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13 Sep 2019
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Deceptive combined effects of short allele dominance and stuttering: an example with Ixodes scapularis, the main vector of Lyme disease in the U.S.A.

New curation method for microsatellite markers improves population genetics analyses

Recommended by based on reviews by Eric Petit, Martin Husemann and 2 anonymous reviewers

Genetic markers are used for in modern population genetics/genomics to uncover the past neutral and selective history of population and species. Besides Single Nucleotide Polymorphisms (SNPs) obtained from whole genome data, microsatellites (or Short Tandem Repeats, SSR) have been common markers of choice in numerous population genetics studies of non-model species with large sample sizes [1]. Microsatellites can be used to uncover and draw inference of the past population demography (e.g. expansion, decline, bottlenecks…), population split, population structure and gene flow, but also life history traits and modes of reproduction (e.g. [2,3]). These markers are widely used in conservation genetics [4] or to study parasites or disease vectors [5]. Microsatellites do show higher mutation rate than SNPs increasing, on the one hand, the statistical power to infer recent events (for example crop domestication, [2,3]), while, on the other hand, decreasing their statistical power over longer time scales due to homoplasy [6].
To perform such analyses, however, an excellent and reliable quality of data is required. As emphasized in the article by De Meeûs et al. [7] three main issues do bias the observed heterozygosity at microsatellites: null alleles, short allele dominance (SAD) and stuttering. These originates from poor PCR amplification. As a result, an excess of homozygosity is observed at the microsatellite loci leading to overestimation of the variation statistics FIS and FST as well as increased linage disequilibrium (LD). For null alleles, several methods and software do help to reduce the bias, and in the present study, De Meeûs et al. [7] propose a way to tackle issues with SAD and stuttering.
The authors study a dataset consisting of 387 samples from 61 subsamples genotyped at nine loci of the species Ixodes scapularis, i.e. ticks transmitting the Lyme disease. Based on correlation methods and FST, FIS they can uncover null alleles and SAD. Stuttering is detected by evaluating the heterozygote deficit between alleles displaying a single repeat difference. Without correction, six loci are affected by one of these amplification problems generating a large deficit of heterozygotes (measured by significant FIS and FST) remaining so after correction for the false discovery rate (FDR). These results would be classically interpreted as a strong Wahlund effect and/or selection at several loci.
After correcting for null alleles, the authors apply two novel corrections: 1) a re-examination of the chromatograms reveals previously disregarded larger alleles thus decreasing SAD, and 2) pooling alleles close in size decreasing stuttering. The corrected dataset shows then a significant excess of heterozygotes as could be expected in a dioecious species with strong population structure. The FDR correction removes then the significant excess of homozygotes and LD between pairs of loci. FST on the cured dataset is used to demonstrate the strong population structure and small effective subpopulation sizes. This is confirmed by a clustering analysis using discriminant analysis of principal components (DAPC).
While based on a specific dataset of ticks from different populations sampled across the USA, the generality of the authors’ approach is presented in Figure 6 in which they provide a step by step flowchart to cure microsatellite datasets from null alleles, SAD and stuttering. Several criteria based on FIS, FST and LD between loci are used as decision keys in the flowchart. An excel file is also provided as help for the curation steps. This study and the proposed methodology are thus extremely useful for all population geneticists working on non-model species with large number of samples genotyped at microsatellite markers. The method not only allows more accurate estimates of heterozygosity but also prevents the thinning of datasets due to the removal of problematic loci. As a follow-up and extension of this work, an exhaustive simulation study could investigate the influence of these data quality issues on past demographic and population structure inference under a wide range of scenarios. This would allow to quantify the current biases in the literature and the robustness of the methodology devised by De Meeûs et al. [7].

References

[1] Jarne, P., and Lagoda, P. J. (1996). Microsatellites, from molecules to populations and back. Trends in ecology & evolution, 11(10), 424-429. doi: 10.1016/0169-5347(96)10049-5
[2] Cornille, A., Giraud, T., Bellard, C., Tellier, A., Le Cam, B., Smulders, M. J. M., Kleinschmit, J., Roldan-Ruiz, I. and Gladieux, P. (2013). Postglacial recolonization history of the E uropean crabapple (Malus sylvestris M ill.), a wild contributor to the domesticated apple. Molecular Ecology, 22(8), 2249-2263. doi: 10.1111/mec.12231
[3] Parat, F., Schwertfirm, G., Rudolph, U., Miedaner, T., Korzun, V., Bauer, E., Schön C.-C. and Tellier, A. (2016). Geography and end use drive the diversification of worldwide winter rye populations. Molecular ecology, 25(2), 500-514. doi: 10.1111/mec.13495
[4] Broquet, T., Ménard, N., & Petit, E. (2007). Noninvasive population genetics: a review of sample source, diet, fragment length and microsatellite motif effects on amplification success and genotyping error rates. Conservation Genetics, 8(1), 249-260. doi: 10.1007/s10592-006-9146-5
[5] Koffi, M., De Meeûs, T., Séré, M., Bucheton, B., Simo, G., Njiokou, F., Salim, B., Kaboré, J., MacLeod, A., Camara, M., Solano, P., Belem, A. M. G. and Jamonneau, V. (2015). Population genetics and reproductive strategies of African trypanosomes: revisiting available published data. PLoS neglected tropical diseases, 9(10), e0003985. doi: 10.1371/journal.pntd.0003985
[6] Estoup, A., Jarne, P., & Cornuet, J. M. (2002). Homoplasy and mutation model at microsatellite loci and their consequences for population genetics analysis. Molecular ecology, 11(9), 1591-1604. doi: 10.1046/j.1365-294X.2002.01576.x
[7] De Meeûs, T., Chan, C. T., Ludwig, J. M., Tsao, J. I., Patel, J., Bhagatwala, J., and Beati, L. (2019). Deceptive combined effects of short allele dominance and stuttering: an example with Ixodes scapularis, the main vector of Lyme disease in the USA. bioRxiv, 622373, ver. 4 peer-reviewed and recommended by Peer Community In Evolutionary Biology. doi: 10.1101/622373

