Increased differentiation and reduced gene ﬂow in sex
chromosomes relative to autosomes between lineages
of the brown creeper Certhia americana
Joseph D. Manthey and Garth M. Spellman
J. D. Manthey (email@example.com), Biodiversity Inst. and Dept of Ecology and Evolutionary Biology, Univ. of Kansas, Lawrence,
KS 66045, USA. – JDM and G. M. Spellman, Center for the Conservation of Biological Resources, Dept of Biology, Black Hills State Univ.,
Spearﬁsh, SD 57799, USA.
e properties of sex chromosomes, including patterns of inheritance, reduced levels of recombination, and hemizygosity
in one of the sexes may result in the faster ﬁxation of new mutations via drift and natural selection. Due to these patterns
and processes, the two rules of speciation to describe the genetics of postzygotic isolation, Haldane’s rule and the
large-X eﬀect, both explicitly include quicker evolution on sex chromosomes relative to autosomes. Because sex-linked
mutations may be the ﬁrst to become ﬁxed in the speciation process, and appear to be due to stronger genetic drift (in
birds), we may identify pronounced genetic diﬀerentiation in sex chromosomes in taxa experiencing recent speciation
and diverging mainly via genetic drift. Here, we use nine sex-linked and 21 autosomal genetic markers to investigate
diﬀerential divergence and introgression between marker types in Certhia americana. We identiﬁed increased levels
of genetic diﬀerentiation and reduced levels of gene ﬂow on sex chromosomes relative to autosomes. is pattern is
similar to those observed in other recently-divergent avian species, providing another case study of the earlier role of sex
chromosomes in divergence, relative to autosomes. Additionally, we identify three markers that may be under selection
between Certhia americana lineages.
Birds, snakes, butterﬂies, and some ﬁshes and lizards exhibit
female heterogamety and Z–W sex determination. Certain
properties of sex chromosomes, including patterns of inheri-
tance, reduced levels of recombination, and hemizygosity in
one of the sexes (Vicoso and Charlesworth 2006) can result
in the faster ﬁxation of new mutations via drift and natural
selection. ese properties have led to the explicit inclusion
of sex chromosomes in the two rules of speciation used to
characterize the genetics of postzygotic isolation: Haldane’s
rule and the large-X eﬀect (Coyne and Orr 1989).
Haldane’s rule states that hybrid incompatibility is more
pronounced in the heterogametic sex due to expression of
hemizygous (Z-linked) alleles, whether recessive or domi-
nant (Haldane 1922). ree main hypotheses have been pro-
posed to explain Haldane’s rule, including the faster-male
hypothesis, dominance, and the fast-Z. e faster-male
hypothesis suggests evolution on sex chromosomes is quick-
ened due to sexual selection on males, which would reduce
the eﬀective population size of Z-chromosomes (NEZ) rela-
tive to the eﬀective population size of autosomes (NEA),
thereby increasing the eﬀects of genetic drift (Wu and Davis
1993); the faster-male hypothesis could be exacerbated fur-
ther by skew in operational sex ratio, leading to larger vari-
ance in diﬀerences between NEZ and NEA. e dominance
hypothesis of Haldane’s rule states that mutations involved
in reduced hybrid ﬁtness are on average recessive; therefore
the negative eﬀects of these mutations is more pronounced if
they are located on sex chromosomes, where they would be
expressed in the heterogametic sex (Turelli and Orr 1995).
Finally, the fast-Z eﬀect suggests that sex chromosomes may
exhibit faster rates of adaptive change compared to auto-
somes (Charlesworth et al. 1987), although these eﬀects
may be caused in part by the faster-male or dominance
hypotheses, as well as vary in eﬀect between species due to
diﬀerences in eﬀective population size (Mank et al. 2010a).
e second rule of speciation is the large-X, or in the case of
birds, the large-Z eﬀect, which states that mutations on the
Z chromosome have a relatively large eﬀect on hybrid ﬁtness
compared to similar mutations on autosomes (Charlesworth
et al. 1987, Coyne and Orr 1989).
