Download Direct and indirect consequences of meiotic recombination

Opinion
Direct and indirect consequences of
meiotic recombination: implications
for genome evolution
Matthew T. Webster1 and Laurence D. Hurst2
1
2
Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
Department of Biology and Biochemistry, University of Bath, Bath, UK
There is considerable variation within eukaryotic genomes in the local rate of crossing over. Why is this and
what effect does it have on genome evolution? On the
genome scale, it is known that by shuffling alleles,
recombination increases the efficacy of selection. By
contrast, the extent to which differences in the recombination rate modulate the efficacy of selection between
genomic regions is unclear. Recombination also has
direct consequences on the origin and fate of mutations:
biased gene conversion and other forms of meiotic drive
promote the fixation of mutations in a similar way to
selection, and recombination itself may be mutagenic.
Consideration of both the direct and indirect effects of
recombination is necessary to understand why its rate is
so variable and for correct interpretation of patterns of
genome evolution.
The evolutionary consequences of meiotic
recombination
Meiosis involves the formation of DNA double-stranded
breaks (DSBs), which are subsequently repaired by the
process of homologous recombination. The functions of
recombination are twofold: crossovers (COs) are necessary
for accurate chromosomal disjunction in most eukaryotes
[1] and the shuffling of alleles by recombination has a
beneficial role for evolution [2,3]. However, recombination
also has costs. For example, DSBs may aberrantly pair
with non-homologous loci, leading to structural rearrangements via non-allelic homologous recombination (NAHR)
[4]. Such exchanges are often lethal or highly deleterious
[5]. These considerations suggest that the rate of crossing
over should be tightly controlled. However, there is extensive variation in the frequency of crossing over both within
and between genomes. What factors influence this variation and what other benefits and consequences does recombination have?
The major evolutionary advantage of recombination in
eukaryotes is thought to be that it breaks up associations
that occur between genetically linked variants, which
allows natural selection to promote the fixation of beneficial mutations and removal of deleterious ones with greater efficacy [2]. This we term the indirect consequence of
Corresponding author: Webster, M.T. ([email protected]).
recombination. In theory, however, there are many conditions under which recombination is not advantageous. This
is because associations between neighbouring loci may be
either positive (when either beneficial variants or deleterious variants are linked) or negative (when beneficial and
deleterious mutations are linked to each other) and there is
only a net advantage to recombination if most associations
are negative. In finite populations, negative associations
accumulate between neighbouring loci owing to a process
Glossary
Background selection: reduction in linked genetic variation due to purifying
selection at neighbouring loci.
Codon bias: most amino acids can be encoded by multiple codons. Codon bias
is the unequal use of codons for a particular amino acid.
Crossover (CO): exchange of genetic material between homologous chromosomes involving chromosomal breakage followed by rejoining to its homolog.
Direct effects of recombination: we define the direct effects of recombination
as the transmission and mutational biases that may occur during meiosis.
dN/dS: the rate of nonsynonymous substitution (dN) relative to the rate of
synonymous substitution (dS). This ratio is typically used to make inferences
on the type and strength of selection on amino acid mutations acting on a
gene. Assuming synonymous changes to be mostly neutral, positive selection
on amino acid changes is expected to increase dN/dS, whereas negative
selection decreases it.
Effective population size (Ne): a fundamental concept in population genetics
defined as the size of an ideal population that would experience an equal
magnitude of genetic drift as the observed population.
Fitness: average reproductive success of an individual, or the effect a genetic
variant has on this value. Individuals with greater fitness are likely to contribute
more offspring to the next generation than are individuals with lesser fitness.
Genetic drift: random changes in allele frequency due to random sampling
from the previous generation.
Genetic hitchhiking: process by which an evolutionarily neutral or deleterious
allele spreads through the gene pool by virtue of being linked to a positively
selected one.
Hill–Robertson interference (HRI): build-up of negative linkage disequilibrium
between linked loci due to selection. This association between variants with
differing fitness effects reduces the efficacy of selection.
Indirect effects of recombination: we define the indirect effects of recombination as the breaking down of linkage disequilibrium between neighbouring loci
owing to crossing over.
Linkage disequilibrium (LD): nonrandom association of alleles at two or more
loci.
Meiotic drive: unequal transmission of alleles from a heterozygote into its
gametes.
Positive selection: tendency for selection to increase the frequency of
beneficial variants towards fixation in a population.
Purifying (negative) selection: tendency for selection to reduce the population
frequency of deleterious variants towards their loss from a population.