Deceptive combined effects of short allele dominance and stuttering: an example with Ixodes scapularis, the main vector of Lyme disease in the U.S.A.Thierry De Meeûs, Cynthia T. Chan, John M. Ludwig, Jean I. Tsao, Jaymin Patel, Jigar Bhagatwala, and Lorenza Beati<p>Null alleles, short allele dominance (SAD), and stuttering increase the perceived relative inbreeding of individuals and subpopulations as measured by Wright’s FIS and FST. Ascertainment bias, due to such amplifying problems are usually caused ...Evolutionary Ecology, Other, Population Genetics / GenomicsAurelien Tellier2019-05-02 20:52:08 View
09 Dec 2019
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Trait-specific trade-offs prevent niche expansion in two parasites

Trade-offs in fitness components and ecological source-sink dynamics affect host specialisation in two parasites of Artemia shrimps

Recommended by ORCID_LOGO based on reviews by Anne Duplouy, Seth Barribeau and Cindy Gidoin

Ecological specialisation, especially among parasites infecting a set of host species, is ubiquitous in nature. Host specialisation can be understood as resulting from trade-offs in parasite infectivity, virulence and growth. However, it is not well understood how variation in these trade-offs shapes the overall fitness trade-off a parasite faces when adapting to multiple hosts. For instance, it is not clear whether a strong trade-off in one fitness component may sufficiently constrain the evolution of a generalist parasite despite weak trade-offs in other components. A second mechanism explaining variation in specialisation among species is habitat availability and quality. Rare habitats or habitats that act as ecological sinks will not allow a species to persist and adapt, preventing a generalist phenotype to evolve. Understanding the prevalence of those mechanisms in natural systems is crucial to understand the emergence and maintenance of host specialisation, and biodiversity in general.
In their study "Trait-specific trade-offs prevent niche expansion in two parasites", Lievens et al. [1] report the results of an evolution experiment involving two parasitic microsporidians, Anostracospora rigaudi and Enterocytospora artemiae, infecting two sympatric species of brine shrimp, Artemia franciscana and Artemia parthenogenetica. The two parasites were originally specialised on their primary host: A. rigaudi on A. parthenogenetica and E. artemiae on A. franciscana, although they encounter both species in the wild but at different rates. After passaging each parasite on each single host and on both hosts alternatively, Lievens et al. asked how host specialisation evolved. They found no change in specialisation at the fitness level in A. rigaudi in either treatment, while E. artemiae became more of a generalist after having been exposed to its secondary host, A. parthenogenetica. The most interesting part of the study is the decomposition of the fitness trade-off into its underlying trade-offs in spore production, infectivity and virulence. Both species remained specialised for spore production on their primary host, interpreted as caused by a strong trade-off between hosts preventing improvements on the secondary host. A. rigaudi evolved reduced virulence on its primary host without changes in the overall fitness trad-off, while E. artemiae evolved higher infectivity on its secondary host making it a more generalist parasite and revealing a weak trade-off for this trait and for fitness. Nevertheless, both parasites retained higher fitness on their primary host because of the lack of an evolutionary response in spore production.
This study made two important points. First, it showed that despite apparent strong trade-off in spore production, a weak trade-off in infectivity allowed E. artemiae to become less specialised. In contrast, A. rigaudi remained specialised, presumably because the strong trade-off in spore production was the overriding factor. The fitness trade-off that results from the superposition of multiple underlying trade-offs is thus difficult to predict, yet crucial to understand potential evolutionary outcomes. A second insight is related to the ecological context of the evolution of specialisation. The results showed that E. artemiae should be less specialised than observed, which points to a role played by source-sink dynamics on A. parthenogenetica in the wild. The experimental approach of Lievens et al. thus allowed them to nicely disentangle the various sources of constraints on the evolution of host adaptation in the Artemia system.

References

[1] Lievens, E.J.P., Michalakis, Y. and Lenormand, T. (2019). Trait-specific trade-offs prevent niche expansion in two parasites. bioRxiv, 621581, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/621581

Trait-specific trade-offs prevent niche expansion in two parasitesEva JP Lievens, Yannis Michalakis, Thomas Lenormand<p>The evolution of host specialization has been studied intensively, yet it is still often difficult to determine why parasites do not evolve broader niches – in particular when the available hosts are closely related and ecologically similar. He...Adaptation, Evolutionary Ecology, Evolutionary Epidemiology, Experimental Evolution, Life History, Species interactionsFrédéric Guillaume2019-05-13 13:44:34 View
23 Jan 2020
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A novel workflow to improve multi-locus genotyping of wildlife species: an experimental set-up with a known model system

Improving the reliability of genotyping of multigene families in non-model organisms

Recommended by based on reviews by Sebastian Ernesto Ramos-Onsins, Helena Westerdahl and Thomas Bigot

The reliability of published scientific papers has been the topic of much recent discussion, notably in the biomedical sciences [1]. Although small sample size is regularly pointed as one of the culprits, big data can also be a concern. The advent of high-throughput sequencing, and the processing of sequence data by opaque bioinformatics workflows, mean that sequences with often high error rates are produced, and that exact but slow analyses are not feasible.
The troubles with bioinformatics arise from the increased complexity of the tools used by scientists, and from the lack of incentives and/or skills from authors (but also reviewers and editors) to make sure of the quality of those tools. As a much discussed example, a bug in the widely used PLINK software [2] has been pointed as the explanation [3] for incorrect inference of selection for increased height in European Human populations [4].
High-throughput sequencing often generates high rates of genotyping errors, so that the development of bioinformatics tools to assess the quality of data and correct them is a major issue. The work of Gillingham et al. [5] contributes to the latter goal. In this work, the authors propose a new bioinformatics workflow (ACACIA) for performing genotyping analysis of multigene complexes, such as self-incompatibility genes in plants, major histocompatibility genes (MHC) in vertebrates, and homeobox genes in animals, which are particularly challenging to genotype in non-model organisms. PCR and sequencing of multigene families generate artefacts, hence spurious alleles. A key to Gillingham et al.‘ s method is to call candidate genes based on Oligotyping, a software pipeline originally conceived for identifying variants from microbiome 16S rRNA amplicons [6]. This allows to reduce the number of false positives and the number of dropout alleles, compared to previous workflows.
This method is not based on an explicit probability model, and thus it is not conceived to provide a control of the rate of errors as, say, a valid confidence interval should (a confidence interval with coverage c for a parameter should contain the parameter with probability c, so the error rate 1- c is known and controlled by the user who selects the value of c). However, the authors suggest a method to adapt the settings of ACACIA to each application.
To compare and validate the new workflow, the authors have constructed new sets of genotypes representing different extents copy number variation, using already known genotypes from chicken MHC. In such conditions, it was possible to assess how many alleles are not detected and what is the rate of false positives. Gillingham et al. additionally investigated the effect of using non-optimal primers. They found better performance of ACACIA compared to a preexisting pipeline, AmpliSAS [7], for optimal settings of both methods. However, they do not claim that ACACIA will always be better than AmpliSAS. Rather, they warn against the common practice of using the default settings of the latter pipeline. Altogether, this work and the ACACIA workflow should allow for better ascertainment of genotypes from multigene families.

