Lousy grouse: Comparing evolutionary patterns in Alaska galliform lice to understand host evolution and host–parasite interactions

Abstract

Understanding both sides of host-parasite relationships can provide more complete insights into host and parasite biology in natural systems. For example, phylogenetic and population genetic comparisons between a group of hosts and their closely associated parasites can reveal patterns of host dispersal, interspecies interactions, and population structure that might not be evident from host data alone. These comparisons are also useful for understanding factors that drive host-parasite coevolutionary patterns (e.g., codivergence or host switching) over different periods of time. However, few studies have compared the evolutionary histories between multiple groups of parasites from the same group of hosts at a regional geographic scale. Here, we used genomic data to compare phylogenomic and population genomic patterns of Alaska ptarmigan and grouse species (Aves: Tetraoninae) and two genera of their associated feather lice: Lagopoecus and Goniodes. We used wholegenome sequencing to obtain hundreds of genes and thousands of single-nucleotide polymorphisms (SNPs) for the lice and double-digest restriction-associated DNA sequences to obtain SNPs from Alaska populations of two species of ptarmigan. We found that both genera of lice have some codivergence with their galliform hosts, but these relationships are primarily characterized by host switching and phylogenetic incongruence. Population structure was also uncorrelated between the hosts and lice. These patterns suggest that grouse, and ptarmigan in particular, share habitats and have likely had historical and ongoing dispersal within Alaska. However, the two genera of lice also have sufficient dissimilarities in the relationships with their hosts to suggest there are other factors, such as differences in louse dispersal ability, that shape the evolutionary patterns with their hosts.

Consumers’ active choice behavior promotes coevolutionary units

“…Coevolutionary units have been suggested as a product of cospeciation and arms race. Under These hypotheses, the consumers are predicted to have evolutionary patterns of diversification that are congruent with the patterns of their resources, where closely related resource species would have similar defenses and closely related consumers would feed on closely related resources [42,43]. However, these hypothesis has little support in empirical studies [42,44–47], except for tight specialized interactions [48].…”

“…Under These hypotheses, the consumers are predicted to have evolutionary patterns of diversification that are congruent with the patterns of their resources, where closely related resource species would have similar defenses and closely related consumers would feed on closely related resources [42,43]. However, these hypothesis has little support in empirical studies [42,44–47], except for tight specialized interactions [48]. The incongruence between host and parasite phylogenies, for example, has previously been explained in terms of host switching, extinction, duplication events and failure of the parasite to speciate in response to host speciation [49].…”

“…The measure of all the mentioned metrics was implemented through the bipartite package and performed in an R [40] environment. Modularity was measured using the DIRTLPAwb+ algorithm using the computeModules function [41]. Specialization H2' was measured using the H2fun function [41].…”

“…Modularity was measured using the DIRTLPAwb+ algorithm using the computeModules function [41]. Specialization H2' was measured using the H2fun function [41]. Both metrics use quantitative matrices.…”

“…Both metrics use quantitative matrices. The connectance (C) was calculated in binary matrices and refers to the ratio between the number of non-zero cells by the matrix size [41]. The connectance indicates the percentage of all interaction occurred during the analyzed time.…”