Genome-wide data obtained from even a small number of individuals can provide unprecedented levels of detail about the evolutionary history of populations and species [1], determinants of genetic diversity [2], species boundaries and the process of speciation itself [3]. Loire and Galtier [4] present a clear example, using the emblematic Galápagos giant tortoise (Chelonoidis nigra), of how multi-species comparative population genomic approaches can provide valuable insights about population structure and species delimitation even when sample sizes are limited but the number of loci is large and distributed across the genome.

Galápagos giant tortoises are endemic to the Galápagos Islands and are currently recognized as an endangered, multi-species complex including both extant and extinct taxa. Taxonomic definitions are based on morphology, geographic isolation and population genetic evidence based on short DNA sequences of the mitochondrial genome (mtDNA) and/or a dozen or so nuclear microsatellite loci [5-8]. The species complex enjoys maximal protection. Population recoveries have been quite successful and spectacular conservation programs based on mitochondrial genes and microsatellites are ongoing. This includes for example individual translocations, breeding program, “hybrid” sterilization or removal, and resurrection of extinct lineages).

In 2013, Loire et al. [9] provided the first population genomic analyses based on genome scale data (~1000 coding loci derived from blood-transcriptomes) from five individuals, encompassing three putative “species”: Chelonnoidis becki, C. porteri and C. vandenburghi. Their results raised doubts about the validity/accuracy of the currently accepted designations of “genetic distinctiveness”. However, the implications for conservation and management have remained unnoticed.

In 2017, Loire and Galtier [4] have re-appraised this issue using an original multi-species comparative population genomic analysis of their previous data set [9]. Based on a comparison of 53 animal species, they show that both the level of genome-wide neutral diversity (πS) and level of population structure estimated using the inbreeding coefficient (F) are much lower than would be expected from a sample covering multiple species. The observed values are more comparable to those typically reported at the “among population” level within a single species such as human (Homo sapiens). The authors go to great length to assess the sensitivity of their method to detect population structure (or lack thereof) and show that their results are robust to potential issues, such as contamination and sequencing errors that can occur with Next Generation Sequencing techniques; and biases related to the small sample size and sub-sampling of individuals. They conclude that published mtDNA and microsatellite-based assessment of population structure and species designations may be biased towards over-splitting.

This manuscript is a very good read as it shows the potential of the now relatively affordable genome-wide data for helping to both resolve and clarify population and species boundaries, illuminate demographic trends, evolutionary trajectories of isolated groups, patterns of connectivity among them, and test for evidence of local adaptation and even reproductive isolation. The comprehensive information provided by genome-wide data can critically inform and assist the development of the best strategies to preserve endangered populations and species. Loire and Galtier [4] make a strong case for applying genomic data to the Galápagos giant tortoises, which is likely to redirect conservation efforts more effectively and at lower cost. The case of the Galápagos giant tortoises is certainly a very emblematic example, which will find an echo in many other endangered species conservation programs.

References

[1] Li H and Durbin R. 2011. Inference of human population history from individual whole-genome sequences. Nature, 475: 493–496. doi: 10.1038/nature10231

[2] Romiguier J, Gayral P, Ballenghien M, Bernard A, Cahais V, Chenuil A, Chiari Y, Dernat R, Duret L, Faivre N, Loire E, Lourenco JM, Nabholz B, Roux C, Tsagkogeorga G, Weber AA-T, Weinert LA, Belkhir K, Bierne N, Glémin S and Galtier N. 2014. Comparative population genomics in animals uncovers the determinants of genetic diversity. Nature, 515: 261–263. doi: 10.1038/nature13685

[3] Roux C, Fraïsse C, Romiguier J, Anciaux Y, Galtier N and Bierne N. 2016. Shedding light on the grey zone of speciation along a continuum of genomic divergence. PLoS Biology, 14: e2000234. doi: 10.1371/journal.pbio.2000234

[4] Loire E and Galtier N. 2017. Lacking conservation genomics in the giant Galápagos tortoise. bioRxiv 101980, ver. 4 of September 26, 2017. doi: 10.1101/101980

[5] Beheregaray LB, Ciofi C, Caccone A, Gibbs JP and Powell JR. 2003. Genetic divergence, phylogeography and conservation units of giant tortoises from Santa Cruz and Pinzón, Galápagos Islands. Conservation Genetics, 4: 31–46. doi: 10.1023/A:1021864214375