References

[1] Ioannidis, J. P. A, Greenland, S., Hlatky, M. A., Khoury, M. J., Macleod, M. R., Moher, D., Schulz, K. F. and Tibshirani, R. (2014) Increasing value and reducing waste in research design, conduct, and analysis. The Lancet, 383, 166-175. doi: 10.1016/S0140-6736(13)62227-8
[2] Chang, C. C., Chow, C. C., Tellier, L. C. A. M., Vattikuti, S., Purcell, S. M. and Lee, J. J. (2015) Second-generation PLINK: rising to the challenge of larger and richer datasets. GigaScience, 4, 7, s13742-015-0047-8. doi: 10.1186/s13742-015-0047-8
[3] Robinson, M. R. and Visscher, P. (2018) Corrected sibling GWAS data release from Robinson et al. http://cnsgenomics.com/data.html
[4] Field, Y., Boyle, E. A., Telis, N., Gao, Z., Gaulton, K. J., Golan, D., Yengo, L., Rocheleau, G., Froguel, P., McCarthy, M.I . and Pritchard J. K. (2016) Detection of human adaptation during the past 2000 years. Science, 354(6313), 760-764. doi: 10.1126/science.aag0776
[5] Gillingham, M. A. F., Montero, B. K., Wihelm, K., Grudzus, K., Sommer, S. and Santos P. S. C. (2020) A novel workflow to improve multi-locus genotyping of wildlife species: an experimental set-up with a known model system. bioRxiv 638288, ver. 3 peer-reviewed and recommended by Peer Community In Evolutionary Biology. doi: 10.1101/638288
[6] Eren, A. M., Maignien, L., Sul, W. J., Murphy, L. G., Grim, S. L., Morrison, H. G., and Sogin, M.L. (2013) Oligotyping: differentiating between closely related microbial taxa using 16S rRNA gene data. Methods in Ecology and Evolution 4(12), 1111-1119. doi: 10.1111/2041-210X.12114
[7] Sebastian, A., Herdegen, M., Migalska, M. and Radwan, J. (2016) AMPLISAS: a web server for multilocus genotyping using next‐generation amplicon sequencing data. Mol Ecol Resour, 16, 498-510. doi: 10.1111/1755-0998.12453

A novel workflow to improve multi-locus genotyping of wildlife species: an experimental set-up with a known model systemGillingham, Mark A. F., Montero, B. Karina, Wilhelm, Kerstin, Grudzus, Kara, Sommer, Simone and Santos, Pablo S. C.<p>Genotyping novel complex multigene systems is particularly challenging in non-model organisms. Target primers frequently amplify simultaneously multiple loci leading to high PCR and sequencing artefacts such as chimeras and allele amplification...Bioinformatics & Computational Biology, Evolutionary Ecology, Genome Evolution, Molecular EvolutionFrançois Rousset Helena Westerdahl, Sebastian Ernesto Ramos-Onsins, Paul J. McMurdie , Arnaud Estoup, Vincent Segura, Jacek Radwan , Torbjørn Rognes , William Stutz , Kevin Vanneste , Thomas Bigot, Jill A. Hollenbach , Wieslaw Babik , Marie-Christin...2019-05-15 17:30:44 View
28 Aug 2019
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Is adaptation limited by mutation? A timescale-dependent effect of genetic diversity on the adaptive substitution rate in animals

To tinker, evolution needs a supply of spare parts

Recommended by based on reviews by Konstantin Popadin, David Enard and 1 anonymous reviewer

Is evolution adaptive? Not if there is no variation for natural selection to work with. Theory predicts that how fast a population can adapt to a new environment can be limited by the supply of new mutations coming into it. This supply, in turn, depends on two things: how often mutations occur and in how many individuals. If there are few mutations, or few individuals in whom they can originate, individuals will be mostly identical in their DNA, and natural selection will be impotent.
This theoretical prediction has been hard to test. The rate at which new mutations arise in a population can be manipulated experimentally, and some work has shown that the fitness of a population increases more rapidly if more new mutations appear per generation, lending support to the mutation-limitation hypothesis [1]. However, the question remains whether this limitation has played a role in the history of life over the evolutionary timescale. Maybe all natural populations are so large, the mutation rate so high, and/or the environment changes so slowly, that any novel variant required for adaptation is already there when selection starts to act? Some recent work does suggest that when strong selection begins to favor a certain phenotype, multiple distinct genetic variants producing this phenotype spread; this is what has happened, for instance, at the origin of insecticide resistance in wild populations of Drosophila melanogaster [2] or lactose persistence in humans [3]. In many other cases, though, adaptations seem to originate through a single mutation event, suggesting that the time needed for this mutation to arise may be important.
To complicate things, adaptation is hard to quantify. It leaves a trace in differences between individuals of the same species as well as of different species. However, this trace is often masked or confounded by other processes, including natural selection disfavoring newly arising deleterious variants, interference from selection acting at linked sites, and changes in population size. In 1991, McDonald and Kreitman [4] have come up with a method to infer the rate of adaptation in the presence of strong negative selection, and later work has developed upon it to control for some of the other confounders. Still, the method is data-intensive, and previous attempts to employ it to compare the rates of adaptation between species have yielded somewhat contradictory results.
The new paper by Rousselle et al. recommended by PCI Evol Biol [5] fills this gap. The authors use published data as well as their own newly generated dataset to analyze, in a McDonald and Kreitman-like framework, both closely and distantly related species. Importantly, these comparisons cover species with very different polymorphism levels, spanning two orders of magnitude of difference levels.
So is adaptation in fact limited by supply of new mutations? The answer is, it depends. It does indeed seem that the species with a lower level of polymorphism adapt at a lower rate, consistent with the mutation-limitation hypothesis. However, this only is true for those groups of species in which the variability is low. Therefore, if a population is very small or the mutation rate very low, there may be in fact not enough mutations to secure its need to adapt.
In more polymorphic species, and in comparisons of distant species, the data hint instead at the opposite relationship: the rate of adaptations declines with variability. This is consistent with a different explanation: when a population is small, it needs to adapt more frequently, repairing the weakly deleterious mutations that can’t be prevented by selection under small population sizes.
There are quite a few problems small populations have to deal with. Some of them are ecological: e.g., small numbers make populations more vulnerable to stochastic fluctuations in size or sex ratio. Others, however, are genetic. Small populations are prone to inbreeding depression and have an increased rate of genetic drift, leading to spread of deleterious alleles. Indeed, selection against deleterious mutations is less efficient when populations are small, and less numerable species accumulate more of such mutations over the course of evolution [6]. The work by Rouselle et al. [5] suggests that small populations also face an additional burden: a reduced ability to adapt.
Has the rate of adaptation in our own species also been limited by our deficit of diversity? The data hints at this. Homo sapiens, as well as the two other studied extinct representatives of the genus Homo, Neanderthals and Denisovans, belong to the domain of relatively low polymorphism levels, where an increase in polymorphism matters for the rate at which adaptive substitutions accumulate. Perhaps, if our ancestors were more numerous or more mutable, they would have been able to get themselves out of trouble, and there would be multiple human species still alive rather than just one.