Because the two rules of speciation explicitly tie sex
chromosomes to speciation, the Z chromosome often may
be responsible for the development of pre- (e.g. cellular
incompatibilities) or postzygotic (e.g. male plumage char-
acteristics; Mank et al. 2010b) reproductive isolation in
recently diverged species. Several recent studies of contact
zones between bird species (Sæther et al. 2007, Carling and
Brumﬁeld 2009, Storchova et al. 2010, Backström and
Väli 2011, Elgvin et al. 2011) have shown reduced levels
of introgression between species in Z-linked markers
Journal of Avian Biology 44: 001–008, 2013
© 2013 e Authors. Journal of Avian Biology © 2013 Nordic Society Oikos
Subject Editor: Staﬀan Bensch. Accepted 3 September 2013
compared to autosomal markers, supporting the strong role
of sex-linked mutations in speciation. Additionally, a study
by Mank et al. (2010b) investigated the fast-Z eﬀect using
the genome drafts of Taeniopygia guttata and Gallus gallus.
ey found a lack of positive selection, and hypothesized
that the fast-Z may be predominantly due to increased
eﬀects of genetic drift, potentially from sexual selection in
males reducing NEZ (i.e. partially from the faster-male
Because sex-linked mutations may be the ﬁrst to become
ﬁxed in the evolution of reproductive isolation, and appear
to be due to increased eﬃcacy of genetic drift in birds (Mank
et al. 2010b), Z-linked markers may be relatively strongly
diﬀerentiated in taxa exhibiting recent speciation and diverg-
ing mainly under genetic drift. e brown creeper Certhia
americana, a widespread North American avian taxon, is cur-
rently considered a single species (AOU 1983); however,
recent phylogeographic studies (Manthey et al. 2011a, b)
suggest C. americana is two species. Mitochondrial and
nuclear DNA identiﬁed a basal split between northern and
southern populations at approximately 32°N latitude. is
split occurred recently (~ 1.50 million yr ago), with diver-
gence between populations caused by isolation (genetic drift)
and lack of gene ﬂow (Manthey et al. 2011a, b).
Here, using nine sex-linked and 21 autosomal markers,
we measure divergence and ﬁxation between Certhia lin-
eages and determine if genetic markers are evolving under
neutral processes or via selection. Although we cannot test
speciﬁc processes described above relating to ﬁtness and
hybrid incompatibilities, we aim to examine the relative
eﬀects of sex chromosomes on diﬀerentiation between
Certhia lineages. Using these data, we examine the follow-
ing hypotheses: (H01) Diﬀerentiation between lineages will
be greater in sex-linked markers than autosomal markers;
(H02) Sex-linked markers will exhibit relatively less gene
ﬂow between lineages.
Sampling and laboratory procedures
Tissue samples of 16 brown creeper individuals were obtained
from two populations, representing the basal lineages identi-
ﬁed in phylogeographic studies (Manthey et al. 2011a, b).
ese samples were from LaPlata County, CO, USA (n 8)
and the state of Jalisco in Mexico (n 8). One sample of the
Eurasian treecreeper Certhia familiaris was used as an out-
group taxon. We attempted to minimize any eﬀects of sam-
ple size on estimates of polymorphism and divergence by
sampling mainly males (only one female included in this
study). Because one female was included, all analyses
included 31 alleles for Z-linked markers and 32 alleles for
Total genomic DNA was previously extracted for earlier
studies. e sequences of 21 autosomal loci were obtained
from Manthey et al. (2011b), which included anonymous
loci (developed in that study) and introns (developed by
Backström et al. 2008). An additional nine Z-linked introns
were obtained using polymerase chain reaction (PCR) ampli-
ﬁcation with previously designed primers (Backström et al.
2006, 2010, Kimball et al. 2009). PCR ampliﬁcation of all
sequences was carried out in 15 ml reactions and included an
initial denaturation period of 10 min at 95°C, with 40
subsequent cycles of 95°C for 30 s, TA for 45 s, and 72°C for
1 min; annealing temperature varied with loci and samples
from 55–61°C. PCR products were puriﬁed and sequenced
using 10 ml ABI BigDye sequencing reactions. Sequencing
reactions were puriﬁed using a standard ethanol precipita-
tion clean-up followed by sequencing on an ABI 3130
Phased and trimmed haplotype sequences were taken
directly from Manthey et al. (2011b) for the autosomal
sequences, which were previously checked (and trimmed if
necessary) for recombination. Newly sequenced loci were
processed using the following methodology. Sequences were
automatically aligned and manually checked and edited
using Sequencher 4.8 (GeneCodes). On introns, any partial
exon sequence was removed prior to analyses. Haplotypes
were inferred using PHASE (Stephens et al. 2001, Stephens
and Donelly 2003), with an output threshold of 0.7, as
implemented in DnaSP (Librado and Rozas 2009). Using
RDP3, and seven inclusive tests in the program (Smith 1992,
Padidam et al. 1999, Gibbs et al. 2000, Martin and Rybicki
2000, Posada and Crandall 2001, Martin et al. 2005, Heath
et al. 2006, Boni et al. 2007), we checked for recombination.