[6] Ciofi C, Milinkovitch MC, Gibbs JP, Caccone A and Powell JR. 2002. Microsatellite analysis of genetic divergence among populations of giant Galápagos tortoises. Molecular Ecology, 11: 2265–2283. doi: 10.1046/j.1365-294X.2002.01617.x

[7] Garrick RC, Kajdacsi B, Russello MA, Benavides E, Hyseni C, Gibbs JP, Tapia W and Caccone A. 2015. Naturally rare versus newly rare: demographic inferences on two timescales inform conservation of Galápagos giant tortoises. Ecology and Evolution, 5: 676–694. doi: 10.1002/ece3.1388

[8] Poulakakis N, Edwards DL, Chiari Y, Garrick RC, Russello MA, Benavides E, Watkins-Colwell GJ, Glaberman S, Tapia W, Gibbs JP, Cayot LJ and Caccone A. 2015. Description of a new Galápagos giant tortoise species (Chelonoidis; Testudines: Testudinidae) from Cerro Fatal on Santa Cruz island. PLoS ONE, 10: e0138779. doi: 10.1371/journal.pone.0138779

[9] Loire E, Chiari Y, Bernard A, Cahais V, Romiguier J, Nabholz B, Lourenço JM and Galtier N. 2013. Population genomics of the endangered giant Galápagos tortoise. Genome Biology, 14: R136. doi: 10.1186/gb-2013-14-12-r136

Genetic diversity in temperate and boreal forests tree species has been strongly affected by late Pleistocene climate oscillations [2,3,5], but also by anthropogenic forces. Particularly in Europe, where a long history of human intervention has re-distributed species and populations, it can be difficult to know if a given forest arose through natural regeneration and gene flow or through some combination of natural and human-mediated processes. This uncertainty can confound inferences of the causes and consequences of standing genetic variation, which may impact our interpretation of demographic events that shaped species before humans became dominant on the landscape. In their paper entitled "Genomic data provides new insights on the demographic history and the extent of recent material transfers in Norway spruce", Chen et al. [1] used a genome-wide dataset of 400k SNPs to infer the demographic history of Picea abies (Norway spruce), the most widespread and abundant spruce species in Europe, and to understand its evolutionary relationship with two other spruces (Picea obovata [Siberian spruce] and P. omorika [Serbian spruce]). Three major Norway spruce clusters were identified, corresponding to central Europe, Russia and the Baltics, and Scandinavia, which agrees with previous studies. The density of the SNP data in the present paper enabled inference of previously uncharacterized admixture between these groups, which corresponds to the timing of postglacial recolonization following the last glacial maximum (LGM). This suggests that multiple migration routes gave rise to the extant distribution of the species, and may explain why Chen et al.'s estimates of divergence times among these major Norway spruce groups were older (15mya) than those of previous studies (5-6mya) – those previous studies may have unknowingly included admixed material [4]. Treemix analysis also revealed extensive admixture between Norway and Siberian spruce over the last ~100k years, while the geographically-restricted Serbian spruce was both isolated from introgression and had a dramatically smaller effective population size (Ne) than either of the other two species. This small Ne resulted from a bottleneck associated with the onset of the iron age ~3000 years ago, which suggests that anthropogenic depletion of forest resources has severely impacted this species. Finally, ancestry of Norway spruce samples collected in Sweden and Denmark suggest their recent transfer from more southern areas of the species range. This northward movement of genotypes likely occurred because the trees performed well relative to local provenances, which is a common observation when trees from the south are planted in more northern locations (although at the potential cost of frost damage due to inappropriate phenology). While not the reason for the transfer, the incorporation of southern seed sources into the Swedish breeding and reforestation program may lead to more resilient forests under climate change. Taken together, the data and analysis presented in this paper allowed inference of the intra- and interspecific demographic histories of a tree species group at a very high resolution, and suggest caveats regarding sampling and interpretation of data from areas with a long history of occupancy by humans.

