ORIGINAL ARTICLE

Scombroid Fishes Provide Novel Insights into the Trait/RateAssociations of Molecular Evolution

Fan Qiu • Andrew Kitchen • J. Gordon Burleigh •

Michael M. Miyamoto

Received: 15 December 2013 / Accepted: 19 April 2014

� Springer Science+Business Media New York 2014

Abstract The study of which life history traits primarily

affect molecular evolutionary rates is often confounded by

the covariance of these traits. Scombroid fishes (billfishes,

tunas, barracudas, and their relatives) are unusual in that

their mass-specific metabolic rate is positively associated

with body size. This study exploits this atypical pattern of

trait variation, which allows for direct tests of whether

mass-specific metabolic rate or body size is the more

important factor of molecular evolutionary rates. We

inferred a phylogeny for scombroids from a supermatrix of

molecular and morphological characters and used new

phylogenetic comparative approaches to assess the asso-

ciations of body size and mass-specific metabolic rate with

substitution rate. As predicted by the body size hypothesis,

there is a negative correlation between body size and

substitution rate. However, unexpectedly, we also find a

negative association between mass-specific metabolic and

substitution rates. These relationships are supported by

analyses of the total molecular data, separate mitochondrial

and nuclear genes, and individual loci, and they are robust

to phylogenetic uncertainty. The molecular evolutionary

rates of scombroids are primarily tied to body size. This

study demonstrates that groups with novel patterns of trait

variation can be particularly informative for identifying

which life history traits are the primary factors of molec-

ular evolutionary rates.

Keywords Molecular evolutionary rates � Comparative

methods � Scombroidei � Mass-specific metabolic rate �Body size

Introduction

Molecular evolutionary rates vary greatly among taxa, and

elucidating the mechanisms that drive this variation

remains an important challenge in evolutionary biology

(Lanfear et al. 2010). A number of biological traits,

including mass-specific metabolic rate, body size, genera-

tion time, population size, DNA repair mechanisms, and

habitat, have been associated with molecular evolutionary

rates (Smith and Donoghue 2008; Bromham 2009, 2011).

However, it can be difficult to distinguish among the

individual effects of these traits because they often co-vary

(Nabholz et al. 2008; Welch et al. 2008; Lanfear et al.

2013). For example, the metabolic rate hypothesis (Martin

and Palumbi 1993; Gillooly et al. 2005; Santos 2012)

predicts that species with a high mass-specific metabolism

generate many mutagenic byproducts (e.g., reactive oxygen

species, reactive aldehydes, and singlet oxygen) through

cellular respiration. These byproducts introduce mutations

by way of oxidative DNA damage, which increases the

nucleotide substitution rate along with the mutation rate.

Correspondingly, species with high mass-specific meta-

bolic rates will have higher molecular evolutionary rates

than species with lower metabolism. However, species with

high mass-specific metabolic rates often have small body

sizes, short generation times, short lifespans, and high

fecundities, all of which may also result in higher

Electronic supplementary material The online version of thisarticle (doi:10.1007/s00239-014-9621-4) contains supplementarymaterial, which is available to authorized users.

F. Qiu (&) � J. G. Burleigh � M. M. Miyamoto

Department of Biology, University of Florida,

Box 118525, Gainesville, FL 32611-8525, USA

e-mail: fqiu@ufl.edu

A. Kitchen

Department of Anthropology, University of Iowa, Iowa City,

IA 52242-1322, USA

123

J Mol Evol

DOI 10.1007/s00239-014-9621-4

nucleotide substitution rates (Welch et al. 2008; Bromham

2009, 2011).

Bony fishes of the suborder Scombroidei (Table 1) are

unusual as they include both regionally endothermic and

ectothermic groups (Block et al. 1993; Dickson 1995;

Dickson and Graham 2004). Regional endothermy is one of

many physiological, morphological, and biochemical

adaptations for an active predatory lifestyle in the pelagic

zone. The regional endotherms, which include the billf-

ishes, tunas, and butterfly mackerel, are all able to warm

their viscera, muscles, and/or cranial regions to above

ambient temperatures. Direct experimental measures of

mass-specific standard metabolic rate (SMR) are available

from only seven scombrid species (Supplementary

Table 1). This paucity of direct experimental SMRs is due

to the many technical challenges with obtaining and

interpreting the metabolic rates of fish species that are often

large, active, pelagic, and continuously swimming (Blank

et al. 2007; Fitzgibbon et al. 2008). Nevertheless, these

seven direct estimates show that the SMRs of regional

endotherms are higher than those of ectothermic species

(Dickson and Graham 2004; Fitzgibbon et al. 2008). Fur-

thermore, the available measures of oxygen consumption

versus swimming speed from four scombrid species indi-

cate that the mass-specific maximum metabolic rates

(MMRs) of the regional endotherms are also similarly

higher (Sepulveda and Dickson 2000; Sepulveda et al.