Using these tests, recombination was not detected in any of
the Z-linked loci.
Levels of variation, neutrality and selection
Measures of genetic diversity (polymorphic sites and nucle-
otide diversity (p)) and neutrality statistics (Tajima’s D;
(Tajima 1989) and Fu and Li’s D* (Fu and Li 1993)) were
estimated using DnaSP ver. 5 (Librado and Rozas 2009).
Signiﬁcance of neutrality indices was inferred via 1000
bootstrap replicates implemented directly in DnaSP. Taji-
ma’s D uses the number of segregating sites and nucleotide
diversity in a genetic marker to identify an excess or lack of
polymorphisms, signifying population size changes or
selection. Similarly, Fu and Li’s D* investigates polymor-
phism frequencies, although focusing on singletons, to
identify purifying selection or recent selective sweeps.
To identify loci under selection, we used two tests: 1)
the Hudson–Kreitman–Aguade (HKA) test (Hudson et al.
1987, implemented online at: http://genfaculty.rutgers.
edu/hey/software#HKA ), and 2) a Bayesian method,
implemented in BAYESFST (Beaumont and Balding
2004). HKA compares ratios of polymorphisms to diver-
gence levels to identify signals (or lack thereof) of selection
in an entire dataset. We compared the two lineages of
C. americana, performing the test using 10 000 coalescent
simulations for three datasets: 1) all loci together,
2) Z-linked loci, and 3) autosomal loci. BAYESFST identi-
ﬁes individual loci that exhibit a signal of selection by
implementing an MCMC to estimate locus, population,
and population-by-locus interaction eﬀects. Using default
settings, we ran ﬁve iterations of BAYESFST to ensure
replicative results, again with three datasets (as with
the HKA test). We applied a 5% signiﬁcance level to the
tests, which corresponds to an approximate transformed
p-value of 2.94; low outliers suggest loci evolving under
balancing selection while high outliers suggest loci evolving
under diversifying selection.
Investigation of population structure and gene ﬂow
We investigated population structure and genetic-structure
variation between autosomal and sex-linked markers using
several methods: 1) private, shared and ﬁxed polymor-
phisms, 2) summary statistics, including the ﬁxation index
(FST; Hudson et al. 1992) and relative node depth (RND;
Feder et al. 2005), and 3) a measure of genetic diﬀerentia-
tion and population sorting that uses phylogenies, the gene-
alogical sorting index (GSI; Cummings et al. 2008). e
RND is measured as the average pairwise divergence (Dxy;
Nei 1987) between lineages divided by Dxy between all
C. americana samples and the outgroup (C. familiaris).
e RND was used to identify ‘fast’ evolution between
C. americana lineages relative to the outgroup. e GSI is a
normalized statistic that quantiﬁes exclusive ancestry of
populations in gene trees. Input for calculating the
GSI are gene trees for each locus. erefore, TOPALi ver.
2.5 (Milne et al. 2009), using a PhyML analysis (Guindon
and Gascuel 2003), was used to construct maximum likeli-
hood phylogenies for each locus. GSI values range from 0
(complete mixing of populations in the gene tree) to 1
(monophyly) with signiﬁcance assessed by comparing
observed values to values obtained from 10 000 permuta-
tions of the individuals assigned to each gene trees’ tips.
Because the GSI is a standardized statistic, the value of GSI
for all loci can be combined to produce an ensemble GSI,
which measures the structure of populations in an entire
To investigate gene ﬂow between lineages we used a
coalescent method implemented in the Isolation with Migra-
tion (IMa) software (Hey and Nielsen 2007) using separate
datasets for autosomal and Z-linked loci. Trial runs were
used to identify appropriate priors for the IMa model;
following trial runs, we ran IMa for a burn-in period of
500 000 steps followed by 100 million iterations ( 100
eﬀective sample size for each parameter). We performed
three runs of IMa with identical priors and diﬀerent starting
seeds to assess convergence. Additionally, we used log-likeli-
hood ratio tests of nested models implemented in IMa to
determine if models identifying no or asymmetrical migra-
tion explained the data as well as the full model. Nested
models were ranked using Akaike’s information criterion
(AIC; Carstens et al. 2009).
