Search for: All records

Phytoplasmas are a group of plant-pathogenic, cell-wall-less bacteria vectored primarily by leafhoppers (Hemiptera Cicadellidae), one of the most diverse families of insects. Despite the importance of documenting associations between phytoplasmas, their insect vectors, and plant hosts to prevent disease outbreaks, such knowledge is currently highly incomplete and largely neglects the diversity of the system in natural areas. Here, we used anchored hybrid enrichment (AHE) to recover the DNA of five plant genes (rbcL, matK, ITS1, ITS2, and trnH-psbA) in 58 phloem-feeding leafhoppers from around the world that had previously tested positive for phytoplasma infection. Using BLASTn and a strict filtering approach, we assigned taxonomic classifications to the plant sequences and tested for cophylogenetic signals between potential Deltocephalinae leafhopper vectors and their associated plants. We observed incongruence between plant and insect phylogenies. Many leafhopper species, including presumed grass specialists, fed on distantly related plant lineages; 66% of sampled leafhoppers fed on plants from at least two different orders. By disentangling phytoplasma–leafhopper–plant interactions, we identify locations at risk of phytoplasma disease outbreaks. Furthermore, the observed wide diet breadth raises questions about how phytoplasma infection may manipulate the feeding preference of their insect host and helps fill the gaps in understanding the ecology and diversification of the tripartite association. 

Based on study of the holotype of Scaphytopius (Tumeus) rubidus DeLong, 1980, it was determined that this species does not belong in any genus of the subfamily Deltocephalinae described so far. To accommodate this species, we describe and illustrate a new genus in the tribe Bahitini, Anavilhanas gen. nov., and propose the new combination, Anavilhanas rubida (DeLong) comb. nov. 

Large systematic revisionary projects incorporating data for hundreds or thousands of taxa require an integrative approach, with a strong biodiversity-informatics core for efficient data management to facilitate research on the group. Our original biodiversity informatics platform, 3i (Internet-accessible Interactive Identification) combined a customized MS Access database backend with ASP-based web interfaces to support revisionary syntheses of several large genera of leafhopers (Hemiptera: Auchenorrhyncha: Cicadellidae). More recently, for our National Science Foundation sponsored project, “GoLife: Collaborative Research: Integrative genealogy, ecology and phenomics of deltocephaline leafhoppers (Hemiptera: Cicadellidae), and their microbial associates”, we selected the new open-source platform TaxonWorks as the cyberinfrastructure. In the scope of the project, the original “3i World Auchenorrhyncha Database” was imported into TaxonWorks. At the present time, TaxonWorks has many tools to automatically import nomenclature, citations, and specimen based collection data. At the time of the initial migration of the 3i database, many of those tools were still under development, and complexity of the data in the database required a custom migration script, which is still probably the most efficient solution for importing datasets with long development history. At the moment, the World Auchenorrhyncha Database comprehensively covers nomenclature of the group and includes data on 70 valid families, 6,816 valid genera, 47,064 valid species as well as synonymy and subsequent combinations (Fig. 1). In addition, many taxon records include the original citation, bibliography, type information, etymology, etc. The bibliography of the group includes 37,579 sources, about 1/3 of which are associated with PDF files. Species have distribution records, either derived from individual specimens or as country and state level asserted distribution, as well as biological associations indicating host plants, predators, and parasitoids. Observation matrices in TaxonWorks are designed to handle morphological data associated with taxa or specimens. The matrices may be used to automatically generate interactive identification keys and taxon descriptions. They can also be downloaded to be imported, for example, into Lucid builder, or to perform phylogenetic analysis using an external application. At the moment there are 36 matrices associated with the project. The observation matrix from GoLife project covers 798 taxa by 210 descriptors (most of which are qualitative multi-state morphological descriptors) (Fig. 2). Illustrations are provided for 9,886 taxa and organized in the specialized image matrix and could be used as a pictorial key for determination of species and taxa of a higher rank. For the phylogenetic analysis, a dataset was constructed for 730 terminal taxa and >160,000 nucleotide positions obtained using anchored hybrid enrichment of genomic DNA for a sample of leafhoppers from the subfamily Deltocephalinae and outgroups. The probe kit targets leafhopper genes, as well as some bacterial genes (endosymbionts and plant pathogens transmitted by leafhoppers). The maximum likelihood analyses of concatenated nucleotide and amino acid sequences as well as coalescent gene tree analysis yielded well-resolved phylogenetic trees (Cao et al. 2022). Raw sequence data have been uploaded to the Sequence Read Archive on GenBank. Occurrence and morphological data, as well as diagnostic images, for voucher specimens have been incorporated into TaxonWorks. Data in TaxonWorks could be exported in raw format, get accessed via Application Programming Interface (API), or be shared with external data aggregators like Catalogue of Life, GBIF, iDigBio. 

