Meta-transcriptomic analysis of tick virome diversity and ecological characteristics in Yunnan Province, southwestern China

Abstract

Emerging tick-borne viruses are posing an increasing health concern. However, there is limited knowledge about the distribution characteristics of tick virome in Yunnan Province, southwestern China, where it is distinguished by its diverse eco-climatic zones and rich biodiversity, making it a hotspot for studying tick-borne pathogens. The present study aimed to explore the diversity and ecological characteristics of tick virome in Yunnan Province, especially to identify novel potentially pathogenic viruses threatening human and vertebrate animals, and to investigate host-specific viral tropisms and their transmission characteristics. Using a meta-transcriptomic approach, the study analyzed the viromes of 448 individual ticks and approximately 10,000 eggs collected from nine counties with different hosts, altitudes and landscapes. The ticks encompassed eight species across four genera. The study focused on delineating virome diversity profiles, evaluating host-specific viral tropisms, and investigating potential transovarial transmission through viral contigs identification and Sanger sequencing. The study identified 53 viral families, revealing significant virome diversity and geographic and environmental specificity. Haemaphysalis and Ixodes ticks exhibited greater viral richness and abundance, with host taxonomy being a primary influencing factor. We determined 102 viral genomes encompassing 35 species, comprising 15 novel viruses identified when their RNA-dependent RNA polymerase/DNA polymerase sequences exhibited <90% amino acid identity to known viruses. The novel vectors for vertebrate-related or potentially pathogenic viruses were also detected, thus providing new insights into transmission cycles. The evidence for transovarial transmission was reinforced by the absence of significant differences in Chuviridae and Nairoviridae families between female ticks and their eggs. These findings underscore the necessity of continuous surveillance to avert the spillover of emerging pathogens.

Highlights

• •We assembled 102 viral genomes of 35 species, including 15 novel viruses.
• •This study detected viruses in both ticks and eggs, suggesting potential transovarial transmission.
• •Vector and host identity, together with temperature and precipitation, shaped distinct viral distribution patterns.
• •These findings highlight the need for ongoing tick-associated virus monitoring in Yunnan Province to prevent spillover.

Introduction

Ticks (Acari: Ixodidae) are obligate blood-feeding vectors that feed in their larval, nymphal, and adult stages. They adapt to various ecological and human-modified environments and carry more zoonotic pathogens (viruses, bacteria, rickettsiae, spirochetes, protozoa) than other blood-feeding arthropods. The increasing prevalence and global distribution of emerging tick-borne viruses (TBVs) have raised substantial health concerns (Zhou et al., 2023; Yu and Park, 2024). Over the past decade (2015–2025), several emerging tick-borne viral pathogens have been confirmed in China, including Wetland virus (Zhang et al., 2024) and Xuecheng virus (Zhang et al., 2025).

In addition to these well-known pathogenic TBVs, ticks are carriers of numerous novel viruses with unknown or potential pathogenic effects. This phenomenon is largely due to the co-evolution of tick-associated viruses and the complex relationships between ticks and their multiple alternative hosts, leading to mutual tolerance, adaptation, and significant genetic diversity and geographical distribution of tick-associated viruses. As of March 6, 2025, the DRodVir online database has documented over 8000 viral species spanning 23 taxonomic families, serving as a pivotal global repository for tracking tick-associated virus diversity and bio-geographic distribution patterns (Zhou et al., 2022).

Many new tick-associated viruses have been discovered worldwide, for example in Romania, Kenya, and even the Antarctic Peninsula, aided by high-throughput sequencing technologies (Zhang et al., 2021; Bratuleanu et al., 2022). Specifically, research on tick virome has become a key focus in China. At the national level, a study of 724 RNA viruses from 31 tick species in the mainland of China revealed the extensive diversity of tick-associated viral genome structures, highlighting ticks as significant reservoirs for RNA viruses (Ni et al., 2023).

Regionally, novel tick-associated viruses continue to emerge across China. Along the China-Korea border, the Baishan forest tick virus has been identified, while Liaoning reports tick-associated hepe-like virus infections. Additionally, pathogenic virome diversity has been documented in ticks infesting domestic mammals in northeast China, herbivorous species in Qinghai, Xinjiang, and Inner Mongolia's pastoral zones, and various vectors from Hubei, Zhejiang, Shandong, Hainan, and Guangdong provinces (Yang et al. 2021, 2023; Xu et al., 2021; He et al., 2022; Kong et al., 2022; Guo et al., 2022; Wang et al., 2024; Ye et al., 2024). These studies underline the abundance and diversity of tick virome across various regions, emphasizing their complex evolutionary histories, potential ecological factors, and the genetic and biological characteristics of their vectors. However, compared with these regions, systematic research on Yunnan Province—a key area with particularly prominent ecological diversity—has lagged relatively behind. It is hypothesized that these factors encompassing both tick-specific variables and ecological driver influence the distribution and characteristics of tick virome, and require further verification through broader geographical surveys and the examination of a more diverse range of tick species. In addition, as tick-borne pathogens continue to emerge in new geographical areas, a growing public health threat posed by tick virome remains a persistent challenge. Therefore, further investigations into the tick virome in specific regions are critical for the surveillance and early detection of emerging pathogenic viruses within ticks.

