Does recombination slow mutation accumulation in sexual populations? Is there any evidence?

Does recombination slow mutation accumulation in sexual populations? Is there any evidence?

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Mullers Ratchet is the process by which asexual organisms would accumulate mutations without bound. It is claimed that sexual organisms would slow this mutation accumulation through recombination. Is there any evidence that recombination achieves this? Preferably experimental evidence.

It's a good question and one without a wholly satisfactory answer. Here's a nice review from 2012 outlining the theoretical questions regarding Mueller's ratchet and recombination.

There also is "unequivocal evidence that deleterious mutations accumulate in low recombining regions of the genome, due to the reduced efficacy of purifying selection. " So if you accept this correlation between recombination and removal of deleterious mutations, then studies such as these are compelling evidence of what's happening in real populations .

One other thing to keep in mind that in terms of experimental evidence, it is non-trivial to translate theoretical measures of fitness (e.g. "selection coefficients") to something that we can directly measure in real populations. So even determining if there is an increase/decrease in deleterious alleles is going to dependent on having useful data in the first place. The assignment of "true" measures of selection on individual genotypes is the mainstay of experimental evolution (nice review here) and is very labor intensive. Moreover, the vast majority of this work has been carried out in bacteria (due to their short generation times) so effects of recombination are not addressed. Nevertheless there are some cool comparative studies in yeast showing how recombination can make selection more efficient.

There have been a ton of mathematical arguments and computer simulations demonstrating Muller's Ratchet and its relationship to asexual reproduction. However, as far as I know, the experimental evidence is still hotly debated. The debate generally revolves around whether a given biological system fulfills the conditions necessary for the ratchet to operate. Here are a couple of relevant papers:

Quantifying the genomic decay paradox due to Muller's ratchet in human mitochondrial DNA.

Asexual Amoebae Escape Muller's Ratchet through Polyploidy

Mutations that are positively selected reduce the ratchet effect in large asexual populations. They spread, eliminating everything else, and so other mutations only matter if they happen in descendants of those mutations. It's as if the average population size is smaller.

Unfavorable mutations can hitch-hike with the selected ones, but only if they are unimportant enough that the combination is still selected.

Sexual reproduction reduces the ratchet effect to single linkage groups. But it allows things like meiotic drive. Mutations that result in the mutant version distributed to more than half the offspring can still be selected even if they reduce survival of the offspring later. And that happens a lot faster than the ratchet.

Experimental evidence -- that's hard. Maybe you could grow haploid yeast that don't do sex over a long period in a particular environment and measure changes in fitness in that environment. (The obvious way to measure changes in fitness is to grow them mixed with the wild-type and see how long it takes one to outcompete the other.)

Grow other yeast that do some recombination in the same environment and see whether they evolve faster. (Again, grow them together and see which one consistently wins.)

Some yeast that look reliably asexual have rare events that turn on sexuality. For example if they are all the same mating type, they can rarely have something that turns an individual into the other mating type. If your asexual populations have that happen while the experiment is running it contaminates your results. So be careful about that.

It looks like a whole lot of work. If the sexual form usually evolves faster then you have done a whole lot of work to show what almost everybody already believed.

Mutation Accumulation in an Asexual Relative of Arabidopsis

Asexual populations experience weaker responses to natural selection, which causes deleterious mutations to accumulate over time. Additionally, stochastic loss of individuals free of deleterious mutations can lead to an irreversible increase in mutational load in asexuals (the “click” in Muller’s Ratchet). Here we report on the genomic divergence and distribution of mutations across eight sympatric pairs of sexual and apomictic (asexual) Boechera (Brassicaceae) genotypes. We show that apomicts harbor a greater number of derived mutations than sympatric sexual genotypes. Furthermore, in phylogenetically constrained sites that are subject to contemporary purifying selection, the ancestral, conserved allele is more likely to be retained in sexuals than apomicts. These results indicate that apomictic lineages accumulate mutations at otherwise conserved sites more often than sexuals, and support the conclusion that deleterious mutation accumulation can be a powerful force in the evolution of asexual higher plants.

Author summary

A chromosomal inversion is a segment of the chromosome that is flipped (inverted arrangement) relative to the normal orientation (standard arrangement). Such structural mutations may facilitate evolutionary processes such as adaptation and speciation, because reduced recombination in inverted regions allows beneficial combinations of alleles to behave as a single unit. This locally reduced recombination can have major consequences for the evolution of the allelic content inside the inversion. We used simulations to investigate some of these consequences. Inverted regions tended to accumulate more deleterious recessive mutations than the rest of the genome, which decreased the fitness of homokarotypes (individuals with two copies of the same arrangement). This led to a strong selective advantage for heterokaryotypes (individuals with one copy of each arrangement), maintaining the inversion polymorphism in the population. The accumulation of deleterious mutations also resulted in strong divergence between arrangements. We occasionally observed an arrangement that diverged into a small number of highly differentiated haplotypes, stopping the fitness decrease in homokaryotypes. Our results highlight the dynamic features of inversions by showing how the evolution of allelic content can greatly affect the fate of an inversion.

Citation: Berdan EL, Blanckaert A, Butlin RK, Bank C (2021) Deleterious mutation accumulation and the long-term fate of chromosomal inversions. PLoS Genet 17(3): e1009411.

Editor: Alex Buerkle, University of Wyoming, UNITED STATES

Received: June 5, 2020 Accepted: February 10, 2021 Published: March 4, 2021

Copyright: © 2021 Berdan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: SliM scripts, analysis scripts, and seeds are available at

Funding: E.L.B. was supported by a Marie Skłodowska-Curie fellowship 704920 – ADAPTIVE INVERSIONS from the European Commission ( R.K.B. was supported by the NERC Grants NE/P001610/1 and NE/P012272/1 ( and by ERC Advanced Grant 693030 - BARRIERS from the European Research Council ( C.B. is grateful for support by EMBO Installation Grant IG4152 ( A.B. and C.B. were supported by ERC Starting Grant 804569 - FIT2GO from the European Research Council ( This work was supported by Fundação Calouste Gulbenkian ( The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.


The three progeny arrays exhibited similar genotype diversities [D(V − progeny) =𠂐.19, D(T − progeny) =𠂐.20, D(I − progeny) =𠂐.28] with 5𠄸 genotypes per progeny array. Pairwise genetic distances between genotypes showed that most progenies were clonal and identical to the respective mother genotype, but non-maternal offspring appeared in all three progenies. Character incompatibility methods revealed recombinants in the T and V clones. After averaging proportions of recombinant genotypes over the three progeny arrays, the mean number of recombinants as a proxy for recombination rate per generation was computed as r =𠂐.061 (Table  1 ).

Table 1

Genotyping using microsatellite analysis of three progenies of R. carpaticola × R. cassubicifolius. C = maternal clone, M = SSR mutant clone, R = recombinant

Progeny array (mother plant ID)No. of progeniesNo. of offspring genotypesNo. of C, M and R plants per progeny array% of recombinant genotypes per progeny arrays
V (35/28)39831 (C), 4 (M), 4 (R)10.26
T (29/15)38534 (C), 1 (M), 3 (R)7.89
I (8492/27)30625 (C), 5 (M), 0 (R)0.00
Mean36630 (C), 3 (M), 2 (R)6.05

Starting at time t =𠂐 generations after a new deleterious mutation has become fixed in a non-recombining clone, the frequency of mutant clones κm =𠂑. A facultative asexual plant population with a non-zero recombination rate per generation and with one fixed deleterious mutation consists of three different offspring classes in the first generation (Additional file 3a). The frequencies of genotypes are given as: ρ0 (non-mutant recombinant from sexual seeds ‘R’ genotype in Additional file 3a-b), ρm (mutant recombinant from sexual seeds ‘R’ genotype marked with an asterisk in Additional file 3a-b), κm (mutant clone from apomictic seeds 𠆌’ genotype marked with an asterisk in Additional file 3a-b). We assume that recombination operates in all subsequent generations with the empirically estimated rate r =𠂐.061 or

𠂖% of recombinant genotypes per generation and that further generations can continue to produce both recombinant and clonal offspring (‘R’ and 𠆌’ genotypes in Additional file 3a-b). Hence, in the second generation, the mutant clonal and mutant recombinant mothers each can produce three offspring classes (i.e., non-mutant and mutant recombinants and mutant clones). In contrast, the non-mutant recombinant mother can produce non-mutant clonal offspring (𠆌’ in Additional file 3a-b) with a frequency given as κ0 in the second and following generations (Additional file 3c).