Recombination hotspot: localised regions of the genome (typically 1–2 kb) that
exhibit elevated rates of meiotic recombination.
Selective sweep: process whereby an allele becomes more common in a
population owing to positive selection. This typically results in a reduction in
levels of linked variation by genetic hitchhiking.
0168-9525/$ – see front matter ß 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.tig.2011.11.002 Trends in Genetics, March 2012, Vol. 28, No. 3
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Opinion
known as the Hill–Robertson effect [6], which results from
the interaction between genetic drift and selection. Selection works in opposite directions on negatively associated
variants, which results in interference (known as Hill–
Robertson interference; HRI; see Glossary). This reduces
the efficacy of selection and provides an advantage to
recombination [7].
The evolutionary advantage of recombination is supported by the observation that species reproducing
completely asexually (and thus without recombination)
are both extremely rare and typically short lived [8] and,
similarly, that non-recombining genomic regions of sexually reproducing organisms accumulate deleterious mutations and deteriorate [9]. Experimental studies in
nematodes and unicellular eukaryotes have demonstrated
that strains undergoing recombination experience greater
rates of adaptation when selection is strong, for example
owing to new or fluctuating environmental conditions [10–
12]. If recombination increases the rate of adaptation, then
the recombination rate itself is predicted to be adaptive.
Several studies have demonstrated that rates of recombination evolve in response to strong selection on traits
unrelated to meiosis, such as when rotifers are forced to
adapt in heterogeneous environments [13], or fruit flies are
selected for geotaxis or DDT resistance [14]. It has also
been suggested that domestic species exhibit increased
recombination rates owing to the strong artificial selection
they have experienced [15–17], although this awaits confirmation. However, the extent to which the rate of recombination limits adaptation in natural populations is
unclear. Another important question, which we discuss
here, is whether the local rate of recombination in a genomic region is adaptive.
More recently, evidence has accumulated that other
recombination-associated processes can significantly influence genome evolution and play an important role in
determining variation in the recombination rate. These
include at least three forms of meiotic drive. The first,
Trends in Genetics March 2012, Vol. 28, No. 3
GC-biased gene conversion (gBGC) [18], results from biased incorporation of G and C nucleotides during repair of
mismatches formed during homologous recombination.
The second, which we term ‘hotspot drive’, results from
the biased transmission of non-recombinogenic alleles over
recombinogenic ones in hotspots of recombination [19]. The
third, which we term ‘indel drive’, refers to the biased
transmission of either the shorter or longer allele of an
indel during meiosis. In addition to this, the contentious
possibility that recombination generates point mutations
has also been discussed [20]. We refer to these processes as
the direct effects of recombination (further details are
presented in Box 1 and Figure 1).
Although one of the advantages of the indirect effects of
recombination is the efficient removal of deleterious alleles
from a population, its direct effects may sometimes themselves be harmful. In particular, recent research has implicated gBGC in promoting fixation of weakly deleterious
mutations [21]. In addition, the direct effects of recombination may play an important role in how recombination
rates vary across the genome. For example, hotspot drive is
believed to result in rapid shifts in the location of recombination hotspots [19,22].
Here, we propose that an understanding of both the
direct and indirect effects of recombination is crucial for the
interpretation of patterns of genome evolution and to
explain variation in the recombination rate across the
genome. There is now much evidence to suggest that
selection influences the level of linked genetic variation
across the genomes of eukaryotes, particularly in regions of
low recombination rate [23–27]. This could also indicate
that the efficacy of selection varies across the genome
owing to variation in the degree of HRI mediated by
recombination rate. If recombination rate places limits
on the efficacy of selection and the rate of adaptation, then
the local recombination rate could also be adaptive, leading
to selection on local modifiers of recombination rate.
However, what evidence is there that variation in the
Box 1. Direct effects of recombination
GC-biased gene conversion (gBGC)
During meiosis, gBGC causes heterozygotes with one AT and
one GC allele to produce slightly more gametes containing the
GC allele. This is hypothesised to result from a bias in the repair
of mismatches caused by heterozygous sites occurring in heteroduplex DNA during recombination [18]. There is experimental
evidence in yeast that gBGC is associated with meiotic
gene conversion events [59] and indirect evidence that gBGC
affects genome evolution and the segregation of alleles
in many other taxa [18,59,73,102]. gBGC is thought to
be responsible for the correlation between GC content and
recombination [18] and the large-scale variation in GC content
observed in many eukaryotic genomes [73]. It is also implicated in
episodes of accelerated evolution in localised genomic regions
[18,21,72,74].
