In this study sperm morphology is studied in 15 Daphnia species and the morphological data are mapped on a Daphnia phylogeny. The authors found that despite the internal fertilization mode, Daphnia have among the smallest sperm recorded, as would be expected with external fertilization. The authors also conclude that increase in sperm length has evolved twice, that sperm encapsulation has been lost in a clade, and that this clade has very polymorphic sperm with long, and often numerous, filopodia.

Daphnia is an interesting model to study sperm morphology because the biology of sexual reproduction is often ignored in (cyclical) parthenogenetic species. Daphnia is part of the very diverse and successful group of cladocerans with cyclical parthenogenetic reproduction. The success of this reproduction mode is reflected in the known 620 species that radiated within this order, this is more than half of the known Branchiopod species diversity and the estimated number of cladoceran species is even two to four times higher (Forró et al. 2008). Looking at this particular model with a good phylogeny and some particularity in the mode of fertilization/reproduction, has thus a large value. Most Daphnia species are cyclical parthenogenetic and switch between sexual and asexual reproduction depending on the environmental conditions. Within the genus Daphnia, evolution to obligate asexuality has evolved in at least four independent occasions by three different mechanisms: (i) obligate parthenogenesis through hybridisation with or without polyploidy, (ii) asexuality has been acquired de novo in some populations and (iii) in certain lineages females reproduce by obligate parthenogenesis, whereas the clonally propagated males produce functional haploid sperm that allows them to breed with sexual females of normal cyclically parthenogenetic lineages (more on this in Decaestecker et al. 2009).

This study is made in the context of a body of research on the evolution of one of the most fundamental and taxonomically diverse cell types. There is surprisingly little known about the adaptive value underlying their morphology because it is very difficult to test this experimentally.  Studying sperm morphology across species is interesting to study evolution itself because it is a "simple trait". As the authors state: The understanding of the adaptive value of sperm morphology, such as length and shape, remains largely incomplete (Lüpold & Pitnick, 2018). Based on phylogenetic analyses across the animal kingdom, the general rule seems to be that fertilization mode (i.e. whether eggs are fertilized within or outside the female) is a key predictor of sperm length (Kahrl et al., 2021). There is a trade-off between sperm number and length (Immler et al., 2011). This study reports on one of the smallest sperm recorded despite the fertilization being internal. The brood pouch in Daphnia is an interesting particularity as fertilisation occurs internally, but it is not disconnected from the environment. It is also remarkable that there are two independent evolution lines of sperm size in this group. It suggests that those traits have an adaptive value. 

References

Decaestecker E, De Meester L, Mergeay J (2009) Cyclical Parthenogenesis in Daphnia: Sexual Versus Asexual Reproduction. In: Lost Sex: The Evolutionary Biology of Parthenogenesis (eds Schön I, Martens K, Dijk P), pp. 295–316. Springer Netherlands, Dordrecht. https://doi.org/10.1007/978-90-481-2770-2_15

Duneau David, Möst M, Ebert D (2022) Evolution of sperm morphology in a crustacean genus with fertilization inside an open brood pouch. bioRxiv, 2020.01.31.929414, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2020.01.31.929414

Forró L, Korovchinsky NM, Kotov AA, Petrusek A (2008) Global diversity of cladocerans (Cladocera; Crustacea) in freshwater. Hydrobiologia, 595, 177–184. https://doi.org/10.1007/s10750-007-9013-5

Immler S, Pitnick S, Parker GA, Durrant KL, Lüpold S, Calhim S, Birkhead TR (2011) Resolving variation in the reproductive tradeoff between sperm size and number. Proceedings of the National Academy of Sciences, 108, 5325–5330. https://doi.org/10.1073/pnas.1009059108

Kahrl AF, Snook RR, Fitzpatrick JL (2021) Fertilization mode drives sperm length evolution across the animal tree of life. Nature Ecology & Evolution, 5, 1153–1164. https://doi.org/10.1038/s41559-021-01488-y

Lüpold S, Pitnick S (2018) Sperm form and function: what do we know about the role of sexual selection? Reproduction, 155, R229–R243. https://doi.org/10.1530/REP-17-0536

​Of the four evolutionary forces, three can be straightforwardly summarized both conceptually and mathematically in the context of an allele at a genomic locus.  Mutation (the mutation rate, μ) is simply captured by the per-site, per-generation probability that an allele mutates into a different allele. Recombination (the recombination rate, r) is captured as the probability of recombination between two sites, wherein alleles that are in different genomes in one generation come together in the same genome in the next generation.  Natural selection (the selection coefficient, s) is captured by the probability that an allele is present in the next generation, relative to some reference.  

