Dataset Information

Phylogeny of hard- and soft-tick taxa (Acari: Ixodida) based on mitochondrial 16S rDNA sequences.

ABSTRACT: Ticks are parasitiform mites that are obligate hematophagous ectoparasites of amphibians, reptiles, birds, and mammals. A phylogeny for tick families, subfamilies, and genera has been described based on morphological characters, life histories, and host associations. To test the existing phylogeny, we sequenced approximately 460 bp from the 3' end of the mitochondrial 16S rRNA gene (rDNA) in 36 hard- and soft-tick species; a mesostigmatid mite, Dermanyssus gallinae, was used as an outgroup. Phylogenies derived using distance, maximum-parsimony, or maximum-likelihood methods were congruent. The existing phylogeny was largely supported with four exceptions. In hard ticks (Ixodidae), members of Haemaphysalinae were monophyletic with the primitive Amblyomminae and members of Hyalomminae grouped within the Rhipicephalinae. In soft ticks (Argasidae), the derived phylogeny failed to support a monophyletic relationship among members of Ornithodorinae and supported placement of Argasinae as basal to the Ixodidae, suggesting that hard ticks may have originated from an Argas-like ancestor. Because most Argas species are obligate bird octoparasites, this result supports earlier suggestions that hard ticks did not evolve until the late Cretaceous.

SUBMITTER: Black WC

PROVIDER: S-EPMC44952 | biostudies-other | 1994 Oct

REPOSITORIES: biostudies-other

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Phylogeny of hard- and soft-tick taxa (Acari: Ixodida) based on mitochondrial 16S rDNA sequences.

Black W C WC Piesman J J

Proceedings of the National Academy of Sciences of the United States of America 19941001 21

Ticks are parasitiform mites that are obligate hematophagous ectoparasites of amphibians, reptiles, birds, and mammals. A phylogeny for tick families, subfamilies, and genera has been described based on morphological characters, life histories, and host associations. To test the existing phylogeny, we sequenced approximately 460 bp from the 3' end of the mitochondrial 16S rRNA gene (rDNA) in 36 hard- and soft-tick species; a mesostigmatid mite, Dermanyssus gallinae, was used as an outgroup. Phyl ...[more]

PMID: 7937832

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Project description:BackgroundThe 5' region of cytochrome oxidase I (COI) is the standard marker for DNA barcoding. However, COI has proved to be of limited use in identifying some species, and for some taxa, the coding sequence is not efficiently amplified by PCR. These deficiencies lead to uncertainty as to whether COI is the most suitable barcoding fragment for species identification of ticks.MethodsIn this study, we directly compared the relative effectiveness of COI, 16S ribosomal DNA (rDNA), nuclear ribosomal internal transcribed spacer 2 (ITS2) and 12S rDNA for tick species identification. A total of 307 sequences from 84 specimens representing eight tick species were acquired by PCR. Besides the 1,834 published sequences of 189 tick species from GenBank and the Barcode of Life Database, 430 unpublished sequences representing 59 tick species were also successfully screened by Bayesian analyses. Thereafter, the performance of the four DNA markers to identify tick species was evaluated by identification success rates given by these markers using nearest neighbour (NN), BLASTn, liberal tree-based or liberal tree-based (+threshold) methods.ResultsGenetic divergence analyses showed that the intra-specific divergence of each marker was much lower than the inter-specific divergence. Our results indicated that the rates of correct sequence identification for all four markers (COI, 16S rDNA, ITS2, 12S rDNA) were very high (> 96%) when using the NN methodology. We also found that COI was not significantly better than the other markers in terms of its rate of correct sequence identification. Overall, BLASTn and NN methods produced higher rates of correct species identification than that produced by the liberal tree-based methods (+threshold or otherwise).ConclusionsAs the standard DNA barcode, COI should be the first choice for tick species identification, while 16S rDNA, ITS2, and 12S rDNA could be used when COI does not produce reliable results. Besides, NN and BLASTn are efficient methods for species identification of ticks.

