Abstract
We determined the whole mitochondrial genome sequence for spotted green pufferfish, Tetraodon nigroviridis (Teleostei: Tetraodontiformes). The genome (16,488 bp) contained 37 genes (two ribosomal RNA genes, 22 transfer RNA genes, and 13 protein-coding genes) plus control region as found in other vertebrates, with the gene order identical to that of typical vertebrates. The sequence was used to estimate phylogenetic relationships and divergence times among major lineages of fishes, including representative model organisms in fishes. We employed partitioned Bayesian approaches for these two analyses using two datasets that comprised concatenated amino acid sequences from 12 protein-coding genes (excluding the ND6 gene) and concatenated nucleotide sequences from the 12 protein-coding genes (without 3rd codon positions), 22 transfer RNA genes, and two ribosomal RNA genes. The resultant trees from the two datasets were well resolved and largely congruent with those from previous studies, with spotted green pufferfish being placed in a reasonable phylogenetic position. The approximate divergence times between spotted green pufferfish and model organisms in fishes were 85 million years ago (MYA) vs. torafugu, 183 MYA vs. three-spined stickleback, 191 MYA vs. medaka, and 324 MYA vs. zebrafish, all of which were about twice as old as the divergence times estimated by their earliest occurrences in fossil records.
INTRODUCTION
The human genome sequence was generated by the Human Genome Project (Venter et al., 2001) , and using it we can identify and characterize human genes. Most genetic information that governs how humans develop and function is encoded in their genome sequence. Comparing the genomes of different organisms will guide future approaches to understanding gene function, regulation, and evolution. Recently, the genomes of several fishes have been sequenced and compared with the human and other vertebrates' genomes. Torafugu ( Takifugu rubripes ) became the second vertebrate organism to be sequenced to draft quality prior to tetrapods (Aparicio et al., 2002) . Other genome projects for several species of ray-finned fishes, such as spotted green pufferfish ( Tetraodon nigroviridis ), zebrafish ( Danio rerio ), medaka ( Oryzias latipes ), and three-spined stickleback ( Gasterosteus aculeatus ), are also ongoing.
INTRODUCTION
Although ray-finned fishes and humans diverged from their common ancestor as long as 450 MYA (Kumazawa et al., 1999; Hedges and Kumar, 2003) , their genomes have essentially the same genes and regulatory sequences. Furthermore, some ray-finned fishes have great advantages over mammals for research purposes: many are small and easy to maintain and have short reproductive cycles. Among ray-finned fishes, pufferfishes have a genome of approximately 400 Mb, and the effort needed for sequencing to obtain a comparable amount of information is modest by comparison with the effort needed for mammalian genomes (2.0-5.0 Gb). The spotted green pufferfish, Tetraodon nigroviridis , was proposed as a model organism for genomic studies (Crnogorac-Jurcevic et al., 1997) , and recently its draft sequence was published (Jaillon et al., 2004) .
INTRODUCTION
The correct interpretation of any kind of comparative biological data requires an evolutionary framework, namely, well-supported phylogeny with precise divergence times. Compared with the relationships among other vertebrate groups, relationships among major lineages of ray-finned fishes, comprising over half of all vertebrate species, remain ill defined, and thus the proposed relationships among model organisms in fishes have traditionally relied on morphology-based hypotheses. Only recently, several efforts are underway that rely on extensive taxonomic coverage of the diversity of ray-finned fishes to estimate higher-level relationships (e.g., . There are a few studies on divergence time estimation for ray-finned fishes, and the estimates based on the earliest fossil records and molecular clock were very different. Molecular clock estimates were much older than fossil estimates; for example, fossil records have shown that the radiation of Perciformes dates back to the early Cenozoic (Benton, 1993 (Benton, , 2005 , but a molecular clock estimate has placed it from the Jurassic to the early Cretaceous (Kumazawa et al., 1999) . In studies on model organisms in fishes, the proposed divergence times have exclusively referred to the estimates based on the earliest fossil records (e.g., Volff et al., 2003; Chen et al., 2004) .
