Supplementary materials & methods



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SUPPLEMENTARY MATERIALS
1. MATERIALS & METHODS

SPECIMENS AND DNA EXTRACTION

A portion of epaxial musculature (ca. 0.25 g) from fresh specimens of each species was excised and the tissue immediately preserved in 99.5% ethanol. Total genomic DNA from the ethanol-preserved tissue was extracted using DNeasy (Qiagen) or Aquapure genomic DNA isolation kit (Bio-Rad Laboratories, Inc.) following the manufacturer’s protocols.



PCR AND SEQUENCINGS

Whole mitochondrial genomes of the 31 anguilliform species were amplified in their entirety using a long PCR technique (Cheng et al. 1994). Seven fish-versatile PCR primers for long PCR were used in the following four combinations: L2508-16S + H12293-Leu; L2508-16S + H15149-CYB; L8343-Lys + H1065-12S; and L12321-Leu + S-LA-16S-H (for locations and sequences of these primers, see Inoue et al. 2000, 2001a; Ishiguro et al. 2001, Kawaguchi et al. 2001; Miya & Nishida 2000) to amplify the entire mitochondrial genome in two reactions. Species-specific primers were designed in cases where no appropriate fish-versatile primers for the long PCR were available. Long PCR reaction conditions followed Miya & Nishida (1999). Long PCR products diluted with TE buffer (1:19) were subsequently used as templates for short PCR reactions employing fish-versatile PCR primers in various combinations to amplify contiguous, overlapping segments of the entire mitochondrial genome. When these primers did not work effectively, taxon-specific primers were designed from the obtained sequences for the primer walking strategy. The short PCR reactions were carried out following protocols previously described (Miya & Nishida 1999), then purified using Exosap-IT enzyme (GE Healthcare Bio-Sciences Corp.) and subsequently sequenced with dye-labeled terminators (BigDye terminator ver. 1.1/3.1, Applied Biosystems) and the primers used in the short PCRs. Sequencing reactions were conducted following the manufacturer’s instructions, followed by electrophoresis on an ABI Prism 377 or 3100 DNA sequencer (Applied Biosystems). A list of PCR primers used in this study is available from JGI upon request.



SEQUENCE EDITING AND ALIGNMENT

Whole mitochondrial genome sequences from 58 species were arranged into the typical gene order of vertebrates (beginning from tRNA-Phe) and the dataset was subjected to multiple alignment using MAFFT ver. 6 (Katoh & Toh 2008). We imported the aligned sequences into MacClade 4.08 (Maddison & Maddison 2005) and adjusted the alignment by eye. Amino acids were used to guide the alignment of the protein-coding genes and secondary structure models guided the alignment of tRNA genes. Regions that could not be unambiguously aligned, such as the 5´ and 3´ ends of several protein-coding genes and loop regions of rRNA and several tRNA genes, were excluded. The dataset comprises 10,821 positions from the 12 protein-coding genes (excluding ND6 gene), 1728 positions from the two rRNA genes and 1152 positions from the 22 tRNA genes (total 13,701 base pairs).



PHYLOGENETIC ANALYSIS

Unambiguously aligned sequences were divided into five partitions (first, second and third codon positions, rRNA and tRNA genes) and subjected to the partitioned ML analysis using RAxML ver. 7.2.4 (Stamatakis 2006). A general time reversible model with sites following a discrete gamma distribution (GTR + ; the model recommended by the author) was used and a rapid bootstrap (BS) analysis was conducted with 1000 replications (–f a option). This option performs BS analysis using GTRCAT, which is a GTR approximation with optimization of individual per-site substitution rates and classification of those individual rates into a certain number of rate categories. After implementing the BS analysis, the program uses every fifth BS tree as a starting point for another ML search using the GTR +  model of sequence evolution. The top 10 best-scoring ML trees are saved (fast ML searches), and BS probabilities are shown on the best-scoring ML tree.



TRACING CHARACTER EVOLUTION

The ancestral growth habitat was reconstructed on the best-scoring ML tree under the MK1 model (Lewis 2001) in Mesquite ver. 2.6 (Maddison & Maddison 2009). Four character states were assigned to the growth habitats (Miller & Tsukamoto 2004): shallow water (character state 0), outer shelf and slope (state 1), oceanic midwater (state 2) and freshwater (state 3).

