Download Candidate gene analysis of metamorphic timing in ambystomatid

Molecular Ecology (2003) 12, 1217–1223
Candidate gene analysis of metamorphic timing in
ambystomatid salamanders
Blackwell Publishing Ltd.
S . R . V O S S ,* K . L . P R U D I C ,† J . C . O L I V E R ‡ and H . B . S H A F F E R §
*Department of Biology, University of Kentucky, Lexington, KY 40506, USA; †Ecology and Evolutionary Biology and ‡Center for Insect
Science, University of Arizona, Tucson, USA; §Section of Evolution and Ecology and Center for Population Biology, University of
California, Davis, USA
Abstract
Although much is known about the ecological significance of metamorphosis and metamorphic timing, few studies have examined the underlying genetic architecture of these
traits, and no study has attempted to associate phenotypic variation to molecular variation
in specific genes. Here we report on a candidate gene approach (CGA) to test specific loci
for a statistical contribution to variation in metamorphic timing. Three segregating populations (SP1, SP2 and SP3) were constructed utilizing three species of paedomorphic
Mexican ambystomatid salamander, including the axolotl, Ambystoma mexicanum. We
used these replicated species to test the hypothesis that inheritance of alternate genotypes
at two thyroid hormone receptor loci (TRα , TRβ ) affects metamorphic timing in ambystomatid salamanders. A significant TRα*SP effect indicated that variation in metamorphic
timing may be influenced by TRα genotype, however, the effect was not a simple one,
as both the magnitude and direction of the phenotypic effect depended upon the genetic
background. These are the first data to implicate a specific gene in contributing to variation
in metamorphic timing. In general, candidate gene approaches can be extended to any
number of loci and to any organism where simple genetic crosses can be performed to
create segregating populations. The approach is thus of particular value in ecological
studies where target genes have been identified but the study organism is not one of the
few well-characterized model systems that dominate genetic research.
Keywords: Ambystoma, axolotl, evolutionary genetics, life cycle evolution, metamorphosis
Received 10 September 2002; revision received 6 January 2003; accepted 6 January 2003
Introduction
Many organisms experience life in two distinct habitats as
a result of undergoing a metamorphosis during ontogeny.
A particularly conspicuous example of metamorphosis
concerns the transition from an aquatic larval phase to a
more terrestrial adult phase, which has been intensively
studied for many insect and amphibian species (Wilbur
1980; Butler 1984; Tauber et al. 1986; Werner 1986; Danks
1991). Several decades of ecological research suggests that
metamorphic timing is a critical life history event because
aquatic and terrestrial habitats are temporarily and spatially
variable with respect to ecological factors that may affect
an individual’s probability of survival and reproduction
Correspondence: S. R. Voss. Tel.: +1 859 257 9888; Fax:
+1 859 257 1717; E-mail: [email protected]
© 2003 Blackwell Publishing Ltd
(e.g. Wilbur & Collins 1973; Berven & Gill 1983). As such,
natural selection for metamorphic timing may be an important process underlying the evolutionary diversification of
biphasic life cycles, both within (Wilbur & Collins 1973;
Harris 1987) and between (Shaffer & Voss 1996) species.
Variation in metamorphic timing is conspicuous among
amphibians at all levels of biological organization. At an
interspecific level, the great diversity of amphibian life cycles
suggests an amazing evolutionary potential for changes in
the relative duration of the larval phase vs. the adult phase:
amphibian species have larval periods that are played-out
over weeks (e.g. Leips & Travis 1994), months (e.g. Beachy
1995) and years (e.g. Castanet et al. 1996). Interestingly, in
some clades (but not others), intraspecific variation in
metamorphic timing is often of the same magnitude as that
observed between species. In fact, individuals of the same
cohort may differ in age at metamorphosis by weeks,
1218 S . R . V O S S E T A L .
months and even years (Voss 1993a). In the extreme, this
incredible range of variation in metamorphic timing is
bounded by the elimination of the ancestral biphasic condition and the evolution of direct development with no
aquatic larval period (e.g. Wake & Hanken 1996) or the
evolution of obligate paedomorphosis with no terrestrial
adult phase (e.g. Shaffer & Voss 1996).
