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Marsh JI, Johri P. Biases in ARG-Based Inference of Historical Population Size in Populations Experiencing Selection. Mol Biol Evol 2024; 41:msae118. [PMID: 38874402 PMCID: PMC11245712 DOI: 10.1093/molbev/msae118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 06/05/2024] [Accepted: 06/11/2024] [Indexed: 06/15/2024] Open
Abstract
Inferring the demographic history of populations provides fundamental insights into species dynamics and is essential for developing a null model to accurately study selective processes. However, background selection and selective sweeps can produce genomic signatures at linked sites that mimic or mask signals associated with historical population size change. While the theoretical biases introduced by the linked effects of selection have been well established, it is unclear whether ancestral recombination graph (ARG)-based approaches to demographic inference in typical empirical analyses are susceptible to misinference due to these effects. To address this, we developed highly realistic forward simulations of human and Drosophila melanogaster populations, including empirically estimated variability of gene density, mutation rates, recombination rates, purifying, and positive selection, across different historical demographic scenarios, to broadly assess the impact of selection on demographic inference using a genealogy-based approach. Our results indicate that the linked effects of selection minimally impact demographic inference for human populations, although it could cause misinference in populations with similar genome architecture and population parameters experiencing more frequent recurrent sweeps. We found that accurate demographic inference of D. melanogaster populations by ARG-based methods is compromised by the presence of pervasive background selection alone, leading to spurious inferences of recent population expansion, which may be further worsened by recurrent sweeps, depending on the proportion and strength of beneficial mutations. Caution and additional testing with species-specific simulations are needed when inferring population history with non-human populations using ARG-based approaches to avoid misinference due to the linked effects of selection.
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Affiliation(s)
- Jacob I Marsh
- Department of Biology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Parul Johri
- Department of Biology, University of North Carolina, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
- Integrative Program for Biological and Genome Sciences, University of North Carolina, Chapel Hill, NC 27599, USA
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2
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Wheeler LC, Wing BA, Smith SD. Structure and contingency determine mutational hotspots for flower color evolution. Evol Lett 2021; 5:61-74. [PMID: 33552536 PMCID: PMC7857289 DOI: 10.1002/evl3.212] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 10/26/2020] [Accepted: 11/25/2020] [Indexed: 01/26/2023] Open
Abstract
Evolutionary genetic studies have uncovered abundant evidence for genomic hotspots of phenotypic evolution, as well as biased patterns of mutations at those loci. However, the theoretical basis for this concentration of particular types of mutations at particular loci remains largely unexplored. In addition, historical contingency is known to play a major role in evolutionary trajectories, but has not been reconciled with the existence of such hotspots. For example, do the appearance of hotspots and the fixation of different types of mutations at those loci depend on the starting state and/or on the nature and direction of selection? Here, we use a computational approach to examine these questions, focusing the anthocyanin pigmentation pathway, which has been extensively studied in the context of flower color transitions. We investigate two transitions that are common in nature, the transition from blue to purple pigmentation and from purple to red pigmentation. Both sets of simulated transitions occur with a small number of mutations at just four loci and show strikingly similar peaked shapes of evolutionary trajectories, with the mutations of the largest effect occurring early but not first. Nevertheless, the types of mutations (biochemical vs. regulatory) as well as their direction and magnitude are contingent on the particular transition. These simulated color transitions largely mirror findings from natural flower color transitions, which are known to occur via repeated changes at a few hotspot loci. Still, some types of mutations observed in our simulated color evolution are rarely observed in nature, suggesting that pleiotropic effects further limit the trajectories between color phenotypes. Overall, our results indicate that the branching structure of the pathway leads to a predictable concentration of evolutionary change at the hotspot loci, but the types of mutations at these loci and their order is contingent on the evolutionary context.
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Affiliation(s)
- Lucas C. Wheeler
- Department of Ecology and Evolutionary BiologyUniversity of ColoradoBoulderCOUSA
| | - Boswell A. Wing
- Department of Geological SciencesUniversity of ColoradoBoulderCOUSA
| | - Stacey D. Smith
- Department of Ecology and Evolutionary BiologyUniversity of ColoradoBoulderCOUSA
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3
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Lyons DM, Zou Z, Xu H, Zhang J. Idiosyncratic epistasis creates universals in mutational effects and evolutionary trajectories. Nat Ecol Evol 2020; 4:1685-1693. [PMID: 32895516 PMCID: PMC7710555 DOI: 10.1038/s41559-020-01286-y] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2020] [Accepted: 07/23/2020] [Indexed: 01/06/2023]
Abstract
Patterns of epistasis and shapes of fitness landscapes are of wide interest because of their bearings on a number of evolutionary theories. The common phenomena of slowing fitness increases during adaptations and diminishing returns from beneficial mutations are believed to reflect a concave fitness landscape and a preponderance of negative epistasis. Paradoxically, fitness decreases tend to decelerate and harm from deleterious mutations shrinks during the accumulation of random mutations-patterns thought to indicate a convex fitness landscape and a predominance of positive epistasis. Current theories cannot resolve this apparent contradiction. Here, we show that the phenotypic effect of a mutation varies substantially depending on the specific genetic background and that this idiosyncrasy in epistasis creates all of the above trends without requiring a biased distribution of epistasis. The idiosyncratic epistasis theory explains the universalities in mutational effects and evolutionary trajectories as emerging from randomness due to biological complexity.