Yunnan Province, located in southwest China, features significant altitudinal variations and diverse climate types, encompassing four primary and nine secondary climatic zones with its rich biodiversity (https://www.resdc.cn/Default.aspx). The region supports approximately 47 tick species across seven genera, with region-specific distribution patterns of ticks (Guo, 2016; Zhang et al., 2019). Notably, various pathogens including Rickettsia spp., Anaplasma spp., Ehrlichia spp., and Coxiella burnetii have been detected in tick specimens across multiple prefectures of Yunnan Province (Jiao et al., 2021; Lu et al., 2022; Du et al., 2024). However, there were few studies on tick virus in Yunnan Province, which only focused on the Jingmen tick virus (JMTV) in Ha. longicornis (Wu et al., 2023), and the Dabieshan tick virus (DBTV) in Rhipicephalus microplus (Wang et al., 2021). Previous studies on tick virome in Yunnan have typically focused on specific tick species, such as Ha. longicornis, R. haemaphysaloides and R. microplus, or concentrated on limited local areas, such as Nujiang Lisu Autonomous Prefecture and Tengchong city (Shi et al., 2021; Wang et al., 2023b; Ni et al., 2023). Accordingly, to address this gap, we conducted a systematic survey across a broader area of Yunnan Province to identify both known and novel TBVs and examine the ecological characteristics of viral composition using meta-transcriptomics, combined with epidemiological analyses. This work not only provides crucial insights for the proactive prevention and control of emerging viruses within the tick virome in this particular region but also significantly expands our understanding of the public health risk posed by tick-borne viruses across China.

Results

Data summary of tick species

A total of 448 individual ticks and more than 10,000 eggs, representing eight species across four genera in nine counties, were collected. Eight sampling sites were situated within the middle subtropical zone, while a single site was located in a plateau climate region (Fig. 1A). Species identification was based on cytochrome c oxidase subunit I (COI) gene analysis (Fig. 1B, Supplementary Fig. S1). The eight species belonging to four genus were confirmed:Haemaphysalis colasbelcouri, Ha. kolonini, Ha. montgomeryi, Hyalomma marginatum, Ixodes ovatus, I. acutitarsus, Rhipicephalus haemaphysaloides and R. microplus. The most frequently sampled tick species were Ha. montgomeryi (237 individuals), R. microplus (102 individuals), which were found in seven of the nine sampling counties and across all four landscape types. In Weishan County, five tick species were identified, including Ha. colasbelcouri and Ha. kolonini (Fig. 1A, Supplementary Fig. S1), which were newly recorded and recently discovered species. To understand the spatial distribution patterns of the eight tick species, spatial autocorrelation analysis was conducted. The results showed a Global Moran's Index of 0.77 (P < 0.001), indicating a high degree of spatial autocorrelation in the distribution of tick species in Yunnan (Fig. 1C).

Fig. 1.

Overview of the samples analyzed in this study. A The geographical distribution of climatic zones alongside the locations of sampling sites across Yunnan Province. Pie charts display the composition of tick species sampled at each location, with the total area of the pies proportional to the number of individuals captured. Different colors represent various tick species, consistent with the color scheme in Fig. 1B. B Maximum likelihood phylogenetic tree depicting the relationships among tick individuals, constructed using the COI gene. C Spatial autocorrelation analysis among eight tick species in Yunnan Province.

Meta-transcriptomic analysis of tick virome

Before meta-transcriptomic sequencing, the ticks were categorized and pooled based on collection site, species, gender, host, life stage, and landscape. The number of individual ticks in each pool were recorded in Supplementary Table S1. The transcriptomes of 62 libraries were categorized, which included samples from R. microplus (n = 23), Ha. montgomeryi (n = 22), I. ovatus (n = 11), I. acutitarsus (n = 2), Ha. colasbelcouri (n = 1), Ha. kolonini (n = 1), Hy. marginatum (n = 1), and R. haemaphysaloides (n = 1). Approximately 619.68 gigabases (Gb) of paired-end reads, each 150 bp in length, was generated through total RNA sequencing. After raw data filtering, trimming, and error removal, de novo assembly produced 13,219,543 contigs. A total of 839,483 viral reads were identified and classified into 53 families of non-phage-host viruses. These reads showed significant differences in virus prevalence and abundance across different tick genera and locations (Fig. 2A). These families included 23 positive-sense single-stranded RNA (ssRNA(+)) virus families, 11 negative-sense single-stranded RNA (ssRNA(−)) virus families, 8 double-stranded DNA (dsDNA) virus families, 7 double-stranded RNA (dsRNA) virus families, and 3 single-stranded DNA (ssDNA) virus families (Fig. 2B).

Fig. 2.