Random genetic drift – the random fluctuation in allele frequency due to sampling in a finite population - is not so straightforwardly summarized.  The first, and most common way of characterizing evolutionary dynamics in a finite population is the Wright-Fisher model, in which the only deviation from the assumptions of Hardy-Weinberg conditions is finite population size.  Importantly, in a W-F population, mating between diploid individuals is random, which implies self-fertile monoecy, and generations are non-overlapping.  In an ideal W-F population, the probability that a gene copy leaves i descendants in the next generation is the result of binomial sampling of uniting gametes (if the locus is biallelic).  The – and the next word is meaningful – magnitude/strength/rate/power/amount of genetic drift is proportional to 1/2N, where N is the size of the population.  All of the following are affected by genetic drift: (1) the probability that a neutral allele ultimately reaches fixation, (2) the rate of loss of genetic variation within a population, (3) the rate of increase of genetic variance among populations, (4) the amount of genetic variation segregating in a population, (5) the probability of fixation/loss of a weakly selected variant.    

Presumably no real population adheres to ideal W-F conditions, which leads to the notion of "effective population size", Ne (Wright 1931), loosely defined as "the size of an ideal W-F population that experiences an equivalent strength of genetic drift".  Almost always, Ne<N, and any violation of W-F assumptions can affect Ne.  Importantly, Ne can be defined in different ways, and the specific formulation of Ne can have different implications for evolution.  Ne was initially defined in terms of the rate of decrease of heterozygosity (inbreeding effective size) and increase in variance among populations (variance effective size).  Ewens (1979) defined the Eigenvalue effective size (equivalent to the "random extinction" effective size) and elaborated on the conditions under which the various formulations of Ne differ (Ewens 1982).  Nordborg and Krone (2002) defined the effective size in terms of the coalescent, and they identified conditions in which genetic drift cannot be described in terms of a W-F model (Sjodin et al. 2005); also see Karasov et al. (2010); Neher and Shraiman (2011).

Distinct from the issue of defining Ne is the issue of calculating Ne from data, which is the focus of this paper by De Meeus and Noûs (2023).  Pudovkin et al. (1996) showed that the Eigenvalue effective size in a dioecious population can be formulated in terms of excess heterozygosity, which the current authors note is equivalent to formulating Ne in terms of Wright's FIS statistic.  As emphasized by the title, the marquee contribution of this paper is to provide a better approximation of the Eigenvalue effective size in a dioecious population.  Science marches onward, although the empirical utility of this advance is obviously limited, given the tremendous inherent sources of uncertainty in real-world estimates of Ne.  Perhaps more valuable, however, is the extensive set of appendixes, in which detailed derivations are provided for the various formulations of effective size.  By way of analogy, the material presented here can be thought of as an extension of the material presented in section 7.6 of Crow and Kimura (1970), in which the Inbreeding and Variance effective population sizes are derived and compared.  The appendixes should serve as a handy go-to source of detailed theoretical information with respect to the different formulations of effective population size.

REFERENCES

Crow, J. F. and M. Kimura. 1970. An Introduction to Population Genetics Theory. The Blackburn Press, Caldwell, NJ.

De Meeûs, T. and Noûs, C. 2023. A new and almost perfectly accurate approximation of the eigenvalue effective population size of a dioecious population: comparisons with other estimates and detailed proofs. Zenodo, ver. 6 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.5281/zenodo.7927968

Ewens, W. J. 1979. Mathematical Population Genetics. Springer-Verlag, Berlin.

