Contrasting patterns of nucleotide polymorphism suggest different selective regimes within different parts of the PgiC1 gene in Festuca ovina L.
Li et al. Hereditas
Contrasting patterns of nucleotide polymorphism suggest different selective regimes within different parts of the PgiC1 gene in Festuca ovina L.
Yuan Li 0
Bengt Hansson 0
Lena Ghatnekar 0
Honor C. Prentice 0
0 Department of Biology, Lund University , Lund , Sweden
Background: Phosphoglucose isomerase (PGI, EC 18.104.22.168) is an essential metabolic enzyme in all eukaryotes. An earlier study of the PgiC1 gene, which encodes cytosolic PGI in the grass Festuca ovina L., revealed a marked difference in the levels of nucleotide polymorphism between the 5' and 3' portions of the gene. Methods: In the present study, we characterized the sequence polymorphism in F. ovina PgiC1 in more detail and examined possible explanations for the non-uniform pattern of nucleotide polymorphism across the gene. Results: Our study confirms that the two portions of the PgiC1 gene show substantially different levels of DNA polymorphism and also suggests that the peptide encoded by the 3' portion of PgiC1 is functionally and structurally more important than that encoded by the 5' portion. Although there was some evidence of purifying selection (dN/dS test) on the 5' portion of the gene, the signature of purifying selection was considerably stronger on the 3' portion of the gene (dN/dS and McDonald-Kreitman tests). Several tests support the action of balancing selection within the 5' portion of the gene. Wall's B and Q tests were significant only for the 5' portion of the gene. There were also marked peaks of nucleotide diversity, Tajima's D and the dN/dS ratio at or around a PgiC1 codon site (within the 5' portion of the gene) that a previous study had suggested was subject to positive diversifying selection. Conclusions: Our results suggest that the two portions of the gene have been subject to different selective regimes. Purifying selection appears to have been the main force contributing to the relatively low level of polymorphism within the 3' portion of the sequence. In contrast, it is possible that balancing selection has contributed to the maintenance of the polymorphism within the 5' portion of the gene.
Festuca ovina; Cytosolic phosphoglucose isomerase; PgiC1; Nucleotide polymorphism; Purifying selection
Levels of nucleotide polymorphism have been shown to
vary greatly between different parts of the genome (e.g.
[1–3]), and there may also be variation in the levels of
polymorphism within individual genes (e.g. [4–7]). A
non-uniform pattern of nucleotide polymorphism within
genes may arise if different types of selective pressure
are operating on different regions of the gene (cf. [8, 9]).
Different regions of a gene may code for peptides that
have different structural or functional significances, and
the regions of a gene with more stringent structural
and/or functional requirements are expected to be
subject to stronger purifying selection  and, therefore,
tend to show lower levels of nucleotide polymorphism
than regions that are subject to less stringent constraints
[11, 12]. Positive directional selection may reduce the
levels of local nucleotide polymorphism within a gene
, while balancing selection may increase the levels of
nucleotide polymorphism at, and in the vicinity of, the
selected sites [13, 14]. A classic example of a case where
selection results in non-uniform levels of nucleotide
polymorphism between different gene regions is that of
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
the major histocompatibility complex (MHC) genes.
These genes are crucial for the ability of a vertebrate host’s
immune system to detect evolving pathogens, and it is
frequently suggested that the maintenance of the high levels
of non-synonymous polymorphism in the MHC gene
regions encoding the antigen binding site is a reflection of
pathogen-driven balancing selection [15, 16]. In addition
to selective processes, varying rates of recombination and
mutation, as well as stochastic processes, may also
contribute to non-uniform levels of nucleotide polymorphism
between different regions of a gene (cf. [11, 17]).
The PgiC1 gene, which encodes the cytosolic version
of the metabolic enzyme phosphoglucose isomerase
(PGI, EC 22.214.171.124), in the grass Festuca ovina L.,
represents one of the few reported cases in which the levels
of nucleotide polymorphism differ substantially between
the 3’ and 5’ portions of a gene . PGI catalyses the
second step of glycolysis , and is also known to have
diverse moonlighting functions (see the references in
). The functional PGI enzyme is formed by two
monomers, with each monomer being composed of two
main domains (the “small domain” and the “large
domain”) [21, 22] (Fig. 1-a). High levels of
allozyme/isozyme variation have been frequently reported for PGI in
many different species . Observed differences in
enzyme activity between PGI variants in a number of
species are consistent with observed associations
between the PGI variation and environmental variables or
life-history traits – suggesting that the loci coding for
PGI may be under selection (e.g. [24, 25]).
Festuca ovina is a perennial, tussock-forming and
outcrossing grass, with wind-dispersed pollen and seeds
. The species has a broad ecological amplitude and is
widespread in unfertilized grasslands in northern Europe
(e.g. [26, 27]). The steppe-like “alvar” grasslands on the
Baltic island of Öland (Sweden) are characterized by
a fine-scale edaphic mosaic, with moist and dry, and
high and low pH microhabitats. Earlier studies
suggest that cytosolic PGI isozyme variation in F. ovina
may be involved in fine-scale microhabitat adaptation
on Öland [26, 28, 29]. Analysis of replicated samples
from different alvar sites shows that, despite the fact
that F. ovina is strongly outcrossing, the frequencies
of different cytosolic PGI isozyme electromorphs are
significantly associated with microhabitat variation in
the alvar grasslands and that electromorph
frequencies change in response to experimental habitat
manipulation [26, 28].
In F. ovina, cytosolic PGI is coded for by two loci,
PgiC1 and PgiC2 . The “native” PgiC1 locus is
Fig. 1 The structure of the PgiC1 gene and the 3-D protein structure of its gene product. a PGI dimer, coded for by PgiC1, in F. ovina and homology
modelled in an earlier study . One monomer is shown in yellow. In the other monomer, the large domain is shown in green and the small domain is
shown in dark blue. The three active site residues (equivalent to Lys516, Glu360, and His391 in F. ovina) that are directly involved in the PGI isomerization
reaction are shown in red. The rest of the monomer is represented in light blue. b The gene structure is summarized for the part of the PgiC1 gene
corresponding to the 1 633 bp sequence of the 29 Öland sequences characterized in the present study. Boxes represent the exons and lines represent
introns. The gene structure is scaled according to an earlier published PgiC1 gene sequence (GenBank accession numbers HQ616103). The 5’ and 3’
portions (see Fig. 2) of the PgiC1 gene that are compared in the present study include, respectively, exons 1–12 and exons 13–22
present in all F. ovina individuals, whereas PgiC2 is only
present in some individuals and appears to have been
horizontally acquired from a distantly related grass
genus [29, 31–33]. Earlier analyses of the PgiC1 gene in
F. ovina suggest that two PgiC1 amino acid codon sites
may be affected by positive selection , and SNP
(single nucleotide polymorphism) alleles at these two codon
sites show significant associations with microhabitat
variables in the alvar grasslands (Y Li, B Hansson, M
Lönn, HC Prentice, unpublished results).
