Supplementary Information Environmental Temperatures Shape
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Supplementary Information Environmental temperatures shape thermal physiology as well as diversification and genome-wide substitution rates in lizards Garcia-Porta, Irisarri, et al. Supplementary methods Phylogenomic data set assembly This study is mainly based on two new phylogenomic data sets (RNAseq and AHE), for which we especially selected lacertid species to represent the major clades of Lacertini that so far have evaded reliable phylogenetic reconstruction. As these two data sets contained different selections of taxa, they were first analyzed separately. To create a taxonomically more comprehensive tree for downstream analyses, both phylogenomic datasets were combined with five gene fragments commonly used in lacertid phylogenetics and available for a large number of species. The amphisbaenian, Blanus cinereus, known to represent the sister group of Lacertidae 1, was used as an outgroup in all phylogenetic analyses. The Anchored Hybrid Enrichment (AHE) method 2 was used to target 394 anonymous nuclear loci (of which 324 loci were retained for analysis). To generate the AHE data set, genomic DNA was extracted from fresh or ethanol-preserved tissue samples with a Qiagen DNeasy® Tissue Kit, DNA concentration measured with a Qubit® fluorometer, and samples with > 12 µg/ml selected for enrichment and sequencing in the Center for Anchored Phylogenomics at Florida State University (www.anchoredphylogeny.com), following previously outlined methods 2,3. Briefly, genomic DNA was sonicated to a fragment size of 200–800 bp and libraries prepared and indexed following the protocol of Meyer and Kircher 4 with minor modifications 2, using a Beckman-Coulter Biomek FXp liquid-handling robot. Following library preparation, libraries were pooled in equal quantities in batches of 16 libraries. Equal quantities of indexed samples were pooled and enrichments were performed with probes designed for anchored loci from amniotes 3,5,6, specifically using the Squamate-optimized kit 6. Sequencing was carried out on two lanes of an Illumina HiSeq2500 sequencer with PE150 sequencing (~33 samples per lane, 2 lanes, 98 gigabases total). After quality filtering using the high chastity setting in Illumina’s Casava software, the reads were de-multiplexed using the 8 bp indexes, with zero mismatches tolerated. Paired reads were 7 then merged using a Bayesian approach . This approach trims adapters and corrects sequencing errors in overlapping regions. Reads were assembled using a quasi-de novo approach 8 but with Anolis and Salvator probe region sequences serving as references for the assembly 6. In order to avoid the effects of possible contamination and/or misindexing, assembled contigs derived from fewer than 100 reads were removed prior to downstream analyses. Contigs passing this filter were then assessed for orthology using pairwise distances 8. Orthologous sequences were aligned using MAFFT (v. 7.023b) 9 then trimmed/ masked, with MINGOODSITES=14, MINPROPSAME=0.5, and MISSINGALLOWED=35 8. Alignments were manually inspected in Geneious R9 (Biomatters Ltd.) 10 in order to identify misaligned regions, which were masked prior to phylogenetic analyses. New transcriptomic (RNAseq) data were generated from from 100 mg of tissue of each lizard, consisting of combined or separate skin, muscle, or liver samples preserved in RNAlater and frozen at -80°C. RNA extraction was carried out using standard trizol protocols. Sequencing was 1 carried out with a High Output 150 cycle kit. Illumina reads were quality-trimmed and filtered using Trimmomatic v. 0.32 11 with default settings and later filtered for rRNA sequences with SortMeRNA 12. Paired and unpaired filtered reads were used for de novo transcriptome assembly using Trinity v. 2.1.0 13 following published protocols 14. Candidate coding regions within transcript sequences from the final assembly were identified and translated using Transdecoder 2.1.0 14. We used a previously compiled alignment of 4593 + 1506 + 1195 nuclear genes 15 as a reference for ortholog selection, hereafter reference set. Coding sequences of the new transcriptomes identified by Transdecoder were aligned to the reference set using the software Forty-Two (D. Baurain; https://bitbucket.org/dbaurain/42/). Sequence decontamination and paralog resolution followed the previously established protocol 15. Briefly, contaminant sequences from non-vertebrate sources (e.g. Apicomplexa or Nematodes) were detected by BLAST searches and removed. For each species and locus, redundant and/or divergent sequences were eliminated by comparing every sequence against all other sequences in the alignment using BLAST. Sequences with average bit scores at least 10% lower than the best average