Ewens, W. J. 1982. On the concept of the effective population size. Theoretical Population Biology 21:373-378. https://doi.org/10.1016/0040-5809(82)90024-7

Karasov, T., P. W. Messer, and D. A. Petrov. 2010. Evidence that adaptation in Drosophila Is not limited by mutation at single sites. Plos Genetics 6. https://doi.org/10.1371/journal.pgen.1000924

Neher, R. A. and B. I. Shraiman. 2011. Genetic Draft and Quasi-Neutrality in Large Facultatively Sexual Populations. Genetics 188:975-U370. https://doi.org/10.1534/genetics.111.128876

Nordborg, M. and S. M. Krone. 2002. Separation of time scales and convergence to the coalescent in structured populations. Pp. 194–232 in M. Slatkin, and M. Veuille, eds. Modern Developments in Theoretical Population Genetics: The Legacy of Gustave Malécot. Oxford University Press, Oxford. https://www.webpages.uidaho.edu/~krone/malecot.pdf

Pudovkin, A. I., D. V. Zaykin, and D. Hedgecock. 1996. On the potential for estimating the effective number of breeders from heterozygote-excess in progeny. Genetics 144:383-387. https://doi.org/10.1093/genetics/144.1.383

Sjodin, P., I. Kaj, S. Krone, M. Lascoux, and M. Nordborg. 2005. On the meaning and existence of an effective population size. Genetics 169:1061-1070. https://doi.org/10.1534/genetics.104.026799

Wright, S. 1931. Evolution in Mendelian populations. Genetics 16:0097-0159. https://doi.org/10.1093/genetics/16.2.97

Studying the evolution of animal cognition is challenging because many environmental and species-related factors can be intertwined, which is further complicated when looking at deep-time evolution. Previous knowledge has emphasized the role of intraspecific interactions in affecting the socio-ecological environment shaping cognition. However, much less is known about such an effect at the interspecific level. Yet, the coexistence of different species in the same geographic area at a given time (sympatry) can impact the evolutionary history of species through character displacement due to biotic interactions. Trait evolution has been observed and tested with morphological external traits but more rarely with brain evolution. Compared to most species’ traits, brain evolution is even more delicate to assess since specific brain regions can be involved in different functions, may they be individual-based and social-based information processing. 

In a very original and thoroughly executed study, Robira & Perez-Lamarque (2023) addressed the question: How does the co-occurrence of congeneric species shape brain evolution and influence species diversification? By considering brain size as a proxy for cognition, they evaluated whether species sympatry impacted the evolution of cognition in frugivorous primates. Fruit resources are hard to find, not continuous through time, heterogeneously distributed across space, but can be predictable. Hence, cognition considerably shapes the foraging strategy and competition for food access can be fierce. Over long timescales, it remains unclear whether brain size and the pace of species diversification are linked in the context of sympatry, and if so how. Recent studies have found that larger brain sizes can be associated with higher diversification rates in birds (Sayol et al. 2019). Similarly, Robira & Perez-Lamarque (2023) thus wondered if the evolution of brain size in primates impacted their dynamic of species diversification, which has been suggested (Melchionna et al. 2020) but not tested.

Prior to anything, Robira & Perez-Lamarque (2023) had to retrace the evolutionary history of sympatry between frugivorous primate lineages through time using the primate tree of life, species’ extant distribution, and process-based models to estimate ancestral range evolution. To infer the effect of species sympatry on the evolution of cognition in frugivorous primates, the authors evaluated the support for phylogenetic models of brain size evolution accounting or not for species sympatry and investigated the directionality of the selection induced by sympatry on brain size evolution. Finally, to better understand the impact of cognition and interactions between primates on their evolutionary success, they tested for correlations between brain size or species’ sympatry and species diversification.

Robira & Perez-Lamarque (2023) found that the evolution of the whole brain or brain regions used in immediate information processing was best fitted with models not considering sympatry. By contrast, models considering species sympatry best predicted the evolution of brain regions related to long-term memory of interactions with the socio-ecological environment, with a decrease in their size along with stronger sympatry. Specifically, they found that sympatry was associated with a decrease in the relative size of the hippocampus and striatum, but had no significant effect on the neocortex, cerebellum, or overall brain size.