Although interspecific and intraspecific surveys indicate
an amazing potential for temporal modifications of the
amphibian larval vs. the adult phase, few studies have
attempted to determine if this potential is reflected in the
underlying genetic architectures of natural species. Classical quantitative approaches have been applied to estimate
genetic variance components for metamorphic timing, or
genetic covariances and correlations among larval morphological traits that may be associated with metamorphic
timing (Berven 1982, 1987; Berven & Gill 1983; Travis et al.
1987; Newman 1988, 1994; Harris et al. 1990; Blouin 1992).
Results from these studies suggest a range of genetic architectures, including high and low estimates of heritability
for metamorphic timing (e.g. 0.87 for Scaphiopus holbrooki,
Newman 1988; 0.01 for Rana sylvatica, Berven 1982).
Although informative for understanding short-term evolutionary responses, such approaches do not associate
phenotypic variation with the inheritance of specific genes,
and therefore cannot provide mechanistic information concerning the relationship between genotype and phenotype.
Knowledge of these genetic details is essential for understanding the relationships among development, physiology and genetic architecture (Cheverud & Routman 1995),
and ultimately for identifying the genes underlying ecologically and evolutionarily important traits.
The identification of genes underlying natural trait variation (i.e. not generated by mutagenesis in the laboratory)
is not a trivial matter, even for model organisms with long
research histories and extensive resources available for
molecular genetic analysis. Quantitative trait locus (QTL)
mapping is one relatively simple approach for identifying
chromosomal regions that contribute statistically to trait
variation, although only a few recent studies have begun to
associate QTL with specific, protein-coding loci (Doebley
et al. 1997; Frary et al. 2000; Gahan et al. 2001). To go from
a QTL to a protein-coding locus may require an extensive
map-based cloning effort, in which the QTL region is completely sequenced or screened for all possible candidates.
Even with such an effort, there is no guarantee that the
locus or loci that are the target of selection will be identified, as linkage to genes outside the sequenced region may
contribute to the statistical correlation on which QTLs are
based (Zeng 1993). Given the effort required to accomplish
map-based cloning, we have begun to evaluate a complementary approach that we call candidate gene analysis
(CGA). Unlike QTL analysis, with CGA one starts with
one or more candidate loci and tests each directly for a
statistical contribution to the trait variation of interest.
CGA assumes that our increasing knowledge of development and molecular mechanism can greatly reduce the size
of the genomic haystack being screened for important
genes, and that the strategy will only increase in power
as our knowledge of how genes produce phenotypes
increases in the future. CGA is not a new approach to
evolutionary ecology; it was used more than a decade ago
to test allozymes for a genetic contribution to physiological performance (reviewed in Mitton 1997). However,
much has happened in the last 10 years and CGA is no
longer constrained by polymorphism detection methods
to test relatively few candidate loci. Rather, as genomes
and phenotypes become better understood, the list of
potential candidates has grown to the point at which
CGA is a viable strategy. It is also important to note that
QTL and candidate gene analysis can be complementary
approaches, as shown recently by Gahan et al. (2001) in the
search for a Bt resistance allele in the tobacco budworm,
Heliothis virescens.