2003). Fish physiologists have synthesized these different

lines of evidence to conclude that regional endotherms

have a higher mass-specific metabolic rate than do ecto-

thermic scombroids (Dickson and Graham 2004; Blank

et al. 2007; Fitzgibbon et al. 2008). Correspondingly,

according to the metabolic rate hypothesis, the regional

endotherms should also have higher rates of molecular

evolution.

Body size is often negatively correlated with molecular

evolutionary rate (Martin and Palumbi 1993; Gillooly et al.

2005; Welch et al. 2008; Santos 2012). This may be because

body size is tied to the number of cell divisions that are

required by an organism for its growth, maturation, and

maintenance (Bromham 2011). In this scenario, species with

more cell divisions may place a greater adaptive premium on

the efficiency of DNA replication and repair than species with

fewer cell divisions to ensure their successful development

and reproduction. Conversely, body size may be associated

with some other life history trait(s) that in turn has a greater

direct effect on molecular evolutionary rates (Bromham

2009). For example, generation time, longevity, and popula-

tion size often co-vary with body size, and these factors have

been implicated in molecular evolutionary rate variation

(Ohta 1992; Nabholz et al. 2008; Thomas et al. 2010).

In contrast to most other animal taxa, the mass-specific

metabolic rates and body sizes of scombroids are positively

correlated (Schmidt-Nielsen 1984; Bromham 2009, 2011).

The largest scombroids, including billfishes, tunas, and

butterfly mackerel, have higher mass-specific metabolic

rates than other smaller scombroids (Dickson 1995; Dick-

son and Graham 2004). Thus, unlike other animal groups,

the metabolic rate hypothesis makes a contradictory pre-

diction about the molecular evolutionary rates of the

billfishes, tunas, and butterfly mackerel than we would

expect based on body size. If metabolic inefficiency is a

major source of substitutions, then the metabolic rate

hypothesis predicts higher molecular evolutionary rates for

the regionally endothermic billfishes, tunas, and butterfly

mackerel. Conversely, if body size is a more important

factor, then the body sizes of these species suggest lower

molecular evolutionary rates.

This study exploits these contradictory predictions to

directly test whether mass-specific metabolic rate or body

size is the more important factor of molecular evolutionary

rate variation. We first inferred a scombroid phylogeny

from a molecular and morphological supermatrix and then

tested for associations between mass-specific metabolic

rate, body size, and nucleotide substitution rate using three

recently developed comparative methods that directly

account for the phylogenetic non-independence of species

(Lartillot and Poujol 2011; Mayrose and Otto 2011; Fel-

senstein 2012). These tests support the body size prediction

and refute mass-specific metabolic rate as a primary pre-

dictor of the molecular evolutionary rate variation. Our

investigation demonstrates how studying groups with

unusual patterns of trait variation can provide novel

insights into which traits are most closely associated with

variable molecular evolutionary rates.

Table 1 Scombroid taxonomy

Families Generaa Species Common namesb

Gempylidae 16 24 Snake mackerels and escolars

Istiophoridae* 3 11 Sailfishes, spearfishes, and

marlins

Scombridae 15 51 Tunas*, bonitos, mackerels, and

butterfly mackerel*

Sphyraenidae 1 21 Barracudas

Trichiuridae 10 39 Cutlassfishes, hairtails,

scabbardfishes, and frostfishes

Xiphiidae* 1 1 Swordfish

Totals 46 147

This taxonomy conforms to the traditional arrangement of six families

(Johnson 1986; Carpenter et al. 1995; Nelson 2006; Wiley and

Johnson 2010) and the National Center for Biotechnology Informa-

tion classificationa The numbers of genera and species per family follow Nelson (2006)b Asterisks mark the regionally endothermic billfishes (Istiophoridae

and Xiphiidae), tunas (Allothunnus, Auxis, Euthynnus, Katsuwonus,

and Thunnus), and butterfly mackerel (Gasterochisma melampus)

J Mol Evol

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Methods

Molecular and Morphological Systematic Data

All scombroid core nucleotide sequences were down-

loaded from the National Center for Biotechnology

Information (NCBI) on October, 2009 using the NCBI

Taxonomy Browser (Sayers et al. 2009). To generate

clusters of homologous sequences, we first performed an

all-by-all BLASTN search of all sequences (Altschul

et al. 1990). Any pair of sequences that had a significant

BLAST hit, with a maximum E-value of 10e-10 and the

pairwise alignment length covering C50 % of the length

of both sequences, was considered homologous. We then

performed single linkage clustering to obtain all clusters

of sequences (representing homologous loci) that formed

a connected component in a graph with nodes (sequen-

ces) linked by edges representing significant BLAST hits.

