Download Male-Biased Mutation Rate and Divergence in Autosomal, Z

Male-Biased Mutation Rate and Divergence in Autosomal,
Z-Linked and W-Linked Introns of Chicken and Turkey
Erik Axelsson, Nick G.C. Smith,1 Hannah Sundström, Sofia Berlin, and Hans Ellegren
Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Sweden
To investigate mutation-rate variation between autosomes and sex chromosomes in the avian genome, we have analyzed
divergence between chicken (Gallus gallus) and turkey (Meleagris galopavo) sequences from 33 autosomal, 28 Z-linked,
and 14 W-linked introns with a total ungapped alignment length of approximately 43,000 bp. There are pronounced
differences in the mean divergence among autosomes and sex chromosomes (autosomes [A] ¼ 10.08%, Z chromosome ¼
10.99%, and W chromosome ¼ 5.74%), and we use these data to estimate the male-to-female mutation-rate ratio (am)
from Z/A, Z/W, and A/W comparisons at 1.71, 2.37, and 2.52, respectively. Because the am estimates of the three
comparisons do not differ significantly, we find no statistical support for a specific reduction in the Z chromosome
mutation rate (Z reduction estimated at 4.89%, P ¼ 0.286). The idea of mutation-rate reduction in the sex chromosome
hemizygous in one sex (i.e., X in mammals, Z in birds) has been suggested on the basis of theory on adaptive mutationrate evolution. If it exists in birds, the effect would, thus, seem to be weak; a preliminary power analysis suggests that it is
significantly less than 18%. Because divergence may vary within chromosomal classes as a result of variation in mutation
and/or selection, we developed a novel double-bootstrapping method, bootstrapping both by introns and sites from
concatenated alignments, to estimate confidence intervals for chromosomal class rates and for am. The narrowest interval
for the am estimate is 1.88 to 2.97 from the Z/W comparison. We also estimated am using maximum likelihood on data
from all three chromosome classes; this method yielded am ¼ 2.47 and approximate 95% confidence intervals of 2.27 to
2.68. Our data are broadly consistent with the idea that mutation-rate differences between chromosomal classes can be
explained by the male mutation bias alone.
Introduction
How do mutation rates vary within genomes? To date,
most vertebrate studies on mutation-rate variation have
focused on mammals with increasing evidence of significant local and regional substitution rate variation at putative
neutral sites within mammalian chromosomes (Wolfe,
Sharp, and Li 1989; Matassi, Sharp, and Gautier 1999;
Williams and Hurst 2000; Lercher, Williams, and Hurst
2001; Smith, Webster, and Ellegren 2002; Waterston et al.
2002; Hardison et al. 2003). The causes of this variation are
poorly understood (Ellegren, Smith, and Webster 2003),
although the observation of covariation of substitution rates
in orthologous regions along independent primate lineages
shows that regional rate variation is deterministic and
repeatable (Smith, Webster, and Ellegren 2002; Hardison et
al. 2003). Attempts to explain mutation-rate heterogenity
include invoking sequence context effects (Silva and
Kondrashow 2002; Zhao and Boerwinkle 2002; Arndt,
Petrov, and Hwa 2003; Smith, Webster, and Ellegren
2003), an association between mutation and recombination
processes (Lercher and Hurst 2002; Waterston et al. 2002;
Hardison et al. 2003; Hellmann et al. 2003), and the
evolution of isochores and the correlation between GC
content and substitution rates (Eyre-Walker and Hurst
2001). Understanding how and why mutation rates vary is
important not only in the contexts of the molecular basis for
mutation and genome evolution but also for addressing the
possibility for selection to modify mutation rates (mutationrate evolution [Sniegowski et al. 2000]).
1
Present address: Dept of Mathematics and Statistics, Fylde
College, Lancaster University, Lancaster, UK.
Key words: male-biased mutation, Z chromosome, W chromosome,
adaptive mutation rates, nonparametric bootstrapping.
E-mail: [email protected].
Mol. Biol. Evol. 21(8):1538–1547. 2004
doi:10.1093/molbev/msh157
Advance Access publication May 12, 2004
Substitution-rate variation is also seen at the level of
individual chromosomes. There are significant differences
in the mean substitution rate among autosomes in various
mammalian comparisons (Lercher, Willians, and Hurst
2001; Ebersberger et al. 2002). The sex chromosomes
show the most extreme variation, with the X chromosome
evolving slower than autosomes and the Y chromosome
evolving faster than autosomes (Li, Yi, and Makova 2002).
At least two factors are thought to affect mutation rate
variation between the mammalian sex chromosomes. First,
if replication error that occurs during germline cell division
is the major mutagenic process, then the much greater
number of germline cell divisions in males than in females
should increase the Y chromosome mutation rate relative
to the X chromosome (Miyata et al. 1987). This difference
underlies the argument for a male-biased mutation or maledriven evolution. In primates, molecular evolutionary
analyses show Y chromosome divergence to be approxiamtely 2.2 times higher than X chromosome divergence
(Shimmin, Chang, and Li 1993; Makova and Li 2002; but
see Bohossian, Skaletsky, and Page [2000]), which
translates to a male-to-female mutation rate ratio (am) of
4 to 6. In rodents, am is estimated at approximately 2
(Chang et al. 1994) and in goats at 3 to 4 (Lawson and
Hewitt 2002), potentially indicating a correlation between
generation time and am.
Second, we may expect selection to favor a reduced
mutation rate on the X chromosome because of the
hemizygous exposure of recessive deleterious mutations
(McVean and Hurst 1997). This theory was supported by
an early finding that the X-linked synonymous substitution
rate in the mouse-rat comparison was reduced to a greater
extent than could be caused by a male mutation bias alone
(McVean and Hurst 1997). However, the current evidence
for such an adaptive reduction in the X-linked mutation
rate of mammals is weak. For example, in a humanchimpanzee comparison of genomic sequences, the
Molecular Biology and Evolution vol. 21 no. 8 Ó Society for Molecular Biology and Evolution 2004; all rights reserved.
Divergence in Autosomal, Z-Linked, and W-Linked Avian Introns 1539
reduction in X-linked rates can be explained by a male
mutation bias and high ancestral polymorphism because
confidence intervals of the estimates of the male mutation
bias derived from different chromosome comparisons X/A,
Y/A, and Y/X overlap (Ebersberger et al. 2002). A similar
conclusion was recently reached by Malcom, Wyckoff, and
Lahn (2003) from extensive human-mouse and mouse-rat
comparisons that used synonymous substitution rates. It is
unclear why the results from the two latter studies are not
consistent with the observation of McVean and Hurst
(1997).