An overview of the tick-associated virome. A Relative abundance of viral families detected in each library. Each cell in the heatmap represents the normalized number of reads belonging to the viral family. The colors on the heatmap represent different tick species, hosts and sampling locations. B Virome composition was determined for each tick genus. C Principal coordinate analysis showing variation in virome compositions among tick genera. All P values were calculated using adonis test. D Comparison of the viral Shannon index among tick genera. The P value was calculated using a two-sided Wilcoxon rank-sum test for pairwise comparisons and a Kruskal-Wallis test for multiple comparisons. E Principal coordinate analysis showing variation in virome compositions among tick locations. F Comparison of the viral Shannon index among tick locations.

Viral abundance and richness

Among these virus families, Artiviridae was the most frequently detected, present in all 62 libraries, followed by Phenuiviridae (present in 52 libraries), Chuviridae and Rhabdoviridae (present in 50 libraries), Parvoviridae and Orthomyxoviridae (present in 30 libraries), and Nairoviridae (present in 35 libraries). Arthropod-associated viruses are characterized by their obligate biological reliance on arthropods, which function either as principal reservoirs or critical vectors facilitating transmission to vertebrate hosts through hematophagous behavior. Notably, members of the Chuviridae exhibited the highest prevalence and abundance across all tick species in this study. Artiviridae viruses, previously known to infect insects and crustaceans, also exhibit high abundance and prevalence in all tested tick species. Phenuiviridae also showed high prevalence and abundance in seven tick species (Fig. 2A). Significant variation at thefamily level was observed among the three tick genera (adonis test, R² = 0.23, P = 0.001; Fig. 2C). We conducted comparative analyses across three tick genera (Rhipicephalus, Haemaphysalis, and Ixodes) with sufficient sample sizes. Notably, virus families in Rhipicephalus ticks generally exhibited lower prevalence and abundance than those in Haemaphysalis and Ixodes ticks (Shannon index, P = 0.011, Fig. 2D; Simpson index, P = 0.011, Supplementary Fig. S2A). Further comparisons revealed significant differences in viral diversity among the three tick species, with R. microplus exhibiting lower prevalence and abundance than Ha. montgomeryi and I. ovatus (Shannon index, P = 0.005, Supplementary Fig. S2B; Simpson index, P = 0.004, Supplementary Fig. S2C). Notably, ticks sampled from the nine locations exhibited a tendency to cluster together (adonis test, P = 0.002; Fig. 2E), suggesting a potential association between location and the virome structure of ticks. Considering the possibility that paired female ticks and eggs may carry viruses transmitted vertically, an analysis of the diversity of these groups was conducted after the removal of nine pools from egg samples to gain greater insight into the ecological factors influencing tick virome composition. The results indicated that viral family diversity was elevated in the central and northwestern regions of Yunnan Province, particularly in the Weishan and Yulong districts (Shannon index, P = 0.012, Fig. 2F; Simpson index, P = 0.0163, Supplementary Fig. S2D). We selected five dominant viral families: Chuviridae, Nairoviridae, Phenuiviridae, Rhabdoviridae, and Artiviridae. A significant association between tick genera and viral family dominance was demonstrated by Fisher's exact test (P < 0.001), suggesting genus-specific ticks preferences for particular viral lineages. Kruskal-Wallis tests revealed substantial heterogeneity in viral abundance across three tick genera (Ixodes, Rhipicephalus, Haemaphysalis) for all five families (P < 0.001). Specifically, Haemaphysalis exhibited markedly higher Nairoviridae abundance compared to Ixodes and Rhipicephalus (Wilcoxon rank-sum, P < 0.001, Supplementary Fig. S3A). Notably, Chuviridae predominated in Weishan and Nairoviridae abundance peaked in Yulong (Wilcoxon rank-sum, P < 0.001, Supplementary Fig. S3B).

Further multivariate linear regression analysis of ecological determinants revealed significant associations between viral family diversity and climatic variables. Notably, virome richness demonstrated positive correlations with three-month temperature averages (β = 0.05, P = 0.01), while it showed a significant negative correlation with preceding monthly precipitation levels (β = −0.01, P < 0.001), with precipitation exhibiting stronger effect magnitudes (Supplementary Fig. S4).

Differential viral abundance in developmental stages

To investigate whether viruses could be transmitted transovarially, we compared the viromes of engorged female ticks and their eggs. Only statistics from samples with non-zero detected viral abundance greater than 5 were included, to minimize statistical error. Overall, virus prevalence and abundance were generally higher in female adults than in eggs (Shannon index, P = 0.014, Supplementary Fig. S2E, Simpson index, P = 0.031, Supplementary Fig. S2F). However, subsequent bar graphs quantifying differences for each viral family, using the Mann-Whitney U test, showed no significant differences between the two stages (Fig. 3A). Heatmaps depicting virus abundance in nine pairs of female ticks and their eggs (Fig. 3B) illustrated the viral characteristics of different growth stages. Further analysis of key viruses, using paired box plots and Wilcoxon signed-rank tests, revealed no significant differences in the relative abundance of viruses between two stages (Fig. 3C). Further evidence of transovarial transmission of Yunnan nairo-like virus 54 and Wuhan mivirus in I. ovatus and R. microplus, respectively, was obtained based on the results of the RdRp (Supplementary Table S2). Strikingly, Sanger sequencing and blast analysis confirmed the presence of identical Yunnan nairo-like virus 54 (in I. ovatus) and Wuhan mivirus (in R. microplus) in both female ticks and their eggs, with >99% nucleotide sequence identity (Supplementary Table S3). This provides compelling molecular evidence supporting the transovarial transmission of these viruses within their respective tick populations.