Hotspot drive
Molecular genetic analysis of human recombination hotpots
has shown that when an individual is heterozygous for a
recombinogenic and non-recombinogenic allele, there is a bias in
favour of transmitting the non-recombinogenic allele [63], a
process inferred to be widespread using evolutionary genetic
analyses [19]. Along with the rapid evolution of PRDM9 (see main
text), this form of biased gene conversion is likely to be partly
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responsible for rapid shifts in the location of recombination
hotspots [19,22,65].
Indel drive
Evidence of transmission bias at indel polymorphisms is limited. In
Caenorhabditis elegans, chromosomes with insertions have been
observed to segregate preferentially away from the X chromosome
during meiosis, whereas chromosomes with deletions tend to be
inherited together with the X chromosome [103]. In Drosophila
melanogaster, preferential transmission of an allele containing a
P-element insertion over a non-insertion allele has been observed
[104]. Indel drive has also been observed in yeast and fungi, although
its direction varies between loci and crosses [105,106].
Mutagenic recombination
In yeast, there is experimental evidence that mitotic recombination
causes point mutations [83,84]. If meiotic recombination was also
mutagenic, it could explain why levels of genetic variation correlate
with the CO rate in some species [23,25,30,31,85]. However, whether
this is true in yeast or any other species is far from resolved (see main
text). It is clear, however, that recombination causes structural
mutations via NAHR [4], including those involved in human disease
[5]. In support of this, domains of high recombination tend to be more
highly rearranged (e.g. [58])
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Trends in Genetics March 2012, Vol. 28, No. 3
(a)
GC-biased gene conversion
(b)
Hotspot drive
G
C
A
T
DSB formation by Spo11
PRDM9
G
C
T
Strand invasion
C
G
T
Gap repair by strand synthesis
G
C
G
T
Mismatch repair
G
C
G
C
Biased transmission of
G
C
Biased transmission of
TRENDS in Genetics
Figure 1. Molecular mechanisms of two types of meiotic drive. GC-biased gene conversion (gBGC) and hotspot drive occur during homologous recombination, which
involves the formation of a DNA double-stranded break (DSB) followed by its repair using its homologue. (a) gBGC occurs in individuals that are heterozygous for a GC/AT
single nucleotide polymorphism (SNP). Heteroduplex mismatches that occur between alleles at this SNP during recombination are preferentially repaired towards GC,
leading to a bias toward transmission of the GC allele. (b) Hotspot drive occurs in individuals that are heterozygous for a recombinogenic motif (red box) that promotes
recombination by binding PR domain containing 9 (PRDM9) and a non-recombinogenic variant of the motif (blue box) that does not. The DSB occurs at the recombinogenic
motif, which is repaired by the non-recombinogenic one, leading to biased transmission of the non-recombinogenic variant.
recombination rate leads to variation in the efficacy of
selection across the genome? Could the direct effects of
recombination affect measures of the efficacy of selection?
What role do physical constraints have on determining
recombination rate variation? In addition to its effect of
breaking down genetic associations by shuffling alleles, we
outline several other important ways in which recombination can potentially contribute to phenotypic evolution by
altering the rate at which functional mutations occur and
become fixed in populations.
Evidence of intragenomic variation in the efficacy of
selection
Genomic regions that do not undergo meiotic recombination tend to accumulate deleterious mutations and lose
functional genes [9], a process that is well documented in
the neo-sex chromosomes of Drosophila miranda [28]. This
supports the notion that recombination aids the efficient
removal of deleterious mutations by selection. Both positive and negative selection are predicted to reduce the
effective population size (Ne) at neighbouring loci, which
reduces the local efficacy of selection owing to HRI [29].
Variation in the CO rate and density of sites under selection across the genome is therefore expected to generate
variation in locus-specific Ne.
What evidence is there that variation in the CO rate
across the genome outside non-recombining regions leads to
variation in the efficacy of selection? Regions of low crossing
over have reduced levels of neutral genetic variation in
humans, Drosophila and some plants [23,26,30,31] (but
not rice [32]). This is at least partly an effect of selection
reducing levels of variation at linked sites, indicating that
the evolutionary fates of mutations are affected by selection
at linked loci, but whether this leads to substantial variation
in the efficacy of selection is unclear. A study of variation in
genome-wide patterns of neutral genetic diversity across the
genomes of a variety of eukaryotes indicated that there is
highly significant variation in Ne, although this variation
showed no strong relationship with either the CO rate or the
density of selected sites, leaving most of the intragenomic
variation in Ne unexplained [27].