The uneven distribution of polymorphic nucleotide
sites along the PgiC1 gene was noted in an earlier study
that included five PgiC1 coding sequences from Skåne, S
Sweden . The longest intron (intron 12, Fig. 1-b) was
used as a demarcation point between the polymorphic 5’
portion of the gene and the, substantially less
polymorphic, 3’ portion of the gene. The aim of the present
study was to investigate the possible evolutionary
mechanisms that may have contributed to the contrasting
levels of nucleotide polymorphism in the two portions of
the PgiC1 gene in F. ovina. We analysed the levels of
PgiC1 nucleotide polymorphism within a larger dataset
(29 PgiC1 cDNA sequences) from F. ovina individuals
collected from the alvar grasslands on Öland, and
carried out a range of tests to assess the relative importance
of different types of selection that may have contributed
to the non-uniform pattern of nucleotide polymorphism
The 3’ portion of PgiC1 in F. ovina encodes the
structurally important large domain and three functionally
essential active site residues (Figs. 1-a and 2). The extensive
inter-monomer interaction between the large domains of
the two monomers is necessary for the formation of a
stable PGI dimer  and the three active site residues
(equivalent to Glu360, His391 and Lys516 in F. ovina)
participate directly in the isomerization reaction of PGI .
If the 3’ portion of PgiC1 codes for products that are
subject to greater structural or functional constraints than the
products of the 5’ portion of the gene, then a relatively
stronger level of purifying selection (i.e. negative
selection) may be expected to have contributed to the
low level of nucleotide polymorphism within the 3’
portion of PgiC1 in F. ovina. The 5’ portion of PgiC1
contains the amino acid codon sites 173 and 200
(Fig. 2). If these sites are under balancing selection
(i.e. positive intraspecific diversifying selection), as
suggested by , then balancing selection targeting
the two sites might be expected to contribute to the
high level of nucleotide polymorphism within the 5’
portion of PgiC1. The present study provides support
for the prediction that there is a stronger purifying
selection on the 3’ portion than on the 5’ portion of
PgiC1, and suggests that there is balancing selection
on the 5’ portion of the gene.
Fig. 2 Sliding window analyses of nucleotide diversity (πT), Tajima’s D
and ω. The ticks on the x axis represent the boundary of each analysed
PgiC1 exon within the PgiC1 coding sequence. In F. ovina, PgiC1 exons
5–12 encode the small domain of a PGI monomer while exons 13–21
encode the large domain. The two dots on the x axis show the locations
of the two PgiC1 codon sites (173 and 200) that were earlier identified as
being candidates for positive diversifying selection . The three stars
on the x axis represent the three active site residues (equivalent to
Lys516, Glu360, and His391 in F. ovina) that are directly involved in the
PGI isomerization reaction . The grey dotted vertical line shows the
location of intron 12, which is used as the demarcation point for
defining the 5’ and 3’ portions of PgiC1 sequence. The brown dotted
vertical line indicates codon site 200 which is under positive diversifying
selection and located at or near to peaks of πT, Tajima’s D and ω
Plant material and sequences
The present study examined variation within 29 PgiC1
cDNA sequences (GenBank accession numbers
KF487737KF487765, ) from Öland populations of F. ovina. The
sequences were derived from 15 individuals that were
chosen to represent the five cytosolic PGI electromorphs
(EMs 1, 2, 4, 5 and 6) that occur most frequently within
populations of F. ovina on Öland [26, 28, 29] – with a
particular focus on the two most common electromorphs, EM
1 and EM 2 . The sequences were obtained by, first,
synthesizing the total cDNA from the total RNA of each
studied F. ovina individual . The PgiC1 cDNA was then
PCR-amplified from the synthesized total cDNA, and the
amplified PgiC1 cDNA was cloned and sequenced .
Two PgiC1 cDNA alleles were acquired from each
(diploid) individual, giving a total of 30 alleles from the 15
studied individuals . However, one of the alleles
(GenBank accession number KF487766) contained an aberrant
(113 bp) insertion  and was excluded from the analyses
in the present study, unless specified.
Each of the 29 analysed PgiC1 cDNA sequences covers
96% (1 633 bp) of the full-length (1701 bp, excluding
stop codon) PgiC1 coding sequence, and ranges from
exon 1 to exon 22 (Fig. 1-b). For comparative purposes,
we also downloaded the five Skåne F. ovina PgiC1
coding sequences (GenBank accession numbers
DQ225731-DQ225735) which were examined in the
earlier study that noted the difference in the levels of
polymorphism between the 5’ and 3’ portions of PgiC1
. These five Skåne sequences represent the common
cytosolic PGI isozyme electromorphs 1, 2 and 6, as well
as the rare electromorph 8 [26, 28]. Each of the five
sequences covers 1 182 bp, out of the full-length PgiC1
coding sequence , and ranges from exons 5 to 11
and from exons 13 to 21.
Analysis of sequence data
The number of polymorphic sites (S), nucleotide diversity
(π; ), Watterson’s estimator of the population
mutation rate (θW; ), and the number of haplotypes (Nh)
were calculated using DnaSP v. 5.10.01 . All the
statistics were calculated, separately, for the two portions of the
five Skåne PgiC1 sequences (5’: exons 5-11; 3’: exons
1321) and of the 29 Öland (5’: exons 1-12; 3’: exons 13-22)
PgiC1 sequences. Total nucleotide diversity (πT) was
estimated separately for each of the 22 studied PgiC1
exons for the 29 Öland PgiC1 sequences. Sliding window
analysis of πT was also carried out for the 29 Öland PgiC1
sequences using DnaSP v. 5.10.01 (window length: 100 bp;
step size: 10 bp). The remaining analyses only considered
the 29 Öland PgiC1 sequences, unless specified.