INTRODUCTION
In this study, we determined the whole mitochondrial genome sequence for the spotted green pufferfish, Tetraodon nigroviridis , and analyzed its genome contents. Recent studies have used many genes to estimate divergence times in the hope of reducing the effect of rate variation (Nei and Glazko, 2002) . We used the whole mitochondrial genome sequence to estimate the divergence times between the model organisms and major fish lineages because they have been demonstrated in recent studies to be useful for estimating the divergence times among basal lineages within tetrapods (Kumazawa et al., 2004) , primates (Schrago and Russo, 2003) , and actinopterygians (Inoue et al., 2005) . The partitioned Bayesian approach, which does not assume constancy of evolutionary rates (Thorne and Kishino, 2002) , was employed for estimation of divergence times because evolutionary rate heterogeneity was observed in the mitochondrial genes among the species used in this study.
MATERIALS AND METHODS
Sample and DNA extraction. A portion of the epaxial musculature (about 0.25g) was excised from a fresh specimen and immediately preserved in 99.5% ethanol. Total genomic DNA was extracted using a Qiagen DNeasy tissue kit (Qiagen) following the manufacturer's protocol. The voucher specimen was deposited at the Department of Zoology, Natural History Museum & Institute, Chiba (CBM-ZF 10554).
MATERIALS AND METHODS
PCR and sequencing. The mitochondrial genome of spotted green pufferfish was amplified in its entirety using a long polymerase chain reaction (PCR) technique (Cheng et al., 1994) . Long PCR primers (Table 1) were used so as to amplify the entire mitochondrial genome in two reactions. The long-PCR products were diluted with TE buffer (1:19) for subsequent use as PCR templates.
MATERIALS AND METHODS
A total of 67 fish-versatile PCR primers and a speciesspecific primer (Table 1) were used in various combinations to amplify contiguous, overlapping segments of the entire mitochondrial genome for spotted green pufferfish. Long PCR and subsequent short PCR were carried out as previously described (e.g., Miya and Nishida, 1999; Inoue et al., 2003) . Double-stranded PCR products, purified using ExoSAP-IT (USB), were subsequently used for direct cycle sequencing with dye-labeled terminators (Applied Biosystems). The primers used were the same as those for PCR. All sequencing reactions were performed according to the manufacturer's instructions. Labeled fragments were analyzed using a Model 377 DNA sequencer (Applied Biosystems).
MATERIALS AND METHODS
Alignments. We chose five model species for genome science (spotted green pufferfish, torafugu, three-spined stickleback, medaka, and zebrafish) and representatives from major lineages of fishes (total 21 species, Table  2 ). Final rooting was done using the small-spotted catshark.
MATERIALS AND METHODS
The DNA sequences were edited and analyzed with EditView ver. 1.0.1, AutoAssembler ver. 2.1 (Applied Biosystems), and DNASIS ver. 3.2 (Hitachi Software Engineering Co. Ltd.). The individual gene sequences for the 21 species were aligned manually using DNASIS based on the previously aligned sequences of 48 teleosts (Miya et al., 2001) . Amino acids were used for alignments of the protein-coding genes and secondary structure models (Kumazawa and Nishida, 1993) were used for the alignment of tRNA genes. Since strictly secondary-structurebased alignment for the two rRNA genes was impractical for the large dataset, we instead employed machine alignment, which would minimize erroneous assessment of the positional homology of the rRNA molecules. The two Mitochondrial genome of green pufferfish rRNA gene (12S and 16S rRNA) sequences were aligned using Clustal X (Thompson et al., 1997) with default gap penalties.
MATERIALS AND METHODS
The ND6 gene was not used in the phylogenetic analyses because of its heterogeneous base composition and consistently poor phylogenetic performance . Ambiguously aligned regions, such as the 5´ and 3´ ends of several protein-coding genes and loop regions of several tRNA genes, were excluded from the analyses. The "saturation" at 3rd codon positions in the protein-coding genes was eliminated from the analyses by translating nucleotide sequences into amino acid sequences or simply excluding 3rd codon positions in the protein-coding genes, leaving a total of 14,384 available nucleotide positions (10,809, 1480, and 2095 positions for protein-coding, tRNA, and rRNA genes, respectively) for the analyses. Two datasets were used in our analyses: dataset #1: concatenated amino acid sequences from 12 protein-coding genes (total 3603 positions); dataset #2: concatenated nucleotide sequences from 12 protein-coding genes (without 3rd codon positions), 22 tRNA genes, and two rRNA genes (total 10,781 positions).