References

[1] Chen, J., Milesi, P., Jansson, G., Berlin, M., Karlsson, B., Aleksić, J. M., Vendramin, G. G., Lascoux, M. (2018). Genomic data provides new insights on the demographic history and the extent of recent material transfers in Norway spruce. BioRxiv, 402016. ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/402016
[2] Holliday, J. A., Yuen, M., Ritland, K., & Aitken, S. N. (2010). Postglacial history of a widespread conifer produces inverse clines in selective neutrality tests. Molecular Ecology, 19(18), 3857–3864. doi: 10.1111/j.1365-294X.2010.04767.x
[3] Ingvarsson, P. K. (2008). Multilocus patterns of nucleotide polymorphism and the demographic history of Populus tremula. Genetics, 180, 329-340. doi: 10.1534/genetics.108.090431
[4] Lockwood, J. D., Aleksić, J. M., Zou, J., Wang, J., Liu, J., & Renner, S. S. (2013). A new phylogeny for the genus Picea from plastid, mitochondrial, and nuclear sequences. Molecular Phylogenetics and Evolution, 69(3), 717–727. doi: 10.1016/j.ympev.2013.07.004
[5] Pyhäjärvi, T., Garcia-Gil, M. R., Knürr, T., Mikkonen, M., Wachowiak, W., & Savolainen, O. (2007). Demographic history has influenced nucleotide diversity in European Pinus sylvestris populations. Genetics, 177(3), 1713–1724. doi: 10.1534/genetics.107.077099 "

​​Durability of plant resistance to diploid pathogen Hirohisa Kishino Based on the population genetic and epidemiologic model, Saubin et al. (2021) report that the resistant hosts generated by the breeding based on the gene-for-gene interaction is durable much longer against diploid pathogens than haploid pathogens. The avr allele of pathogen that confers the resistance is genetically recessive. The heterozygotes are not recognized by the resistant hosts and only the avr/avr homozygote is adaptive. As a result, the trajectory of avr allele frequency becomes more stochastic due to genetic drift. Although the paper focuses on the evolution of standing polymorphism, it seems obvious that the adaptive mutations in pathogen have much larger probability of being deleted from the population because the individuals own the avr allele mostly in the form of heterozygote at the initial phase after the mutation. Since only few among many models of plant resistance deployment study the case of diploid pathogen and the contribution of the pathogen life cycle, this work will add an important intellect to the literature (Rimbaud et al. 2021).

From the study of host-parasite interaction in flax rust Melampsora lini, Flor (1942, 1955) showed that the host resistance is formed by the interaction of a host resistance gene and a corresponding pathogen gene. This gene-for-gene hypothesis has been supported by experimental evidence and has served as a basis of the methods of molecular breeding targeting the dominant R genes. However, modern agriculture provides the pathogen populations with the homogeneous environments and laid strong selection pressure on them. As a result, the newly developed resistant plants face the risk of immediate resistance breakdown (Möller and Stukenbrock 2017).

Currently, quantitative resistance is getting attention as characters as a potential target for long-life (mild) resistant breeds (Lannou, 2012). They are polygenic and controlled partly by the same genes that mediate qualitative resistance but mostly by the genes that encode defense-related outputs such as strengthening of the cell wall or defense compound biosynthesis (Corwin and Kliebenstein, 2017). Progress of molecular genetics may overcome the technical difficulty (Bakkeren and Szabo, 2020). Saubin et al. (2021) notes that the pattern of genetic inheritance of the pathogen counterparts that respond to the host traits is crucial regarding with the durability of the resistant hosts. The resistance traits for which avr alleles are predicted to be recessive may be the targets of breeding.

References

Bakkeren, G., and Szabo, L. J. (2020) Progress on molecular genetics and manipulation of rust fungi. Phytopathology, 110, 532-543. https://doi.org/10.1094/PHYTO-07-19-0228-IA

Corwin, J. A., and Kliebenstein, D. J. (2017) Quantitative resistance: more than just perception of a pathogen. The Plant Cell, 29, 655-665. https://doi.org/10.1105/tpc.16.00915

Flor, H. H. (1942) Inheritance of pathogenicity in a cross between physiological races 22 and 24 of Melampsova lini. Phytopathology, 35. Abstract.

Flor, H. H. (1955) Host-parasite interactions in flax rust-its genetics and other implications. Phytopathology, 45, 680-685.

