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SYSTEMATIC BIOLOGY
VOL. 54
Syst. Biol. 54(6):952–961, 2005
c Society of Systematic Biologists
Copyright ISSN: 1063-5157 print / 1076-836X online
DOI: 10.1080/10635150500234674
Between Two Extremes: Mitochondrial DNA is neither the Panacea nor the Nemesis
of Phylogenetic and Taxonomic Inference
D ANIEL R UBINOFF1 AND B RENDEN S. HOLLAND 2
1
Department of Plant and Environmental Protection Sciences, University of Hawaii, 3050 Maile Way, 310 Gilmore Hall, Honolulu, Hawaii 96822,
USA; E-mail: rubinoff@hawaii.edu
2
Center for Conservation Research and Training, University of Hawaii, 3050 Maile Way, 408 Gilmore Hall, Honolulu, Hawaii 96822, USA
“Don’t throw out the baby with the bathwater”
anon
“Don’t drink the bathwater either”
D.R.
Recently, the role of mitochondrial DNA (mtDNA) sequences in taxonomy and phylogenetic inference has
become contentious, and two extreme viewpoints have
emerged, although, as far as we know, never juxtaposed prior to this article. One position criticizes the
use of mtDNA because the marker suggests misleading patterns of variation; specifically, phylogenies that
are inconsistent with those derived from nuclear gene
sequences in the context of species relationships among
closely related taxa (Ballard and Whitlock, 2004; Shaw,
2002). The other extreme, the DNA “barcode” movement, espouses the sole use of small fragments of a single
mtDNA gene, cytochrome c oxidase I (COI), to identify
most of life (Hebert et al., 2003a). The intention of this
article is to present the disadvantages of these two extreme viewpoints and to argue for an integrated role for
mtDNA, one that takes advantage of mtDNA’s strengths
but also accounts for its shortcomings by using it in concert with other independent data sources (e.g., nuclear
DNA, cytosystematic, morphological, behavioral). We
are against the abolition of the use of mtDNA in phylogenetics but also against its narrow use in barcoding as currently defined. We demonstrate why neither viewpoint
is particularly productive and emphasize how analysis
of mtDNA can be an important tool in the context of both
taxonomic and phylogenetic studies.
The use of mtDNA in phylogenetics has been contentious since it became clear that individual gene and
species phylogenetic trees are not always congruent
(Avise, 2004; Avise et al., 1983; Avise and Saunders, 1984),
and discrepancies between nuclear and mtDNA inheritance patterns have been well documented (see Funk and
Omland, 2003). Recently, there has been a striking discord on the suitability of mtDNA in phylogenetics and
taxonomy. Some (Hebert et al., 2003b) have argued that
mtDNA barcodes, or approximately 600-bp segments of
a small and discrete part of the genome, can be used to
identify all of life, though the issue is actively debated
(Hebert et al., 2003, 2004; Lipscomb et al., 2003; Moritz
and Cicero, 2004; Pennisi, 2003; Scotland et al., 2003;
Seberg et al., 2003; Will and Rubinoff, 2004). In sharp contrast to advocates of the use of mtDNA barcode segments
alone for the identification of all biodiversity, others caution against use of certain mtDNA genes in some taxa
(Lin and Danforth, 2004; Thalmann et al., 2004), whereas
Ballard and Whitlock (2004), referencing studies such
as that of Shaw (2002), question the utility of mtDNA
for any study of systematics or phylogenetics. They advocate elimination of mtDNA from phylogenetic studies, suggesting that it is “risky to infer general patterns
from an idiosyncratic small fraction of the genome” (page
731). The implication is that mtDNA can be inaccurate
or diverges from the true phylogeny. We argue that most
phylogenetic studies, other than the handful employing a large-scale, multigenomic approach (Rokas et al.,
2003), may suffer drawbacks from using only a small
fraction of the total genome. But it strikes us as misleading to strongly criticize use of a character source that has
yielded over 25 years of phylogenetic data, the majority
of which have proven useful, with dozens of published
oligonucleotide primer sets and approximately 250,000
entries available in GenBank, DDBJ, and EMBL, including complete mtDNA genomes for more than 800 species
(http://www.mitomap.org/euk mitos.html). The optimal role for mtDNA is somewhere between these extreme positions. Although these two radical viewpoints
have not been juxtaposed in previous arguments, they
are intrinsically related and are best examined in light of
one another.