Fig. 3.

Comparative analysis of viral abundance between eggs and female ticks. A Box plot with error bars of viral abundance between eggs and female ticks. Groups were compared using the Mann-Whitney U test. Individual samples are shown as scatter points (red circles: adult females; blue circles: eggs), representing relative viral abundance values. B Heatmap displaying the viral abundance across 9 paired samples of eggs and female ticks. C Paired box plots for viruses with statistically significant differences between eggs and female ticks, as determined by the Wilcoxon signed-rank test. The plot includes individual sample connections, highlighting paired variation.

Taxonomy and evolution of RNA viruses

A total of 102 viral contigs encoding RdRp for RNA viruses and DNA polymerase for DNA viruses were identified, representing 35 virus species from 11 families. Of these, 15 viruses were classified as novel according to the criteria established by International Committee on Taxonomy of Viruses (ICTV) (Fig. 4A–E, Supplementary Fig. S5–S14). Among the identified viruses, nineteen ssRNA(−) viruses from five viral families (Rhabdoviridae, Nairoviridae, Chuviridae, Orthomyxoviridae, and Phenuiviridae) were detected, seven of which were newly discovered. Of the twelve known species, the Rhipicephalus-associated rhabdo-like virus, Wuhan mivirus and Taian Botou tick virus were detected for the first time in Ha. montgomeryi, while Zhangye Rhabd tick virus 1 and Bole tick virus were observed for the first time in Hy. marginatum (Fig. 5A). Among the eight novel ssRNA(−) virus species, three each belonged to the Nairoviridae and Phenuiviridae families, and two belonged to the Chuviridae family (Fig. 4A). The amino acid similarity in the RdRp of these viruses was less than 90% compared to their most closely related species (Supplementary Table S2).

Fig. 4.

Phylogenetic diversity of eleven major viral families. A–D Phylogenetic trees were established based on amino acid sequences of the RdRp protein for RNA viruses or the replicase protein for DNA viruses for the currently identified viruses that included: (A) Nineteen ssRNA(−) viruses; (B) Six dsRNA viruses; (C) One ssDNA virus; (D) Seven ssRNA(+) viruses. The best-fitting model was determined by the ModelFinder program implemented in IQ-TREE v2.2.2.3. Phylogenetic inference was performed using maximum likelihood method with 1000 bootstrap replicates. Branch lengths are indicated by the scale bar. The red, blue, green, and black lines represent mammal, tick, insect and other hosts, respectively. The black circle represent novel virus. E Taxonomic distribution of viruses discovered in this study, circles of different colors represent distinct virus types.

Fig. 5.

Cross-species transmission of viruses. A The cross-species pattern of 20 known viruses is depicted based on a combination of our data and the virus records from the NCBI database. Red cycles indicate viruses which were identified in ticks for the first time. Red, blue, and brown asterisks indicate viruses with cross-species risk, cross-genera risk, and cross order identified in this study, respectively. Purple triangles indicate known viruses, brown triangles indicate new viruses. B A Sankey diagram to visualize the associations among the prevalence of viruses identified in this study. C A host network map illustrating connections among different species of vector/host through shared 35 viruses in this study. The number of viruses by each vector/host group is indicated within bracket. Purple circles indicate known viruses, brown circles indicate new viruses. The size of circles corresponds to the number of viral sequences.

Among the dsRNA viruses, six novel viruses were identified in the family Artiviridae (Fig. 4B), with 46.95%–85.99% identities to known viruses. Four of these viruses were identified in Ha. kolonini. Among the ssDNA viruses, a previously reported virus, Circovirus sp. gt3aAU, was detected for the first time in I. ovatus ticks (Figs. 4C and 5A). Seven ssRNA(+) viruses were identified across the Flaviviridae, Narnaviridae, and Botourmiaviridae families, six of which exhibited high similarity to previously characterized viruses but were first found in new tick vectors. Given that ticks frequently ascend vegetation during host-seeking behavior, they may acquire and transmit plant-associated viruses (Jeger, 2020). One novel Narnaviridae virus was identified in Ha. montgomeryi (Figs. 4D and 5A). All 102 sequences encoding complete or nearly complete RdRp were deposited in GenBank, including 24 sequences from novel viruses and 78 sequences from known viruses (Fig. 4E).

