DOI: 10.5061/dryad.15dv41p2q
title: The genomic signatures of evolutionary stasis

description: Evolutionary stasis characterizes lineages that seldom speciate and show
 little phenotypic change over long stretches of geological time. Although
 lineages that appear to exhibit evolutionary stasis are often called
 living fossils, no single mechanism is thought responsible for their slow
 rates of morphological evolution and low species diversity. Some analyses
 of molecular evolutionary rates in a handful of living fossil lineages
 have indicated they exhibit slow rates of genomic change. Here, we
 investigate mechanisms of evolutionary stasis using a dataset of 1,105
 exons for 481 vertebrate species. We demonstrate that two ancient clades
 of ray-finned fishes classically called living fossils, gars, and
 sturgeons, exhibit the lowest rates of molecular substitution in
 protein-coding genes among all jawed vertebrates. Comparably low rates of
 evolution are observed at four-fold degenerate sites in gars and
 sturgeons, implying a mechanism of stasis decoupled from selection that we
 speculate is linked to a highly effective DNA repair apparatus. We show
 that two gar species last sharing common ancestry over 100 million years
 ago naturally produce morphologically intermediate and fertile hybrids.
 This makes Gars the oldest naturally hybridizing divergence among
 eukaryotes and supports a theoretical prediction that slow rates of
 nucleotide substitution across the genome slow the accumulation of genetic
 incompatibilities, enabling hybridization across deeply divergent lineages
 and perhaps slowing the rate of speciation. Our results help establish
 molecular stasis as a barrier to speciation and phenotypic innovation and
 provide a mechanism to explain the low species diversity in living fossil
 lineages.
description: <strong>Molecular evolutionary rates among major lineages
 of jawed vertebrates.</strong> To test whether
 slow rates of morphological evolution are paired with low rates of
 molecular evolution in living fossils like gars, sturgeons, and
 paddlefishes, we estimated molecular rate variation across 1,105 exons
 from a sample of 471 jawed vertebrate species. We identified orthologous
 exon sequences from the genomes of selected species in the NCBI database
 for the following major jawed vertebrate lineages: Acipenseriformes, Aves,
 Crocodylia, Chondrichthyes, Lepidosauria, Lissamphibia, Marsupialia,
 Placentalia, Polypteridae, and Teleostei (Figure S1a). The HMM protocol
 available in HMMER 3.1 (Wheeler and Eddy 2013) was used to search each of
 the downloaded genomes for orthologous exons. These exon sequences were
 extracted using Python scripts from a phylogenomic analysis of ray-finned
 fishes using these loci (Hughes et al. 2018). For each group of the exon
 sequences, we aligned them using MAFFT v.7.3 (Katoh and Standley 2013)
 with default parameters. Exon alignments for the seven living species of
 gars (Lepisosteidae) used in a phylogenomic study (Brownstein et al.,
 2023) were included in the comparative analysis. Each exon was separately
 aligned among the species in a given vertebrate lineage, resulting in a
 maximum of 1,105 alignments sampled for each lineage. Fourfold degenerate
 (4D) sites were extracted from all exons and concatenated in every
 vertebrate clade except Polypteridae and Acipenseriformes. This was
 because we could not find orthologous 4D site sequences for all the
 available genome assemblies for these two clades; sampling 4D sites for
 all three species would be needed to sample the common ancestors of
 Polypteridae and Acipenseriformes, as we were only able to include three
 species of each in our exon rate estimate analyses. We
 estimated and compared posterior molecular substitution rates at each exon
 across all major vertebrate clades using fixed input trees in Bayesian
 molecular clock analyses. We used previously published time-calibrated
 phylogenies for Teleostei (Hughes et al. 2018), Acipenseriformes (Kumar et
 al. 2017), Polypteridae (Near et al. 2014), Lepisosteidae ( Brownstein et
 al. 2023), Chondrichthyes (Kumar et al. 2017), Testudines (Shaffer et al.
