The human genome not only encodes for biological functions and for what makes us human, it also encodes the population history of our ancestors. Changes in past population sizes, for example, affect the distribution of times to the most recent common ancestor (tMRCA) of genomic segments, which in turn can be inferred by sophisticated modelling along the genome.
A key framework for such modelling of local tMRCA tracts along genomes is the Sequentially Markovian Coalescent (SMC) (McVean and Cardin 2005, Marjoram and Wall 2006) . The problem that the SMC solves is that the mosaic of local tMRCAs along the genome is unknown, both in their actual ages and in their positions along the genome. The SMC allows to effectively sum across all possibilities and handle the uncertainty probabilistically. Several important tools for inferring the demographic history of a population have been developed built on top of the SMC, including PSMC (Li and Durbin 2011), diCal (Sheehan et al 2013), MSMC (Schiffels and Durbin 2014), SMC++ (Terhorst et al 2017), eSMC (Sellinger et al. 2020) and others.
In this paper, Sellinger, Abu Awad and Tellier (2020) review these SMC-based methods and provide a coherent simulation design to comparatively assess their strengths and weaknesses in a variety of demographic scenarios (Sellinger, Abu Awad and Tellier 2020). In addition, they used these simulations to test how breaking various key assumptions in SMC methods affects estimates, such as constant recombination rates, or absence of false positive SNP calls.
As a result of this assessment, the authors not only provide practical guidance for researchers who want to use these methods, but also insights into how these methods work. For example, the paper carefully separates sources of error in these methods by observing what they call “Best-case convergence” of each method if the data behaves perfectly and separating that from how the method applies with actual data. This approach provides a deeper insight into the methods than what we could learn from application to genomic data alone.
In the age of genomics, computational tools and their development are key for researchers in this field. All the more important is it to provide the community with overviews, reviews and independent assessments of such tools. This is particularly important as sometimes the development of new methods lacks primary visibility due to relevant testing material being pushed to Supplementary Sections in papers due to space constraints. As SMC-based methods have become so widely used tools in genomics, I think the detailed assessment by Sellinger et al. (2020) is timely and relevant.
In conclusion, I recommend this paper because it bridges from a mere review of the different methods to an in-depth assessment of performance, thereby addressing both beginners in the field who just seek an initial overview, as well as experienced researchers who are interested in theoretical boundaries and assumptions of the different methods.

References

[1] Li, H., and Durbin, R. (2011). Inference of human population history from individual whole-genome sequences. Nature, 475(7357), 493-496. doi: https://doi.org/10.1038/nature10231
[2] Marjoram, P., and Wall, J. D. (2006). Fast"" coalescent"" simulation. BMC genetics, 7(1), 16. doi: https://doi.org/10.1186/1471-2156-7-16
[3] McVean, G. A., and Cardin, N. J. (2005). Approximating the coalescent with recombination. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1459), 1387-1393. doi: https://doi.org/10.1098/rstb.2005.1673
[4] Schiffels, S., and Durbin, R. (2014). Inferring human population size and separation history from multiple genome sequences. Nature genetics, 46(8), 919-925. doi: https://doi.org/10.1038/ng.3015
[5] Sellinger, T. P. P., Awad, D. A., Moest, M., and Tellier, A. (2020). Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data. PLoS Genetics, 16(4), e1008698. doi: https://doi.org/10.1371/journal.pgen.1008698
[6] Sellinger, T. P. P., Awad, D. A. and Tellier, A. (2020) Limits and Convergence properties of the Sequentially Markovian Coalescent. bioRxiv, 2020.07.23.217091, ver. 3 peer-reviewed and recommended by PCI Evolutionary Biology. doi: https://doi.org/10.1101/2020.07.23.217091
[7] Sheehan, S., Harris, K., and Song, Y. S. (2013). Estimating variable effective population sizes from multiple genomes: a sequentially Markov conditional sampling distribution approach. Genetics, 194(3), 647-662. doi: https://doi.org/10.1534/genetics.112.149096
[8] Terhorst, J., Kamm, J. A., and Song, Y. S. (2017). Robust and scalable inference of population history from hundreds of unphased whole genomes. Nature genetics, 49(2), 303-309. doi: https://doi.org/10.1038/ng.3748

