The study titled "Complex genetic determination of male-fertility restoration in the gynodioecious snail Physa acuta" by Skarlou et al. (doi.org/10.1101/2024.08.08.607164) investigates the genetic mechanisms underlying male fertility restoration in the freshwater snail Physa acuta, a species exhibiting gynodioecy—a reproductive system where both hermaphroditic and female individuals coexist.

In many plant species, cytoplasmic male sterility (CMS) arises from interactions between mitochondrial genes causing male sterility and nuclear genes known as restorers that can suppress this effect, restoring male fertility. While CMS is well-documented in plants, it was unknown in animals until it was recently described in Physa acuta (David et al., 2022), where it was found that different CMS factors were associated with strikingly divergent mitochondrial types. This further study aims to elucidate the inheritance and specificity of male-fertility restoration in P. acuta, providing insights into CMS dynamics in animal systems.

The researchers contrasted lines originating from two natural populations of P. acuta: a "naïve" population with no recent exposure to CMS and a "non-naïve" population where one CMS type is prevalent and largely restored. They found that restoration potential is heritable in both populations and specific to the CMS type. In the naïve population, certain alleles act as weak quantitative modifiers, partially restoring male fertility without prior selection pressure. In the non-naïve population, strong, dominant restorer alleles have evolved, effectively counteracting CMS due to historical selection pressures. These strong alleles were however unable to restore CMS associated with another mitochondrial type.

This study provides the first characterizations of nuclear restorers of CMS in an animal model, highlighting the complexity and variability of genetic interactions involved. It demonstrates that CMS and its restoration are not exclusive to plants and that similar genetic conflicts can shape reproductive strategies in animals. By revealing how population history influences the evolution of restorer alleles, the research offers insights into the coevolutionary dynamics between mitochondrial and nuclear genomes, advancing our understanding of sexual system evolution in hermaphroditic species.

References

Elpida Skarlou, Fanny Laugier, Kévin Béthune, Timothée Chenin, Jean-Marc Donnay, Céline Froissard, Patrice David (2025) Complex genetic determinism of male-fertility restoration in the gynodioecious snail Physa acuta. bioRxiv, ver.3 peer-reviewed and recommended by PCI Evolutionary Biology https://doi.org/10.1101/2024.08.08.607164

David, P., Degletagne, C., Saclier, N., Jennan, A., Jarne, P., Plenet, S., Konecny, L., Francois, C., Gueguen, L., Garcia, N., Lefebure, T., & Luquet, E. (2022). Extreme mitochondrial DNA divergence underlies genetic conflict over sex determination. Current Biology, 32(10), 2325-2333.e6. https://doi.org/10.1016/j.cub.2022.04.014

The breeder’s equation is a classical equation in evolutionary theory, and basically states that the response of a trait to selection is equal to the strength of selection on this trait multiplied by the heritability of the trait. There can be several reasons why reality does not conform to a narrow interpretation of this equation, but in spite of that, let us actually indulge in a broad interpretation of the equation. Typically, the heritability of a trait is interpreted to refer to the genetic basis of a trait (the additive genetic variance). However, a broad interpretation of the breeder’s equation would be that if selection acts on a trait and that trait is somehow heritable, we should expect to observe an evolutionary change in that trait. In other words, the source and mechanism of inheritance does not matter for the breeder’s equation to have applicability.

In this paper, Pujol et al. (2025) follow this rationale for epigenetic variation, and more specifically for differentially methylated regions in the model plant Arabidopsis thaliana. They used 120 lines which vary across 126 differentially methylated regions of the genome, but are genetically identical, thereby eliminating additive genetic variance from the heritability component of the breeder’s equation. Previous studies have already shown that these differentially methylated regions are associated with different phenotypes, suggesting they somehow functionally affect the development of the plants. Previous studies have also shown that these differentially methylated regions are stably transmitted across generation, i.e., that they are heritable. This predicts that if one selects for different phenotypes, there should be an evolutionary response in the phenotypes, and an associated shift in the differentially methylated regions that are responsible for the phenotypic variation.