 2017), Amphibia (Kumar et al. 2017), Lepidosauria (Pyron and Burbrink
 2014), Aves (Prum et al. 2015), Crocodylia (Green et al. 2014),
 Marsupialia (Upham et al. 2019), and Placentalia (Upham et al. 2019). The
 time tree of vertebrates used in the branch rate analysis of coelacanths
 and lungfish was taken from the literature (Wang et al. 2021) and
 timetree.org (Kumar et al. 2017). We used these time-calibrated molecular
 phylogenies in BEAST 2.5.2 (Bouckaert et al. 2019) by inserting them in
 Newick format into the ‘Starting Tree’ tab in the BEAUTi terminal. The
 following operators were turned off to ensure the input tree remained
 fixed: tree scaler, tree root scaler, uniform operator, subtree slide,
 narrow and wide exchange, and Wilson-Balding. In turn, we neither
 estimated tree topology nor divergence times. Custom scripts for inserting
 the trees, along with XML files containing the tree topologies used, are
 in the Supplementary Data. BEAST 2.5.2 (Bouckaert et
 al. 2019) was used to estimate the Bayesian posterior nucleotide
 substitution rate for each of the 1,105 exons and fourfold degenerate
 sites separately from each vertebrate clade. The computer program BEAUTi
 (Bouckaert et al. 2019) was used to construct individual XML files from
 each exon alignment and the pooled fourfold degenerate sites for each
 clade with the clade-specific time-calibrated phylogeny. The
 time-calibrated phylogeny was fixed such that BEAST did not estimate
 topology or divergence times. Because of the large number of BEAST
 analyses, we took advantage of the Yale High-Performance Computing cluster
 and built custom scripts to produce and run XML files along this pipeline.
 First, we produced a template XML for each clade that specified all input
 parameters regarding a single XML. We then used a custom batch script
 (Supplementary Information) to fit the specifications given by the
 template XML file with each gene to produce individual XML files for every
 single exon sampled in a given vertebrate clade. We used a Yule
 (pure-birth) branching model as the tree prior, a relaxed Lognormal clock
 model as the clock before allowing independent rates for each branch, and
 an HKY model of nucleotide evolution to allow for unequal frequencies and
 transition rates, and ran each analysis ran for 10 million generations.
 Upon completion of the analyses, we confirmed sufficient MCMC mixing
 (ESS&gt;200) for each BEAST run using the program Tracer v. 1.7
 (Rambaut et al. 2018) and the R package “coda” v.0.19-4 (Makowski et al.
 2019). To test whether our rate estimates were
 unaffected by tree model choice, we reran exons in lepidosaurs and
 teleosts with the five fastest, five slowest, and five middlemost rate
 estimates under a Birth-Death tree model. Theoretically, tree model choice
 should not affect our results because we fixed the time tree in each
 analysis, but we chose to test this outright. Parameter choices were
 otherwise the same as the original runs. We then compared absolute rate
 estimates between runs using the Yule and Birth-Death models. Next, we
 tested to see whether the number of species sampled for different clades
 biased estimated rates. Among the six clades with more than seven species
 sampled that had average estimated substitution rates higher than the
 average in gars (Figure 2), we subsampled seven species of lepidosaurs and
 teleosts (the number of species sampled for gars) that captured the common
 ancestry of major subclades (i.e., Squamata, Toxicofera, Euteleostei,
 Acanthomorpha) out of our exon dataset and reran the analyses under the
 original parameter specification (i.e., under a Yule model). We then
 compared absolute rate estimates between runs using the full and reduced
 sampling of lepidosaurs and teleosts.
 <strong>Estimation of branch-specific molecular
 evolutionary rates for living fossils.</strong>
 We investigated the rates of molecular substitution in candidate
 living fossil lineages including paleognathous birds, the
 Hoatzin <em>Opisthocomus hoazin</em>, the Tuatara
 <em>Sphenodon punctatus</em>, the Salamanderfish
 <em>Lepidogalaxias salamandroides</em>, the African Coelacanth
 <em>Latimeria chalumnae</em>,<em> </em>the
 Australian Lungfish <em>Neoceratodus forsteri</em>, and the
 West African Lungfish <em>Protopterus annectens</em>. We
 extracted the estimated posterior molecular substitution rates for the
 corresponding terminal branches in our fixed time trees. For the two
 lungfishes and African Coelacanth, we constructed a time tree that
 included these taxa and the species of Lissamphibia for which exon data
 was available. We included Lissamphibians to ensure that the time tree
 accommodated the paraphyly of sarcopterygian “fishes.” This was
 accomplished by taking the fixed tree of Lissamphibia (see ‘Input Tree
 Selection’) and manually adding <em>Latimeria
 chalumnae</em>,<em> </em>the Australian Lungfish
 <em>Neoceratodus forsteri</em>, and the West African Lungfish
 <em>Protopterus annectens</em> as progressive outgroups to
 Amphibia (following (Amemiya et al. 2013; Meyer et al. 2021; Wang et al.