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Affiliation(s)
| | | | | | - Jianzhi Zhang
- Correspondence to Jianzhi Zhang, Department of Ecology and Evolutionary Biology, University of Michigan, 4018 Biological Sciences Building, 1105 North University Avenue, Ann Arbor, MI 48109, USA, Phone: 734-763-0527,
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4
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Reia SM, Campos PRA. Analysis of statistical correlations between properties of adaptive walks in fitness landscapes. ROYAL SOCIETY OPEN SCIENCE 2020; 7:192118. [PMID: 32218986 PMCID: PMC7029893 DOI: 10.1098/rsos.192118] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 01/13/2020] [Indexed: 06/10/2023]
Abstract
The fitness landscape metaphor has been central in our way of thinking about adaptation. In this scenario, adaptive walks are idealized dynamics that mimic the uphill movement of an evolving population towards a fitness peak of the landscape. Recent works in experimental evolution have demonstrated that the constraints imposed by epistasis are responsible for reducing the number of accessible mutational pathways towards fitness peaks. Here, we exhaustively analyse the statistical properties of adaptive walks for two empirical fitness landscapes and theoretical NK landscapes. Some general conclusions can be drawn from our simulation study. Regardless of the dynamics, we observe that the shortest paths are more regularly used. Although the accessibility of a given fitness peak is reasonably correlated to the number of monotonic pathways towards it, the two quantities are not exactly proportional. A negative correlation between predictability and mean path divergence is established, and so the decrease of the number of effective mutational pathways ensures the convergence of the attraction basin of fitness peaks. On the other hand, other features are not conserved among fitness landscapes, such as the relationship between accessibility and predictability.
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Affiliation(s)
- Sandro M. Reia
- Instituto de Física de São Carlos, Universidade de São Paulo, Caixa Postal 369, 13560-970 São Carlos, São Paulo, Brazil
| | - Paulo R. A. Campos
- Evolutionary Dynamics Lab, Physics Department, Federal University of Pernambuco, Recife, Brazil
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5
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Bergman J, Eyre-Walker A. Does Adaptive Protein Evolution Proceed by Large or Small Steps at the Amino Acid Level? Mol Biol Evol 2019; 36:990-998. [PMID: 30903659 DOI: 10.1093/molbev/msz033] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
A long-standing question in evolutionary biology is the relative contribution of large and small effect mutations to the adaptive process. We have investigated this question in proteins by estimating the rate of adaptive evolution between all pairs of amino acids separated by one mutational step using a McDonald-Kreitman type approach and genome-wide data from several Drosophila species. We find that the rate of adaptive evolution is highest among amino acids that are more similar. This is partly due to the fact that the proportion of mutations that are adaptive is higher among more similar amino acids. We also find that the rate of neutral evolution between amino acids is higher among more similar amino acids. Overall our results suggest that both the adaptive and nonadaptive evolution of proteins are dominated by substitutions between similar amino acids.
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Affiliation(s)
- Juraj Bergman
- Institut für Populationsgenetik, Vetmeduni Vienna, Wien, Austria.,Vienna Graduate School of Population Genetics, Wien, Austria
| | - Adam Eyre-Walker
- School of Life Sciences, University of Sussex, Brighton, United Kingdom
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6
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Thurman TJ, Barrett RDH. The genetic consequences of selection in natural populations. Mol Ecol 2016; 25:1429-48. [DOI: 10.1111/mec.13559] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2015] [Revised: 12/21/2015] [Accepted: 01/27/2016] [Indexed: 01/06/2023]
Affiliation(s)
- Timothy J. Thurman
- Redpath Museum and Department of Biology; McGill University; Sherbrooke Street West Montreal Quebec Canada H3A 1B1 Canada
- Smithsonian Tropical Research Institute; Panamá Panamá
| | - Rowan D. H. Barrett
- Redpath Museum and Department of Biology; McGill University; Sherbrooke Street West Montreal Quebec Canada H3A 1B1 Canada
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7
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John S, Seetharaman S. Exploiting the Adaptation Dynamics to Predict the Distribution of Beneficial Fitness Effects. PLoS One 2016; 11:e0151795. [PMID: 26990188 PMCID: PMC4798746 DOI: 10.1371/journal.pone.0151795] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2015] [Accepted: 03/04/2016] [Indexed: 11/18/2022] Open
Abstract
Adaptation of asexual populations is driven by beneficial mutations and therefore the dynamics of this process, besides other factors, depends on the distribution of beneficial fitness effects. It is known that on uncorrelated fitness landscapes, this distribution can only be of three types: truncated, exponential and power law. We performed extensive stochastic simulations to study the adaptation dynamics on rugged fitness landscapes, and identified two quantities that can be used to distinguish the underlying distribution of beneficial fitness effects. The first quantity studied here is the fitness difference between successive mutations that spread in the population, which is found to decrease in the case of truncated distributions, remains nearly a constant for exponentially decaying distributions and increases when the fitness distribution decays as a power law. The second quantity of interest, namely, the rate of change of fitness with time also shows quantitatively different behaviour for different beneficial fitness distributions. The patterns displayed by the two aforementioned quantities are found to hold good for both low and high mutation rates. We discuss how these patterns can be exploited to determine the distribution of beneficial fitness effects in microbial experiments.