Epidemiological characteristics and transmission cycle of tick virome

A combination of our data with virus records obtained from the NCBI database revealed that 12 out of 20 known viruses are capable of cross-species transmission. As mentioned above, new hosts (I. ovatus, Hy. marginatum and Ha. montgomeryi) were identified for six viruses. Of particular significance is the detection of Taian Botou tick virus 2, Dali Chuvi tick virus 1, Rhipicephalus-associated rhabdo-like virus, and Wuhan mivirus across diverse tick genera, underscoring their broad vector range (Fig. 5A, Supplementary Table S4).

Of the 12 viruses capable of cross-species transmission, eight were found to transmit between different tick genera. We performed a resampling analysis on association networks involving 35 tick-associated RNA viruses and six tick species (another two tick species with incomplete viral sequences were omitted from analysis). The results showed that 27 of these viruses exhibited genus specificity: 5 virus species were specific to the genus Rhipicephalus, 14 were specific to Haemaphysalis, and 8 were specific to Ixodes (Fig. 5B and C). Estimated prevalence based on pooled samples of viruses in the family Chuviridae was significantly higher than that of other virus families (53.23%, 95% [CI] 40.21%−65.84%), with Wuhan mivirus exhibiting the highest prevalence of approximately 38.71% (95% [CI] 26.87%–51.95%). A novel virus, Yunnan_tick_unclassified exhibited the second-highest prevalence (14.52%, 95% [CI] 7.25%–26.28%) (Fig. 5B, Supplementary Table S5).

Discussion

Our study presents a comprehensive analysis of viruses across eight tick species from nine counties in Yunnan Province, mapping the diversity and ecological characteristics of the tick virome. Specifically, we identified new vectors for known viruses and discovered both known and novel viruses in unstudied ticks. We also explored cross-species transmission and documented transovarial transmission for certain viruses. This work provides a more detailed investigation and accurate comparative analysis of the tick virome in Yunnan, highlighting the critical role of ticks as significant hosts in viral evolution and transmission to humans.

Among the 11 viral families identified, the presence of both known and novel viruses in Artiviridae, Phenuiviridae, Chuviridae, Rhabdoviridae, Parvoviridae, Orthomyxoviridae, and Nairoviridae was further confirmed. These viruses are highly homologous to pathogenic viruses of vertebrates and humans. Notably, viruses from the Artiviridae, Phenuiviridae, and Nairoviridae families exhibited high abundance and prevalence across all or most of the surveyed tick species. This finding aligns with previous investigations, such as one conducted by Wang et al., which examined 2570 ticks in Nujiang, a city located on the northwestern border of Yunnan (Wang et al., 2023b). However, only 13 RNA viruses were identified in that study, likely due to the large number of ticks pooled (100 ticks per pool), which may have overlooked some low-abundance pathogens. Additionally, the dominant tick species in that study were different from those in our study. In contrast, R. microplus and Ha. montgomeryi were identified as the dominant tick species in the present study, with the latter species not being collected in Nujiang. The extension of geographical sampling coverage throughout Yunnan enabled systematic documentation of tick virome diversity and ecological patterns, culminating in the discovery of both new tick species records and a number of novel viruses. These findings highlight the importance of further investigations into larger geographical areas to assess potential public health risks.

The aggregation patterns of tick populations in Yunnan Province and their virome are likely determined by a combination of factors, including tick taxonomy, location, and habitat. These factors also influence the epidemiological dynamics of tick-borne diseases in the region (MacDonald, 2018; Randolph and Rogers, 2000; Estrada-Peña Agustin, 2003; Xu et al., 2021; Ye et al., 2024). Correlation analyses revealed two key findings in this study. Firstly, significant differences were observed between tick genera at the virome family level. Haemaphysalis and Ixodes ticks exhibited higher viral abundance and prevalence compared to other genera. Previous research on seven tick genera across China and two genera from Hubei supports the conclusion that host species is a key factor influencing the structure of the tick virome group (Xu et al., 2021; Ni et al., 2023). Secondly, higher diversity of virus families in central and northwestern Yunnan Province, particularly in Weishan and Yulong, suggests a potential association between geolocation and the virome structure of ticks (Xu et al., 2021; Kong et al., 2022). Notably, more tick species (5/8, 62.5%) and the highest viral diversity and prevalence of the virome were found in Weishan. This phenomenon may be attributed to the unique ecological characteristics of Weishan, including its middle subtropical monsoon climate with abundant rainfall, evergreen broadleaf forests, and high biodiversity of small mammals, which provide favorable habitats for ticks and diverse reservoirs for viral maintenance. Further, detection of Wuhan mivirus and Yunnan nairo-like virus 54 in both female ticks and their eggs was exclusively observed in specimens collected from the Weishan region, suggesting that these ecological conditions may also facilitate sustained tick populations and efficient pathogen circulation. This further substantiates Yunnan Province's epidemiological significance as a hotspot for transovarial transmission of tick-associated pathogens. These findings could provide valuable insights for the prevention and control of tick-associated infectious diseases in Weishan and ecologically similar regions. Unlike in previous studies on a specific tick species, Ha. longicornis, in Shandong, ecological factors (altitude, habitat) of the sampling sites in this study may have multiple covariates, making it difficult to accurately analyze the key factors influencing the composition of the virus population and the positivity rate (Ye et al., 2024).