 2021)) and fixing divergence times following TimeTree.org searches. BEAST
 analyses were run using the same parameters as in the whole-clade rate
 estimation runs and extracted branch-specific rates for <em>L.
 chalumnae </em>and Dipnoi.
 <strong>Hybridization among deeply divergent gar lineages
 <em>Lepisosteus </em>and <em>Atractosteus</em>.
 </strong> Next, we investigated signatures of
 hybridization across deeply divergent gar lineages to test whether slow
 rates of molecular evolution might be associated with incomplete
 reproductive isolation across deep time in living fossil lineages. To
 check for regions where both extant gar genera are currently sympatric, we
 downloaded occurrence data for species of <em>Lepisosteus</em>
 and <em>Atractosteus </em>spatula from FishNet2
 (http://fishnet2.net/). We pruned erroneous and duplicate records. The
 clean occurrence data files are included in the Supplementary
 Data. Natural hybrids have been reported among wild
 populations of <em>Atractosteus spatula </em>and
 <em>Lepisosteus osseus </em>in Texas and Oklahoma (Bohn et al.
 2017; Taylor et al. 2020), and so we examined genomic evidence of
 hybridization in these populations. We obtained tissue samples from 206
 specimens of <em>Atractosteus spatula, Lepisosteus osseus,
 </em>and hypothesized <em>A. spatula </em>X<em> L.
 osseus </em>hybrids from across the Gulf of Mexico coastal river
 systems (Table S1) to test for both the commonality of hybrids and the
 presence of both F1s and F2s in the Brazos river system. The Brazos and
 Trinity systems and Choke Canyon Reservoir were targeted because previous
 studies have convincingly demonstrated the presence of
 hybrid <em>Atractosteus spatula </em>X <em>Lepisosteus
 osseus </em>individuals in this region (Bohn et al. 2017; Taylor et
 al. 2019). We chose a subset of five <em>A. spatula </em>and
 seven <em>L. osseus </em>isolations with high DNA
 concentrations based on Qubit fluorometer (Life Technologies, Carlsbad,
 CA, USA) readings to test for naturally occurring hybrids between species
 in these genera. These were compared with tissue samples from individuals
 that showed morphological intermediacy consistent with being a hybrid, as
 well as their identification in a previous study (Bohn et al.
 2017)<em>.</em> We used double digest
 restriction site associated DNA sequencing (ddRADseq) to obtain a large
 dataset of single nucleotide polymorphisms (SNPs) to investigate whether
 sympatric populations of <em>Lepisosteus osseus </em>and
 <em>Atractosteus spatula </em>show evidence of hybridization.