The sex chromosome system of birds (ZZ males and
ZW females) offers an interesting contrast to that of
mammals, not least because the avian sex chromosomes
evolved independently of those in mammals; that is,
mammalian X chromosomes and avian Z chromosomes
are not syntenic (Fridolfsson et al. 1998; Nanda et al. 1999,
2002). We expect the avian Z chromosome to have an
elevated mutation rate caused by the male mutation bias
because the Z chromosome spends two-thirds of its time in
males, where rates of germline cell division are high.
Accordingly, Z should evolve faster than the femalespecific W chromosome. This prediction is supported by
analyses of substitution rates in gametologous introns
shared between the Z and W chromosome of various bird
lineages (Ellegren and Fridolfsson 1997; Kahn and Quinn
1999; Carmichael et al. 2000; Fridolfsson and Ellegren
2000; Bartosch-Härlid et al. 2003); the Z chromosome
evolves faster than the W chromosome. There is some
variation in the different estimates of avian am (1.7 to 6.5),
but the confidence intervals associated with these estimates
are large, and so far, all estimates have been based on
molecular evolutionary analyses of a limited number of
short introns or short coding sequences.
Predictions for an adaptive reduction in X-linked
mutation rates apply in the same way to the avian Z
chromosome. Because deleterious mutations will be
exposed on the Z chromosome when hemizygous in
females, selection may favor a reduced mutation rate on
this chromosome. The effects of adaptive mutation rates
and the male mutation bias are, thus, expected to work in
opposition in birds, leading to reduced and increased Z
rate, respectively. Note that avian W as well as mammalian
Y is always hemizygous but, as will be discussed later,
several lines of arguments suggest that there is little
potential for adaptive mutation-rate evolution on these
chromosomes. The evidence for Z evolving faster than W
seems unambiguous, but this does not rule out that the Z
rate is lower than what should be expected from malebiased mutation alone.
Fortunately, a quantitative assessment of the role of
the male mutation bias and chromosome-specific mutation
rates in birds can by obtained from comparisons of
substitution rates in autosomes (A), the Z chromosome,
and the W chromosome. If the male mutation bias is the
main factor governing the mean mutation rate of
chromosomes, then estimates of am should be similar
from Z/A, Z/W, and A/W comparisons (cf. Miyata et al.
1987; McVean and Hurst 1997; Malcom, Wyckoff, and
Lahn 2003). On the other hand, if the Z chromosome
mutation rate is specifically reduced, am estimated from
A/W should be higher than when estimated from Z/A and
Z/W comparisons. To address this issue, we here make
a large-scale attempt to analyze substitution rate variation
in the avian genome by studying divergence in roughly 43
kb of orthologous, noncoding sequence of chicken (Gallus
gallus) and turkey (Meleagris galopavo). We obtain data
from 74 different introns on autosomes, Z chromosome,
and W chromosome and contrast am estimates from Z/A,
Z/W, and A/W comparisons.
Materials and Methods
Collection of Sequence Data
Chicken and turkey intron sequences were derived for
autosomal, Z-linked or W-linked genes (map information
from ArkDB farm animal database at www.thearkdb.org
or Schmid et al. [2000]), with the criterion of using only
introns longer than 200 bp to reduce stochastic variation in
estimates of divergence. This decision was motivated by
the use of a novel bootstrapping method that bootstraps by
both introns and sites. Also, excluding short introns may
reduce the effect of constraint on small introns that results
from conservation of splice sites. Because the exon-intron
organization is not given for most avian genes in
GenBank, we first Blasted chicken cDNA sequences
against the draft human genome at NCBI (July 2003
build). Large gaps in the avian sequence produced in such
Blast alignments should represent positions of putative
introns; for all genes analyzed in this study, this approach
revealed putative avian introns at precisely the same
positions as in orthologous human genes. After this
procedure, we designed exonic PCR primers for sequencing of both chicken and turkey introns (Appendix 1–3).
For a few genes, the full genomic sequence, including
exons and introns, was available in chicken. In those cases,
exonic primers were designed for amplification in turkey
only.
Chicken and turkey DNA was extracted from fresh
muscle tissue by standard proteinase K digestion and
phenol/chloroform purification, adapted from Hoelzel and
Green (1998). PCR reactions were carried out in 50-ll
reaction volumes that contained 20 to 250 ng of DNA
template, 13PCR Gold buffer (Applied Biosystems),
0.2 lM of each primer, 2.0 mM MgCl2, 0.2 mM dNTPs
(Amersham Pharmacia Biotech Inc), and 1 U Ampli Taq
Gold (Applied Biosystems). Amplification reactions were
performed using an initial denaturation at 958C for 5 min,
followed by 33 to 40 cycles at 948C for 30 s and specific
annealing and extension conditions for every intron.
Amplified fragments were purified using the Qiaquick
purification protocol (Qiagen), sequenced using BigDyeÔ
Terminator Cycle Sequencing chemistry with original
primers (Applied Biosystems), and sequences were
recorded with an ABI377 semiautomated sequencing
instrument (Applied Biosystems). Sites found to be
heterozygous in direct sequencing were excluded from
analysis. In some cases, sequencing was preceded by
cloning, which was done using the pGEM-T vector kit.
Sequencing reactions were then initiated with M13
vector primers. Sequence data from this article have
been deposited with the GenBank Data Library under
1540 Axelsson et al.
accession numbers AF006660, AF526055, AY139836
to AY139865, AY142943 to AY142944, AY144673
to AY144682, AY189754 to AY189777, AY194125 to
AY194147, AY298959 to AY299013, AY380785 to
AY380789, and AY426725 to AY426737.
Sequence Analysis
Orthologous chicken and turkey introns were aligned
by use of ClustalW on default settings (Thompson,
Higgins, and Gibson 1994), although some manual
adjustment was required to improve the alignment of
repetitive sequences. Pairwise distances were estimated by
use of the baseml program in PAML version 3.11 (Yang
1997), with the Tamura-Nei (Tamura and Nei 1993) model
of sequence evolution. Distances were estimated on the
assumption that all sites evolve at the same rate (i.e., no
among-site rate variation).