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Affiliation(s)
- Sona John
- Theoretical Sciences Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur P.O., Bangalore 560064, India
- * E-mail:
| | - Sarada Seetharaman
- Theoretical Sciences Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur P.O., Bangalore 560064, India
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8
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Park SC, Neidhart J, Krug J. Greedy adaptive walks on a correlated fitness landscape. J Theor Biol 2016; 397:89-102. [PMID: 26953649 DOI: 10.1016/j.jtbi.2016.02.035] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2015] [Revised: 02/24/2016] [Accepted: 02/26/2016] [Indexed: 12/24/2022]
Abstract
We study adaptation of a haploid asexual population on a fitness landscape defined over binary genotype sequences of length L. We consider greedy adaptive walks in which the population moves to the fittest among all single mutant neighbors of the current genotype until a local fitness maximum is reached. The landscape is of the rough mount Fuji type, which means that the fitness value assigned to a sequence is the sum of a random and a deterministic component. The random components are independent and identically distributed random variables, and the deterministic component varies linearly with the distance to a reference sequence. The deterministic fitness gradient c is a parameter that interpolates between the limits of an uncorrelated random landscape (c=0) and an effectively additive landscape (c→∞). When the random fitness component is chosen from the Gumbel distribution, explicit expressions for the distribution of the number of steps taken by the greedy walk are obtained, and it is shown that the walk length varies non-monotonically with the strength of the fitness gradient when the starting point is sufficiently close to the reference sequence. Asymptotic results for general distributions of the random fitness component are obtained using extreme value theory, and it is found that the walk length attains a non-trivial limit for L→∞, different from its values for c=0 and c=∞, if c is scaled with L in an appropriate combination.
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Affiliation(s)
- Su-Chan Park
- Department of Physics, The Catholic University of Korea, Bucheon 14662, Republic of Korea.
| | - Johannes Neidhart
- Institut für Theoretische Physik, Universität zu Köln, 50937 Köln, Germany
| | - Joachim Krug
- Institut für Theoretische Physik, Universität zu Köln, 50937 Köln, Germany
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9
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Stearns FW, Fenster CB. Fisher's geometric model predicts the effects of random mutations when tested in the wild. Evolution 2016; 70:495-501. [PMID: 26768168 DOI: 10.1111/evo.12858] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2015] [Revised: 12/21/2015] [Accepted: 12/23/2015] [Indexed: 01/30/2023]
Abstract
Fisher's geometric model of adaptation (FGM) has been the conceptual foundation for studies investigating the genetic basis of adaptation since the onset of the neo Darwinian synthesis. FGM describes adaptation as the movement of a genotype toward a fitness optimum due to beneficial mutations. To date, one prediction of FGM, the probability of improvement is related to the distance from the optimum, has only been tested in microorganisms under laboratory conditions. There is reason to believe that results might differ under natural conditions where more mutations likely affect fitness, and where environmental variance may obscure the expected pattern. We chemically induced mutations into a set of 19 Arabidopsis thaliana accessions from across the native range of A. thaliana and planted them alongside the premutated founder lines in two habitats in the mid-Atlantic region of the United States under field conditions. We show that FGM is able to predict the outcome of a set of random induced mutations on fitness in a set of A. thaliana accessions grown in the wild: mutations are more likely to be beneficial in relatively less fit genotypes. This finding suggests that FGM is an accurate approximation of the process of adaptation under more realistic ecological conditions.