The contentions on the one hand that mtDNA is misleading and on the other hand that it is universally applicable for systematic identification and reconstruction of
evolutionary history are not mutually tenable. We maintain that neither viewpoint considers the appropriate role
that mtDNA should play in systematic studies because
both fail to consider the information provided by the
gene in context. We discuss the criticisms of mtDNA
made by Ballard and Whitlock (2004) and point out
why these authors do not satisfactorily justify avoiding
mtDNA as a marker for phylogenetic reconstruction; the
data conflicts they cite as problems can be informative
when the context for the conflict is understood. We illustrate our point using Ballard and Whitlock’s (2004) argument and their reference to Shaw’s (2002) conclusions
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POINTS OF VIEW
(which led her to disavow results based on a mtDNA
data set), finally demonstrating how, in spite of its limitations, informed use of mtDNA is appropriate, practical,
and often essential. We continue with a caution against
so-called DNA barcoding, as currently espoused, and
briefly discuss why it is detrimental to systematic and
biodiversity studies because the research model fails to
recognize the importance of conflicting data in a broader
context. We conclude with a presentation of an appropriate, integrated role for mtDNA that considers issues
from both extreme viewpoints.
T HE UTILITY AND LIMITATIONS OF M ITOCHONDRIAL
DNA M ARKERS
In terms of sheer number of characters, statistical
power, and time spent in analysis, variable nucleic acid
sequences provide the most abundant source of data
and an important comparative data set for morphological, cytological, and ecological characters in evolutionary studies. Analysis of mtDNA sequence data has
been used extensively to study the evolutionary relationships both within and among species. Mitochondrial
DNA offers a particularly rich source of markers for the
study of closely related taxa because of the very low
rate of recombination (Piganeau et al., 2004), maternal
inheritance, simple genetic structure, reduced effective
population size (Ne ), and relatively rapid rates of evolution (Avise et al., 1983; Moritz et al., 1987). In “higher”
animals, the circular double-stranded mtDNA chromosome is one of the most well-characterized components
of the genome, and comprises approximately 16 kb encoding 2 rRNAs, 22 tRNAs, and usually 13 other genes
primarily encoding electron transport proteins (Moritz
et al., 1987). Varying levels of evolutionary and functional constraints result in rate heterogeneity within and
among genes. The phylogenetic effects of mitochondrial
introgression are particularly important because a lack
of recombination suggests that all mitochondrial gene
positions introgress as a completely linked block (Smith,
1992). This phenomenon provides a partial explanation of why mtDNA is so effective for measuring hybridization. Animal mtDNA has also proven extremely
powerful for inferring genealogical and evolutionary relationships among and within populations. Since mitochondrial DNA sequences frequently evolve faster than
do nuclear sequences (Brown et al., 1979; Kocher, 1991;
Moritz et al., 1987), the number of variable sites, as well
as informative sites, is often greater for mtDNA than for
nuclear loci. Because of relatively rapid rates of substitution, mtDNA is particularly useful for species-level and
genus-level analyses; however, for deeper divergences,
saturation can result in homoplasy, because phylogenetic
signal is diminished (Caterino et al., 2001; Holland et al.,
2004; Reed and Sperling, 1999; Rubinoff and Sperling,
2002).
Technical problems can arise with nucleic acid data
sets depending on various factors that may be locus specific, taxon specific, and technique specific, as well as ar-
953
tifacts. For example, in certain insect taxa, some mtDNA
genes exhibit more heterogeneous patterns of amongsite substitution rate variation (thus lower α, or gamma
shape parameter) than do some nuclear genes (Lin and
Danforth, 2004). Because there is a positive correlation
between consistency index (CI) and gamma shape parameter (α) (Lin and Danforth, 2004), data sets with more
homogeneous among-site substitution patterns tend to
have less homoplasy. Additionally, in general, nuclear
loci tend to have less biased base composition than do
mitochondrial genes (Lin and Danforth, 2004), with certain notable exceptions (Tarrı́o et al., 2001). Inadvertent
polymerase chain reaction (PCR) amplification of nuclear copies of highly conserved mtDNA genes has led
to problems as well, particularly with D-loop control
region analyses in vertebrates (Thalmann et al., 2004;
Zhang and Hewitt, 1996a), and in certain invertebrate
taxa (Zhang and Hewitt, 1996b). In such cases, nuclear
copies of mtDNA genes can be coamplified by PCR with
the mtDNA sequences and hinder the use of the marker
in population analyses. However, nuclear genes suffer
from multiple technical drawbacks as well; nuclear loci
(nDNA) can be more difficult to work with because of
heterozygosity, low substitution rate, low copy number,
and the frequent occurrence of paralogous loci with multiple copies. For example, as pointed out by Lin and
Danforth (2004), the nuclear gene wingless occurs in at
least five copies and therefore should be approached with
extreme caution when considering it for use in phylogenetic applications (Schubert et al., 2000). It is a subjective
exercise to focus on the drawbacks of mtDNA in isolation and to judge the inherent difficulties with mtDNA as
being more acute than those associated with nuclear loci.