Several other studies have specifically investigated
whether the efficacy of selection varies according to the
CO rate. Two measures have been used as proxies for the
efficacy of selection: dN/dS and codon usage bias. The
dN/dS ratio is a measure of the rate of protein adaptation.
If most nonsynonymous mutations are weakly deleterious,
then dN/dS is likely to be reduced when selection is more
efficient, because purifying selection would prevent more
of these mutations rising to fixation. Conversely, if most
nonsynonymous mutations are advantageous, then dN/dS
is likely to be increased when selection is more efficient,
owing to a higher rate of adaptive nonsynonymous fixations. Codon usage bias is a measure of the proportion of
‘preferred’ codons in a gene, which is commonly used as an
estimate of the intensity of selection in species with large
population sizes (i.e. not mammals). Genes containing a
higher proportion of preferred codons, which correspond to
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the most abundant tRNAs, are often expressed more efficiently. There may therefore be a selective advantage for a
gene to contain preferred codons. This leads to the prediction that codon usage bias should be greater in regions of
the genome where selection is more efficient.
Studies in Drosophila have come to conflicting conclusions about the effect of the CO rate on the dN/dS ratio [33–
36]. One genome-wide analysis found little evidence of
differences in dN or dS between genomic regions with high
and low CO rates, except in non-recombining domains,
which have elevated dN/dS [35]. This may indicate that
the efficacy of selection is reduced in non-recombining
domains, but that low CO rates are sufficient to overcome
the negative effects of HRI. A further genome-wide study
[36] observed a weak but significant positive correlation
between dN/dS and the recombination rate in a set of genes
inferred to be under positive selection, and an opposite
weak but significant negative correlation in all other genes.
This was interpreted as an effect of HRI: if highly recombining regions experience more efficient selection, then
genes under predominantly positive selection would experience elevated dN/dS in these regions, whereas those
under predominantly negative selection would experience
reduced dN/dS. It was argued that these results were
consistent with this scenario [36]. However, even in positively selected genes, most nonsynonymous variants could
still be under purifying selection, so the net effect of
differences in the efficacy of selection on dN/dS is difficult
to predict.
In humans, it has been found that the average dN/dS is
constant across CO rate categories, which may be evidence
of an absence of variation in the efficacy of selection
according to the genomic recombination environment
[37]. Notably, in contrast to the studies in Drosophila,
there is no evidence of elevated dN/dS in regions of no
recombination in humans. In yeasts, there is a strong
negative correlation between the local recombination rate
and dN (and dN/dS) [38]. However, this is largely explained
as a covariate to the expression rate of the genes concerned,
with slow-evolving highly expressed genes tending to be
found disproportionately in regions of high recombination
rate [38–40]. Indeed, the rate of pre-meiotic DSB events
(which should have no effect on HRI) is also a strong
predictor of rates of evolution, in part because this too is
correlated with the expression rate [39]. There is no evidence of substantial variation in the efficacy of selection
across the yeast genome owing to recombination when
these factors are corrected for [38,39].
There is a slight positive correlation between the proportion of preferred codons and the CO rate in Drosophila
[18]. One interpretation of this is that selection for preferred codons is more efficient in regions of elevated recombination [41]. However, preferred codons in Drosophila
all end in G or C, and it has been demonstrated that the GC
content of noncoding DNA is higher in regions of elevated
recombination [42]. It is therefore possible that silent sites
in coding regions and surrounding noncoding DNA both
become GC-rich through a neutral effect of recombination
on GC content owing to gBGC. Variation in codon usage
patterns across Caenorhabditis elegans and Drosophila
could both be explained by this effect [43]. It has also been
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Trends in Genetics March 2012, Vol. 28, No. 3
suggested that high rates of adaptive protein evolution on
strongly selected genes could actually reduce levels of
codon bias. This is because strong selection on nonsynonymous sites could interfere with weak selection on nearby
synonymous sites owing to HRI [44].
There are several reasons why interpretation of the
results presented above is problematic. First, without
knowledge of the distribution of positive and negative
fitness effects on each gene, it is impossible to know a
priori whether a positive or negative correlation between
dN/dS and the CO rate is expected. Any interpretation of a
correlation, be it positive or negative, therefore comes with
after-the-fact supposition of the form of the distribution.