The estimation of confidence intervals and hypothesis
testing was carried out by application of nonparametric
bootstrapping. We developed a new bootstrapping procedure, termed double bootstrapping. For a given chromosome category (A, Z, or W) we first bootstrapped by
introns, randomly sampling introns with replacement to
give the same total number of introns as in the original data
set, and then, for each of the intron alignments, we
bootstrapped by sites, randomly sampling sites with
replacement to generate alignments of the same length as
the originals. The first stage of the bootstrapping procedure
accounts for variation in substitution rates between
different introns, as may be caused by regional variation
in mutation and/or selection (reviewed in Ellegren, Smith,
and Webster [2003]). Our preliminary observations
suggest that this variation may be significant in bird
genomes and that it is present in autosomes as well as the
sex chromosomes (S. Berlin, N. G. C. Smith, and H.
Ellegrin, unpublished data). Note, for instance, that the
point estimates of divergence in autosomal introns varies
between 3.9% and 18.5% (table 1), although these
estimates are associated with large confidence intervals.
We are currently investigating the causes of this rate
heterogeneity. Preliminary analyses suggest that conserved
sites or blocks explain part of the variation, but an
underlying variation in the mutation rate contributes as
well. One important implication of regional substitutionrate variation is that estimates of am can be heavily biased
when based on individual introns. The second stage of the
bootstrapping accounts for noise generated during the
estimation of divergence. Pairwise distances were calculated for each of the alignments after the double
bootstrapping, and the unweighted mean of these distances
was taken as the output.
The bootstrapping process was repeated 1,000 times,
thereby giving 1,000 sets of W-linked, Z-linked, and
autosomal divergences from which to estimate the male
mutation bias (am) and other rate statistics. The standard
deviation of the bootstrap values gives an estimate of the
standard error of the bootstrapped statistic (Sokal and
Rohlf 1995). Hypothesis testing that required the comparison of rate statistics was performed by direct comparison
of randomized bootstrap values.
Results
A set of autosomal, Z-linked and W-linked introns
were sequenced and analyzed in chicken and turkey, two
species with a divergence time of 28 MYA, estimated by
use of mitochondrial DNA–based molecular clocks
(Dimcheff, Drovetski, and Mindell 2002). We obtained
33 orthologous autosomal alignments with a total ungapped length of 16,188 bp (table 1), 28 Z-linked
alignments with total length 16,079 bp (table 2), and 14
W-linked alignments with total length 10,621 bp (table 3).
There are pronounced differences in mean divergence
among autosomes and sex chromosomes (autosomes [A] ¼
10.06%, Z chromosome ¼ 10.95%, and W chromosome ¼
5.71%). When the divergences were calculated using the
double-bootstrapping method (see Materials and Methods), we obtained the following values of medians and
standard errors for the concatenated alignments: A ¼
10.08% 6 0.67%, Z ¼ 10.99% 6 0.48%, and W ¼
5.74% 6 0.49%. Thus, both autosomal and Z-linked sequences seem to evolve at just under twice the rate of
W-linked sequences in the chicken–turkey comparison.
Figure 1 shows the distribution of bootstrap values for
autosomes, the Z chromosome, and the W chromosome
with the double-bootstrapping method.
Divergence data from autosomes and sex chromosomes allows the partitioning of the effects of the male
mutation bias and one other factor that affects substitution
rates. If substitution rates are solely determined by the
male mutation bias, then all three estimates of the male
mutation bias (am) based on pairwise comparisons of
divergence in pairs of chromosome categories (equations 1
to 3, using the approach of Miyata et al. [1987]) should
give the same value.
am ðZ=WÞ ¼ ð3Z=W 1Þ=2
ð1Þ
am ðA=WÞ ¼ ð2A=W 1Þ
am ðZ=AÞ ¼ ð3Z=A 2Þ=ð4 3Z=AÞ
ð2Þ
ð3Þ
From equations 1 to 3, we obtain the following am
estimates: Z/A ¼ 1.71 (95% confidence interval 0.62 to
7.16), Z/W ¼ 2.37 (1.18 to 2.97), A/W ¼ 2.52 (1.88 to
3.34). The bootstrap distribution of am estimates for each
comparison is shown in figure 2.
We can quantify any discrepancies in the three
estimates of am by using rearrangements of equations 1 to
3 to predict divergence in one chromosome category, given
observed divergences in the two other. Here, we predict
divergence on the Z chromosome, given the autosomal and
W-linked data. Comparing the expected and observed Zlinked divergences then gives the percentage reduction in
the Z-linked substitution rate, termed Zr (equation 4).
Z
Zr ¼ 100 1 ð4Þ
ð4A WÞ=3
Using the double-bootstrapping method, the median
value of Zr is 4.89%, with a large bootstrap standard error
of 8.50%. So in this approach, there no evidence of
a significant discrepancy (P ¼ 0.286; one-tailed probability
of Zr 0) from the male mutation bias predictions. Hence,
Divergence in Autosomal, Z-Linked, and W-Linked Avian Introns 1541
Table 1
Data for Autosomal Introns
Locus name
Nicotinic acetylcholine
receptor, c-subunit
Actin, b
Actin, b
Adenylate kinase 1
Annexin V
Annexin V
POU domain
Neural secreted
glycoprotein
Creatin kinase, brain
Clathrin heavy chain
Crystalline, bA3
Transcriptional
repressor-d EF1
Fatty acid synthase
Growth hormone 1
Glyceraldehyde-3-phosphate
dehydrogenase
Hemoglobin, aD
Heat shock 108 kDa
protein 1
Interleukin 8
Luteinizing hormone/
choriogonadotropin recep
Ribosomal protein–encoding
gene L37A
Ribosomal protein–encoding
gene L5
Ribosomal protein–encoding
gene L7A
Ribosomal protein–encoding
gene L7A
Myosin light chain
Opsin
Opsin
Opsin
Ovomucoid
Rhodopsin visual
pigment
Rhodopsin visual
pigment
Ribosomal protein–encoding
gene L30
Transforming growth factor–b2
Vimentin
Locus
Symbol
Intron
ACGR
ACTB
ACTB
AK1
ANXA5
ANXA5
BRN-3
F
2
3
3
5
7
1
CEPU
CKB
CLTC
CRYBA3
Chicken Accession
Numbers
Turkey Accession
Numbers
Ungapped Alignment
Length (bp)
Divergence (%)
K02904
X00182
X00182
D00251
U01671
U01671
X91997
AY144678
AY298978
AY298979
AY298973
AY298974
AY298975
AY298977
691
479
297
366
387
390
370
7.1
3.9
12.6
6.4
6
10.9
9
1
1
5
2
AJ225897
AY139862
AJ429073
M84460
AY142943
AY139863
AY142944
AY14467
607
469
619
776
6.9
4.9
9.5
8.3
DEF1
FASN
GH1
3
Y
2
D76434
J02839
D10484
AY144673
AY298980
AY144673
621
417
435
8.8
7.6
9.1
10
GAPD
HBAD
3
2
M11213
X59989
AY298981
AY298976
271
247
13.3
HSP108
IL8
1
3
AY139864
AJ009800
AY139865
AY298982
662
539
17.5
15.2
LHCGR
7
AJ289775
AY144675
498
9.1
RPL37A
3
D14167
AY298987
827
9.9
RPL5
4
D10737
AY380788
592
8.3
RPL7A
3
D14522
AY380789
341
12.9
RPL7A
MLC
OPSIN
OPSIN
OPSIN
OVM
4
6
1
3
4
G
D14522
X00460
U87449
U87449
U87449
AF170979
AY298988
AY144675
AY298983
AY298984
AY298985
AF170984
345
460
438
204
370
431
7.1
13.1
14.4
10.1
18.5
4.8
RHO
1
D00702
AY144679
818
15.9
RHO
4
D00702
AY144680
356
11.8
RPL30
TGFB2
VIM
3
5
E
D14521
X60091
M15852
AY144681
AY298986
AY144682
731
552
582
10.2
9.7
9.4
with the present data set, the male-mutation bias is
sufficient to explain observed differences in divergence
of autosomal, Z-linked, and W-linked sequences in the
chicken–turkey comparison.
