Biological source material for genome sequencing of ticks

Biological material metadata was compiled for the 54 tick genome assemblies. For the zoogeographic origin (see Guglielmone et al., Reference Guglielmone, Nava and Robbins2023) of the tick material, the most assemblies (∼35%) are generated from ticks collected in the Nearctic zoogeographic region (North America), followed by ∼31% Palearctic (Europe and China) and ∼26% Afrotropical (Africa) (Figure 2A, Table S3). It is noted that some tick species are invasive and have been collected outside their native zoogeographic region and a genome assembly generated from this material, such as Haemaphysalis longicornis (see Guerrero et al., Reference Guerrero, Bendele, Ghaffari, Guhlin, Gedye, Lawrence, Dearden, Harrop, Heath, Lun, Metz, Teel, Perez de leon, Biggs, Pomroy, Johnson, Blood, Bellgard and Tompkins2019; Moustafa et al., Reference Moustafa, Barnes, Wagner, Bodine, Bendele, Teel, Saelao and Price2025). Currently, there are no genome assemblies from ticks collected in the Oriental region (South Asia and Southeast Asia) nor the Neotropical region (Central America and South America) (Figure 2A, Table S3), which have the second and fourth highest number of hard tick species (Guglielmone et al., Reference Guglielmone, Nava and Robbins2023), respectively. It is recommended that the Neotropical and Oriental zoogeographic regions be prioritized in future tick genome projects.

Figure 2.

Biological source material for 54 tick genome assemblies. (A) Geographic origin of the tick material. Two assemblies were generated using ticks from 3 locations. (B) Collection source of the tick material. Laboratory colony ticks are maintained across generations in a lab environment. Laboratory-reared ticks are defined as those collected from the field and maintained in the laboratory until a desired life stage is obtained, not across generations. Field-caught ticks are collected from either the environment or hosts. Tick cell lines are preserved cells, typically derived from embryos. (C) Sample size of the tick material, either an individual tick or pooled ticks. (D) Life stage of the ticks in individual versus pooled material. (E) Sex of the adult ticks in individual versus pooled material. See Table S3 for further details.

Figure 2 Long description

Panel A shows a world map with circular markers indicating the number of tick genome assemblies per location. Marker size represents the count, with larger markers indicating more assemblies. Assemblies are concentrated in North America, Europe and parts of Asia. Panel B is a donut chart showing assemblies by source type: Lab colony 39 percent, Field caught 33 percent, Lab reared 24 percent, Cell line 4 percent. Lab colony is the dominant source. Panel C is a donut chart showing assemblies by sample type: Individual 56 percent, Pool 44 percent, with Individual being more common. Panel D is a stacked bar chart with the vertical axis labeled Percent, ranging from 0 to 100. It compares life stages in Individual and Pooled samples. Adults dominate in Individual, while Eggs are more prevalent in Pooled. Panel E is a stacked bar chart with the vertical axis labeled Percent, ranging from 0 to 100. It compares sex distribution in Individual and Pooled samples. Female is the dominant sex in both categories. The figure summarizes geographic sources and sample metadata breakdowns for tick genome assemblies.

For the collection source of the tick material, the highest number of assemblies are generated from tick colonies (Figure 2B, Table S3). The second highest number of assemblies are generated from ticks caught in the field and the third highest from laboratory-reared ticks that were caught in the field and maintained in the laboratory until a desired life stage had been obtained (Figure 2B, Table S3). The smallest number of assemblies are from tick cell lines (Figure 2B, Table S3). These cell lines are typically created from heterogeneous embryonic cells and maintained indefinitely in a laboratory, which leads to large-scale genome duplications, rearrangements and deletions (Kotsarenko et al., Reference Kotsarenko, Vechtova, Lieskovska, Füssy, Cabral-de-mello, Rego, Alberdi, Collins, Bell-Sakyi, Sterba and Grubhoffer2020). It is recommended that the biological source material for assemblies be obtained from laboratory colonies, laboratory-reared or field-caught.