Unfortunately then, many results are in principle consistent with HRI, rendering the test weak by necessity.
Second, the analyses are based on currently observed
recombination rates, but these need not reflect the recombinational history of the gene if the local recombination
rate is fast evolving [45]. Third, there are many other
genomic features that correlate with recombination, which
may also influence dN, dS and codon usage bias. How and
when a gene is expressed appears to correlate with the
recombination rate [39,40,46] and the expression parameters of a gene are one of the best predictors of its evolutionary rate [47]. Furthermore, GC content correlates with
the recombination rate, and GC content across regions of
the genome is not always at equilibrium. In particular, GCrich regions in the human genome and many other mammalian genomes are decaying, which may result in increased mutation rates in these regions [48,49]. The
density of genes, which also correlates with both GC content and the recombination rate, may also play a role in the
intensity of HRI in a particular genomic region, owing to
the density of sites under selection. Direct effects of recombination can also affect dN/dS. For example, increased dN/
dS can occur in regions of high recombination owing to
fixation of weakly deleterious nonsynonymous substitutions by gBGC (see below; [50,51]).
Although there is good evidence that the rate of allele
shuffling by recombination is adaptive and can be modified
by selection in various eukaryotes [10–14], we find no compelling evidence that the recombination rate modulates the
efficiency of selection across the genome in humans, Drosophila or yeast (save for in some non-recombining
domains). This is consistent with theory suggesting that
only a small amount of crossing over is necessary to achieve
most of the benefits associated with recombination [52]. If so,
it is unlikely that selection to minimise HRI is a strong force
determining intragenomic variation in recombination rate.
Molecular control of intragenomic variation in the
recombination rate
To understand the forces constraining the distribution of
recombination and its effects on genome evolution, we need
to understand the molecular mechanisms controlling it. On
the large scale, it is known that COs are required for the
accurate disjunction of chromosomes, placing a minimum
requirement of one CO per chromosome arm [53] (or possibly chromosome [54]). This physical constraint ensures a
minimum level of crossing over across the autosomes,
although some other parts of the genome have intrinsically
Opinion
high CO rates (e.g. pseudoautosomal regions), whereas it is
absent in others (e.g. the mitochondrial genome and mammalian Y chromosome).
Several factors have been shown to correlate with recombination on the large scale. Levels of germline DNA
methylation appear to correlate with CO rates in human
[55], which may suggest that it has a role in recombination.
In addition, imprinted genes (and genes with monoallelic
expression) exhibit high recombination rates [46], whereas
genes transcribed in the germ line exhibit reduced rates of
recombination [46,56] (but see [57]). Consequently, genes
expressed in many tissues (i.e. housekeeping genes) tend to
have low recombination rates in humans [46] and possibly
also in Drosophila [58]. One explanation for these findings
is that germline transcription somehow inhibits CO formation, which places a constraint on their location.
On the fine scale, recombination events in many eukaryotic genomes are largely confined to short (1–2 kb) hotspots
[59,60]. A common mechanism of initiation of recombination
in hotspots is the binding of the histone methyltransferase
PR domain containing 9 (PRDM9) to a specific DNA sequence motif. This results in a histone methylation followed
by the formation of a DSB. The precise locations of hotspots
evolve rapidly in many species [22,61,62]. In humans, comparative genomic and sperm typing studies have both demonstrated the action of a form of biased genome conversion
that we term ‘hotspot drive’ (Box 1; Figure 1), which promotes the spread of non-recombinogenic alleles at hotspots
and, thus, their extinction [19,63]. The DNA-binding zinc
finger domain of PRDM9 also appears to have been evolving
rapidly in a wide range of animal genomes, which leads to
regular shifts in the motif that it recognises [19,64]. Together, these processes suggest that a rapidly shifting recombination landscape on the local scale is a feature of many
genomes containing an active PRDM9.
In some other species, PRDM9 evolves more slowly,
which predicts a slower turnover of hotspot locations,
whereas other species lack an active copy of PRDM9,
and in these species hotspots are predicted either to be
absent or controlled by another mechanism [65]. In dog,
one of the only mammals missing an active PRDM9,
recombination hotspots appear to be more evolutionarily
stable [66]. On the fine scale, therefore, the genomic landscape of recombination and its rate of evolution both show
large variability between species, but it is unclear whether
these observations have any adaptive significance.