MATERIALS AND METHODS
Phylogenetic analysis. Partitioned Bayesian phylogenetic analyses were conducted with MrBayes ver. 3.1 (Ronquist and Huelsenbeck, 2003) . We set 12 (dataset #1: 12 protein-coding genes) and 4 (dataset #2: 1st, 2nd codon positions, tRNA genes, and rRNA genes) partitions depending on the datasets. We used the mtmam (Yang et al., 1998) model with some sites assumed to follow a discrete gamma distribution (mtmam + Γ ; Yang, 1994) for dataset #1, and the two-parameter model variant for unequal base frequencies (HKY85; Hasegawa et al., 1985) with variable sites assumed to follow a discrete gamma distribution (HKY85 + Γ ) for dataset #2. We assumed that all of the model parameters were unlinked and the rate multipliers were variable across partitions for datasets #1 and #2. The Markov chain Monte Carlo (MCMC) process was set so that four chains (three heated and one cold) ran simultaneously. On the basis of preliminary runs with varying cycles (100,000-500,000), we estimated average log likelihood scores at stationarity (dataset #1 ≈ -45,590; dataset #2 ≈ -82,890), and subsequently conducted two independent runs for each dataset. After reaching stationarity in the two runs at 20,000 cycles, we continued the runs for 980,000 cycles to confirm lack of improvement in the likelihood scores, with one in every 100 trees being sampled. Posterior probabilities for internal branches and parameters of the model of sequence evolution for the two sets of 980,000 cycles (9800 trees) after reaching stationarity were in excellent agreement for the two datasets. Thus, we determined posterior probabilities of the phylogeny and its branches based on the 19,600-pooled trees from the two runs for the two datasets.
MATERIALS AND METHODS
Divergence time estimation. The analysis of divergence time was conducted with the partitioned Bayesian approach (Thorne and Kishino, 2002 Takezaki et al., 1995) . As a reference point for dating, the divergence time between sarcopterygians and actinopterygians (450 MYA) was used for the age of root node following previous analyses based on both fossils and molecules (see Kumazawa et al., 1999; Hedges and Kumar, 2003) . The program Thornian Time Traveler ver. 1.0 (T3; see http://abacus.gene.ucl.ac.uk/) was used to estimate the divergence time following the partitioned Bayesian method of Thorne and Kishino (2002) . We set 12 (dataset #1) and four (dataset #2: 1st, 2nd, codon positions, tRNA, and rRNA genes) partitions depending on the datasets. For dataset #2, we assumed that functional constraints on sequence evolution are more similar within codon positions (or types of molecules) across genes than across codon positions (or types of molecules) within genes. Branch lengths were estimated with the estbNewAA and estbNew programs of T3 for datasets #1 and #2, respectively, in conjunction with the tree topology obtained by Bayesian analysis of dataset #2 (Fig. 1) , which was identical with those from the previous studies (e.g., Miya et al., 2003) . We used the mtmam + Γ model for dataset #1 and the HKY85 + Γ model for dataset #2. For dataset #2, we used the baseml program in the PAML ver. 3.14 package (Yang, 1997) to obtain estimates of the transition/transversion rate ratio and the rates for site classes under the discrete-gamma model of rates among sites under the HKY85 + Γ model. Divergence time was estimated using the program multidivtime of T3. In each case, Markov chain Monte Carlo (MCMC) approximations were obtained with a burnin period of 100,000 proposal cycles. Thereafter, samples of the Markov chain were taken every 100 cycles until a total of 10,000 samples were obtained. To diagnose possible failure of the Markov chains to converge on their stationary distribution, we performed at least two replicate MCMC runs with different initial starting points for each analysis. Application of the multidivtime program requires a value for the mean of the prior distribution for the time separating the ingroup root from the present Fig. 1 . Phylogenetic tree of 20 bony fishes plus an outgroup and prior distribution of divergence times. We assumed that the tree topology was fixed in the topology, which is the 50% majority rule consensus tree of the 19,600-pooled trees from the two independent Bayesian analyses of dataset #2 [concatenated nucleotide sequences from 12 protein-coding genes (without 3rd codon positions), 22 tRNA genes, and two rRNA genes (total 10,781 positions)] using MrBayes 3.1 (Ronquist and Huelsenbeck, 2003) with HKY85 + Γ model of sequence evolution. The asterisks indicate branches supported by posterior probabilities less than 100% (Node 13: 79%; Node 14: 91%). Topological incongruities with dataset #1 are denoted by arrowheads. Ages for earliest fossil records are shown to right of the tree. The divergence time between sarcopterygians and actinopterygians (Node 1), i.e., 450 MYA, was used for the age of root node following previous analyses based on both fossils and molecules (see Kumazawa et al., 1999; Hedges and Kumar, 2003) . In the partitioned Bayesian approach, we used the two maximum (U) and nine minimum (L) constraints according to the fossil and molecular information (Table 3) .