References

[1] G, J. A., Visser, M. de, Zeyl, C. W., Gerrish, P. J., Blanchard, J. L., and Lenski, R. E. (1999). Diminishing Returns from Mutation Supply Rate in Asexual Populations. Science, 283(5400), 404–406. doi: 10.1126/science.283.5400.404
[2] Karasov, T., Messer, P. W., and Petrov, D. A. (2010). Evidence that Adaptation in Drosophila Is Not Limited by Mutation at Single Sites. PLOS Genetics, 6(6), e1000924. doi: 10.1371/journal.pgen.1000924
[3] Jones, B. L., Raga, T. O., Liebert, A., Zmarz, P., Bekele, E., Danielsen, E. T., Olsen, A. K., Bradman, N., Troelsen, J. T., and Swallow, D. M. (2013). Diversity of Lactase Persistence Alleles in Ethiopia: Signature of a Soft Selective Sweep. The American Journal of Human Genetics, 93(3), 538–544. doi: 10.1016/j.ajhg.2013.07.008
[4] McDonald, J. H., and Kreitman, M. (1991). Adaptive protein evolution at the Adh locus in Drosophila. Nature, 351(6328), 652–654. doi: 10.1038/351652a0
[5] Rousselle, M., Simion, P., Tilak, M. K., Figuet, E., Nabholz, B., and Galtier, N. (2019). Is adaptation limited by mutation? A timescale-dependent effect of genetic diversity on the adaptive substitution rate in animals. BioRxiv, 643619, ver 4 peer-reviewed and recommended by Peer Community In Evolutionary Biology. doi: 10.1101/643619
[6] Popadin, K., Polishchuk, L. V., Mamirova, L., Knorre, D., and Gunbin, K. (2007). Accumulation of slightly deleterious mutations in mitochondrial protein-coding genes of large versus small mammals. Proceedings of the National Academy of Sciences, 104(33), 13390–13395. doi: 10.1073/pnas.0701256104

Is adaptation limited by mutation? A timescale-dependent effect of genetic diversity on the adaptive substitution rate in animalsMarjolaine Rousselle, Paul Simion, Marie-Ka Tilak, Emeric Figuet, Benoit Nabholz, Nicolas Galtier<p>Whether adaptation is limited by the beneficial mutation supply is a long-standing question of evolutionary genetics, which is more generally related to the determination of the adaptive substitution rate and its relationship with the effective...Adaptation, Evolutionary Theory, Genome Evolution, Molecular Evolution, Population Genetics / GenomicsGeorgii Bazykin2019-05-21 09:49:16 View
03 May 2020
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When does gene flow facilitate evolutionary rescue?

Reconciling the upsides and downsides of migration for evolutionary rescue

Recommended by based on reviews by 3 anonymous reviewers

The evolutionary response of populations to changing or novel environments is a topic that unites the interests of evolutionary biologists, ecologists, and biomedical researchers [1]. A prominent phenomenon in this research area is evolutionary rescue, whereby a population that is otherwise doomed to extinction survives due to the spread of new or pre-existing mutations that are beneficial in the new environment. Scenarios of evolutionary rescue require a specific set of parameters: the absolute growth rate has to be negative before the rescue mechanism spreads, upon which the growth rate becomes positive. However, potential examples of its relevance exist (e.g., [2]). From a theoretical point of view, the technical challenge but also the beauty of evolutionary rescue models is that they combine the study of population dynamics (i.e., changes in the size of populations) and population genetics (i.e., changes in the frequencies in the population). Together, the potential relevance of evolutionary rescue in nature and the models' theoretical appeal has resulted in a suite of modeling studies on the subject in recent years.
In this manuscript [3], Tomasini and Peischl address a question that has been contentiously discussed in the literature: when does migration favor evolutionary rescue? They expand on past work (specifically, [4, 5]) by studying the influence of the interaction of the speed and severity of environmental change and the amount of dispersal on the probability of evolutionary rescue. They develop simple analytical results (complemented by simulations) for a haploid one-locus model of two populations connected by gene flow, where both populations deteriorate successively such that evolutionary rescue is required for the metapopulation to survive. For example, the authors derive a simple analytical condition demonstrating that migration between the subpopulations favors evolutionary rescue if environmental change occurs slowly across the two populations (which leaves time for the second population to serve as an immigration source), if the new environment is very harsh and/or if rescue mutations are strongly beneficial in the new environment. The latter conditions ensure that the rescue mutations can spread easily in the new environment without much competition with immigrating, maladapted, genotypes. This result is intuitive and connects between traditional single and multiple-deme models.
Altogether, Tomasini and Peischl present an extensive theoretical study and address also the effect of various tweaks to the model assumptions, such as asymmetries in gene flow and/or carrying capacities, and the effects of different density regulation and local growth rates. They successfully made an effort to explain and interpret their results for a general audience, such that also non-theoreticians should not be afraid to take a look at this manuscript.

