The genomic revolution has given us access to inexpensive genetic data for any species. Simultaneously we have lost the ability to easily identify chimerism in samples or some unusual deviations from standard Mendelian genetics. Methods have been developed to identify sex chromosomes, characterise the ploidy, or understand the exact form of parthenogenesis from genomic data. However, we rarely consider that the tissues we extract DNA from could be a mixture of cells with different genotypes or karyotypes. This can nonetheless happen for a variety of (fascinating) reasons such as somatic chromosome elimination, transmissible cancer, or parental genome elimination. Without a dedicated analysis, it is very easy to miss it.

In this preprint, Jaron et al. (2022) used an ingenious analysis of whole individual NGS data to test the hypothesis of paternal genome elimination in the globular springtail Allacma fusca. The authors suspected that a high fraction of the whole body of males is made of sperm in this species and if this species undergoes paternal genome elimination, we would expect that sperm would only contain maternally inherited chromosomes. Given the reference genome was highly fragmented, they developed a two-tissue model to analyse Kmer spectra and obtained confirmation that around one-third of the tissue was sperm in males. This allowed them to test whether coverage patterns were consistent with the species exhibiting paternal genome elimination. They combined their estimation of the fraction of haploid tissue with allele coverages in autosomes and the X chromosome to obtain support for a bias toward one parental allele, suggesting that all sperm carries the same parental haplotype. It could be the maternal or the paternal alleles, but paternal genome elimination is most compatible with the known biology of Arthropods. SNP calling was used to confirm conclusions based on the analysis of the raw pileups.

I found this study to be a good example of how a clever analysis of Kmer spectra and allele coverages can provide information about unusual modes of reproduction in a species, even though it does not have a well-assembled genome yet. As advocated by the authors, routine inspection of Kmer spectra and allelic read-count distributions should be included in the best practice of NGS data analysis. They provide the method to identify paternal genome elimination but also the way to develop similar methods to detect another kind of genetic chimerism in the avalanche of sequence data produced nowadays.

References

Jaron KS, Hodson CN, Ellers J, Baird SJ, Ross L (2022) Genomic evidence of paternal genome elimination in the globular springtail Allacma fusca. bioRxiv, 2021.11.12.468426, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.11.12.468426

Duplications, mutations and recombination may be considered the main sources of genomic variation and evolution. In addition, sexual recombination is essential in purging deleterious mutations and allowing advantageous allelic combinations to occur (Glémin et al. 2019). However, in parthenogenetic asexual organisms, variation cannot be explained by sexual recombination, and other mechanisms must account for it. Although it is known that transposable elements (TE) may influence on genome structure and gene expression patterns, their role as a primary source of genomic variation and rapid adaptability has received less attention. An important role of TE on adaptive genome evolution has been documented for fungal phytopathogens (Faino et al. 2016), suggesting that TE activity might explain the evolutionary dynamics of this type of organisms.
The phytopathogen nematode Meloidogyne incognita is one of the worst agricultural pests in warm climates (Savary et al. 2019). This species, as well as other root-knot nematodes (RKN), shows a wide geographical distribution range infecting diverse groups of plants. Although allopolyploidy may have played an important role on the wide adaptation of this phytopathogen, it may not explain by itself the rapid changes required to overcome plant resistance in a few generations. Paradoxically, M. incognita reproduces asexually via mitotic parthenogenesis (Trudgill and Blok 2001; Castagnone-Sereno and Danchin 2014) and only few single nucleotide variations were identified between different host races isolates (Koutsovoulos et al. 2020). Therefore, this is an interesting model to explore other sources of genomic variation such the TE activity and its role on the success and adaptability of this phytopathogen.
To address these questions, Kozlowski et al. (2020) estimated the TE mobility across 12 geographical isolates that presented phenotypic variations in Meloidogyne incognita, concluding that recent activity of TE in both genic and regulatory regions might have given rise to relevant functional differences between genomes. This was the first estimation of TE activity as a mechanism probably involved in genome plasticity of this root-knot nematode. This study also shed light on evolutionary mechanisms of asexual organisms with an allopolyploid origin. These authors re-annotated the 185 Mb triploid genome of M. incognita for TE content analysis using stringent filters (Kozlowski 2020a), and estimated activity by their distribution using a population genomics approach including isolates from different crops and locations. Canonical TE represented around 4.7% of the M. incognita genome of which mostly correspond to TIR (Terminal Inverted Repeats) and MITEs (Miniature Inverted repeat Transposable Elements) followed by Maverick DNA transposons and LTR (Long Terminal Repeats) retrotransposons. The result that most TE found were represented by DNA transposons is similar to the previous studies with the nematode species model Caenorhabditis elegans (Bessereau 2006; Kozlowski 2020b) and other nematodes as well. Canonical TE annotations were highly similar to their consensus sequences containing transposition machinery when TE are autonomous, whereas no genes involved in transposition were found in non-autonomous ones. These findings suggest recent activity of TE in the M. incognita genome. Other relevant result was the significant variation in TE presence frequencies found in more than 3,500 loci across isolates, following a bimodal distribution within isolates. However, variation in TE frequencies was low to moderate between isolates recapitulating the phylogenetic signal of isolates DNA sequences polymorphisms. A detailed analysis of TE frequencies across isolates allowed identifying polymorphic TE loci, some of which might be neo-insertions mostly of TIRs and MITEs (Kozlowski 2020c). Interestingly, the two thirds of the fixed neo-insertions were located in coding regions or in regulatory regions impacting expression of specific genes in M. incognita. Future research on proteomics is needed to evaluate the functional impact that these insertions have on adaptive evolution in M. incognita. In this line, this pioneer research of Kozlowski et al. (2020) is a first step that is also relevant to remark the role that allopolyploidy and reproduction have had on shaping nematode genomes.