In total, 3271 base pairs from nine Z-linked loci were
sequenced for 16 brown creeper samples and supplemented
with 5063 base pairs from 21 autosomal loci from Manthey
et al. (2011b). One sample from the data matrix, from the
locus MUSK, could not be sequenced. For all Z-linked loci,
except BRM15, one sample of Certhia familiaris was
sequenced. Few (3/9) Z-linked loci shared any haplotypes
between populations, while the majority (15/21) of auto-
somal loci shared haplotypes between populations. DNA
sequences obtained in this study were deposited in GenBank
under accession numbers KF570392 – KF570652. Sequences
shorter than 200 base pairs are provided in the Supplemen-
tary material Appendix 1 because GenBank currently does
not accept sequences of this length.
Genetic diversity, neutrality and selection
Estimates of genetic diversity are shown in Table 1 and
Fig. 1. In general, the southern population exhibited greater
genetic diversity. In the northern population (southern
population), nucleotide diversity ranges from 0–0.67%
(0.03–0.88%) and 0–1.57% (0–1.99%) in Z-linked and
autosomal loci, respectively. Variance in nucleotide diversity
was signiﬁcantly higher in autosomal loci for the northern
population (Levene’s test; p 0.028) but not signiﬁcantly
diﬀerent between marker types in the southern population
(p 0.235). None of the loci deviated from neutrality
using both Tajima’s D and Fu and Li’s D* (Table 1).
e HKA test did not reject evolution under the neutral
model for the Z-linked (p 0.595), the autosomal
(p 0.969) or the combined (p 0.973) datasets. BAYES-
FST results identiﬁed seven outlier loci (Fig. 2) with the full
dataset (all loci). ree loci (MUSK, Ca34, and Ca65) are
suggestive of disruptive selection and four (MADH2, 00895,
13093, and Ca9) of balancing selection. BAYESFST results
for the autosomal and Z-linked datasets identiﬁed the same
outliers (results not shown) with the exception of MUSK,
which was not an outlier in the dataset with only Z-linked
Genetic structure and gene ﬂow
Z-linked markers exhibit a smaller level of shared polymor-
phisms between populations, while having more than
double the amount of ﬁxed polymorphisms (Fig. 1, Table 1).
e mean FST for Z-linked loci is higher (Mann–Whitney
U-test; p 0.014) than autosomal loci (Table 1, Fig. 3).
0 0.008 0.016
Proportion of base pairs polymorphic
Figure 1. Rates of polymorphisms in autosomal and Z-linked
markers, represented as proportion of total number of base pairs
that are polymorphic. Private polymorphisms (North and South),
polymorphisms shared between lineages (Shared) and polymor-
phisms ﬁxed between lineages (Fixed).
In this study, we identiﬁed increased levels of genetic dif-
ferentiation between lineages of C. americana on sex chro-
mosomes relative to autosomes (Fig. 1, Table 1), supporting
H01 (diﬀerentiation between lineages will be greater in
sex-linked markers than autosomal markers). e observed
levels of ﬁxed diﬀerences on sex chromosomes (2.05 the
autosomal level) are higher than what would be expected
under neutral evolution (~ 1.33). e ratio drops, but is still
higher (1.56 the autosomal level) than what would be
expected, when loci putatively evolving under selection are
removed. ese deviations from strict neutral evolution
could be due to sexual selection in males, causing deviations
in NEZ (Wu and Davis 1993), speciﬁc population size eﬀects
in birds (Mank et al. 2010a), or higher variance in male
reproductive success (Barker et al. 2008), leading to a
larger signal of faster-Z diﬀerentiation between lineages.
Alternatively, the levels observed here might be within the
expected variance of ﬁxed diﬀerences given the number of
base pairs sampled.
Additionally, we ﬁnd reduced gene ﬂow between
lineages on sex chromosomes (Table 2), supporting H02
(sex-linked markers will exhibit relatively less gene ﬂow
between lineages). ese estimates are limited in inferring
between pre-divergence genetic structure and post-divergence
gene ﬂow (Becquet and Przeworkski 2009); however, either
interpretation (i.e. high pre-divergence structure or low post-
divergence gene ﬂow on sex chromosomes) lends weight to
the hypothesis of the importance of sex chromosomes in the
speciation process in Certhia americana. Sampling individu-
als from a single population for each lineage introduces a
potential bias in parameter estimation of gene ﬂow (includ-
ing potential biases in eﬀective population size estimation);
however, this sampling regime limits the eﬀects of genetic
structure within each lineage in inducing further biases
in IMa, as both the northern and southern lineages of
C. americana have strong population structure (Wahlund
1928, Manthey et al. 2011a, b).
