bioRxivEvolutionary Biology
Host phylogeny and ecological associations best explain Wolbachia host shifts in scale insects
E. Sanaei, G. F. Albery, Y. K. Yeoh, Y. P. Lin, L. G. Cook, J. Engelstaedter
Abstract
Wolbachia are among the most prevalent and widespread endosymbiotic bacteria on earth. Wolbachia s success in infecting an enormous number of arthropod species is attributed to two features: the range of phenotypes they induce in their hosts, and their ability to switch to new host species. Whilst much progress has been made in elucidating the phenotypes induced by Wolbachia, our understanding of Wolbachia host shifting is still very limited: we lack answers to even fundamental questions concerning Wolbachias routes of transfer and the importance of factors influencing host shifts. Here, we investigate the diversity and host-shift patterns of Wolbachia in scale insects, a group of arthropods with intimate associations with other insects that make them well-suited to studying host shifts. Using Illumina pooled amplicon sequencing of Wolbachia-infected scale insects and their direct associates we determined the identity of all Wolbachia strains, revealing that 32% of samples were multiply infected (with up to five distinct strains per species). We then fitted a Generalised Additive Mixed Model (GAMM) to our data to estimate the influence of factors such as the host phylogeny and the geographic distribution of each species on Wolbachia strain sharing among scale insect species. The model predicts no significant contribution of host geography but strong effects of host phylogeny, with high rates of Wolbachia sharing among closely related species and a sudden drop-off in sharing with increasing phylogenetic distance. We also detected the same Wolbachia strain in scale insects and several intimately associated species (ants, wasps, beetles, and flies). This indicates putative host shifts and potential routes of transfers via these associates and highlights the importance of ecological connectivity in Wolbachia host-shifting.
- assay: DNA methylation
- research focus: host-pathogen & immune response
- research focus: ecology & biodiversity
- research focus: cell type annotation
- research focus: clustering
- approach: statistical model
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