We identified clusters of loci that had been used in

phylogenetic inferences of bony fishes (Little et al. 2010;

Betancur et al. 2013; Miya et al. 2013) and confirmed

that their sequences were annotated similarly in Gen-

Bank. These clusters likely correspond to orthologous

sequences, given that gene duplications in mitochondrial

DNA (mtDNA) are rare, the nuclear DNA (nDNA) sets

represent low copy genes, and there is little obvious

conflict among gene trees. We then edited these clusters

of putative orthologs by deleting any sequences that

were not associated with a formal species designation

and by removing those clusters with sequences from

fewer than four species. If a species had more than one

sequence in the same cluster, then we deleted all but the

longest one.

Multiple sequence alignments for each gene cluster

were generated with MUSCLE v3.8.31 (Edgar 2004). The

initial MUSCLE alignments for the mitochondrial 12S

and 16S rRNA genes required further edits involving the

reassignment of unpaired gaps in stems to adjacent loops

as guided by the secondary structures of 12S and 16S

rRNA in teleost fishes (Cannone et al. 2002). We also

assembled a character matrix for the 62 morphological

characters described by Carpenter et al. (1995). These

characters were originally scored for different non-over-

lapping genera and families that were accepted as

monophyletic by these authors. These accepted genera

and families do not include the three genera and one

family that are not monophyletic in our maximum like-

lihood (ML) phylogeny (Supplementary Sect. 1). For each

accepted genus and family, we assigned their morpho-

logical states from Carpenter et al. (1995) to all species of

that group found in the supermatrix. We concatenated the

final alignments for all 20 genes and 62 morphological

characters to form a single supermatrix.

Phylogenetic Inference and Reference Phylogenies

We used the Akaike Information Criterion (AIC) in

MODELTEST v3.7 to identify the preferred set of parti-

tions and associated substitution models for the molecular

data (Posada and Crandall 1998). We examined various

partitioning schemes, including the use of one partition for

all molecular data, separate partitions for mtDNA and

nDNA, two subsets for protein-coding and rRNA genes,

four subdivisions for the protein-coding and rRNA loci of

both mtDNA and nDNA, and a separate subdivision for

each gene. We also extended these partitioning schemes to

include subdivisions for the first, second, and third codon

positions of the protein-coding genes and/or stems and

loops of the rRNA loci. The log likelihoods for the best

substitution models were summed across all partitions to

generate a total likelihood score and AIC for that parti-

tioning strategy. Based on a comparison of the total AICs

for each partitioning strategy, we used a separate partition

for the first, second, and third codon positions of each

protein-coding gene and for the stems and loops of each

rRNA locus, with various substitution models for these 56

partitions (Supplementary Table 2). The morphological

characters comprised their own partition, and we used the

Mk model for this subdivision (Lewis 2001).

Maximum likelihood phylogenetic inference of the

partitioned molecular and morphological data was per-

formed with GARLI v2.0 using two sequential chains of

100 million generations each (Zwickl 2006). We also

performed 1,000 nonparametric bootstrap replicates to

assess phylogenetic uncertainty (Felsenstein 1985).

For the comparative analyses, we used the ML phy-

logeny as well as 20 randomly selected bootstrap trees to

examine the possible effects of phylogenetic uncertainty.

We were limited to 20 bootstrap trees by the intensive

computational demands of our comparative analyses. The

branch lengths of the ML phylogeny and 20 bootstrap trees

were estimated by GARLI with the molecular data only.

We also transformed the molecular branch lengths of the

21 trees to make them ultrametric using the penalized

likelihood method implemented in r8s v1.8 (Sanderson

2003) prior to their use as the reference phylogenies in the

comparative tests. These ultrametric conversions were

performed with a smoothing parameter of 10, which was

selected by cross validation based on 12 well-documented

calibration dates from the scombroid fossil record (Sup-

plementary Table 3).

Rate Variation Among Lineages

The degree of rate heterogeneity among lineages was

quantified with the index of dispersion [R(t); Bedford and

Hartl 2008]. Substitution rates were estimated by r8s for all

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internodes of the ML phylogeny after the ultrametric

conversion of its branch lengths for the total molecular

data. These estimates of substitution rates were converted

into weighted counts of substitutions per branch following

the procedure of Bedford and Hartl (2008). The index of

dispersion was then calculated for scombroids as the var-

iance-to-mean ratio of these weighted substitution counts.

The expected value for this ratio is 1 if the weighted sub-

stitution counts are Poisson distributed.