The hippocampus is a brain region that plays a crucial role in processing and memorizing spatiotemporal information, which is relevant for frugivorous primates in their foraging behavior. The study suggests that competition between sympatric species for limited food resources may lead to a more complex and unpredictable food distribution, which may in turn render cognitive foraging not advantageous and result in a selection for smaller brain regions involved in foraging. Niche partitioning and dietary specialization in sympatry may also impact cognitive abilities, with more specialized diets requiring lower cognitive abilities and smaller brain region sizes.

On the other hand, the absence of an effect of sympatry on brain regions involved in immediate sensory information processing, such as the cerebellum and neocortex, suggests that foragers do not exploit cues left out by sympatric heterospecific species, or they may discard environmental cues in favor of social cues.

This is a remarkable study that highlights the importance of considering the impact of ecological factors, such as sympatry, on the evolution of specific brain regions involved in cognitive processes, and the potential trade-offs in brain region size due to niche partitioning and dietary specialization in sympatry. Further research is needed to explore the mechanisms behind these effects and to test for the possible role of social cues in the evolution of brain regions. This study provides insights into the selective pressures that shape brain evolution in primates.

References

Melchionna M, Mondanaro A, Serio C, Castiglione S, Di Febbraro M, Rook L, Diniz-Filho JAF, Manzi G, Profico A, Sansalone G, Raia P (2020) Macroevolutionary trends of brain mass in Primates. Biological Journal of the Linnean Society, 129, 14–25. https://doi.org/10.1093/biolinnean/blz161

Robira B, Perez-Lamarque B (2023) Primate sympatry shapes the evolution of their brain architecture. bioRxiv, 2022.05.09.490912, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.05.09.490912

Sayol F, Lapiedra O, Ducatez S, Sol D (2019) Larger brains spur species diversification in birds. Evolution, 73, 2085–2093. https://doi.org/10.1111/evo.13811

Differentiation-based genome scans lie at the core of speciation and adaptation genomics research. Dating back to Lewontin & Krakauer (1973), they have become very popular with the advent of genomics to identify genome regions of enhanced differentiation relative to neutral expectations. These regions may represent genetic barriers between divergent lineages and are key for studying reproductive isolation. However, genome scan methods can generate a high rate of false positives, primarily if the neutral population structure is not accounted for (Bierne et al. 2013). Moreover, interpreting genome scans can be challenging in the context of secondary contacts between diverging lineages (Bierne et al. 2011), because the coupling between different components of reproductive isolation (local adaptation, intrinsic incompatibilities, mating preferences, etc.) can occur readily, thus preventing the causes of differentiation from being determined.

Smadja and collaborators (2022) applied a sophisticated genome scan for trait association (BAYPASS, Gautier 2015) to underlie the genetic basis of a polygenetic behaviour: assortative mating in hybridizing mice. My interest in this neat study mainly relies on two reasons. First, the authors used an ingenious geographical setting (replicate pairs of “Choosy” versus “Non-Choosy” populations) with multi-way comparisons to narrow down the list of candidate regions resulting from BAYPASS. The latter corrects for population structure, handles cost-effective pool-seq data and allows for gene-based analyses that aggregate SNP signals within a gene. These features reinforce the set of outlier genes detected; however, not all are expected to be associated with mating preference. 

The second reason why this study is valuable to me is that Smadja et al. (2022) complemented the population genomic approach with functional predictions to validate the genetic signal. In line with previous behavioural and chemical assays on the proximal mechanisms of mating preferences, they identified multiple olfactory and vomeronasal receptor genes as highly significant candidates. Therefore, combining genomic signals with functional analyses is a clever way to provide insights into the causes of reproductive isolation, especially when multiple barriers are involved. This is typically true for reinforcement (Butlin & Smadja 2018), suspected to occur in these mice because, in that case, assortative mating (a prezygotic barrier) evolves in response to the cost of hybridization (for example, due to hybrid inviability). 

As advocated by the authors, their study paves the way for future work addressing the genetic basis of reinforcement, a trait of major evolutionary importance for which we lack empirical data. They also make a compelling case using complementary approaches that olfactory and vomeronasal receptors have a central role in mammal speciation.