In humans, hotspots are biased against occurring in
genes and a possible explanation for this is that hotspot
locations are also subject to selective constraint to mediate
deleterious effects, such as NAHR or other direct effects
[60]. However, the factors that constrain recombination
events on the fine scale are generally unknown. Nevertheless, it is clear that the recombination rate is governed by
several physical and molecular constraints on both the
large and local scale, which are unrelated to its evolutionary advantages.
Direct effects of recombination on evolutionary
inference
One way in which consideration of the direct effects of
recombination is important is for the inference of natural
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selection acting on genomic sequences. A popular approach
to identify genes under positive selection is to scan the
genome for acceleration in dN/dS on a certain lineage (e.g.
[67]). However, analyses of genome scans for genes with
elevated dN/dS in the human and other primate branches
reveal that many such genes show GC-biased patterns of
evolution on the branch on which they were identified,
characteristic of the action of gBGC [50,51,68]. Mathematical modelling suggests that gBGC interferes with purifying selection, and can even cause dN/dS to increase to
above one under certain realistic parameter combinations,
providing a false signal of positive selection [50,51]. Up to
20% of genes with elevated dN/dS in humans may be better
explained by gBGC than by positive selection [68].
An example of such a gene is the human adenylate
cyclase activating polypeptide 1 (ADCYAP1) gene, which
was identified in a genome scan as having significantly
elevated dN/dS on the human lineage [67], and additionally exhibits all the hallmarks of gBGC [68,69]. It is found
close to a telomere in a region of highly elevated male
recombination, overlapping a recombination hotspot. Its
two most diverged exons have accumulated 20 substitutions, which are all AT ! GC, and this pattern extends into
noncoding regions (Figure 2). Of the 20 substitutions, 17
change an amino acid, and it has been suggested that the
high rate of evolution at nonsynonymous sites could not
have been produced by gBGC alone [69]. However, mathematical modelling of the predicted effect of gBGC on this
gene under a range of plausible scenarios, incorporating
the population size-scaled coefficients of selection and
gBGC and the distribution of negative fitness effects,
suggests that a model of gBGC alone is sufficient to explain
the acceleration in dN/dS [68].
Careful evaluation of patterns of molecular evolution in
genes with elevated dN/dS ratios is warranted before
concluding that positive selection is responsible. For instance, the brain-expressed microcephalin 1 (MCPH1) and
abnormal spindle-like microcephaly-associated protein
(ASPM) genes, both suggested to be under selection on
the lineages leading to humans for increased cognitive
function [70,71], also overlap human recombination hotpots and exhibit GC-biased patterns of evolution on the
human lineage. Microcephalin has 20 AT ! GC and seven
GC ! AT changes, whereas ASPM has ten AT ! GC and
four GC ! AT, which are both different from the genome
average, where GC ! AT changes predominate (data from
[67]). This may indicate that, contra to the prior assumption [70,71], gBGC is a more probable driver of elevated
dN/dS on the human lineage in these genes than is positive
selection.
Direct effects of recombination on fitness
The evolutionary trajectory of a genetic variant depends
not only on its phenotypic effect, but also on biases affecting its probability of transmission into the next generation.
Because most new mutations with an effect on fitness are
expected to be deleterious, by increasing the probability of
fixation of GC alleles regardless of their fitness effects, the
process of gBGC may incur a substantial ‘fixation load’ [18].
In regions of extremely elevated recombination, gBGC may
generate bursts of GC allele fixation, which in species
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(a) GC bias
1
0.5
0
(b) Human substitutions
(c) ADCYAP1 exons
(d) Missing macaque sequence
1 kb
TRENDS in Genetics
Figure 2. Evolution of ADCYAP1 on the human lineage. Adenylate cyclase activating polypeptide 1 (ADCYAP1) is a gene identified by genome scans as having significantly
elevated dN/dS on the human lineage. It is found close to the telomere on the short arm of chromosome 18p in a region of elevated male recombination (4.17 cM/Mb) within
a recombination hotspot defined by patterns of linkage disequilibrium. This figure shows the pattern of nucleotide substitutions on the human lineage inferred using
human–chimpanzee–macaque alignments. (a) GC bias is the proportion of substitutions that are AT ! GC, calculated in a sliding window of 20 substitutions (only
considering AT ! GC and GC ! AT substitutions). Windows with a bias >0.5 are shown in red. (b) Locations of substitutions on the human lineage (red, AT ! GC; blue,
GC ! AT; black, others). (c) Locations of exons indicated by black rectangles. (d) Regions where human-specific substitutions were not inferred owing to missing
orthologous sequence from macaque. A strongly GC-biased pattern of substitution is observed, which encompasses, but is not restricted to, exonic sequences. This pattern
is consistent with the action of gBGC.