Body Size and Mass-Specific Metabolic Rate Data

Estimates of maximum body mass (in kg) were derived

from different sources (Supplementary Table 4) and then

log transformed. Scombroids are a relatively well-studied

group (Collette 2010; FishBase October 2012; http://www.

fishbase.org), which thereby minimizes the problem of

sampling error in estimations of both maximum and aver-

age body mass. Maximum body mass was chosen over

average body mass because it is reported for the entire

species, whereas the average is often presented for a par-

ticular stock or population. For example, Yamashita et al.

(2005) reported an average body mass of 3.6 kg for skip-

jack tuna (Katsuwonus pelamis) from around Japan,

whereas Kaneko and Ralston (2007) published an average

body mass of 8.6 kg for this species from near Hawaii.

Mass-specific metabolic rate was scored as a binary

character with ‘‘high’’ states for regionally endothermic

billfishes, tunas, and butterfly mackerel and ‘‘low’’ states

for the ectothermic scombroids. Mass-specific metabolic

rate was scored as a binary, rather than continuous, trait

because direct experimental SMRs are available for only

seven scombrids (Supplementary Table 1). The scoring of

regionally endothermic and ectothermic species as ‘‘high’’

and ‘‘low’’, respectively, follows the widely accepted

conclusion of fish physiologists (Sepulveda and Dickson

2000; Sepulveda et al. 2003; Dickson and Graham 2004;

Blank et al. 2007; Fitzgibbon et al. 2008).

Correlation of Body Size and Mass-Specific Metabolic

Rate

We tested for a correlation between body size and mass-

specific metabolic rate with the Comparative Threshold

Test (CTT) of THRESHML (Felsenstein 2012). The CTT

assumes that each binary character (i.e., high/low mass-

specific metabolic rate) is determined by an unobserved

continuous trait known as the liability. Liability values that

exceed an estimated threshold result in state ‘‘1’’ (e.g., high

mass-specific metabolic rate) for the discrete character.

The CTT uses the current provisional covariance matrix to

transform the continuous and liability characters of the

internal and/or external nodes of the tree into a set of new

variables that are evolving along the phylogeny by inde-

pendent Brownian motion. This set of variables is updated

by Markov chain Monte Carlo (MCMC) sampling that is

operating within a likelihood framework. The resultant

MCMC samples allow for the re-estimation of the covari-

ance matrix, and thereby, an inference of the correlation

between the evolutionary changes of the continuous and

discrete characters along the phylogeny.

Our CTT was performed with 30 consecutive chains of

one million generations each (i.e., successive cycles of

updated covariance matrix and transformed characters).

The proposal size for the Metropolis updates of tip liabil-

ities was set to 7.5. Burn-in was retained at the default

length of 1,000 initial liabilities. Such long runs and larger

proposal sizes were necessary to maintain the acceptance

rate of the newly proposed tip liabilities at *0.47 and to

minimize the transformation errors to \2 %. The rela-

tionship between log maximum body mass and mass-spe-

cific metabolic rate was determined with the Pearson

product-moment correlation coefficient (Pearson’s r).

Association of Mass-Specific Metabolic and Molecular

Evolutionary Rates

The association between the binary character for mass-spe-

cific metabolic rate and substitution rate was assessed with a

likelihood ratio test (LRT) in TRAITRATE v1.1 (Mayrose

and Otto 2011). The LRT evaluates the null hypothesis of no

association between the mass-specific metabolic and

molecular evolutionary rates. Specifically, it compares the fit

of a two-clock model, which estimates separate substitution

rates for each character state, to that of a null model with a

single substitution rate for the entire tree. The two-clock

model estimates r, which represents the ratio of the substi-

tution rates associated with the two character states.

We performed 100 stochastic character mappings using

the total molecular data, separate mtDNA and nDNA

genes, and eight individual mtDNA and nDNA loci with

sequences from [20 species from all six families (Sup-

plementary Table 2). TRAITRATE does not allow parti-

tioned data nor does it estimate the proportion of invariable

sites (I). It also provides only four substitution models (JC,

K80, HKY, and GTR; Mayrose and Otto 2011). Thus, each

LRT was performed using a single partition and the pre-

ferred model (of the four available in TRAITRATE) as

determined by MODELTEST. Furthermore, the gamma

distribution alone (C) was used to account for rate variation

among sites even when the best model called for ‘‘C?I’’ or

‘‘I’’. The significance of each LRT was evaluated using the

Chi square distribution with a of 0.0005. We used a con-

servative cutoff to evaluate the test statistic (d) because

parametric bootstrapping was not computationally feasible

for all datasets.