Lannou, C. (2012) Variation and selection of quantitative traits in plant pathogens. Annual review of phytopathology, 50, 319-338. https://doi.org/10.1146/annurev-phyto-081211-173031

Möller, M. and Stukenbrock, E. H. (2017) Evolution and genome architecture in fungal plant pathogens. Nature Reviews Microbiology. 15, 756–771. https://doi.org/10.1038/nrmicro.2017.76

Rimbaud, L., Fabre, F., Papaïx, J., Moury, B., Lannou, C., Barrett, L. G., and Thrall, P. H. (2021) Models of Plant Resistance Deployment. Annual Review of Phytopathology, 59. https://doi.org/10.1146/annurev-phyto-020620-122134

Saubin, M., De Mita, S., Zhu, X., Sudret, B. and Halkett, F. (2021) Impact of ploidy and pathogen life cycle on resistance durability. bioRxiv, 2021.05.28.446112, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.05.28.446112

Exciting times are afoot for those of us interested in the ecology and evolution of invasive populations. Recent years have seen evolutionary process woven firmly into our understanding of invasions (Miller et al. 2020). This integration has inspired a welter of empirical and theoretical work. We have moved from field observations and verbal models to replicate experiments and sophisticated mathematical models. Progress has been rapid, and we have seen science at its best; an intimate discussion between theory and data.
An area currently under very active development is our understanding of pushed invasions. Here a population spreads through space driven, not by dispersal and growth originating at the leading tip of the invasion, but by dispersal and growth originating deeper in the bulk of the population. These pushed invasions may be quite common – they result when per capita growth and dispersal rates are higher in the bulk of the wave than at the leading tip. They result from a range of well-known phenomena, including Allee effects and density-dependent dispersal (Gandhi et al. 2016; Bîrzu et al. 2019). Pushed invasions travel faster than we would expect given growth and dispersal rates on the leading tip, and they lose genetic diversity more slowly than classical pulled invasions (Roques et al. 2012; Haond et al. 2018; Bîrzu et al. 2019).
Well… in theory, anyway. The theory on pushed waves has momentarily streaked ahead of the empirical work, because empirical systems for studying pushed invasions are rare (though see Gandhi et al. 2016; Gandhi, Korolev, and Gore 2019). In this paper, Dahirel and colleagues (2020) make the argument that we may be able to generate pushed invasions in laboratory systems simply by reducing the connectedness of our experimental landscapes. If true, we might have a simple tool for turning many of our established experimental systems into systems for studying pushed dynamics.
It’s a nice idea, and the paper goes to careful lengths to explore the possibility in their lab system (a parasitoid wasp, Trichogramma). They run experiments on replicate wasp populations comparing strongly- v poorly-connected arrays, and estimate the resulting invasion speeds and rate of diversity loss. They also build a simulation model of the system, allowing them to explore in-silico a range of possible processes underlying their results.
As well as developing these parallel systems, Dahirel and colleagues (2020) go to careful lengths to develop statistical analyses that allow inference on key parameters, and they apply these analyses to both the experimental and simulation data. They have been motivated to apply methods that might be used in both laboratory and field settings to help classify invasions.
Ultimately, they found reasonable evidence that their poorly-connected habitat did induce a pushed dynamic. Their poorly connected invasions travelled faster than they should have if they were pulled, they lost diversity more slowly than the highly connected habitat, and replicates with a higher carrying capacity tended to have higher invasion speeds. All in line with expectations of a pushed dynamic. Interestingly, however, their simulation results suggest that they probably got this perfect result for unexpected reasons. The strong hint is that their poorly-connected habitat induced density dependent dispersal in the wasps. Without this effect, their simulations suggest they should have seen diversity decreasing much more rapidly than it did.
There is a nuanced, thoughtful, and carefully argued discussion about all this in the paper, and it is worth reading. There is much of value in this paper. Theirs is not a perfect empirical system in which all the model assumptions are met and in which huge population sizes make stochastic effects negligible. Here is a system one step closer to the messy reality of biology. The struggle to align this system with new theory has been worth the effort. Not only does it give us hope that we might usefully be able to discriminate between classes of invasions using real-world data, but it hints at a rule that Tolstoy might have expressed this way: all pulled invasions are alike, each pushed invasion is pushed in its own way.

