Data from: Non-random associations of maternally transmitted symbionts in insects: the roles of drift versus co-transmission and selection
Mathé-Hubert, Hugo; Kaech, Heidi; Hertaeg, Corinne; Vorburger, Christoph (2019), Data from: Non-random associations of maternally transmitted symbionts in insects: the roles of drift versus co-transmission and selection, Dryad, Dataset, https://doi.org/10.5061/dryad.ch4dp8n
Virtually all higher organisms form holobionts with associated microbiota. To understand the biology of holobionts we need to know how species assemble and interact. Controlled experiments are suited to study interactions between particular symbionts, but they can only inform about a tiny portion of the diversity within each species. Alternatively, interactions can be inferred from associations among symbionts in the field that are more or less frequent than expected under random assortment. However, random assortment may not be a valid null hypothesis for maternally transmitted symbionts in finite populations, where drift alone can result in associations. Here we report results from a European field survey of endosymbionts in the pea aphid (Acyrthosiphon pisum), and we develop a model to study the effect of drift on symbiont associations under different population sizes, considering varying rates of horizontal and maternal transmission. The model showed that even though horizontal transmissions and maternal transmission failures randomise symbiont associations, drift can induce significant departures from random assortment, at least in moderate-sized populations. Based on these results, we carefully interpret our field survey and we re-visit the association between Spiroplasma and Wolbachia in Drosophila neotestacea reported by Jaenike et al. (2010). For this and for several significant associations between symbionts in European pea aphids we conclude that under reasonable assumptions of effective population size, they are indeed likely to be maintained by biased co-transmission or selection. Our study shows that formulating appropriate null expectations can strengthen the biological inference from co-occurrence patterns in the field.