It is noteworthy that the am estimates from the three
possible comparisons remain consistent despite the
significant differences in GC content between autosomes
and sex chromosomes: autosomes ¼ 46.7%, Z chromosome ¼ 36.3%, and W chromosome ¼ 33.1% (t-tests: WA, P 0.0001; Z-A, P 0.0001; Z-W, P ¼ 0.088). This
finding suggests that GC content does not have a strong
effect on mean divergence of chromosomal classes, at least
not in the sense that it would affect am estimates.
The observed divergences can be used for estimation
of absolute substitution rates between chicken and turkey.
Using a divergence time of 28 MYA (Dimcheff, Drovetski,
and Mindell 2002), we obtain rates of A ¼ 3.6 3 1029, Z ¼
3.9 3 10–9 and W ¼ 2.0 3 10–9 substitutions per site per
year. These rate estimates may be useful for dating events
in bird evolution based on nuclear sequence data, although
substitution rates may, of course, vary among avian
lineages. In mammals, substitution rates in the human
and mouse lineages since the split of primates and rodents
have been estimated at 2.2 3 10–9 and 4.5 3 10–9, respectively (Waterston et al. 2002). Note that these latter substitution rates represent the average rates since the time of
divergence, and that current rates may differ even more as
the difference in generation time between human and most
rodents should be more significant now than shortly after
divergence (assuming a generation time effect on substitution rates).
It is interesting to note that the substitution rate
estimates for the chicken–turkey comparison are very
similar to that obtained from restriction site analysis of
1542 Axelsson et al.
Table 2
Data for Z-linked Introns
Locus Name
Aconitase 1
Aldolase B
Aldolase B
Aldolase B
Aldolase B
ATP synthase
a2subunit on Z
brm
Chromo-helicase-DNA
binding 1 on Z
Chromo-helicase-DNA
binding 1 on Z
Chromo-helicase-DNA
binding 1 on Z
Chromo-helicase-DNA
binding 1 on Z
Chromo-helicase-DNA
binding 1 on Z
Chromo-helicase-DNA
binding 1 on Z
Chromo-helicase-DNA
binding 1 on Z
Chromo-helicase-DNA
binding 1 on Z
Chromo-helicase-DNA
binding 1 on Z
Chromo-helicase-DNA
binding 1 on Z
Chromo-helicase-DNA
binding 1 on Z
Histidine triad
nucleotide-binding
protein on Z
Patched
Patched
Purpurin
Spindlin on Z
Ubiquitin-associated
protein 2 on Z
Ubiquitin-associated
protein 2 on Z
Ubiquitin-associated
protein 2 on Z
Very-low-density
lipoprotein receptor
(95 kDa)
Very-low-density
lipoprotein receptor
(95 kDa)
Locus
Symbol
ACO1
ALDOB
ALDOB
ALDOB
ALDOB
Intron
Chicken Accession
Number
Turkey Accession
Number
Ungapped Alignment
Length (bp)
Divergence (%)
2
1
2
5
7
AY139856
AY380785
AY139836
AY139839
AY139841
AY139857
AY380786
AY139842
AY139845
AY139847
387
277
239
470
413
13.4
8.9
13.9
9.9
9.2
3
15
AF165969
AY298991
AF165971
AY298992
789
278
12.3
10.1
CHD1Z
6
AY298997
AY299005
719
12.2
CHD1Z
7
AY298998
AY299006
234
10.2
CHD1Z
9
AY298999
AY299007
482
14.8
CHD1Z
10
AY298993
AY299000
605
12
CHD1Z
11
AY298994
AY299001
771
12.4
CHD1Z
12
AY426729–30
AY426733
996
13
CHD1Z
13
AY298995
AY299002
324
11.2
CHD1Z
15
AF525980
AF526014
419
14.2
CHD1Z
22
AY426728
AY426734
1222
11.2
CHD1Z
24
AF526056
AY299008
394
8.7
CHD1Z
25
AY298996
AY299004
702
11.9
HINTZ
PTCH
PTCH
PURP
SPINZ
2
7
8
3
2
AB026676
AY299009
AY299011
AY298989
AY194142
AY194147
AY299010
AY299012
AY298990
AY194143
685
346
420
259
768
11.7
9.8
10.1
6.9
11.3
UBAP2Z
1
AY189761
AY189760
1185
7.3
UBAP2Z
2
AY189777
AY189776
406
9.1
UBAP2Z
4
AY426726
AY426732
1442
9.6
VLDLR
7
AY139848
AY139851
460
11.1
VLDLR
9
AY139850
AY139853
387
10.4
ATP5A1Z
BRM
several galliform species (Helm-Bychowski and Wilson
1986). These authors mapped 161 restriction sites from
three autosomal regions and associated estimates of
divergence with fossil evidence. Using different calibration
points in galliform evolution, they arrived at rate estimates
of 3.4 3 1029 to 4.0 3 1029 substitutions per site per year.
Apparently, the relative early molecular evolutionary work
of Helm-Bychowski and Wilson (1986) is in good
agreement with data from large-scale DNA sequencing.
