possible, wild carrots were sampled in the immediate vicinity of a sampled plot and, if not available, were sampled as close as possible to a sampled crop, usually within kilometric distances. The geographic position of the various sampling sites is shown in Figure 1, and the characteristics of all

<figure><img src="image_13.png" /><figcaption>Fig. 1. Locations of carrot sampling sites (coded by small letters) within the two departments of Gironde and Landes of the Nouvelle-Aquitaine region of France. Red crosses indicate the presence of farm (cultivated and off-type) carrot populations at a location and green circles that of wild carrot populations. Colored ellipses indicate the four geographic clusters of sampling sites (South [S], Southeast [SE], Villenave d'Ornon [V], and West [W]).</figcaption></figure>
sampled carrot populations are provided in Supplementary Table S1. Sampling sites were regrouped in the present study into four geographic clusters: South (S), Southeast (SE), Villenave d'Ornon (V), and West (W) (Fig. 1; Supplementary Table S1).

In one sampling site, a specific effort was made to separately sample cultivated carrots growing at the periphery of the plot from those growing at the center (populations 20_2 and 20_3, respectively; Supplementary Table S1).

Besides the carrot crops, a low proportion of so-called “off-type” carrots also grow within cultivated plots. These plants show some phenotypic characteristics of wild carrots (early bolting, small, often white tap root), suggesting they originate from contamination of commercial seed lots. When they were present in a cultivated plot, off-type carrots were sampled alongside cultivated carrots, considering them a separate population type at that site. Throughout, we use the term “farm carrots” to collectively refer to cultivated and off-type carrots.

## Double-stranded RNA-based HTS analysis of individual plants

To validate the quality of virome description using pooled samples, in the case of two populations sampled in 2019 (one wild and one cultivated, populations 19_7 and 19_9, respectively; Supplementary Table S1), double-stranded RNAs (dsRNAs) were independently extracted from stored leaves of the 50 individual plants that had contributed to the pool sequenced by Schönegger et al. (2023a) following the procedure of Marais et al. (2018). In parallel, a negative extraction control was similarly prepared using only buffer. For each sample, purified dsRNAs were converted to cDNA and randomly amplified while simultaneously adding different MID tags by RT-PCR (François et al. 2018; Marais et al. 2018). Amplification products were purified using the MinElute PCR Purification Kit (Qiagen SAS France, Courtaboeuf, France) and their concentration determined spectrophotometrically. Equal amounts (3 µg) of amplification products from each sample were sequenced (2 × 150 bp) at the GetPlaGe platform (GenoToul INRAE, Toulouse, France) on an Illumina NovaSeq 6000 system. Viral contigs obtained from the HTS data generated from these individual plants were also used, together with PCR amplicons (see below), for the analysis of the genetic diversity of aphid-transmitted viruses.

## Bioinformatic analysis of HTS data from individual plants

Demultiplexing, quality trimming, reads mapping, de novo assembly, and contig annotation were performed as described by Schönegger et al. (2023a). Briefly, raw sequencing reads were imported into CLC Genomics Workbench (CLC-GW version 21.0.3), demultiplexed, and trimmed on quality to a minimum read length of 60 nucleotides (nt), using default settings. Reads were mapped against a set of reference viral genomic sequences from GenBank (for known viruses) and of near-complete or partial genome sequences for novel agents (Schönegger et al. 2023a). Supplementary Table S2 lists the reference sequences used, along with taxonomic information and relevant GenBank accession numbers. Contigs assembled de novo from individual plants for viruses of interest were identified by local Blast searches in CLC-GW.

## Prevalence of aphid-transmitted viruses in farm and wild carrots

We estimated the prevalences of 16 aphid-transmitted viruses (poleroviruses, enamoviruses, umbraviruses) and associated subviral agents (tlaRNAs, satRNAs), including the central known helper virus of CMD (CtRLV) and associated dependent agents (CMoV, CMoMV, CtRLVaRNA, CMoV-satRNA) and newly discovered congeners. For this analysis, total RNAs were extracted from individual plants from eight carrot populations (two cultivated, one off-type, and five wild populations: 19_1, 19_2, 19_7, 19_6, 19_9, 19_12, 19_13, and 19_14; Fig. 2; Supplementary Table S1). Populations were selected randomly within each population type and represent half of the populations sampled in 2019 by Schönegger et al. (2023a). Preponderance was given to wild populations to support an analysis of virus co-occurrence because virus prevalence in farm populations was too high to give meaningful results. Briefly 10 mg of dried plant material was transferred to a 2-ml Eppendorf tube containing a steel bead. The tubes and contents were frozen at -80°C for 1 h or longer before being shaken on a horizontal shaker (Retsch MM301, Haan, Germany) for 1 to 2 min at a frequency of 30 Hz, until a fine powder was obtained. Total RNA was then purified using the NucleoSpin 96 RNA extraction kit (Macherey-Nagel, Hœrdt, France) following the manufacturer's instructions.

