Skip to main content
Microbiology Resource Announcements logoLink to Microbiology Resource Announcements
. 2022 Dec 21;12(1):e00330-22. doi: 10.1128/mra.00330-22

Mitochondrial Genomes of the American Dog Tick (Dermacentor variabilis) Isolated from Horses in the Midwestern United States

Samantha Reynolds a, Makaela Hedberg a, Brian Herrin a, Jeba R J Jesudoss Chelladurai a,
Editor: Jason E Stajichb
PMCID: PMC9872707  PMID: 36541790

ABSTRACT

Here, we report two complete and three partial mitochondrial genome sequences of Dermacentor variabilis specimens collected from horses in the United States. The complete genomes are 14,837 bp long and contain 13 protein-coding genes, 2 rRNA genes, and 22 tRNA genes. The sequences have been deposited under GenBank accession numbers ON052120 to ON052124.

ANNOUNCEMENT

Dermacentor variabilis (Say, 1821) is an important ectoparasite that is capable of parasitizing a wide variety of mammals, including humans. It is distributed discontinuously from southern Canada to the Gulf Coast of Mexico and can expand further due to climate change (1, 2). It is an important vector of Rickettsia rickettsii (3), other Rickettsia species (4), Francisella tularensis (5) and is an experimental vector of Cytauxzoon felis (6). Despite its importance, complete mitochondrial genomes of only two isolates, from Georgia, USA (GenBank accession number MN165636.1), and Oklahoma, USA (GenBank accession number MN175686.1), have been sequenced. To contribute to larger phylogeographic efforts, we present two complete mitochondrial genome sequences of Dermacentor variabilis specimens isolated from horses in Wisconsin, USA, and three partial mitochondrial genome sequences of specimens from Kansas and Illinois, USA.

Dermacentor variabilis adults were isolated from the pelage of horses as part of the National Equine Tick Survey (7) and identified using established keys (8). Exoskeletons are retained as voucher specimens (accession numbers DvarWI152-3, DvarWI152-4, DvarIL245-1, DvarIL245-2, and DvarKSKon15) at the Kansas State University College of Veterinary Medicine. Genomic DNA was extracted from the specimens using the DNeasy blood and tissue kit (Qiagen). Complete mitochondrial genomes were amplified as two overlapping fragments, L3 and L4, using primers GCTAKTGGGTTCATACCCCAA, CGACCTCGATGTTGGATTAGGA, CCAACCTGATTCWCATCGGTCT, and TCATCGCGGTAAAATGACTGA (annealing temperature 55°C) as described previously (9). Amplicons were fragmented, sequencing libraries were prepared using the NEBNext Ultra DNA library preparation kit (New England Biolabs), and libraries were pooled and sequenced on an Illumina MiSeq instrument in paired-end 150-bp read mode. An average of 100,710 paired-end reads were generated for each sample. Sequences were analyzed with FastQC v0.73 (10), adapters were trimmed using Trimmomatic v0.38.1 (11), and sequences were mapped to the reference genome (GenBank accession number NC_061217.1) using Minimap2 v2.24 (12). Consensus sequences were extracted using the Integrative Genomics Viewer (IGV) v2.12.3 (13) based on parameters described previously (14). The average coverage was 577× for the complete mitochondrial sequences. Annotation was performed using Mitos v2 (15).

The complete mitochondrial genomes are 14,837 bp and contain 13 protein-coding genes, 22 tRNA genes, and 2 control regions. Nine genes (nad2, cox1, cox2, atp8, atp6, cox3, nad3, nad6, and cytb) are encoded on the positive strand and four (nad1, nad5, nad4, and nad4L) on the negative strand. The GC content is low at 21.3%, typical of metastriate mitochondrial genomes (16). Comparison of the complete mitochondrial genomes revealed similarity of 99.18% between the Wisconsin isolate and the reference Georgia isolate (GenBank accession number NC_061217.1).

Sequences for 13 protein-coding genes and 2 rRNA genes obtained in this study and a selected set of tick sequences from GenBank were compiled. Individual gene sequences were aligned with MAFFT (17), trimmed with trimAI (18), and concatenated in the same order as in the genome. A 15-gene maximum likelihood phylogenetic tree was created using PhyML-SMS (19, 20) and included 11,746 bp of concatenated nucleotides (Fig. 1). Dermacentor variabilis forms a monophyletic clade with a high level of support.

FIG 1.

FIG 1

Maximum likelihood phylogenetic tree of 15 mitochondrial genes (13 protein-coding genes and 2 rRNA genes) constructed with the GTR+G+I model in PhyML to infer the relationship of Dermacentor variabilis to other selected tick species in the family Ixodidae (GenBank accession numbers precede biological names). There were 11,746 bp in the final data set. Complete mitochondrial genomes from this study are marked with black diamonds and partial mitochondrial genomes with white diamonds.

Data availability.

The mitochondrial genome sequences from the study have been deposited in GenBank under the accession numbers ON052120 to ON052124. Raw reads have been deposited under NCBI BioProject accession number PRJNA885479 and SRA accession numbers SRX17751554 to SRX17751558.

ACKNOWLEDGMENTS

This work was supported by a grant from the National Center for Veterinary Parasitology and start-up funds from the Kansas State University College of Veterinary Medicine.