 ddRADseq was performed following a modified version of the frequently used
 protocol (Peterson et al. 2012)<em>.</em> Additional details
 are described in the Supplementary Information. Pooled libraries were
 size-selected for 300-500 bps using a BluePippin sequenced by the
 University of Oregon Genomics & Cell Characterization Core
 Facility on an Illumina HiSeq 4000. We assembled the gar ddRAD dataset
 using iPyrad v.0.9.68 (Eaton and Overcast 2020) with the
 <em>Lepisosteus oculatus </em>genome (NCBI accession number:
 GCF_000242695.1) (Braasch et al. 2016) as a reference, resulting in a
 total of 256,750 loci shared by at least four samples. For analysis of
 hybridization, ddRAD SNPs were filtered using VCFTools v.0.1.15 (Danecek
 et al. 2011) so that only biallelic SNPs with minor allele counts
 &gt;1 and &lt;5% missing data were retained. To minimize the
 effects of linkage among markers, one random SNP per 10,000 bp window was
 retained, resulting in a dataset containing 2,097 SNPs (2.2% missing
 data). In addition, we used a custom R script to identify 1,223 SNPs (2.1%
 missing data) that were fixed between the parental species
 (<em>Atractosteus spatula</em> and <em>Lepisosteus
 osseus</em>). Demultiplexed ddRAD Illumina reads are deposited at
 the NCBI SRA (PRJNA1077910). We assessed genomic
 signals of hybridization between <em>Atractosteus spatula</em>
 and <em>Lepisosteus osseus</em>. First, missing genotypes were
 imputed with the “impute” function (method = “random”) in the R package
 LEA v.3.4.0<em> </em>(Frichot and François 2015). To examine
 patterns of genetic variation, we then performed principal component
 analysis (PCA) using the 2,097 filtered SNPs with the “dudi.pca” function
 in the R package ade4 v.2.1.4 (Dray and Dufour 2007; Thioulouse et al.
 2018)<em>.</em> In addition, we estimated genomic ancestry
 coefficients for each individual with sparse nonnegative matrix
 factorization implemented in the R package LEA. Ten replicate analyses
 were performed with between two and ten ancestral populations (K). We
 examined cross-entropy scores to determine the optimal value of K (Figure
 S3a). Hybrid classification was performed using the
 dataset of 1,223 fixed SNPs. First, the “find.clusters” function from the
 Adegenet v.2.1.4 R package (Jombart and Ahmed 2011) was used to assign all
 individuals to two genetic clusters by performing 10 million search
 iterations of the K-means algorithm with 1,000 random starting centroids.
 Starting with the K-means group memberships, we used the Adegenet
 “snapclust” function (Beugin et al. 2018) to estimate the probability of
 membership to parental, F1, or backcross classes. A maximum of ten million
 generations for 1,000 replicate runs of the expectation–maximization were
 performed. Additionally, we estimated the ancestry index and interspecific
 heterozygosity for each individual using the R package HIest v.2.0
 (Fitzpatrick 2012). To better understand patterns of
 hybridization, including skewed sex ratios among parental
 <em>Atractosteus spatula </em>and <em>Lepisosteus
 osseus</em>, we interrogated mitochondrial DNA (mtDNA) data for a
 sample of 201 gars including all living species in Lepisosteidae. Because
 mitochondrial DNA is maternally inherited, inferring a phylogenetic tree
 using mitochondrial sequence data can illuminate skewed sex ratios in
 hybrid crosses. We included two specimens of <em>Amia
 calva</em> to serve as outgroups in the phylogenetic analysis.
 Sampling locations of specimens used for genetic analyses are listed in
 Supplemental File Table_S1.csv. DNA was extracted from 95%
 ethanol-preserved tissues using a standard DNeasy Qiagen Blood and Tissue
 Kit (QIAGEN, Valencia, CA, USA). To minimize downstream enzymatic
 inhibition, we purified DNA extractions with ethanol precipitation: 3M
 sodium acetate (pH = 5.2) was added equal to 10% of the total volume of
 the DNA extraction followed by 100% ethanol equal to 2.5 times the total
 volume of DNA. After mixing, extractions were incubated for 10 minutes at
 -80C. Samples were centrifuged for 30 minutes at 8,000 RCF, the
 supernatant was carefully poured off, and the DNA pellet was washed with
 250 uL of cold 70% ethanol. Samples were centrifuged again for 5 minutes
 at 8,000 RCF, supernatant was poured off, the pellet was allowed to air
 dry for ~15 minutes, and the DNA pellet was resuspended with the desired
 amount of DNAse-free water. The mtDNA gene tree of gars
 (Figure 5f) was inferred with a phylogenetic analysis of the mitochondrial
 encoded cytochrome <em>b</em> (<em>cytb</em>)
 gene. The molecular phylogenetic analysis included 33 specimens of
 <em>Atractosteus spatula</em>, two specimens of <em>A.
 tristoechus</em>, eight specimens of <em>A.
 tropicus</em>, 65 specimens of <em>Lepisosteus
 osseus</em>, five specimens of <em>L. platostomus</em>,
 44 specimens of <em>L. oculatus</em>, 23 specimens of
 <em>L. platyrhincus</em>, 21 specimens of
 <em>Atractosteus spatula </em>X <em>Lepisosteus osseus
 </em>hybrids, and a single specimen of both
 <em>Amia</em> <em>calva</em> and
 <em>A</em>. <em>ocellicauda</em> to serve as
 outgroups. The <em>cytb</em> gene was amplified using
 previously published PCR primers and cycling conditions (Wright et al.