References

[1] Bell, G. (2017). Evolutionary Rescue. Annual Review of Ecology, Evolution, and Systematics 48(1), 605-627. doi: 10.1146/annurev-ecolsys-110316-023011
[2] Oziolor, E. M., Reid, N. M., Yair, S. et al. (2019). Adaptive introgression enables evolutionary rescue from extreme environmental pollution. Science, 364(6439), 455-457. doi: 10.1126/science.aav4155
[3] Tomasini, M. and Peischl, S. (2020) When does gene flow facilitate evolutionary rescue? bioRxiv, 622142, ver. 5 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/622142
[4] Uecker, H., Otto, S. P., and Hermisson, J. (2014). Evolutionary rescue in structured populations. The American Naturalist, 183(1), E17-E35. doi: 10.1086/673914
[5] Tomasini, M., and Peischl, S. (2018). Establishment of locally adapted mutations under divergent selection. Genetics, 209(3), 885-895. doi: 10.1534/genetics.118.301104

When does gene flow facilitate evolutionary rescue?Matteo Tomasini, Stephan Peischl<p>Experimental and theoretical studies have highlighted the impact of gene flow on the probability of evolutionary rescue in structured habitats. Mathematical modelling and simulations of evolutionary rescue in spatially or otherwise structured p...Evolutionary Dynamics, Evolutionary Theory, Population Genetics / GenomicsClaudia Bank2019-05-22 11:12:13 View
09 Dec 2019
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Systematics and geographical distribution of Galba species, a group of cryptic and worldwide freshwater snails

The challenge of delineating species when they are hidden

Recommended by based on reviews by Pavel Matos, Christelle Fraïsse and Niklas Wahlberg

The science of naming species (taxonomy) has been renewed with the developments of molecular sequencing, digitization of museum specimens, and novel analytical tools. However, naming species can be highly subjective, sometimes considered as an art [1], because it is based on human-based criteria that vary among taxonomists. Nonetheless, taxonomists often argue that species names are hypotheses, which are therefore testable and refutable as new evidence is provided. This challenge comes with a more and more recognized and critical need for rigorously delineated species not only for producing accurate species inventories, but more importantly many questions in evolutionary biology (e.g. speciation), ecology (e.g. ecosystem structure and functioning), conservation biology (e.g. targeting priorities) or biogeography (e.g. diversification processes) depend in part on those species inventories and our knowledge of species [2-3]. Inaccurate species boundaries or diversity estimates may lead us to deliver biased answers to those questions, exactly as phylogenetic trees must be reconstructed rigorously and analyzed critically because they are a first step toward discussing broader questions [2-3]. In this context, biological diversity needs to be studied from multiple and complementary perspectives requiring the collaboration of morphologists, molecular biologists, biogeographers, and modelers [4-5]. Integrative taxonomy has been proposed as a solution to tackle the challenge of delimiting species [2], especially in highly diverse and undocumented groups of organisms.
In an elegant study that harbors all the characteristics of an integrative approach, Alda et al. [6] tackle the delimitation of species within the snail genus Galba (Lymnaeidae). Snails of this genus represent a peculiar case study for species delineation with a long and convoluted taxonomic history in which previous works recognized a number of species ranging from 4 to 30. The confusion is likely due to a loose morphology (labile shell features and high plasticity), which makes the identification and naming of species very unstable and likely subjective. An integrative taxonomic approach was needed. After two decades of taxon sampling and visits of type localities, the authors present an impressively dense taxon sampling at a global scale for the genus, which includes all described species. When it comes to delineate species, taxon sampling is often the key if we want to embrace the genetic and morphological diversity. Molecular data was obtained for several types of markers (microsatellites and DNA sequences for four genes), which were combined to morphology of shell and of internal organs, and to geographic distribution. All the data are thoroughly analyzed with cutting-edge methods starting from Bayesian phylogenetic reconstructions using multispecies coalescent models, followed by models of species delimitation based on the molecular specimen-level phylogeny, and then Bayesian divergence time estimates. They also used probabilistic models of ancestral state estimation to infer the ancestral phenotypic state of the Galba ancestors.
Their numerous phylogenetic and delimitation analyses allow to redefine the species boundaries that indicate that the genus Galba comprises six species. Interestingly, four of these species are morphologically cryptic and likely constitute species with extensive genetic diversity and widespread geographic distribution. The other two species have more geographically restricted distributions and exhibit an alternative morphology that is more phylogenetically derived than the cryptic one. Although further genomic studies would be required to strengthen some species status, this novel delimitation of Galba species has important implications for our understanding of convergence and morphological stasis, or the role for stabilizing selection in amphibious habitats; topics that are rarely addressed with invertebrate groups. For instance, in terms of macroevolutionary history, it is striking that an invertebrate clade of that age (22 million years ago) has only given birth to six species today. Including 30 (ancient taxonomy) or 6 (integrative taxonomy) species in a similar amount of evolutionary time does not tell us the same story when studying the diversification processes [7]. Here, Alda et al. [6] present a convincing case study that should foster similar studies following their approach, which will provide stimulating perspectives for testing the concepts of species and their effects on evolutionary biology.

References

[1] Ohl, M. (2018). The art of naming. MIT Press.
[2] Dayrat, B. (2005). Towards integrative taxonomy. Biological Journal of the Linnean Society, 85(3), 407–415. doi: 10.1111/j.1095-8312.2005.00503.x
[3] De Queiroz, K. (2007). Species concepts and species delimitation. Systematic Biology, 56(6), 879–886. doi: 10.1080/10635150701701083
[4] Padial, J. M., Miralles, A., De la Riva, I., and Vences, M. (2010). The integrative future of taxonomy. Frontiers in Zoology, 7(1), 16. doi: 10.1186/1742-9994-7-16
[5] Schlick-Steiner, B. C., Steiner, F. M., Seifert, B., Stauffer, C., Christian, E., and Crozier, R. H. (2010). Integrative taxonomy: A multisource approach to exploring biodiversity. Annual Review of Entomology, 55(1), 421–438. doi: 10.1146/annurev-ento-112408-085432
[6] Alda, P. et al. (2019). Systematics and geographical distribution of Galba species, a group of cryptic and worldwide freshwater snails. BioRxiv, 647867, v3 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/647867
[7] Ruane, S., Bryson, R. W., Pyron, R. A., and Burbrink, F. T. (2014). Coalescent species delimitation in milksnakes (Genus Lampropeltis) and impacts on phylogenetic comparative analyses. Systematic Biology, 63(2), 231–250. doi: 10.1093/sysbio/syt099

