DOI: 10.5061/dryad.249v096
title: Data from: Genomic data reveal deep genetic structure but no support for current taxonomic designation in a grasshopper species complex

description: Taxonomy has traditionally relied on morphological and ecological traits
 to interpret and classify biological diversity. Over the last decade,
 technological advances and conceptual developments in the field of
 molecular ecology and systematics have eased the generation of genomic
 data and changed the paradigm of biodiversity analysis. Here we illustrate
 how traditional taxonomy has led to species designations that are
 supported neither by high throughput sequencing data nor by the
 quantitative integration of genomic information with other sources of
 evidence. Specifically, we focus on Omocestus antigai and O. navasi, two
 montane grasshoppers from the Pyrenean region that were originally
 described based on quantitative phenotypic differences and distinct
 habitat associations (alpine vs. Mediterranean-montane habitats). To
 validate current taxonomic designations, test species boundaries, and
 understand the factors that have contributed to genetic divergence, we
 obtained phenotypic (geometric morphometrics) and genome-wide SNP data
 (ddRADSeq) from populations covering the entire known distribution of the
 two taxa. Coalescent-based phylogenetic reconstructions, integrative
 Bayesian model-based species delimitation, and landscape genetic analyses
 revealed that populations assigned to the two taxa show a spatial
 distribution of genetic variation that do not match with current taxonomic
 designations and is incompatible with ecological/environmental speciation.
 Our results support little phenotypic variation among populations and a
 marked genetic structure that is mostly explained by geographic distances
 and limited population connectivity across the abrupt landscapes
 characterizing the study region. Overall, this study highlights the
 importance of integrative approaches to identify taxonomic units and
 elucidate the evolutionary history of species.
description: SNAPP input
 fileInput file (NEXUS
 format) used for phylogenomic analyses in SNAPPSNAPP_InputFile.nexSVDQuartets input fileInput file (NEXUS format) used for phylogenomic analyses in SVDQuartetsSVDQuartets_InputFile.nexBPP input filesThis ZIP folder contains the genetic datasets used to perform BPP analysesBPP.zipiBPP input filesThis ZIP folder contains the genetic and morphological datasets (males and females) used to perform iBPP analysesiBPP.zipRaw landmark coordinates of morphological traitsThis ZIP folder contains raw coordinates of landmarks used to characterize shape variation of the different morphological traits (head, pronotum, forewing and ovopositor valve) analyzed in males and females. Landmarks are stored in TPS format.LandmarkCoordinates.zipPrincipal component scores of morphological traitsPrincipal component scores (PC1 and PC2) summarizing shape variation of the different morphological traits (head, pronotum, forewing and ovopositor valve) analyzed in males and femalesMorphology_PCs.xlsxSTRUCTURE input fileInput file (str. format) used for analyses of genetic structure in STRUCTURESTRUCTURE_InputFile_10000loci.strFASTSTRUCTURE and PCA input fileInput file (str. format) used for analyses of genetic structure in FASTSTRUCTURE and ADEGENET (PCA)FASTSTRUCTURE_InputFile_64365loci.strCONSTRUCT input filesThis ZIP folder contains the input files (genetic and geographic data) used for spatial analyses of genetic structure in CONSTRUCTConStruct.zipDifferentiation and distance matrices used in MMRR analysesThis ZIP folder contains genetic (FST) and phenotypic (PST) differentiation matrices and distance matrices (geographic, resistance, and environmental) used in Multiple Matrix Regression with Randomization (MMRR) analysesMMRR.zipSampled populations and individualsDescription of individual and population codes used in the different analyses and genomic datasets.Samples.xlsxBFD input filesThis ZIP folder contains the input files (.xml format) used to perform Bayes Factor Delimitation (BFD) analyses in SNAPPBFD.zip