 2012). Amplification products were prepared for DNA sequencing using a
 polyethylene glycol precipitation. Contiguous sequences were assembled
 from individual DNA sequencing reactions using the computer program
 Geneious v.7.2 (Kearse et al. 2012). New <em>cytb</em>
 sequences were aligned by eye to those previously generated in early
 studies of gar phylogeny (Wright et al. 2012). The optimal data
 partitioning scheme, among the three codon positions of the
 <em>cytb</em> gene, and molecular evolutionary models was
 determined using the Bayesian information criterion in the computer
 program Partitionfinder v. 2.1 (Lanfear et al. 2017). The mitochondrial
 gene tree was inferred from the aligned cytb sequences using the optimal
 molecular evolutionary models and partitioning scheme using the computer
 program MrBayes v. 3.2 (Ronquist et al. 2012), where posterior
 probabilities for the phylogeny and parameter values were estimated using
 Metropolis-couple Markov chain Monte Carlo (Larget and Simon 1999;
 Huelsenbeck et al. 2001). The MrBayes analysis was run for
 10<sup>7</sup> generations with two simultaneous runs each
 with four chains. Convergence of the MC3 algorithm and stationarity of the
 chains was assessed by monitoring the average standard deviation of the
 split frequencies between the two runs, which was less than 0.005 after 3
 x 10<sup>6</sup> generations. In addition, the likelihood
 score and all model parameter estimates were plotted against the
 generation number to determine when there was no increase relative to the
 generation number in the computer program Tracer v. 1.7 (Rambaut et al.
 2018). The first 50% of the sampled generations were discarded as burn-in,
 and the posterior phylogeny was summarized as a 50% majority-rule
 consensus tree. All <em>cytb</em> gene sequences generated for
 this study are available at GenBank PP331004 - PP331204.
 <strong>Geometric morphometric analyses of gar
 hybrids.</strong> To quantify how the phenotypes
 of hybrid individuals of the two extant gar genera compared to those of
 their parental lineages, we used a dataset sampled from 25 specimens of
 <em>Atractosteus spatula, Lepisosteus osseus</em>, and
 <em>A. spatula </em>x <em>L. osseus </em>from the
 Brazos River system in Texas. The skull and mandible were selected as
 regions of study because there is morphological variation in these traits
 among lineages of extant and extinct gars (Wiley 1976; Kammerer et al.
 2006; Grande 2010; Brito et al. 2017) and both the skull and mandible
 contain key apomorphies of both <em>Atractosteus</em> and
 <em>Lepisosteus </em>(Wiley 1976; Grande 2010). These include
 features like the orientation and contact of the dentary symphyses and the
 width of the skull, which differ among <em>Lepisosteus
 </em>and<em> Atractosteus </em>and might appear distinct
 in hybrid individuals. A total of 7 meristic counts and proportions were
 measured. We included 24 morphometric landmarks: 12 on
 the skull in dorsal view and 12 on the mandible in ventral view (Figure
 S6). Landmarks were placed based on previously defined borders between
 major craniomandibular elements (Grande 2010). We digitized landmark
 coordinates and defined scales for each skull using tpsUtil64 v. 1.7 and
 tpsDIG2 v. 2.26. We ran analyses in both the R package geomorph (Adams and
 Otárola-Castillo 2013) and the program MorphoJ (Klingenberg 2011). In both
 programs, we applied a generalized Procrustes superimposition to exclude
 size, positional, and orientation effects before conducting principal
 components analyses on the data. We checked the resulting Procrustes fit
 graph for outliers and then ran principal components analyses.