Systematics and geographical distribution of Galba species, a group of cryptic and worldwide freshwater snailsPilar Alda, Manon Lounnas, Antonio Alejandro Vázquez, Rolando Ayaqui, Manuel Calvopina, Maritza Celi-Erazo, Robert Dillon, Luisa Carolina González Ramírez, Eric S. Loker, Jenny Muzzio-Aroca, Alberto Orlando Nárvaez, Oscar Noya, Andrés Esteban Pere...<p>Cryptic species can present a significant challenge to the application of systematic and biogeographic principles, especially if they are invasive or transmit parasites or pathogens. Detecting cryptic species requires a pluralistic approach in ...Phylogeography & Biogeography, Systematics / TaxonomyFabien Condamine Pavel Matos, Christelle Fraïsse2019-05-25 10:34:57 View
26 Nov 2019
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Pleiotropy or linkage? Their relative contributions to the genetic correlation of quantitative traits and detection by multi-trait GWA studies

Understanding the effects of linkage and pleiotropy on evolutionary adaptation

Recommended by based on reviews by Pär Ingvarsson and 1 anonymous reviewer

Genetic correlations among traits are ubiquitous in nature. However, we still have a limited understanding of the genetic architecture of trait correlations. Some genetic correlations among traits arise because of pleiotropy - single mutations or genotypes that have effects on multiple traits. Other genetic correlations among traits arise because of linkage among mutations that have independent effects on different traits. Teasing apart the differential effects of pleiotropy and linkage on trait correlations is difficult, because they result in very similar genetic patterns. However, understanding these differential effects gives important insights into how ubiquitous pleiotropy may be in nature.
In the preprint "Pleiotropy or linkage? Their relative contributions to the genetic correlation of quantitative traits and detection by multi-trait GWA studies", Chebib and Guillaume [1] explore the conditions under which trait correlations caused by pleiotropy result in similar and different genetic patterns than trait correlations caused by linkage. Their main finding is that pleiotropic architectures result in higher trait correlations than do architectures in which completely linked mutations affect different traits. This results clarifies and goes against a previous theoretical study that predicted that pleiotropic architectures could not be distinguished from completely linked mutations that affect independent traits.
In genome-wide association studies (GWAS), it is difficult to know if a significant signal is a causal variant that truly affects the trait, a false positive neutral variant linked to a causal variant, or a false positive causal variant that affects a different trait but is significant because of trait correlations. In their study, Chebib and Guillaume [1] show that this latter category can be a common source of false positives in GWAS studies when mutations affecting different traits are linked. One of the main limitation of this aspect of their analysis is the lack of simulation of neutral loci, which would likely show even higher rates of false positives than reported in their study.
The main limitation in their study is the restrictive assumptions about the genetic architectures (e.g. all pairs of loci have a fixed recombination rate among them). In reality, new causal mutations that arise near another causal mutation may have higher or lower establishment probabilities depending on the direction of effects on the trait and the parameters for selection and demography. Their study still deserves a recommendation, however, because of the new insights it gives into the genetic architecture of trait correlations.

References

[1] Chebib, J. and Guillaume, F. (2019). Pleiotropy or linkage? Their relative contributions to the genetic correlation of quantitative traits and detection by multi-trait GWA studies. bioRxiv, 656413, v3 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/656413

Pleiotropy or linkage? Their relative contributions to the genetic correlation of quantitative traits and detection by multi-trait GWA studiesJobran Chebib and Frédéric Guillaume<p>Genetic correlations between traits may cause correlated responses to selection depending on the source of those genetic dependencies. Previous models described the conditions under which genetic correlations were expected to be maintained. Sel...Bioinformatics & Computational Biology, Evolutionary Applications, Evolutionary Dynamics, Evolutionary Theory, Genome Evolution, Genotype-Phenotype, Molecular Evolution, Population Genetics / Genomics, Quantitative GeneticsKathleen Lotterhos2019-06-05 13:51:43 View
20 Jan 2020
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A young age of subspecific divergence in the desert locust Schistocerca gregaria, inferred by ABC Random Forest

Estimating recent divergence history: making the most of microsatellite data and Approximate Bayesian Computation approaches

Recommended by and based on reviews by Michael D Greenfield and 2 anonymous reviewers

The present-day distribution of extant species is the result of the interplay between their past population demography (e.g., expansion, contraction, isolation, and migration) and adaptation to the environment. Shedding light on the timing and magnitude of key demographic events helps identify potential drivers of such events and interaction of those drivers, such as life history traits and past episodes of environmental shifts.

The understanding of the key factors driving species evolution gives important insights into how the species may respond to changing conditions, which can be particularly relevant for the management of harmful species, such as agricultural pests (e.g. [1]). Meaningful demographic inferences present major challenges. These include formulating evolutionary scenarios fitting species biology and the eco-geographical context and choosing informative molecular markers and accurate quantitative approaches to statistically compare multiple demographic scenarios and estimate the parameters of interest. A further issue comes with result interpretation. Accurately dating the inferred events is far from straightforward since reliable calibration points are necessary to translate the molecular estimates of the evolutionary time into absolute time units (i.e. years). This can be attempted in different ways, such as by using fossil and archaeological records, heterochronous samples (e.g. ancient DNA), and/or mutation rate estimated from independent data (e.g. [2], [3] for review). Nonetheless, most experimental systems rarely meet these conditions, hindering the comprehensive interpretation of results.

The contribution of Chapuis et al. [4] addresses these issues to investigate the recent history of the African insect pest Schistocerca gregaria (desert locust). They apply Approximate Bayesian Computation-Random Forest (ABC-RF) approaches to microsatellite markers. Owing to their fast mutation rate microsatellite markers offer at least two advantages: i) suitability for analyzing recently diverged populations, and ii) direct estimate of the germline mutation rate in pedigree samples. The work of Chapuis et al. [4] benefits of both these advantages, since they have estimates of mutation rate and allele size constraints derived from germline mutations in the species [5].