By and large, this is what Pujol et al. (2025) found. They selected divergently on four different plants traits (biomass, rosette size, flowering time, and height at first fruit), in two different populations, and with two different selection strengths. For most traits they found a phenotypic shift, and this largely corresponded with associated shifts in the differentially methylated regions. The patterns were very congruent between the different selection strengths, and very similar for the two different populations. We can therefore confidently conclude that epigenetic variation has effects on fitness-relevant phenotypic traits, that therefore natural selection can act on this epigenetic variation, and if so that this would cause an evolutionary change in the phenotypes under selection and in the differentially methylated regions causing this phenotypic variation. I.e., the breeder’s equation can indeed by applied to more than just genetically heritable variation, it can also be applied to non-genetically heritable variation. 

While this seems like a very obvious result, there are still very few studies that show how selection on non-genetic heritable variation results in a between-generation shift in this non-genetic heritable variation. In that sense, this study can function as a case in favour of a broader interpretation of evolution; to refer to a heritable between-generation change in the composition of a population, independent of whether the heredity is genetic or non-genetic. Critics might say that this study has only limited validity, since the epigenetic variation has been artificially increased in the used plant lines, and may not reflect naturally occurring variation. Indeed, more studies on natural selection on epigenetic variation are called for, but these will have the added complication that they need to correct for genetic variation, which is often correlated to epigenetic variation. Here, the authors could exclude genetic variation by working with epigenetically different lines that were genetically identical.

The study stands out in yet another respect – it uses a highly unusual and apparently novel selection design (although the authors do not know for sure if their idea is actually novel). Typically, in a selection study only a subset of parents is allowed to reproduce out of the total set of potential parents. If one wants to select for different traits separately, or with different selection strengths, separate selection studies need to be undertaken. Here the authors took a different approach. They let all their parents reproduce (3 offspring per plant), and phenotyped all offspring. They then, virtually, selected for different traits or for different selection strengths in the parents by excluding from their dataset the offspring of parents that are selected not to reproduce – after they had actually already reproduced! It is almost as if selection acts with a time delay, destroying not only the selected parents but also their offspring. This has the benefit that a single dataset is generated (all phenotyped offspring of all parents), and then selection can be exerted as often as one wants, for example for distinct types of selection, or on different (combinations) of traits. While the initial effort to phenotype offspring of all potential parents is large, and exponentially so if multiple generations are selected, the subsequent evaluation of distinct types of selection on any of the phenotyped traits is virtually effortless. For example, the authors applied divergent selection, but could reuse their dataset to apply stabilising selection. This novel selection design may therefore be a very attractive approach for many other researchers.

References

Benoit Pujol, Mathieu Latutrie, Pierick Mouginot, Nelia Luviano- Aparicio, Jésaëlle Piquet, Sara Marin, and Stéphane Maury (2025) Experimental evidence for short term directional selection of epigenetic trait variation. Zenodo, ver.2 peer-reviewed and recommended by PCI Evolutionary Biology https://doi.org/10.5281/zenodo.15227609

The study by Pfenninger (2025) addresses the critical need to understand the genomic basis of ecologically important traits to better predict and respond to the impacts of global change on biodiversity (Gienapp et al. 2017). It introduces the popGWAS, a novel GWAS approach, which utilizes phenotypic population means and genome-wide allele frequency data, obtainable through methods like Pool-sequencing (Pool-Seq), to identify the genetic loci underlying quantitative polygenic traits in natural populations and predict their mean. The core idea is that trait-increasing alleles should exhibit higher frequencies in populations with higher mean trait values. popGWAS then maps mean allele frequencies across populations to their trait means. Working with as many allele frequency values as populations sampled, popGWAS potentially has more power to find significant associations at genomic loci than individual-based GWAS working with three genotypes at a locus. This new method addresses some of the problems faced by traditional genome-wide association studies (GWAS), which require extensive resources and large sample sizes, posing challenges for biodiversity research on non-model species in natural populations. 