The study revealed that 27 viruses exhibited genus specificity. In addition, all four viruses detected in Ha. kolonini were novel viruses belonging to the family Artiviridae, while those detected in R. microplus were previously reported viruses. As Ha. kolonini was a newly identified species in 2018, and R. microplus is a common species widely distributed throughout China, further studies of the virome of uncommon tick vectors are warranted (Du et al., 2018). The present study also revealed that Chuviridae exhibited a markedly elevated abundance and prevalence within the genus Rhipicephalus, accompanied by a notable abundance and prevalence of Nairoviridae and Chuviridae in Haemaphysalis ticks.

Cross-species transmission represents a relatively common phenomenon within the field of virus ecology. Besides 15 novel viruses, most of the known viruses were also first detected in ticks, extending the host range of these viruses. Of the 20 known viruses examined in this study, 12 demonstrated cross-species transmission, and 8 were capable of transmission between different tick genera. This finding emphasizes the pivotal role of ticks as intricate transmission mediators within the viral ecosystem.

Furthermore, our research identified new vectors for the viruses, as well as cross-species and vertical transmission characteristics and influencing factors. Particularly, the discovery of new vectors for some vertebrate-related viruses expanded our understanding of transmission cycles, indicating that ticks may act as vectors in the transmission cycle of animal viruses, underscoring the significance of comprehensive biomonitoring in ticks. It has been demonstrated that although some tick-associated viruses are more clearly associated with specific tick species, they may also be transmitted across tick species under appropriate conditions. For instance, Dabie bandavirus is more likely to infect Ha. longicornis, which can then transmit the virus (Luo et al., 2015; Ye et al., 2024). Nevertheless, the transmission mechanisms of these viruses, including cross-stage and transovarial transmission, may influence their host specificity and lead to variations in adaptation and host preference (Hu et al., 2020). This highlights the necessity for sustained research into the host specificity of tick virome and its potential capacity for cross-species transmission.

In addition, transovarial transmission represents a significant route for certain viruses. Laboratory evidence has demonstrated that viruses such as Dabie bandavirus, JMTV, and DBTV were capable of transovarial transmission in specific tick species, posing a considerable threat to human and animal health (Huard et al., 1978; Hu et al., 2020; Wu et al., 2023; Wang et al., 2023a; Xu et al., 2024). Previous studies have indicated the potential for transovarial transmission of Dugbe orthonairovirus in Amblyomma variegatum ticks from Nigeria (Huard et al., 1978). This study identified potential transovarial transmission of a newly discovered Nairoviridae virus in I. ovatus and Wuhan mivirus in R. microplus. However, further experimental studies are required to confirm this phenomenon.

This study has several limitations that need to be addressed. Firstly, the sample size of some tick species was relatively small, and some rare tick species, such as Ha. colasbelcouri, Ha. kolonini, and Hy. marginatum, were underrepresented, which may have influenced the richness and abundance of the data. Secondly, the potential pathogenicity of the newly identified viruses to humans and other mammals remains unknown due to the constraints of the time frame and experimental conditions. Further studies such as virus isolation and serological testing for exposed humans and livestock are required to elucidate this aspect.

Conclusions

In conclusion, this study enhances our understanding of the high diversity of tick virome and its ecological characteristics within Yunnan Province. It reveals critical linkages between virome composition, distribution, and characteristics of transmission with associated risks. These findings underscore the necessity for continuous surveillance to avert the spillover of emerging pathogens, providing a solid foundation for proactive prevention and control of tick-associated pathogens and potential hazards in the future.

Materials and methods

Sample collection and species identification

From October 2022 to November 2023, field surveys of ticks were conducted across nine counties in Yunnan Province, southwestern China. The survey sites covered a variety of landscapes, including alpine meadows, bushes, broadleaved forests, and mixed forests, spanning an altitude gradient of 1564–3907 m (Fig. 1A). Host-seeking ticks were collected using flag-sweeping on vegetation, while parasitic blood-feeding ticks from mammals were removed with forceps. All tick samples were initially identified based on morphological characteristics by entomologists. The engorged ticks were then reared in an artificial climate chamber until they laid eggs. All samples were stored at −80 °C until further processing. To confirm the tick species, barcoding identification of the COI gene was performed (Geller et al., 2013).

