New Preprint: Selective sweeps under dominance and self-fertilisation

A preprint of my latest manuscript, “Selective sweeps under dominance and self-fertilisation”, is now available on bioRxiv. This work (carried out with Thomas Bataillon) continues my long-standing interest in investigating the mechanisms of adaptation under different reproductive modes. This preprint outlines how the genetic signatures of different adaptive events (for example, whether beneficial mutations arose from new mutation, or from standing variation) are altered by (i) dominance, which is a measure of the fitness effects of individuals carrying one copy of the adaptive gene, compared to the fitness of individuals with two copies; and (ii) self-fertilisation, where individuals can produce both male and female sex cells that are capable of fertilising one another. We show how both these effects impact upon signatures of selection, as well as how to differentiate between scenarios that may produce similar signatures.

You can download the preprint here, with the abstract given below:

A major research goal in evolutionary genetics is to uncover loci experiencing adaptation from genomic sequence data. One approach relies on finding ‘selective sweep’ patterns, where segregating adaptive alleles reduce diversity at linked neutral loci. Recent years have seen an expansion in modelling cases of ‘soft’ sweeps, where the common ancestor of derived variants predates the onset of selection. Yet existing theory assumes that populations are entirely outcrossing, and dominance does not affect sweeps. Here, we develop a model of selective sweeps that considers arbitrary dominance and non-random mating via self-fertilisation. We investigate how these factors, as well as the starting frequency of the derived allele, affect average pairwise diversity, the number of segregating sites, and the site frequency spectrum. With increased self-fertilisation, signatures of both hard and soft sweeps are maintained over a longer map distance, due to a reduced effective recombination rate and faster fixation times of adaptive variants. We also demonstrate that sweeps from standing variation can produce diversity patterns equivalent to hard sweeps. Dominance can affect sweep patterns in outcrossing populations arising from either a single novel mutation, or from recurrent mutation. It has little effect where there is either increased selfing or the derived variant arises from standing variation, since dominance only weakly affects the underlying adaptive allele trajectory. Different dominance values also alters the distribution of singletons (derived alleles present in one sample). We apply models to a sweep signature at the SLC24A5 gene in European humans, demonstrating that it is most consistent with an additive hard sweep. These analyses highlight similarities between certain hard and soft sweep cases, and suggest ways of how to best differentiate between related scenarios. In addition, self-fertilising species can provide clearer signals of soft sweeps than outcrossers, as they are spread out over longer regions of the genome.


Digest: Effects of spatially‐spreading adaptive mutations on genome‐wide diversity

I recently wrote a digest for Evolution, “Effects of spatially‐spreading adaptive mutations on genome‐wide diversity“. Here I summarised Allman and Weissman’s paper “Hitchhiking in space: Ancestry in adapting, spatially extended populations“, which modelled how genetic diversity is affected by beneficial mutations spreading out over a spatial region. Due to this effect, neutral variation sampled at the edge of a population’s range would have mostly originated at its centre, demonstrating a scenario where the effects of adaptation and spatial structure on genetic diversity have become intertwined.

You can read my summary here; check out Allman and Weissman’s paper here.

New Preprint: The Facultative Sex Coalescent with Crossing Over Recombination and Multi-Site Gene Conversion

I have submitted a new preprint to bioRxiv, “The Facultative Sex Coalescent with Crossing Over Recombination and Multi-Site Gene Conversion”. Building on previous single-site models, this research investigates how different types of genetic exchange (meiotic recombination, gene conversion) affects linkage disequilibrium (how genetic sites are correlated along a genome) in facultative sexual organisms, which alternate reproduction between biparental sex and asexuality. These results can be used to infer these phenomena from genome sequence data.

You can download the preprint here. I have also published the simulation code used in the analyses, along with documentation. The Facultative Sex Coalescent program is available from GitHub here.