Discussion
In this study, we addressed between-chromosome
variation in mutation rates in birds. Our approach was to
use variation in intronic divergence to infer mutation-rate
variation directly. How well justified is this inference? The
most likely complication is the effect of selection on
intronic sequences in birds. Little is yet known on this
subject, but given that comparative studies are uncovering
numerous nongenic conserved regions in mammalian
genomes (e.g., see Dermitzakis et al. [2002]) and that
bird genomes are smaller than mammalian genomes, it
seems possible that conserved regulatory sequences may
be relatively common in avian genomes. However, given
that a large number of introns were analyzed for each
chromosome category and that there may by regional
mutation-rate variation or local effects of selection, the
present data set may better reflect the mean substitution
Divergence in Autosomal, Z-Linked, and W-Linked Avian Introns 1543
Table 3
Data for W-linked introns
Locus Name
ATP synthase
a-subunit on W
Chromo-helicase-DNA
binding 1 on W
Chromo-helicase-DNA
binding 1 on W
Chromo-helicase-DNA
binding 1 on W
Chromo-helicase-DNA
binding 1 on W
Chromo-helicase-DNA
binding 1 on W
Chromo-helicase-DNA
binding 1 on W
Chromo-helicase-DNA
binding 1 on W
Chromo-helicase-DNA
binding 1 on W
Chromo-helicase-DNA
binding 1 on W
Spindlin on W
Ubiquitin-associated
protein 2 on W
Ubiquitin-associated
protein 2 on W
Ubiquitin-associated
protein 2 on W
Locus
Symbol
Intron
Chicken Accession
Number
ATP5A1W
3
AF165968
CHD1W
7
CHD1W
Ungapped Alignment
Length (bp)
Divergence (%)
AF165970
771
7.6
AY298971
AY426735
250
4.4
10
AY298965
AY298959
569
6.9
CHD1W
11
AY298966
AY298960
582
6.7
CHD1W
12
AY426727
AY426736–7
1066
6.4
CHD1W
15
AY298972
AF526013
274
5.9
CHD1W
17
AY298970
AY299013
677
5.4
CHD1W
22
AY298968
AY298963
1249
5.4
CHD1W
25
AY298969
AY298964
684
4.1
CHD1W
SPINW
24
2
AF526055
AY194125
AF526077
AY194126
405
611
8.5
4.1
UBAP2W
1
AY189754
AY189755
1204
3.8
UBAP2W
2
AY189767
AY189768
832
4.5
UBAP2W
4
AY426725
AY426731
1447
6.1
rate of chromosome category than a similar amount of
sequence derived from a single region for each category.
Turkey Accession
Number
Our point estimates of am for the chicken–turkey
comparison are 1.71, 2.37, or 2.52, depending on whether
based on Z/A, Z/W, or A/W comparison. Previous studies
of male-biased mutation in birds have revealed am
estimates in the range of 1.7 to 6.5 (Ellegren and
Fridolfsson 1997, Kahn and Quin 1999, Carmichael et
al. 2000, Fridolfsson and Ellegren 2000, Bartosch-Härlid
et al. 2003), so our point estimates are in the lower range
of reported values (table 4). However, most of the
estimates are associated with large confidence intervals,
and the confidence intervals obtained in this study (0.62 to
7.16, 1.18 to 2.97, and 1.88 to 3.34) generally overlap with
those of previous studies.
If we assume a single true value of am, then we can
estimate it by combining data from autosomes, the Z
chromosome, and the W chromosome. For each intron, the
observed number of substitutions [O(S)] is given by the
ungapped length of the alignment multiplied by the
divergence. Note that although we refer to these data as
‘‘observed,’’ strictly speaking they are inferred from the
alignments, but here we assume perfect inference of
divergence. Then assuming a single am, we can calculate
the expected number of substitutions, E(S), for each intron
FIG. 1.—Histogram of 1,000 bootstrap values of autosomal, Wlinked, and Z-linked divergences. Bootstrap values were obtained using
the double-bootstrap method (see Materials and Methods).
FIG. 2.—Histogram of 1,000 bootstrap values of the male-to-female
mutation-rate ratio am(A/W), am(Z/W), and am(Z/A). Bootstrap values
were obtained by use of the double-bootstrap method.
The Male Mutation Bias
1544 Axelsson et al.
Table 4
Estimates of am in Birds
Type of
Sequence
Length
(bp)
CHD1Z/CHD1W
CHD1Z/CHD1W
CHD1Z/CHD1W
Intron
Exon
Intron
711
2,754
738
1.4–2.2
1.3–3.3
1.7–3.2
2.3–2.7
2.4–4.6
1.1–6.7
3.1–5.1
ATP5A1Z/ATP5A1W
ATP5A1Z/ATP5A1W
CHD1Z/CHD1W
74 different regions
CHD1Z/CHD1W
CHD1Z/CHD1W
CHD1Z/CHD1W
Intron
Intron
Intron
Intron
Intron
Exon
Intron
;800
;800
711
42,888
711
615
428
4.7
3.4–6.0
CHD1Z/CHD1W
Intron
731
5.0
6.5
3.3–6.6
2.8–10.2
ATP5A1Z/ATP5A1W
CHD1Z/CHD1W
Intron
Intron
;800
230
am
CI
1.7
1.7
1.8
0.9–2.5
ND
1.2–2.3
1.8
2.3
2.4
2.5
3.5
3.9
4.1
Gene
Species
Reference
Ten passeriforms
Three different orders
One anseriform, two
galliforms
Two galliforms
Two anseriforms
Six passeriforms
Two galliforms
Four passerforms
Two passeriforms
One galliform, three
anseriforms
Two procellariiforms,
four charadriiforms
Two gulls
Four passeriforms
Bartosch-Härlid et al. (2003)
Fridolfsson and Ellegren (2000)
Bartosch-Härlid et al. (2003)
Carmichael et al. (2000)
Carmichael et al. (2000)
Bartosch-Härlid et al. (2003)
This study
Bartosch-Härlid et al. (2003)
Ellegren and Fridolfsson (1997)
Kahn and Quinn (1999)
Bartosch-Härlid et al. (2003)
Carmichael et al. (2000)
Ellegren and Fridolfsson (1997)
NOTE.—Confidence interval (CI) is 95% (when available). The method for estimating CI has varied among studies. ND indicates not determined.
as the product of ungapped alignment length, a chromosome-specific scaling factor, and a normalizing factor that
ensures the sum of expected substitutions equals the sum of
observed substitutions. The chromosome-specific scaling
factors (K) reflect the proportion of time spent in the male
and female germlines: KW ¼ 1, KA ¼ (11 am)/2, and KZ ¼
(112am)/3. The log-likelihood of am can be approximated
by the G-test statistic (page 692 in Sokal and Rohlf [1995]),
which uses the O(S) and E(S) values to generate
a maximum-likelihood estimate of am ¼ 2.47. Approximate
95% confidence intervals can be estimated as the range of
am for which the log-likelihood is within 2 units of the
maximum, which yields a range of 2.27 to 2.68.