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Correlation of Body Size and Molecular Evolutionary

Rate

The correlation between body size and substitution rate

was assessed with the Phylogenetic Corrected Covariance

Test (PCCT) of COEVOL v1.3c (Lartillot and Poujol

2011). The PCCT uses a Bayesian MCMC approach to

generate a phylogenetic corrected covariance matrix for the

continuous traits and substitution rate parameters under

study. The evolution of the traits and substitution rates is

modeled along the phylogeny using a multivariate

Brownian diffusion process. The PCCT imposes a prior on

the covariance matrix that is conjugate to the Brownian

process and also relies on data augmentation, whereby the

MCMC sampling is conditional on a complete history

(mapping) of substitutions for all sites across the phylog-

eny. These strategies greatly improve the computational

efficiency of the PCCT.

Log maximum body mass and substitution rate were the

trait and molecular evolutionary parameter of interest in

our PCCTs, respectively. The PCCTs were performed for

the total molecular data, separate mtDNA and nDNA

genes, and eight individual loci with sequences from [20

species from all six families using the GTR model that is

provided in the program. Each PCCT consisted of 50,000

consecutive cycles of data augmentation (i.e., successive

re-samplings of the substitution history as conditioned on

the current parameter values) and a 10 % burn-in. Such

long runs were necessary to ensure effective sample sizes of

[200 for all datasets. The prior mean variance parameter

for the two components of the covariance matrix was set to

a truncated Jeffreys’ prior. The mean substitution rate

along each branch was calculated with the geodesic aver-

aging procedure. A posterior probability of \0.025 for a

positive Pearson’s r was considered decisive for a negative

correlation between body size and substitution rate (Lar-

tillot and Poujol 2011).

The PCCTs were conducted with the same 12 well-doc-

umented dates from the scombroid fossil record that were

used to date the reference phylogenies with r8s (Supple-

mentary Table 3). COEVOL also requires that an age esti-

mate be provided for the root of the tree. In the absence of

such an estimate from the fossil record, we used the average

and standard deviation age of the roots for the ML phylogeny

and 1,000 bootstrap trees as estimated by penalized likeli-

hood in r8s (152.5 ? 17.3 million years ago).

Data Accessibility

Our molecular and morphological supermatrix, reference

phylogenies, and input/output files for the comparative

analyses are available on FigShare (http://dx.doi.org/10.

6084/m9.figshare.1011438).

Results

Highly Variable Rates of Molecular Evolution

The index of dispersion for the weighted substitution

counts for all branches of the ML phylogeny (Fig. 1)

indicates a high level of rate variation among scombroid

lineages. The variance-to-mean ratio of the weighted sub-

stitution counts for scombroids is 14.0. This ratio for

scombroids exceeds the Poisson expectation of 1 by an

even greater amount than the overdispersed R(t) estimates

of *5 for mammals and *1.5–3.0 for Drosophila (Bed-

ford and Hartl 2008; Bedford et al. 2008). Thus, scombroid

substitution rates are highly variable, and it is this hetero-

geneity that remains the focus of our comparative tests with

mass-specific metabolic rate and body size (Tables 2, 3).

Positive Correlation Between Body Size and Mass-

Specific Metabolic Rate

The CTT with the ML phylogeny (Fig. 1) supports a sig-

nificant positive correlation between log maximum body

mass and the liability character for high/low mass-specific

metabolic rate (Pearson’s r = 0.396, degrees of free-

dom = 95, P \ 0.001). The covariance between body size

and mass-specific metabolic rate is 0.188, and body size

explains 15.7 % of the total variation in the liability of

metabolic rate. The CTTs with the 20 bootstrap trees also

consistently support a significant positive correlation

between body size and mass-specific metabolic rate

(Pearson’s r, range of 0.348–0.491; P \ 0.001 in each

case). Collectively, these results provide new phylogenetic

comparative corroboration for the previous conclusion of

fish physiologists (Dickson 1995; Dickson and Graham

2004; Fitzgibbon et al. 2008) that billfishes, tunas, and

butterfly mackerel share a high mass-specific metabolic

rate and are also the bigger scombroids.

Negative Association Between Mass-Specific

Metabolic and Substitution Rates

The LRTs with the ML phylogeny support a significant

association between mass-specific metabolic and substitu-

tion rates for the total molecular data as well as the mtDNA

and nDNA genes (Table 2). The ML estimates of r (the

substitution rate ratio for high and low metabolisms) range

from 0.449 to 0.705 for these three datasets, indicating that

high substitution rates are associated with low mass-spe-

cific metabolic rates. A significant association is similarly

found for all eight individual mtDNA and nDNA genes

with the larger samples. Parameter r for these eight genes

ranges from 0.220 to 0.851 (mean = 0.464). The LRTs

also recover a significant negative association in C95 % of

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the bootstrap replicates for all datasets, except for Cyt b

and ND 2 (75 and 60 %, respectively). Still, r is \1.0 for

these two genes in 85 and 95 % of their bootstrap repli-

cates, respectively. Collectively, the LRTs support a neg-

ative association between mass-specific metabolic and

substitution rates, whereby species with a high mass-spe-

cific metabolic rate (regionally endothermic billfishes,

tunas, and butterfly mackerel) have molecular evolutionary

rates that are *50 % slower than those of species with a

low metabolism (ectothermic scombroids). This negative

(not positive) association contradicts the metabolic rate

hypothesis as a primary explanation of the molecular

evolutionary rate variation.