Contributor Information

Jeba R. J. Jesudoss Chelladurai, Email: jebaj@vet.k-state.edu.

Jason E. Stajich, University of California, Riverside

REFERENCES

  • 1.Minigan JN, Hager HA, Peregrine AS, Newman JA. 2018. Current and potential future distribution of the American dog tick (Dermacentor variabilis, Say) in North America. Ticks Tick Borne Dis 9:354–362. doi: 10.1016/j.ttbdis.2017.11.012. [DOI] [PubMed] [Google Scholar]
  • 2.Boorgula GDY, Peterson AT, Foley DH, Ganta RR, Raghavan RK. 2020. Assessing the current and future potential geographic distribution of the American dog tick, Dermacentor variabilis (Say) (Acari: Ixodidae) in North America. PLoS One 15:e0237191. doi: 10.1371/journal.pone.0237191. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Gage KL, Schrumpf ME, Karstens RH, Burgdorfer W, Schwan TG. 1994. DNA typing of rickettsiae in naturally infected ticks using a polymerase chain reaction/restriction fragment length polymorphism system. Am J Trop Med Hyg 50:247–260. doi: 10.4269/ajtmh.1994.50.247. [DOI] [PubMed] [Google Scholar]
  • 4.Hecht JA, Allerdice MEJ, Dykstra EA, Mastel L, Eisen RJ, Johnson TL, Gaff HD, Varela-Stokes AS, Goddard J, Pagac BB, Paddock CD, Karpathy SE. 2019. Multistate survey of American dog ticks. Vector Borne Zoonotic Dis 19:652–657. doi: 10.1089/vbz.2018.2415. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Goethert HK, Telford SR. 2009. Nonrandom distribution of vector ticks (Dermacentor variabilis) infected by Francisella tularensis. PLoS Pathog 5:e1000319. doi: 10.1371/journal.ppat.1000319. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Blouin EF, Kocan AA, Glenn BL, Kocan KM, Hair JA. 1984. Transmission of Cytauxzoon felis Kier, 1979 from bobcats, Felis rufus (Schreber), to domestic cats by Dermacentor variabilis (Say). J Wildl Dis 20:241–242. doi: 10.7589/0090-3558-20.3.241. [DOI] [PubMed] [Google Scholar]
  • 7.Hedberg M, Gigliotti J, Herrin BH. 2021. Regional variations and patterns of infestation of ticks from horses across the United States. American Association of Veterinary Parasitologists Conference, Lexington, KY.
  • 8.Yunker CE, Keirans JE, Clifford CM, Easton ER. 1986. Dermacentor ticks (Acari, Ixodoidea, Ixodidae) of the New-World: a scanning electron-microscope atlas. Proc Entomol Soc Washington 88:609–627. [Google Scholar]
  • 9.Chen Z, Xuan Y, Liang G, Yang X, Yu Z, Barker SC, Kelava S, Bu W, Liu J, Gao S. 2020. Precise annotation of tick mitochondrial genomes reveals multiple copy number variation of short tandem repeats and one transposon-like element. BMC Genomics 21:488. doi: 10.1186/s12864-020-06906-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Andrews S. 2010. FastQC: a quality control tool for high throughput sequence data. https://www.bioinformatics.babraham.ac.uk/projects/fastqc.
  • 11.Bolger AM, Lohse M, Usadel B. 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120. doi: 10.1093/bioinformatics/btu170. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Li H. 2018. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34:3094–3100. doi: 10.1093/bioinformatics/bty191. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G, Mesirov JP. 2011. Integrative Genomics Viewer. Nat Biotechnol 29:24–26. doi: 10.1038/nbt.1754. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Cavener DR. 1987. Comparison of the consensus sequence flanking translational start sites in Drosophila and vertebrates. Nucleic Acids Res 15:1353–1361. doi: 10.1093/nar/15.4.1353. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Donath A, Jühling F, Al-Arab M, Bernhart SH, Reinhardt F, Stadler PF, Middendorf M, Bernt M. 2019. Improved annotation of protein-coding genes boundaries in metazoan mitochondrial genomes. Nucleic Acids Res 47:10543–10552. doi: 10.1093/nar/gkz833. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Wang T, Zhang S, Pei T, Yu Z, Liu J. 2019. Tick mitochondrial genomes: structural characteristics and phylogenetic implications. Parasit Vectors 12:451. doi: 10.1186/s13071-019-3705-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Katoh K, Standley DM. 2013. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 30:772–780. doi: 10.1093/molbev/mst010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Capella-Gutiérrez S, Silla-Martínez JM, Gabaldón T. 2009. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25:1972–1973. doi: 10.1093/bioinformatics/btp348. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, Gascuel O. 2010. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol 59:307–321. doi: 10.1093/sysbio/syq010. [DOI] [PubMed] [Google Scholar]
  • 20.Lefort V, Longueville JE, Gascuel O. 2017. SMS: Smart Model Selection in PhyML. Mol Biol Evol 34:2422–2424. doi: 10.1093/molbev/msx149. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The mitochondrial genome sequences from the study have been deposited in GenBank under the accession numbers ON052120 to ON052124. Raw reads have been deposited under NCBI BioProject accession number PRJNA885479 and SRA accession numbers SRX17751554 to SRX17751558.


Articles from Microbiology Resource Announcements are provided here courtesy of American Society for Microbiology (ASM)

RESOURCES