<table><thead><tr><th rowspan="2">Geo-Cluster</th><th colspan="2">South (S)</th><th colspan="2">South-east (SE)</th><th colspan="2">Villenave (V)</th><th colspan="2">West (W)</th><th colspan="3">Aggregate</th></tr><tr><th>B</th><th>B</th><th>F</th><th>H</th><th>E</th><th>M</th><th>G</th><th>L</th><th>Mean_All</th><th>Mean_Farm</th><th>Mean_Wild</th></tr><tr><th>Sampling site</th><th>Off-type</th><th>Cultivated</th><th>Cultivated</th><th>Wild</th><th>Wild</th><th>Wild</th><th>Wild</th><th>Wild</th><th>n = 8 pops</th><th>n = 3 pops</th><th>n = 5 pops</th></tr></thead><tbody><tr><td>Type</td><td>19_2</td><td>19_1</td><td>19_7</td><td>19_9</td><td>19_12</td><td>19_13</td><td>19_14</td><td>19_6</td><td></td><td></td><td></td></tr><tr><td>Population</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>N plants sampled</td><td>39</td><td>50</td><td>49</td><td>50</td><td>50</td><td>44</td><td>44</td><td>50</td><td>53.1</td><td>100.0</td><td>25.0</td></tr><tr><td>Known</td><td>CtRLV (Polerovirus)</td><td>100</td><td>100</td><td>100</td><td>24</td><td>20</td><td>14</td><td>25</td><td>42</td><td></td><td></td><td></td></tr><tr><td>Known</td><td>CMoV (Umbravirus)</td><td>100</td><td>100</td><td>80</td><td>16</td><td>18</td><td>20</td><td>20</td><td>64</td><td>52.3</td><td>93.3</td><td>27.6</td></tr><tr><td>Known</td><td>CtRLVaRNA (tlaRNA)</td><td>100</td><td>98</td><td>86</td><td>16</td><td>22</td><td>27</td><td>9</td><td>54</td><td>51.5</td><td>94.7</td><td>25.6</td></tr><tr><td>Known</td><td>CMoV-satRNA (sat RNA)</td><td>95</td><td>96</td><td>33</td><td>18</td><td>40</td><td>16</td><td>23</td><td>32</td><td>44.1</td><td>74.7</td><td>25.8</td></tr><tr><td>Known</td><td>WCMoV (Umbravirus)</td><td>77</td><td>88</td><td>20</td><td>14</td><td>20</td><td>23</td><td>36</td><td>34</td><td>39.0</td><td>61.7</td><td>25.4</td></tr><tr><td>Known</td><td>ALVEaRNA (tlaRNA)</td><td>95</td><td>98</td><td>29</td><td>2</td><td>0</td><td>0</td><td>0</td><td>10</td><td>29.3</td><td>74.0</td><td>2.4</td></tr><tr><td>Known</td><td>CMoMV (Umbravirus)</td><td>56</td><td>70</td><td>10</td><td>10</td><td>16</td><td>23</td><td>9</td><td>30</td><td>28.0</td><td>45.3</td><td>17.6</td></tr><tr><td>Novel</td><td>CaUV2 (Umbravirus)</td><td>0</td><td>2</td><td>2</td><td>4</td><td>14</td><td>14</td><td>7</td><td>18</td><td>7.6</td><td>1.3</td><td>11.4</td></tr><tr><td>Novel</td><td>CaEV1 (Enamovirus)</td><td>0</td><td>0</td><td>4</td><td>6</td><td>4</td><td>14</td><td>9</td><td>14</td><td>6.4</td><td>1.3</td><td>9.4</td></tr><tr><td>Novel</td><td>CaPV1 (Polerovirus)</td><td>0</td><td>0</td><td>0</td><td>6</td><td>6</td><td>16</td><td>20</td><td>0</td><td>6.0</td><td>0.0</td><td>9.6</td></tr><tr><td>Novel</td><td>CMoVsatRNA2 (sat RNA)</td><td>0</td><td>2</td><td>0</td><td>2</td><td>10</td><td>5</td><td>5</td><td>20</td><td>5.5</td><td>0.7</td><td>8.4</td></tr><tr><td>Novel</td><td>CtRLVaRNA2 (tlaRNA)</td><td>3</td><td>0</td><td>0</td><td>2</td><td>0</td><td>14</td><td>11</td><td>2</td><td>4.0</td><td>1.0</td><td>5.8</td></tr><tr><td>Novel</td><td>CaUV1 (Umbravirus)</td><td>3</td><td>12</td><td>12</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>3.4</td><td>9.0</td><td>0.0</td></tr><tr><td>Novel</td><td>CaUV3 (Umbravirus)</td><td>0</td><td>0</td><td>0</td><td>2</td><td>8</td><td>0</td><td>5</td><td>0</td><td>1.9</td><td>0.0</td><td>3.0</td></tr><tr><td>Known</td><td>BWYVaRNA (tlaRNA)</td><td>3</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.4</td><td>1.0</td><td>0.0</td></tr><tr><td>Novel</td><td>CaPV2 (Polerovirus)</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.3</td><td>0.7</td><td>0.0</td></tr></tbody></table>

**Fig. 2.** Prevalence (%) of known and novel aphid-borne viruses and virus-like agents in a subset of eight wild and farm carrot populations sampled in 2019. Taxa are ordered from most prevalent (red) to least prevalent (blue) as determined by analysis-wide mean prevalences (Mean_All). Prevalence is determined by taxa-specific RT-PCR testing of individual plants. For each population, the number of plants tested is indicated, together with its geographic cluster, sampling site, population type, and population code (see Supplementary Table S1). On the right, mean prevalence values are given for all tested populations (pops) (Mean_All), farm populations alone (cultivated and off-type, Mean_Farm), and wild populations alone (Mean_Wild). Virus acronyms follow Supplementary Table S2 and are categorized by colored font following the color scheme in Figure 6: helper poleroviruses and enamoviruses (pink), dependent umbraviruses (blue), and associated or satellite RNAs (green).
Primer pairs targeting aphid-borne viruses involved in assistance/dependency relationships were designed manually from sequence alignments (Supplementary Table S3). For some *Solemoviridae* and *Tombusviridae* viruses and for satRNAs, previously developed primer pairs (Babalola et al. 2022; Schönegger et al. 2022) were used. These primers target conserved sequences that allow for discrimination of closely related viruses, thus ensuring both inclusiveness (ability to detect all isolates of a virus) and specificity (ability to only amplify isolates of the target virus). RT-PCR amplifications were performed according to Marais et al. (2012) with PCR cycling conditions as follows: 40 cycles each at 95°C for 30 s, virus-specific annealing temperature (Supplementary Table S3) for 30 s, and 72°C for 30 s.