Here we report on a candidate gene approach to associate phenotypic variation in the timing of metamorphosis
with the inheritance of specific genes. The approach
requires that we accomplish two objectives: (i) identify
candidate loci that contribute genetically to variation in
metamorphic timing, and (ii) test candidate loci in natural
populations. Although our study focuses on metamorphic
timing in ambystomatid species, in theory the approach
can be extended to any trait/species for which there is segregating phenotypic and DNA variation. Here we describe
our experimental system and preliminary results that are
relevant to accomplishing the first objective. Specifically,
we describe the segregation of phenotypic variation for
metamorphic timing among offspring from interspecific
crosses in the laboratory. Urodeles are somewhat unusual
among vertebrates in the degree to which segregating
populations can be made by crossing distinct species, some
of which are distantly related phylogenetically (Voss &
Shaffer 1996). To date, we have primarily used offspring
deriving from crosses between two members of the tiger
salamander complex (Shaffer & McKnight 1996), the
paedomorph (that is, nonmetamorphic) A. mexicanum and
the metamorphic A. t. tigrinum, for genetic analyses of
metamorphic completion or failure (Voss & Shaffer 1997,
2000; Voss et al. 2000; Smith 2002). In backcrosses between these species (e.g. A. mexicanum/A. t. tigrinum F1 ×
A. mexicanum) both metamorphs and nonmetamorphs are
produced, although the great majority of individuals from
crosses using wild-caught A. mexicanum undergo metamorphosis. Here we summarize similar crossing data for
three paedomorphic species and show significant intercross variation in the timing of metamorphosis when
different nonmetamorphic species are crossed into the
same genetic background. Assuming that paedomorphosis
© 2003 Blackwell Publishing Ltd, Molecular Ecology, 12, 1217–1223
G E N E T I C S O F M E T A M O R P H I C T I M I N G 1219
represents an evolutionary modification of the genes that
control continuous variation in metamorphic timing, these
data suggest that our three study species exploit multiple
genetic architectures for their independent evolutions of
paedomorphosis. We then ask if variation in the timing of
metamorphosis is accounted for by the inheritance of two
candidate genes: thyroid hormone receptor alpha (TRα)
and thyroid hormone receptor beta (TRβ ). Thyroid hormone
receptors are strong candidate genes for metamorphic
timing because they mediate gene expression pathways
that regulate developmental programmes underlying the
transformation of an aquatic larva into a terrestrial adult
(Shi et al. 1996; Voss et al. 2000).
Materials and methods
Segregating populations were created by artificially
crossing obligate, paedomorphic salamanders (Ambystoma
mexicanum, A. dumerilii and A. andersoni) with obligate,
metamorphosing salamanders (A. tigrinum tigrinum; but
see Whiteman et al. 1998). These three paedomorphic
species are all members of a recently derived clade which
we refer to as the tiger salamander (A. tigrinum) complex
(Shaffer & McKnight 1996). Although all derived within
the last several million years, our three target species are
not each other’s closest relatives (Shaffer & McKnight 1996)
and each has evolved paedomorphosis independently
(Shaffer 1993; Shaffer & Voss 1996). Three to five F1 hybrids
from each cross type were backcrossed to their respective nonmetamorphic parental species to produce three
segregating populations (SP1–3), following the crossing
method of Voss (1995). A total of 93 hatchlings from the
A. mexicanum backcross (SP1), 54 hatchlings from the A.
dumerilii backcross (SP2) and 146 individuals from the
A. andersoni backcross (SP3) were reared according to the
methods of Voss (1995), except that individuals were fed
brine shrimp (small larvae) and black worms (larger
larvae) to satiation, the light cycle corresponded to the
natural light cycle of Davis, CA and environmental temperature varied between 18 and 22 °C. The majority of individuals were reared until the completion of metamorphosis
and then sacrificed; liver tissue was cryo-preserved. Three
individuals from each SP died before metamorphosis or
the termination of the experiment. A few individuals were
kept for future experiments; a small piece of tail tissue
was cryo-preserved from these. Seventeen offspring from
SP1, 11 from SP2, and 4 from SP3 did not undergo metamorphosis during the experiment (300 days after hatching).
These individuals were considered to be paedomorphs,
as observed for a proportion of individuals from other
interspecific backcrosses (Voss 1995; Voss & Shaffer 1996;
Smith 2002). These paedomorphic individuals were not
included in the calculation of metamorphic timing or in the
statistical analyses reported below.