The decay steepness (Fig.  2 ) is more dependent on the rate of recombination than on the strength of selection because selection can act only on homozygous mutant recombinants (ρm). Based on the Eq. (1) we revealed an estimate of time (t) needed to reach an arbitrary minimum frequency of mutant clones κm,min, where mutants can be considered as eliminated or lost by genetic drift. Considering any value of κm,min, the time necessary to reach it corresponds to t (κm,min) = ln[(1-ρm)κm,min −𠂑 ]ρ0 −𠂑 , or expressed with recombination and selection:

Abortion rates of viable reproductive units during sexual and aposporous development. Development starts from the megaspore phase (a), continues with gametophyte (b) and the embryo phase (c), and ends with the seedling phase. The major abortion (mean 52%) happens during the reduced female gametophyte (FG) phase (b) of the sexual development (blue dashed line). In comparison, the decline is less steep during the unreduced aposporous female gametophyte phase (solid gray line). These results suggest stronger selection upon the reduced phase (n) of the sexual development than upon the unreduced phase (2n) of the aposporous development. The decline from the embryo stage to the offspring (seedling) stage is in sexual and apomictic offspring almost the same, as germination rates are not significantly different. Proportions of reproductive units are given as means with confidence intervals. Data were adapted from [25, 26]

Even if mutation accumulation operates rapidly in small populations, a constant recombination rate of 6% restores the least-loaded genotype class within a single generation cycle. According to the Eq. (2), the elimination of all mutant clones (e.g., κm,min <𠂐.001) takes approximately 138 generations for s =𠂑.000, 204 generations for s =𠂐.520 or 246 generations for s =𠂐.212 (Fig.  2 ). However, if obligate apomixis without any recombination is assumed, Muller’s ratchet would act rapidly in our model system. Depending on the model used, the ratchet would click between 32 and 3570 generations (Table  2 ).

Table 2

The speed of Muller’s ratchet under obligate asexuality, assuming fixed population size N =� 3 individuals and deleterious mutation rate U =𠂑.116. n0 = Number of individuals within the least-loaded class, s = selection coefficient, t(J) = interclick time estimate based on Eq. 34 in [28], t(NS) = interclick time estimate based on Eq. 33 in [29] and t(ME) = interclick time estimate based on Eq. 24 [30] all time estimates are given as numbers of generations per 𠇌lick”. Bold text =𠂞stimates of the selection coefficients of the fastest ratchets the (J)-value was computed according to Eq. 34 in [28], corresponding to a U-shaped function with a local minimum at s =𠂐.212, which we considered as a critical value of the fastest ratchet acting on sporophytes

s n 0 t (J) t (NS) t (ME)
0.340 (ME) 3866493008 3570
0.218 (NS) 633 3214,006
0.212 (J) 5 333216,146

Materials and Methods

Treatments to Exclude Deleterious Mutations.

We used three treatments to preclude the occurrence of deleterious mutations that might act as stepping stones during adaptive evolution (Fig. S1A). These treatments differed in their impact on the overall mutation rate and the distribution of fitness effects (Fig. S1 BD).

The RvD treatment reverted any nonlethal deleterious mutation to its previous state. Lethal mutations were not reverted because they cannot act as stepping stones. Deleterious mutations make up a large proportion of all mutations (typically about half in evolved genomes), and therefore this treatment reduced the overall mutation rate (Fig. S1B). To account for this effect on the mutation rate, the RpD treatment replaced a nonlethal deleterious mutation with another mutation by randomly sampling potential mutations until one belonging to a permissible class—beneficial, neutral, or lethal—was found. The RpD treatment thus maintained the overall mutation rate. However, this treatment increased the load of lethal mutations because they generally comprised the largest proportion of the permissible classes (Fig. S1C). The RpDL treatment addressed the increased load of lethal mutations by replacing both deleterious and lethal mutations, again maintaining the overall mutation rate but allowing only two classes of mutations, neutral and beneficial (Fig. S1D).

Two exceptions sometimes occurred that are not covered above. First, in the RpD and RpDL treatments, we tested a maximum of 100 candidate replacements before stopping the search to find a mutation belonging to an allowed class. This threshold was never reached under the RpD treatment because lethal alternative mutations were always abundant. However, in the RpDL treatment, the two largest classes of mutation (deleterious and lethal) were disallowed, and this threshold was occasionally reached. We examined 1,092,337 attempted replacements at 200 uniformly spaced updates across the 50 RpDL populations, and only 281 (<0.03%) failed to identify an acceptable replacement. In these rare cases, the original mutant was eliminated to prevent any deleterious mutations from entering the population. The second exception occurred in all treatments, including the controls. We occasionally encountered a mutant that, when tested in isolation, produced an offspring that was not an exact copy of itself, even if the mutation rate was set to zero. This type of unstable genotype can occur when an organism’s self-replication process is damaged. For example, a point mutation might cause the organism to copy only part of its genome, or to copy part of its genome more than once. We disallowed mutations that produced unstable genotypes in all treatments, including the control treatment, because our analyses were predicated on single mutations occurring in genomes of constant length.

Measuring the Fitness of Digital Organisms.

In the isolated test environment, and with additional mutations prevented, we evaluated each candidate mutant’s fitness by allowing it to execute its genome. We measured two aspects of its performance: the rate at which it acquired SIPs (single-instruction processing units) and the number of instructions executed to replicate itself. The ratio of these two numbers is a close approximation to the organism’s absolute fitness. If digital organism A has twice the fitness of organism B, then A will, on average, produce twice as many offspring as B in the same amount of time. This expectation is not frequency-dependent i.e., it is independent of the relative abundance of A and B. Note also that previous work has shown that the outcome of direct competition is quantitatively consistent with the calculated differences in fitness except at very high mutation rates (31), where differences in offspring viability may become important this effect is minimal at the mutation rates used in our study.

An organism obtained additional SIPs if, in the course of executing its genomic program, it performed one or more of nine distinct one- and two-input logic operations, according to the multiplicative schedule in Table S3. If a mutant could not self-replicate (within an allotted maximum time), the mutation was categorized as lethal. Otherwise, we classified the mutation as beneficial, neutral, or deleterious based on whether the mutant’s fitness was higher than, equal to, or lower than that of its immediate progenitor.

Reversion and Replacement of Neutral Mutations.

The RvN, RpN, and RpNL treatments followed the same procedures as the RvD, RpD, and RpDL treatments, respectively, except that neutral mutations were reverted or replaced rather than deleterious mutations. For the RvN and RpN treatments, mutations that changed fitness by <1% were considered to be neutral whereas, for the RpNL treatment, mutations were treated as neutral only if they did not affect fitness at all. Other experiments suggested that the exact definition of neutrality was immaterial to our general conclusions.

Reversion and Replacement in Sexual Populations.

Sexual recombination in digital organisms was implemented as described elsewhere (27, 32). In brief, an organism first produced an asexual copy of its genome. Then, two copies from different parents exchanged a section of their genomes to produce two offspring we used two randomly chosen crossover points to define that section.

Potential mutations were tested for deleterious effects, and reversions were performed after genomes were copied but before recombination events. Therefore, mutations were judged as deleterious or not only against the background of the parent in which they arose. We did not perform replacement (rather than reversion) treatments in sexual populations.