Plants display an amazing diversity of reproductive strategies with and without sex. This diversity is particularly remarkable in flowering plants, as highlighted by Charles Darwin, who wrote several botanical books scrutinizing plant reproduction. One particularly influential work concerned floral variation [1]. Darwin recognized that flowers may present different forms within a single population, with or without sex specialization. The number of species concerned is small, but they display recurrent patterns, which made it possible for Darwin to invoke natural and sexual selection to explain them. Most of early evolutionary theory on the evolution of reproductive strategies was developed in the first half of the 20th century and was based on animals. However, the pioneering work by David Lloyd from the 1970s onwards excited interest in the diversity of plant sexual strategies as models for testing adaptive hypotheses and predicting reproductive outcomes [2]. The sex specialization of individual flowers and plants has since become one of the favorite topics of evolutionary biologists. However, attention has focused mostly on cases related to sex differentiation (dioecy and associated conditions [3]). Separate unisexual flower types on the same plant (monoecy and related cases, rendering the plant functionally hermaphroditic) have been much less studied, apart from their possible role in the evolution of dioecy [4] or their association with particular modes of pollination [5].
Two specific non-mutually exclusive hypotheses on the evolution of separate sexes in flowers (dicliny) have been proposed, both anchored in Lloyd’s views and Darwin’s legacy, with selfing avoidance and optimal limited resource allocation. Intermediate sex separation, in which sex morphs have different combinations of unisexual and hermaphrodite flowers, has been crucial for testing these hypotheses through comparative analyses of optimal conditions in suggested transitions. Again, cases in which floral unisexuality does not lead to sex separation have been studied much less than dioecious plants, at both the microevolutionary and macroevolutionary levels. It is surprising that the increasing availability of plant phylogenies and powerful methods for testing evolutionary transitions and correlations have not led to more studies, even though the frequency of monoecy is probably highest among diclinous species (those with unisexual flowers in any distribution among plants within a population [6]).
The study by Torices et al. [7] aims to fill this gap, offering a different perspective to that provided by Diggle & Miller [8] on the evolution of monoecious conditions. The authors use heads of a number of species of the sunflower family (Asteraceae) to test specifically the effect of resource limitation on the expression of sexual morphs within the head. They make use of the very particular and constant architecture of inflorescences in these species (the flower head or “capitulum”) and the diversity of sexual conditions (hermaphrodite, gynomonoecious, monoecious) and their spatial pattern within the flower head in this plant family to develop an elegant means of testing this hypothesis. Their results are consistent with their expectations on the effect of resource limitation on the head, as determined by patterns of fruit size within the head, assuming that female fecundity is more strongly limited by resource availability than male function.
The authors took on a huge challenge in choosing to study the largest plant family (about 25 thousand species). Their sample was limited to only about a hundred species, but species selection was very careful, to ensure that the range of sex conditions and the available phylogenetic information were adequately represented. The analytical methods are robust and cast no doubt on the reported results. However, I can’t help but wonder what would happen if the antiselfing hypothesis was tested simultaneously. This would require self-incompatibility (SI) data for the species sample, as the presence of SI is usually invoked as a powerful antiselfing mechanism, rendering the unisexuality of flowers unnecessary. However, SI is variable and frequently lost in the sunflower family [9]. I also wonder to what extent the very specific architecture of flower heads imposes an idiosyncratic resource distribution that may have fixed these sexual systems in species and lineages of the family. Although not approached in this study, intraspecific variation seems to be low. It would be very interesting to use similar approaches in other plant groups in which inflorescence architecture is lax and resource distribution may differ. A whole-plant approach might be required, rather than investigations of single inflorescences as in this study. This study has no flaws, but instead paves the way for further testing of a long-standing dual hypothesis, probably with different outcomes in different ecological and evolutionary settings. In the end, sex is not only in the head.