Tick material has varied in sample size for assemblies, with ∼56% from individual ticks and ∼44% from pooled ticks (Figure 2C, Table S3). For assemblies generated from individuals, all are adult ticks, apart from 3 nymphs (Figure 2D, Table S3). For assemblies generated from pooled tick material, the highest number of assemblies came from eggs (∼46%) (Figure 2D, Table S3). For the assemblies generated from individuals, ∼78% were from adult females (Figure 2E, Table S3), most likely because they generally are larger than males resulting in higher DNA yields. Since 2020, assemblies (contigs) generated from a single individual have been feasible (Tables S2 and S3), often in conjunction with pooled DNA for high-throughput chromosome conformation capture (Hi-C) assembly scaffolding (see De et al., Reference De, Kingan, Kitsou, Portik, Foor, Frederick, Rana, Paulat, Ray, Wang, Glenn and Pal2023). While pooling individual ticks or eggs provides sufficient DNA yield for a variety of sample preparation and sequencing approaches, due to sequence variation amongst individual ticks, pooling ticks leads to a less contiguous assembly (see Cassens et al., Reference Cassens, Villalta, Aguirre, Ecklund, Stenger, Abdi, Venigalla, Shiffman, Bastug, Thielen and Faulk2025). It is recommended to prioritize tick assemblies generated from individual ticks to achieve a high-quality haploid assembly.

Tick whole-genome sequencing and assembly developments from 2011 to 2025

The history of the 54 tick genome assemblies was traced. The first tick assembly (JCVI_ISG_i3_1.0) was for the species Ixodes scapularis, with the assembly publicly available on the NCBI genome database in 2011 (Figure 3, Table S2) and paper published in 2016 (Gulia-Nuss et al., Reference Gulia-Nuss, Nuss, Meyer, Sonenshine, Roe, Waterhouse, Sattelle, de la Fuente, Ribeiro, Megy, Thimmapuram, Miller, Walenz, Koren, Hostetler, Thiagarajan, Joardar, Hannick, Bidwell, Hammond, Young, Zeng, Abrudan, Almeida, Ayllón, Bhide, Bissinger, Bonzon-kulichenko, Buckingham, Caffrey, Caimano, Croset, Driscoll, Gilbert, Gillespie, Giraldo-calderón, Grabowski, Jiang, Khalil, Kim, Kocan, Koci, Kuhn, Kurtti, Lees, Lang, Kennedy, Kwon, Perera, Qi, Radolf, Sakamoto, Sánchez-gracia, Severo, Silverman, Simo, Tojo, Tornador, Van zee, Vázquez, Vieira, Villar, Wespiser, Yang, Zhu, Arensburger, Pietrantonio, Barker, Shao, Zdobnov, Hauser, Grimmelikhuijzen, Park, Rozas, Benton, Pedra, Nelson, Unger, Tubio, Tu, Robertson, Shumway, Sutton, Wortman, Lawson, Wikel, Nene, Fraser, Collins, Birren, Nelson, Caler and Hill2016). This genome project resulted from a 2004 community white paper, with I. scapularis prioritized due to its medical importance in the United States, as the key tick species associated with Lyme disease (Hill and Wikel, Reference Hill and Wikel2005). The JCVI_ISG_i3_1.0 assembly is the only tick assembly to use Sanger dideoxy chain termination on capillary instruments (first-generation sequencing) (Satam et al., Reference Satam, Joshi, Mangrolia, Waghoo, Zaidi, Rawool, Thakare, Banday, Mishra, Das and Malonia2023). The high amount of DNA input required for cloning Sanger sequencing templates required pooling many individual ticks. The resulting modest length reads were unable to produce a highly contiguous assembly due to the high proportion of transposable elements and variation among individuals in the pool.

Figure 3.

Timeline of 54 tick genome assemblies, first release was in 2011. Each point is the assembly release date on a database; up to 5 tick assemblies have been released together. Sequencing platforms are in chronological order, with first generation (Sanger or 454-FLX), second generation (Illumina) and third generation (PacBio or Nanopore). Followed by combinations of sequencing platforms. Integrations to the sequencing platforms were none, RNA-seq alone, Hi-C alone or Hi-C with RNA-seq. See Table S2 for further details.

