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A high-quality Ixodes scapularis genome advances tick science

Nature Genetics volume 55, pages 301–311 (2023)Cite this article

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Abstract

Ixodes spp. and related ticks transmit prevalent infections, although knowledge of their biology and development of anti-tick measures have been hindered by the lack of a high-quality genome. In the present study, we present the assembly of a 2.23-Gb Ixodes scapularis genome by sequencing two haplotypes within one individual, complemented by chromosome-level scaffolding and full-length RNA isoform sequencing, yielding a fully reannotated genome featuring thousands of new protein-coding genes and various RNA species. Analyses of the repetitive DNA identified transposable elements, whereas the examination of tick-associated bacterial sequences yielded an improved Rickettsia buchneri genome. We demonstrate how the Ixodes genome advances tick science by contributing to new annotations, gene models and epigenetic functions, expansion of gene families, development of in-depth proteome catalogs and deciphering of genetic variations in wild ticks. Overall, we report critical genetic resources and biological insights impacting our understanding of tick biology and future interventions against tick-transmitted infections.

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Fig. 1: Assembly of high-quality I. scapularis genome.
Fig. 2: Annotation and analyses of I. scapularis genome.
Fig. 3: Chromosome-level assembly of scaffolds and analyses of gene clusters.
Fig. 4: Ash2 is required for early tick gut development during feeding.
Fig. 5: R. buchneri genome assembly and annotation.
Fig. 6: Variations in tick population genetic structures as assessed by RAD-seq.
Fig. 7: Whole-body proteome analysis of I. scapularis over the course of feeding and adult development.

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Data availability

All sequence data and genome assembly data are deposited into NCBI under BioProject accession no. PRJNA678334. The assembly information is available in the following link: https://www.ncbi.nlm.nih.gov/data-hub/genome/GCF_016920785.2/. The data are also available through VEuPathDB (VectorBase release 59, 30 August 2022) using the following link: https://vectorbase.org/vectorbase/app/record/dataset/DS_bb84a3ee55. All other datasets generated and analyzed during the present study are available in the Supplementary information or the source data provided with this paper.

Code availability

All data processing and analyses were performed by existing software packages, which are either available publicly from the internet or previous publications, as detailed in the Methods and the Nature Portfolio Reporting Summary. No customized code or software was used for any aspect of data processing or analysis.

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Acknowledgements

We thank K. Nassar for her assistance with the preparation of the manuscript. We thank PacBio for providing part of the reagents for DNA-seq. We deeply appreciate the assistance of I. Liachko and M. Wood with the Hi-C analyses. The present study was supported by grants from the National Institute of Allergy and Infectious Diseases (award nos. R01AI080615, R01AI116620 and P01AI138949 to U.P.) and the National Institute of Dental and Craniofacial Research (grant no. ZIA DE000751 to Y.W.).

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Author notes

  1. These authors contributed equally: Sandip De, Sarah B. Kingan, Chrysoula Kitsou.

Authors and Affiliations

  1. Department of Veterinary Medicine, University of Maryland, College Park, MD, USA

    Sandip De, Chrysoula Kitsou, Shelby D. Foor, Vipin S. Rana & Utpal Pal

  2. Pacific Biosciences, Menlo Park, CA, USA

    Sarah B. Kingan & Daniel M. Portik

  3. Department of Environmental Health Science, University of Georgia, Athens, GA, USA

    Julia C. Frederick & Travis C. Glenn

  4. Department of Biological Sciences, Texas Tech University, Lubbock, TX, USA

    Nicole S. Paulat & David A. Ray

  5. Mass Spectrometry Facility, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA

    Yan Wang

  6. Institute of Bioinformatics, University of Georgia, Athens, GA, USA

    Travis C. Glenn

  7. Virginia-Maryland College of Veterinary Medicine, College Park, MD, USA

    Utpal Pal

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Contributions

S.D., S.B.K., C.K., D.M.P. and U.P. designed research, carried out experiments, analyzed data, prepared figures and wrote part of the manuscript. S.D.F., J.C.F., V.S.R. and N.S.P. carried out experiments, analyzed data and prepared text and figures. Y.W. assisted with the MS experiments, analyzed data and prepared figures. D.A.R. supervised experiments, analyzed data and wrote part of the manuscript. T.C.G. supervised experiments, provided reagents, analyzed data and wrote part of the manuscript. U.P. conceived and designed experiments, supervised the study, prepared figures and wrote the paper with critical input from all authors. C.K. is a recipient of Blackman Postdoctoral Fellowship from Global Lyme Alliance.