References

[1] Darwin, C. (1877). The different forms of flowers on plants of the same species. John Murray.
[2] Barrett, S. C. H., and Harder, L. D. (2006). David G. Lloyd and the evolution of floral biology: from natural history to strategic analysis. In L.D. Harder, L. D., and Barrett, S. C. H. (eds) Ecology and Evolution of Flowers. OUP, Oxford. Pp 1-21.
[3] Geber, M. A., Dawson, T. E., and Delph, L. F. (eds) (1999). Gender and sexual dimorphism in flowering plants. Springer, Berlin.
[4] Charlesworth, D. (1999). Theories of the evolution of dioecy. In Geber, M. A., Dawson T. E. and Delph L. F. (eds) (1999). Gender and sexual dimorphism in flowering plants. Springer, Berlin. Pp. 33-60.
[5] Friedman, J., and Barrett, S. C. (2008). A phylogenetic analysis of the evolution of wind pollination in the angiosperms. International Journal of Plant Sciences, 169(1), 49-58. doi: 10.1086/523365
[6] Renner, S. S. (2014). The relative and absolute frequencies of angiosperm sexual systems: dioecy, monoecy, gynodioecy, and an updated online database. American Journal of botany, 101(10), 1588-1596. doi: 10.3732/ajb.1400196
[7] Torices, R., Afonso, A., Anderberg, A. A., Gómez, J. M., and Méndez, M. (2019). Architectural traits constrain the evolution of unisexual flowers and sexual segregation within inflorescences: an interspecific approach. bioRxiv, 356147, ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/356147
[8] Diggle, P. K., and Miller, J. S. (2013). Developmental plasticity, genetic assimilation, and the evolutionary diversification of sexual expression in Solanum. American journal of botany, 100(6), 1050-1060. doi: 10.3732/ajb.1200647
[9] Ferrer, M. M., and Good‐Avila, S. V. (2007). Macrophylogenetic analyses of the gain and loss of self‐incompatibility in the Asteraceae. New Phytologist, 173(2), 401-414. doi: 10.1111/j.1469-8137.2006.01905.x

Estimating the genetic and environmental components of variation in reproductive success is crucial to understanding the adaptive potential of populations to environmental change. To date, the heritability of lifetime reproductive success (fitness) has been estimated in a handful of wild animal population, mostly in mammals and birds, but has never been estimated for a marine species. The primary reason that such estimates are lacking in marine species is that most marine organisms have a dispersive larval phase, making it extraordinarily difficult to track the fate of offspring from one generation to the next.
In this study, Salles et al. [1] use an unprecedented 10 year data set for a wild population of orange clownfish (Amphiprion percula) to estimate the environmental, maternal and additive genetic components of life time reproductive success for the self-recruiting portion of the local population. Previous studies show that over 50% of juvenile clownfish recruiting to the population of clownfish at Kimbe Island (Kimbe Bay, PNG) are natal to the population. In other words, >50% of the juveniles recruiting to the population at Kimbe Island are offspring of parents from Kimbe Island. The identity and location of every adult clownfish in the Kimbe Island population was tracked over 10 years. At the same time newly recruiting juveniles were collected at regular intervals (biennially) and their parentage assigned with high confidence by 22 polymorphic microsatellite loci. Salles et al. then used a pedigree comprising 1735 individuals from up to 5 generations of clownfish at Kimbe Island to assess the contribution of every breeding pair of clownfish to self-recruitment within the local population. Because clownfish are site attached and live in close association with a host sea anemone, it was also possible to examine the contribution of reef location and host anemones species (either Heteractis magnifica or Stichodactyla gigantea) to reproductive success within the local population.
The study found that breeders from the eastern side of Kimbe Island, and mostly inhabiting S. gigantea sea anemones, produced more juveniles that recruited to the local population than breeders from other location around the island, or inhabiting H. magnifica. In fact, host anemone species and geographic location explained about 97% of the variance in reproductive success within the local population (i.e. excluding successful recruitment to other populations). By contrast, maternal and additive genetic effects explained only 1.9% and 1.3% of the variance, respectively. In other words, reef location and the species of host anemone inhabited had an overwhelming influence on the long-term contribution of breeding pairs of clownfish to replenishment of the local population. This overwhelming effect of the local habitat on reproductive success means that the population is potentially susceptible to rapid environmental changes - for example if S. giganta sea anemones are disproportionately susceptible to global warming, or reef habitats on the eastern side of the island are more susceptible to disturbance. By contrast, the small component of additive genetic variance in local reproductive success translated into low heritability and evolvability of lifetime reproductive success within the local population, as predicted by theory [2] and observed in some terrestrial species. Consequently, fitness would evolve slowly to environmental change.
Establishing the components of variation in fitness in a wild population of marine fishes is an astonishing achievement, made possible by the unprecedented long-term individual-level monitoring of the entire population of clownfish at Kimbe Island. A next step in this research would be to include other clownfish populations that are demographically and genetically connected to the Kimbe Island population through larval dispersal. It would be intriguing to establish the environmental, maternal and additive genetic components of reproductive success in the dispersing part of the Kimbe Island population, to see if this potentially differs among breeders who contribute more or less to replenishment within the local population.