© 2003 Blackwell Publishing Ltd, Molecular Ecology, 12, 1217–1223
DNA was isolated from backcross offspring according
to the method of Voss (1993b), and genotypes were
determined for TRα and TRβ. DNA fragments corresponding to TR genes were amplified by polymerase chain
reaction (PCR) using the following primers: Trα forward, 5′-TCCTGACAGTGAGACGCTG-3′; Trα reverse,
5 ′-TAGGGCCACTTCGGTGTCATC-3′; TR β forward,
5′-CCCGGAAAGCAAAACCTT-3′; TRβ reverse, 5′-TATCATCCAGGTTAAATGAC-3′. The TRα and TRβ primers
flank 150 and 136 bp sequences, respectively, of the ligand
binding domains, and were designed from cloned sequences
from both A. mexicanum and A. tigrinum (Safi et al. 1997).
PCR conditions for both TR sequences were 200 ng DNA,
0.25 mm each primer, 1 mm MgCl2, 0.1 U Taq DNA polymerase, 200 µm each of dATP, dTTP, dCTP, dGTP and 1×
PCR buffer (10 mm Tris–HCl, pH 8.3, 50 mm KCl) at a total
reaction volume of 25 µL. The PCR cycling parameters
were: 4 min initial melt at 94 °C; 30 cycles of 1 min at 94 °C,
1.5 min at 60 °C (TRα) or 1.5 min at 57 °C (TRβ); 1 cycle for
5 min at 72 °C. TRa alleles were scored as single-stranded
confirmational polymorphisms (SSCPs; Orita et al. 1989).
Approximately 8 µL from each TRa PCR amplification
was mixed with 2.5 µL of formamide loading buffer (98%
formamide, 1 m NaOH, bromophenol blue, cyanol green)
and denatured for 4 min at 94 °C. Denatured samples were
immediately placed on ice and then loaded into 16 × 20 cm,
6% polyacrylamide gels (Hiss et al. 1994; Voss et al. 2000).
Electrophoresis was at 350 V for 2.5 h at 17 °C using 0.6×
TBE buffer. Gels were then stained with ethidium bromide
and visualized under UV light. TRβ alelles were scored as
restriction fragment length polymorphisms (RFLPs). The
restriction enzyme XhoI recognizes a single cut site in the
TRβ allele of the P1 A tigrinum, that is absent in A. mexicanum,
A. dumerilii and A. andersoni. Approximately 7 µL of each
TRβ PCR amplification was mixed with 1 µL of 10× enzyme
reaction buffer and 2.5 U XhoI. After an overnight incubation at 37 °C, restriction digests were loaded into 15% polyacrylamide gels (16 × 20 cm). Electrophoresis was at 150 V
for 5 h at room temperature using 1× TBE buffer, and gels
were stained with ethidium bromide and visualized under
UV light.
Two genotypes are expected to segregate equally for
each TR locus in a backcross design: a heterozygous and a
homozygous genotype. We used χ2 tests to test for equal
segregation of each TR genotype within SPs (Sokal & Rohlf
1987). We also used a full factorial anova to examine the
effects of SP (fixed effect with three levels corresponding
to cross type), TRα genotype (fixed effect with two levels
corresponding to heterozygotes and homozygotes) and
TRβ genotype (also a fixed, two-level effect) on the number
of days to completion of metamorphosis. The anova
assumption of equal variances was tested using Fmax tests
(Sokal & Rohlf 1987). Student’s t-test was used subsequently for pair-wise contrasts of specific group means.
1220 S . R . V O S S E T A L .
SP1
SP2
Table 1 Sample size, mean, and standard
deviation of age at metamorphosis (days)
for individuals from segregating populations (SP) 1–3
SP3
Genotype
N
Mean
SD
N
Mean
SD
N
Mean
SD
TRα Heterozygote
TRα Homozygote
TRβ Heterozygote
TRβ Homozygote
Family totals
39
30
43
26
69
206.49
199.94
199.49
210.50
203.64
22.04
22.19
21.64
21.76
22.18
11
27
15
23
38
136.55
156.15
153.69
150.78
150.97
30.13
45.02
42.91
42.87
42.93
40
60
47
52
100
217.05
200.85
212.70
202.44
207.33
38.00
26.78
31.05
33.72
32.56
The assumption of independence of TR loci (i.e. independent assortment) has been confirmed by genetic linkage
mapping (Voss et al. 2001; unpublished data). Four offspring of SP1 and two offspring from SP2 were not
included in the statistical analyses because no genotypic
data were collected; we genotyped a random sample of 100
individuals of SP3. All statistical analyses were performed
using jmp Version 3 (SAS Institute) and significance was
evaluated at α = 0.05.