M ITOCHONDRIAL DNA R EPRESENTS
EVOLUTIONARY HISTORY
One of the main arguments made against using
mtDNA is that it is maternally inherited and therefore
does not represent the “true” genomic (i.e., nuclear) inheritance of an organism (Ballard and Whitlock, 2004).
Although mtDNA does not necessarily always reflect
nuclear inheritance patterns, it does represent a fundamental element of an organism’s heritage and evolutionary history—certainly not the only, or definitive,
source of genetic information, but nonetheless valid
and accurate. Mitochondrial function is fundamental
to cellular survival. As such, the patterns of selection
and inheritance reflected in segments of its genome are
also nontrivial. Mitochondrial DNA is no less a part
of an organism, and therefore an organism’s evolutionary history, than nDNA; to say otherwise is an arbitrary and unfounded devaluation of a character set.
Differential inheritance patterns between the nuclear
and mitochondrial genomes are not necessarily uninformative since accurate, legitimate, evolutionarily based
disagreement between two sources of data is not false
phylogenetic signal (Avise and Wollenberg, 1997). For
example, incongruence among true trees (n versus mt
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VOL. 54
or n versus n) should be integrated when attempting to
delineate species boundaries (Milinkovitch et al., 2002).
In a literature review of 584 mtDNA-based, low-level
animal phylogeny and phylogeography studies, Funk
and Omland (2003) detected species-level paraphyly or
polyphyly in 23% of 2319 assayed species. They found
the phenomenon to be statistically supported, taxonomically widespread, and more common than generally
realized. However, far from calling for elimination or
limitations on the use of mtDNA (i.e., blaming the tool)
in such studies, the authors argued for increased attention to sampling and interpretation of paraphyletic and
polyphyletic gene trees, and for a “new tradition of congeneric phylogeography” based on mtDNA. Funk and
Omland (2003) went on to invoke and discuss causes for
these patterns, including imperfect taxonomy, selection,
interspecific hybridization, paralogy, and incomplete lineage sorting. Evidence of species-level polyphyly and paraphyly can be systematically problematic if undetected,
yet when recognized, it can provide informative clues
that motivate future work (Funk, 1996; Harrison, 1998;
Milinkovitch et al., 2002).
Independent sources of characters, such as mtDNA
and nDNA, can reflect different, but equally accurate,
phylogenetic patterns (Bowen et al., 2005; Patton and
Smith, 1994; Sperling and Harrison, 1994; Talbot and
Shields, 1996; Baker and Gatesy, 2002; Griffiths et al.,
2004; Avise and Wollenberg, 1997). Incongruence between two data sources does not, innately, provide a criterion by which to select one phylogeny over another.
In fact, such disagreements often lead to an enhanced
understanding of the evolutionary history of the taxa in
question, including elucidation of patterns of introgression, complex population structure, and sex-biased gene
flow (see Bowen et al., 2005). Quality data sets that have
disagreement between mtDNA and nDNA should be
considered to be of at least the same value, perhaps even
of greater value, than data sets that are strictly congruent,
because the incongruence enriches our understanding
of evolutionary processes. Incorporating and analyzing
incongruent data sets remains a challenging and
contentious issue because the major problem is to differentiate “real” conflicts (i.e., conflicting but true gene phylogenies characterized by differential lineage sorting)
from “erroneous” conflicts (i.e., one or several of the gene
phylogenetic trees are wrong because of homoplasy).
tify the same tree. Phylogenetic congruence refers to the
agreement among partitions; for example, between phylogenetic estimates based on different sets or sources of
characters (Page and Holmes, 1998) or between a gene
tree and the species tree (Avise, 2004; Maddison, 1996), or
internal agreement in the informative characters within
a single partition (Hillis et al., 1996). If substitution rates
exceed a certain threshold and are heterogeneously distributed, and branch lengths meet certain configurations,
then inconsistency has been shown to be a problem for
all classes of phylogenetic analysis, including maximum
parsimony, minimum evolution, and maximum likelihood approaches (Felsenstein, 1978; Waddell et al., 2000).
Regardless of the method used, faster-evolving characters often strongly disagree with more slowly evolving
characters in recovering the underlying tree, and the
combined data sets may indicate an incorrect tree (Bull
et al., 1993). Therefore, many authors recommend that
an effort be made to detect data partitions that lead to
inferences of statistically distinct trees and to proceed
cautiously if differences are found (Cunningham, 1997).