References

[1] Salles, O. C., Almany, G. R., Berumen, M.L., Jones, G. P., Saenz-Agudelo, P., Srinivasan, M., Thorrold, S. R., Pujol, B., Planes, S. (2019). Strong habitat and weak genetic effects shape the lifetime reproductive success in a wild clownfish population. Zenodo, 3476529, ver. 3 peer-reviewed and recommended by Peer Community In Evolutionary Biology. doi: 10.5281/zenodo.3476529
[2] Fisher, R.A. (1930). The genetical theory of natural selection. Clarendon Press, Oxford, U.K.

Species everywhere are facing rapid climatic change, and we are increasingly asking whether populations will adapt, shift, or perish [1]. There is a growing realisation that, despite limited within-population genetic variation, many species exhibit substantial geographic variation in climate-relevant traits. This geographic variation might play an important role in facilitating adaptation to climate change [2,3].
Much of our understanding of geographic variation in climate-relevant traits comes from model organisms [e.g. 4]. But as our concern grows, we make larger efforts to understand geographic variation in non-model organisms also. If we understand what adaptive geographic variation exists within a species, we can make management decisions around targeted gene flow [5]. And as empirical examples accumulate, we can look for generalities that can inform management of unstudied species [e.g. 6,7]. Rudin-Bitterli’s paper [8] is an excellent contribution in this direction.
Rudin-Bitterli and her co-authors [8] sampled six frog populations distributed across a strong rainfall gradient. They then assayed these frogs and their offspring for a battery of fitness-relevant traits. The results clearly show patterns consistent with local adaptation to water availability, but they also reveal trade-offs. In their study, frogs from the driest source populations were resilient to the hydric environment: it didn’t really affect them very much whether they were raised in wet or dry environments. By contrast, frogs from wet source areas did better in wet environments, and they tended to do better in these wet environments than did animals from the dry-adapted populations. Thus, it appears that the resilience of the dry-adapted populations comes at a cost: frogs from these populations cannot ramp up performance in response to ideal (wet) conditions.
These data have been carefully and painstakingly collected, and they are important. They reveal not only important geographic variation in response to hydric stress (in a vertebrate), but they also adumbrate a more general trade-off: that the jack of all trades might be master of none. Specialist-generalist trade-offs are often argued (and regularly observed) to exist [e.g. 9,10], and here we see them arise in climate-relevant traits also. Thus, Rudin-Bitterli’s paper is an important piece of the empirical puzzle, and one that points to generalities important for both theory and management.