 <strong>Assessing the morphological disparity of gars in
 deep time.</strong> To quantify variation in gar
 morphology over deep time, we collected data for individual specimens of
 extant and extinct gar species spanning over 75 million years to compare
 the shape of the skull across the gar crown clade. We opted for a
 quantitative comparison of these features in crown gars rather than an
 analysis of the rates of trait evolution through time given the small
 sample size of this clade (n=12 species; Fig. 1) and focused on
 two-dimensional measurements and meristic counts to mitigate the effects
 of post-mortem compression and deformation of gar fossils.
 Our measurements and meristic dataset include all currently
 described extinct species confidently placed in the gar crown group (Fig.
 1), as well as a new sample of <em>Atractosteus spatula</em> X
 <em>Lepisosteus osseus</em> hybrid crosses. Hybrids examined
 included one alcohol-preserved head (KUI uncatalogued), three
 alcohol-preserved full fish (KUI 18407, 18408, 18560), and three
 skeletonized skulls also used in our geometric morphometric analyses (KUI
 18558, 18409, 18559). These specimens were collected from the same river
 systems from which our sequence data establishes the presence of hybrids:
 the Trinity River ~1.6 km north of the US Route 90 Bridge in Liberty,
 Texas (KUI 18407), near the mouth of the Trinity River (KUI 18560, 18558,
 18559), and at the mouth of the Trinity River near Trinity Bay (KUI 18408,
 18409). Measurements taken included dimensional ratios
 of all gar skull roof bones, as well as standard length, head length,
 lateral line scale, and fin ray counts. All measurements were taken using
 digital calipers. The sample was combined with the total sample of crown
 gars in Grande (2010)<em> </em>for a total of n=124 specimens,
 and the dataset was analyzed and plotted in R using ggplot2. All
 measurements and meristic data are available in the Supplement.
 <strong>Detection of introgression among living lineages of
 gars.</strong> Lastly, we assessed whether living
 species of Lepisosteidae exhibit signatures of introgression over deeper
 phylogenetic time scales. First, we used MrBayes 3.2.7 (Ronquist et al.
 2012) to generate Bayesian gene trees for the subset of 770 orthologous
 exons identified by Brownstein et al. (2023) to be variant in gars sampled
 for all extant gars and two teleost outgroups (<em>Megalops
 cyprinoides</em> and <em>Osteoglossum bicirrhosum</em>).
 These represent the variable exons in gars sampled to reconstruct our
 tip-dated Bayesian phylogenomic hypothesis. We used an HKY+I+G molecular
 evolutionary model as implemented in the computer program MrBayes v. 3.2
 (Ronquist et al. 2012) and estimated posterior probabilities for the
 phylogeny and parameter values using Metropolis-couple Markov chain Monte
 Carlo (Larget and Simon 1999; Huelsenbeck et al. 2001). MrBayes was run
 for 1.5 x 10<sup>6</sup> generations with two simultaneous
 runs each with four chains for each exon. Convergence of the posteriors
 was checked in Tracer v. 1.7 (Rambaut et al. 2018). Finally, we used the
 program DensiTree (Bouckaert 2010) to assess concordance among the
 resulting gene trees (Fig. 1, Fig. 4a). Previous
 studies (e.g., Maddison, 1997; Mallet et al., 2016; Edelman et al. 2019)
 have noted that evidence of topological discordance across gene tree
 topologies may be reflective of both incomplete lineage sorting and
 introgression. As such, we conducted a secondary test of introgressive
 episodes across Lepisosteidae using PhyloNet 3.7.3 (Wen et al.
 2018)<em>. </em>Based on the 770 gene trees generated in Mr.