Autosomal FST comparisons have a greater range (0.000–
0.941) than Z-linked FST comparisons (0.4438–0.9636),
but do not have a signiﬁcantly greater variance (p 0.238).
Interestingly, in Z-linked loci, nucleotide diversity of the
southern population was negatively correlated with FST sta-
tistics (r –0.770, p 0.015) while northern nucleotide
diversity was not (p 0.585). In autosomal loci, FST com-
parisons are not correlated with nucleotide diversity in the
northern (p 0.071) or the southern lineage (p 0.089),
but nucleotide diversity between lineages is correlated
(p 0.001). While these properties may be biologically
meaningful (e.g. diﬀerent patterns of genetic diversity rela-
tionships with FST in Z-linked markers between lineages),
genetic diversity patterns between populations can limit
upper bounds of FST estimates (Jakobsson et al. 2013) which
may have led to the observed pattern.
Estimates of RND and Dxy (Table 1, Fig. 3) were, on
average, higher in Z-linked loci, although it was not statisti-
cally signiﬁcant (Mann–Whitney U-test; Dxy p-value 0.330;
RND p-value 0.647). Ensemble GSI statistics were
approximately the same for each population (Table 1). GSI
statistics were signiﬁcant for a majority of loci in both the
southern (8/9 Z-linked and 15/20 autosomal) and the north-
ern (8/9 Z-linked and 9/20 autosomal) populations. Many
of the loci show nested monophyly of one population (5/9
Z-linked and 7/21 autosomal) with the other paraphyletic
(one population’s GSI 1.00 and the other’s GSI 0.88).
Gene ﬂow estimates from coalescent-based analyses
(2Nm), as implemented in IMa, were lower in Z-linked
loci than autosomal loci (Table 2). Analyses of nested mod-
els identiﬁed models with reduced number of parameters
that could explain the data as well as the full model (Sup-
pementary material Appendix 1, Table A1, A2). However,
when using the AIC, the full model was best for the auto-
somal dataset and a model with zero migration north to
south was best for the Z-linked model. Although we
detected non-zero gene ﬂow in coalescent-based estimates,
it is not substantial enough (2Nm 2) to counteract the
eﬀects of genetic drift (Wright 1931, Slatkin 1987).
–5 –3 –1 1357
Transformed p-value; logit(2|P-0.5|)
Figure 2. Results from the BAYESFST analysis of all loci. e estimates of FST plotted against empirical p-values for each locus. e
vertical bar shows the 0.05 signiﬁcance level (~ 2.94 transformed p-value) used for identifying outlier loci. In analyses with autosomal or
Z-linked speciﬁc markers, results were the same as the full dataset with the exception of MUSK (denoted with an *) not being recognized
as an outlier.
0.0 0.2 0.4 0.6 0.8 1.0
Figure 3. FST values between lineages for each marker. e top nine markers are Z-linked and the bottom 21 are autosomal.
Lines through values indicate averages for each dataset separately.
Patterns of reduced gene ﬂow between lineages and
increased genetic diﬀerentiation between lineages in sex
chromosomes are similar to patterns observed in other
closely related avian species, including Ficedula ﬂycatchers
(Sætre et al. 2003, Borge et al. 2005), Luscinia nightin-
gales (Storchova et al. 2010), Passer sparrows (Elgvin et al.
2011) and Passerina buntings (Carling and Brumﬁeld
2008, 2009). Alternatively, other avian species (often with
low overall genetic diﬀerentiation) have shown greater
intraspeciﬁc Z-linked gene ﬂow (Dallimer et al. 2002, Li
and Merila 2010). ese patterns may suggest that
increased levels of diﬀerentiation on Z-linked markers and
reduced introgression only occur following signiﬁcant
divergence in allopatry (as opposed to within species
between localities). On average, RND indicates the north-
ern and southern C. americana lineages are nearly as diver-
gent as C. americana is to its sister-species (C. familiaris),
providing further support to previous literature (Manthey
et al. 2011a, b) suggesting signiﬁcant divergence in allopa-
try between C. americana lineages.