Statistical techniques for coping with multiple data
sources and evaluating congruence have therefore become important and contentious, and a variety of viewpoints have emerged (see Baker and Gatesy, 2002; Bull
et al., 1993; de Queiroz et al., 1995; DeSalle and Brower,
1997; Farris et al., 1994; 1995; Funk and Omland, 2003;
Huelsenbeck et al., 1996; Kishino and Hasegawa, 1989;
Kluge, 1989; Larson, 1994; Nixon and Carpenter, 1996;
Reed and Sperling, 1999; Shimodaira and Hasegawa,
1999; Waddell et al., 2000).
A qualitative measure of phylogenetic robustness can
be obtained by comparison of topologies produced using
various analytic methods, such as maximum parsimony
and maximum likelihood, or by the use of statistics
such as bootstrap support (Felsenstein, 1985) or posterior probabilities (Huelsenbeck, 2001; Lemmon and
Milinkovitch, 2002). In cases where different methods
give similar topologies, confidence that the results represent the true evolutionary history of the characters comprising the data set is enhanced (Carranza et al., 2002;
Holland and Hadfield, 2004). Similarly, when multiple
independent data partitions indicate cohesive evolutionary patterns, confidence is increased that the data sets reflect the same evolutionary history (Cunningham, 1997;
Rubinoff and Sperling, 2002).
COMBINING D ATA S ETS AND PROBLEMS WITH
CONGRUENCE
There is a growing preference for using multiple
molecular data sources, rather than a single data source,
which is increasingly facilitated by the availability of
high throughput DNA sequencing methods (Hillis et al.,
1996; Rokas et al., 2003). When different types of data
are employed in a phylogenetic analysis, an important
issue is whether they lead to the same conclusion, once
sampling error is eliminated. The data set may consist
of a mixture of sites or data partitions (a gene, a portion of a gene, a set of genes, etc.) that may not iden-
CAUSES OF I NCONGRUENCE
The difference between a tree estimate and the true tree
is a function of stochastic variance about the estimator’s
mean resulting from sample size, stochastic bias, and systematic error (Waddell et al., 2000). However, stochastic
bias decreases rapidly with increasing sequence length
and rarely has been shown to be a dominant factor in tree
inference. Another cause of incongruence is retention
of ancestral polymorphism through differential sorting,
although taxa outside of species complexes tend to be
separated by reasonably long periods that are typically
longer than the ancestral population coalescence time.
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POINTS OF VIEW
Furthermore, if recombination rates are similar to substitution rates, finding gene trees that disagree strongly;
e.g., with the bootstrap, is even more unlikely (Waddell,
1995).
Causes of disagreement between gene and species
trees have been addressed (e.g., Avise, 2000; Maddison,
1996). According to Maddison (1996), disagreement between these trees can be caused by common ancestry
of gene copies at a particular locus extending deeper
than speciation events. Separate genetic lineages that
coexisted in ancestral species, and subsequently sorted
out differentially into the descendant species’ sampled
copies, is one source of such disagreement (Avise, 1983;
Maddison, 1996). Another source of discordance is gene
duplication, where one copy of a duplicated gene may
be lost, and therefore the tree of the surviving copy disagrees with the species tree (Goodman et al., 1979). A
third possible cause of gene versus species tree incongruence is horizontal gene transfer (Cummings, 1994),
in which the gene copy breaks the bounds of the species
tree and is transferred between branches, either by a viral
mechanism or through hybridization.
Disagreement among multiple data sets is often accompanied by topologies with low statistical support
(bootstrap, Bremer decay index, etc.). In such instances,
some authors propose that combining the data into a single analysis can improve resolution of and support for
the reconstruction (Baker and Gatesy, 2002). Indeed, several studies have demonstrated that homoplasious data
sets may contain informative phylogenetic signal (Baker
et al., 2001; Baker and DeSalle, 1997, Savolainen et al.,
2000).
Several recent studies have cautioned against use of
mtDNA (Hare, 2001; Lin and Danforth, 2004; Shaw, 2002;
Thalmann et al., 2004; Zhang and Hewitt, 2003), but
Ballard and Whitlock (2004) have made the most fervent argument. They conceded that mtDNA has been
historically informative in phylogenetic inference, but
contended that it should be discarded from future phylogenetic studies because of problems with its “natural
history,” including recombination, effective population
size, mutation rates, introgression, and neutrality. Their
arguments are frequently based on problems that also occur in single-copy nuclear genes (Avise, 2004) (heterogeneous mutation rates, non-neutrality, recombination), or
are points that, when considered in context, are actually
arguments that support the inclusion of mitochondrial
data in a combined analysis.