RNA extraction, library construction, and sequencing

Before meta-transcriptomic sequencing, the ticks were categorized and pooled based on collection site, species, gender, host, life stage, and landscape. The number of individual ticks in each pool were recorded in Supplementary Table S1. Total RNA was extracted and purified from each pool using the RNeasy Mini Kit (Qiagen, Germany), following the manufacturer's instructions. The purified RNA was quantified using a Qubit 4.0 fluorometer. Next-generation sequencing was then applied to each pool, and the sequencing library was constructed using the NEBNext Ultra II Directional RNA Library Prep Kit (NEB, USA). Paired-end transcriptome sequencing (RNA-seq) of the RNA library was performed on the Illumina NovaSeq 6000 (PE150 bp) sequencing platform (San Diego, USA). We developed virus-specific primer pairs targeting conserved RdRP genomic regions to enable PCR-based detection of epidemiologically important viruses identified in this study. The resultant amplicons were subsequently subjected to Sanger sequencing. The obtained sequences were subjected to blastn analysis against the NCBI nt database (E-value <1 × 10⁻⁵) to evaluate phylogenetic relationships and sequence homology.

Virus discovery

The raw sequencing data underwent trimming for low-quality bases using the fastp program (v0.20.0). Ribosomal reads were subtracted from each library by mapping to the SILVA rRNA database (https://www.arb-silva.de/) using Bowtie2 (v2.2.5). Clean reads were clustered based on a 95% sequence identity threshold and 95% alignment coverage using MMseqs2 (Mirdita et al., 2021). The remaining reads were then compared against a viral protein database and the non-redundant protein (nr) database using the diamond blastx program (v2.1.8) to identify viral-associated reads. Subsequently, all viral-associated reads were compared against the nt and nr databases using blastn (v2.9.0) and blastx (v2.9.0) for further confirmation (Buchfink et al., 2021). A significant hit was defined by an E-value smaller than 1 × 10⁻⁵. In addition, we also removed any possible contaminating viral sequences linked to laboratory components from high-throughput sequencing, as previously reported (Asplund et al., 2019). The taxonomic lineage information of the reads was derived from the top blast hit for each viral read. Viral read abundance was estimated using virus-annotated reads (including clustered reads) and summarized by viral family based on taxonomic lineage. Read counts of each viral RNA were acquired from the mapping results, and within-sample normalization (reads per million/viral reads, RPM) was performed to compare samples.

Viral contigs assembly and annotation

Clean reads were de novo assembled using SPAdes (v3.13.0), and contigs with significant hits to viral sequences were retained as viral contigs (Prjibelski et al., 2020). The contigs were arranged and linked sequentially according to their alignment with the reference, with gaps represented by a series of 'N's to indicate unknown sequences between them. Potential open reading frames (ORFs) within these contigs were compared with reference sequences from NCBI using SnapGene (v7.2.0). The RNA-dependent RNA polymerase (RdRp) region of these viral contigs was manually annotated using predicted open reading frames and protein blast results. Putative viral ORFs were identified according to the following criteria: sequences were removed if the amino acid (aa) length was less than 20% of the full length. A novel virus was proposed if its RdRp sequence showed less than 90% aa similarity to known viruses when species demarcation criteria were unclear (Wille et al., 2020; Ni et al., 2023). Viruses identified in this study were classified according to ICTV report (https://talk.ictvonline.org/ictv-reports/ictv online report/). All putative novel viruses were provisionally named “Yunnan”, plus the family name, excluding “viridae” characters according to their taxonomy.

Phylogenetic analysis and viral species demarcation

RdRp sequences were selected and aligned within families using MAFFT (v7.490), and ambiguously aligned regions were removed with TrimAl (v1.4) to ensure precision (Capella-Gutiérrez et al., 2009; Rozewicki et al., 2019). Phylogenetic reconstruction was carried out using the maximum likelihood (ML) method implemented in the IQ-TREE (v2.2.2.3) program (Nguyen et al., 2015). Furthermore, an investigation of all identified viruses was conducted to assess cross-species transmission events. The host range determination of novel viruses relied exclusively on the host source information collected during this study. For the known viruses, host range determination was conducted using data obtained from NCBI/GenBank, as of the version released on September 25, 2024 (https://ftp.ncbi.nlm.nih.gov/genbank). The host order/viral species ratio is defined as the number of host orders that can harbor or transmit the total number of viral species. Specifically, if a viral species was identified in more than one host species, it was classified as a “cross-species” virus (Chen et al., 2023).

Statistical analysis

Viral family-level alpha diversity was evaluated utilizing the Shannon and Simpson indices, with the Kruskal-Wallis test and Wilcoxon rank-sum test applied to examine significant variations in diversity metrics across distinct tick populations and ecological variables. Multivariate linear regression was performed to analyze the relationships between continuous climatic variables and virome composition. Separately, fisher's exact test was applied to examine associations between categorical variables and the occurrence of significant viral families. A similarity matrix was constructed for the various groups based on the Bray-Curtis distance index. Principal coordinates analysis (PCoA) was then performed to analyze the beta diversity of the virome among different tick genera and environmental factors. The spatial autocorrelation analysis (Global Moran's I) was conducted using ArcGIS software (version 10.8). Mean temperature and precipitation data were obtained from the Institute of Geographic Sciences and Natural Resources Research (accessible at: https://www.resdc.cn/). The positivity rate, along with a 95% confidence interval (CI), for each tick-associated RNA virus was calculated using R software (version 4.4.1).