 Bayes 3.2.7, we inferred phylogenetic networks from maximum
 pseudolikelihood (MPL) with a reticulation of zero and then compared the
 log-probability of the reticulations up to six with 200 replications for
 each reticulation scenario.  <strong>Comparison
 of hybridizing species pair MRCA ages and whole-clade
 rates</strong>. We searched the literature for
 information on the most deeply divergent lineages that still hybridize for
 the major vertebrate clades analyzed in this study (Figure 2). The ages of
 the oldest hybridizing divergences were plotted against the mean exon
 substitution rate estimates generated in this paper. These data are
 included in the Supplemental File Table_S2.csv.
description: # The genomic signatures of evolutionary stasis Note that blank cell
 entries in all spreadsheets and datasets are missing data/absent data and
 should be treated as such. All measurements are in mm unless explicitly
 noted. ### scripts.zip **Vertebrate_Rate_Estimation:** * plotScripts =
 Custom scripts for extracting and plotting rate data * logs = Log files
 produced from analysis of 1,105 exons in 11 clades of 478 vertebrates
 including genomic substitution rates * filteringScripts = Custom scripts
 for filtering out problematic log files/invariant or non-converging
 analyses * 4D_logs = Log files produced from analysis of 4D sites in 9
 clades of 472 vertebrates ### RESULTS This zipped archive includes all
 direct output from primary analyses and reruns for convergence for all
 clade-wide rate estimates, as well as the sarcopterygian branch estimation
 runs:lo * xml = folder in each directory contains XML files generated
 using fixed tree topology for each clade (see methods) * BEAST rate
 posteriors = *.log files * BEAST tree posteriors = *.trees files ###
 RATES\_DATA **Original Alignments:** * Alignments.zip = fasta alignment
 files for exons from Hughes et al. (2018) arranged by group for input into
 analyses ### **Gar\_DDRAD\_DATA** **Raw data:** * demultiplexed .fastq
 files * iPyrad parameter file (params-AspaXLoss_reference.txt) **SNP
 dataset:** * VCF file for LEA = VCFtools to retain biallelic, unlinked (10
 kb thinning) SNPs with MAC &gt; 1 and &lt;10% missing data * VCF file for
 SNAPCLUST = same as above file but the &lt;5% missing data per SNP and
 only SNPs fixed between Lepisosteus and Atractosteus ###
 HYBRID\_MORPHOLOGY * KUI_gar_skulls = Photographs of gar skulls used in
 geometric morphometric analyses, photographs by Andrew Bentley * tps = tps
 files for geometric morphometric analyses of gar skulls generated using
 TPSDig2 and TPSUtil64 * plots = Resulting plots from geometric
 morphometric analyses of gar skulls ### PHYLONET * mrbayes_block.txt =
 Insert block for running Bayesian analysis in MrBayes *
 Nexus_files_introgression = Nexus files for running Bayesian analysis *
 Gar_exon_mrbayes_trees = Resulting trees from analysis of exons in
 MrBayes, for use in PHYLONET reconstructions ### XPC\_GENE * Gene_Tree =
 Nexus and FASTA alignments of amino acid sequences of XPC, downloaded from
 Ensemble * XPC_Alignments_for_Convergence.fas = XPC amino acid alignments,
 aligned in MUSCLE, used to detect convergent amino acid shifts among
 different living fossil lineages ### DISTRIBUTION\_data Data downloaded
 from FishBase and filtered for gar occurrences ### GAR\_MEASUREMENTS *
 Meristics and proportions data for sample of n=124 gar individuals from
 the crown group * originalAlignments.zip = input xmls built around 1,105
 exons examined in rate estimation analyses * orignalAlignments4d.zip =
 input xmls built around 4D sites examined in rate estimation analyses ###
 CLOCK\_MODEL\_TEST Input xmls and output logs for tests of alternative
 clock prior scheme for gar, lepidosaur, and teleost rate estimates
 **Gar:** * five_median = median exons * five_fastest = fastest exons *
 five_slowest = slowest exons * log_output = output log files
 **Lepidosaur:** * Bottom_5 = slowest exons * Median_5 = median exons *
 Top_5 = fastest exons * Logs = output log files **Teleost:** * Bottom_5 =
 slowest exons * Middle_5 = median exons * Top_5 = fastest exons * Logs =
 output log files ### SUBSAMPLE\_TEST Input and output runs where clades
 were subsampled to n=7, the number of gar species * teleost_sample.tar.gz
 = teleost run * lepid.tar.gz = lepidosaur run * attributes.tsv = DDRAD
 Data attributes ### LIST OF INDIVIDUALS SAMPLED * List_of_Individuals.xlsx
 = list of individuals sampled