Total RNA from individual plants was analyzed by RT-PCR in 96-well PCR plates and amplicons visualized following 1.2% nondenaturing agarose gel electrophoresis. To confirm the specificity of the PCR assays and for subsequent sequence analysis of viral diversity, up to 39 positive amplicons per virus and population were Sanger sequenced (Eurofins Genomics, Ebersberg, Germany).

## Dual strategy to limit errors from read cross-talk

A frequent problem in viral metagenomic studies is cross-talk or “bleeding” of reads among samples, which can result from experimental contamination, as well as from low-level index hopping during Illumina sequencing (Illumina 2017; van der Valk et al. 2020). To limit this problem, we used a dual strategy to determine individual reliable positivity thresholds for mapped reads of each virus. This approach was conservative and took into account read numbers in negative and buffer-only controls, as well as comparison of HTS read numbers with RT-PCR results from testing of a large number of individual plants. This strategy limited false-positive detections to a very low probability, thus notably reducing the chances of incorrectly reporting any artifactual virus traces as actual detections.

## Virus species richness and virome composition

To evaluate virus species richness, we calculated the number of verified viral species detections per population and tested the significance of differences in means between cultivated, off-type, and wild populations with two-sided *t* tests (confidence level 95%) after confirming normality and variance homogeneity with Shapiro-Wilk and F-tests.

To compare the virus species compositions (virome compositions) of carrot populations, we used hierarchical clustering (R package ‘stats’). Briefly, after conducting z-score-based scaling of mapped read numbers from normalized datasets, we generated a dissimilarity matrix with nonparametric Spearman rank correlation and with complete linkage as the agglomerative clustering method. We visualized the clustering with the heatmap.2 function implemented in the ‘ggplot’ package.

To examine viral links among populations, we constructed, evaluated, and visualized bipartite networks with the ORA-LITE network analysis software (2022, version 3.0.9.9.142, CASOS Center, Carnegie Mellon University, Pittsburgh, PA, U.S.A.; https://www.cmu.edu/casos-center/research/tools/ora-lite.html). We used an agent × location structure, with edge width set to represent read number. One set of nodes represented different virus taxa (n = 36) and the second set of nodes the host carrot populations (n = 31).

## Co-occurrence of aphid-transmitted viruses and virus-like agents in wild carrot populations

To evaluate the co-occurrence of aphid-transmitted helper and dependent viruses, we implemented a probabilistic and distribution-free model based on combinatorics implemented in the R package ‘cooccur’ (Griffith et al. 2016).

The algorithm compares the probabilities that observed frequencies of co-occurrence are significantly higher than, lower than, or equal to the frequencies expected by random and then deduces positive, negative, or random associations between pairs of viruses (Veech 2013). We used this approach to evaluate non-random virus associations from presence/absence data obtained by RT-PCR detection of aphid-transmitted viruses in individual plants from five wild carrot populations (see above). This analysis was conducted with wild populations because virus infection was so widespread in cultivated populations that co-occurrence analysis would have been statistically ineffective.

## Sequence comparison and phylogenetic analyses

We used ClustalW as implemented in MEGA 7 (Kumar et al. 2018) to align contigs obtained from individual plants, RT-PCR viral amplicon sequences from individual plants, and GenBank reference sequences. Maximum likelihood phylogenetic trees were inferred from alignments using nucleotide identities calculated in MEGA 7. The support of branches was estimated with 1,000 bootstrap replicates.

# Results

## Viruses detected in farm and wild carrots

We evaluated virus distributions in 31 carrot populations sampled over 2019 and 2020 in the Gironde and Landes departments (Nouvelle-Aquitaine, France), including 11 cultivated, 7 off-type, and 13 wild populations. To allow for the analysis of potential local scale effects, sampling sites were regrouped into four geographic clusters, S, SE, V, and W (Fig. 1; Supplementary Table S1). Throughout what follows, the term “farm carrots” is used to collectively refer to cultivated and off-type carrots growing side by side in cultivated plots. For all populations, we examined the datasets generated by a dsRNA-based metagenomic approach as part of a large virus discovery effort (Schönegger et al. 2023a). These datasets contained on average 41% of viral reads (range 1 to 80%).

The focal Nouvelle-Aquitaine populations contained a rich virome of 36 viruses and subviral agents (Supplementary Table S2) out of the 45 viruses and satellites identified in the broader virome study of Schönegger et al. (2023a). For these analyses, CMoV satRNA (CMoVsatRNA) and CMOMV satRNA (CMoMVsatRNA) were considered as a single species due to their high nucleotide identity (93%) and possible cross-mapping of reads between them. Half (18) of the Nouvelle-Aquitaine viruses were already known and belong to seven genera in seven families (*Solemoviridae*, *Tombusviridae*, *Betaflexiviridae*, *Secoviridae*, *Closteroviridae*, *Bromoviridae*, and *Partitiviridae*) or represent unclassified *Riboviria* or subviral agents (Supplementary Table S2). The remaining 18 viruses are novel and belong to the same families as the known viruses (*Betaflexiviridae*, *Closteroviridae*, *Partitiviridae*, *Solemoviridae*, and *Tombusviridae*), as well as to the *Totiviridae* and *Amalgaviridae* families. Also included are two putative novel *Riboviria* and four subviral agents, two of which are circular hammerhead satellites recently described by Babalola et al. (2022) and one a tlaRNA described by Schönegger et al. (2022) (Supplementary Table S2). Of the virus families represented, the majority are generally transmitted horizontally by vectors, whereas *Amalgaviridae* and *Partitiviridae* are vertically transmitted; *Totiviridae* generally infect fungi. Overall, the virome was relatively stable between years, with 81% of the viruses detected in both years and the differences between the two sampling years involving only rare viruses detected in a single carrot population.
## Shared core virome of farm and wild Nouvelle-Aquitaine carrot populations