Negative Correlation Between Body Size

and Substitution Rate

The PCCTs with the ML phylogeny support a decisive

negative correlation between log maximum body mass and

substitution rate for the total molecular data as well as the

mtDNA and nDNA genes (Table 3). Body size explains

between 13.8 and 29.9 % of the total variation in substi-

tution rate for these three datasets. A decisive negative

correlation is similarly found for three of the five mtDNA

and two of the three nDNA genes with the larger samples.

Although non-decisive, a negative covariance is still sup-

ported for Cyt b, 16S rRNA, and Rhod. The PCCTs with the

20 bootstrap trees also recover a decisive negative corre-

lation in C95 % of the replicates for the same datasets as

those using the ML phylogeny, except for the mtDNA

genes, ND 2, and 12S rRNA (80, 55, and 75 %, respec-

tively). Furthermore, a negative covariance is found in

C95 % of all bootstrap replicates for all datasets. Collec-

tively, the PCCTs support a negative correlation between

body size and substitution rate, whereby the large species

(predominantly billfishes, tunas, and butterfly mackerel)

have lower molecular evolutionary rates than the small

ones. This relationship is consistent with the prediction of

the body size hypothesis.

Discussion

Evidence Contradicting the Metabolic Rate Hypothesis

The metabolic rate hypothesis was supported early on by

mtDNA and nDNA analyses of endothermic and ectother-

mic vertebrates (Martin et al. 1992; Martin and Palumbi

1993). Lanfear et al. (2007) later rejected the metabolic rate

hypothesis based on a study of 12 nDNA and mtDNA genes

for [300 metazoan species. Recently, Santos (2012)

Table 2 Likelihood ratio tests per gene and genome with the ML phylogeny as the reference tree (Fig. 1) and high/low mass-specific metabolic

rate as the trait of interest

Genomes Genesa Log likelihood

under the

null model

Log likelihood

under the

two-clock model

Likelihood

ratio test

statistic (d)b

Relative

rate

parameter (r)

Bootstrap

proportionsc

MtDNA COX I (73) -18,251.90 -18,149.20 205.40 0.560 1.00 {1.00}

Cyt b (72) -22,315.70 -22,306.30 18.80 0.851 0.75 {0.85}

ND 2 (42) -15,484.70 -15,465.30 38.80 0.751 0.60 {0.95}

16S rRNA (40) -5,802.35 -5,733.44 137.82 0.220 1.00 {1.00}

12S rRNA (40) -4,670.42 -4,557.38 226.08 0.223 1.00 {1.00}

All 11 genes (96) -81,073.30 -80,848.50 449.60 0.705 1.00 {1.00}

NDNA Tmo-4c4 (57) -3,594.45 -3,575.50 37.90 0.370 1.00 {1.00}

Rhod (38) -4,844.95 -4,823.38 43.14 0.413 0.95 {1.00}

RAG 2 (21) -5,391.34 -5,341.02 100.64 0.326 1.00 {1.00}

All 9 genes (64) -20,704.00 -20,621.60 164.80 0.449 1.00 {1.00}

MtDNA and nDNA All 20 genes (97) -102,357.00 -102,101.00 512.00 0.651 1.00 {1.00}

a The numbers of sampled species per gene and genome are given in parenthesesb All of these LRTs are significant at a = 0.0005c Bootstrap proportions refer to the frequencies of 20 bootstrap trees that recover a significant association or an r \ 1.0 (in curly brackets)

b Fig. 1 Molecular and morphological ML phylogeny. This ML

phylogeny is rooted with Sphyraenidae (Carpenter et al. 1995; Nelson

2006). Bootstrap scores are presented for internal branches with

[50 % support. Branches are proportional to their molecular branch

lengths. For display purposes, branches with double slashes are

shortened by 50 %. Red and blue highlight species with high and low

mass-specific metabolic rates, respectively, disk shading corresponds

to the log maximum body mass (kg) of each species (Supplementary

Table 4), the numbers of sampled sequences per species are given in

parentheses, and the 12 dated nodes for the r8s and COEVOL

analyses are numbered according to Supplementary Table 3. Details

about the molecular and morphological supermatrix, the relationships

within the tree, the bootstrap support values, and the estimated dates

for the internal nodes without fossil calibrations are provided in

Supplementary Sects. 1 and 2

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demonstrated that the mass-specific active (but not resting)

metabolic rates of poison frogs are positively correlated with

their nDNA and mtDNA substitution rates. These mass-

specific active and resting metabolic rates correspond to the

MMRs and SMRs of fishes, respectively (Sepulveda and

Dickson 2000; Sepulveda et al. 2003).