The level of recombination was estimated (as the
minimum number of recombination events, RM, using the
method of Hudson RR and Kaplan NL  as implemented
in DnaSP v. 5.10.01) for each of the two PgiC1 gene
portions in the 29 Öland sequences. The level of
recombination was also estimated as the population recombination
rate (ρ = 4Ner, where Ne is the effective population size and
r is the per-generation per-site recombination rate ),
using the program omegaMap . We used the same
procedure as in  to run omegaMap, but used a sliding
window of 10 codons to estimate ρ in the present study. The
level of linkage disequilibrium (LD) within PgiC1 was
estimated using r2 statistics , calculated between all pairs of
polymorphic sites (excluding a single site that segregates
with more than two nucleotides ), using Haploview v.
4.2 . The genotypes of the 15 studied Öland individuals
, at each of the analyzed polymorphic sites, were used
as input to the Haploview analyses. In order to generate a
complete set of genotype data for the 15 individuals, as
required for the Haploview analyses, we included the
additional sequence (GenBank accession number KF487766) –
acquired from the 15 F. ovina individuals but containing an
aberrant insertion that may have resulted from incomplete
splicing of the PgiC1 precursor mRNA . This insertion
was removed for the Haploview analyses.
The dN/dS ratio (ω) (dN = non-synonymous
substitution rate; dS = synonymous substitution rate) was
estimated, together with ρ (using omegaMap), for each
amino acid codon translated from the PgiC1 sequence.
The estimated ω value was used to examine whether
purifying (i.e. negative selection, ω < 1) or balancing (i.e.
positive intraspecific diversifying) selection (ω > 1) may
have contributed to the amounts and patterning of
sequence variation within and between the two gene
portions for the 29 studied PgiC1 sequences (cf. ).
Sliding window analysis of ω was also carried out
(manually, on the basis of the results from OmegaMap)
with a window length of 99 and a step size of 12.
Neutrality tests, including the
Hudson-KreitmanAguadé (HKA) test , Tajima’s D test , Fay and
Wu’s H test , MacDonald and Kreitman’s (MK) test
 and Wall’s B and Q tests  were also used to
examine whether selection may have contributed to the
amounts and patterning of sequence variation within each
of the two PgiC1 gene portions in the 29 sequences. All
the neutrality tests were carried out using DnaSP v.
5.10.01. The significances of the Tajima’s D, Fay and Wu’s
H, and Wall’s B and Q were conservatively estimated
(without allowing for recombination), using 10 000
coalescent simulations and on the basis of the observed number
of segregating sites. A single PgiC cDNA sequence from F.
altissima (GenBank accession number DQ225740),
encoding cytosolic PGI, was used as the outgroup for the
HKA test, Fay and Wu’s H test and the MK test. We used
the HKA test to compare the 5’- and 3’-portions of PgiC1
in terms of intraspecific polymorphism (within F. ovina)
and interspecific divergence (between F. ovina and F.
altissima). In the MK test, we compared the ratio of DN/DS
(DN or DS = the number of fixed non-synonymous [for
DN] or synonymous [for DS] substitutions per gene
between F. ovina and F. altissima), with the ratio of PN/PS
(PN or PS = the number of non-synonymous [for PN] or
synonymous [for PS] polymorphic sites per gene within F.
ovina). The degree of synonymous divergence (KS [JC]:
Jukes-Cantor corrected number of synonymous
substitutions per synonymous site) between the outgroup PgiC
sequence and the 29 F. ovina PgiC1 sequences was 0.240.
Sliding window analyses were also carried out,
respectively, for Tajima’s D, ω, Fay and Wu’s H, as well as for Ka/
Ks (the number of nonsynonymous substitutions per
nonsynonymous site/the number of sysnonymous
substitutions per synonymous site), with a window length of
100 bp and a step size of 10 bp using DnaSP v. 5.10.01.
Analysis of the evolutionary conservation of amino acid
The degree of evolutionary conservation at each of the
respective PGI amino acid sites corresponding to the
PgiC1 translated amino acid sites was estimated, on the
basis of the phylogenetic relationships among a large set
of homologous sequences, from a wide range of different
species, using the online application ConSurf Server
. The database UniRef90  was searched for
sequences that were homologous with the F. ovina PgiC1
input sequence, using CSI-BLAST  (cutoff E-value =
0.0001; number of interactions = 3; maximum homologs
to collect = 150). Within CSI-BLAST, redundant
sequences were filtered out by clustering blast hits with a
sequence identity of 95% or more and only using one
representative of each cluster in the analysis. BLAST hits
that shared a sequence identity of less than 35% with the
input sequence were ignored. A multiple-species
alignment (Additional file 1: File S1) of the acquired
homologous sequences was constructed using MAFFT [51, 52],
and this alignment was then used to build a phylogenetic
tree using the neighbour-joining algorithm as
implemented in the Rate4Site program . The level of
evolutionary conservation was then estimated, as a
conservation score for each amino acid site using an
empirical Bayesian algorithm  implemented in the
ConSurf Server. The lower the conservation score, the
more evolutionarily conserved are the amino acid
residues at that specific site. The translated amino acid
sequence from a PgiC1 sequence (GenBank accession
number KF487738), representing the most common
PgiC1 sequence in F. ovina, was used as the input to the
The analyses of the five Skåne PgiC1 coding sequences
confirmed the earlier finding  that the 5’ portion of the
gene (L [sequence length] = 570, S = 30, Nh = 5, π = 0.025,
θW = 0.025) was considerably more polymorphic than the
3’ portion (L = 612, S = 3, Nh = 4, π = 0.002, θW = 0.002).
Also in agreement with the observed pattern of sequence
polymorphism within the five Skåne PgiC1 sequences, the
analyses of the 29 Öland PgiC1 cDNA sequences showed
that the 5’ portion of the sequence (πT = 0.019, θW = 0.020)
was substantially more polymorphic than the 3’ portion of
the sequence (πT = 0.004, θW = 0.007) (Fig. 2, Table 1).
There was a significant difference between the πT values
for each of the 12 exons (exons 1–12) within the 5’ portion
of the PgiC1 gene in the 29 sequences, and those for each
of the 10 exons (exons 13–22) within the 3’ portion of the
29 sequences (Wilcoxon rank sum test; W = 96, P = 0.019,
Additional file 2: Table S1). The sliding window analyses of
πT showed that the PgiC1 codon site 200 (under positive
diversifying selection ) was within the highest peak of
πT at exon 8 within the 5’ portion of the gene (Fig. 2).