Higher levels of diﬀerentiation and reduced levels of
gene ﬂow on sex chromosomes also could be attributed to
female biased dispersal. Multiple lines of evidence suggest
biased dispersal is not the cause of this pattern. While no
studies have investigated natal philopatry in C. americana,
studies in C. familiaris show patterns of site tenacity follow-
ing establishment of territories (Cramp and Perrins 1993,
Peach et al. 1995) while young birds will disperse at least one
kilometer (Suorsa et al. 2003). ough Certhia species may
have short natal dispersal distances, they are likely inconse-
quential; research on C. americana song in California dem-
onstrates the formation of local dialects in populations less
than 50 km apart (Baptista and Krebs 2000). Finally, coales-
cent estimates of gene ﬂow (all estimates of 2Nm 2)
between the northern and southern clades of C. americana
(this study and Manthey et al. 2011b) indicate gene
ﬂow, including male- or female-biased gene ﬂow, was incon-
sequential in the evolutionary history of these lineages.
In general, the overall dataset did not deviate from
neutrality (HKA test, neutrality statistics; Table 1), however,
Table 1. Per locus statistics of polymorphism neutrality, and divergence. Statistics include: base pairs of marker (BP), nucleotide
diversity ( 100) in the north (p N) and south (p S), number of polymorphisms in the northern (N) and southern (S) lineages, number of
shared polymorphisms (PS), number of ﬁxed polymorphisms (PF), Tajima’s D (TD), Fu and Li’s D (FLD), FST, relative node depth (RND), and
genealogical sorting index of the southern (GSI S) and northern lineage (GSI N). Signiﬁcance (p 0.05) of neutrality indices and sample-
size corrected signiﬁcance (p 0.05) of GSI indicated by an asterisk (*).
Locus BP p N p S N S PSPFTD N TD S FLD N FLD S FST RND GSI S GSI N
MADH2 (Z) 482 0.667 0.535 10 10 5 0 0.24 20.62 0.53 20.73 0.4438 0.636 0.88*0.43*
PTCH6 (Z) 540 0.235 0.101 3 1 0 3 1.08 1.50 1.04 0.70 0.8120 0.743 1.00*0.88*
ALDOB3 (Z) 137 0 0.875 0 3 0 0 – 0.83 – 1.06 0.5079 0.759 0.03 0.76*
MUSK (Z) 349 0.108 0.044 3 1 0 7 21.70 21.15 22.20 21.37 0.9636 1.614 0.88*1.00*
GPBP1 (Z) 212 0.248 0.288 1 2 0 2 1.47 20.02 0.69 20.48 0.8468 1.883 0.88*1.00*
PPWD1 (Z) 423 0.238 0.515 6 7 0 0 20.58 20.18 0.91 20.75 0.4516 0.628 0.88*1.00*
IQGAP2 (Z) 395 0.095 0.034 3 1 0 3 21.70 21.16 22.20 21.43 0.9384 1.008 0.88*1.00*
BRM15 (Z) 290 0 0.795 0 8 0 1 – 20.23 – 0.33 0.5061 – 0.88*1.00*
24105 (Z) 443 0.102 0.194 2 4 0 0 20.65 20.97 20.50 20.60 0.5128 0.175 0.67*0.25
13093 (3) 322 1.571 1.991 16 14 11 0 20.06 1.28 0.41 1.23 0.0570 1.311 0.10 0.33
00895 (28) 218 0.665 0.887 3 7 3 0 1.75 20.29 1.04 20.44 0.0626 1.375 0.33 0.33
02108 (15) 194 1.349 0.851 6 4 2 0 1.53 1.15 1.27 1.14 0.1466 0.527 0.45*0.33
22528 (2) 265 0.579 0.333 5 3 0 0 0.06 20.07 0.46 1.04 0.1944 0.480 0.45*0.38
04550 (15) 89 0.539 0.627 1 1 1 0 1.03 1.53 0.69 0.69 0.0083 0.841 0.45*0.33
Ca4 (1A) 266 0.219 0 2 0 0 0 20.08 –20.50 – 0.2222 0.316 0.77*0.03
Ca8 (21) 172 – – – – – – – – – – – 0.000 – –
Ca9 (20) 274 1.183 1.128 9 10 7 0 0.72 0.10 0.91 20.35 0.0137 0.988 0.52*0.18
Ca10 (4A) 258 0.266 0.217 3 2 0 2 20.71 20.19 20.04 0.91 0.8125 0.906 0.88*1.00*
Ca13 (6) 266 0.595 0.746 4 9 1 0 0.98 20.99 1.14 21.01 0.4425 0.826 0.59*0.88*