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Correspondence to Utpal Pal.

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S.B.K. is an employee and shareholder of Pacific Biosciences. No other authors declare any competing interests.

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Nature Genetics thanks Wu-Chun Cao, Abhijeet Nayak and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Roles of Set1 and NSD2 in tick biology.

a,b, Comparisons of the Set1 and NSD2 gene models by VectorBase (blue) and NCBI (green). Raw Iso-Seq reads are shown in the bottom (grey). c, RT-qPCR analysis of Set1 and NSD2 RNA in unfed, 8 h-, 24 h-, 48 h- and 72 h-fed ticks post placement on naïve mice. Error bars show the mean with SEM from four biological replicates. d, RT-qPCR analysis of Set1 and NSD2 RNA in 8 h-fed ticks post placement on naïve mice. Separate groups of ticks were injected with dsGFP, dsSet1, or dsNSD2. Error bars show the mean with SEM from four biological replicates (n = 4); two-tailed Mann–Whitney U-test. e, Impact of RNAi on tick engorgement time during feeding. The percentage of ticks collected after 96, 120, 144, and 168 h of tick placement on mice are shown. Error bars denote the mean with SEM from three biological replicates. f, Impact of RNAi on tick engorgement success. The total percentage of ticks collected after completion of tick feeding is shown. Error bars denote the mean with SEM from three biological replicates (n = 3); Student’s t-test. g, Impact of RNAi on tick weight. The weights of fully engorged ticks (mg) are shown, with each data point representing one nymph. Error bars denote the mean with SEM from three biological replicates of 25 ticks from each group; two-tailed Mann–Whitney U-test. h, Impact of RNAi on tick molting. The percentage of fully engorged nymphs that molted into adult ticks is shown. Error bars denote the mean with SEM from three biological replicates (n = 3); Student’s t-test.

Extended Data Fig. 2 Ash2 immunization and roles in tick biology.

a, Ash2 immunization does not affect tick feeding. The upper left panel shows the percentage of ticks collected after 96 and 120 h of feeding after placement on phosphate-buffered saline (PBS)- or Ash2-immunized mice; the upper right panel shows the total percentage of engorged ticks collected after the completion of feeding on PBS- and Ash2-immunized mice. Error bars denote the mean with SEM of three biological replicates, with 25 ticks per group (two-tailed Mann–Whitney U-test). The lower left panel denotes the weights of fully engorged ticks (mg). Each data point represents a single tick collected (n = 75) from three biological replicates; two-tailed Mann–Whitney U-test. The lower right panel shows the percentage of fully engorged nymphs that molted into adult ticks after feeding on PBS-immunized and Ash2-immunized mice. Error bars denote the mean with SEM (n = 4 biological replicates, each with 25 ticks per group); two-tailed Mann–Whitney U-test. b, Comparison of the amino acid sequences of the SPRY domains (left panel) and ZFD domains (right panel) from human, I. scapularis, D. melanogaster, A. gambiae, and A. aegypti Ash2 proteins. The human has three Ash2 protein isoforms, while the tick, Drosophila, A. gambiae, and A. aegypti each have two Ash2 isoforms. Human Ash2 isoforms do not contain any ZFDs. c, Staining of dsGFP and dsash2 groups representing 8 h-fed and 48 h-fed tick guts with anti-PH3 antibody (arrow) and DAPI. The insets show zoomed-in pictures of the tick gut cells. The PH3 positive nuclei are less apparent in Ash2-deficient tick gut. The experiment was repeated independently three times with similar results. White bar = 20 µm.

Extended Data Fig. 3 Variations in tick population genetic structures as assessed by RAD-Seq.

a,b, DAPC plot and locations of tick collection and the tick cell line. The maps were created in R scripts using open-source data for the U.S. political boundaries. c, Genetic distance tree depicts the phylogenetic relationship between ticks collected from target geographical areas and ISE6 cells.

Supplementary information

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Supplementary Notes 1–7, Methods, Figs. 1–4 and Tables 1–28.

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Source data

Source Data Fig. 4

Unprocessed western blot corresponding to Fig. 4f.

Source Data Fig. 7

Spreadsheet showing full list of identified proteins for Fig. 7.

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De, S., Kingan, S.B., Kitsou, C. et al. A high-quality Ixodes scapularis genome advances tick science. Nat Genet 55, 301–311 (2023). https://doi.org/10.1038/s41588-022-01275-w

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