bit score and with ≥95% sequence overlap to other redundant sequences were eliminated. Paralogs were identified and resolved using a custom script 15. Final alignments contained only lacertid sequences as well as Blanus cinereus used as outgroup. We selected a total of 6,556 loci containing at least 15 lacertids. The corresponding nucleotide sequences for the retained amino acid alignments were recovered using the program leel (Denis Baurain, unpublished), and aligned according to the amino acid alignments. All subsequent analyses were based on nucleotide alignments. A final quality filtering was performed by comparing every branch length of single gene trees to the corresponding branch in the concatenated ML tree (inferred under GTR+Γ with RAxML v.8 16) in order to identify and remove problematic sequences not captured in previous decontamination steps 15. A total of 2,352 individual sequences were removed in the following way: 961 sequences displaying terminal branches on gene trees 9 times longer than the concatenated ML tree and 1,391 sequences displaying a terminal branch 5 times longer. Finally, 252 gene alignments were discarded based on a too low coefficient of correlation between gene branch length and concatenation branch length (i.e. below the mean -1.96 SD of the observed R, in practice 0.65). The final dataset contained a total of 6,269 genes for 24 lacertids (22 species; two species had two individuals each) and one outgroup, each containing at least 15 lacertid sequences. DNA sequences from previous studies for the nuclear proto-oncogene mos gene (c-mos) and the mitochondrial genes for 12S and 16S ribosomal RNA (12S, 16S), Cytochrome b (cob), and NADH-dehydrogenase subunit 4 (nd4) were retrieved manually from Genbank based on the most recent publications, to ensure that for taxa that underwent taxonomic revision the sequences included in the supermatrix were correctly assigned. Phylogenetic analyses For each of the resulting AHE and RNASeq datasets as well as the combined dataset including five additional genes (12S, 16S, cob, nd4, c-mos) (hereafter AHE, RNASeq, and combined, respectively) we performed ML phylogenetic inference analyses using IQTREE v. 1.5.4 17. We selected best-fitting partitioning scheme and substitution models by AIC assuming edge- proportional rates and using a relaxed hierarchical clustering approach, as implemented in IQTREE (“-spp -m MFP+MERGE –rcluster 10” options). The -spp option specifies branch lengths as linked, evolutionary rates as unlinked. Node support was estimated in IQTREE with 1,000 replicates of ultrafast bootstrapping 18. Because of the large size of the combined matrix (247 species and 6,598 loci) and high 2 proportion of missing data (47%), best-fit partition finding across the full parameter space proved computationally infeasible even on high-performance clusters. We then applied two alternative approaches, (i) heuristic search restricting the set of candidate models to GTR, HYK or JC, with or without discrete Γ distribution to model among site rate heterogeneity in order to represent the parameter space by the simplest and the most complex models available (“-m TESTMERGE – mset JC, HKY, GTR –mrate E,G –rcluster 1”), and (ii) using the best-fit partitions previously applied for the separate analyses of the RNAseq and AHE datasets, and the newly estimated best- fit partitions for the legacy gene data set. In final analyses, we allowed each partition to have either JC, HKY or GTR models, with or without gamma parameter (“-m TEST -mset JC, HKY, GTR -mrate E,G”). Based on empirical evaluation of the suggested partition settings and resulting trees we chose the second alternative for our final analysis. Conflicting genealogical histories can confound phylogenetic inferences of concatenated multi-locus matrices potentially resulting in incorrect trees with high support 19 and this can be exacerbated in phylogenomic-level analyses 20. Therefore, we estimated species trees from the two phylogenomic data sets under the multi-species coalescence model as implemented in ASTRAL II 21. ASTRAL was fed with locus trees estimated under the best-fitting model as estimated in IQTREE with 1,000 ultrafast bootstrap replicates. Branch support was assessed by multilocus bootstrapping using the gene and site re-sampling strategy, as implemented in ASTRAL II 22. Phylogenetic placement of fossils and molecular dating The fossil record of Lacertidae mostly consists of fragmentary cranial bones and isolated postcranial elements, often making reliable taxonomic or systematic assignments difficult. We therefore included only the following lacertid fossils in our morphological data set, some of which we also microCT scanned: 1) Dracaenosaurus croizeti 23 (scored for 27 cranial characters), based on an excellently preserved skull partly