The grassland leafhopper genus Aconurella is widespread in the Old World. Species of this genus are difficult to identify by traditional morphological characters but the morphology-based species classification in this genus has not previously been tested using molecular data. This study analysed DNA sequence data from two mitochondrial genes (COI, 16S) and one nuclear gene (ITS2) to infer the phylogenetic relationships and status of five previously recognized Aconurella species and compare the performance of different molecular species-delimitation methods using single and multiple loci. The analysis divided the included haplotypes into five well-supported subclades, most corresponding to existing morphology-based species concepts. However, different molecular species delimitation methods (jMOTU, ABGD, bPTP, GMYC and BPP) yielded somewhat different results, suggesting the presence of between 4 and 8 species, sometimes lumping the haplotypes of Aconurella diplachnis and Aconurella sibirica into a single species or recognizing multiple putative species within Aconurella prolixa. Considering the different results yielded by various methods employing single loci, the BPP method, which combines data from multiple loci, may be more reliable for delimiting species of Aconurella. Our results suggest that the morphological characters previously used to identify these species are reliable and adequately reflect boundaries between genetically distinct taxa. 

Despite several decades’ effort to detect and identify phytoplasmas (Mollicutes) using PCR and Sanger sequencing focusing on diseased plants, knowledge of phytoplasma biodiversity and vector associations remains highly incomplete. To improve protocols for documenting phytoplasma diversity and ecology, we used DNA extracted from phloem-feeding insects and compared traditional Sanger sequencing with a next-generation sequencing method, Anchored Hybrid Enrichment (AHE) for detecting and characterizing phytoplasmas. Among 22 of 180 leafhopper samples that initially tested positive for phytoplasmas using qPCR, AHE yielded phytoplasma 16Sr sequences for 20 (19 complete and 1 partial sequence) while Sanger sequencing yielded sequences for 16 (11 complete and 5 partial). AHE yielded phytoplasma sequences for an additional 7 samples (3 complete and 4 partial) that did not meet the qPCR threshold for phytoplasma positivity or yielded non-phytoplasma sequences using Sanger sequencing. This suggests that AHE is more efficient for obtaining phytoplasma sequences. Twenty-three samples with sufficient data were classified into eight 16Sr subgroups (16SrI-B, I-F, I-AO, III-U, V-C, IX-J, XI-C, XXXVII-A), three new subgroups (designated as 16SrVI-L, XV-D, XI-G) and three possible new groups. Our results suggest that screening phloem-feeding insects using qPCR and AHE sequencing may be the most efficient method for discovering new phytoplasmas. 

Reliable host plant records are available for only a small fraction of herbivorous insect species, despite their potential agricultural importance. Most available data on insect–plant associations have been obtained through field observations of occurrences of insects on particular plants. Molecular methods have more recently been used to identify potential host plants using DNA extracted from insects, but most prior studies using these methods have focused on chewing insects that ingest tissues expected to contain large quantities of plant DNA. Screening of Illumina data obtained from sap feeders of the hemipteran family Cicadellidae (leafhoppers) using anchored hybrid enrichment indicates that, despite feeding on plant fluids, these insects often contain detectable quantities of plant DNA. Although inclusion of probes for bacterial 16S in the original anchored hybrid probe kit yielded relatively high detection rates for chloroplast 16S, the Illumina short reads also, in some cases, included DNA for various plant barcode genes as “by-catch”. Detection rates were generally only slightly higher for Typhlocybinae, which feed preferentially on parenchyma cell contents, compared to other groups of leafhoppers that feed preferentially on phloem or xylem. These results indicate that next-generation sequencing provides a powerful tool to investigate the specific association between individual insect and plant species.