Data Analyses and Statistics.

Analyses and statistics were performed in Python, using the libraries numpy, scipy, and matplotlib. Wilcoxon signed-rank tests were performed in R. All statistical tests were two-tailed. To correct for multiple tests in the replay experiments, we adjusted P values using the Dunn–Sidak method of the Bonferroni correction (30).

The causes of mutation accumulation in mitochondrial genomes

A fundamental observation across eukaryotic taxa is that mitochondrial genomes have a higher load of deleterious mutations than nuclear genomes. Identifying the evolutionary forces that drive this difference is important to understanding the rates and patterns of sequence evolution, the efficacy of natural selection, the maintenance of sex and recombination and the mechanisms underlying human ageing and many diseases. Recent studies have implicated the presumed asexuality of mitochondrial genomes as responsible for their high mutational load. We review the current body of knowledge on mitochondrial mutation accumulation and recombination, and conclude that asexuality, per se, may not be the primary determinant of the high mutation load in mitochondrial DNA (mtDNA). Very little recombination is required to counter mutation accumulation, and recent evidence suggests that mitochondrial genomes do experience occasional recombination. Instead, a high rate of accumulation of mildly deleterious mutations in mtDNA may result from the small effective population size associated with effectively haploid inheritance. This type of transmission is nearly ubiquitous among mitochondrial genomes. We also describe an experimental framework using variation in mating system between closely related species to disentangle the root causes of mutation accumulation in mitochondrial genomes.

1. Introduction

The primary defining feature of eukaryotes is the existence of cytoplasmic organelles that have separate genomes and often experience very different modes of inheritance. These mechanisms of inheritance are expected to have profound effects on the evolutionary forces shaping the different genomes (Birky et al. 1983). The nuclear genome, for example, is generally inherited biparentally with regular recombination. In fact, persistently asexual nuclear genomes are notably rare (Bell 1982). Since recombination is required for an effective clearance of deleterious mutations (Charlesworth et al. 1993), one interpretation of this pattern is that lineages with asexually transmitted nuclear genomes are vulnerable to extinction via the accumulation of deleterious mutations (Muller 1964). In contrast to the nuclear genome, mitochondrial genomes are generally assumed to undergo little, if any, recombination among genetically distinct partners. This leads to the expectation of high mutation loads in mitochondrial DNA (mtDNA e.g. Gabriel et al. 1993 Howell 1996).

Accordingly, comparative surveys of mutation accumulation in plants, animals and fungal mitochondrial and nuclear genomes consistently find that mitochondrial genomes (Lynch 1997 Lynch & Blanchard 1998) and the nuclear genomes of asexuals (Normark & Moran 2000) and selfers (Weinreich & Rand 2000 Bustamante et al. 2002 Glémin et al. 2006) accumulate deleterious mutations at a higher rate than nuclear genomes in outcrossing sexuals (reviewed in Charlesworth & Wright 2001). A similar pattern is seen in portions of the nuclear genome lacking recombination compared with the regions of recombination (e.g. Navarro-Sabaté et al. 2003 Haddrill et al. 2007). Bazin et al. (2006) also showed that mitochondrial genomes are different from nuclear genomes in that polymorphism and rates of evolution are relatively insensitive to variation in census population size in nature. Their interpretation was that for non-recombining mitochondrial genomes, efficient selection in large populations reduces the efficacy of selection at linked sites such that these sites experience a reduced Ne, perhaps similar to that experienced by small census populations (sensu ‘genetic draft’ Gillespie 2000, 2001). There is some discussion in the literature about whether the findings of Bazin et al. reflect positive selection versus purifying selection (reviewed in Meiklejohn et al. 2007), but the central role of asexuality as the driving force in mitochondrial mutation accumulation is assumed throughout.

Recombination can influence mutation accumulation in two ways. First, it can directly reverse the accumulation of deleterious mutations present at low frequency (Muller's ratchet, Muller 1964) by generating offspring genomes that have fewer deleterious mutations than their parent(s). Second, recombination can affect mutation accumulation via its effect on the effective population size (Ne). Absent or very infrequent recombination reduces Ne, and thus the efficacy of selection against deleterious mutations (Ohta & Kimura 1971), by increasing selective interference from linked loci (Hill & Robertson 1966 Birky & Walsh 1988 McVean & Charlesworth 2000 Marais & Charlesworth 2003 e.g. hitchhiking, background selection). The implication of the inverse relationship between the efficacy of selection against deleterious mutations and Ne is that any factor that reduces effective population size (including but not limited to the consequences of absent or very infrequent recombination) will similarly affect mutation accumulation. Thus, the effects of restricted recombination versus other mechanisms of mutation accumulation may be difficult to tease apart. It is generally assumed that the higher mutation load in the mitochondrial genome and in the asexual nuclear genomes results from a lack of recombination (e.g. Bell 1988 Jansen & de Boer 1998 Stewart et al. 2008). However, the fact is that we do not know which of the factors that can reduce Ne are causal.

We review and synthesize several lines of evidence suggesting that relative to the other aspects of mitochondrial transmission, absent/infrequent recombination may be of less central importance for mutation accumulation than that is often assumed. First, it takes very little recombination to counteract mutation accumulation (Pamilo et al. 1987 Charlesworth et al. 1993 Green & Noakes 1995 Haddrill et al. 2007), and there is mounting evidence for mitochondrial recombination in a variety of taxa (Piganeau et al. 2004 Tsaousis et al. 2005 reviewed in Barr et al. 2005 White et al. 2008). Second, high mutational loads have been documented in the mitochondrial genomes of taxa that have biparental inheritance of mitochondria and/or direct evidence for mitochondrial recombination (Lynch & Blanchard 1998). Third, bottlenecking of mitochondrial genomes during transmission is widespread (Rand 2001), and genetic drift during the bottleneck may be an important factor affecting the mitochondrial genomes that have very different patterns of transmission and recombination (Lynch & Blanchard 1998). What is more, the haploid uniparental inheritance usually associated with the bottleneck renders recombination, to the extent that it occurs between identical genomes, irrelevant to the process of mutational clearance.

Identifying the primary determinants of mutation accumulation in mtDNA is important for several reasons. For one, greater understanding of the extent to which the recombination counters mutation accumulation will help to inform the debate surrounding the selective value of genetic recombination and sexual reproduction. Many argue that recombination and sex are advantageous mainly in clearing deleterious mutations (e.g. Kondrashov 2001). However, others focus on the ability of recombination to facilitate the spread of beneficial mutations (Colegrave 2002), or believe that multiple mechanisms are more likely to maintain sex than any mechanism operating alone (West et al. 1999). Determining whether deleterious mutation accumulation is due to the lack of recombination is of direct relevance to this controversy.

More broadly, both somatic and germ-line mitochondrial mutations are often implicated in human disease and ageing (Linnane et al. 1989 Chinnery & Turnbull 2000 Kujoth et al. 2007). Germ-line mutations in mtDNA are what constitutes ‘mutational load’ and are of particular interest because they are transmitted between generations. It is now clear that differences in the number and effect of germ-line mutations are related to the severity of the disease phenotype and patient lifespan. Germ-line mutations can also exacerbate the deleterious effects of somatic mitochondrial mutations, resulting in premature ageing (e.g. Ozawa 1999). Thus, understanding the factors that lead to the accumulation of germ-line mutations in mtDNA can inform research into disease and ageing.