MATERIALS AND METHODS
(rttm). We used a conservative estimate of 450 MYA for rttm (see above). Other settings for running multidivtime were as follows: standard deviation of rttm (rttmsd) = 0.5 × rttm; rtrate = X/rttm, where rtrate is the mean of prior distribution for the rate at the root node and X is the median amount of evolution from the ingroup root to the ingroup tips; rtratesd = 0.5 × rtrate, where rtratesd is the standard deviation of rtrate; rttm × brownmean = 1, where brownmean is the mean of the prior distribution for the autocorrelation parameter (í); and brownsd = brownmean, where brownsd is the standard deviation of the prior distribution for ν .
MATERIALS AND METHODS
The multidivtime program allows for both minimum and maximum fossil constraints. Whereas minima are often based on earliest occurrences in the fossil record, maxima are intrinsically more difficult to estimate. However, we constrained two upper limits to obtain narrower credibility intervals on posterior divergence times according to Kishino and Thorne (2002) . With the exception of Nodes 1 and 2 (Table 3, Fig. 1 ), we could not use the maximum because fossils of teleosts are not well preserved in general (Benton, 1993; Kumazawa et al., 1999) . Accordingly, we used the two maximum and nine minimum constraints for the divergence time estimation (Table 3 , Fig. 1 ).
RESULTS AND DISCUSSION
Genome organization. The complete L-strand nucleotide sequence of the spotted green pufferfish mitochondrial genome has been registered in DDBJ/EMBL/ GenBank under the accession number AP006046 . The total length of the mitochondrial genome of spotted green pufferfish is 16,488 bp. The genome contents included 13 protein-coding, 22 tRNA, and two rRNA genes, and a control region, as found in other vertebrates. Also, as in other vertebrates, most genes were encoded on the H strand, except for the ND6 gene and eight tRNA genes (tRNA-Gln, tRNA-Ala, tRNA-Asn, tRNA-Cys, tRNA-Tyr, tRNA-Ser (UCN), tRNA-Glu, and tRNA-Pro genes), and all genes were similar in length to those in other vertebrates. The gene arrangement was identical to those in typical vertebrates.
RESULTS AND DISCUSSION
Protein-coding genes. There were 13 protein-coding genes, of which two reading-frame overlaps on the same strand (ATP8 and ATP6 shared 10 nucleotides; ND4L and ND4 shared seven nucleotides). All protein-coding genes began with an ATG start codon, except for the COI gene, which started with GTG. Stop codons of protein-coding genes were TAA in the ATP8, Cyt b , ND4L, and ND5 genes, TAG in the ND1 gene, TA in the ATP6, ND2, and COIII genes, T in the COII, ND3, and ND4 genes, and AGG in the COI and ND6 genes. For those genes that have an incomplete stop codon, the transcripts would be modified to form the complete termination signal UAA by polyadenylation after cleavage of the polycistronic RNA, as demonstrated for other metazoan mtDNAs (Ojala et al., 1981) .