Depending on life-history traits such as population
level history, degree of isolation, reproductive strategy,
and levels of hybridization, incongruent patterns may
occur between mtDNA and nDNA phylogenetic trees.
However, the benefits derived from information gained
through use of mtDNA markers far outweigh any disadvantages. In many instances, mtDNA and nDNA markers analyzed together can provide statistically robust, informative, congruent, and thorough reconstructions of
the phylogenies of closely related species and/or populations (e.g., Reed and Sperling, 1999; Rubinoff and
Sperling, 2002; Caterino et al., 2001).
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ELIMINATING mtDNA ANALYSIS B ASED ON
“M ISLEADING R ESULTS ”
In support of their position for avoiding mtDNA in
phylogenetic inference, Ballard and Whitlock referred
to Shaw (2002), who contended that admittedly rare
hybridization events followed by selection on mtDNA
haplotypes can cause the displacement of a species’
mtDNA haplotype with that of a sympatric congener.
We agree with Ballard and Whitlock (2004) that “Introgression is particulary important for closely related
sympatric taxa—successful hybridization is more likely
with closely related taxa and is only possible with some
sympatry” (page 736), and with their contention that
exchange of sister species haplotypes is also expected
where allopatric differentiation has occurred followed
by secondary contact and hybridization. But mtDNA is
a well-established tool for detecting introgression events
and defining hybrid zones in spite of its uniparental
mode of inheritance (e.g., Avise and Saunders, 1984; Carr
et al., 1986; Moritz et al., 1987) and provides both an
opportunity to detect the direction of gene flow in hybrid crosses and enhances the ability to distinguish the
effects of introgression from symplesiomorphy or character convergence caused by linkage among mtDNA
markers (Avise and Saunders, 1992). Despite some interesting and useful results in Shaw’s (2002) study, there
are several technical issues that should be addressed in
light of its use by Ballard and Whitlock (2004) as support
for avoiding mtDNA.
Specifically, Shaw (2002) concluded that the nDNAbased phylogenetic tree is preferred because of its
agreement with Otte’s (1994) “Laupala species groups”
hypothesis, which contends, based on morphology, that
the Hawaiian species of the cricket genus Laupala fall into
the following three clades: kauai, pacifica, and cerasina.
However, the strict consensus mtDNA tree (Fig. 1) from
Shaw (2002) shows multiple unsupported clades. Apparently the Laupala mtDNA tree has internal disagreement
of characters sampled, perhaps because of homoplasy.
Shaw (2002) concluded that the nDNA tree is the correct topology, and that sympatric species are not each
others’ closest relatives, even though only two of the
species groups are supported (cerasina and pacifica) and
only moderately (bootstrap 63%) in the nDNA tree. It
is ill-advised to use a poorly supported mtDNA tree to
make a point in support of one approach over another
(nDNA over mtDNA). The poor support for the mtDNA
tree might be addressed by adding additional mtDNA
characters. The logical response to such discordance is
not the expulsion of one data partition (mtDNA), but further sampling of additional mtDNA sequence to confirm
the phenomenon and to minimize the possibility that
sampling error is the cause of incongruence. For these
reasons, Shaw’s study does not provide adequate justification or support for Ballard and Whitlock’s contention
that studies using nDNA alone should be pursued.
Shaw (2002) did not discuss combined analysis of the
data sets, nor did she present results of agreement analyses such as the commonly used incongruence length
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difference (ILD) tests or likelihood-ratio tests (LRT). Although there are multiple perspectives on the issue, ranging from the view that combining poorly resolved trees
produces improved results, or at least offers the potential
for new insights not possible with individual data sets
(Baker and Gatesy, 2002), to views that data sets should
be rigorously tested and combined only if preestablished
statistical criteria indicating that they do not differ significantly are met (e.g., Bull et al., 1993; Huelsenbeck, 1996;
Waddell et al., 2000).