2. The selective sieve

Lynch (1996, 1997) studied mutation accumulation in mitochondrial and nuclear transfer RNA (tRNA) genes in various animals, plants and fungi, and found that mitochondrial tRNAs generally retained a greater number of mildly deleterious mutations than their nuclear counterparts. Next, Lynch & Blanchard (1998) estimated the ratio of non-synonymous substitutions (dN) to synonymous substitutions (dS) in protein-coding genes from the nuclear and mitochondrial genomes of plants, animals and fungal taxa. dN/dS can be taken as a measure of the efficacy of selection because synonymous mutations are assumed to be largely invisible to selection and to accumulate at a rate that approximates the mutation rate, while the usually deleterious non-synonymous mutations are subject to removal by natural selection (Li et al. 1985). Lynch and Blanchard dubbed dN/dS the ‘selective sieve’, and found that mitochondrial genes had wider selective sieves (i.e. accumulated deleterious mutations at a higher rate relative to the underlying rate of mutation) than nuclear genes in plants, animals and fungal taxa.

Lynch & Blanchard (1998) then used their selective sieve estimates to solve for the selection coefficients against mitochondrial and nuclear mutations, and found that the absolute strength of selection was similar in the two genomes (reviewed in Lynch 2007). This result is consistent with the mitochondrial sequence data showing that mitochondrial mutations are, on average, mildly deleterious (Hasegawa et al. 1998 Lynch & Blanchard 1998 Nachman 1998 Elson et al. 2004). Nevertheless, it is notoriously difficult to directly estimate the distribution of mutational effects, and hence separate the intensity of selection from the efficacy of selection in driving sequence evolution (Lynch 2007).

The data presented in Lynch & Blanchard (1998) are consistently cited as some of the best empirical support for the contention that the absence of recombination will inevitably lead to severe fitness loss due to mutation accumulation in mitochondrial genomes (e.g. Johnson & Seger 2001 Gemmell et al. 2004 Rand et al. 2004 Loewe 2006 also see Rokas et al. 2003). However, Lynch and Blanchard used a post hoc evaluation of their data to tentatively attribute this result to reductions in Ne linked to the uniparental transmission of mitochondrial genomes rather than the absence of recombination (also see Blanchard & Lynch 2000). Specifically, they used the standard diffusion approximation for the fixation probability of a mildly deleterious mutation (Crow & Kimura 1970) to calculate the expected dN/dS in nuclear versus organellar genomes, and showed that the increased dN/dS in organelles could be explained entirely by their different mode of inheritance. Uniparental transmission, when combined with the bottlenecking that characterizes mitochondrial transmission and propagation, will usually render mitochondrial genomes ‘effectively’ haploid (Birky et al. 1983). Since the multiple copies of the mitochondrial genome present within each cell will nearly always be identical (Birky et al. 1983 reviewed in Barr et al. 2005, but see White et al. 2008), recombination will not alleviate mutation accumulation. In this case, it is haploidy rather than a lack of physical recombination that results in effective asexuality for mtDNA, and if physical recombination does occur, mitochondria might be more appropriately viewed as selfers rather than as asexuals (sensu, Charlesworth & Wright 2001).

3. How much recombination does it take to counter mutation accumulation?

If compensatory mutation is rare (Wagner & Gabriel 1990), a complete lack of recombination will ultimately lead to extinction (Charlesworth et al. 1993 Lynch et al. 1993). However, simulation-based studies have found that very little recombination is required to achieve most of its evolutionary benefits (Pamilo et al. 1987 Charlesworth et al. 1993 Green & Noakes 1995 also see Bell 1988).

Charlesworth et al. (1993) simulated recombination along a chromosome of 1000 loci to estimate the amounts of recombination required to halt Muller's ratchet and the drift-catalysed fixation of deleterious mutations. They found that for a population size of (N) <100, a recombination rate equivalent to one crossover per chromosome per 100 generations (10 −5 /locus/generation) effectively countered Muller's ratchet. This is much lower than the minimum of one crossover per chromosome arm per generation that is thought to occur in sexual taxa (Pardo-Manuel de Villena & Sapienza 2001). A higher, but still very low, recombination rate of approximately 10 −4 can impede the selective interference that would otherwise enhance the fixation of deleterious mutations due to genetic drift.

To clarify the difference between genetic drift and Muller's ratchet, we define the process of mutation accumulation as the repeated loss of the class of individuals with the fewest deleterious mutations. In an asexual population, this process is irreversible except by back mutation (Wagner & Gabriel 1990). The loss of the most mutation-free class can occur by two processes: the fixation of mutations at individual loci (which we refer to as drift) and the accumulation of low-frequency mutations at many loci (which we refer to as Muller's ratchet). Recombination can retard both of these processes by increasing the effective population size and the efficacy of selection against the mutations. Under Muller's ratchet, recombination is of added importance because it can always regenerate the least-loaded class. By contrast, fixation due to drift is only affected by recombination during the interval when the mutation is segregating in the population. In large populations, Muller's ratchet and fixation via genetic drift occur more slowly, and even lower rates of recombination will effectively arrest mutation accumulation. Charlesworth et al.'s (1993) results, and our interpretations, are summarized in figure 1.

Figure 1 Results from the simulation study of Charlesworth et al. (1993) investigating the effect of recombination and mating system on mutation accumulation. The accumulation of low-frequency (polymorphic mutations, circles) alleles by Muller's ratchet is particularly sensitive to (a) recombination rate (probability of recombination among adjacent loci/generation), but not (b) mating system (outcrossing rate). The fixation of deleterious alleles by drift (diamonds) is particularly sensitive to mating system. Therefore, testing whether mutation accumulation is more sensitive to mating system or to recombination, per se, gives insight into the relative importance of these two forces. See tables 1 and 4 in Charlesworth et al. (1993), where N=25 and u=0.1.

The theoretical prediction that very little recombination is needed to retard mutation accumulation finds empirical support from a recent study of patterns of sequence evolution in portions of the Drosophila genome (Haddrill et al. 2007). Haddrill et al. (2007) found that genomic regions where recombination is absent (or so low as to be undetected among marker loci along the chromosomes) were characterized by a pattern of sequence evolution consistent with the higher load of deleterious mutations expected under ‘greatly enhanced’ effects of Hill–Robertson selective interference. However, the pattern of molecular evolution in genomic regions of very low recombination rates of approximately 10 −8 /bp/generation was indistinguishable from the portions of the Drosophila genome with the highest frequency of recombination. Assuming that current regions of high and low recombination reflect historical patterns, the similar patterns of molecular evolution observed across a wide range of recombination rates suggest that extremely ‘low’ levels of recombination are high enough to counter mutation accumulation. Such levels of recombination may nevertheless be too low to be detected using the sequence data (Posada & Crandall 2001), as we discuss below.

(a) How much recombination occurs in mitochondrial DNA?

The fact that even very rare recombination might have profound effects on mutation accumulation begs the question of how much recombination actually occurs in mitochondrial genomes. A wide range of taxa have been surveyed for the presence of mitochondrial recombination. Most researchers now agree that plant and fungal mitochondrial genomes undergo occasional recombination involving genetically distinct partners (reviewed in Barr et al. 2005). In particular, yeast mtDNA experiences frequent recombination.

In animal mitochondria, there are clear indications that key components of the recombination machinery are present (e.g. Kajander et al. 2001 Rokas et al. 2003 reviewed in Howell 1997). Direct evidence for recombination has now been documented in several taxa (e.g. Lunt & Hyman 1997 Ladoukakis & Zouros 2001 Burzyński et al. 2003 Kraytsberg et al. 2004), and there is a growing body of indirect evidence for mtDNA recombination in a variety of animal taxa (Piganeau et al. 2004 Tsaousis et al. 2005 reviewed in Rokas et al. 2003 Barr et al. 2005 White et al. 2008), although there are other possible interpretations for these patterns (e.g. mutational hot spots Innan & Nordborg 2002).

(b) Detecting infrequent recombination

There are significant obstacles to obtaining direct estimates of infrequent mitochondrial recombination (White et al. 2008). Indirect estimates are available, which detect the statistical and genealogical effects of recombination in gene trees, but even these tests perform poorly when recombination is very rare (Posada & Crandall 2001). This raises the possibility that even if there is enough mitochondrial recombination to counter mutation accumulation, this level of recombination may be difficult or impossible to detect (Barr et al. 2005).