To evaluate the effectiveness of popGWAS, Pfenninger (2025) conducted extensive population genetic forward simulations, examining scenarios with varying numbers of populations, ranging from 12 to 60. The results indicated that popGWAS performance improved with increasing sample size, showing a diminishing return above 36 populations. In a direct comparison across all simulation scenarios, popGWAS consistently outperformed individual-based GWAS (iGWAS). On average, popGWAS identified more true positive loci than iGWAS. In addition, when combined with minimum entropy feature selection (MEFS), popGWAS achieved large predictive accuracy of population means of 0.8 or better in over 97% of simulations with 36 or more populations, regardless of other parameters. In contrast, iGWAS failed to generate valid phenotypic predictions in over 70% of the simulations. Also, unlike iGWAS, popGWAS did not suffer from p-value inflation. Yet, population structure or varying levels of relatedness among individuals were not fully accounted for in the simulations. The extent to which popGWAS would be sensitive to such individual covariates remains to be shown. Finally, popGWAS was relatively insensitive to low trait heritability because random individual variation gets averaged out when calculating the population mean trait value. 

The study demonstrates that popGWAS is a promising approach, particularly for oligogenic and moderately polygenic traits. The method performs more poorly for polygenic traits with large genetic redundancy, where different alleles contribute to the same trait mean in different populations. The method thus performs better when large-effect loci contribute to genetic differentiation in parallel across populations, as expected when gene flow is moderate to high (Yeaman & Whitlock 2011). Low genomic predictability is reached when drift dominates or when genetic architectures are highly polygenic.

The popGWAS method proved effective with a moderate number of sampled populations and, when combined with machine learning for genomic prediction, exhibited strong performance in predicting population means, even for low-heritability traits. Notably, popGWAS consistently outperformed iGWAS in terms of identifying true positive loci and prediction accuracy. This suggests that popGWAS can make GWAS studies more accessible for biodiversity genomics research, providing a valuable tool for dissecting the genetic basis of complex traits in natural populations. A key aspect contributing to the efficiency of popGWAS is its compatibility with pooled sequencing (Pool-Seq). Pool-Seq provides estimates of allele frequencies within a population by sequencing a mixed DNA sample representing multiple individuals from that population (Futschik & Schlötterer 2010). This approach is significantly more cost-effective than sequencing each individual separately, allowing researchers to obtain genome-wide allele frequency data across multiple populations with a substantially reduced budget. This data efficiency makes GWAS more accessible to a wider range of researchers, particularly those working in biodiversity genomics where financial resources may be limited. Furthermore, popGWAS can be coupled with bulk phenotyping methods, such as automatic video recording, remote sensing, metabolomics/transcriptomics, etc., to efficiently obtain population-level phenotypic data, further streamlining the research process. Ultimately, popGWAS represents a valuable addition to the geneticist's toolkit, offering a complementary approach to iGWAS that can be particularly advantageous in specific research contexts where predicting trait mean is more important than resolving the precise genetic basis of a trait.

References

Futschik, A. and Schlötterer, C. 2010. The Next Generation of Molecular Markers From Massively Parallel Sequencing of Pooled DNA Samples. Genetics 186(1): 207-218. https://doi.org/10.1534/genetics.110.114397

Gienapp, P., Fior, S., Guillaume, F., Lasky, J. R., Sork, V. L. and Csilléry, K. 2017. Genomic Quantitative Genetics to Study Evolution in the Wild. Trends Ecol. Evol. 32(12): 897-908. https://doi.org/10.1016/j.tree.2017.09.004

Markus Pfenninger (2025) On the potential for GWAS with phenotypic population means and allele-frequency data (popGWAS). bioRxiv, ver.3 peer-reviewed and recommended by PCI Evol Biol https://doi.org/10.1101/2024.06.12.598621

Yeaman, S. and Whitlock, M. C. 2011. The genetic architecture of adaptation under migration-selection balance. Evolution 65(7): 1897-1911. https://doi.org/10.1111/j.1558-5646.2011.01269.x

The joint full distribution of fitness effects (DEF) is an important indicator in population genetic studies, and its inference has been the subject of intense research [1]. However, we still lack a solid framework to estimate DFE under certain demographic conditions.

