Novel insights into symbiont population structure: Globe‐trotting avian feather mites contradict the specialist–generalist variation hypothesis

Abstract

Researchers often examine symbiont host specificity as a species‐level pattern, but it can also be key to understanding processes occurring at the population level, which are not as well understood. The specialist–generalist variation hypothesis (SGVH) attempts to explain how host specificity influences population‐level processes, stating that single‐host symbionts (specialists) exhibit stronger population genetic structure than multi‐host symbionts (generalists) because of fewer opportunities for dispersal and more restricted gene flow between populations. However, this hypothesis has not been tested in systems with highly mobile hosts, in which population connectivity may vary temporally and spatially. To address this gap, we tested the SGVH on proctophyllodid feather mites found on migratory warblers (family Parulidae) with contrasting host specificities, Amerodectes protonotaria (a host specialist of Protonotaria citrea) and A. ischyros (a host generalist of 17 parulid species). We used a pooled‐sequencing approach and a novel workflow to analyse genetic variants obtained from whole genome data. Both mite species exhibited fairly weak population structure overall, and contrary to predictions of the SGVH, the generalist was more strongly structured than the specialist. These results may suggest that specialists disperse more freely among conspecifics, whereas generalists sort according to geography. Furthermore, our results may reflect an unexpected period for mite transmission – during the nonbreeding season of migratory hosts – as mite population structure more closely reflects the distributions of hosts during the nonbreeding season. Our findings alter our current understanding of feather mite biology and highlight the potential for studies to explore factors driving symbiont diversification at multiple evolutionary scales.

Population Genomics of Pooled Samples: Unveiling Symbiont Infrapopulation Diversity and Host–Symbiont Coevolution

“…Many other analytical frameworks exist for inferring different population genetic statistics from Pool-Seq data [51][52][53] with variable benchmarking results [54,55], which alludes to the difficulty of untangling Pool-Seq data [18,23,56]. Our strategy described above is highly conservative, utilizes well-maintained public programs, and allows us to more directly compare population structure [57]. We visually assessed the impact of the different linkage thresholds through principal components analyses (PCA) using PLINK.…”