To illustrate this, consider Posada & Crandall's (2001) estimates of the threshold level of recombination that can be detected from the sequence data. Posada and Crandall used simulations to study the efficacy of 14 different tests for recombination. They defined a population-wide recombination rate occurring at a single locus, ρ, as 4Nrl, where N is the population size r is the rate of recombination per site per generation and l is the sequence length. They found that the most powerful methods detected recombination only 50 per cent of the time when ρ=1, which corresponded to three recombination events in the genealogical history of the sequences. To detect recombination more frequently, say, 80 per cent of the time, ρ needs to exceed four (12 recombination events).

Now consider the rate of recombination among loci, which opposes Muller's ratchet (modelled in Charlesworth et al. 1993). Charlesworth et al.'s (1993) model used a chromosome with 1000 loci represented by points along a line. For a population where N=100, a recombination rate of 10 −5 between adjacent loci per generation is sufficient to counter Muller's ratchet (Charlesworth et al. 1993). If the genealogy has a neutral coalescent time of 2N (=200) generations (Hudson 1990), then a probability of recombination between adjacent loci of approximately 2 −3 (one crossover per 500 loci over the history of the genealogy) opposes Muller's ratchet. If one were to embark on a sequencing study of 1000 bp, located between any pair of loci, there would need to be three recombination events within that stretch of nucleotides over the history of the genealogy to have a 50 per cent chance of detecting recombination (ρ=1 Posada & Crandall 2001). Therefore, a level of recombination that is detectable among contiguous nucleotides will be orders of magnitude higher than the level of recombination required to suppress Muller's ratchet among distant loci.

Sequence data often perform poorly in detecting relevant levels of recombination because recombination across large physical distances can be relevant to mutation accumulation and other evolutionary processes, but will often translate into undetectable recombination rates among adjacent nucleotides. It is therefore critically important to consider the scale of physical distances involved for the question at hand. For example, if we are studying mutation accumulation along an entire chromosome, it would be best to estimate recombination rates using the sequence data from the entire genome, or from non-contiguous nucleotides that span the physical distances over which recombination is more likely to occur. The latter is essentially what is being done in studies that estimate nuclear recombination rates from the marker data (e.g. Haddrill et al. 2007). Alternatively, one might be interested in, say, the possibility that Muller's ratchet operates within a single gene. In this case, Charlesworth et al.'s (1993) threshold rate of one recombination event per 500 loci (or in this instance of a single gene, nucleotides) approaches the detectable level of recombination from the sequence data at this scale. In the present context, the question is whether Muller's ratchet contributes to mutation accumulation in mitochondrial genomes, so that estimates of recombination should use whole-genome sequence data (e.g. Gantenbein et al. 2005 Guo et al. 2006 Ujvari et al. 2007).

The ability to detect relevant rates of recombination also depends upon effective population size. In large populations, the ability to detect rare recombination improves because recombination events are more likely to occur as Ne increases (Posada & Crandall 2001). However, the level of recombination necessary to oppose mutation accumulation decreases with increasing Ne (Charlesworth et al. 1993). Thus, although infrequent recombination becomes easier to detect in larger populations, the threshold level of recombination necessary to counter mutation accumulation is lower. Small populations pose a different problem for detecting recombination. In mtDNA, the relevant effective population size depends on the degree of bottlenecking during mitochondrial transmission, with greater bottlenecking leading to a smaller Ne (Birky et al. 1983 Roze et al. 2005). If the bottleneck during mitochondrial transmission is severe (as is generally the case), low levels of recombination will be especially difficult to detect because the recombining sequences will usually not be divergent enough to identify recombinant progeny. As a logical extension of this last point, recombination becomes not only undetectable, but also irrelevant, if the bottleneck is so severe that the probability of recombination between genetically distinct genomes approaches zero.

In summary, a failure to detect recombination could mean anything from no physical recombination, or no meaningful recombination, to recombination that is sufficient to counter mutation accumulation. Thus, there is really no firm evidence that low recombination is problematic for mitochondrial genomes, even if those genomes appear to be asexual. More rigorous tests of the extent to which mtDNA experiences recombination should involve nucleotides distributed throughout the genome in order to maximize the chance of detecting infrequent recombination.

4. Mutation accumulation and the mitochondrial bottleneck

While mitochondrial and nuclear genomes differ in several important respects, an obvious factor reducing Ne in mitochondrial genomes is their haploid, uniparental transmission (Lynch & Blanchard 1998) and, more specifically, the sharp reduction in mtDNA number that characterizes mitochondrial transmission across a wide variety of taxa (Hauswirth & Laipis 1982 Rand 2001). When and where the bottleneck occurs is the subject of recent debate (Cao et al. 2008 Cree et al. 2008 Wai et al. 2008) the present evidence suggests that both a physical bottlenecking of mitochondrial genomes in primordial germ cells and a genetic bottleneck during post-natal folliculogenesis are responsible (Wai et al. 2008). This bottleneck process culminates in a sharp reduction of the effective number of segregating units of mitochondrial genomes inhabiting a cell (Bendall et al. 1996 Jenuth et al. 1996 Jansen & de Boer 1998 Roze et al. 2005 Wai et al. 2008), rendering the mitochondrial genome effectively haploid (Birky et al. 1983 Jansen & de Boer 1998 Jansen 2000 e.g. Marchington et al. 1998) and reducing the Ne experienced by the mitochondria (Roze et al. 2005).

The expectation that the mitochondrial bottleneck will generate low effective population size has implicated genetic drift during the bottleneck as a causal factor in the high mutation load in mtDNA. For example, Chinnery et al. (2000) highlighted genetic drift due to bottlenecking as a primary explanation for the transmission of deleterious mtDNA mutations in humans (also see Jenuth et al. 1996 Marchington et al. 1998 Brown et al. 2000). Stewart et al. (1996) suggested that bottlenecking might underlie the high rate of substitution in male mitotypes relative to female mitotypes in bivalve species with doubly uniparental inheritance (also see Ort & Pogson 2007) because males experience a more severe bottleneck in mitochondrial number during sperm formation.

By contrast, others have suggested that the mitochondrial bottleneck acts to oppose mutation accumulation by increasing the variance between cells within organisms, or between organisms within populations, thus increasing the efficacy of selection against deleterious mutations (Hauswirth & Laipis 1982 Takahata & Slatkin 1983 Bergstrom & Pritchard 1998 Jansen & de Boer 1998 Krakauer & Mira 1999 Rispe & Moran 2000 Roze et al. 2005 Rand 2008 Stewart et al. 2008 White et al. 2008). There is recent empirical evidence that this type of mechanism can promote the selective elimination of deleterious mitochondrial mutations during oocyte maturation (Fan et al. 2008 Shoubridge & Wai 2008 Stewart et al. 2008).

How the mitochondrial bottleneck ultimately affects the efficacy of selection is of fundamental importance for understanding the mutation accumulation in mitochondrial genomes. If the net effect of the bottleneck is to reduce the efficacy of selection (and increase dN/dS) relative to the nucleus, then it may contribute to the higher mutation load observed in mitochondrial genomes. Instead, if the net effect of the mitochondrial bottleneck is to increase the efficacy of selection in mitochondrial genomes, then the observed patterns of molecular evolution must be due to some other mechanism, and occur despite the net ‘positive’ effects of the bottleneck during transmission.