Below is the abstract:

The extent of correlations between loci, as measured by linkage disequilibrium, is commonly used to infer the effect of different types of gene exchange. It can also provide information on rates of sex in facultative sexual organisms, as meiotic crossing over occurs during sexual reproduction. In addition, recent theoretical and empirical work has provided evidence that gene conversion shapes genetic diversity in facultative sexuals. Here we outline computational models of a facultative sexual coalescent process that includes both crossover recombination and multi-site gene conversion, to determine how linkage disequilibrium is affected with facultative sex. We demonstrate that the decay in linkage disequilibrium scales with the rate of sex if it is sufficiently high, indicating that linkage disequilibrium data can be potentially used to deduce rates of sex from genome data. With very low rates of sex, mitotic gene conversion both breaks down associations between alleles and removes within-individual diversity. The two combined effects produce complex linkage disequilibrium patterns. Furthermore, strong population structure and low rates of sex lead to lower average linkage disequilibrium values than those in panmictic populations, due to the influence of low-frequency polymorphisms created by allelic sequence divergence arising in individual subpopulations. These analyses provide information on how to interpret observed linkage disequilibrium patterns in facultative sexuals, and determine what genomic forces are likely to shape them.

New paper: The Evolutionary Interplay between Adaptation and Self-Fertilization


An Arabidopsis thaliana rosette, one of the most extensively studied self-fertilising plants. Picture from Wikimedia Commons.

I’m excited to announce a new review paper, “The Evolutionary Interplay between Adaptation and Self-Fertilization“, recently published in Trends in Genetics.

One of my long-standing research interests is investigating how self-fertilisation (fertilisation of male and female sex cells that are produced by the same individual) affects the fixation of adaptive mutations in a population. To this end, myself, Sylvain Glémin and Thomas Bataillon have reviewed how self-fertilisation and adaptation interact with each other. After providing an introduction of the basic concepts concerning how self-fertilisation affects beneficial genes, the review focuses on three main points:

  1. Self-fertilising species have different adaptation rates. Self-fertilisation can lead to offspring inherting genes from just one parent, as opposed to two under biparental sex. This inheritance mode can create highly uniform genomes, weakening how selection acts on individual mutations, and diminishing the ability for recombination to create new genotypes. (I have previously carried out theoretical investigations on the impact of this reduced effective recombination rate on genetic evolution. For example, self-fertilisation can make it likelier for deleterious mutations to fix with adaptive mutations, or for competing beneficial variants to be lost).
  2. Alterations in how adaptation affects genetic diversity. As adaptive mutations fix, so does any neutral variation lying close to it. This creates a distinctive reduction in genetic diversity around adaptive variants, called a ‘selective sweep’. Self-fertilisation can alter these sweep patterns. Furthermore, changes in a species’ population size can skew signals of genetic adaptation; this effect can be more pronounced under this reproductive mode, so the two outcomes have to be disentangled.
  3. Polygenic adaptation, where traits are affected by multiple interacting genes, is also affected by self-fertilisation. This mating system can rapidly create genotypes exhibiting extremely high (or low) characteristics, such as height or weight. These extremes may respond more quickly to selection in the short-term, but new genetic combinations may not be as easily created in the long-term.

You can read the (open-access!) paper here. Here’s the abstract:

Genome-wide surveys of nucleotide polymorphisms, obtained from next-generation sequencing, have uncovered numerous examples of adaptation in self-fertilizing organisms, especially regarding changes to climate, geography, and reproductive systems. Yet existing models for inferring attributes of adaptive mutations often assume idealized outcrossing populations, which risks mischaracterizing properties of these variants. Recent theoretical work is emphasizing how various aspects of self-fertilization affects adaptation, yet empirical data on these properties are lacking. We review theoretical and empirical studies demonstrating how self-fertilization alters the process of adaptation, illustrated using examples from current sequencing projects. We propose ideas for how future research can more accurately quantify aspects of adaptation in self-fertilizers, including incorporating the effects of standing variation, demographic history, and polygenic adaptation.

The Improbability Principle

In my last blogpost, I touched on how chance and probability are major drivers of evolutionary phenomena. Around the same time I found “The Improbability Principle” by David Hand in the university library, a book that in part discusses the lottery of evolution.

If you’re first thought upon reading that intro was “That’s a strange coincidence!” then this book is for you. Hand, a Professor of Statistics at Imperial College London, uses his life-long expertise of statistical modelling to explain why seemingly improbable events occur with surprising regularity. Lotteries provide a good example of highly unlikely yet frequent events. Evelyn Marie Adams won the jackpot on the New Jersey State lottery twice; once in 1985, and again in 1986. Impossible? Then consider Maurice and Jeanette Garlepy of Alberta who won the jackpot the Canadian Lottery twice; the probability of that outcome is one-in-200 trillion. If dreams are more your cup of Earl Grey, then what explains déja vu, that strange feeling we sometimes get that we’ve lived through something before? Are these flashbacks just freak events, or the inevitable outcomes of each of us doing the same tasks, meeting the same people on a daily basis?