Project description:BACKGROUND:Close relationships between ticks and microbial communities are important for tick fitness and pathogen colonization and transmission. Haemaphysalis longicornis, distributed widely in China, can carry and transmit various pathogens and pose serious damages to public health and economics. However, little is known about the broader array of microbial communities and symbionts in H. longicornis under natural conditions. In the present study, we investigated the composition of bacterial communities associated with H. longicornis and evaluated the putative symbionts. METHODS:The eubacterial 16S rRNA gene clone libraries of H. longicornis were constructed and analyzed by restriction fragment length polymorphism (RFLP) and DNA sequencing. In addition, diagnostic PCR was performed to assess the prevalence, vertical transmission and infection sites of the symbionts in H. longicornis. RESULTS:Vertically-transmitted symbionts, potential pathogens and allochthonous nonpathogenic bacteria were identified from the field-collected H. longicornis. Three types of symbionts (Coxiella-like, Arsenophonus-like and Rickettsia-like symbionts) were identified in a single host simultaneously. A series of analyses revealed the vertical transmission, prevalence, and infection sites of these symbionts. However, only Coxiella-like bacteria were transmitted stably in the laboratory-reared ticks. In addition, we identified a novel Coxiella-like agent with 95.31% sequence similarity to the taxon described previously. CONCLUSIONS:The present study demonstrated that natural H. longicornis harboured a diverse array of microbial communities. Three types of symbionts were identified in a single host simultaneously. Moreover, high prevalence, vertical transmission and the infection sites supported an obligate symbiotic association between Coxiella symbiont and its host. The role of Coxiella symbiont in the host fitness and the interaction among microbial communities remained to be elucidated. Our investigation of microbial communities in the ticks revealed the complexity of ecological interactions between host and microbe and provided insight for the biological control of ticks.

Project description:BACKGROUND:Shotgun metagenomic sequencing reveals the potential in microbial communities. However, lower-cost 16S ribosomal RNA (rRNA) gene sequencing provides taxonomic, not functional, observations. To remedy this, we previously introduced Piphillin, a software package that predicts functional metagenomic content based on the frequency of detected 16S rRNA gene sequences corresponding to genomes in regularly updated, functionally annotated genome databases. Piphillin (and similar tools) have previously been evaluated on 16S rRNA data processed by the clustering of sequences into operational taxonomic units (OTUs). New techniques such as amplicon sequence variant error correction are in increased use, but it is unknown if these techniques perform better in metagenomic content prediction pipelines, or if they should be treated the same as OTU data in respect to optimal pipeline parameters. RESULTS:To evaluate the effect of 16S rRNA sequence analysis method (clustering sequences into OTUs vs amplicon sequence variant error correction into amplicon sequence variants (ASVs)) on the ability of Piphillin to predict functional metagenomic content, we evaluated Piphillin-predicted functional content from 16S rRNA sequence data processed through OTU clustering and error correction into ASVs compared to corresponding shotgun metagenomic data. We show a strong correlation between metagenomic data and Piphillin-predicted functional content resulting from both 16S rRNA sequence analysis methods. Differential abundance testing with Piphillin-predicted functional content exhibited a low false positive rate (< 0.05) while capturing a large fraction of the differentially abundant features resulting from corresponding metagenomic data. However, Piphillin prediction performance was optimal at different cutoff parameters depending on 16S rRNA sequence analysis method. Using data analyzed with amplicon sequence variant error correction, Piphillin outperformed comparable tools, for instance exhibiting 19% greater balanced accuracy and 54% greater precision compared to PICRUSt2. CONCLUSIONS:Our results demonstrate that raw Illumina sequences should be processed for subsequent Piphillin analysis using amplicon sequence variant error correction (with DADA2 or similar methods) and run using a 99% ID cutoff for Piphillin, while sequences generated on platforms other than Illumina should be processed via OTU clustering (e.g., UPARSE) and run using a 96% ID cutoff for Piphillin. Piphillin is publicly available for academic users (Piphillin server. http://piphillin.secondgenome.com/.).

Dataset Information

Phylogeny of hard- and soft-tick taxa (Acari: Ixodida) based on mitochondrial 16S rDNA sequences.

Publications

Phylogeny of hard- and soft-tick taxa (Acari: Ixodida) based on mitochondrial 16S rDNA sequences.

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