To confirm the results from the ML reconstruction, a Bayesian approach implemented in SIMMAP ver. 1.0 Beta 2.4 (Bollback 2006) was performed for two ancestral nodes (A and B in figure 2). For the latter approach, partitioned Bayesian phylogenetic analysis was conducted with MrBayes 3.1.2 (Ronquist & Huelsenbeck, 2003) using the same evolutionary models as in the RAxML analysis. We assumed that all model parameters were unlinked and that rate multipliers were variable across partitions. The default settings for the priors on the proportion of invariable site (0–1) and the gamma shape parameter (0.1–50.0) were used. A Dirichlet distribution was assumed for the rate matrix and base frequencies and every tree topology was assumed to be equally probable. The Markov chain Monte Carlo (MCMC) process was set so that four chains (three heated and one cold) ran simultaneously. We continued the runs for 1,000,000 cycles, with 1 in every 1000 trees being sampled. “Stationarity” (lack of improvement in the likelihood score) was checked graphically and all trees and parameters before reaching the stationarity were discarded (“burn-in”). All trees after the “burn-in” period (200,000 cycles) were pooled and these trees (800 trees) were used for the reconstruction of the ancestral character states.
2. ACKNOWLEDGEMENTS

This study was supported in part by Research Fellowships of the Japan Society for the Promotion of Science for Young Scientists (07304), JSPS Postdoctoral Fellowships for Research Abroad, and Grants-in-Aid from the Ministry of Education, Culture, Sports, Science and Technology, Japan (12NP0201, 15380131, 17207007 and 19207007). We thank the captain, officers, crew, scientists and students on board of the KT-96-1, KT-96-19, KT-99-6 and KT-01-6 cruises of the R/V Tansei Maru and the KH-95-2, KH-00-1, KH-00-5 and KH-01-1 cruises of the R/V Hakuho Maru for their assistance in collecting samples.


3. REFRENCES

Bollback, J.P. 2006 SIMMAP: Stochastic character mapping of discrete traits on phylogenies. BMC Bioinformatics 7, 88.

Cheng, S., Higuchi, R. & Stoneking, M. 1994 Complete mitochondrial genome amplification. Nat. Genet. 7, 350–351. (doi:10.1038/369684a0)

Inoue, J. G., Miya, M., Aoyama, J., Ishikawa, S., Tsukamoto, K. & Nishida, M. 2001b Complete mitochondrial DNA sequence of the Japanese eel Anguilla japonica. Fish. Sci. 67, 118–125. (10.1111/j.1444-2906.2001.00207.x)

Inoue, J.G., Miya, M., Tsukamoto, K. & Nishida, M. 2000 Complete mitochondrial DNA sequence of the Japanese sardine Sardinops melanostictus. Fish. Sci. 66, 924–932. (doi: 10.1111/j.1444-2906.2000.00148.x)

Inoue, J. G., Miya, M., Tsukamoto, K. & Nishida, M. 2003 Evolution of the oceanic gulper eel mitochondrial genomes: large-scale gene rearrangements originated within the eels. Mol. Biol. Evol. 20, 1917–1927. (doi: 10.1093/molbev/msg206)

Ishiguro, N.B., Miya, M. & Nishida, M. 2001 Complete mitochondrial DNA sequence of ayu, Plecoglossus altivelis. Fish. Sci. 67, 474–481. (doi: 10.1046/j.1444-2906.2001.00283.x)

Kawaguchi, A., Miya, M. & Nishida, M. 2001 Complete mitochondrial DNA sequence of Aulopus japonicus (Teleostei: Aulopiformes), a basal Eurypterygii: longer DNA sequences and higher-level relationships. Ichthyol. Res. 48, 213–223. (doi: 10.1007/s10228-001-8139-0)

Kawahara, R., Miya, M., Mabuchi, K., Lavoue, S., Inoue, J. G., Satoh, T. P., Kawaguchi, A. & Nishida, M. 2007 Interrelationships of the 11 gasterosteiform families (sticklebacks, pipefishes, and their relatives): a new perspective based on whole mitogenome sequences from 75 higher teleosts. Mol. Phylogenet. Evol. 46, 224–236. (doi: 10.1016/j.ympev.2007.07.009)

Lewis, P. O. 2001. A likelihood approach to estimating phylogeny from discrete morphological character data. Syst. Biol. 50, 913–925. (doi: 10.1080/106351501753462876)

Maddison, W.P. & Maddison, D.R. 2005 MacClade version 4.08. Sunderland, Massachusetts: Sinauer Associates.