RESULTS AND DISCUSSION
Transfer RNA genes. The mitochondrial genome of spotted green pufferfish contained 22 tRNA genes, which were in clusters or individually scattered in the genome. The tRNA genes ranged in size from 64 to 74 nucleotides, large enough that the encoded tRNAs can fold into the cloverleaf secondary structure characteristic of tRNAs. This structure was possible provided that formation of the G-U wobble and other atypical pairings were allowed in the stem regions. All postulated cloverleaf structures Table 3 Maximum (U) and minimum (L) constrains (MYA) and calibration information for constraints in Fig. 1 Node Constraints Calibration information 1 U528 The estimated divergence time between chondrichthyans and osteichthyans (528 MYA) from independent molecule studies (Kumazawa et al., 1999; Kumazawa and Nishida, 2000; Hedges and Kumar, 2003) 1 L411 The Andreolepis fossil (Actinopterygii) from Ludfordian (Silurian)* 2 U450 The estimated divergence time between sarcopterygians and actinopterygians (450 MYA) based on both fossils and molecules (Kumazawa et al., 1999; Hedges and Kumar, 2003 The tetraodontiform fossil from 95 MYA (Cretaceous) (Tyler and Sorbini, 1996) 17 L56.5
RESULTS AND DISCUSSION
The balistoid fossil from Thanetian (Paleocene) (Tyler and Bannikov, 1992) * Minima (L) are based on earliest occurrences in the fossil records (Benton, 1993) .
RESULTS AND DISCUSSION
contained 7 bp in the amino acid stem, 5 bp in the TYC stem, 5 bp in the anticodon stem, and 4 bp in the DHU stem, except that there were 3 bp in DHU stem of the tRNA-Ser (AGY) gene.
RESULTS AND DISCUSSION
Ribosomal RNA genes. The 12S rRNA and 16S rRNA genes of spotted green pufferfish were 949 bp and 1676 bp, respectively. They were located, as in other vertebrates, between the tRNA-Phe and tRNA-Leu (UUR) genes, being separated by the tRNA-Val gene. Preliminary assessment of their secondary structure indicated that the present sequences could be reasonably superimposed on the proposed secondary structure of goby 12S rRNA (Wang and Lee, 2002) and loach 16S rRNA (Gutell et al., 1993) .
RESULTS AND DISCUSSION
Non-coding sequences. As in most vertebrates, the origin of light strand replication (O L ) in spotted green pufferfish was 33 bp, located between the tRNA-Asn and tRNA-Cys genes. This region has the potential to fold into a stable stem-loop secondary structure with 20 bp in the stem and 13 bp in the loop. The conserved motif 5´-GCCGG-3´ was found at the base of the stem within the tRNA-Cys gene (Hixson et al., 1986) . The major non-coding region found in spotted green pufferfish is located between the tRNA-Pro and tRNAPhe genes and its length is 810 bp. This non-coding sequence appears to correspond to the control region, because it has several conserved sequence blocks (CSB) and a terminal-associated sequence (TAS), which are characteristic of the region (Doda et al., 1981; Walberg and Clayton, 1981) .
RESULTS AND DISCUSSION
Phylogenetic analysis. Fig. 1 shows a 50% majority rule consensus tree of the 19,600 combined samples from the two Bayesian analyses of the 21 whole mitogenomic sequences from the concatenated 12 protein-coding, 22 tRNA genes, plus two rRNA genes (dataset #2) using the HKY85 + Γ model of sequence evolution (Hasegawa et al., 1985) . Most of the internal branches were supported by high Bayesian posterior probabilities (= 100%) except for two nodes. The resultant topology was identical with those from previous studies (e.g., Miya et al., 2001 Miya et al., , 2003 Inoue et al., 2003) . Bayesian analysis using amino acid sequences of 12 protein-coding genes (dataset #1) produced a similar tree, with minor differences in the placements of Japanese sardine and bastard halibut (Fig.  1) . The position of spotted green pufferfish was consistently supported as a sister species of torafugu, with these two species forming a clade with the other tetraodontiforms, masked triggerfish and thread-sail filefish.
RESULTS AND DISCUSSION
Divergence time estimation among model organisms. The partitioned Bayesian approach estimated the divergence times between green spotted pufferfish and other model organisms as follows (datasets #1/#2): 96.2/ 73.3 MYA vs. torafugu (Node 18 in Fig. 2 ), 191.5/175.1 MYA vs. three-spined stickleback (Node 14), 198.6/183.7 MYA vs. medaka (Node 12) , and 333.0/314.7 MYA vs. zebrafish (Node 3). The divergence time estimates between spotted green pufferfish and major lineages of fishes are also shown in Fig. 2 and Table 4 . On the whole, the estimates made using dataset #1 (amino acids) were slightly older than those made using dataset #2 (nucleotides), but the 95% credibility intervals from the two estimates largely overlapped with each other. In the following discussion, we use the averages of the estimates from the two datasets as the estimated divergence times for convenience.