Recombination and linkage disequilibrium
The analyses of the 29 PgiC1 sequences from Öland
revealed a high overall level of recombination (RM = 22; ρ
= 0.217, Additional file 3: Table S2). The level of
recombination in the highly polymorphic 5’ portion (RM = 20;
ρ = 0.383) was substantially higher than that for the less
variable 3’ portion of the gene (RM = 1; ρ = 0.026) (Table 1
and Fig. 3_a). However, the matrix of r2 values (Fig. 3_b)
shows that there is a low level of LD throughout the
entire PgiC1 gene, with no “strong LD” blocks (cf. ).
The ω and neutrality tests
The fact that the overall ω (dN/dS ratio) value for the
entire PgiC1 sequence was substantially lower than 1
(mean ω over all the studied amino acid codons = 0.209,
Additional file 3: Table S2) indicates that purifying
selection has acted on the overall sequence. Purifying
selection is also indicated for both the 5’ portion (291
amino acid codons; average ω = 0.280) and the 3’ portion
(253 amino acid codons; average ω = 0.128) of the
sequence. The fact that codons within the 3’ portion of the
PgiC1 sequence had a significantly lower ω than those in
the 5’ portion (Wilcoxon rank sum test; W = 42229, P =
0.003) suggests that the 3’ portion may be under
stronger purifying selection than the 5’ portion. The sliding
window analyses of ω showed a marked plateau of ω
values (between exons 8-9 within the 5’ portion) around
the PgiC1 codon site 200 (Fig. 2), that a previous study
had suggested was subject to positive diversifying
selection . There were 40 segregating sites out of the total
of 570 nucleotide sites included in the analysis of the 5’
portion, whereas there were only 14 segregating sites out
of 612 sites in the 3’ portion (Additional file 4: Table S3).
The levels of interspecific DNA divergence between the
3’ portion 761 20 15 4
Table 1 Analyses of the 3’ and 5’ portions of 29 PgiC1 sequences from Öland F. ovina
Nh π (×10−3) θW (×10−3) RM ρ
−1.363 n.s. −1.768 n.s.
0.000 n.s. 0.000 n.s.
The table shows the lengths of the 5’ and 3’ portions of the sequence (L), the number of segregating sites (S), the number of haplotypes (Nh), the total nucleotide
diversity (π), the total Watterson’s estimator of population mutation rate (per site) (θW), the minimum number of recombination events (RM), the population
recombination parameter (ρ) (per site), the average ω ratio, Tajima’s D, Fay & Wu’s H, and Wall’s B and Q, as well as the mean conservation score (the smaller the
value, the more conserved) estimated using the online ConSurf Server. Because parts of the coding sequence are not available for the outgroup sequence from
F. altissima, the 5’ and 3’ portions of F. ovina PgiC1 that were considered in the Fay and Wu’s H test span, respectively, coding sequence nucleotide positions
259-828 & 919-1530
*0.01 < P < 0.05; n.s. non-significant
Fig. 3 Levels of recombination and linkage disequilibrium (LD) within the F. ovina PgiC1 sequence. a Population recombination rate (ρ) across PgiC1.
The heavy line represents the mean value of ρ, while the thin lines represent the upper and lower 95% HPD (highest posterior density) interval bounds
for the posterior distribution of ρ. b LD matrix for PgiC1. The level of LD is measured by the pairwise correlation coefficient r2 values  for all the
polymorphic nucleotide sites (except for one that segregates into more than two nucleotides ). Shades of grey indicate the r2 values, ranging from
r2 = 0 (white) to r2 = 1 (black). The proportional spacing of the polymorphic sites, which is scaled according to an earlier published PgiC1 gene
sequence (GenBank accession number HQ616103), is indicated by black vertical lines on a white horizontal bar (shown above the LD matrix)
two gene portions were similar: 29.6 nucleotide
differences among 570 sites for the 5’ portion, and 35.8
nucleotide differences among 612 sites for the 3’ portion
(Additional file 4: Table S3). However the HKA test
didn’t reject the null neutral model (P = 0.064,
Additional file 4: Table S3).
Wall’s B and Q values were significant for the 5’
portion of the PgiC1 sequence (Table 1), indicating an
excess of LD between adjacent segregating sites, which
may reflect balancing selection (cf. [47, 56]). Wall’s B
and Q values were non-significant for the 3’portion of
the PgiC1 sequence (Table 1). There was a negative, but
non-significant (P = 0.064, Table 1) Tajima’s D for the 3’
portion of the PgiC1 sequence, while the Tajima’s D for
the 5’ portion was near zero (D = -0.195, Table 1). The
sliding window analyses of the Tajima’s D showed that
the highest peak of D was located at the PgiC1 codon
site 200 (exon 8) (Fig. 2) which was identified as a
potential target of positive diversifying selection in an
earlier study . The D value at this peak (D = 1.439)
was near-significant (P = 0.060; post hoc significance test
without correction for multiple tests). The Fay &
Wu’s H values were non-significant for both the 5’ (P
= 0.669) and the 3’ (P = 0.148) portions of the PgiC1
sequence (Table 1). The sliding window analysis of
Fay and Wu’s H showed that the deepest valley of H
was at exon 16 (within the 3’ portion), near which a
striking valley of Tajima’s D was also observed
(Additional file 5: Figure S1). Both D and H had
negative values in these valleys (Additional file 5:
Figure S1), and according to the post hoc tests of
significance (not subject to multiple test correction),
the H was significant (H = -1.862, P = 0.006), while D
was near-significant (D = -1.509, P = 0.095).
The MK test rejected the neutral null model for the 3’
portion of the PgiC1 sequence (Fisher’s exact test, P =
0.018). The significant MK test reflects a lower DN/DS ratio
(0.064) relative to the PN/PS ratio (0.556), which is
consistent with purifying selection within this portion of the gene
(Table 2). The MK test for the 5’ portion of the sequence
was non-significant (DN/DS = 0.235; PN/PS = 0.323; Fisher’s
exact test, P = 0.755, Table 2).
Degree of amino acid site conservation
The PGI amino acid sites showed a tendency to be less
evolutionarily conserved within the region
corresponding to the 5’ portion of the translated PgiC1 amino acid
sequence (291 amino acid sites; mean conservation
score = 0.105) than those corresponding to the 3’ portion
of the translated PgiC1 amino acid sequence (253 amino
acid sites; mean conservation score = -0.121) (Wilcoxon
rank sum test; W = 39886, P = 0.093) (Table 1,
Additional file 6: Table S4).