After a series of chapters outlining the basics of statistics and probability calculations, Hand offers five ‘laws’ to explain why seemingly impossible events arise with startling regularity. What could have been a dry book on statistical methods is instead a breezy and frivolous lesson on the roles probabilities play in our day-to-day lives, with each case richly illustrated using fun anecdotes. The five laws are:

  • The law of inevitability: Put simply, something has to happen. Your personal chance of winning the National Lottery is vanishingly small, but someone usually wins every week due to the amount of people who play. Similarly, there’s…
  • The law of truly large numbers: Given enough opportunities for something implausible to happen, it will happen. In 2010 a dog accidentally shot its owner after it stepped on his shotgun. A far-fetched story? Yet As Ben “Bad Science” Goldacre pointed out, two similar cases were reported in 2007, as well as in 2004. The world has plenty of dogs and guns, so puppycide will occur.
  • The law of selection: You can make anything implausible seem inevitable if you state what you’re looking for after the event. Abraham Lincoln apparently dreamed that he was going to be assassinated a week before it happened. Yet how many other people have predicted their own death, but then lived a long life? What about those who foresaw the end of the world, then moped that they had ‘miscalculated’ when we all happily survived?
  • The law of the probability lever: A slight change in circumstances can have huge impacts on predicted outcomes, making improbable events much more likely. Possibly the most infamous example of this law was used in the Sally Clark trial, a solicitor whose two children died young. Clark argued that both children died from natural causes (‘cot death’). The prosecution claimed that the probability of such an event was 1 in 73 million, and Clark was subsequently convicted of murder. However, the prosecutor’s calculation makes the erroneous assumption that each death was an independent event. In reality, if one cot death occurs in a family, subsequent deaths are much more likely so the 1 in 73 million claim is a gross overstatement. Clark was jailed for three years before her wrongful conviction was overturned.
  • The law of ‘near enough’: Did you predict an unlikely event, but it didn’t arise? You can still claim it happened if something similar materialised instead. It’s exceedingly unlikely for someone to win a lottery jackpot twice, but how many compulsive gamblers have won two lesser prizes?
Modified by CombineZP

A bluebottle with compound eyes. Photo from Wikipedia Commons.

One of the fascinating aspects of evolutionary theory is that formation of complex adaptations essentially follows these laws. How did the eye, which started off as light-sensing proteins in unicellular bacteria, evolve into the complex camera-organ that all humans carry? If the rudimentary light-detecting organism were left to mutate by chance then it would be incredibly unlikely to form a complex eye. Natural selection however greatly skews these odds.

Consider a rudimentary bacterium, whose ‘eye’ was a collection of light-sensing proteins. This bacterium will reproduce many times, and eventually some offspring will be produced that will carry more developed ‘eyes’ (a variant of ‘the law of truly large numbers’). These individuals would be more able to survive, so these evolved eyes will persist in nature; rather aptly, this rule is an application of ‘the law of selection’. Repeat this process for millions of years (‘the law of truly large numbers’ in action, again) and eyes will eventually evolve into their complex modern forms. It seems that the Improbability Principle is living and breathing all around us in our natural world.

“On the origin of asexual species by means of hybridisation and drift”

My new commentary piece has just been published in the latest issue of Molecular Ecology. It’s a summary of a paper by Ament-Velásquez et al. on the origin of asexual Lineus ribbon worms.

A prediction for detecting highly asexual organisms is that each gene copy in a diploid species should become extremely divergent from each other over time. This is because with no sexual gene exchange between parents, the two gene copies become essentially isolated from each other, and will hence mutate independently. However, this pattern also arises when a new species is form by hybridisation, due to mixing two distinct sets of genes from parental species. Ament-Velasquez et al. studied gene samples over several species of Lineus worms, and partitioned observed genetic divergence in an asexual species into that arising via hybridisation and asexual genetic isolation.

Click here to read the commentary piece, which gives a further overview of their research as well as reflections on how to dissect the many genetic outcomes of asexual reproduction.