Miller, M. J. & Tsukamoto, K. 2004 An introduction to leptocephali: Biology and identification. Tokyo: Ocean Research Institute, The University of Tokyo.

Minegishi, Y., Aoyama, J., Inoue, J. G., Miya, M., Nishida, M. & Tsukamoto, K. 2005 Molecular phylogeny and evolution of the freshwater eels genus Anguilla based on the whole mitochondrial genome sequences. Mol. Phylogenet. Evol. 34, 134–146. (doi: doi:10.1016/j.ympev.2004.09.003)

Miya, M. & Nishida, M. 2000 Use of mitogenomic information in teleostean molecular phylogenetics: a tree-based exploration under the maximum-parsimony optimality criterion. Mol. Phylogenet. Evol. 17, 437–455. (doi:10.1006/mpev.2000.0839)

Robins, C.R. 1989 The phylogenetic relationships of the anguilliform fishes. In Orders Anguilliformes and Saccopharyngiformes, Fishes of the western North Atlantic (ed. E.B. Böhlke) Part 9, Vol. 1, pp. 9–23. New Haven: Sears Foundation for Marine Research.

Ronquist, F. & Huelsenbeck, J.P. 2003 MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19, 1572–1574.

Table S1. List of the species used in this study.

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Order/Suborder a Family Species Accession No.

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Outgroup

Elopiformes Elopidae Elops hawaiensis AB051070

Albuliformes Notacanthidae Notacanthus chemnitzi AP002975

Ingroup

Anguilliformes

Anguilloidei Anguillidae Anguilla japonica AB038556

A. reinhardtii AP007248

A. megastoma AP007243

A. celebesensis AP007239

A. marmorata AP007242

A. nebulosa nebulosa AP007246

A. nebulosa labiata AP007245

A. interioris AP007241

A. obscura AP007247

A. bicolor bicolor AP007236

A. bicolor pacifica AP007237

A. mossambica AP007244

A. borneensis AP007238

A. dieffenbachii AP007240

A. australis australis AP007234

A. australis schmidtii AP007235

A. rostrata AP007249

A. anguilla AP007233

Heterenchelyidae Pythonichthys microphthalmus AP010842

Moringuidae Moringua edwardsi AP010840

M. microchir AP010841

Muraenoidei Chlopsidae Kaupichthys hyoproroides AP010845



Robinsia catherinae AP010846

Myrocongridae Myroconger compressus AP010847

Muraenidae Anarchias sp. AP010843

Gymnothorax kidako AP002976

Rhinomuraena quaesita AP010844

Congroidei Synaphobranchidae Ilyophis brunneus AP010848



Synaphobranchus kaupii AP002977

Simenchelys parasitica AP010849

Ophichthidae Ophisurus macrorhynchus AP002978



Myrichthys aki AP010862

Colocongridae Coloconger cadenati AP010863

Derichthyidae Nessorhamphus ingolfianus AP010850

Derichthys serpentinus AP010851

Muraenesocidae Muraenesox bagio AP010852



Cynoponticus ferox AP010853

Nemichthyidae Nemichthys scolopaceus AP010854



Avocettina infans AP010855

Labichthys carinatus AP010856

Congridae Heteroconger hassi AP010859



Paraconger notialis AP010860

Ariosoma shiroanago AP010861

Conger myriaster AB03838

Nettastomatidae Nettastoma parviceps AP010864



Hoplunnis punctata AP010865

Facciolella oxyrhyncha AP010866

Serrivomeridae Serrivomer sector AP007250



S. beanii AP010857

Stemonidium hypomelas AP010858

Unidentified Thalassenchelys sp. AP010867

Unidentified Type II larva AP010868

Saccopharyngiformes

Cyematidae Cyema atrum AP010870 Saccopharyngidae Saccopharynx lavenbergi AB047825

Eurypharyngidae Eurypharynx pelecanoides AB046473

Monognathidae Monognathus jesperseni AP010869

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a Classifications follow Robins (1989) and Miller & Tsukamoto (2004)





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