comparisons appear as clusters of nucleotide substitutions
[21]. Clusters of substitutions on the human lineage tend to
be GC-biased and occur near telomeres and in regions of
elevated recombination, with a stronger association with
recombination in males [72,73]. It has subsequently been
shown that GC bias in highly diverged sequences is a
common feature in metazoans [74]. It is thought that these
clusters are associated with recombination hotspots (which
need not be currently active), which generate GC-biased
fixations due to gBGC.
Several studies have identified human accelerated
regions (HARs), which are short elements with a high
degree of sequence conservation in vertebrates but that
have experienced accelerated evolutionary rates in the
human lineage (e.g. [75,76]). Although such a pattern of
evolution might be expected owing to the action of positive
selection, many of these elements are found in regions of
elevated male recombination, and have an excess of GCbiased substitutions on the human lineage, which also
extends into the flanking sequence, which is more indicative of gBGC. Hence, the action of gBGC in some HARs may
have influenced the emergence of human-specific characteristics. Although elevated substitution rates in most
HARs may be because of positive selection, the patterns
of evolution in the two most highly accelerated regions
identified so far, HAR1 and HAR2 (also called HACNS1),
are strongly indicative of the action of gBGC [21].
Functional analysis of the human and chimpanzee versions of HACNS1 show that it acts as an enhancer of gene
expression. A study using a mouse construct showed that
the human-specific nucleotide substitutions result in increased expression in the developing limb [75]. On the
basis of this finding, it was hypothesised that these substitutions resulted in a gain of function in this tissue,
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potentially contributing to the evolution of a human-specific characteristic. It has been argued that gBGC is unlikely to result in such a gain of function, because it is
generally expected to result in the fixation of neutral or
deleterious changes [69]. However, a recent analysis has
provided evidence that the human-specific substitutions
actually disrupt the function of a repressor module [77],
which is potentially more consistent with the fixation of
deleterious mutations by gBGC.
It has also been shown that gBGC can result in an
elevated rate of fixation of weakly deleterious amino acid
changes [50,51]. This can also have effects on the genome
scale. A significantly elevated dN/dS ratio has been observed in outcrossing wheat species compared with selfers
[78]. This contrasts with classical predictions, which suggest that the efficacy of selection should be greater in
outcrossing species owing to a reduction in HRI, which
should lead to more efficient purifying selection and, hence,
reduced dN/dS. Paradoxically, therefore, outcrossing species may suffer an additional load of deleterious fixations
because gBGC represents an additional cost of recombination [79]. There is also evidence that gBGC contributes to
the spread of deleterious mutations in human populations,
because the site frequency spectrum of nonsynonymous
mutations and those implicated in human genetic disease
also show the hallmarks of a transmission bias towards GC
[80].
Indel drive may yet prove to be equally important for
genome evolution, although so far there is little evidence of
a general transmission bias toward insertions or deletions
(Box 1). If shorter indels have a transmission advantage,
for example, this might explain the observation [81] that
short introns are observed in domains of high recombination, rendering it unnecessary to evoke (again) differences
Opinion
in the strength of selection, the conventional model for
interpreting this finding. Similarly, a bias favouring the
transmission of insertions over deletions could contribute
to the observation that deletions segregate at lower frequencies in humans and are enriched in fixed differences
since the human–chimpanzee ancestor compared with human polymorphism [82].
Is recombination mutagenic?
Besides its role in generating allelic transmission biases,
recombination may also lead to new mutations. Although it
is clear that recombination generates structural changes
via NAHR, early suggestions that it also leads to point
mutations [20] have not been conclusively proven. There is
strong evidence in yeast that mitotic DSB repair is mutagenic [83,84], but the repair of DSBs formed during meiosis
is mechanistically different and it is unclear whether this
is also mutagenic. The extent to which these findings can
be applied to other species is also not clear.