Table 2 Three-way anova of age at metamorphosis given TRα
genotype, TRβ genotype, and segregating population (SP)
Source
d.f.
Sum of
squares
F ratio
Prob > F
Results
TRα
TRβ
SP
TRα *TRβ
TRα *SP
TRβ *SP
TRα *TRβ *SP
1
1
1
1
1
1
1
1.833
214.613
93002.015
47.134
7753.436
4021.312
835.583
0.002
0.223
71.417
0.049
4.026
2.088
0.434
0.965
0.637
< 0.0001
0.587
0.019
0.127
0.649
A variable number of heterozygous and homozygous
genotypes were observed for each TR locus (Table 1).
The genotypic proportions for TRα in SP1 (Ambystoma
mexicanum) and TRβ in SP2 (A. dumeriili) and SP3 (A.
andersoni) were consistent with a hypothesis of equal
segregation (TRα SP1: χ2 = 1.17, d.f. = 1, P > 0.05; TRβ SP2:
χ2 = 1.00, d.f. = 1, P > 0.05; TRβ SP3: χ2 = 0.16, d.f. = 1,
P > 0.05). However, the proportions of genotypes for TRβ
in SP1 and TRα genotypes in SP2 and SP3 were not (TRβ
SP1: χ2 = 4.19, d.f. = 1, P < 0.05; TRα SP2: χ2 = 6.94, d.f. = 1,
P < 0.05; TRα SP3: χ2 = 6.94, d.f. = 1, P < 0.05). The unequal
segregation of genotypes for TRβ in SP1 and TRα in SP2
and SP3 could not be attributed to a viability effect during larval development, as only three individuals died
from each SP during the experiment. There was equal
representation of both TR genotypes among paedomorphic individuals that were not included in the analysis
(SP1 TRβ nine heterozygous vs. eight homozygous paedomorphs; SP2 TRα: five heterozygous vs. six homozygous
paedomorphs; SP3 TRα: two heterozygous vs. two homozygous paedomorphs). Thus, the unequal segregation for
TRβ in SP1 and TRα in SP2 and SP3 must reflect a
prehatchling effect that led to the unequal representation
of genotypes at metamorphosis.
The anova assumption of equal variance was met for
all 12 genotypic groups in Table 1 (Fmax = 2.07, a = 12,
d.f. = 43, P > 0.05), as well as for all subsequent contrasts of
pair-wise genotypic group means (e.g. Fmax = 2.23, a = 2,
d.f. = 25, P > 0.05 for the contrast between Trα heterozygotes and Trα homozygotes within SP2). The anova indi-
cated a significant interaction (SP*TRα) and main (SP)
effect on metamorphic timing. The significant SP main
effect is explained by a dramatic difference in mean time
to metamorphosis, with SP2 individuals metamorphosing ≈ 50 days earlier than those from SP1 and SP3 (SP1 vs.
SP2: t = 8.44, d.f. = 1, P = 7e−15; SP1 vs. SP3: t = 0.926, d.f. = 1,
P = 0.356; SP2 vs. SP3: t = 6.66, d.f. = 1, P = 4e−18; Tables 1
and 2). The significant SP*TRα interaction was examined
further by contrasting heterozygous vs. homozygous
genotypic means within each SP. The greatest difference
between genotypic classes was observed in SP2, where the
average time to metamorphosis was ≈ 20 days earlier for
the TRα heterozygous class. This difference was only
marginally statistically significant (t = 1.87, d.f. = 1, P >
t = 0.062) but sample sizes for genotypic classes within SP2
are somewhat limited. Average time to metamorphosis
was not significantly different between genotypic classes
in SP1 (t = 0.886, d.f. = 1, P > t = 0.377). However timing
of metamorphosis was significantly different among TRα
genotypic classes in SP3 (t = 2.491, d.f. = 1, P > t = 0.014).