Because the amount of sequence data in the present
study exceeds that of earlier avian studies by one or two
orders of magnitude, and the data are based on autosomes
as well as sex chromosomes, our maximum-likelihood am
estimate may be viewed as the most accurate estimate yet
obtained for birds. This contention is substantiated by the
fact that our estimate is based upon sequence data from
a large number of regions from each chromosome
category. Regional mutation-rate variation would make
am estimates sensitive to the particular regions used for
molecular evolutionary analysis. Previous studies of malebiased mutation in birds (e.g., Ellegren and Fridolfsson
[1997], Kahn and Quinn [1999], Carmichael et al. [2000],
and Bartosch-Härlid et al. [2003]), as well as many studies
in other organisms (e.g., Shimmin, Chang, and Li [1993],
Bohossian, Skaletsky, and Page [2000], and Makova and
Li [2002]), have been based on one or a few genomic
regions only.
Given the overlap in confidence intervals between the
present am estimates in the chicken–turkey comparison
and those obtained in studies of other bird species, it would
be premature to conclude that the male mutation bias is
lower in galliforms than in other birds. On the other hand,
a low-point estimate of 1.8 was independently obtained for
chicken and turkey using ATP5A1Z/ATP5A1W intron
sequences (Carmichael et al. 2000), and the same estimate
was obtained in a three-species comparison that included
one anseriform and two other galliform species using
CHD1Z/CHD1W introns (Bartosch-Härlid et al. 2003). We
have recently found evidence of am being higher in avian
lineages with longer generation time and with higher
intensity of sexual selection, which suggests a link
between life-history characteristics and the male mutation
bias (Bartosch-Härlid et al. 2003). Most galliforms breed
at the age of 1 year, so a rather weak male mutation bias
would be consistent with a generation time effect.
A potential problem in estimation of the male
mutation bias from sex-linked sequences is the effect of
ancestral polymorphism, which can bias estimates of am
when distances are low and lineage sorting is incomplete
(Makova and Li 2002; Ellegren 2002a). However, the
effect of ancestral polymorphism in our study is expected
to be minimal because all pairwise distances between
chicken and turkey are relatively high (5% to 11%), and
with a divergence time of 28 MYA, lineage sorting should
have been completed long ago. Makova and Li (2002)
found ancient polymorphism to affect estimates of am in
the human–chimpanzee comparison (;1% divergence) but
not in comparisons of human and more distantly related
primates.
Is There a Reduction in the Z Chromosome
Mutation Rate?
Our results indicated that in birds, the Z-linked
introns evolve slightly faster than autosomal introns,
which, in turn, evolve much faster than W-linked introns.
These qualitative findings are in keeping with the male
mutation bias predictions of Miyata et al. (1987), and there
is, thus, no apparent need to invoke factors additional to
the male mutation bias to explain variation in divergence
among chromosomal classes. Alternatively, we can view
our results as indicating that such potential factors, if they
exist, must be weak, which is opposite to some previous
suggestions (McVean and Hurst 1997).
There is the theoretical possibility that the increased
efficacy of selection against slightly deleterious mutations
Divergence in Autosomal, Z-Linked, and W-Linked Avian Introns 1545
on the avian Z chromosome relative to the autosomes
(Charlesworth, Coyne, and Barton 1987) could reduce the
mutation rate on the Z chromosome relative to null
expectations. However, a quantitative analysis provides
confidence that weak selection is unlikely to be responsible, for example, for a 5% reduction (the estimated
value of Zr) in the Z chromosome mutation rate.
Irrespective of the nature of dosage compensation in birds
(see Ellegren [2002b]), the expected substitution rate of
autosomal relative to Z-linked sequences, RA/Z, is given by
(see equations 8a and 9 in Charlesworth, Coyne, and
Barton [1987]):
1
1
ð5Þ
RA=Z ¼ 1 þ Ns h 3
2
Even if all slightly deleterious mutations are recessive
(McVean and Charlesworth 1999), a conservative assumption with respect to the strength of selection required, then
equation 5 shows that a 5% reduction in Z-linked
divergence requires the magnitude of Ns, the product of
the selective coefficient of mutations and the effective
population size, to be unrealistically high.
We conclude that some theoretical arguments as well
as our empirical observations do not support a significantly
reduced Z-chromosome mutation rate. On the other hand,
failure to demonstrate an effect does not mean that it does
not exist. Our data set may simply have been too small to
allow detection of a modest reduction in Z rate. Additional
data are, thus, needed to firmly settle the question and
should be accompanied by a power analysis to reveal what
minimum reduction in the Z-chromosome mutation rate
would be detectable with the data. Such an analysis would
require a deeper insight into the patterns and causes of
substitution rate heterogeneity among introns or other
chromosomal regions. However, as a preliminary analysis
of the power of our data set to determine the maximum
value of a putative Z reduction, we took the 95% percentile
of the 1,000 double-bootstrap estimates of Zr. This method
indicated that Zr is significantly less than 18%. We note
that this value is considerably less than the point estimate
of Zr ¼ 30% in rodents obtained from the X and A
substitution data of McVean and Hurst (1997) combined
with the assumption of a male-to-female mutation bias of 2
in rodents (Chang et al. 1994).
Why Not a Reduced W-Chromosome Mutation Rate?
It should be noted that we may as well had predicted
divergence on the W chromosome, given the observed
autosomal and Z-linked rates. Similarly, in theory, we
could have inferred the reduction in W-linked substitution
rates, Wr, by comparison of expected and observed
divergences (table 4). Using the present data set, the
outcome of such an analysis would have been the same as
the analysis of a possible reduction on Z; all comparisons
give the same one-tailed probability (P ¼ 0.286) and, thus,
provide no statistical support for deviations from expectations from the male mutation bias. However, the question
of which approach is the correct one is still warranted from
a general perspective: Shall we rely on the observed W rate
to calculate the expected Z rate (via comparison with
autosomes), or shall we use the observed Z rate to predict
the rate on W? Put in other words, should potential
discrepancies between the three ways of estimating am be
interpreted as a reduction in the substitution rate on the Z
chromosome or as a reduction in the substitution rate on
the W chromosome (or as some combination of the two
factors)? In fact, the corresponding question applies to
studies of mammalian sex chromosomes: Shall the
observed Y rate be used to predict the rate on X, or shall
the observed X rate be used to calculated the expected rate
on Y? Previous work in this field has ignored the latter
possibility and only addressed the possible reduction in
X-chromosome mutation rate (McVean and Hurst 1997;
Nachman and Crowell 2000; Ebersberger et al. 2002;
Malcom, Wyckoff, and Lahn 2003).