About half of carrot-associated viral taxa in Nouvelle-Aquitaine (47%, 17 viruses) are shared among all three carrot population types (Fig. 3; Supplementary Table S4). This core virome includes mostly aphid-transmitted viruses, such as members of the families *Solemoviridae* and *Tombusviridae* and dependent satellite and associated RNAs, as well as carrot torradovirus 1 (*Secoviridae*). All three population types also share seedborne viruses of the family *Partitiviridae*, including a divergent isolate of dill cryptic virus 2 and carrot cryptic virus. A detailed list of the viruses and their presence in the different carrot population types are shown in Figure 3, with the corresponding number of infected populations in both years given in Supplementary Table S4. Of note, the frequency of any single shared virus sometimes varied significantly among carrot population types. For example, the seedborne carrot cryptic virus was common in farm populations (82 and 86% of the cultivated and off-type populations, respectively) but was found in only 1 of the 13 analyzed wild populations (8%).

## Differentiation of the virome of farm and wild carrot populations

Of the 36 viral taxa identified in Nouvelle-Aquitaine carrot populations, 89% (32 taxa) were found in one or more farm populations (27 taxa in cultivated carrots, 26 in off-type ones), and 69% (25 taxa) were detected in one or more wild carrot populations (Fig. 3). Four viruses (11%) were uniquely shared among farm carrots (cultivated and off-type) and not found in wild carrots and belong to the genera *Closterovirus* and *Chordovirus* and also include a tlaRNA, beet western yellows-associated RNA, and a new unclassified virus with homologies with members of the *Benyviridae* family, carrot-associated RNA virus 1 (CaRNAV1; Fox et al. 2022). Eight additional viruses (22%) were unique to one type of farm carrot

(cultivated or off-type) and not found in wild carrots. Another four viral agents (11%) were found exclusively in wild carrots: a known polerovirus (wild carrot red leaf virus), a novel polerovirus (carrot polerovirus 1, CaPV1; Schönegger et al. 2023a), a new tlaRNA (carrot red leaf virus-associated RNA 2, CtRLVaRNA2; Schönegger et al. 2022) and an ilarvirus reported here for the first time in carrots (solanum nigrum ilarvirus 1; Ma et al. 2020).

As predicted, viral species richness, defined as the number of virus species detected within an individual carrot population, was significantly greater in wild carrot populations than in cultivated ones (15.5 ± 2.4 viruses compared with 12.2 ± 2.6, *P* = 0.004 in a two-sided *t* test). Off-type carrot populations exhibited an intermediate richness (14 ± 1.8 viruses), not statistically different from either cultivated or wild carrot populations. We further compared the species richness differences between wild and cultivated populations with the V geographic cluster omitted because it contains only wild populations might thus inflate their richness estimate. However, the difference in species richness among wild and cultivated populations remained significant (*P* = 0.01), thus ruling out a potential effect linked to the geographical clustering of sampling sites.

Hierarchical clustering, weighted and scaled by the number of mapped reads, distinguished between wild and farm populations (Fig. 4), with off-type and cultivated populations clustering together, reflecting similarities in virome structures. Clustering was not notably influenced by sampling year, but some geographic clustering was evident, as for four 2019 wild populations of the V geographic cluster (Fig. 4). In addition, in several cases, cultivated and off-type populations from the same sampling site tightly clustered together, indicating evidence of significant local effects on the virome structure. This includes, for example, populations 20-1 and 20-5 (at sampling site P), populations 20-3 and 20-4 (site P), and populations 19-4 and 19-5 (site I) (Fig. 4).

<figure><img src="image_14.png" /><figcaption>**Fig. 3.** Venn diagram showing the number and corresponding percentages of viruses and virus-like agents detected in 31 cultivated, off-type, or wild carrot populations by the high-throughput sequencing effort of Schönegger et al. (2023a) in Nouvelle-Aquitaine (France) and analyzed further here. The identity of the viruses and virus-like agents in each part of the diagram is given in the associated boxes. The aphid-borne viruses and virus-like agents analyzed individually by RT-PCR testing in this study are indicated in bold.</figcaption></figure>
## Bipartite network analysis confirms contrasting viromes between wild and farm carrot populations

Consistent with the hierarchical clustering analysis, the bipartite network analysis shows a clear division of carrot populations by type (Fig. 5). The farm carrot populations (triangles) are associated with each other in the upper left of the network, with no particular grouping according to population type (cultivated or off-type) or to geographic cluster, whereas the wild populations (squares) are located together in the lower right, with a regrouping of populations from geographic cluster V (Fig. 5). This pattern confirms the differentiation of the viromes between wild and farm carrot populations seen in the hierarchical clustering analysis. In a few cases, a proximity is observed between wild and farm populations. In particular, a cultivated population (20_2; Supplementary Table S1) that was sampled on the outer border of a cultivated plot directly adjacent to wild population, 20_6 (Supplementary Table S1), is relatively close to the latter and to wild population 20_10, which was sampled in a different site in the same W geographic cluster (Fig. 5). In fact, all cases of closeness in the network of farm populations to wild populations involve sampling sites of the W geographic cluster.