Analyses of the 29 Öland F. ovina PgiC1 cDNA
sequences in the present study, together with the analyses
of the five Skåne PgiC1 sequences, shows that the
nucleotide polymorphism is not evenly distributed
within the PgiC1 gene (Fig. 2). The 5’ portion of the PgiC1
sequence is substantially more polymorphic than the 3’
portion, and our analyses suggest that the difference in the
level of polymorphism may have resulted from different
selective regimes in the two portions of the gene.
Which evolutionary mechanisms may have contributed to
the relatively low level of nucleotide polymorphism
within the 3’ portion of the PgiC1 sequence?
The parts of a protein that are more important for the
stability and/or function of an enzyme are likely to be
subject to stronger purifying selection  and,
therefore, tend to exhibit a lower level of intraspecific
polymorphism than the parts of the protein with less
stringent functional and structural requirement [11, 12].
In F. ovina, the 3’ portion of the PgiC1 sequence
encodes a peptide that includes the structurally important
large domain of the PGI monomer  and the three
most conserved, functionally essential, active site
residues . The fact that the peptide translated from the
3’ portion of PgiC1 contains important components of
the 3-D structure of PGI suggests that this peptide may
have a greater overall importance for the function of
PGI than the peptide translated from the 5’ portion of
PgiC1. The suggested difference in the functional and
structural significance of the translated peptides between
the two portions of PgiC1 is supported by the estimated
amino acid conservation scores in the present study,
which show that the PGI amino acid sites corresponding
to the 3’ portion of the PgiC1 sequence tend to be
evolutionarily more conserved than those of the 5’ portion in
a wide range of species (cf. ).
If the peptide translated from the 3’ portion of PgiC1 is
more important for the function of the PGI enzyme than
the peptide from the 5’ portion, then the 3’ portion of the
gene may be expected to be under stronger purifying
selection than the 5’ portion (cf. [10, 12]). In line with this
expectation, the average ω value for the 3’ portion of PgiC1
was considerably lower than that for the 5’ portion. The
average values for both portions were much lower than 1
(suggesting purifying selection ). The fact that the value
of Tajima’s D was more strongly negative for the 3’ portion
(D = -1.363; P = 0.064) than for the 5’ portion (D = -0.195;
P = 0.484) of the PgiC1 sequence, is also consistent with
the 3’ portion being under stronger purifying selection than
the 5’ portion of the sequence (cf. ). The significant
MK test result for the 3’ portion and the non-significance
of the test for the 5’ portion of the PgiC1 sequence may,
again, suggest that the 3’ portion is under stronger
purifying selection than the 5’ portion of the sequence. The
significant MK test for the 3’ portion of PgiC1, with a lower
ratio of fixed non-synonymous/synonymous substitutions
between species (DN/DS = 0.064) than the ratio of
nonsynonymous/synonymous polymorphism within species
(PN/PS = 0.556), suggests purifying selection, where the
within-species nonsynonymous polymorphism that is
maintained in selection–mutation balance consists mainly
of weakly deleterious mutations .
Because the PGI protein structural elements are closely
similar in a wide range of organisms (e.g. [21, 35, 59]), the
functional and structural significance and the pattern of
Table 2 MacDonald-Kreitman tests for the 3’ and 5’ portions of F. ovina PgiC1
Because parts of the coding sequence are not available for the outgroup sequence from F. altissima, the 5’ and 3’ portions of F. ovina PgiC1 that were considered
in the test span, respectively, coding sequence nucleotide positions 259-828 & 919-1530
aThe number of fixed substitutions (per gene) between F. ovina and the outgroup (the number of nucleotide sites that are fixed for different nucleotides in F.
ovina and the outgroup)
bThe number of nucleotide polymorphic sites (per gene) within F. ovina
*0.01 < P < 0.05; n.s. non-significant
nucleotide polymorphism within the Pgi gene might be
expected to be similar between F. ovina and other species.
However, at present, only a few studies of Pgi have
investigated gene-wide patterns of nucleotide polymorphism.
Two of these studies, on the butterflies Melitaea cinxia
 and Colias eurytheme [61, 62], reveal a nearly
uniformly high level of nucleotide polymorphism across the
entire Pgi gene. The pattern of nucleotide polymorphism
in these two species was interpreted in terms of balancing
selection (targeting a few amino acid sites located within
the large domain) and moderate to high levels of LD
within the entire Pgi gene [60, 61]. A high level of
synonymous polymorphism was observed regionally around a
nonsynonynous mutation within the 5’ portion of the PgiC
gene in Arabidopsis thaliana, and interpreted in terms of
balancing selection and an overall low level of
In contrast to the Pgi genes of the three species
mentioned above, the F. ovina PgiC1 gene showed a high
level of recombination (RM = 22): M. cinxia had a RM of
6 , whereas C. eurytheme RM = 11  and A.
thaliana showed no clear evidence of recombination ).
The high estimated recombination value is consistent
with the fact that F. ovina is a highly outcrossing species
, and may indicate that different parts of the
sequence could have evolved (at least to some extent)
independently, resulting in a non-uniform pattern of
nucleotide polymorphism across the sequence. Most of
the identified recombination is within the 5’ portion of
the PgiC1 sequence, while the 3’ portion of the sequence
shows limited recombination. However, the relatively
low level of recombination detected for the 3’ portion of
the sequence may be a consequence of purifying
selection having removed variation at both the sites under
selection and linked neutral sites (cf. ) – thereby
removing the molecular signatures of recombination and
lowering the numbers of identified recombination events
(cf. ). The hypothesis that purifying selection may
have removed the detectable signatures of
recombination within the 3’ portion of PgiC1 agrees with the
PgiC1 LD matrix, where a uniformly low level of LD is
observed along the entire PgiC1 cDNA sequence.
In addition to purifying selection, a selective sweep may
also have contributed to the low level of nucleotide
diversity within the 3’ portion of the gene: the near, but
nonsignificant (P = 0.064), result of the HKA test suggests that
variation-reducing selective forces may be acting on the
PgiC1 3’ portion and/or variation-increasing forces acting
on the 5’ portion (cf. ). The sliding window analyses
revealed striking valleys of both Fay and Wu’s H and
Tajima’s D at exon 16 (within the 3’ portion) (Additional
file 5: Figure S1). In these valleys, the Fay and Wu’s H is
significantly negative (H = -1.862; P = 0.006) and the
Tajima’s D is also near-significantly negative (D = -1.509;
P = 0.095). These negative values reflect a high-frequency
of derived SNPs (around the valleys), suggesting a selective
sweep (cf. ). A nearby shallow valley of total nucleotide
diversity (Fig. 2) is also suggestive of a selective sweep .