RESULTS AND DISCUSSION
Benton (2005) analyzed the radiation of ray-finned fishes based on earliest fossil records, and reported divergence times much more recent than those in this study, especially for those of higher teleost fishes (Table 4) : bowfin/other actinopterygians (Node 2 in Fig. 2 Kumazawa et al. (1999) estimated divergence times of major lineages of ray-finned fishes based on mitochondrial ND2 and Cyt b genes using a molecular-clock approach, and obtained estimates largely congruent with those obtained in this study. The rate calibration of Kumazawa et al. (1999) was based on the assumption that African and neotropical cichlids diverged 100 MYA and that actinopterygians and sarcopterygians split 450 MYA. Inoue et al. (2005) estimated divergence times of basal ray-finned fishes using the same methods and sequences as employed in this study, and obtained estimated times slightly more recent than those in this study. Crnogorac-Jurcevic et al. (1997) calculated the divergence time between torafugu and spotted green pufferfish to be [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] by using a molecular clock of 376 bp of Cyt b gene sequences based on Cantatore et al. (1994) . Cantatore et al. (1994) estimated the rates of monica61@example.com% per million years by using five shark species, and the divergence time between Acipenseriformes and Perciformes was calibrated to be about 200 MYA, corresponding to Node 2 in Fig. 2 [403. 6 MYA].
RESULTS AND DISCUSSION
There appears to be a considerable time gap between the molecular and fossil evidence. The fossil estimates are usually based on the earliest occurrences. The earliest fossil records, however, do not necessarily indicate that a group diverged from its sister group at that time. In addition, fossil records tend to be incomplete in various respects and the long-term lack of teleostean fossils was probably influenced by the population sizes and taphonomic conditions for fossilization (Kumazawa et al., 1999) . Also it has been reported that molecular divergence time estimates often exceed fossil estimates in ver-tebrates (e.g., Springer et al., 2003; Inoue et al., 2005) . We interpret this apparent discrepancy to be indicative of the paucity of teleostean fossil records rather than the inaccuracy of our molecular time estimates.
RESULTS AND DISCUSSION
A timescale is necessary not only for estimating rates of molecular and morphological changes in organisms but also for interpreting patterns of macroevolution and biogeography. Moreover, the availability of genomic data from model organisms has created a demand for reliable estimation of divergence time to help understand the temporal component of evolution. The results obtained in this study were much older than those based on the earliest occurrences of fossil records and were in accord with those obtained by Kumazawa et al. (1999) , implying that the radiation of major lineages of ray-finned fishes is much older than previously thought. Even in recent genomic studies of fishes, however, calculation of evolutionary rates or understanding of patterns of evolution was obtained exclusively from divergence times estimated from the earliest fossil records. This accumulated knowledge associated with timescale should be reconsidered based on molecular estimation. More detailed analyses with further taxonomic sampling may allow reliable estimation of the timescale for fish evolution. Fig. 1 using the mtmam + Γ model of sequence evolution. The horizontal rectangles represent the estimated 95% credibility intervals of divergence times. Arrowheads indicate the nodes under maximum or minimum constraints (see Table 3 , Fig. 1) .
RESULTS AND DISCUSSION
We thank N. B. Ishiguro, M. M. Yamauchi, and other graduate students at the Molecular Marine Biology Laboratory, Ocean Research Institute, University of Tokyo, for their helpful suggestions during this study. We also thank Jacob Egge for correcting the English in the manuscript. Critical comments from two anonymous reviewers were helpful to improve the manuscript. A portion of this study was supported by Grants-in-Aid from the Ministry of Education, Culture, Sports, Science, and Technology, Japan (13556028, 13640711, 15570090, 15380131, and 12NP0201) and Research Fellowship of the Japan Society for the Promotion of Science for Young Scientists (07304). 

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