Taking a closer look at virome composition, the 20_2 population was the only cultivated population in 2020 in which the novel viruses CaEV1 and CtFLV1 were identified (they were also identified in the adjacent wild 20_6 population). Contigs of umbraviruses shared between the two populations (two novel viruses, CaUV2 and CaUV3, and the well-known CMoV) were compared in multiple

alignments. CaUV2 and CMoV contigs showed 100% nucleotide identity in overlap regions of 1,063 and 300 nt, respectively, whereas CaUV3 contigs showed a single-nucleotide polymorphism over a 1,252-nt shared region, reinforcing the notion of the closeness of the viromes of these two carrot populations.

The network groups known aphid-transmitted viruses or associated RNAs/satellites that are highly connected (identified in all or most populations) in the center of the graph. Among these are CtRLV, CMoV, CMoV-satRNA, CMoMV, CtRLVaRNA, and wild carrot mottle virus (WCMoV), all of which are key members of the CMD disease complex. Although a few aphid-transmitted new viruses also occupy a relatively central position (CaUV2, CaUV3, CaEV1, and CMoVsatRNA2), the majority of new viruses are found on the outside of the network, positioned close to wild populations on the right of the network. Other viruses that cluster in the center of the network are preferentially linked either to wild populations (e.g., CaUV2, CaUV3, CaEV1, and CMoVsatRNA2; Supplementary Table S4) or to cultivated/off-type populations (e.g., carrot torradovirus 1, CaUV1, and ALVEaRNA; Supplementary Table S4). Viruses that are less connected (rare viruses) and those that are specific for wild or farm populations, such as CaPV1 or wild carrot red leaf virus for wild populations and members of the genera *Clositerovirus* and *Chordovirus* for cultivated populations, are found at the periphery of the network (Fig. 5; Supplementary Table S4). Overall, the network analysis complements and confirms the results obtained by hierarchical clustering. In particular, it shows no

<figure><img src="image_15.png" /><figcaption>**Fig. 4.** Heatmap showing the number of reads mapped for each reference viral genome (in rows indicated by acronyms on the right, see Supplementary Table S2) and the corresponding hierarchical clustering dendrogram of viromes from all 31 farm (red branches) and wild (green branches) carrot populations sampled in 2019 and 2020. The high-throughput sequencing data used are from Schönegger et al. (2023a). Matrix cells are colored by number of reads, following the Z-score scale (upper left). The individual carrot populations (columns) are coded following Supplementary Table S1. Geographic clusters (South [S], Southeast [SE], Villenave d'Ornon [V], and West [W]) are indicated in color above the sampling site letter and the population code names, with the code prefix indicating the sampling year (2019 or 2020) and the suffix indicating the type of population: c = cultivated; cb = cultivated at the border of a field; cc = cultivated at the center of a field; off = off-type carrots within fields; w = wild population.</figcaption></figure>
clear grouping by year of sampling and only limited grouping by geographical sampling cluster as discussed above.

## Prevalence of aphid-transmitted viruses in individual farm and wild carrot populations

To evaluate the prevalence and diversity of aphid-transmitted viruses and support phylogenetic analysis of intraspecies relationships, a total of 376 individual plants from eight 2019 populations (two cultivated, one off-type, and five wild populations: 19_1, 19_2, 19_7, 19_6, 19_9, 19_12, 19_13, and 19_14; Fig. 2; Supplementary Table S1) were screened by RT-PCR for the presence of 16 viruses and subviral agents, including CtRLV, CaPV1, CaPV2, CaEV1 CMoV, CMoMV, WCMoV, CaUV1, CaUV2, CaUV3, CtRLVaRNA, CtRLVaRNA2, ALVEaRNA, beet western yellows-associated RNA, CMoVsatRNA, and CtMoVsatRNA2.

Overall, the RT-PCR analyses revealed that known aphid-borne viruses and subviral agents were more prevalent in cultivated carrots, whereas novel viruses were more prevalent in wild carrots (Fig. 2). With the exception of beet western yellows-associated RNA, which was detected in a single plant of a single population, all other tested known aphid-borne viruses were generally more prevalent in farm populations than in wild ones. The most prevalent virus—the well-known polerovirus CtRLV—was detected in

100% of cultivated and off-type plants but only in 14 to 42% of individuals in wild populations. Known umbraviruses were likewise more prevalent in farm populations than in wild ones. For CMoV, prevalences were 80 to 100% (farm) versus 16 to 64% (wild); for CMoMV, 10 to 70% versus 9 to 30%; and for WCMoV, 20 to 88% versus 14 to 36% (Fig. 2). Known associated RNAs and satellites were similarly more prevalent in farm populations with prevalences of 86 to 100% (farm) versus 9 to 54% (wild) for CtRLVaRNA; 29 to 98% versus 0 to 10% for ALVEaRNA; and 33 to 96% versus 16 to 40% for CMoVsatRNA (Fig. 2).

However, the converse pattern was evident for nearly all novel aphid-borne viruses examined: The prevalence of these novel taxa was generally greater in wild carrot populations, and they were largely absent or rare in farm populations (Fig. 2). The exception was the novel umbravirus CaUV1, which was not detected in wild carrots and showed a prevalence of 12% in cultivated carrots and 3% in the single analyzed off-type population (Fig. 2).