There are several reasons to believe that this bottleneck is ultimately a contributor to the high mutation load in mtDNA. For one, there is evidence that many phenotypically important mitochondrial mutations escape the bottleneck to segregate at the organismal level (Taylor & Turnbull 2005 Fan et al. 2008 Shoubridge & Wai 2008 Wai et al. 2008). In addition, simulation models indicate that bottlenecking does not increase the efficacy of selection once bottlenecks exceed approximately 20 segregating units (see fig. 5 in Bergstrom & Pritchard 1998), which is smaller than many estimates of bottleneck size (Rand & Harrison 1986 Bendall et al. 1996 Jenuth et al. 1996 Gocke et al. 1998 Cree et al. 2008). Another simulation study used a multilevel selection approach to determine how the selection and drift of mitochondrial mutants are affected by bottlenecks that simultaneously reduce Ne and increase opportunities for selection within and between cells (Roze et al. 2005). They found that the Ne-reducing effect of the bottleneck more than offset the increased efficacy of selection, such that the net effect of the bottleneck was to increase the rate of fixation of deleterious alleles and decreased the rate of fixation of advantageous alleles (Roze et al. 2005).

The data from taxa that experience frequent mitochondrial recombination also point to the mitochondrial bottleneck, rather than uniparental transmission or the absence of recombination, as the root cause of high mutation load in mitochondrial genomes. For example, the mitochondrial genome in the yeast Saccharomyces cerevisiae recombines freely and is biparentally inherited, but nevertheless has a high mutation load relative to the nuclear genome (Lynch 1997 Lynch & Blanchard 1998). One possible explanation for this observation could be the mating system: Saccharomyces yeasts are predominantly selfing (Field & Wills 1998 Johnson et al. 2004), which is expected to increase genomic mutational load (Charlesworth & Wright 2001) relative to biparental inheritance from unrelated individuals (Charlesworth 2003 Glémin 2007 see below). For yeast, however, selfing should increase the selective sieve for both the mitochondrial and the nuclear genomes, since both genomes have the capability for regular biparental transmission. More likely, the example of yeast points to the importance of the mitochondrial bottleneck and vegetative segregation during the rounds of cell division. These combine to result in effectively haploid mitochondrial transmission, even though physically it is biparentally inherited (reviewed in Birky 2001).

In summary, the current body of theory and the data suggest that the mitochondrial bottleneck exacerbates the fixation of deleterious mutations via drift. The high mutational load in yeast illustrates specifically why this bottleneck reduces effective population size relative to the nucleus. The nuclear genome of eukaryotes is transmitted in just two copies in each cell generation, and into each zygote, but mitosis and meiosis ensure that one copy is dutifully retained from each parent. Thus, the nuclear genome is diploid. The mitochondrial bottleneck is superficially less severe in the sense that more genome copies are transmitted from one generation to the next, but without a fair meiosis/mitosis, selection or drift among those genome copies within cell lineages results in haploid inheritance (Birky 2001). Additional empirical research following the dynamics of mitochondrial mutations within and between cells (e.g. Taylor et al. 2002 Roze et al. 2005 Rand 2008 Shoubridge & Wai 2008 Stewart et al. 2008) may clarify the distinct genetic and evolutionary processes that influence mitochondrial genomes.

5. Mating system, effective population size and mutation accumulation

A promising way to investigate what forces affect Ne and drive mutation accumulation is to consider how the Ne experienced by nuclear genomes varies among taxa with different mating systems (Birky et al. 1983 Pollak 1987 Birky & Walsh 1988 Nordborg 2000 Charlesworth & Wright 2001 Butlin 2002 Glémin et al. 2006 Glémin 2007). It would be especially informative to identify the patterns of nucleotide substitution in nuclear genomes under circumstances where they should accumulate mutations differently than their mitochondrial counterparts, and compare these patterns to situations where the nuclear genome should experience the same Ne, or recombination rate, as the mitochondrial genome.

In outcrossing hermaphrodites, a twofold difference in Ne is expected between mitochondrial and nuclear genomes (fourfold for outcrossing dioecious species Birky et al. 1983). In highly selfing species, nuclear recombination occurs, but the difference in Ne between nuclear and mitochondrial genomes is expected to be sharply reduced. This is, in large part, due to the decrease in efficacy of recombination caused by increased homozygosity in the nuclear genome (Nordborg 2000 Charlesworth & Wright 2001). By contrast, the Ne experienced by a uniparentally inherited mitochondrial genome should be less affected by selfing unless hitch-hiking effects are extreme (Charlesworth 2003 Glémin 2007). The nuclear genome of asexual species should also experience reduced Ne relative to the nuclear genome in sexual species owing to the increased likelihood of hitch-hiking and background selection when recombination is absent (Hill & Robertson 1966).

Although theory indicates that the increase in homozygosity that accompanies selfing can promote mutation accumulation via the reduced efficacy of recombination (Heller & Maynard Smith 1979), simulations demonstrate that it only takes a small amount of outcrossing to counter mutation accumulation in largely selfing populations (Pamilo et al. 1987). Moreover, other simulations show that the sharp reductions in fitness due to mutation accumulation in small selfing populations are more a consequence of restricted outcrossing than limits upon recombination (Charlesworth et al. 1993). We take these results to mean that mutation accumulation in highly selfing populations should be linked to reductions in Ne due more to uniparental reproduction than to restricted effects of recombination. In this context, it is not the presumed asexuality of mitochondrial genomes that is responsible for their high mutation load, but the mechanism of inheritance that essentially turns mitochondria, to the extent that they are ‘sexual’, into selfers.

Following this logic, the width of the selective sieve in the mitochondrial and nuclear genomes should become more similar in selfing species if reduction in Ne, unrelated to recombination, is the crucial determinant of mutation accumulation for both genomes (also see Charlesworth 2003). By contrast, if the nuclear and mitochondrial selective sieves are more similar in asexual species than in selfing and outcrossing species, the lack of recombination must play a central role in mutation clearance.

Evaluating these alternatives requires nuclear and mitochondrial genomic data from closely related taxa that vary in mating system. This type of mating system variation is common in some taxa, such as freshwater snails (Jarne & Städler 1995) and many groups of angiosperms. Although these data are not currently available (Charlesworth & Wright 2001 Charlesworth 2003 Glémin 2007), several studies suggest that processes of molecular evolution (including mutation accumulation) in mitochondrial and nuclear genomes may be more similar in selfing than outcrossing taxa (Weinreich & Rand 2000 Graustein et al. 2002), and in recombining versus non-recombining sections of the nuclear genome (Comeron et al. 1999 Munte et al. 2001 Navarro-Sabaté et al. 2003 Haddrill et al. 2007). Moreover, when closely related sexual and asexual taxa are compared, asexuals (‘effectively asexual’ in the case of the endosymbionts studied in Moran 1996 Woolfit & Bromham 2003) suffer increased retention of deleterious nuclear (Normark & Moran 2000) and mitochondrial (Moran 1996 Woolfit & Bromham 2003, 2005 Paland & Lynch 2006) mutations relative to their sexual counterparts.

Taken together, these studies provide preliminary support for the hypothesis that both the mating system and the presence of recombination are important determinants of mutation accumulation, and that such effects can be parsed out with the appropriate data. This would provide an important test of how reduced recombination and uniparental/haploid transmission combine to explain differences in dN/dS in nuclear versus mitochondrial genomes. Such a test would clarify the fundamental evolutionary mechanisms responsible for mutation accumulation in eukaryotic genomes, and how those mechanisms are affected by the inheritance and recombination of those genomes. Understanding the factors underlying the high mutation load in mtDNA also has applied significance, in the light of the links between mitochondrial mutation, human disease and ageing.

Microbiologists have long recognized that the uptake and incorporation of homologous DNA from outside the cell is a common feature of bacteria, with important implications for their evolution. However, the exact reasons why bacteria engage in homologous recombination remain elusive. This Opinion article aims to reinvigorate the debate by examining the costs and benefits that homologous recombination could engender in natural populations of bacteria. It specifically focuses on the hypothesis that homologous recombination is selectively maintained because the genetic variation it generates improves the response of bacterial populations to natural selection, analogous to sex in eukaryotes.