We find that the nucleotide substitution rates of scomb-

roids are negatively associated with their mass-specific

metabolic rates (Table 2). This negative association is cor-

roborated across all molecular data, genomes, and genes,

which suggests that it is an organism, and not a gene or

genome, specific effect and not an artifact of sampling error.

It is the opposite trend predicted if a high metabolic rate is a

major source of substitutions. In particular, the lack of a

positive association in the mtDNA datasets is telling, given

that the mitochondrion is the primary site in the cell where

mutagenic metabolic byproducts are produced (Martin and

Palumbi 1993; Lanfear et al. 2007). Although a positive

relationship between mass-specific metabolic and substitu-

tion rates may be masked by other correlated characters (i.e.,

body size), the negative association in our analyses contra-

dicts the metabolic rate hypothesis as a primary explanation

of molecular evolutionary rate variation. Correspondingly,

our negative relationship likely reflects the unusual positive

co-variation of scombroid mass-specific metabolic rate with

body size (Dickson 1995; Dickson and Graham 2004; our

CTT results).

While mass-specific metabolic rates may play a major

role in some systems, our study provides further evidence

that the metabolic rate hypothesis is not a general expla-

nation of molecular evolutionary rate variation across

animals (Lanfear et al. 2007). This raises the question of

whether previous support for the metabolic rate hypothesis

may have been driven by covariates of mass-specific

metabolic rate (Bromham 2011).

Support for an Association of Body Size and Molecular

Evolutionary Rate

The negative correlation between body size and substitu-

tion rate that we find across all molecular data, genomes,

and genes (Table 3) is consistent with the prediction that

larger species should have lower molecular evolutionary

rates (Bromham 2009, 2011). However, we cannot reject

the possibility that a covariate of body size, and not body

size itself, has a more direct influence on substitution rates.

For example, generation time, which is often positively

correlated with body size, is frequently implicated as a

factor in the molecular evolutionary rates of animals and

plants (Smith and Donoghue 2008; Thomas et al. 2010;

Wilson Sayres et al. 2011). Also, longevity, another com-

mon covariate of body size, is often proposed to influence

molecular evolutionary rates, especially in mtDNA studies

(Nabholz et al. 2008; Welch et al. 2008). In animals with

deterministic development, body size, generation time, and

longevity can be mechanistically related to the rate of

mitosis hypothesis, which posits that the accumulation of

germ line mutations and substitutions per unit time is

linked to the number of mitotic cellular divisions from

zygote to reproductive adult (Lanfear et al. 2013). As more

reliable estimates of these and other life history traits

become available, we recommend that future studies of

Table 3 Phylogenetic corrected covariance tests per gene and genome with the ML phylogeny as the source tree (Fig. 1) and maximum body

mass as the trait of interest

Genomes Genesa Covarianceb Pearson’s r Posterior probabilityc Bootstrap proportionsd

MtDNA COX I (73) -5.040 -0.664 0.000* 1.00 {1.00}

Cyt b (72) -1.310 -0.170 0.180 0.00 {1.00}

ND 2 (42) -1.820 -0.613 0.003* 0.55 {1.00}

16S rRNA (40) -1.490 -0.192 0.280 0.00 {0.95}

12S rRNA (40) -7.650 -0.892 0.000* 0.75 {1.00}

All 11 genes (96) -3.330 -0.372 0.013* 0.80 {1.00}

NDNA Tmo-4c4 (57) -5.130 -0.619 0.000* 1.00 {1.00}

Rhod (38) -2.840 -0.256 0.170 0.00 {1.00}

RAG 2 (21) -12.300 -0.956 0.000* 1.00 {1.00}

All 9 genes (64) -4.880 -0.547 0.001* 1.00 {1.00}

MtDNA and nDNA All 20 genes (97) -4.060 -0.380 0.006* 0.95 {1.00}

a The numbers of sampled species per gene and genome are given in parenthesesb Covariance and Pearson’s r are estimated as the means of their posterior distributionsc Asterisks highlight posterior probabilities of \0.025, which are decisive for a negative Pearson’s rd Bootstrap proportions refer to the frequencies of 20 bootstrap trees that support a decisive posterior probability of \0.025 or a negative

covariance (in curly brackets)

J Mol Evol

123

scombroid molecular evolutionary rates first test whether

these factors (as for mass-specific metabolic rate) are cor-

related with body size in atypical ways (i.e., in a negative

direction for generation time and lifespan).