The main aim of the study is to infer the history of divergence of the two subspecies of the desert locust, which have spatially disjoint distribution corresponding to the dry regions of North and West-South Africa. They first use paleo-vegetation maps to formulate hypotheses about changes in species range since the last glacial maximum. Based on them, they generate 12 divergence models. For the selection of the demographic model and parameter estimation, they apply the recently developed ABC-RF approach, a powerful inferential tool that allows optimizing the use of summary statistics information content, among other advantages [6]. Some methodological novelties are also introduced in this work, such as the computation of the error associated with the posterior parameter estimates under the best scenario. The accuracy of timing estimate is assured in two ways: i) by the use of microsatellite markers with known evolutionary dynamics, as underlined above, and ii) by assessing the divergence time threshold above which posterior estimates are likely to be biased by size homoplasy and limits in allele size range [7]. The best-supported model suggests a recent divergence event of the subspecies of S. gregaria (around 2.6 kya) and a reduction of populations size in one of the subspecies (S. g. flaviventris) that colonized the southern distribution area. As such, results did not support the hypothesis that the southward colonization was driven by the expansion of African dry environments associated with the last glacial maximum, as it has been postulated for other arid-adapted species with similar African disjoint distributions [8]. The estimated time of divergence points at a much more recent origin for the two subspecies, during the late Holocene, in a period corresponding to fairly stable arid conditions similar to current ones [9,10].

Although the authors cannot exclude that their microsatellite data bear limited information on older colonization events than the last one, they bring arguments in favour of alternative explanations. The hypothesis privileged does not involve climatic drivers, but the particularly efficient dispersal behaviour of the species, whose individuals are able to fly over long distances (up to thousands of kilometers) under favourable windy conditions. A single long-distance dispersal event by a few individuals would explain the genetic signature of the bottleneck. There is a growing number of studies in phylogeography in arid regions in the Southern hemisphere, but the impact of past climate changes on the species distribution in this region remains understudied relative to the Northern hemisphere [11,12].

The study presented by Chapuis et al. [4] offers several important insights into demographic changes and the evolutionary history of an agriculturally important pest species in Africa, which could also mirror the history of other organisms in the continent. As the authors point out, there are necessarily some uncertainties associated with the models of past ecosystems and climate, especially for Africa. Interestingly, the authors argue that the information on paleo-vegetation turnover was more informative than climatic niche modeling for the purpose of their study since it made them consider a wider range of bio-geographical changes and in turn a wider range of evolutionary scenarios (see discussion in Supplementary Material). Microsatellite markers have been offering a useful tool in population genetics and phylogeography for decades, but their popularity is perhaps being taken over by single nucleotide polymorphism (SNP) genotyping and whole-genome sequencing (WGS) (the peak year of the number of the publication with “microsatellite” is in 2012 according to PubMed).

This study reaffirms the usefulness of these classic molecular markers to estimate past demographic events, especially when species- and locus-specific microsatellite mutation features are available and a powerful inferential approach is adopted. Nonetheless, there are still hurdles to overcome, such as the limitations in scenario choice associated with the simulation software used (e.g. not allowing for continuous gene flow in this particular case), which calls for further improvement of simulation tools allowing for more flexible modeling of demographic events and mutation patterns. In sum, this work not only contributes to our understanding of the makeup of the African biodiversity but also offers a useful statistical framework, which can be applied to a wide array of species and molecular markers (microsatellites, SNPs, and WGS).

References

[1] Lehmann, P. et al. (2018). Complex responses of global insect pests to climate change. bioRxiv, 425488. doi: https://dx.doi.org/10.1101/425488

[2] Donoghue, P. C., & Benton, M. J. (2007). Rocks and clocks: calibrating the Tree of Life using fossils and molecules. Trends in Ecology & Evolution, 22(8), 424-431. doi: https://dx.doi.org/10.1016/j.tree.2007.05.005

[3] Ho, S. Y., Lanfear, R., Bromham, L., Phillips, M. J., Soubrier, J., Rodrigo, A. G., & Cooper, A. (2011). Time‐dependent rates of molecular evolution. Molecular ecology, 20(15), 3087-3101. doi: https://dx.doi.org/10.1111/j.1365-294X.2011.05178.x

[4] Chapuis, M.-P., Raynal, L., Plantamp, C., Meynard, C. N., Blondin, L., Marin, J.-M. and Estoup, A. (2020). A young age of subspecific divergence in the desert locust Schistocerca gregaria, inferred by ABC Random Forest. bioRxiv, 671867, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: https://dx.doi.org/10.1101/671867

5] Chapuis, M.-P., Plantamp, C., Streiff, R., Blondin, L., & Piou, C. (2015). Microsatellite evolutionary rate and pattern in Schistocerca gregaria inferred from direct observation of germline mutations. Molecular ecology, 24(24), 6107-6119. doi: https://dx.doi.org/10.1111/mec.13465

[6] Raynal, L., Marin, J. M., Pudlo, P., Ribatet, M., Robert, C. P., & Estoup, A. (2018). ABC random forests for Bayesian parameter inference. Bioinformatics, 35(10), 1720-1728. doi: https://dx.doi.org/10.1093/bioinformatics/bty867

[7] Estoup, A., Jarne, P., & Cornuet, J. M. (2002). Homoplasy and mutation model at microsatellite loci and their consequences for population genetics analysis. Molecular ecology, 11(9), 1591-1604. doi: https://dx.doi.org/10.1046/j.1365-294X.2002.01576.x

[8] Moodley, Y. et al. (2018). Contrasting evolutionary history, anthropogenic declines and genetic contact in the northern and southern white rhinoceros (Ceratotherium simum). Proceedings of the Royal Society B, 285(1890), 20181567. doi: https://dx.doi.org/10.1098/rspb.2018.1567

[9] Kröpelin, S. et al. (2008). Climate-driven ecosystem succession in the Sahara: the past 6000 years. science, 320(5877), 765-768. doi: https://dx.doi.org/10.1126/science.1154913

[10] Maley, J. et al. (2018). Late Holocene forest contraction and fragmentation in central Africa. Quaternary Research, 89(1), 43-59. doi: https://dx.doi.org/10.1017/qua.2017.97

[11] Beheregaray, L. B. (2008). Twenty years of phylogeography: the state of the field and the challenges for the Southern Hemisphere. Molecular Ecology, 17(17), 3754-3774. doi: https://dx.doi.org/10.1111/j.1365-294X.2008.03857.x

[12] Dubey, S., & Shine, R. (2012). Are reptile and amphibian species younger in the Northern Hemisphere than in the Southern Hemisphere?. Journal of evolutionary biology, 25(1), 220-226. doi: https://dx.doi.org/10.1111/j.1420-9101.2011.02417.x

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A video about this preprint is available here:

A young age of subspecific divergence in the desert locust Schistocerca gregaria, inferred by ABC Random ForestMarie-Pierre Chapuis, Louis Raynal, Christophe Plantamp, Christine N. Meynard, Laurence Blondin, Jean-Michel Marin, Arnaud Estoup<p>Dating population divergence within species from molecular data and relating such dating to climatic and biogeographic changes is not trivial. Yet it can help formulating evolutionary hypotheses regarding local adaptation and future responses t...Bioinformatics & Computational Biology, Evolutionary Applications, Phylogeography & Biogeography, Population Genetics / GenomicsTakeshi Kawakami2019-06-20 10:31:15 View
11 Dec 2020
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Quantifying transmission dynamics of acute hepatitis C virus infections in a heterogeneous population using sequence data

Phylodynamics of hepatitis C virus reveals transmission dynamics within and between risk groups in Lyon

Recommended by based on reviews by Chris Wymant and Louis DuPlessis

Genomic epidemiology seeks to better understand the transmission dynamics of infectious pathogens using molecular sequence data. Phylodynamic methods have given genomic epidemiology new power to track the transmission dynamics of pathogens by combining phylogenetic analyses with epidemiological modeling. In recent year, applications of phylodynamics to chronic viral infections such as HIV and hepatitis C virus (HVC) have provided some of the best examples of how phylodynamic inference can provide valuable insights into transmission dynamics within and between different subpopulations or risk groups, allowing for more targeted interventions.
However, conducting phylodynamic inference under complex epidemiological models comes with many challenges. In some cases, it is not always straightforward or even possible to perform likelihood-based inference. Structured SIR-type models where infected individuals can belong to different subpopulations provide a classic example. In this case, the model is both nonlinear and has a high-dimensional state space due to tracking different types of hosts. Computing the likelihood of a phylogeny under such a model involves complex numerical integration or data augmentation methods [1]. In these situations, Approximate Bayesian Computation (ABC) provides an attractive alternative, as Bayesian inference can be performed without computing likelihoods as long as one can efficiently simulate data under the model to compare against empirical observations [2].
Previous work has shown how ABC approaches can be applied to fit epidemiological models to phylogenies [3,4]. Danesh et al. [5] further demonstrate the real world merits of ABC by fitting a structured SIR model to HCV data from Lyon, France. Using this model, they infer viral transmission dynamics between “classical” hosts (typically injected drug users) and “new” hosts (typically young MSM) and show that a recent increase in HCV incidence in Lyon is due to considerably higher transmission rates among “new” hosts . This study provides another great example of how phylodynamic analysis can help epidemiologists understand transmission patterns within and between different risk groups and the merits of expanding our toolkit of statistical methods for phylodynamic inference.

References

[1] Rasmussen, D. A., Volz, E. M., and Koelle, K. (2014). Phylodynamic inference for structured epidemiological models. PLoS Comput Biol, 10(4), e1003570. doi: https://doi.org/10.1371/journal.pcbi.1003570
[2] Beaumont, M. A., Zhang, W., and Balding, D. J. (2002). Approximate Bayesian computation in population genetics. Genetics, 162(4), 2025-2035.
[3] Ratmann, O., Donker, G., Meijer, A., Fraser, C., and Koelle, K. (2012). Phylodynamic inference and model assessment with approximate bayesian computation: influenza as a case study. PLoS Comput Biol, 8(12), e1002835. doi: https://doi.org/10.1371/journal.pcbi.1002835
[4] Saulnier, E., Gascuel, O., and Alizon, S. (2017). Inferring epidemiological parameters from phylogenies using regression-ABC: A comparative study. PLoS computational biology, 13(3), e1005416. doi: https://doi.org/10.1371/journal.pcbi.1005416
[5] Danesh, G., Virlogeux, V., Ramière, C., Charre, C., Cotte, L. and Alizon, S. (2020) Quantifying transmission dynamics of acute hepatitis C virus infections in a heterogeneous population using sequence data. bioRxiv, 689158, ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi: https://doi.org/10.1101/689158

Quantifying transmission dynamics of acute hepatitis C virus infections in a heterogeneous population using sequence dataGonche Danesh, Victor Virlogeux, Christophe Ramière, Caroline Charre, Laurent Cotte, Samuel Alizon<p>Opioid substitution and syringes exchange programs have drastically reduced hepatitis C virus (HCV) spread in France but HCV sexual transmission in men having sex with men (MSM) has recently arisen as a significant public health concern. The fa...Evolutionary Epidemiology, Phylogenetics / PhylogenomicsDavid Rasmussen2019-07-11 13:37:23 View
03 Apr 2020
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Evolution at two time-frames: ancient and common origin of two structural variants involved in local adaptation of the European plaice (Pleuronectes platessa)

Genomic structural variants involved in local adaptation of the European plaice

Recommended by based on reviews by 3 anonymous reviewers

Awareness has been growing that structural variants in the genome of species play a fundamental role in adaptive evolution and diversification [1]. Here, Le Moan and co-authors [2] report empirical genomic-wide SNP data on the European plaice (Pleuronectes platessa) across a major environmental transmission zone, ranging from the North Sea to the Baltic Sea. Regions of high linkage disequilibrium suggest the presence of two structural variants that appear to have evolved 220 kya. These two putative structural variants show weak signatures of isolation by distance when contrasted against the rest of the genome, but the frequency of the different putative structural variants appears to co-vary in some parts of the studied range with the environment, indicating the involvement of both selective and neutral processes. This study adds to the mounting body of evidence that structural genomic variants harbour significant information that allows species to respond and adapt to the local environmental context.

References

[1] Wellenreuther, M., Mérot, C., Berdan, E., & Bernatchez, L. (2019). Going beyond SNPs: the role of structural genomic variants in adaptive evolution and species diversification. Molecular ecology, 28(6), 1203-1209. doi: 10.1111/mec.15066
[2] Le Moan, A. Bekkevold, D. & Hemmer-Hansen J. (2020). Evolution at two time-frames: ancient and common origin of two structural variants involved in local adaptation of the European plaice (Pleuronectes platessa). bioRxiv, 662577, ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/662577

Evolution at two time-frames: ancient and common origin of two structural variants involved in local adaptation of the European plaice (Pleuronectes platessa)Alan Le Moan, Dorte Bekkevold & Jakob Hemmer-Hansen<p>Changing environmental conditions can lead to population diversification through differential selection on standing genetic variation. Structural variant (SV) polymorphisms provide examples of ancient alleles that in time become associated with...Adaptation, Hybridization / Introgression, Population Genetics / Genomics, SpeciationMaren Wellenreuther2019-07-13 12:44:01 View