VOL. 54
One implication of Shaw’s (2002) mtDNA phylogeny
is that hybridization may be common among the sister
taxa examined, and is therefore likely to be an important evolutionary force. We argue that incongruence in
data partitions is not justification for disregarding one of
the sources (Baker and Gatesy, 2002) and that combining accurate data is often more informative than analysis of one data type (Bowen et al., 2005). Empirical
investigations have demonstrated that combining heterogeneous data can produce well-resolved and strongly
FIGURE 1. Nuclear (anonymous intron, Fig. 1a) and mtDNA (partial 12S, 16S, and tRNAval , b) phylogenies of Hawaiian Laupala crickets
(modified from Shaw 2002). Shaw (2002) concluded from these contrasting topologies that the nDNA reconstruction was superior because of its
congruence with Otte’s (1994) morphology-based species groupings, whereas the mtDNA tree was in significant conflict with these groupings
and was therefore a “misleading” result. The relationships shown in the mtDNA topology generally have lower bootstrap support than the
nDNA tree. The mtDNA tree was generated from less than half the data as the nDNA tree (531 and 1085 base pairs, respectively). Otte’s cerasina
species group is represented by open boxes at the terminal branch positions of each tree, whereas the pacifica group is indicated by closed boxes,
and the Kauai group has no representative symbol. Note that the majority of clades in the mtDNA topology that are in conflict with Otte’s
Hawaiian Laupala species groupings are statistically not supported (1000 bootstrap replicates). (Continued)
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957
FIGURE 1. (Continued)
supported hypotheses (Baker and DeSalle, 1997). Even
when two data sets violate commonly used tests such
as ILD (Farris et al., 1994, but see Yoder et al., 2001), if
the two data sets are combined, the resulting tree has
greater support, stability, and resolution than trees resulting from separate analyses (Baker and Gatesy, 2002;
Baker and DeSalle, 1997). Combined analyses (e.g., morphological, cytological, nDNA, and mtDNA) should at
least be explored when independent sources are available. For example, we analyzed the 37 cricket isolates
(with PAUP*3.0b10; Swofford, 2002) from Shaw (2002)
for which both mtDNA and nDNA sequences were available from Genbank. A maximum parsimony analysis of
the combined data set gave a well-resolved phylogenetic tree with CI = 0.713, and ModelTest (Posada and
Crandall, 1998) was run through PAUP to produce a
gamma shape parameter = 0.8931 (based on the TRN
+I+G substitution model), suggesting relatively high
among site substitution rate homogeneity between the
genomes.
We agree with Ballard and Whitlock (2004) that further research into the natural history of mtDNA is likely
to be a fruitful pursuit. But the gaps in our knowledge of the molecule and its history do not preclude
its utility. In practical terms (which we do not mean
to be the primary justification), far more primer sets
and well-characterized genetic markers are available for
mtDNA than for nDNA, particularly for research focusing on invertebrate systematics. Considering the practicality and technical strengths of this resource, we find
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the suggestion by Ballard and Whitlock (2004) that evolutionary biologists turn away from this vast potential
source of data misguided at best.
DNA B ARCODING AND THE LIMITS
OF mtDNA R ESOLUTION
The use of so-called barcodes (approximately 600-bp
DNA fragments of mtDNA for animals, plastid DNA for
plants) as the sole source of data to identify all of life is
a concept that has been a source of recent controversy
(Hebert et al., 2003a; Lipscomb et al., 2003; Pennisi, 2003;
Scotland et al., 2003; Seberg et al., 2003; Sperling, 2003;
Will and Rubinoff, 2004). Although several papers claim
to have demonstrated the utility of barcodes (Whitfield,
2003; Hebert et al., 2003b, 2004; Stoeckle, 2003; Stoeckle
et al., 2003), we concur with those authors who feel that
mtDNA barcodes cannot fulfill the promise their proponents tout. We will not reiterate the complete argument
on either side but refer the interested reader to the cited
literature. However, it is pertinent to consider the opposing point of view that the barcoding movement offers
to Ballard and Whitlock’s discard of mtDNA discussed
above. Many of the same arguments we use above to defend the use of mtDNA could be seen as a defense or
support for DNA barcoding in another context. In fact,
many of the arguments put forth by Ballard and Whitlock
against the use of mtDNA are actually appropriate criticisms for those who would advocate the sole use of the
mtDNA molecule in new species identification. For example, the Shaw (2002) mtDNA tree (Fig. 1) confounds
species-level relationships compared to nDNA and morphologically based taxonomy. The extreme viewpoints
regarding mtDNA err in degree but not necessarily in
their nature. There are several important distinctions that
separate our advocacy for the retention of mtDNA in
phylogenetics from the barcoders’ suggestion that it can
be the sole source of data for taxonomy.