## Co-occurrence of aphid-transmitted viruses and virus-like agents in wild carrot populations

We further analyzed the RT-PCR detection data for evidence of statistically supported co-occurrence associations, as might be expected to occur for carrot disease complexes such as CMD that in-

<figure><img src="image_16.png" /><figcaption>**Fig. 5.** Bipartite network depicting relationships between viruses and host populations based on the reads mapping matrix. Individual viral taxa (n = 36) are represented by hexagons (yellow: known viruses; red: new viruses), and carrot populations (n = 31) are represented by squares (wild carrots) or triangles (farm carrots). Carrot populations are colored by geographic cluster (legend on left). The inset (upper right) shows a close-up of the viral agents at the network center. Code names of viral taxa and host populations are the same as in Figure 4 and are based on Supplementary Tables S1 and S2. Edge width reflects read numbers.</figcaption></figure>
volve a *Solemoviridae* helper virus with dependent umbraviruses, tlaRNA, and/or satRNA. The analysis focused on virus occurrences within five wild populations (19_7, 19_6, 19_9, 19_12, 19_13, and 19_14; Supplementary Table S1) because prevalences within the farm populations (very high or very low) were not conducive to it. The analysis revealed 25 positive non-random co-occurrence associations (Fig. 6; Supplementary Table S5). No statistically supported negative associations were identified.

The most frequent positive co-occurrences were observed between members of the *Umbravirus* genus (20%, 5/25) and between associated subviral agents and umbraviruses (52%, 13/25) (Fig. 6). Only 24% (6/25) of positive co-occurrences were between *Solemoviridae* helper viruses and dependent *Tombusviridae* members (Fig. 6). Two positive co-occurrences (8%) were found between helper viruses and associated satellites, which in both cases are novel: CaPV1 and CaEV1 (helper viruses) positively co-occurred with CtRLVaRNA2 and CMoV-satRNA2 (dependent agents), respectively. A single positive co-occurrence between two helper viruses, CaPV1 and CaEV1, was also observed. The limited number of positive associations identified for the *Solemoviridae* helper viruses could suggest the existence of significant specificity. However, the fact that some expected associations were not identified, such as for CtRLV, which is known to be able to assist CMoV, CMoMV, CMoVsatRNA, and CtRLVaRNA but for which only a positive association with CMoV was observed, suggests an alternative hypothesis of promiscuity of many umbraviruses and satellites that could be assisted by several different helper viruses (Schönegger et al. 2022).

<figure><img src="image_17.png" /><figcaption>**Fig. 6.** Diagram showing statistically supported co-occurrence associations between pairs of aphid-transmitted viruses or viral agents identified in the carrot virome. Associations are color coded as follows: positive, light blue; random, gray. Helper viruses of the *Solemoviridae* family are indicated in pink, dependent umbraviruses in blue, and dependent subviral agents in green. An asterisk indicates novel viruses, and the red box highlights all positive associations observed between helper and dependent viruses and virus-like agents. P values indicating the statistical significance of non-random associations are given in the cells. An asterisk indicates novel viruses, and the red box highlights all positive associations observed between helper viruses and dependent viruses or virus-like agents.</figcaption></figure>

## Phylogenetic analysis of aphid-transmitted viruses and virus-like agents

The sequences of RT-PCR amplicons and HTS contigs obtained for the 16 aphid-transmitted viruses from individually analyzed plants were used to generate multiple alignments for each virus, consisting of up to 66 sequences. GenBank reference sequences were also included in these alignments in the case of known agents. These alignments were used to reconstruct maximum likelihood phylogenetic trees.

Populations of novel aphid-transmitted viruses (including CaUV1, CaUV2, CaUV3, CaPV1, CaPV2, CaEV1, CtRLVaRNA2, and CMoVsat2) mainly present in wild carrots and with an overall low prevalence (Fig. 2) did not show genetic differentiation between different carrot populations according to phylogenetic analyses (Supplementary Fig. S1). Similarly, there was no differentiation between populations of most known aphid-transmitted viruses (Supplementary Fig. S2). However, besides the main clades that group WCMoV and CtRLV isolates from different carrot population types, the phylogenetic analysis revealed for both viruses separate clades specific to farm (WCMoV) or to wild carrots (CtRLV) (Fig. 7A and B). On the other hand, an analysis of the isolates involved in these clades showed that three out of four (WCMoV; Fig. 7A) or all four clades (CtRLV; Fig. 7B) regroup isolates coming from populations corresponding to different geographic clusters (Fig. 7A and B), indicating that these clades do not merely reflect local sampling effects.

## Discussion

This study is among the first to evaluate field-collected virome data for evidence of viral exchange among a crop and its wild relative growing sympatrically in its native range. This work provides fundamental information that can undergird development of strategies to manage viral exchanges in complex agro-ecological landscapes. To address viral disease threats to crops, it is increasingly recognized that viral dynamics are best investigated with an integrated ecological approach that considers multiple vegetation types within a landscape, not just crops. Because viral biodiversity is vast and much is not yet catalogued, much virus ecology work is thus conducted with two simultaneous goals: (i) to develop baseline information about known and novel viral species within key vegetation components, both cultivated and wild, and (ii) to investigate specific ecological questions about the dynamics of these viruses within the study system. The study presented here deepens the initial description of the virome of cultivated and wild carrots in France and uses phylogenetic and related approaches to show that despite geographic and genetic similarity between cultivated and wild relative hosts, some elements of their viromes remain differentiated. Put in an agricultural context, these findings highlight the value of identifying what specific environmental barriers might limit viral exchanges among crops and their wild relatives for future virus management.