There is no way to differentiate between these
possibilities with present data, because three chromosome
categories means only two degrees of freedom, and one of
those is used to estimate the male mutation bias. If we had
some way of knowing the ‘‘true’’ male mutation bias, we
could use the extra degree of freedom to differentiate
between a W reduction and a Z reduction by seeing which
of the Z/A and A/W comparisons gave the am estimate
closest to the true value. However, evolutionary theory
may help to resolve the issue. The argument for a reduction
in the Z chromosome mutation rate (McVean and Hurst
1997) relies on cost-benefit considerations of adaptive
mutation rates. Given that the Z chromosome contains
many more genes than the tiny W chromosome (probably
by at least two orders of magnitude [Ellegren 2000;
Schmid et al. 2000]), the strength of selection for a reduced
mutation rate should be expected to be much higher on Z
than on W. Moreover, note that the benefit of a reduced
mutation rate is the avoidance of deleterious mutations
being exposed in a hemizygote chromosome. Although W
is always hemizygous, a majority of the avian W-linked
genes so far characterized have highly similar, and likely
functionally equivalent, homologs on Z (Ellegren 2002b).
Recessive mutations in these W-linked genes are likely to
be masked by the gametologous Z-linked genes, thereby
giving little benefit of mutation-rate reduction.
The Double-Bootstrapping Method
Estimating the confidence intervals of divergence
measures by bootstrapping individual sites from concatenated data sets is commonly applied in molecular
evolutionary studies. However, the increasing support for
regional mutation-rate variation within genomes (reviewed
in Ellegren,. Smith, and Webster [2003]), which includes
our preliminary data for birds, necessitated an adjustment
in the method for estimating the confidence intervals of
chromosomal class divergences. Simply concatenating all
alignments and then bootstrapping by sampling with
replacement from all sites is not sufficient, because it does
not account for the variation generated by the choice of
a limited number of introns. To account for regional
variation, we developed the double-bootstrapping method,
which bootstraps by introns and by sites within intronic
alignments and then takes the unweighted mean of the
1546 Axelsson et al.
bootstrapped alignments. With this method, we found no
statistical support for a specific reduction of the Zchromosome mutation rate. Had we only bootstrapped
by sites, slightly different divergence medians and
significantly different standard errors would have been
obtained (A ¼ 10.27% 6 0.28%, Z ¼ 10.89% 6 0.28%,
and W ¼ 5.66% 6 0.26%). Note that the much lower
standard errors compared with the double-bootstrapping
procedure is a consequence of not taking rate variation
among introns into account. Importantly, with this
approach, there would have been significant support for
a reduction in the Z-chromosome mutation rate (Zr ¼
7.88%, P ¼ 0.026). We believe this observation is one of
general significance and that it calls for careful statistical
treatment of molecular evolutionary data sets in the
presence of underlying rate heterogeneity.
Acknowledgment
Financial support was obtained from the Swedish
Research Council. H.E. is a Royal Academy of Sciences
Research Fellow supported by the Knut and Alice
Wallenberg Foundation. We thank Scott Edwards and
two anonymous reviewers for useful comments.
Literature Cited
Arndt, P. F., D. A. Petrov, and T. Hwa, 2003. Distinct changes of
genomic biases in nucleotide substitution at the time of
mammalian radiation. Mol. Biol. Evol. 20:1887–1896.
Bartosch-Härlid, A., S. Berlin, N. G. C. Smith, A. P. Møller, and
H. Ellegren. 2003. Life history and the male mutation bias.
Evolution 57:2398–2406.
Bohossian, H. B., H. Skaletsky, and D. C. Page. 2000.
Unexpectedly similar rates of nucleotide substitution found
in male and female hominids. Nature 406:622–625.
Carmichael, A. N., A. K. Fridolfsson, J. Halverson, and H.
Ellegren. 2000. Male-biased mutation rates revealed from Z
and W chromosome-linked ATP synthase alpha-subunit
(ATP5A1) sequences in birds. J. Mol. Evol. 50:443–447.
Chang, B. H. J., L. C. Shimmin, S. K. Shyue, D. Hewett-Emmett,
and W. H. Li. 1994. Weak male-driven evolution in rodents.
Proc. Natl. Acad. Sci. USA 91:827–831.
Charlesworth, B., J. A. Coyne, and N. H. Barton. 1987. The
relative rates of evolution of sex chromosomes and autosomes. Am. Nat. 130:113–146.
Dermitzakis, E. T., A. Reymond, R. Lyle et al. (11 co-authors).
2002. Numerous potentially functional but non-genic conserved sequences on human chromosome 21. Nature
420:578–582.
Dimcheff, D. E., S. V. Drovetski, and D. P. Mindell. 2002.
Phylogeny of Tetraoninae and other galliform birds using
mitochondrial 12S and ND2 genes. Mol. Phyl. Evol. 24:
203–215.
Ebersberger, I., D. Metzler, C. Schwarz, and S. Paabo. 2002.
Genomewide comparison of DNA sequences between humans
and chimpanzees. Am. J. Hum. Genet. 70:1490–1497.
Ellegren, H. 2000. Evolution of the avian sex chromosomes and
their role in sex determination. Trends Ecol. Evol. 15:
188–192.
———. 2002a. Human mutation: blame (mostly) men. Nat.
Genet. 31:9–10.
———. 2002b. Dosage compensation: do birds do it as well?
Trends Genet. 18:25–28.
Ellegren, H., and A. K. Fridolfsson. 1997. Male-driven evolution
of DNA sequences in birds. Nat. Genet. 17:182–184.
Ellegren, H., N. G. C. Smith, and M. T. Webster. 2003. Mutation
rate variation in the mammalian genome. Curr. Opin. Genet.
Dev. 13:562–568.
Eyre-Walker, A., and L. D. Hurst. 2001. The evolution of
isochores. Nat. Rev. Genet. 2:549–555.
Fridolfsson, A. K., H. Cheng, N. G. Copeland et al. (10 coauthors). 1998. Evolution of the avian sex chromosomes from
an ancestral pair of autosomes. Proc. Natl. Acad. Sci. USA 95:
8147–8152.