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Analysis of isozyme variation in three species of psychid moths revealed that the genetic diversity of the sexual species D. charlottae and S. rupicolella is higher than that of the asexual species D. fennicella. Allele richness, gene and genotypic diversity were also higher in the sexual species than in the asexual species. Higher genotype diversity in sexual than in asexual populations is most likely the logical result of recombination and was an expected result. The sexual populations also showed higher allele diversity, which is a more intriguing outcome [30]. One possible explanation for this difference is that the asexual lineage retained only a portion of the diversity of its sexual ancestor. Alternatively, a lower per locus diversity in the asexual species could reflect lower population sizes compared to the sexual species. Asexual D. fennicella is, in general, rarer than the sexual species, although it was the most abundant species in some locations. A lower population size is also suggested by the higher differentiation (FST) among D. fennicella populations than among sexual populations.

Surprisingly, parthenogenetic D. fennicella showed a considerable amount of genotype diversity, with 65 different genotypes detected among 86 individuals. This was in contrast with a previous analysis with allozyme markers which found limited diversity among samples of D. fennicella [39]. This amount of genotype diversity was higher than that recently observed in Potamopyrgus snails [20] and that reported in animals (reviewed in[40]) and in plants (reviewed in [41]) in the previous allozymes literature. Interestingly, clonal lineages of D. fennicella were mostly restricted to single populations. Only two genotypes were shared among distant populations. The lack of a common broadly adapted haplotype spread over different populations is in conflict with the hypothesis of the general-purpose-genotype [42]. Instead, adaptation to different microclimates or other specific environmental conditions of these locales could explain the presence of many different genotypes, as suggested by Vrijenhoek's [43] frozen niche variation hypothesis. However, we found no significant differences in morphology, size and life-history characters between two different D. fennicella populations that would reflect ecological specialisation [34]. Although several studies have reported allozymes as not neutral (reviewed in [44, 45]), in our study there were no indications that they deviate from neutrality, thus these markers are expected to be subjected more to drift than to selection. High genotypic diversity could indicate the presence of cryptic sex in the parthenogenetic species. Although we cannot completely rule out this hypothesis, we never observed sex in the species. All parthenogenetic females lay eggs immediately after hatching from pupa and never show the characteristic behaviour of sexual females when they secrete pheromones to attract potential mates (Kumpulainen et al. 2004). Moreover, mitochondrial sequences from sexual and asexual females clearly indicate these are two different species (Grapputo et al. 2005). This high genotypic diversity could also be explained by alternative types of parthenogenesis involving recombination, such as the automictic thelytoky [46].

High clonal diversity and the observed distribution of different clones could be the result of a restricted dispersal capacity and the fragmentation of suitable habitats for these psychid moths. Large differentiation was also observed among populations of diploid parthenogenetic D. triquetrella in the Alps but not among tetraploid populations of the same species in Finland [47]. The same pattern, however, could be explained by an extinction-colonisation process associated with a long persistence of the populations, which would explain the high intrapopulation diversity. Large genetic differentiation among populations was also observed in both the sexual species, D. charlottae and S. rupicolella, which is consistent with their extremely low ability for active dispersal (see also [31]) and the patchy distribution of suitable habitats. Nevertheless, psychid moths sometimes colonise new areas as suggested by the absence of D. charlottae in the Isosaari population in 1999 and its presence in 2000 (T. Kumpulainen, personal observation). Most probably, dispersal between different populations is a relatively rare event taking place as passive aerial dispersal of very small larvae [31]. The large genetic differentiation among D. charlottae and S. rupicolella populations is in contrast with the data obtained for populations of sexual D. triquetrella in the Alps by Lokki et al[47], where allelic frequencies were described as homogeneous among populations, although rigorous tests of population differentiation were not carried out.

The observed proportion of heterozygotes was not different between the two sexual species D. charlottae and S. rupicolella (0.29) and was very similar to that previously observed in another sexual species D. triquetrella (0.23) [47]. The level of heterozygosity was also highly similar among populations in both sexual species. D. charlottae and S. rupicolella, in contrast to D. triquetrella, were not in HW equilibrium for most of the loci and populations. Heterozygote deficiency has been widely reported in allozyme surveys of natural populations of marine invertebrates (reviewed in [48, 49]) and also in fishes (e.g. [50, 51]), amphibians and reptiles (reviewed in [52]). Alternative hypotheses have been advanced to explain such heterozygote deficiencies [48, 49, 53]. The high heterozygosity deficiency in all three species of bag worm moths could be explained by null alleles. The high variation across loci in FIS values correlate among species and the methods of Brookfield [38] for the calculation of null alleles frequencies strongly suggest that most of the loci in the three species are affected by null alleles. Most populations of sexual psychid moths are small, consisting of just 30 to 100 individuals. Suitable forest patches are also small and isolated. Moreover, females are apterous and unable to disperse. When sexual females emerge from pupae they quickly start to secrete pheromones to attract males. Once emerged, males respond promptly to the female pheromones because they have a very short adult life span (about 10 hours). Therefore, copulation most likely occurs between emerging adults that are both spatially and temporally close. This could create substructured populations and a Wahlund effect, both spatial and temporal, which could maintain a high number of alleles in the population but increase the homozygosity [54].


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Does recombination slow mutation accumulation in sexual populations? Is there any evidence? - Biology

In spite of the number of ways bacteria can exchange genetic instructions, many of them haven't evolved very far — not as bacteria anyway. There are many modern bacteria that look very similar to fossils of the earliest bacteria of over 3 billion years ago. Eukaryotes are much better at evolving than prokaryotes. Eukaryotes first appeared on Earth about 1.7 billion years ago. Eukaryotic cells contain complex subunits, some of which — mitochondria and plastids — have their own DNA. With the appearance of eukaryotes, evolution began to accelerate. All multicelled animals and plants are made of eukaryotic cells. Where did they come from?

Eukaryotes by Symbiosis

Research biologist Lynn Margulis has finally won acceptance for the theory that eukaryotic cells formed by symbiosis among bacterial cells. Under the theory Margulis advocates, mitochondria and plastids did not originate within the eukaryotic cells that now carry them. Rather, these subunits were once free-living prokaryotic cells that infected other bacterial cells and came to reside in them with benefits for both parties. Even the bounded nucleus that characterizes all eukaryotic cells may have evolved this way. This is a whole new kind of evolution. Not just new genes, but new whole cells were incorporated into existing cells. This kind of evolution has already been confirmed by experiment (2). This theory represents a significant amendment to the prevailing paradigm of evolution. Now we know that evolution can proceed by assembling subunits. This mechanism would help evolution to take the giant step from prokaryotes to eukaryotes relatively quickly.

This symbiotic system has an additional consequence — as evolution proceeds, genes originally in the mitochondria and plastids apparently tend to be lost. In May, 1998, molecular biologists who analyzed 210 protein-coding genes from nine fully sequenced chloroplast genomes reported, "Some of these genes have been lost altogether. whereas others have been transferred to the nucleus. We have documented 44 bona fide cases of functional plant nuclear genes among the 210 genes examined . " (2.5). If mitochondria and plastids tend to lose genes, one can reason backward to a time when they had genomes as large as free-living bacteria do. This evidence strengthens the case for the symbiotic evolution Margulis advocates. And if some of those genes are transferred to the nucleus, we have another mechanism for importing whole genes into the nuclear genomes of eukaryotes.

If you had to name one development in all of evolution that was the most important single development, it would definitely be the evolution of eukaryotic cells. This step is apparently the prerequisite for any more highly organized forms of life to evolve. That the mitochondria and plastids in eukaryotes probably got there by symbiosis is a welcome insight. But we still have many other steps to explain. How did the structural system within eukaryotic cells evolve? How did eukaryotes evolve into a multitude of species with the wide variety of features they have? How do multicelled eukaryotes acquire new complex features? Where do the new genes for these steps come from? How do they get installed and activated?