Thus, on average, heterozygous individuals metamorphosed ≈ 20 days before the TRα homozygous genotypic
class in SP2, but ≈ 17 days after the homozygous genotypic
class in SP3. This result suggests that variation in metamorphic timing may be influenced by TRα genotype, or
possibly by other genes closely linked to it, with the magnitude and direction of the phenotypic effect depending upon
genetic background.
© 2003 Blackwell Publishing Ltd, Molecular Ecology, 12, 1217–1223
G E N E T I C S O F M E T A M O R P H I C T I M I N G 1221
Discussion
We used an interspecific crossing design to generate
individuals that segregated for both timing of metamorphosis and molecular variation in two candidate
genes that may be involved in metamorphic timing. In
our approach, SPs were created by crossing individuals
of three obligate nonmetamorphic species (Ambystoma
mexicanum, A. dumerilii and A. andersoni) with individuals
derived from the same population of an obligate metamorphic species (A. t. tigrinum), and then backcrossing F1
hybrids to their respective paedomorphic species. Most
backcross individuals completed metamorphosis, lending
further support to the interpretation that a single locus
recessive model cannot account for the genetic basis of
paedomorphosis in the A. tigrinum clade (e.g. Voss &
Shaffer 2000; Smith 2002). Among those individuals that
completed metamorphosis, timing of metamorphosis was
significantly different among species, with individuals
from A. dumerilii (SP2) metamorphosing ≈ 50 days earlier,
on average, than those from A. mexicanum (SP1) and A.
andersoni (SP3). Because the SPs were created by crossing
different nonmetamorphic species into the same genetic
background, differences in the timing of metamorphosis
likely reflect genetic differences among these species. Presumably, genes from nonmetamorphic species differentially alter physiological pathways that regulate the timing
of metamorphosis. Although it will be necessary to test
the assumption of homogeneity of genetic background
of A. t. tigrinum individuals that are drawn from the same
population (as well as genetic homogeneity for paedomorphs), these data show that considerable phenotypic
variation can be generated for genetic linkage studies by
crossing ambystomatid salamander species that vary in
metamorphic response. They also suggest that phylogenetic
affinity may play a role in the similarity or differences
in genetic architecture, as the two most closely related
paedomophic taxa (A. mexicanum, SP1 and A. andersoni,
SP3; Shaffer and McKnight, 1996) are virtually identical in
their mean time to metamorphosis compared with the
more distantly related A. dumerilii (Table 1).
Although the ecological and evolutionary genetics of
amphibian metamorphosis has long been identified as
a key issue in the evolution of biphasic life histories (e.g.
Berven & Gill 1983), this is the first study to test specific
metamorphic factors for a genetic contribution to variation
in timing of amphibian metamorphosis. Our results indicated
a significant TRα effect on the timing of metamorphosis;
in SP2, the mean time to metamorphosis was earlier for
individuals that inherited a heterozygous TRα genotype (Fig. 1). An earlier mean time to metamorphosis
for heterozygotes is consistent with an additive model of
gene effect, in whcih inheritance of a relatively greater
number of alleles (at one or more loci) from the meta© 2003 Blackwell Publishing Ltd, Molecular Ecology, 12, 1217–1223
Fig. 1 Genetic effects for TRα and TRβ heterozygotes within each
segregating population (SP). Genetic effects are estimated as one
half the difference between heterozygous and homozygous
genotypic means. Light bars, TRα; dark bars, TRβ. Error bars are
1 standard error for the estimated genetic effect.
morphic species is expected to decrease time to metamorphosis. However, in SP3, the mean time to metamorphosis
was greater for heterozygous individuals that inherited a
metamorphic TRα allele (Fig. 1). It is currently not known
if the same TRα allele can have opposite effects on physiology and development when placed in different genetic
backgrounds, however, is seems possible given that nuclear
transcription factors (such as TRα) have bimodal transcriptional properties; that is, depending upon conditions, nuclear
transcription factors may repress or activate target genes
(Collingwood et al. 1999). Indeed, variable penetrance
for the same TRβ point-mutations in human generalized
resistance to thyroid hormone (GRTH) presumably reflects differences in genetic background (Weiss et al. 1993).