## Effectiveness of pooling samples for sequencing

The virome analyses reported here included a reanalysis of HTS datasets generated by Schönegger et al. (2023a) from pools of 50 plants for each sampled carrot population, complemented by additional new analysis of preserved samples. The pooled sampling strategy allows for capturing a large fraction of the virome, including viruses present at a low prevalence in the sampled carrot populations. Indeed, HTS of all individual plants from a wild (19_9) and a cultivated population (19_7; Supplementary Table S1) showed that 94% of the viruses identified by single-plant analyses had been identified by the analysis of the pools containing these plants, giving
<figure><img src="image_18.png" /><figcaption>**Fig. 7.** Maximum likelihood phylogenetic trees reconstructed from nucleotide sequence alignments of RT-PCR amplicons and high-throughput sequencing contigs from individual plants for A, WCMoV and B, carrot red leaf virus (CTRLV). For WCMoV, the amplicons are 499 nt long and cover part of the virus coat protein/movement protein coding region, whereas for CTRLV, they are 263 nt long and represent part of the P1 gene. Colors indicate the type of carrot population from which isolates were identified: red, cultivated; orange, off-type; and blue, wild. Isolate names are coded as follows: population type / population code / geo cluster / sampling site / isolate number. Only bootstrap values higher than 70% are indicated, and bootstrap supported clades are identified. Different sampling sites are indicated by different shapes. Reference sequences, including outgroups, are indicated by black diamonds. On the right of the trees, the proportion of isolates coming from particular carrot population types is provided for each clade with indications to their geographic cluster.</figcaption></figure>
confidence in the completeness of the virome descriptions achieved. However, one limitation of the dsRNA approach used is its inferior performance when it comes to the detection of DNA viruses (Schönegger et al. 2023b).

## Greater virus species richness in wild carrot populations

Wild plants are frequently infected with viruses and commonly harbor new viruses (Bernardo et al. 2018; Ma et al. 2020; Melcher et al. 2008; Muthukumar et al. 2009; Rivarez et al. 2023; Roossinck et al. 2010; Thapa et al. 2015). Consistent with our prediction, we found the species richness of RNA viruses and associated subviral agents to be about 27% greater in wild carrot populations than in cultivated ones (15.5 ± 2.4 versus 12.2 ± 2.6). This difference was still significant when we omitted the V geographic cluster that included no farm populations, thus excluding a potential artifact linked to the geographic clustering of samples. To our knowledge, this work is among the first in-depth comparisons of the viromes of sympatric populations of a crop and its conspecific wild relative, although wild crop relatives are of great interest for crop improvement (Tirnaz et al. 2022). Previous work identified viruses in maize and its teosinte wild relative in Mexico but did not compare virus species richness among population types (Lappe et al. 2022). Other works involved more phylogenetically distant comparisons, with variable findings. For example, Ma et al. (2020) found greater viral operational taxonomic unit richness in cultivated tomato than in a distant congener, but Maclot et al. (2023) found that virus species richness increased with Poaceae host richness along a management gradient from cultivated cereals to natural grassland communities.

## Greater prevalence of aphid-transmitted viruses in farm populations

This study evaluated aphid-transmitted viruses in farm and wild populations and found overall prevalences to be greatest in farm populations (Fig. 2). The prevalence of known aphid-transmitted viruses was much higher in farm carrots than in wild carrots for CtRLV, umbraviruses, and associated subviral agents (Fig. 2). These results support our initial hypothesis and are consistent with other studies at the landscape level showing higher virus prevalence in managed or cultivated areas compared with less managed or wild areas (Bernardo et al. 2018; Pagán et al. 2012). The difference in prevalences might arise in part from higher aphid pressure in the agricultural environment because natural enemies that control aphids and other pests are commonly more abundant in diverse vegetation with perennial elements (Werling et al. 2014). This possibility suggests that the influence of biocontrol-enhancing management strategies on virus prevalence in carrot fields merits continued attention.

In the prevalence data, another striking pattern stood out. Known aphid-transmitted taxa were much more prevalent in farm carrots than in wild carrots, whereas, with the exception of CaUV1 and CaPV2, novel congeners of these known taxa were more prevalent in wild populations (0 to 20%, overall average 7.9%) than in farm populations (0 to 4%, overall average 0.7%) (Fig. 2). This clear and surprising pattern raises the question of its origin. One hypothesis could be that past efforts of plant virologists largely focused on cultivated species, with the consequence that high-prevalence viruses infecting crop carrots have a higher probability of having been discovered than low-prevalence ones of viruses infecting only wild carrots. More broadly, these patterns highlight divergence between the viromes of the farm and wild populations and illustrate the need to understand the selective pressures that have resulted in divergent parallel systems and their consequences for disease impacts.

## Divergent virome compositions of wild and farm populations

Farm and wild carrot populations showed contrasted viromes, as evident in clustering and network analyses (Figs. 4 and 5). Farm populations of cultivated and off-type carrots clustered together in both analyses (Figs. 4 and 5). Off-type carrots grow alongside cultivated carrots in farm fields but are morphologically and phenologically very different, showing early bolting and thin taproots typical of wild carrots. These tap roots are frequently white but also sometimes orange, prompting the hypothesis that off-type plants might result from hybridization between wild and cultivated carrots during commercial seed production (Magnussen and Hauser 2007). The virome similarities between cultivated and off-type carrots, despite their phenotypic and genetic differences, suggest a major impact of local growth conditions, including those created by agriculture, in shaping virome richness, composition, and virus prevalence.