A correlation between genetic variation and the CO rate
exists in several species [23,25,30,31,85], which has been
suggested to reflect a larger effect of linked selection
(selective sweeps or background selection) reducing variation in regions of low recombination. However, at least in
humans, there is also a correlation between putatively
neutral divergence and the recombination rate [85,86],
which suggests that variation in the mutation rate could
account for the correlation between recombination and
genetic variation on a large scale. One interpretation of
this correlation is that recombination is mutagenic. However, because human recombination hotspots are very fast
evolving, any mutagenic effect of recombination need not
necessarily result in higher divergence [19]. There is also
no significant increase in the levels of human genetic
variation around the recombinogenic hotspot motif in data
from the 1000 Genomes Project [87], which would be
expected if recombination were mutagenic.
It is possible that variation in the fixation of different
nucleotides owing to the process of gBGC may generate a
correlation between CO rate and divergence [73]. However,
in the highly recombining human pseudoautosomal region,
there is a significant elevation in substitution rate including A $ T and G $ C substitutions [88] and these should
not be affected by gBGC. Another possibility is that linked
selection has affected levels of divergence between human
and chimpanzee [24]. Forward population genetic simulations suggest that both positive and negative selection in
the ancestral population of humans and chimpanzees could
generate a correlation between CO rate and divergence
[26].
There is a lack of robust evidence of an association
between divergence and CO rate in Drosophila [89] or
yeast [90]. However, in Drosophila, this may be because
of the low resolution of genetic maps, and there is evidence
of a correlation when the CO rate is measured on a fine
scale [91]. Furthermore, there is little power to detect a
signal of mutagenic recombination in yeast [90] because
modern yeast recombines so very rarely that any faint
signal would easily be drowned [92]. Moreover, whether
Drosophila or yeast has a class of sites that are consistently
neutrally evolving is unclear [25].
Trends in Genetics March 2012, Vol. 28, No. 3
A mutagenic effect of meiotic recombination would have
significance for a wide range of evolutionary and medical
genetic analyses. However, although some of the observations presented above are compatible with such an effect,
direct evidence is lacking.
Concluding remarks and future perspectives
Although it is commonly assumed that variation in the
recombination rate across the genome leads to variation in
the efficacy of selection owing to its indirect effects of
shuffling alleles, there is no strong evidence of this, with
the possible exception of non-recombining domains. A lack
of such variation in the efficacy of selection would imply
that variation in the local recombination rate is unlikely to
be subject to strong selection. However, the direct effects of
recombination appear to have strong demonstrable effects
on the genome that are important to consider for correct
evolutionary inference, and also have effects on the distribution of recombination hotspots and the evolution of
functional genomic elements.
Why is the theory on the efficacy of selection not of
greater relevance? One possibility is that positive selection
has typically been assumed to result from recurrent ‘hard’
selective sweeps in which new beneficial mutations are
rapidly driven to fixation by positive selection. However,
selection can also entail more gradual or partial fixation of
genetic variants that may be only weakly beneficial (a ‘soft
sweep’ [93,94]). In both human [95] and Drosophila [96,97]
recent evidence suggests that this mode of adaptation is
common. Furthermore, much of the effect of selection on
linked variation may be because of the elimination of rare
deleterious mutations (background selection). Hard
sweeps have a major effect on linked loci, potentially
eliminating all genetic variation, making crossing over
essential to preserve beneficial mutations and prevent
fixation of deleterious ones in genetic linkage with those
under selection. When variants do not rapidly sweep
through the population (as in soft sweeps or background
selection), it is less important to unlink them from neighbouring loci to prevent interference. This could potentially
explain the lack of evidence for the efficacy of selection
being limited by recombination in human and Drosophila,
except in regions of extremely low recombination.
The interpretation of patterns of genome evolution is
hampered by a poor understanding of the direct effects of
recombination. We suggest that a thorough mechanistic
analysis of the direct impact of recombination is necessary.
What is the strength of gBGC? Why does it correlate with
male, but not female, recombination [98]? Is meiotic recombination mutagenic and, if so, at what rate? These
questions require experimental quantification using techniques such as sperm typing [99], experimental mapping of
COs [100] and analysis of transmission in pedigrees [101].
High-throughput sequencing technologies will be useful for
these goals. There is also a need for a better understanding
of the determinants of the local recombination rate. Why do
germline expressed genes appear to avoid recombination in
mammals? Is this a necessary mechanistic constraint or
the result of selection? What effect does DNA methylation
have on promoting recombination? The use of more detailed post-genomic data sets will be useful to answer these
107
Opinion
questions. To understand the evolutionary importance of
recombination owing to its indirect effects, there is a need
to clarify the direct effects of recombination on genome
evolution.
Acknowledgements
We thank Jonas Berglund for help with Figure 2, and three reviewers for
helpful comments.
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