In the 2010s, tick genome assemblies started using second-generation sequencing. Assemblies CCG_Rmi1.0 and Rmi2.0 of the tick Rhipicephalus microplus used 454-pyrosequencing (Figure 3, Table S2). This sequencing platform obtains millions of ∼500 nt reads at a time, reducing costs compared to Sanger sequencing, but also had limitations in handling repetitive DNA (Satam et al., Reference Satam, Joshi, Mangrolia, Waghoo, Zaidi, Rawool, Thakare, Banday, Mishra, Das and Malonia2023). In 2016, the first tick assembly using the Illumina short read sequencing platform was released (Figure 3, Table S2). Illumina reads are most commonly paired-end 100 or 150 nt (i.e., 200 or 300 nt total), and sequencing is massively paralleled for high throughput, providing higher sequencing coverage (Satam et al., Reference Satam, Joshi, Mangrolia, Waghoo, Zaidi, Rawool, Thakare, Banday, Mishra, Das and Malonia2023). As Illumina uses short reads, it is unable to reliably map or assemble the long repetitive regions present in tick genomes.

In 2017, the first tick assembly using a third-generation sequencing platform, PacBio, was released (Figure 3, Table S2). PacBio has a specialized library preparation (double-stranded DNA is circularized via SMRTbell adapters) and single-molecule sequencing to generate long reads (up to ∼100 kb for single-pass CLR reads or modal length of ∼20 kb when sequenced repeatedly for HiFi reads), which can handle the repetitive genomes of ticks. Initially, PacBio CLR reads were used for tick assemblies to improve contiguity (Miller et al., Reference Miller, Koren, Dilley, Harkins, Stockwell, Shabman and Sutton2018), and Illumina reads were often used in combination to correct uncalled or miscalled bases (Figure 3, Table S2). The current PacBio standard is HiFi reads, which have improved base-calling accuracy and reduced the need for Illumina error correction (Wenger et al., Reference Wenger, Peluso, Rowell, Chang, Hall, Concepcion, Ebler, Fungtammasan, Kolesnikov, Olson, Töpfer, Alonge, Mahmoud, Qian, Chin, Phillippy, Schatz, Myers, DePristo, Ruan, Marschall, Sedlazeck, Zook, Li, Koren, Carroll, Rank and Hunkapiller2019). Between 2020 and 2023, 22 tick assemblies were released, and over half used the PacBio sequencing platform (Figure 3, Table S2).

In 2023, the first tick assembly using the Oxford Nanopore Technologies (hereafter Nanopore) sequencing platform (another third-generation sequencer) was released (Figure 3, Table S2). This platform generates long reads (50 bp to >4 Mbp) in real time via flow cells with nanopores (Branton et al., Reference Branton, Deamer, Marziali, Bayley, Benner, Butler, Di ventra, Garaj, Hibbs, Huang, Jovanovich, Krstic, Lindsay, Ling, Mastrangelo, Meller, Oliver, Pershin, Ramsey, Riehn, Soni, Tabard-cossa, Wanunu, Wiggin and Schloss2008). While Nanopore base-calling accuracy has greatly improved over time, ∼33% of Nanopore tick assemblies have been generated in combination with Illumina short reads to correct base-calling errors (Figure 3, Table S2). In 2024, 20 tick assemblies were released, the most for a single year. These assemblies were ∼40% Nanopore with the remaining using combinations of Nanopore or PacBio, with Illumina (Figure 3, Table S2). By April 2025, 6 assemblies had been released, with 4 using Nanopore (Figure 3). The accuracy of Nanopore reads has now improved sufficiently that Illumina reads are often no longer necessary for error correction(Mostafa, Reference Mostafa2024).

The development of new sequencing methods and platforms has been critical for overcoming the limitations of tick biology (particularly, the large genome sizes and high proportion of repeats), leading to an increasing number of tick genome assemblies. Standalone first-generation sequencing generated ∼4% of tick assemblies, second-generation sequencing ∼20% and third-generation sequencing ∼39% (Figure 3, Table S2). In addition, ∼37% of tick genome assemblies have been generated using combinations of different generation sequencing (Figure 3, Table S2). In summary, advances in sequencing technologies have driven a dramatic recent increase in tick assemblies from 2011 to 2025.