References

Bîrzu, G., Matin, S., Hallatschek, O., and Korolev, K. S. (2019). Genetic drift in range expansions is very sensitive to density dependence in dispersal and growth. Ecology Letters, 22(11), 1817-1827. doi: https://doi.org/10.1111/ele.13364
Dahirel, M., Bertin, A., Haond, M., Blin, A., Lombaert, E., Calcagno, V., Fellous, S., Mailleret, L., Malausa, T., and Vercken, E. (2020). Shifts from pulled to pushed range expansions caused by reduction of landscape connectivity. bioRxiv, 2020.05.13.092775, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. https://doi.org/10.1101/2020.05.13.092775
Gandhi, S. R., Korolev, K. S., and Gore, J. (2019). Cooperation mitigates diversity loss in a spatially expanding microbial population. Proceedings of the National Academy of Sciences, 116(47), 23582-23587. doi: https://doi.org/10.1073/pnas.1910075116
Gandhi, S. R., Yurtsev, E. A., Korolev, K. S., and Gore, J. (2016). Range expansions transition from pulled to pushed waves as growth becomes more cooperative in an experimental microbial population. Proceedings of the National Academy of Sciences, 113(25), 6922-6927. doi: https://doi.org/10.1073/pnas.1521056113
Haond, M., Morel-Journel, T., Lombaert, E., Vercken, E., Mailleret, L. and Roques, L. (2018). When higher carrying capacities lead to faster propagation (2018), bioRxiv, 307322, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/307322
Miller et al. (2020). Eco‐evolutionary dynamics of range expansion. Ecology, 101(10), e03139. doi: https://doi.org/10.1002/ecy.3139
Roques, L., Garnier, J., Hamel, F., and Klein, E. K. (2012). Allee effect promotes diversity in traveling waves of colonization. Proceedings of the National Academy of Sciences, 109(23), 8828-8833. doi: https://doi.org/10.1073/pnas.1201695109

An individual’s sexual phenotype is determined during development. Understanding which pathways are activated or repressed during the developmental stages leading to a sexually mature individual, for example by studying gene expression and how its level is biased between sexes, allows us to understand the functional aspects of dimorphic phenotypes between the sexes.

Several studies have quantified the differences in transcription between the sexes in mature individuals, showing the extent of this sex-bias and which functions are affected. There is, however, less data available on what occurs during the different phases of development leading to this phenotype, especially in species with specific developmental strategies, such as hemimetabolous insects. While many well-studied insects such as the honey bee, drosophila, and butterflies, exhibit an holometabolous development ("holo" meaning "complete" in reference to their drastic metamorphosis from the juvenile to the adult stage), hemimetabolous insects have juvenile stages that look similar to the adult stage (the hemi prefix meaning "half", referring to the more tissue-specific changes during development), as seen in crickets, cockroaches, and stick insects. Learning more about what happens during development in terms of the identity of genes that are sex-biased (are they the same genes at different developmental stages? What are their function? Do they exhibit specific sequence evolution rates? Is one sex over-represented in the sex-biased genes?) and their quantity over developmental time (gradual or abrupt increase in number, if any?) would allow us to better understand the evolution of sexual dimorphism at the gene expression level and how it relates to dimorphism at the organismic level.

Djordjevic et al (2021) studied the transcriptome during development in an hemimetabolous stick insect, to improve our knowledge of this type of development, where the organismic phenotype is already mostly present in the early life stages. To do this, they quantified whole-genome gene expression levels in whole insects, using RNA-seq at three different developmental stages. One of the interesting results presented by Djordjevic and colleagues is that the increase in the number of genes that were sex-biased in expression is gradual over the three stages of development studied and it is mostly the same genes that stay sex-biased over time, reflecting the gradual change in phenotypes between hatchlings, juveniles and adults. Furthermore, male-biased genes had faster sequence divergence rates than unbiased genes and that female-biased genes.

This new information of sex-bias in gene expression in an hemimetabolous insect allowed the authors to do a comparison of sex-biased genes with what has been found in a well-studied holometabolous insect, Drosophila. The gene expression patterns showed that four times more genes were sex-biased in expression in that species than in stick insects. Furthermore, the increase in the number of sex-biased genes during development was quite abrupt and clearly distinct in the adult stage, a pattern that was not seen in stick insects. As pointed out by the authors, this pattern of a "burst" of sex-biased genes at maturity is more common than the gradual increase seen in stick insects.

With this study, we now know more about the evolution of sex-biased gene expression in an hemimetabolous insect and how it relates to their phenotypic dimorphism. Clearly, the next step will be to sample more hemimetabolous species at different life stages, to see how this pattern is widespread or not in this mode of development in insects.

References

Djordjevic J, Dumas Z, Robinson-Rechavi M, Schwander T, Parker DJ (2021) Dynamics of sex-biased gene expression during development in the stick insect Timema californicum. bioRxiv, 2021.01.23.427895, ver. 6 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.01.23.427895