Data availability

The sequencing data have been deposited to SRA under BioProject ID PRJNA1189840 (GenBank: PQ754278-PQ754379) in the NCBI (https://www.ncbi.nlm.nih.gov/) and Science Data Bank (https://doi.org/10.57760/sciencedb.32200).

Author contributions

Rong Xiang: conceptualization, data curation, methodology, validation, writing-original draft; Fengjuan Tian: data curation, formal analysis, validation; Jing-Li: data curation, software, validation; Jihu Yang, Danni Zeng, Yilin Zhao, Wenqiang Shi, Chunfeng Luo, Xiaohe Liu: formal analysis, Zhi Luo, Miao Li, Chaobo Du, Yi Sun: investigation; Yigang Tong: software, supervision; Chunhong Du: conceptualization, resources, investigation; Jiafu Jiang: funding acquisition, resources, project administration, writing-review & editing.

Conflict of interest

The authors have declared no conflict of interest. Prof. Yigang Tong is an editorial board member for Virologica Sinica and was not involved in the editorial review or the decision to publish this article.

Appendix A. Supplementary data

The following are the Supplementary data to this article:

Supplementary Fig. S1.

Phylogenetic relationships of eight tick species in this study. Branch lengths are measured by a scale bar.

Supplementary Fig. S2.

A Comparison of the viral Simpson index among tick genera. B Comparison of the viral Shannon index among tick species. C Comparison of the viral Simpson index among tick species. D Comparison of the viral Simpson index among tick locations. E Comparison of the viral Shannon index among tick development stages. F Comparison of the viral Simpson index among tick development stages.

Supplementary Fig. S3.

Overview of the five dominant tick-associated viral families. A Comparison of the five dominant viral groups across tick genera. B Comparison of the five dominant viral groups across tick collection sites.

Supplementary Fig. S4.

Multivariate linear regression analysis of the relationship between viral family diversity and climatic variables.

Supplementary Fig. S5.

The phylogenetic tree was established based on amino acid sequences of viral RNA-dependent RNA polymerase in the family Rhabdoviridae. Branch lengths are measured by a scale bar. The RNA virus identified in this study is labeled by circle.

Supplementary Fig. S6.

The phylogenetic tree was established based on amino acid sequences of viral RNA-dependent RNA polymerase in the family Nairoviridae. Branch lengths are measured by a scale bar. The RNA virus identified in this study is labeled by circle.

Supplementary Fig. S7.

The phylogenetic tree was established based on amino acid sequences of viral RNA-dependent RNA polymerase in the family Orthomyxoviridae. Branch lengths are measured by a scale bar. The RNA virus identified in this study is labeled by circle.

Supplementary Fig. S8.

The phylogenetic tree was established based on amino acid sequences of viral RNA-dependent RNA polymerase in the family Chuviridae. Branch lengths are measured by a scale bar. The RNA virus identified in this study is labeled by circle.

Supplementary Fig. S9.

The phylogenetic tree was established based on amino acid sequences of viral RNA-dependent RNA polymerase in the family Phenuiviridae. Branch lengths are measured by a scale bar. The RNA virus identified in this study is labeled by circle.

Supplementary Fig. S10.

The phylogenetic tree was established based on amino acid sequences of viral RNA-dependent RNA polymerase in the family Artiviridae. Branch lengths are measured by a scale bar. The RNA virus identified in this study is labeled by circle.

Supplementary Fig. S11.

The phylogenetic tree was established based on amino acid sequences of viral replicase protein in the family Circoviridae. Branch lengths are measured by a scale bar. The RNA virus identified in this study is labeled by circle.

Supplementary Fig. S12.

The phylogenetic tree was established based on amino acid sequences of viral RNA-dependent RNA polymerase in the family Botourmiaviridea. Branch lengths are measured by a scale bar. The RNA virus identified in this study is labeled by circle.

Supplementary Fig. S13.

The phylogenetic tree was established based on amino acid sequences of viral RNA-dependent RNA polymerase in the family Narnaviridae. Branch lengths are measured by a scale bar. The RNA virus identified in this study is labeled by circle.

Supplementary Fig. S14.

The phylogenetic tree was established based on amino acid sequences of viral RNA-dependent RNA polymerase in the family Flaviviridae. Branch lengths are measured by a scale bar. The RNA virus identified in this study is labeled by circle.

Supplementary Table S1

Information and ecological factors of tick samples in Yunnan Province

Supplementary Table S2

Best match of blastx comparison for viruses discovered in this study

Supplementary Table S3

Virus host information from this study and the NCBI database

Supplementary Table S4

The prevalence of viruses detected in ticks from Yunnan Province

Supplementary Table S5

Sanger sequencing validation of viral sequences identified in different developmental stages of ticks