For the 54 tick assemblies, ∼37% used 1 or more integrations (Hi-C or RNA-sequencing) to the sequencing platform. Hi-C is a molecular approach that improves the contiguity of an assembly (Satam et al., Reference Satam, Joshi, Mangrolia, Waghoo, Zaidi, Rawool, Thakare, Banday, Mishra, Das and Malonia2023), which is advantageous for the large and repetitive tick genomes. RNA-seq provides direct evidence of transcription, alongside the DNA coding sequences and isoforms (Guizzo et al., Reference Guizzo, Mans, Pienaar and Ribeiro2023). For the 20 assemblies that used integrations, 55% had both Hi-C and RNA-sequencing, 30% RNA-sequencing alone and 15% Hi-C alone (Figure 3, Table S2). In mid-2020, the first tick assembly with Hi-C integrated was released; since then, ∼26% of assemblies have Hi-C integrated (Figure 3, Table S2).

Lack of standardized annotation of tick genome assemblies

Annotation of genes and repetitive elements (particularly, transposable elements) in tick genome assemblies has not yet been standardized. These non-standardized annotations currently limit the ability to compare the genes and repetitive elements between tick assemblies, even for the same species.

Genome assemblies commonly include gene annotation. Tick assemblies have the number of protein-coding genes reported or the total number of genes reported, sometimes both numbers are reported (Table S2). It is recommended that future tick genome studies report both protein-coding genes and total genes.

Gene annotation has been performed for 30 tick assemblies, representing 18 species (Fig. S2, Table S2). Four common annotation approaches have been used. First, a custom automated gene annotation pipeline created for each assembly, used on 7 tick assemblies, with a median of ∼27 100 total genes and ∼26 400 protein-coding genes (Fig. S2, Table S2). Second, taking a custom automated annotation pipeline with RNA-seq data (either pre-existing or generated alongside the genome assembly) integrated using gene modelling programs (such as AUGUSTUS and BRAKER (Stanke et al., Reference Stanke, Schöffmann, Morgenstern and Waack2006, Reference Stanke, Diekhans, Baertsch and Haussler2008)), used on 20 tick assemblies with a median of ∼28 500 total genes and ∼26 700 protein-coding genes (Fig. S2, Table S2). Third, manual curation preceded by an automated pipeline that integrated RNA-seq and proteome data, used on 1 tick assembly, with ∼22 500 protein-coding genes (Fig. S2, Table S2). Fourth, requesting NCBI to perform a RefSeq automated annotation (NCBI Eukaryotic Genome Annotation Pipeline (Thibaud-Nissen et al., Reference Thibaud-Nissen, Souvorov, Murphy, DiCuccio and Kitts2013)), which incorporates RNA-seq and proteome data from NCBI, used on 7 tick assemblies with a median of ∼27 000 total genes and ∼26 900 protein-coding genes (Fig. S2, Table S2). While 4 gene annotation approaches have been used and resulted in variable gene number estimates, the median number for total genes (15 assemblies) across the 4 approaches is between ∼27 000 and ∼28 500 and protein-coding genes (24 assemblies) is between ∼22 500 and ∼26 900. It is recommended that future tick genome studies integrate transcriptomes and the assembly be submitted to NCBI for annotation to achieve robust gene annotation.

As tick genomes are highly repetitive, annotation of these repetitive elements is important. Repetitive elements have been annotated in 25 tick genome assemblies, representing 15 species (Fig. S3, Table S2). Commonly, repetitive elements are annotated using an automated pipeline, such as one or a combination of RepeatModeler (Flynn et al., Reference Flynn, Hubley, Goubert, Rosen, Clark, Feschotte and Smit2020) and RepeatMasker (Smit et al., Reference Smit, Hubley and Green2015). Automated pipelines used on 22 tick assemblies result in a median of ∼62% repetitive DNA, which, when further classified, is ∼1.7% tandem repeats and ∼59% transposable elements (Fig. S3A, Table S2). In studies where the transposable elements have been further classified, the median is ∼19% class I, ∼3.7% class II and ∼5.1% unclassified (Fig. S3B, Table S2). Manual curation of repetitive elements has been used on 3 Ixodes assemblies from one study (Ronai et al., Reference Ronai, de Paula Baptista, Paulat, Frederick, Azagi, Bakker, Dillon, Sprong, Ray and Glenn2026) with a median of 73% repetitive DNA, comprising ∼4.3% tandem repeats and ∼68% transposable elements (Fig. S3A, Table S2). Further classification of the transposable elements results in a median of ∼32% class I and ∼36% class II (Fig. S3B, Table S2). It is recommended that future tick genome studies perform manual curation of the transposable elements until a robust automated pipeline is established.