New Comparative Methods for Traits and Substitution

Rates

Our analyses take advantage of recent advances in phylo-

genetic comparative methods that provide an explicit sta-

tistical framework to test associations of characters with

each other and with molecular evolutionary rates.

THRESHML is presented as the first fully developed

procedure for the phylogenetic comparison of both binary

and continuous traits (Felsenstein 2012). This method dif-

fers from the Phylogenetic Logistic Regression procedure

of Ives and Garland (2010) in that it accounts for the

evolution of both the binary and continuous traits along the

phylogeny, while Phylogenetic Logistic Regression fixes

the continuous characters as known variables of the

external tips. In turn, TRAITRATE (Mayrose and Otto

2011) and COEVOL (Lartillot and Poujol 2011) are new

fully integrated statistical methods to test for the correla-

tion of a binary or continuous trait and the substitution rate,

respectively. In particular, TRAITRATE differs from the

ML method of O’Connor and Mundy (2009) in that it tests

for a phenotype/genotype association among all positions

rather than at a subset of the sites. These three new com-

parative methods make complete use of all branches of the

phylogeny, and thus the full covariance structure among

species, in their phylogenetic comparisons.

In addition to simple linear regressions (i.e., as used in

Table 3), COEVOL can also perform phylogenetic multi-

ple regressions of two or more continuous traits and sub-

stitution rates (Lartillot and Poujol 2011). We were unable

to conduct robust COEVOL multiple regressions of

scombroid mass-specific metabolic rate, maximum body

mass, and substitution rate due to the availability of direct

SMR estimates for only seven scombrid species (Supple-

mentary Table 1). This paucity of direct continuous SMRs

necessitated the TRAITRATE analyses of mass-specific

metabolic rate as a binary trait (Table 2). Still, we have

completed preliminary COEVOL multiple regressions for

the seven known scombrid species as an illustration of how

such tests can be done once a sufficient sample of experi-

mental SMRs is obtained (Supplementary Sect. 3). Obvi-

ously, the results of these preliminary tests must be treated

with caution as they have very low power. Nevertheless, it

is intriguing that we find no pattern of a consistent positive

partial correlation between SMR and substitution rate when

body size is held constant (contra the metabolic rate

hypothesis; Supplementary Table 5). This inconsistency

stands in contrast to the uniform trend of a negative partial

correlation that is found between body size and substitution

rate when mass-specific metabolic rate is controlled for.

The Utility of Groups with Novel Trait Variations

The molecular evolutionary rate for a group can be con-

sidered a character of its life history (Bromham 2011).

Understood in this way, it is not surprising that the sub-

stitution rate for a group is commonly intertwined in

complex ways with many of its other life history traits.

Parsing the effects of individual components within such

complex interrelationships will benefit from the study of

groups with different patterns of trait variation (Nabholz

et al. 2008; Welch et al. 2008). In this study, we exploit the

unusual positive association of scombroid mass-specific

metabolic rate and body size to generate opposing predic-

tions that allow for direct testing of the primacy of the

traits. We thereby document how groups with novel pat-

terns of trait variation can help to untangle the relative

importance of typically confounded factors.

Cartilaginous fishes of the family Myliobatidae consti-

tute another marine group with larger species that share

morphological specializations for regional endothermy

(Dickson and Graham 2004; Bernal et al. 2012). Coupled

with their active and pelagic lifestyles, manta and devil

rays have been considered ‘‘warm bodied’’ (Alexander

1996), which thereby identifies their family as another fish

group with the rare positive association between body size

and mass-specific metabolic rate. However, direct esti-

mates of mass-specific metabolic rate are known for only

three ectothermic myliobatid species (i.e., no such mea-

sures exist for manta and devil rays; Neer et al. 2006).

Furthermore, the taxon sampling of their DNA sequences

remains limited, as most comparative molecular studies of

the family have focused on DNA barcoding and population

genetic questions (Schluessel et al. 2010; Naylor et al.

2012). Nevertheless, myliobatid rays remain a promising

group to independently test the conclusions and recom-

mendations of this study. Future comparative analyses of

their unusual trait variation and substitution rates may

provide further insights into which typically confounded

life history factors are central to the pace of molecular

evolution.

Acknowledgments We thank Charles Baer, Keith Choe, Jamie

Gillooly, Debra Murie, Larry Page, Jose Ponciano, Michele Tennant,

and Ying Wang for their helpful recommendations.

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