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Affiliation(s)
- Frank W Stearns
- Department of Biology, University of Maryland College Park, Maryland, 20742. .,Current Address: Department of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, 21218.
| | - Charles B Fenster
- Department of Biology, University of Maryland College Park, Maryland, 20742
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10
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Park SC, Szendro IG, Neidhart J, Krug J. Phase transition in random adaptive walks on correlated fitness landscapes. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2015; 91:042707. [PMID: 25974527 DOI: 10.1103/physreve.91.042707] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2014] [Indexed: 06/04/2023]
Abstract
We study biological evolution on a random fitness landscape where correlations are introduced through a linear fitness gradient of strength c. When selection is strong and mutations rare the dynamics is a directed uphill walk that terminates at a local fitness maximum. We analytically calculate the dependence of the walk length on the genome size L. When the distribution of the random fitness component has an exponential tail, we find a phase transition of the walk length D between a phase at small c, where walks are short (D∼lnL), and a phase at large c, where walks are long (D∼L). For all other distributions only a single phase exists for any c>0. The considered process is equivalent to a zero temperature Metropolis dynamics for the random energy model in an external magnetic field, thus also providing insight into the aging dynamics of spin glasses.
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Affiliation(s)
- Su-Chan Park
- The Catholic University of Korea, Bucheon 420-743, Korea
| | - Ivan G Szendro
- Institut für Theoretische Physik, Universität zu Köln, Köln 50937, Germany
| | - Johannes Neidhart
- Institut für Theoretische Physik, Universität zu Köln, Köln 50937, Germany
| | - Joachim Krug
- Institut für Theoretische Physik, Universität zu Köln, Köln 50937, Germany
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11
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Effect of drift, selection and recombination on the equilibrium frequency of deleterious mutations. J Theor Biol 2015; 365:238-46. [PMID: 25451760 DOI: 10.1016/j.jtbi.2014.10.023] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2014] [Revised: 08/30/2014] [Accepted: 10/22/2014] [Indexed: 11/22/2022]
Abstract
We study the stationary state of a population evolving under the action of random genetic drift, selection and recombination in which both deleterious and reverse beneficial mutations can occur. We find that the equilibrium fraction of deleterious mutations decreases as the population size is increased. We calculate exactly the steady state frequency in a nonrecombining population when population size is infinite and for a neutral finite population, and obtain bounds on the fraction of deleterious mutations. We also find that for small and very large populations, the number of deleterious mutations depends weakly on recombination, but for moderately large populations, recombination alleviates the effect of deleterious mutations. An analytical argument shows that recombination decreases disadvantageous mutations appreciably when beneficial mutations are rare as is the case in adapting microbial populations, whereas it has a moderate effect on codon bias where the mutation rates between the preferred and unpreferred codons are comparable.
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12
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Seetharaman S, Jain K. Length of adaptive walk on uncorrelated and correlated fitness landscapes. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2014; 90:032703. [PMID: 25314469 DOI: 10.1103/physreve.90.032703] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2014] [Indexed: 06/04/2023]
Abstract
We consider the adaptation dynamics of an asexual population that walks uphill on a rugged fitness landscape which is endowed with a large number of local fitness peaks. We work in a parameter regime where only those mutants that are a single mutation away are accessible, as a result of which the population eventually gets trapped at a local fitness maximum and the adaptive walk terminates. We study how the number of adaptive steps taken by the population before reaching a local fitness peak depends on the initial fitness of the population, the extreme value distribution of the beneficial mutations, and correlations among the fitnesses. Assuming that the relative fitness difference between successive steps is small, we analytically calculate the average walk length for both uncorrelated and correlated fitnesses in all extreme value domains for a given initial fitness. We present numerical results for the model where the fitness differences can be large and find that the walk length behavior differs from that in the former model in the Fréchet domain of extreme value theory. We also discuss the relevance of our results to microbial experiments.
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Affiliation(s)
- Sarada Seetharaman
- Theoretical Sciences Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur P.O., Bangalore 560064, India
| | - Kavita Jain
- Theoretical Sciences Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur P.O., Bangalore 560064, India
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13
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Abstract
Much of the current theory of adaptation is based on Gillespie's mutational landscape model (MLM), which assumes that the fitness values of genotypes linked by single mutational steps are independent random variables. On the other hand, a growing body of empirical evidence shows that real fitness landscapes, while possessing a considerable amount of ruggedness, are smoother than predicted by the MLM. In the present article we propose and analyze a simple fitness landscape model with tunable ruggedness based on the rough Mount Fuji (RMF) model originally introduced by Aita et al. in the context of protein evolution. We provide a comprehensive collection of results pertaining to the topographical structure of RMF landscapes, including explicit formulas for the expected number of local fitness maxima, the location of the global peak, and the fitness correlation function. The statistics of single and multiple adaptive steps on the RMF landscape are explored mainly through simulations, and the results are compared to the known behavior in the MLM model. Finally, we show that the RMF model can explain the large number of second-step mutations observed on a highly fit first-step background in a recent evolution experiment with a microvirid bacteriophage.
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