Quality assessment of tick genome assemblies

The impact of sequencing platform and integration of Hi-C scaffolding on tick assembly quality, using metrics for contiguity (auN, N50, L50 and L90) and assembly completeness (complete BUSCO scores), was comprehensively assessed. Sanger and 454-FLX sequencing platforms were used for the first 2 tick assemblies ever released (Table S2), generating highly fragmented assemblies (Figure 4A–D, Table S4). While the complete BUSCO score for the Sanger assembly was close to 90%, the 454-FLX partial assembly was close to 0% (Figure 4A–D, Table S5).

Figure 4.

Quality metrics for 54 tick genome assemblies across sequencing platforms. (A) auN (comprehensive metric for contiguity), as auN increases so does assembly quality. (B) Contig N50 (the length of the shortest contig that must be included to cover half an assembly), as N50 increases, fewer longer contigs are used to cover half of the assembly, leading to a higher-quality assembly. (C) L50 (minimal number of contigs that cover 50% of the assembly), as L50 decreases assembly quality can increase, however, the BUSCO score needs to be included in the assessment. (D) L90 (minimal number of contigs that cover 90% of the assembly), as L90 decreases assembly quality can increase, however, the BUSCO score needs to be included in the assessment. Each point is a genome assembly. Sequencing platforms were ordered by first generation (Sanger and 454-FLX), second generation (Illumina) and third generation (PacBio and Nanopore), then followed by sequencing platform combinations. Scaffolding for the sequencing platforms was none or Hi-C. Complete BUSCO score (the sum of the single-copy and duplicated genes that can be completely aligned to the assembly with 1 or more than 1 gene copy present), a higher BUSCO score indicates higher assembly completeness and a higher quality assembly. See Tables S2, S4 and S5 for further details.

Figure 4 Long description

The image contains four scatter plots comparing sequencing platforms based on different metrics. The horizontal axis for all plots is labeled ′Sequencing platform′ with categories: Sanger, 454, Illumina, PacBio, Nanopore, 454 plus Illumina and PacBio, Illumina plus PacBio, Illumina plus Nanopore. The legend indicates scaffolding types: Hi-C (diamond) and None (circle) and BUSCO completeness is shown by grayscale intensity. Plot A shows auN log10 (Mbp) on the vertical axis, ranging from negative 2.8 to 2.6. Plot B displays N50 log10 (Mbp) on the vertical axis, with the same range as the auN plot. Plot C presents L50 log10 (n) on the vertical axis, ranging from 0 to 5. Plot D shows L90 log10 (n) on the vertical axis, ranging from 0 to 6. Platforms with higher auN and N50 also show lower L50 and L90, reinforcing the quality trend. Overall, platforms with Hi-C scaffolding generally exhibit better assembly metrics across all plots.

The Illumina sequencing platform has been used for 12 tick assemblies (Table S2). Only one Illumina assembly (that first constructed a 10X Genomics library) integrated Hi-C, I. ricinus (IXRI_v2), generating the highest quality Illumina tick assembly with a ∼95% complete BUSCO score (Figure 4A–D, Tables S4 and S5). The other 11 Illumina assemblies are more fragmented, and 7 did not produce sufficient reads to cover the genome, resulting in lower complete BUSCO scores of 0 to ∼65% (Figure 4A–D, Tables S4 and S5). Therefore, short read platforms without Hi-C are unlikely to be sufficient to handle the genome complexity of ticks.