Another possibility is that orthologous TRs are functionally different among paedomorphic species because different mutations were fixed during each species’ independent
evolutionary history leading to paedomorphosis. Of course,
until we complete more work (e.g. obtain full-length TR
sequences, screen for nonconservative amino acid replacements and test additional linked candidate loci), it is not
possible to rule out other models of gene action and candidate loci.
Although our results suggest that TRα genotype is associated with variation in the timing of metamorphosis, it is
important to note that metamorphic timing was not significantly different between genotypic classes in SP1 and
no significant TRβ effect was identified for any SP. Thus,
there is no simple relationship between the inheritance
of TR alleles and timing of metamorphosis. Furthermore, our interpretation of a significant TRα effect maybe
complicated by the observation of non-Mendelian genotypic ratios at this locus. Non-Mendelian genotypic ratios
are often observed in interspecific and hybrid species
crosses because synthetic lethals are created when certain
combinations of deleterious alleles are brought together
1222 S . R . V O S S E T A L .
(Thompson 1986). Further replication is needed to evaluate
the potentially confounding effect of synthetic lethals, as well
as to understand what is driving deviations from Mendelian expectations. However, because non-Mendelian genotypic ratios were not specific to SP, TR or genotypic class,
underlying deleterious effects were apparently random
with respect to the effects tested. This suggests that the
association between TRα and timing of metamorphosis
is real and not a statistical artefact arising from differential
representation of TRα genotypes. Thus, our study implicates
TRα as contributing to variation in timing of amphibian
metamorphosis.
The extension of candidate gene analysis to additional species (including replicate families within SPs)
and loci is necessary because mechanisms of metamorphic timing will almost certainly vary both within
and between species. This is suggested by (i) the significantly earlier time of metamorphosis for individuals
from SP2, (ii) recent studies which indicate that the genetic
basis of metamorphic failure is different between laboratory A. mexicanum at Indiana University and the natural
population of the same species in Lake Xochimilco, Mexico
(Voss & Shaffer 2000; Smith 2002), and (iii) unpublished
data showing different physiological responses to TH
among this same set of species (Voss, unpublished data).
Given the close phylogenetic relationships of these taxa
(Shaffer & McKnight 1996; Shaffer, unpublished data) and
the evolutionary lability of paedomorphosis within the
group (Shaffer 1993) the growing body of evidence suggesting that each lineage utilizes different genetic systems
to vary both timing and completion of metamorphosis
is striking, and suggests that multiple pathways may
allow for rapid evolutionary changes in this key ecological
variable.
In general, studies of amphibians indicate genetic variation for metamorphic timing within natural populations,
and this may reflect the contribution of multiple underlying mechanisms (e.g. Harris et al. 1990). There is a clear
need for experimental systems and approaches that
can test for multiple mechanisms while controlling for
genetic background, particularly in the nonmodel systems that have been studied in the field. Candidate gene
analysis can meet this challenge because the overall
approach can be extended to any number of loci, and
to taxa for which virtually no genetic resources are
available.
Acknowledgements
We thank Virginia Graue, Santi Graue and Hugh Drummond for
support in Mexico. We also acknowledge the support of S Borland
and G Malacinski at the Indiana Axolotl Colony. This material is
based upon work supported by NSF IBN-9509802, IBN-0080112,
and the UC Davis agricultural experiment station.
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The authors share a common interest in the evolution and ecology
of ambystomatid salamanders. Current studies range from conservation, systematics, hybridization, ecological and evolutionary
physiology, evolutionary genetics, developmental evolution and
genomics.