The valleys of D and H at exon 16 are close to active site
residue His391 (Additional file 5: Figure S1). Sequence
patterns that are identified as the signatures of selection in
neutrality tests (e.g. Tajima’s D and Fay and Wu’s H) may
also result from factors such as population size changes or
reflect population structure [66–68]. In the case of the
highly outcrossing populations of F. ovina on Öland,
population structure is unlikely to be a confounding factor
in the neutrality tests. However, because possible
confounding effects resulting from changes in population size
cannot be excluded, the selective sweep suggested by the
H and D tests should be interpreted with caution.
Which evolutionary mechanisms may have contributed to
the relatively high level of nucleotide polymorphism
within the 5’ portion of the PgiC1 sequence?
An earlier study  identified two F. ovina PgiC1
codon sites (sites 173 and 200) as candidate targets of
balancing selection (i.e. positive intraspecific diversifying
selection) with a considerably stronger signal of selection
for site 200 than for site 173 . The sliding window
analyses in the present study support the results of the
earlier study and reveal a marked plateau of ω around
the selected site 200 (but no peak associated with site
173) (Fig. 2). Protein structure modelling suggests that
the translated amino acid polymorphism at these two
PgiC1 sites may affect either the interaction between the
two monomers, or the domain-domain packing of the
encoded PGI enzyme and, thus, influence the
biochemical properties of the cytosolic PGI enzyme in F. ovina
. Biochemical studies in humans have shown that
mutations at a few amino acid sites, which have similar
3-D structural locations to the two selected amino acid
sites in F. ovina, significantly affect the activity of the
PGI enzyme [69, 70].
Within F. ovina PgiC1, both codon sites 173 and 200,
which were previously identified as candidates for
balancing selection , are located within the 5’ portion of
the sequence (Fig. 2). The significant results from the
Wall’s B and Q tests (Table 1) support the suggestion
that there has been balancing selection on the 5’ portion
of the PgiC1 sequence in F. ovina (cf. ). In addition
to the significant B and Q tests, signals of balancing
selection were also detected at the putative selected site
200. The highest peaks of, respectively, positive Tajima’s
D and total nucleotide diversity were observed at or
around codon site 200 in the sliding window analyses
(Fig. 2), and these peaks are a typical signature of
balancing selection (cf. [13, 14]). No marked peak or plateau
for polymorphism or for Tajima’s D was observed for the
second putative selected site (site 173) in the present
study (Fig. 2), in agreement with the previous study 
which showed a weaker signal of balancing selection for
site 173 than for site 200.
The PgiC1 gene in F. ovina represents one of the few
reported cases in which the levels of nucleotide
polymorphism differ substantially between the 5’ and 3’
portions of a gene. The present study suggests that the
contrasting levels of nucleotide polymorphism between
the two portions of PgiC1 may have resulted from
different selective regimes in the two gene portions. Relatively
strong purifying selection appears to have reduced the
level of polymorphism within the 3’ portion, whereas
balancing selection may have contributed to the maintenance
of the polymorphism in the 5’ portion of the sequence. A
high overall level of recombination and a low level of LD
within PgiC1 may have allowed partially independent
selection and evolution within the two portions of the gene.
Additional file 1: File S1. The aligned multiple-species homologous
amino acid sequences acquired from the Consurf Server. (TXT 96 kb)
Additional file 2: Table S1. The total nucleotide diversity (πT) for each
studied PgiC1 exon. (DOCX 47 kb)
Additional file 3: Table S2. Estimates of ω and ρ (made with
omegaMap) for each analyzed PgiC1 codon. (XLS 119 kb)
Additional file 4: Table S3. Comparison (Hudson-Kreitman-Aguadé
test) between the 5’ and 3’ portions of the sequenced F. ovina PgiC1 in
terms of level of polymorphism and level of divergence from the
outgroup F. altissima. (DOC 33 kb)
Additional file 5: Figure S1. Results for the sliding window analyses of,
respectively, Tajima’s D, Fay and Wu’s H, and Ka/Ks. The ticks on the x axis
represent the boundary of each analysed PgiC1 exon within the PgiC1
coding sequence. In F. ovina, PgiC1 exons 5–12 encode the small domain of
a PGI monomer while exons 13–21 encode the large domain. The three
stars on the x axis represent the three active site residues (equivalent to
Lys516, Glu360, and His391 in F. ovina) that are directly involved in the PGI
isomerization reaction . The dotted vertical line highlights a position
where both D and H have marked valleys. (TIF 1634 kb)
Additional file 6: Table S4. The estimated (normalized) conservation
scores for each PGI amino acid site. (XLS 49 kb)
HKA: Hudson-Kreitman-Aguadé test; HPD: Highest posterior density;
LD: Linkage disequilibrium; MHC: The major histocompatibility complex; MK
test: MacDonald and Kreitman’s test; PGI: Phosphoglucose isomerase;
SNP: Single nucleotide polymorphism
The study was supported by grant 621-2008-5617 (to H.C.P and Anders Tunlid)
from the Swedish Research Council. Bengt Hansson also acknowledges support
from the Swedish Research Council (grant 621-2014-5222). The funders had no
role in study design, data collection and analysis, decision to publish, or
preparation of the manuscript.
Availability of data and materials
All data generated or analyzed during this study are either available in the
GenBank database (GenBank accession numbers DQ225731-DQ225735 &
KF487737-KF487765; https://www.ncbi.nlm.nih.gov/nucleotide) or included in
this published article and its additional files.
YL conceived the study with input from BH, HCP and LG. YL was responsible
for the data collection and data analyses. YL wrote the paper with input
from BH and HCP. All authors read and approved the final manuscript.
1. Huang X , Kurata N , Wei X , Wang Z-X , Wang A , Zhao Q , et al. A map of rice genome variation reveals the origin of cultivated rice . Nature . 2012 ; 490 : 497 - 501 .
2. Hufford MB , Xu X , van Heerwaarden J , Pyhäjärvi T , Chia J-M , Cartwright RA , et al. Comparative population genomics of maize domestication and improvement . Nat Genet . 2012 ; 44 : 808 - 11 .
3. Jiao Y , Zhao H , Ren L , Song W , Zeng B , Guo J , et al. Genome-wide genetic changes during modern breeding of maize . Nat Genet . 2012 ; 44 : 812 - 5 .