Ca14 (3) 264 0.325 0.533 3 5 1 2 20.15 20.22 20.04 21.05 0.6832 1.300 1.00*0.88*
Ca15 (2) 227 0.737 0.671 5 6 2 0 0.19 20.68 0.46 20.05 0.1680 0.527 0.38 0.38
Ca21 (1) 216 0 0.847 0 5 0 2 – 0.19 – 0.46 0.6141 0.230 0.88*1.00*
Ca29 (1A) 189 0.401 0.366 2 2 1 0 0.66 0.91 0.91 0.91 0.0626 0.217 0.45*0.18
Ca34 (8) 222 0.180 0 1 0 0 1 0.65 – 0.69 – 0.8857 – 1.00*0.88*
Ca47 (24) 286 0.398 0.702 3 8 3 0 0.74 20.61 1.04 20.23 0.1126 0.807 0.14 0.33
Ca50 (12) 282 0 0.165 0 1 0 0 – 1.03 – 0.69 0.2666 0.086 0.88*1.00*
Ca51 (19) 290 0 0.129 0 3 0 0 – 21.70 –22.20 0.0000 2.031 0.00 0.27
Ca57 (1) 256 0.358 0.140 2 2 0 3 1.33 21.04 0.91 20.50 0.8477 0.912 0.88*1.00*
Ca58 (5) 246 0.262 0.458 2 4 0 0 0.84 20.25 0.72 20.63 0.4426 0.413 0.68*0.59*
Ca65 (3) 261 0.048 0.048 1 1 0 2 21.16 21.16 21.45 21.45 0.9411 2.000 1.00*0.88*
Z-linked 3271 0.188 0.376 28 37 5 16 0.6648 0.931 0.77*0.81*
Autosomal 5063 0.461 0.516 68 87 32 12 0.3326 0.804 0.58*0.55*
Overall 8334 0.379 0.474 96 124 37 28 0.4323 0.841 0.64*0.63*
Table 2. Coalescent-based (from IMa) estimates of gene ﬂow (2Nm)
from north to south (southward) and south to north (northward),
with associated 95% conﬁdence intervals. Three replicate runs were
performed for sex-linked (Z) and autosomal (A) loci with different
95% CI Northward
Z1 0.036 0.004–0.750 0.036 0.005–0.446
Z2 0.035 0.004–0.753 0.038 0.006–0.447
Z3 0.037 0.004–0.748 0.037 0.006–0.446
A1 0.230 0.022–1.221 0.385 0.114–1.452
A2 0.230 0.021–1.221 0.386 0.115–1.456
A3 0.229 0.021–1.219 0.383 0.115–1.461
in BayesFST analyses, three markers were identiﬁed as
potentially evolving under disruptive or directional selec-
tion (Fig. 2). Of these markers, more mapped to autosomes
than sex chromosomes, suggesting no clear trend in pat-
terns of selection based on marker type. ese results could
be caused by diﬀerential levels of gene ﬂow between mark-
ers or marker-types, potentially causing positive results in
the BayesFST test; these caveats suggest we should inter-
pret these results with caution, as positive selection, or
genetic drift with reduced gene ﬂow, may be driving the
observed patterns of sequence divergence in these loci.
When diﬀerentiation is investigated in concert with RND
(Table 1), the majority of Z-linked and autosomal markers
is not diverging between lineages faster than expected com-
pared to outgroup data, although two of the outliers in the
BAYESFST analysis (Ca65 and MUSK) had FST values
0.9 and RND values 1.6 (in Ca34 the outgroup
could not be ampliﬁed). ese combined patterns suggest
Ca65 and MUSK are good candidates for further investiga-
tion of selection.
Two lines of evidence suggest the selection patterns in the
data are driven by directional selection in the southern
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relationship between diﬀerentiation and genetic diversity in
the northern lineage. Under strict neutral evolution, it is
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correlated with intraspeciﬁc genetic diversity (Kimura 1983,
Li and Graur 2006). Second, in sex-linked markers, seven
loci show patterns of nested monophyly based on the GSI
(Table 1). Six of these indicate the southern lineage is nested
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Supplementary material (Appendix JAV-00233 at www.
oikosoﬃce.lu.se/appendix ). Appendix 1.