What is new about the DNA barcoding concept is
its scale and proposed standardization of the effort
(Moritz and Cicero, 2004). DNA barcoding proposes
to use a limited segment of the COI gene for most
species level identifications (e.g., excluding plants), to
assign unknown individuals to species, and to enhance
discovery of new species (Hebert et al., 2003a). One
issue is whether the “one gene fits all” concept is appropriate for large-scale analyses. In addition, such a limited data set is likely to produce errors simply because
more data generally improve the accuracy of an analysis (Cummings, 1994; Poe and Swofford, 1999; Mitchell
et al., 2000). Furthermore, horizontal gene transfer,
introgression, and the presence of pseudogenes can
commonly affect mtDNA-based analyses, resulting in
paraphyletic and polyphyletic relationships (Funk and
Omland, 2003). The reasons given by Ballard and
Whitlock for abandoning mtDNA might have been more
productively applied to argue against its sole use, as
in the case of barcoding. Multiple sources of data will
give the most accurate representation of the evolutionary history of a group of organisms. Single-copy nu-
VOL. 54
clear DNA and morphology may provide some of the
most robust indicators of overall inheritance, whereas
mtDNA can either support such a phylogeny or provide
essential information regarding the evolution of a particular taxon through mtDNA’s discontinuity with other
data sources. Even in cases where many nuclear markers are evolving too slowly to produce a robust topology, checking for congruence with mtDNA-supported
clades can be productive (Rubinoff and Sperling,
2004).
Delineation of taxonomic boundaries with only DNA
barcodes to support them provides very little information about the taxa in question. Unless other sources of
data have been gathered (in which case it is no longer
a cheap, efficient method without a need for experts),
we are left with a spare identification in which we can
have limited confidence and that has limited utility for
understanding biodiversity. Human inference and interpretation still have a place in the largely automated
field of molecular systematics (Sperling, 2003); taxonomy
must have some biological context beyond just a series
of identifications based on topologies with nameless tips
derived from an arbitrary percentage of divergence in
a single gene. Therefore, we do not advocate the sole
use of mtDNA for most studies, but rather comparison
and inclusion of multiple sources of data (e.g., nDNA,
morphology, behavior, cytology, ecology) as the most effective way to understand the evolutionary history of a
group (Bowen et al., 2005; Caterino et al., 2001; Funk
and Omland, 2003; Patton and Smith, 1994; Rubinoff
and Sperling, 2002, 2004; Sperling and Harrison, 1994;
Zakharov et al., 2004).
WHERE D OES mtDNA B ELONG ?
mtDNA is an incontrovertibly important form of genetic inheritance that reflects one component of the evolutionary history of a taxon (e.g., Avise, 2004). However,
small segments of sequence are not universally adequate,
when considered in a vacuum, for the identification of
new species or clades. Mitochondrial DNA has value,
but not exclusivity in taxonomy and phylogenetic studies. Appropriately sampled mtDNA surveys can provide
efficient means of detecting gene flow, identification of
hybrid zones, assessing levels of reproductive isolation,
evaluation of species limits, and provide insight into the
underlying historical patterns of population structure.
Discovery of cryptic species using mtDNA may have critical conservation implications (Avise, 2004; Bowen et al.,
2001; Holland et al., 2004; Rubinoff and Sperling, 2004).
Mitochondrial DNA, by virtue of the number of studies
available and various technical issues, is far more practical than nDNA for phylogeographic surveys (Funk and
Omland, 2003). Arguments that proclaim a “fundamentalist” value of all or none for mtDNA are not productive. Both DNA barcoding and Ballard and Whitlock’s
call to discard mtDNA represent extremes that are not
constructive in efforts to understand the evolution, identity, or relationships among individuals, populations, or
species. The sole use of mtDNA without independent
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POINTS OF VIEW
confirmation from other molecular or morphological
characters can lead to phylogenetic inferences that are
not broadly supported (Funk and Omland, 2003). It is
also evident from the overwhelming majority of studies
that mtDNA makes a significant contribution to phylogenetics, even when it is discordant with nDNA. Discarding mtDNA entirely is no more compelling a proposal
than using it as the exclusive character set for systematics research.
CONCLUSIONS
Elucidating the historical relationships among living organisms is one of the principal goals of systematic biology (e.g., Rokas et al., 2003). Molecular
markers have become instrumental to efforts aimed at
understanding the patterns and processes resulting in
extant global biological diversity. Despite substantial
progress in recent decades, numerous challenges remain with respect to phylogenetic reconstruction, including choice of appropriate character sources, as
well as incongruence encountered between single-gene
data partitions. We propose that the ideal molecular systematic approach would include both nDNA
and organellar DNA such mtDNA markers (or plastid DNA for plants), and that discrepancies between
partitions be used to enrich the interpretation of the
evolutionary history of the taxa under consideration.