4. Le Corre V , Roux F , Reboud X. DNA polymorphism at the FRIGIDA gene in Arabidopsis thaliana: extensive nonsynonymous variation is consistent with local selection for flowering time . Mol Biol Evol . 2002 ; 19 : 1261 - 71 .
5. Moore RC , Grant SR , Purugganan MD . Molecular population genetics of redundant floral-regulatory genes in Arabidopsis thaliana . Mol Biol Evol . 2005 ; 22 : 91 - 103 .
6. Hasselmann M , Beye M. Signatures of selection among sex-determining alleles of the honey bee . Proc Natl Acad Sci U S A . 2004 ; 101 : 4888 - 93 .
7. Ding Z , Wang C , Chen S , Yu S. Diversity and selective sweep in the OsAMT1; 1 genomic region of rice . BMC Evol Biol . 2011 ; 11 : 61 .
8. Charlesworth B. Effective population size and patterns of molecular evolution and variation . Nat Rev Genet . 2009 ; 10 : 195 - 205 .
9. Cutter AD , Payseur BA . Genomic signatures of selection at linked sites: unifying the disparity among species . Nat Rev Genet . 2013 ; 14 : 262 - 74 .
10. Tourasse NJ , Li W-H. Selective constraints, amino acid composition, and the rate of protein evolution . Mol Biol Evol . 2000 ; 17 : 656 - 64 .
11. Hudson RR , Kreitman M , Aguadé M. A test of neutral molecular evolution based on nucleotide data . Genetics . 1987 ; 116 : 153 - 9 .
12. Kimura M. The neutral theory of molecular evolution . Cambridge : Cambridge University Press ; 1983 .
13. Weedall GD , Conway DJ . Detecting signatures of balancing selection to identify targets of anti-parasite immunity . Trends Parasitol . 2010 ; 26 : 363 - 9 .
14. Charlesworth D. Balancing selection and its effects on sequences in nearby genome regions . PLoS Genet . 2006 ; 2 : e64 .
15. Lamaze FC , Pavey SA , Normandeau E , Roy G , Garant D , Bernatchez L. Neutral and selective processes shape MHC gene diversity and expression in stocked brook charr populations (Salvelinus fontinalis) . Mol Ecol . 2014 ; 23 : 1730 - 48 .
16. Bernatchez L , Landry C. MHC studies in nonmodel vertebrates: what have we learned about natural selection in 15 years ? J Evol Biol . 2003 ; 16 : 363 - 77 .
17. Wright SI , Foxe JP , DeRose-Wilson L , Kawabe A , Looseley M , Gaut BS , et al. Testing for effects of recombination rate on nucleotide diversity in natural populations of Arabidopsis lyrata . Genetics . 2006 ; 174 : 1421 - 30 .
18. Ghatnekar L. Genetic analysis of cytosolic PGI in Festuca ovina . PhD thesis . Lund University, 2003 .
19. Gillespie JH . The causes of molecular evolution . New York : Oxford University Press ; 1991 .
20. Marden JH . Nature's inordinate fondness for metabolic enzymes: why metabolic enzyme loci are so frequently targets of selection . Mol Ecol . 2013 ; 22 : 5743 - 64 .
21. Shaw PJ , Muirhead H. Crystallographic structure analysis of glucose 6- phosphate isomerase at 3.5 Å resolution . J Mol Biol . 1977 ; 109 : 475 - 85 .
22. Wang B , Watt WB , Aakre C , Hawthorne N. Emergence of complex haplotypes from microevolutionary variation in sequence and structure of Colias phosphoglucose isomerase . J Mol Evol . 2009 ; 68 : 433 - 47 .
23. Riddoch BJ . The adaptive significance of electrophoretic mobility in phosphoglucose isomerase (PGI) . Biol J Linn Soc Lond . 1993 ; 50 : 1 - 17 .
24. Dahlhoff EP , Rank NE . Functional and physiological consequences of genetic variation at phosphoglucose isomerase: Heat shock protein expression is related to enzyme genotype in a montane beetle . Proc Natl Acad Sci U S A . 2000 ; 97 : 10056 - 61 .
25. Watt WB . Eggs, enzymes, and evolution: natural genetic variants change insect fecundity . Proc Natl Acad Sci U S A . 1992 ; 89 : 10608 - 12 .
26. Prentice HC , Lönn M , Lefkovitch LP , Runyeon H. Associations between allele frequencies in Festuca ovina and habitat variation in the alvar grasslands on the Baltic island of Öland . J Ecol . 1995 ; 83 : 391 - 402 .
27. Cope T , Gray A. Grasses of the British Isles . London: Botanical Society of the British Isles ; 2009 .
28. Prentice HC , Lönn M , Lager H , Rosén E , van der Maarel E. Changes in allozyme frequencies in Festuca ovina populations after a 9-year nutrient/ water experiment . J Ecol . 2000 ; 88 : 331 - 47 .
29. Prentice HC , Li Y , Lönn M , Tunlid A , Ghatnekar L. A horizontally transferred nuclear gene is associated with microhabitat variation in a natural plant population . Proc R Soc Lond Ser B Biol Sci . 2015 ; 282 : 20152453 .
30. Ghatnekar L. A polymorphic duplicated locus for cytosolic PGI segregating in sheep's fescue (Festuca ovina L.). Heredity (Edinb) . 1999 ; 83 : 451 - 9 .
31. Vallenback P , Jaarola M , Ghatnekar L , Bengtsson BO . Origin and timing of the horizontal transfer of a PgiC gene from Poa to Festuca ovina . Mol Phylogenet Evol . 2008 ; 46 : 890 - 6 .
32. Vallenback P , Ghatnekar L , Bengtsson BO . Structure of the natural transgene PgiC2 in the common grass Festuca ovina . Plos One . 2010 ; 5 : e13529 .
33. Vallenback P , Bengtsson BO , Ghatnekar L. Geographic and molecular variation in a natural plant transgene . Genetica . 2010 ; 138 : 355 - 62 .
34. Li Y , Canbäck B , Johansson T , Tunlid A , Prentice HC . Evidence for positive selection within the PgiC1 locus in the grass Festuca ovina . Plos One . 2015 ; 10 :e0125831.
35. Jeffery CJ , Hardré R , Salmon L. Crystal structure of rabbit phosphoglucose isomerase complexed with 5-phospho-D-arabinonate identifies the role of Glu357 in catalysis . Biochemistry . 2001 ; 40 : 1560 - 6 .