In this study, Castellano and colleagues propose to estimate the DFE by analysing the site frequency spectrum (SFS), and specifically develop a new approach for the joint DFE model inference [2]. The latter is based on the proportion of variants with divergent selection coefficients. Authors performed extensive simulations under models of domestication which is arguably one of the most crucial series of events in human evolution [3]. Domestication is associated with significant genetic costs in animals [4].

While DFE is typically estimated by contrasting SFS of silent and functional mutations [5], it has been recently suggested to use the joint SFS between domesticated and wild populations to estimate the DFE [6]. Authors build on this model and expand its parameterisation. Authors were able to dissect the impact of linked selection on inferred demographic history of wild and domesticated populations, with a robust estimation of the deleterious DFE.

There are still several limitations in the interpretation of DFE as, for instance, some selective sweeps can bias their estimates and some demographic scenarios are challenging to infer. Also, classic quantitative trait models should be evaluated as a complementary approach. Finally, the in silico predictions presented in this study could be validated by empirical scans on existing genomic data sets. Nevertheless, this study is an important contribution to our understanding on how demography, and domestication in particular, can affect variants under selection in recent evolutionary histories.

References

[1] Eyre-Walker A, Keightley PD. The distribution of fitness effects of new mutations. Nat Rev Genet. 2007;8(8):610-618. https://doi.org/10.1038/nrg2146

[2] Castellano D, Vourlaki IT, Gutenkunst RN, Ramos-Onsins SE. Detection of Domestication Signals through the Analysis of the Full Distribution of Fitness Effects. BioRxiv 2025, ver.4 peer-reviewed and recommended by PCI Evol Biol https://doi.org/10.1101/2022.08.24.505198

[3] Frantz LAF, Bradley DG, Larson G, Orlando L. Animal domestication in the era of ancient genomics. Nat Rev Genet. 2020;21(8):449-460. https://doi.org/10.1038/s41576-020-0225-0

[4] Schubert M, Jónsson H, Chang D, et al. Prehistoric genomes reveal the genetic foundation and cost of horse domestication. Proc Natl Acad Sci U S A. 2014;111(52):E5661-E5669. https://doi.org/10.1073/pnas.1416991111

[5] Kousathanas A, Keightley PD. A comparison of models to infer the distribution of fitness effects of new mutations. Genetics. 2013;193(4):1197-1208. https://doi.org/10.1534/genetics.112.148023

[6] Huang X, Fortier AL, Coffman AJ, et al. Inferring Genome-Wide Correlations of Mutation Fitness Effects between Populations. Mol Biol Evol. 2021;38(10):4588-4602. https://doi.org/10.1093/molbev/msab162

The study by Le Cam and colleagues, entitled “Discordant population structure inferred from male- and female-type mtDNAs from Macoma balthica, a bivalve species characterized by doubly uniparental inheritance of mitochondria”, provides a fascinating exploration of the genetic structure and evolutionary dynamics of the Baltic tellin, Macoma balthica, a bivalve species exhibiting doubly uniparental inheritance (DUI) of mitochondria. This work is a significant contribution to the field of evolutionary biology, particularly in understanding how sex-specific mitochondrial inheritance can shape population structure and genetic diversity in marine organisms.

DUI is a remarkable exception to the typical maternal inheritance of mitochondria in metazoans, where both males and females can transmit their mitochondria, but through different routes. In species with DUI, females pass on their mitochondria to all offspring, while males transmit their mitochondria exclusively to their sons. This system results in males being heteroplasmic, carrying both maternal (F-type) and paternal (M-type) mitochondrial DNA (mtDNA). The study leverages this unique inheritance pattern to investigate the genetic diversity, divergence, and population structure of M. balthica across its distribution range, from the North Sea to the Gironde Estuary in Southern France.

