DOI: 10.6084/m9.figshare.91158
title: Phylogenetic maximum likelihood analyses of the voltage-gated sodium channel α subunits

description: Phylogenetic maximum likelihood analyses of the voltage-gated sodium channel α subunit (SCNα) gene family based on amino acid sequence alignments. The sequences and alignments described in <em>Widmark et. al. (2011) Molecular Biology and Evolution 28(1):859-71</em> (1) were used to re-analyze the phylogenetic relationships of vertebrate SCNα subtypes with more powerful methods. <strong>File information:</strong> Two datasets were made; the full subset of identified SCNα sequences in alignment file 1 (<em>9.6_SCNexons.aln</em>) used for the phylogenetic analyses in Figs. 1 and 3; and the identified SCN1A, SCN4A, SCN5A and SCN8A sequences in alignment file 2 (<em>8.14_SCNexons(1,4,5,8).aln</em>) used for the phylogenetic analyses in Figs. 2 and 4. The latter dataset includes only sequences representing each of the four chromosomes harboring SCNα genes in tetrapod genomes (1). Alignment files are provided in the CLUSTAL format. For sequence and alignment curation details see <em>Widmark et. al. (2011)</em> (1). The trees in Figs. 1 and 2 are supported by bootstrap values (see below). Both the final bootstrapped trees and all the bootstrap replicates are provided as txt-files in NEWICK format. The trees in Figs. 3 and 4 are supported by aLRT values (see below). The aLTR-supported trees are also provided in NEWICK format. In all files the first three letters of the sequence names are abbreviations of the species names, followed by the chromosome assignment of the genes and the abbreviated α subunit name (full names for the human sequences). <strong>Phylogenetic methods:</strong> The phylogenetic analyses were done using the PhyML 3.0 algorithm in PhyML-aBayes (3.0.1 beta) or through the web-based form of the PhyML 3.0 algorithm, both available from http://www.atgc-montpellier.fr/phyml. Trees supported by SH-like approximate likelihood ratio tests (aLTR) were done with standard settings: LG model of amino acid substitution; 4 substitution rate categories; equilibrium frequencies from the model; fixed proportion of invariable sites (0.0); gamma shape parameters estimated from the alignment; starting tree estimated using BIONJ; NNI method selected for tree topology improvement with both topology and branch length optimization. Trees supported by non-parametric bootstrap analyses with 100 replicates were done with the following settings: the JTT model of amino acid substitution was chosen based on analysis of the amino acid alignments in ProtTest 1.4 (<em>http://darwin.uvigo.es/software/prottest.html</em>); 8 substitution rate categories; equilibrium frequencies, proportion of invariable sites and gamma shape parameters estimated from the alignment; starting tree estimated using BIONJ; NNI and SPR methods selected for tree topology improvement with both topology and branch length optimization. Statistical support values are shown at the nodes. The trees were rooted with the identified <em>Drosophila melanogaster</em> sequence. <strong>Species abbreviations:</strong> Species abbreviations are applied as follows: Homo sapiens (Hsa, human), Mus musculus (Mmu, mouse), Monodelphis domestica (Mdo, opossum), Gallus gallus (Gga, chicken), Danio rerio (Dre, zebrafish), Oryzias latipes (Ola, medaka), Gasterosteus aculeatus (Gac, stickleback), Tetraodon nigroviridis (Tni, green spotted puffer), Ciona savignyi (Csa, tunicate), Branchiostoma floridae (Bfl, lancelet), Drosophila melanogaster (Dme, fruit fly). <strong>References:</strong> 1. Widmark J, Sundström G, Ocampo Daza D, Larhammar D (2011) Differential evolution of voltage-gated sodium channels in tetrapods and teleost fishes. Molecular biology and evolution 28:859-71. DOI: 10.1093/molbev/msq257. 2. Guindon S et al. (2010) New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Systematic biology 59:307-21. DOI: 10.1093/sysbio/syq010. 3. Abascal F, Zardoya R, Posada D (2005) ProtTest: selection of best-fit models of protein evolution. Bioinformatics 21:2104-5. DOI: 10.1093/bioinformatics/bti263. <em>Description updated 2012-12-06.</em>