The PacBio sequencing platform has been used for 8 tick assemblies, with 2 integrating Hi-C (Table S2). The remaining 6 PacBio assemblies without Hi-C varied in quality (Figure 4A–D, Tables S4 and S5). A combination of PacBio error-corrected with Illumina short reads has been used for 13 tick assemblies (Table S2). Twelve of these assemblies have complete BUSCO scores over 92%, indicating sufficient sequencing coverage of the genome (Figure 4A–D, Tables S4 and S5). Ten of these thirteen assemblies integrated Hi-C, and the three without Hi-C were lower in quality regarding contiguity and coverage (Figure 4A–D, Tables S4 and S5). It is suggested that Hi-C positively impacts assembly contiguity and quality for PacBio tick assemblies, with or without Illumina.

The Nanopore sequencing platform has been used for 12 tick assemblies (Table S2). These assemblies overlap in quality with the Illumina, PacBio and PacBio with Illumina assemblies (Figure 4A–D, Tables S4 and S5). None of the Nanopore assemblies integrated Hi-C (Figure 4A–D). The quality and contiguity of Nanopore assemblies are moderate when compared to the other sequencing platforms. A combination of Nanopore error-corrected with Illumina short reads has been used for 6 tick assemblies (Table S2). The Nanopore with Illumina assemblies had a ∼91% average complete BUSCO value, which was unexpectedly lower than that of the standalone Nanopore assemblies with ∼97% average complete BUSCO (Figure 4A–D, Tables S4 and S5). One of the Nanopore with Illumina assemblies integrated Hi-C, which had higher quality and contiguity compared to those without Hi-C (Figure 4A–D, Tables S4 and S5). The quality of the remaining 5 Nanopore with Illumina assemblies, but without Hi-C, while similar in contiguity had lower complete BUSCO scores compared to the standalone Nanopore tick assemblies (Figure 4A–D, Tables S4 and S5). Therefore, the highest quality Nanopore assembly integrated Hi-C.

Across all the sequencing platform assemblies, integrating Hi-C had higher contiguity, quality and completeness compared to assemblies without Hi-C (Figure 4A–D, Tables S4 and S5). Additionally, assemblies generated by a combination of long-read platforms (PacBio and Nanopore) then error-corrected with Illumina reads had, on average, better contiguity but lower genome completeness compared to those generated by long-read platforms without error-correction, suggesting a trade-off in contiguity versus errors (Figure 4A–D, Tables S4 and S5). In summary, it is recommended that future tick genome assembly projects use long-read sequencing platforms with integration of Hi-C scaffolding to produce high-quality assemblies.

Characterization of high-quality tick assemblies

The quality of the 54 tick genome assemblies was assessed using 4 metrics (number of contigs, contig N50, complete BUSCO score and duplication BUSCO score) to identify 35 high-quality tick genome assemblies that are suitable for downstream analyses (Figure 5). These high-quality assemblies have under 126 000 contigs, a contig N50 over 0.045 Mbp, a complete BUSCO score over 83% and a duplicate BUSCO score under 20% (Figure 5, Tables S4–S6, Fig. S1). The median number of contigs is 8198, contig N50 is 1.589 Mbp, complete BUSCO is 96% and duplicate BUSCO is 2.8%. High-quality assemblies of other arthropod taxa have N50s over 0.01 Mbp and >90% complete BUSCOs (Feron and Waterhouse, Reference Feron and Waterhouse2022). The 35 high-quality tick assemblies have all been generated since 2020 (Figure 3); the sequencing platforms are 14.3% Illumina, 17.1% Nanopore, 17.1% Nanopore + Illumina, 20.0% PacBio and 31.4% PacBio + Illumina (Figure 5, Tables S4–S6). Forty percent of the high-quality tick assemblies integrated Hi-C (Figure 5, Tables S4–S6).

Figure 5.

Quality assessment of 54 tick genome assemblies. Identified 35 high-quality assemblies (dashed line cluster), including a sub-group of 14 highest quality assemblies (dotted line cluster). Each dot is a genome assembly. Contig N50 is the length of the shortest contig that must be included to cover half an assembly, a higher N50 means fewer small contigs, which is a more complete, less fragmented assembly. Number of contigs (greater than 0 bp), fewer contigs typically results in a more contiguous assembly as there is less fragmentation. However, few contigs associated with a low N50 can lead to poor assembly quality. Complete BUSCO score, a higher BUSCO score indicates higher assembly completeness and a higher quality assembly. Duplicate BUSCO score, a lower duplication BUSCO score indicates a higher quality pseudo-haploid assembly. See Tables S4–S6 for further details.