One of the most striking findings of this study is the discordant population structure inferred from the male- and female-type mtDNAs. The authors sequenced the cox1 gene from both F-type and M-type mtDNA in 302 male individuals across 14 sampling sites. They found that the genetic differentiation between northern and southern populations was nearly three times higher for the M-type mtDNA compared to the F-type mtDNA. This discrepancy was further highlighted by the geographic localization of the strongest genetic break, which differed significantly between the two markers. For the F-type mtDNA, the break was located at the Finistère Peninsula, while for the M-type mtDNA, it was found at the Cotentin Peninsula, approximately 250 km apart. The authors propose several explanations for these differences, including a higher mutation rate, relaxed negative selection, and variations in effective population sizes for the M-type mtDNA. These factors could contribute to the observed divergence in genetic structure between the two mitochondrial types. Additionally, the study suggests that mito-nuclear genetic incompatibilities, arising from the interaction between mitochondrial and nuclear genes involved in oxidative phosphorylation and ATP production, could play a role in maintaining these genetic barriers.

The study also provides valuable insights into the phylogeographic history of M. balthica. The divergence times estimated for the F-type and M-type mtDNA clades suggest that the split between the northern and southern populations occurred before the last glacial maximum (LGM). This finding supports a scenario of pre-LGM vicariance rather than post-glacial primary intergradation. The authors' use of net divergence to estimate the timing of cladogenesis events within the Macoma species complex adds a robust temporal dimension to their phylogeographic analysis.

Another intriguing aspect of the study is the evidence of asymmetric introgression and hybrid zone dynamics. The authors observed that the genetic clines for the F-type and M-type mtDNAs were not only discordant in their geographic locations but also in their widths. The cline for the M-type mtDNA was significantly narrower than that for the F-type mtDNA, suggesting different selective pressures or migration balances acting on the two mitochondrial types. This finding raises important questions about the role of sex-specific selection and gene flow in shaping the genetic structure of populations with DUI.

The study also highlights the importance of considering sex-specific genetic markers in population genetic studies. One of the most intriguing aspects is the implication that M-type mtDNA may be evolving under different constraints than its female counterpart. The authors found higher nucleotide diversity and net divergence in M-type sequences suggestive of a relaxed selective regime or an increased mutation rate, which aligns with previous studies on DUI species. Given that M-type mitochondria function predominantly in sperm cells, the potential for oxidative damage, reduced purifying selection, and a higher mutation rate could explain these patterns. More broadly, this finding reinforces the idea that mitochondrial genomes, though typically constrained by purifying selection, can evolve along sex-specific trajectories when their inheritance is decoupled from maternal transmission.

While the study provides compelling evidence for the role of DUI in shaping the genetic structure of M. balthica, it also raises several questions for future research. For instance, the mechanisms underlying the higher mutation rate and relaxed selection in the M-type mtDNA remain to be fully elucidated. Additionally, the potential role of mito-nuclear incompatibilities in maintaining genetic barriers warrants further investigation. The authors suggest that future studies should explore the fitness consequences of inter-lineage crosses and the potential for asymmetric hybrid fitness in the context of DUI.

In conclusion, Le Cam and colleagues have made a significant contribution to our understanding of the evolutionary dynamics of mitochondrial inheritance in bivalves. Their findings not only shed light on the complex interplay between genetic, demographic, and selective factors in shaping population structure but also underscore the importance of considering sex-specific genetic markers in evolutionary studies. This work opens up new avenues for research into the role of DUI in speciation, adaptation, and the maintenance of genetic diversity in marine organisms.

References

Sabrina Le Cam, Brémaud Julie, Vanessa Becquet, Valerie Huet, Pascale Garcia, Amélia Viricel, Sophie Breton, Eric Pante (2025) Discordant population structure inferred from male- and female-type mtDNAs from Macoma balthica, a bivalve species characterized by doubly uniparental inheritance of mitochondria. bioRxiv, ver.4 peer-reviewed and recommended by PCI Evol Biol https://doi.org/10.1101/2022.02.28.479517