This proposal is by no means revolutionary: many researchers follow this paradigm. Yet it is pertinent to
discuss integration in light of the recent literature taking extreme stands on the use or non-use of mtDNA
as a source of phylogenetic characters. The current
push for DNA barcoding has received substantial support (http://www.barcodinglife.org/static/initiative/
bolinitiative.html) and an inflexible response advocating the elimination of mtDNA has also found a
voice (Ballard and Whitlock, 2004). Extreme but simple answers are not a panacea for addressing complex
problems in the field of molecular systematics. By responding to the extreme viewpoints at opposite ends
of the spectrum, we hope to encourage critical consideration of the extreme positions as well as alternatives to these positions. Furthermore, we argue that a
moderate, balanced approach in conjunction with the
use of more inclusive data sets than single-gene and/or
single-character partitions will ultimately lead to an enhanced, more comprehensive understanding of systematic biology and the historical relationships among living
organisms.
ACKNOWLEDGMENTS
We are grateful to the following people for discussion and/or comments on early drafts of this article: M. D. Bird, Stephen Cameron,
Robert Cowie, William Haines, Kenneth Hayes, Roderic Page, Jerry
Powell, Vincent Savolainen, Felix Sperling, Kipling Will, an anonymous
reviewer, and especially Michel Milinkovitch. D.R. was supported by
the College of Tropical Agricultural and Human Resources, University
of Hawaii. B.S.H. was supported by NSF DEB-0316308.
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First submitted 1 January 2005; reviews returned 4 March 2005;
final acceptance 20 April 2005
Associate Editor: Vincent Savolainen
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c Society of Systematic Biologists
Copyright ISSN: 1063-5157 print / 1076-836X online
DOI: 10.1080/10635150500354670
Hastings Ratio of the LOCAL Proposal Used in Bayesian Phylogenetics
M ARK T. HOLDER,1 PAUL O. LEWIS ,2 D AVID L. S WOFFORD ,1 AND B RET LARGET 3,4
1
2
School of Computational Science, Florida State University, Tallahassee, Florida 32306-4120, USA; E-mail: mholder@csit.fsu.edu (M. T. H.)
Department of Ecology and Evolutionary Biology, University of Connecticut, 75 N. Eagleville Road, Unit 3043, Storrs, Connecticut 06269-3043, USA
3
Department of Botany, University of Wisconsin–Madison, 430 Lincoln Drive, Madison, WI 53706-1685, USA
4
Department of Statistics, University of Wisconsin–Madison, 1300 University Avenue, Madison, WI 53706, USA
As part of another study, we estimated the marginal
likelihoods of trees using different proposal algorithms
and discovered repeatable discrepancies that implied
that the published Hastings ratio for a proposal mechanism used in many Bayesian phylogenetic analyses is
incorrect. In this article, we derive the correct Hastings
ratio for the (Larget and Simon, 1999) “LOCAL move
without a molecular clock.” The derivation illustrates
how a recently described method for determining the
acceptance probabilities for proposals in Markov chain
Monte Carlo (Green, 2003) provides an intuitive method
for calculating Hastings ratios. Although the use of the
previously reported Hastings ratio could result in a bias
toward shorter branch lengths, the effect is very minor
and is overwhelmed by the information contained within
even small data sets.
Markov chain Monte Carlo (MCMC) methods are
widely used to explore posterior probability densities by
simulating a walk through tree/model space (Simon and
Larget, 2001; Huelsenbeck and Ronquist, 2001). Many
MCMC simulations employ the Metropolis-Hastings algorithm, which uses a stochastic function to propose a
new state, x , for the chain based upon the current state,
x. The “state of the chain” refers to the values of all of
the parameters in the model (including branch lengths
for the tree). Let q (x, dx ) denote the probability density
of proposing a move from x → x . The Metropolis algorithm (Metropolis et al., 1953) is limited to simulation
schemes in which q (x, dx ) = q (x , dx). Hastings (1970)
significantly eased the task of implementating MCMC
methods by modifying the Metropolis algorithm to allow for the use of asymmetric proposal densities. If one
is sampling the posterior density (which is proportional
to the product of the likelihood, L, and the prior probability density, p), then the probability of accepting a
proposal, α(x, x ), in the Metropolis-Hastings algorithm
is:
L(x ) p(x ) q (x , dx)
α(x, x ) = min 1,
L(x)
p(x) q (x, dx )
(1)
The factor q (x , dx)/q (x, dx ) is referred to as the Hastings
ratio.
S UMMARY OF G REEN’S CONSTRUCTIVE M ETHOD
FOR CALCULATING ACCEPTANCE PROBABILITIES
Green (2003: Section 2.2) generalized the calculation of acceptance ratios to cover both the MetropolisHastings algorithm as well as proposals that implement