A Chance to Adapt?

On the surface, the logic underlying the theory of natural selection is pretty simple. Individuals exist in an environment, each carrying different genetic variants; one (or more) of these variants are better suited to that environment; and hence this variant is more likely to be passed on to offspring, and spread through the entire population over time. In reality, the means by which adaptations appear and evolve can be wildly complex and counterintuitive. In particular there is a large element of chance that is often overlooked; many adaptive types can easily be lost by bad luck. Far from being of minor evolutionary importance, this effect of chance is fundamental with regards to not only how we think about evolution, but also related issues such as conservation and infectious disease emergence. Furthermore, clarifying the likelihood that new adaptations emerge proved imperative in understanding how powerful natural selection is at driving evolution.

The certainty of chance

Let’s illustrate this point with a hypothetical example. Imagine a dainty field of flowers in tightly packed rows, which you might see if you took a cycling tour of Holland. Now, one of these flowers developed a mutated gene, allowing it to grow taller than the others. This alteration would be beneficial for the flower; it would have premium access to sunlight, water, and pollen with are needed for reproduction. If this flower were particularly lucky, it would be able to leave offspring, each of which would be equally tall. This process repeats over time, until all flowers in the field carry this adaptation and are larger as a result.

For this adaptation to spread though, the first flower has to survive. If you trod on it as you marched your way across this field to visit a historic Dutch windmill, then the adaptation dies with the flower itself. Tough luck, evolution.

In this toy example, the adaptation causing increased height would be likely to spread as it offers a large advantage to reproduction. Yet most beneficial mutations are not so prominent. They’re usually tweaks to the existing body, such as creating refined teeth for eating, or generating muscle protein more efficiently. These types of mutations are much more vulnerable to being killed off by chance. Let’s say that such a mutation appears, which causes the individual carrying it to have a 2% higher chance of leaving offspring, and therefore to pass on this new adaptation, over its lifespan. A classic evolutionary genetics result shows that the probability that it will spread through the population at large is only 4%. (Generally, if the advantage is denoted s, the fixation probability is 2s.)

Why is that? In the example above involving tall flowers, the danger for the new mutant is its rarity. If it is only present in one individual, then the death of its sole carrier will also prevent the adaptation from spreading. When the advantage of the mutant is low, then for the most part the carrier will produce as many offspring as non-mutated individuals. Hence this mutant will be present in only a few individuals for long durations of time; its advantage will only become apparent later. It only takes one population shock during this period to eliminate the adaptive form.

One tall flower appears, then two, over longer period of time…

A role for natural selection

Exploring the role of chance in adaptation was an important question for the first wave of evolutionary genetic theorists, most notably Ronald Fisher and John Haldane. They wanted to resolve whether natural selection could indeed cause the appearance of adaptive forms in nature, and what other forces affected it. At the turn of the twentieth century, Darwin’s idea of evolution was widely accepted, but his explanation for it – natural selection – was hotly debated. The old criticism was that chance selection events could not form the complex biology surrounding us. Some variants of this argument are still used by creationists to argue against the theory of evolution.

Fisher and Haldane’s work on this subject made it clear that while natural selection is not guaranteed, it is still a potent force in driving adaptation. While the chance of any individual adaptation arising is small, it is still much more probable than having these mutations spread without the driving force of natural selection. In the non-selected, or neutral case, the fixation probability is instead one over the population size. Given potentially hundreds of thousands of individuals, this value is much smaller than that expected with selection. Furthermore, mechanisms exists that can increase the emergence probability, such as repeated mutation reintroducing the adaptive type, or evolution proceeding via incremental changes. Indeed, one of Fisher’s favourite quotes was: “Natural selection is a mechanism for generating an exceedingly high degree of improbability”.

A role in infectious disease spread

Considering this chance effect still plays a role in modern studies of adaptation and evolution, and the same logic can be applied to other types of biological phenomena. In 2013, I wrote a paper with Sam Alizon explaining how similar thinking can be used to quantify the danger from emerging infectious diseases. In 1978 a strain of smallpox escaped from a university laboratory, leading to a tragic single fatal case. This lone patient was quickly isolated, preventing a full-scale outbreak in a similar way that removing a rare adaptation above halted its evolution. However, since infectious diseases can rapidly spread from person to person, the role of chance is massively reduced.