The cultivated and off-type carrot populations in this study shared a total of 21 viruses (Fig. 3), four of which were unique to them. These include a novel, unclassified virus (CaRNAV1; Fox et al. 2022), showing distant homologies to *Benyviridae* family members and viruses from the families *Closteroviridae* and *Chordoviridae* (Fig. 3; Supplementary Table S4). It must be noted that the later viruses were detected in only two to four of the 18 analyzed farm populations (Supplementary Table S4), so that their apparent specificity could still reflect an undersampling of wild populations. On the other hand, CaRNAV1 was detected in all 18 farm populations but was absent from all 13 wild populations (Supplementary Table S4), even when sampled very near the border of a cultivated plot. Given its very recent discovery (Fox et al. 2022), there is very little information available on CaRNAV1, and it is unclear whether it infects carrots or might infect another organism associated with carrots, such as a fungus.

## Co-occurrence of dependent and helper viruses: Considerations in carrot disease

The agriculturally important CMD arises from a mixed infection of a polerovirus (CtRLV) with a dependent umbravirus (CMoV or CMoMV), sometimes with additional subviral agents, such as a tlaRNA or a satRNA (Yoshida 2020). Even though we identified the known positive association between CtRLV and CMoV, our co-occurrence analysis identified surprisingly few other positive associations between helper viruses and dependent agents (Fig. 6). However, it is noteworthy that for each of the novel *Solemoviridae* helper viruses (CaPV1 and CaEV1), positive associations were detected with one or two umbraviruses and with novel tlaRNA or satRNA. This suggests the existence of viral complexes parallel in structure to that responsible for CMD but involving novel agents. The nature of these CMD-analogous associations in wild plants merits more investigation: Do these complexes cause disease equivalent to CMD? If not, what elements of the system have downregulated pathogenicity?

The limited number of positive associations identified for the *Solemoviridae* helper viruses is nonetheless a surprise given the absolute dependency for aphid transmission of umbraviruses and virus-like agents. Two reasons could explain this situation: The first is that an ability of dependent agents to be assisted by different helper viruses would greatly affect the detection of statistically significant co-occurrences. A second possibility is that although assisted, a dependent agent could be transmitted independently from its helper virus. Indeed, 41% (39/80) of the wild carrots with mixed infections of umbraviruses with subviral agents did not show evidence of the presence of a helper virus. This surprising finding parallels previous observations on umbraviruses or tlaRNAs in the absence of helper viruses (Fox et al. 2022; Schönegger et al. 2022; Yoshida 2020). In such a scenario of umbravirus transmission with-
out concomitant transmission of the helper virus, umbraviruses could further assist subviral agents for movement within the plant, but this would represent a dead-end infection without the possibility of further transmission. This hypothesis should also be considered in light of the recent discovery that some umbra-like viruses have no movement protein and yet are able to systemically infect plants by recruiting host phloem proteins for their movement (Ying et al. 2024).

## Phylogenetic analysis suggests barriers to virus exchange among farm and wild populations

To gain deeper insight into the movement of aphid-transmitted viruses between wild and cultivated carrots, we evaluated the phylogenetic relationships between isolates of viral taxa infecting the three different carrot types using sequences derived from RT-PCR amplicon sequencing and HTS analysis of single plants. For known aphid-transmitted viruses, a sufficient number of isolates were analyzed to compare viral populations from wild, off-type, and cultivated carrots. For CtRLV and WCMoV, phylogenetic analysis identified clades specifically associated with particular carrot population types. The WCMoV phylogeny included a clade specific to farm carrots (Fig. 7A, clade A) and two clades specific to wild carrots (clades B and C). Likewise, for CtRLV, clade C was specific to farm carrots and clades A and B to wild carrots (Fig. 7B). Taken together, these results suggest the existence of barriers to the spread of at least some isolates of CtRLV and WCMoV between the wild and farm compartments. On the other hand, for these two viruses, there also was a fourth clade (clade D in Fig. 7A and B), which included both wild population isolates and farm isolates. These may represent viral fluxes among wild and farm populations, although the directionality of these viral fluxes, from farm to wild (spillover), from wild to farm (spill-back from a wild reservoir), or even from a third unidentified source to both wild and farm could not be established. These results of differentiation of viral populations between host types parallel to those of Maachi et al. (2022), who identified a specific lineage of cucurbit aphid-borne yellows virus in the wild plant *Ecballium elaterium* that was genetically distinct from cucurbit aphid-borne yellows virus isolates in melon crops, and those of Ma et al. (2020) for potato virus Y in the tomato/nightshade pathosystem.

Taken together, the results reported here demonstrate surprisingly different virome compositions and structure between wild and farm carrots. This is in part due to differences in persistent, seedborne viruses, but differences were also observed for other viruses, most of which are expected to be aphid-borne. Although no clustering based on carrot type could be observed for most aphid-transmitted viruses (see, for example, Supplementary Fig. S2), suggesting the existence of viral fluxes between the wild and farm compartments, the results reported here indicate the existence of barriers limiting or altogether preventing these fluxes for some viruses or for specific phylogenetic clades of two aphid-transmitted viruses. The mechanisms underlying these barriers, which might reflect differential susceptibility of carrot populations, vector preferences, or other elements, remain to be identified and will require experimental approaches.

## Acknowledgments

We thank the INRAE GenoToul Platform (Toulouse, France, https://doi.org/10.15454/1.5572369328961167E12) for Illumina sequencing; Corentin Chateau and Stéphane Plas (Invenio, France) and François Villeneuve (CTIFL, France) for facilitating our sampling of carrot crops in Aquitaine; and Chantal Stoner (Michigan State University, East Lansing, MI, U.S.A.) for valuable input on the manuscript.

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