References:

Bierne N, Welch J, Loire E, Bonhomme F, David P (2011) The coupling hypothesis: why genome scans may fail to map local adaptation genes. Mol Ecol 20: 2044–2072. https://doi.org/10.1111/j.1365-294X.2011.05080.x

Bierne N, Roze D, Welch JJ (2013) Pervasive selection or is it…? why are FST outliers sometimes so frequent? Mol Ecol 22: 2061–2064. https://doi.org/10.1111/mec.12241 

Butlin RK, Smadja CM (2018) Coupling, Reinforcement, and Speciation. Am Nat 191:155–172. https://doi.org/10.1086/695136 

Gautier M (2015) Genome-Wide Scan for Adaptive Divergence and Association with Population-Specific Covariates. Genetics 201:1555–1579. https://doi.org/10.1534/genetics.115.181453 

Lewontin RC, Krakauer J (1973) Distribution of gene frequency as a test of the theory of selective neutrality of polymorphisms. Genetics 74: 175–195. https://doi.org/10.1093/genetics/74.1.175 

Smadja CM, Loire E, Caminade P, Severac D, Gautier M, Ganem G (2022) Divergence of olfactory receptors associated with the evolution of assortative mating and reproductive isolation in mice. bioRxiv, 2022.07.21.500634, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.07.21.500634

Theoretical work, initiated by Levene (1953) [1] and Dempster (1955) [2], suggests that within a given environment, the way populations are regulated and contribute to the next generation is a key factor for the maintenance of local adaptation polymorphism. In this theoretical context, hard selection describes the situation where the genetic composition of each population affects its contribution to the next generation whereas soft selection describes the case where the contribution of each population is fixed, whatever its genetic composition. Soft selection is able to maintain polymorphism, whereas hard selection invariably leads to the fixation of one of the alleles. Although the specific conditions (e.g. of migration between populations or drift level) in which this prediction holds have been studied in details by theoreticians, experimental tests have mainly failed, usually leading to the conclusion that the allele frequency dynamics was driven by other mechanisms in the experimental systems and conditions used. Gallet, Froissart and Ravigné [3] have set up a bacterial experimental system which allowed them to convincingly demonstrate that soft selection generates the conditions for polymorphism maintenance when hard selection does not, everything else being equal. The key ingredients of their experimental system are (1) the possibility to accurately produce hard and soft selection regimes when daily transferring the populations and (2) the ability to establish artificial well-characterized reproducible trade-offs. To do so, they used two genotypes resisting each one to one antibiotic and combined, across habitats, low antibiotic doses and difference in medium productivity. The experimental approach contains two complementary parts: the first one is looking at changes in the frequencies of two genotypes, initially introduced at around 50% each, over a small number of generations (ca 40) in different environments and selection regimes (soft/hard) and the second one is convincingly showing polymorphism protection by establishing that in soft selection regimes, the lowest fitness genotype is not eliminated even when introduced at low frequency. In this manuscript, a key point is the dialog between theoretical and experimental approaches. The experiments have been thought and designed to be as close as possible to the situations analysed in theoretical work. For example, the experimental polymorphism protection test (experiment 2) closely matches the equivalent analysis classically performed in theoretical approaches. This close fit between theory and experiment is clearly a strength of this study. This said, the experimental system allowing them to realise this close match also has some limitations. For example, changes in allele frequencies could only be monitored over a quite low number of generations because a longer time-scale would have allowed the contribution of de novo mutations and the likely emergence of a generalist genotype resisting to both antibiotics used to generate the local adaptation trade-offs. These limitations, as well as the actual significance of the experimental tests, are discussed in deep details in the manuscript.

References

[1] Levene H. 1953. Genetic equilibrium when more than one niche is available. American Naturalist 87: 331–333. doi: 10.1086/281792

[2] Dempster ER. 1955. Maintenance of genetic heterogeneity. Cold Spring Harbor Symposia on Quantitative Biology. 20: 25–32. doi: 10.1101/SQB.1955.020.01.005

[3] Gallet R, Froissart R, Ravigné V. 2017. Things softly attained are long retained: dissecting the impacts of selection regimes on polymorphism maintenance in experimental spatially heterogeneous environments. bioRxiv 100743; doi: 10.1101/100743