DOI: 10.5061/dryad.59zw3r28t
title: Dataset for: Conservation genomics of federally endangered Texella harvester species (Arachnida, Opiliones, Phalangodidae) from cave and karst habitats of central Texas

description: Genomic-scale data for non-model taxa are providing new insights into
 landscape genomic structuring and species limits, leading to more informed
 conservation decisions, particularly in taxa with extremely restricted
 microhabitat preferences and small geographic distributions. This study
 applied sequence capture of ultraconserved elements (UCEs) to gather
 genomic-scale data for two federally endangered Texella harvester species
 distributed in Edwards Formation cave and karst habitats of central Texas,
 near Austin. We gathered UCE data for 51 T. reyesi specimens from 46
 different caves, seven T. reddelli specimens from five caves, and from
 relevant outgroup species. For these UCE data we applied a combination of
 phylogenomic, multispecies coalescent phylogenetic, and single-nucleotide
 polymorphism (SNP) machine-learning analyses. We found that samples of T.
 reddelli and T. reyesi together form a single clade in phylogenetic
 analyses, but that T. reddelli samples are not recovered as monophyletic.
 Instead, T. reddelli samples from three northern caves are embedded within
 a larger T. reyesi genetic clade. Significantly, the genetic structuring
 of all samples closely follows geologic barriers defined for the region
 and formalized as karst fauna regions (KFRs). One exception is the
 Jollyville Plateau KFR, which includes two divergent, non-sister genetic
 lineages. Levels of troglomorphy, here assessed by a simple scoring of
 corneal and retinal development, also closely follows clade (and
 geographic) boundaries, implying that divergent genetic lineages might
 also have distinct ecologies. Overall, our study has important taxonomic
 implications, is the first to explore (and validate) regional KFR
 boundaries using intraspecific genetic data, and provides essential data
 for future management decisions involving these federally endangered
 species.
description: We used the Arachnida 1.1Kv1 probe set (Arbor Biosciences) to
 capture UCE loci, using standard methods of library preparation. Sequence
 reads were trimmed and assembled using TRINITY version
 2.1.1. (Grabherr et al. 2011) using default settings (trimmomatic =
 full_cleanup, kmer = 25), then processed using Phyluce
 (Faircloth 2016). Assembled contigs were matched to probes using liberal
 minimum coverage and minimum identity values (both 65). UCE loci were
 aligned with MAFFT (Katoh and Standley
 2013) and trimmed with Gblocks
 (Castresana 2000, Talavera and Castresana 2007) using relaxed settings
 (--b1 0.5 --b2 0.5 --b3 10 --b4 4). Resulting Phyluce
 alignments with at least 50% sample occupancy were imported
 into Geneious 11.0.4 (Biomatters), where ragged ends from individual
 sequences were trimmed from alignments (typical of “standard” museum
 specimens with degraded DNA). Maximum likelihood
 phylogenetic analyses were conducted using IQ-TREE version 2.0-rc2.
 Initial partitions corresponded to individual loci, then ModelFinder
 (Kalyaanamoorthy et al. 2017) was used to find best-fit models and merge
 partitions (-s -p -m TESTMERGE -rcluster 10); the relaxed hierarchical
 clustering algorithm (Lanfear et al. 2014) was used to reduce
 computational burden. Support was assessed via 1000 ultrafast bootstrap
 replicates (Hoang et al. 2018). An SVDQuartets analysis (Chifman and
 Kubatko 2014, 2015) was conducted on a concatenated matrix using PAUP*
 4.0a (Swofford 2002), implementing the multispecies coalescent tree model
 with exhaustive quartets sampling and 1000 bootstrap replicates.