References

[1] Hoffmann, A. A., and Sgrò, C. M. (2011). Climate change and evolutionary adaptation. Nature, 470(7335), 479–485. doi: 10.1038/nature09670
[2] Aitken, S. N., and Whitlock, M. C. (2013). Assisted Gene Flow to Facilitate Local Adaptation to Climate Change. Annual Review of Ecology, Evolution, and Systematics, 44(1), 367–388. doi: 10.1146/annurev-ecolsys-110512-135747
[3] Kelly, E., and Phillips, B. L. (2016). Targeted gene flow for conservation. Conservation Biology, 30(2), 259–267. doi: 10.1111/cobi.12623
[4] Sgrò, C. M., Overgaard, J., Kristensen, T. N., Mitchell, K. A., Cockerell, F. E., and Hoffmann, A. A. (2010). A comprehensive assessment of geographic variation in heat tolerance and hardening capacity in populations of Drosophila melanogaster from eastern Australia. Journal of Evolutionary Biology, 23(11), 2484–2493. doi: 10.1111/j.1420-9101.2010.02110.x
[5] Macdonald, S. L., Llewelyn, J., and Phillips, B. L. (2018). Using connectivity to identify climatic drivers of local adaptation. Ecology Letters, 21(2), 207–216. doi: 10.1111/ele.12883
[6] Hoffmann, A. A., Chown, S. L., and Clusella‐Trullas, S. (2012). Upper thermal limits in terrestrial ectotherms: how constrained are they? Functional Ecology, 27(4), 934–949. doi: 10.1111/j.1365-2435.2012.02036.x
[7] Araújo, M. B., Ferri‐Yáñez, F., Bozinovic, F., Marquet, P. A., Valladares, F., and Chown, S. L. (2013). Heat freezes niche evolution. Ecology Letters, 16(9), 1206–1219. doi: 10.1111/ele.12155
[8] Rudin-Bitterli, T. S., Evans, J. P., and Mitchell, N. J. (2019). Geographic variation in adult and embryonic desiccation tolerance in a terrestrial-breeding frog. BioRxiv, 314351, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. doi: 10.1101/314351
[9] Kassen, R. (2002). The experimental evolution of specialists, generalists, and the maintenance of diversity. Journal of Evolutionary Biology, 15(2), 173–190. doi: 10.1046/j.1420-9101.2002.00377.x
[10] Angilletta, M. J. J. (2009). Thermal Adaptation: A theoretical and empirical synthesis. Oxford University Press, Oxford.

Flowering plants display a staggering diversity of both mating systems and life histories, ranging from almost exclusively selfers to obligate outcrossers, very short-lived annual herbs to super long lived trees. One pervasive pattern that has attracted considerable attention is the tight correlation that is found between mating systems and lifespan [1]. Until recently, theoretical explanations for these patterns have relied on static models exploring the consequences of several non-mutually exclusive important process: levels of inbreeding depression and ability to successfully were center stage. This make sense: successful colonization after long‐distance dispersal is far more likely to happen for self‐compatible than for self‐incompatible individuals in a sexually reproducing species. Furthermore, inbreeding depression (essentially a genetically driven phenomenon) and reproductive insurance are expected to shape the evolution of both mating system and lifespan.
But modelling jointly several processes and how their interplay to shape the evolution of a trait is challenging enough so models for the evolution of mating system tend invariably – for mathematical convenience and tractability – to fix lifespan [2].
However, comparative analysis of between species variations that map traits transitions among sister species in phylogenetic trees reveals a pervasive pattern: frequent transitions from a state outcrossing perennial to selfing annuals. This beg the question: is one transition triggering the other and if so, what comes first or are these transitions happening together? In this work, Lesaffre and Billiard use a very sophisticated machinery developed by Kirkpatrick et al. [3] and consider a general class of so-called modifiers models [4]. They study jointly the evolution of life span and mating system. They do so by using models where different life stages are tracked with life stage having some (fixed for once) amount of inbreeding depression. Their paper is technically demanding, mixing analytics and computer simulations, and along the way generates several important findings that are expected to stimulate further empirical and theoretical studies: (1) pure selfing versus pure outcrossing is the expected stable evolutionary outcomes (despite observation that mixed mating systems can be regularly met in nature), (2) increasing life-span drastically reduces the scope for the evolution of selfing, conversely (3) transition to selfing will also select for shorter life span as a way to mitigate the cumulative effects of inbreeding depression on adult life stages.
As usual there is room for future work, in particular the authors’ model assumes fixed inbreeding depression in the different life stages and this highlights the need for models that explore how inbreeding depression, a pivotal quantity in these models, can itself be molded by both mating system and lifespan. A third-generation of models should be “soon” on the way!

References
[1] Grossenbacher D, Briscoe Runquist R, Goldberg EE, and Brandvain Y. (2015) Geographic range size is predicted by plant mating system. Ecology Letters 18, 706–713. doi: 10.1111/ele.12449
[2] Morgan MT, Schoen DJ, and Bataillon T. (1997) The evolution of self-fertilization in perennials. The American Naturalist 150, 618–638. doi: 10.1086/286085
[3] Kirkpatrick M, Johnson T, and Barton N. (2002) General models of multilocus evolution. Genetics 161, 1727–1750.
[4] Lesaffre, T, and Billiard S. (2019) The joint evolution of lifespan and self-fertilisation. bioRxiv, 420877, ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/420877