Integrating genomic and phenotypic data to evaluate alternative phylogenetic and species delimitation hypotheses in a recent evolutionary radiation of grasshoppers

Abstract

Although resolving phylogenetic relationships and establishing species limits are primary goals of systematics, these tasks remain challenging at both conceptual and analytical levels. Here, we integrated genomic and phenotypic data and employed a comprehensive suite of coalescent-based analyses to develop and evaluate competing phylogenetic and species delimitation hypotheses in a recent evolutionary radiation of grasshoppers (Chorthippus binotatus group) composed of two species and eight putative subspecies. To resolve the evolutionary relationships within this complex, we first evaluated alternative phylogenetic hypotheses arising from multiple schemes of genomic data processing and contrasted genetic-based inferences with different sources of phenotypic information. Second, we examined the importance of number of loci, demographic priors, number and kind of phenotypic characters and sex-based trait variation for developing alternative species delimitation hypotheses. The best-supported topology was largely compatible with phenotypic data and showed the presence of two clades corresponding to the nominative species groups, one including three well-resolved lineages and the other comprising a four-lineage polytomy and a well-differentiated sister taxon. Integrative species delimitation analyses indicated that the number of employed loci had little impact on the obtained inferences but revealed the higher power provided by an increasing number of phenotypic characters and the usefulness of assessing their phylogenetic information content and differences between sexes in among-taxa trait variation. Overall, our study highlights the importance of integrating multiple sources of information to test competing phylogenetic hypotheses and elucidate the evolutionary history of species complexes representing early stages of divergence where conflicting inferences are more prone to appear.

Genomic data reveal deep genetic structure but no support for current taxonomic designation in a grasshopper species complex

“…Thus, incorporating morphological traits has no or very little influence on the outcome of ibpp analyses and the impact of phenotypic traits seems to be overridden by the high amount of genetic data. Our analyses suggest that the species delimitation approach implemented in ibpp does not really help to reduce the number of delineated species, indicating that integrating phenotypic and genetic data into this framework cannot prevent species overestimation (Noguerales et al, ; Sukumaran & Knowles, ). In sum, the strong genetic structure in our study system and the high number of loci employed are likely to have extraordinarily inflated the number of species identified by bpp and bfd * and integrative analyses implemented in ibpp does not seem to help to ameliorate this problem.…”

“…Recent empirical and theoretical studies have shown the limitations of Bayesian species delimitation approaches based on the multi-species coalescent (MSC) model (Rannala & Yang, 2013;Yang & Rannala, 2010), pointing out that such methods are not able to statistically distinguish genetic structure due to population isolation from true species boundaries and tend to over-split genetically differentiated populations rather than capturing species divergence (Huang, 2018;Leaché et al, 2018;Leaché, Zhu, Rannala, & Yang, 2019;Sukumaran & Knowles, 2017). The problem of species overestimation can be particularly exacerbated when using vast genome-wide data due to the high power of a large number of markers (hundreds to tens of thousands) to detect fine-grain population structure (Hime et al, 2016;Noguerales et al, 2018;Sukumaran & Knowles, 2017). In this line, recent empirical studies have found that geographically continuous intraspecific populations presenting genotypic differences simply resulted from isolation by distance can be delimited as distinct species when using hundreds of loci (Huang, 2018; Pyron, Hsieh, Lemmon, Lemmon, & Hendry, 2016).…”

“…Population codes as in Recent studies have suggested that species delimitation approaches integrating genomic data with other sources of information (ecological, morphological, ethological, etc) could help to mitigate the problem of confounding population structure with species limits (Pyron et al, 2016;Sukumaran & Knowles, 2017). Although most phenotypic traits analyzed only presented very subtle differences (Noguerales et al, 2018;Sukumaran & Knowles, 2017). In sum, the strong genetic structure in our study system and the high number of loci employed are likely to have extraordinarily inflated the number of species identified by bpp and bfd* and integrative analyses implemented in ibpp does not seem to help to ameliorate this problem.…”

“…However, integrative species delimitation approaches are not exempt of limitations (Huang, ; Sukumaran & Knowles, ). One of these limitations is the challenge to deal with sexually dimorphic traits (Solis‐Lemus et al, ), which can have a considerable impact on species delimitation inferences (Chan et al, ; Noguerales, Cordero, & Ortego, ). More importantly, the finest detection of genetic differentiation brought by the highest resolution of genomic data can lead to a potential confusion of population genetic structure with species boundaries (Carstens, Pelletier, Reid, & Satler, ; O'Meara, ; Sukumaran & Knowles, ).…”

A genomic evaluation of taxonomic trends through time in coast horned lizards (genus Phrynosoma)

“…The three species recognized under this model are Phrynosoma blainvillii , Phrynosoma cerroense and P. coronatum , with geographic distributions in northern Baja California and California, central Baja California (including Cedros Island) and southern Baja California, respectively (Figure ). There is a general consensus among biologists that an integrative approach that combines diverse types of data from ecology, morphology and genetics will help increase taxonomic accuracy (Dayrat, ; Noguerales et al., ; Solís‐Lemus, Knowles, & Ané, ).…”