36. Nei M. Molecular evolutionary genetics . New York : Columbia University Press ; 1987 .
37. Watterson GA . On the number of segregating sites in genetical models without recombination . Theor Popul Biol . 1975 ; 7 : 256 - 76 .
38. Librado P , Rozas J. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data . Bioinformatics . 2009 ; 25 : 1451 - 2 .
39. Hudson RR , Kaplan NL . Statistical properties of the number of recombination events in the history of a sample of DNA sequences . Genetics . 1985 ; 111 : 147 - 64 .
40. Stumpf MPH , McVean GAT . Estimating recombination rates from population-genetic data . Nat Rev Genet . 2003 ; 4 : 959 - 68 .
41. Wilson DJ , McVean G . Estimating diversifying selection and functional constraint in the presence of recombination . Genetics . 2006 ; 172 : 1411 - 25 .
42. Hill WG , Robertson A. Linkage disequilibrium in finite populations . Theor Appl Genet . 1968 ; 38 : 226 - 31 .
43. Barrett JC , Fry B , Maller J , Daly MJ . Haploview: analysis and visualization of LD and haplotype maps . Bioinformatics . 2005 ; 21 : 263 - 5 .
44. Tajima F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism . Genetics . 1989 ; 123 : 585 - 95 .
45. Fay JC , Wu CI . Hitchhiking under positive Darwinian selection . Genetics . 2000 ; 155 : 1405 - 13 .
46. McDonald JH , Kreitman M. Adaptive protein evolution at the Adh locus in Drosophila . Nature. 1991 ; 351 : 652 - 4 .
47. Wall JD . Recombination and the power of statistical tests of neutrality . Genet Res . 1999 ; 74 : 65 - 79 .
48. Ashkenazy H , Erez E , Martz E , Pupko T , Ben-Tal N. ConSurf 2010: calculating evolutionary conservation in sequence and structure of proteins and nucleic acids . Nucleic Acids Res . 2010 ; 38 : W529 - 33 .
49. Suzek BE , Wang Y , Huang H , McGarvey PB , Wu CH , the UniProt Consortium . UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches . Bioinformatics . 2015 ; 31 : 926 - 32 .
50. Biegert A , Söding J. Sequence context-specific profiles for homology searching . Proc Natl Acad Sci U S A . 2009 ; 106 : 3770 - 5 .
51. Yamada KD , Tomii K , Katoh K. Application of the MAFFT sequence alignment program to large data-reexamination of the usefulness of chained guide trees . Bioinformatics . 2016 ; 32 : 3246 - 51 .
52. Katoh K , Misawa K , Kuma K , Miyata T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform . Nucleic Acids Res . 2002 ; 30 : 3059 - 66 .
53. Pupko T , Bell RE , Mayrose I , Glaser F , Ben-Tal N. Rate4Site: an algorithmic tool for the identification of functional regions in proteins by surface mapping of evolutionary determinants within their homologues . Bioinformatics . 2002 ; 18 : S71 - 7 .
54. Mayrose I , Graur D , Ben-Tal N , Pupko T. Comparison of site-specific rateinference methods for protein sequences: empirical Bayesian methods are superior . Mol Biol Evol . 2004 ; 21 : 1781 - 91 .
55. Gabriel SB , Schaffner SF , Nguyen H , Moore JM , Roy J , Blumenstiel B , et al. The structure of haplotype blocks in the human genome . Science . 2002 ; 296 : 2225 - 9 .
56. Olsen KM , Kooyers NJ , Small LL . Recurrent gene deletions and the evolution of adaptive cyanogenesis polymorphisms in white clover ( Trifolium repens L.). Mol Ecol . 2013 ; 22 : 724 - 38 .
57. Nei M , Suzuki Y , Nozawa M. The neutral theory of molecular evolution in the genomic era . Annu Rev Genom Hum G . 2010 ; 11 : 265 - 89 .
58. Kreitman M. Methods to detect selection in populations with applications to the human . Annu Rev Genom Hum G . 2000 ; 1 : 539 - 59 .
59. Anand K , Mathur D , Anant A , Garg LC . Structural studies of phosphoglucose isomerase from Mycobacterium tuberculosis H37Rv . Acta Crystallogr F Struct Biol Commun . 2010 ; 66 : 490 - 7 .
60. Wheat CW , Hagg CR , Marden JH , Hanski I , Frilander MJ . Nucleotide polymorphism at a gene (Pgi) under balancing selection in a butterfly metapopulation . Mol Biol Evol . 2010 ; 27 : 267 - 81 .
61. Wheat CW , Watt WB , Pollock DD , Schulte PM . From DNA to fitness differences: sequences and structures of adaptive variants of Colias phosphoglucose isomerase (PGI) . Mol Biol Evol . 2006 ; 23 : 499 - 512 .
62. Wang BQ , DePasse JM , Watt WB . Evolutionary Genomics of Colias Phosphoglucose Isomerase (PGI) Introns. J Mol Evol . 2012 ; 74 : 96 - 111 .
63. Kawabe A , Yamane K , Miyashita NT . DNA polymorphism at the cytosolic phosphoglucose isomerase (PgiC) locus of the wild plant Arabidopsis thaliana . Genetics . 2000 ; 156 : 1339 - 47 .
64. Hahn MW . Toward a selection theory of molecular evolution . Evolution . 2008 ; 62 : 255 - 65 .
65. Martin DP , Lemey P , Posada D. Analysing recombination in nucleotide sequences . Mol Ecol Resour . 2011 ; 11 : 943 - 55 .
66. Jensen JD , Foll M , Bernatchez L. The past, present and future of genomic scans for selection . Mol Ecol . 2016 ; 25 : 1 - 4 .
67. Teshima KM , Coop G , Przeworski M. How reliable are empirical genomic scans for selective sweeps? Genome Res . 2006 ; 16 : 702 - 12 .
68. Excoffier L , Hofer T , Foll M. Detecting loci under selection in a hierarchically structured population . Heredity (Edinb) . 2009 ; 103 : 285 - 98 .
69. Lin HY , Kao YH , Chen ST , Meng M. Effects of inherited mutations on catalytic activity and structural stability of human glucose-6-phosphate isomerase expressed in Escherichia coli . Biochim Biophys Acta . 2009 ; 1794 : 315 - 23 .
70. Somarowthu S , Brodkin HR , D'Aquino JA , Ringe D , Ondrechen MJ , Beuning PJ . A tale of two isomerases: compact versus extended active sites in ketosteroid isomerase and phosphoglucose isomerase . Biochemistry . 2011 ; 50 : 9283 - 95 .