Fridolfsson, A. K., and H. Ellegren. 2000. Molecular evolution of
the avian CHD1 genes on the Z and W sex chromosomes.
Genetics 155:1903–1912.
Hardison, R. C., K. M. Roskin, S. Yang et al. (18 co-authors).
2003. Covariation in frequencies of substitution, deletion,
transposition, and recombination during eutherian evolution.
Genome Res. 13:13–26.
Hellmann, I., I. Ebersberger, S. E. Ptak, S. Pääbo, and M.
Przeworski. 2003. A neutral explanation for the correlation of
diversity with recombination rates in humans. Am. J. Hum.
Genet. 72:1527–1435.
Helm-Bychowski, K. M., and A. C. Wilson. 1986. Rates of
nuclear DNA evolution in pheasant-like birds: evidence from
restriction maps. Proc. Natl. Acad. Sci. USA 83:
688–692.
Hoelzel, A. R., and A. Green. 1998. PCR protocols and
population analysis by direct DNA sequencing and PCRbased DNA fingerprinting. Pp. 201–233 in A. R. Hoelzel, ed.
Molecular genetic analysis of populations: a practical approach. Oxford University Press, Oxford, UK.
Kahn, N. W., and T. W. Quinn. 1999. Male-driven evolution
among Eoaves? A test of the replicative division hypothesis in
a heterogametic female (ZW) system. J. Mol. Evol. 49:
750–759.
Lawson, L. J., and G. M. Hewitt. 2002. Comparison of
substitution rates in ZFX and ZFY introns of sheep and goat
related species supports the hypothesis of male-biased
mutation rates. J. Mol. Evol. 54:54–61.
Lercher, M. J., and L. D. Hurst. 2002. Human SNP variability
and mutation rate are higher in regions of high recombination.
Trends Genet. 18:337–340.
Lercher, M. J., E. J. B. Williams, and L. D. Hurst. 2001. Local
similarity in evolutionary rates extends over whole chromosomes in human-rodent and mouse-rat comparisons: implications for understanding the mechanistic basis of the male
mutation bias. Mol. Biol. Evol. 18:2032–2039.
Li, W. H., S. J. Yi, and K. Makova. 2002. Male-driven evolution.
Current Opin. Genet. Dev. 12:650–656.
Makova, K. D., and W. H. Li. 2002. Strong male-driven
evolution of DNA sequences in humans and apes. Nature
416:624–626.
Malcom, C. M., G. J. Wyckoff, and B. T. Lahn. 2003. Genic
mutation rates in mammals: local similarity, chromosomal
heterogeneity, and X-versus-autosome disparity. Mol. Biol.
Evol. 20:1633–1641.
Matassi, G., P. M. Sharp, and C. Gautier. 1999. Chromosomal
location effects on gene sequence evolution in mammals.
Curr. Biol. 9:786–791.
McVean, G. A. T., and B. Charlesworth. 1999. A population
genetic model for the evolution of synonymous codon usage:
patterns and predictions. Genet. Res. 74:145.
McVean, G. T., and L. D. Hurst. 1997. Evidence for a selectively
favourable reduction in the mutation rate of the X chromosome. Nature 386:388–392.
Miyata, T., H. Hayashida, K. Kuma, K. Mitsuyasu, and T.
Yasunaga. 1987. Male-driven molecular evolution: a model
Divergence in Autosomal, Z-Linked, and W-Linked Avian Introns 1547
and nucleotide sequence analysis. Cold Spring Harbor Symp.
Quant. Biol. 52:863–867.
Nachman, M. W., and S. L. Crowell. 2000. Estimate of the
mutation rate per nucleotide in humans. Genetics 156:
297–304.
Nanda, I., Z. Shan, M. Schartl et al. (15 co-authors). 1999. 300
million years of conserved synteny between chicken Z and
human chromosome 9. Nat. Genet. 21:258–259.
Nanda, I., T. Haaf, M. Schartl, M. Schmid, and D. W. Burt. 2002.
Comparative mapping of Z-orthologous genes in vertebrates:
implications for the evolution of avian sex chromosomes.
Cytogenet. Genome Res. 99:178–184.
Schmid, M., I. Nanda, M. Guttenbach et al. (34 co-authors).
2000. First report on chicken genes and chromosomes 2000.
Cytogenet. Cell Genet. 90:169–218.
Shimmin, L. C., B. H. J. Chang, and W. H. Li. 1993. Male-driven
evolution of DNA sequences. Nature 362:745–747
Silva, J. C., and A. S. Kondrashov. 2002. Patterns in spontaneous
mutation revealed by human-baboon sequence comparison.
Trends Genet. 18:544–547.
Smith, N. G. C., M. T. Webster, and H. Ellegren. 2002.
Deterministic mutation rate variation in the human genome.
Genome Res. 12:1350–1356.
———. 2003. A low rate of simultaneous double-nucleotide
mutations in primates. Mol. Biol. Evol. 20:47–53.
Sniegowski, P. D., P. J. Gerrish, T. Johnson, and A. Shaver.
2000. The evolution of mutation rates: separating causes from
consequences. Bioessays 22:1057–1066.
Sokal, R. R., and F. J. Rohlf. 1995. Biometry. W.H. Freeman,
New York.
Tamura, K., and M. Nei. 1993. Estimation of the number of
nucleotide substitutions in the control region of mitochondrial
DNA in humans and chimpanzees. Mol. Biol. Evol. 10:
512–526.
Thompson, J. D., D. G. Higgins, and T. J. Gibson. 1994.
ClustalW—improving the sensitivity of progressive multiple
sequence alignment through sequence weighting, positionspecific gap penalties and weight matrix choice. Nucleic
Acids Res. 22:4673–4680.
Waterston, R. H., K. Lindblad-Toh, E. Birney et al. (222 coauthors). 2002. Initial sequencing and comparative analysis of
the mouse genome. Nature 420:520–562.
Williams, E. J. B., and L. D. Hurst. 2000. The proteins of linked
genes evolve at similar rates. Nature 407:900–903.
Wolfe, K. H., P. M. Sharp, and W. H. Li. 1989. Mutation rates
differ among regions of the mammalian genome. Nature
337:283–285.
Yang, Z. 1997. PAML: a program package for phylogenetic
analysis by maximum likelihood. Comput. Appl. Biosci.
13:555–556.
Zhao, Z., and E. Boerwinkle. 2002. Neighboring-nucleotide
effects on single nucleotide polymorphisms: a study of 2.6
million polymorphisms across the human genome. Genome
Res. 12:1679–1686.
Scott Edwards, Associate Editor
Accepted April 21, 2004