A cluster of 14 tick assemblies that are the highest quality was identified, which have under 17 500 contigs, a contig N50 over 84 Mbp, a complete BUSCO score over 93% and a duplicate BUSCO score less than 10% (Figure 5, Tables S4–S6, Fig. S1). These 14 highest-quality assemblies have all been generated since 2020 (Figure 3); the sequencing platforms are ∼7% Illumina, ∼7% Nanopore + Illumina, ∼21% PacBio and ∼64% PacBio + Illumina (Figure 5, Tables S4–S6). All 14 highest-quality tick assemblies integrated Hi-C, except for the USDA_Rmic assembly (Figure 5, Table S2). The use of comprehensive metrics for the high-quality tick assemblies means future tick assembly projects now have metrics to benchmark against.

Tick species with high-quality genome assemblies

The 35 high-quality genome assemblies represent 21 species of tick (Figure 6). As some species have multiple high-quality assemblies, the best-quality assembly for each of the 21 tick species (Figure 6, Table S6) was determined.

Figure 6.

Assembly total length of the best-quality genome assembly for 21 tick species. The best assembly for each tick species was identified from the high and highest quality assemblies. Tick species were ordered by assembly total length, from smallest to largest. Assemblies are grouped by taxonomic family; the soft tick species (Argasidae) and hard tick species (Ixodidae). See Table S6 for further details.

Figure 6 Long description

The bar graph has a vertical axis labeled Total length left (Mbp) with tick marks from 0 to 3500. The horizontal axis lists tick species names. A legend titled Family lists Argasidae and Ixodidae. Bars increase from left to right. The leftmost bar is near 1100. Many middle bars fall between about 2000 and 2600. The tallest bars at the right end are near 3400.

For the 21 best-quality assemblies, hard ticks have an average assembly length of ∼2390 Mbp and soft ticks ∼1176 Mbp (Figure 6, Table S4). Rhipicephalus spp. have the largest assembly length across all the tick species, with an average of ∼2689 Mbp. The 2 Hyalomma spp. have the smallest assembly lengths for the hard ticks, with an average of ∼1840 Mbp (Figure 6, Table S4). The 2 soft tick Ornithodoros spp. have the smallest assembly lengths for all ticks, with an average of ∼1176 Mbp (Figure 6, Table S4). These reported assembly sizes (length of gapped DNA sequence), however, are not directly equivalent to the ‘genome size’. The average genome size of 7 hard tick species is 2671 Mbp and 2 soft tick species is 1281 Mbp using flow cytometry (Geraci et al., Reference Geraci, Spencer johnston, Paul Robinson, Wikel and Hill2007). Tick assembly size (NCBI assembly size or QUAST assembly total length) is on average 95.5% of the genome size (Table S7), n = 16. Overall, it is hypothesized that hard ticks have larger genomes compared to soft ticks (Figure 6) due to a higher proportion of repetitive elements (Fig. S2A).

The 21 species with high-quality assemblies are 2 soft ticks (Argasidae) and 19 hard ticks (Ixodidae); the hard ticks are 5 Ixodes spp. and 14 non-Ixodes spp. (Table S7). These assemblies are 0.9% (2/216) of soft tick species and 2.4% (19/786) of hard tick species (Mans et al., Reference Mans, Featherston, Kvas, Pillay, De Klerk, Pienaar, De Castro, Schwan, Lopez, Teel, Pérez de león, Sonenshine, Egekwu, Bakkes, Heyne, Kanduma, Nyangiwe, Bouattour and Latif2019; Robbins et al., Reference Robbins, Nava, Ronai, Chong and Guglielmone2025). It is recommended that soft tick species be prioritized for genome sequencing. So far, the tick species sequenced are those of medical and veterinary importance. Therefore, it is also recommended that future tick genome projects prioritize capturing the diversity of tick species.