Viruses and The Origin of Species

Charles Darwin named his greatest work The Origin of Species. Of course, the species is only one level of biological hierarchy. Darwin could have named his book The Origin of Phyla or The Origin of Kingdoms. A species is defined by being reproductively isolated from every other species. Darwin was able to see that if a sexually reproducing animal or plant were ever to take a an evolutionary step big enough to create a new species, it would be necessary for at least a complete breeding pair — one male and one female — to take the step simultaneously. If only one member of a breeding pair, say the female, acquired a speciating new feature, she would be reproductively isolated from the male. They would be unable to reproduce.

Sometimes new species can be produced by hybridization: closely related species can produce hybrid offspring that are able to sexually reproduce with other, similarly produced hybrids but not with members of either of the parents' species. Hybridization alone cannot, however, produce new features it can only add existing ones together.

Today, with our understanding of DNA, we would state the problem differently: new features require new genetic instructions. And small steps are clearly possible without coordination between two members of a breeding pair. But big, speciating steps are still problematic for neo-Darwinism. If only one individual undergoes a mutation of speciating effect, the remaining population is either unable or unlikely to follow this "hopeful monster."

However, if new genetic instructions are inserted by infectious viruses, then the problem of finding breeding pairs equipped for big evolutionary steps is solved. Viruses typically infect whole populations, or substantial parts of them, so many breeding pairs may carry the same new instructions. This is a profound new way for evolution to advance, and in potentially larger steps than Darwin imagined. This proposed mechanism for evolution was already understood by the farseeing genetic researcher Susumo Ohno in 1970. He wrote (3):

The Germ Line

If new genetic programs are as common as viral infections, wouldn't they be more likely to wreak havoc than to improve things — especially in the larger animals and plants, for whom the genome is more complicated and individuals are less expendable? For example, suppose the genetic programs for antlers or antennae got installed and activated in people. That would cause a real-life horror show. The evolutionary world would be much better if each virus infected only a narrow range of hosts. Fortunately, that is how viruses usually work. With a few exceptions, each virus infects only one species or group of closely related species. But there are important exceptions to this rule. For example, arboviruses have two classes of carriers, vertebrate and invertebrate. Sometimes one class of host may not become infected, but usually both do. Over 500 arboviruses are known (4).

Some viruses infect their hosts with no harm to the host. Other viral infections can cause diseases, occasionally lethal ones. One wishes the immune system would keep them out completely. But if evolution depends on viruses, that capability would inhibit evolution. The situation is especially complex in sexually reproducing multicelled animals, where the "germ line" is carefully protected. The germ line, the gametes and their ancestral cells that give rise to the next generation, are isolated early in the life cycle from the rest of the (somatic) cells. In order for a virus to cause evolution in sexually reproducing creatures, it must infect the germ line and become integrated into the genome there. This process has been proven to occur already. "If, for example, the DNA is injected into the nucleus of a mouse's fertilized egg, the genes will be found in many cells of the adult animal and sometimes even in its germ cells" (5). And the descendants of newborn mice infected with a virus have been shown to carry the genes of the infecting virus in their own genomes (6). Also, "When DNA from a retrovirus is inserted into fetal lambs, their offspring inherit the retroviral DNA — a clear sign that the foreign genes had entered the sheep germline" (7). Furthermore, we now know that such insertion can happen in nature at a rate approaching one entire viral genome per host generation (8). By the time the textbook Retroviruses was published, in 1997, this question is settled. ". Retroviruses can become integrated into the germ line as endogenous viruses, leading to permanent genetic consequences for the descendents of the original host, a property they share with a variety of nonviral, but related, reverse-transcriptase-containing elements. " (9).

To accomplish this integration in nature the virus probably would have to spread by lytic infection throughout much of the body. This process will probably have side effects that may appear as symptoms of disease. Perhaps it would be a reasonable compromise if a new virus were able to establish a lytic infection and become widespread within the individual host's body one time only, and never again. Guess what. That's the way our mammalian immune system often handles viruses.

Sometimes retroviruses cause other genes in the host's genome to become "oncogenes" (10). That means they cause cancer. If evolution involves trial and error, cancer seems to be in the error category. However, perhaps it would make evolutionary sense, under some circumstances, for cells carrying newly acquired genes to begin to multiply rapidly.

Cosmic Ancestry assumes that the function of a virus is to install its genes into the germ line of its host. After this mission has been accomplished, it serves no purpose for the host to remain susceptible to lytic infection by the virus. It would make sense if the host's descendant inheriting the new genes were born with immunity to lytic, or disease-causing, infection by the virus.

In fact, it has been known since 1933 that resistance to a disease caused by a virus can be inherited (11). Now there is some reason to believe that even resistance to AIDS may be inheritable. AIDS is an incurable viral disease to which, we once thought, no one is immune. Studies are now suggesting, however, that some children of mothers with AIDS are born immune to the disease. This is the subject of a recent [1996] story in Science, "Can Some Infants Beat HIV?" (12)

Gene Conversion

The Cosmic Ancestry paradigm proposes that the genetic instructions for big evolutionary steps are installed by viruses or other lateral transfer mechanisms, and that some of the steps require several genes — so many that they could hardly be installed all at once but more easily in stages. During the installation process, the not-yet-activated DNA would be silent. To be useful in the future, this silent DNA would need protection against the accumulation of errors.

Among the working genes of sexually reproducing creatures, gene conversion can alter one version of a gene to match the other version. Thus, a defective gene can be edited to match the nondefective version of the gene (12.5):

So if an error develops in one copy of the gene, the process of gene conversion could compare it to the undamaged copy and fix it. In the above example, gene conversion has been demonstrated for working genes. Is there any reason to think that gene conversion also works on silent DNA? Yes. There is indirect evidence based on an otherwise unexplained similarity between silent DNA in humans and mice (13):

The last common ancestor of humans and mice died at least 80 million years ago. Somehow the silent DNA has been maintained over many millions of replications. Gene conversion could be the mechanism. Something is.

If gene conversion works for silent DNA, it becomes possible for very large genetic programs to be installed in stages, without loss of fidelity. The parts installed first would be silent until the whole program had been installed. With gene conversion, this silent part could get continually debugged. The process of gene conversion could clean it up, as necessary, every time it is replicated. Thus, when the whole new genetic program is fully installed and ready to activate, it would be far more likely to be fully functional. The process of gene conversion could make it possible to install big genetic programs in pieces, over many generations.

Additional evidence for the longterm maintenance of silent genes comes from research on certain "retrotransposons" by biologists at The University of Rochester. They studied two related sequences that have remained stable in diverse lineages for over 500 million years. The sequences are always inserted at the same two precise locations in a certain (28S rRNA) gene, inactivating it. "How then do we account for their remarkable stability?" they wonder (14).


Evolution can proceed by the assembly of subunits.
New genes can get installed into whole species by infectious agents, especially viruses.
Viral infections are usually specific to certain hosts only, they are not always harmful to the host, they can enter the germline, and the host can become immune to their harmful effects.
The process of gene conversion can correct deleterious mutations even in silent genes, where natural selection and gene dominance are useless. Gene conversion could protect large genetic programs requiring several generations to install. Thus sex would be important because it increases the fidelity, not the mutability, of inherited genes. Indeed, a clever recent experiment with sexual and asexual yeast cells that were otherwise identical reinforces this last point. Clifford Zeyl of Michigan State University and Graham Bell of McGill University found that both the sexual and asexual populations produced mutations at similar rates, but the sexual cells eliminated deleterious mutations more efficiently (16). And yet another experiment, with viruses, affirms that sex prevents the accumulation of deleterious mutations " because recombination lets an organism reconstruct a mutation free genome from two genomes that contain different mutations " (17).
It seems likely that the sexual reproduction process used by multicelled animals and plants is more important than the current paradigm imagines. It is a likely prerequisite for really big evolutionary steps.

Watch the video: Γιατί να γνωρίζει κάποιος αν έχει κληρονομική προδιάθεση καρκίνου μαστού;. Όμιλος Υγεία (May 2022).


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