References

[1] Bessereau J-L. 2006. Transposons in C. elegans. WormBook. 10.1895/wormbook.1.70.1
[2] Castagnone-Sereno P, Danchin EGJ. 2014. Parasitic success without sex - the nematode experience. J. Evol. Biol. 27:1323-1333. 10.1111/jeb.12337
[3] Faino L, Seidl MF, Shi-Kunne X, Pauper M, Berg GCM van den, Wittenberg AHJ, Thomma BPHJ. 2016. Transposons passively and actively contribute to evolution of the two-speed genome of a fungal pathogen. Genome Res. 26:1091-1100. 10.1101/gr.204974.116
[4] Glémin S, François CM, Galtier N. 2019. Genome Evolution in Outcrossing vs. Selfing vs. Asexual Species. In: Anisimova M, editor. Evolutionary Genomics: Statistical and Computational Methods. Methods in Molecular Biology. New York, NY: Springer. p. 331-369. 10.1007/978-1-4939-9074-0_11
[5] Koutsovoulos GD, Marques E, Arguel M-J, Duret L, Machado ACZ, Carneiro RMDG, Kozlowski DK, Bailly-Bechet M, Castagnone-Sereno P, Albuquerque EVS, et al. 2020. Population genomics supports clonal reproduction and multiple independent gains and losses of parasitic abilities in the most devastating nematode pest. Evol. Appl. 13:442-457. 10.1111/eva.12881
[6] Kozlowski D. 2020a. Transposable Elements prediction and annotation in the M. incognita genome. Portail Data INRAE. 10.15454/EPTDOS
[7] Kozlowski D. 2020b. Transposable Elements prediction and annotation in the C. elegans genome. Portail Data INRAE. 10.15454/LQCIW0
[8] Kozlowski D. 2020c. TE polymorphisms detection and analysis with PopoolationTE2. Portail Data INRAE. 10.15454/EWJCT8
[9] Kozlowski DK, Hassanaly-Goulamhoussen R, Da Rocha M, Koutsovoulos GD, Bailly-Bechet M, Danchin EG (2020) Transposable Elements are an evolutionary force shaping genomic plasticity in the parthenogenetic root-knot nematode Meloidogyne incognita. bioRxiv, 2020.04.30.069948, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. 10.1101/2020.04.30.069948
[10] Savary S, Willocquet L, Pethybridge SJ, Esker P, McRoberts N, Nelson A. 2019. The global burden of pathogens and pests on major food crops. Nat. Ecol. Evol. 3:430-439. 10.1038/s41559-018-0793-y
[11] Trudgill DL, Blok VC. 2001. Apomictic, polyphagous root-knot nematodes: exceptionally successful and damaging biotrophic root pathogens. Annu Rev Phytopathol 39:53-77. 10.1146/annurev.phyto.39.1.53

The social amoeba Dictyostelium discoideum is an important model system for the study of cooperation and multicellularity as is has both unicellular and aggregative life phases. In the aggregative phase, which typically occurs when nutrients are limiting, individual cells eventually gather together to form a fruiting bodies whose spores may be dispersed to another, better, location and whose stalk cells, which support the spores, die. This extreme form of cooperation has been the focus of numerous studies that have revealed the importance genetic relatedness and kin selection (Hamilton 1964; Lehmann and Rousset 2014) in explaining the maintenance of this cooperative collective behavior (Strassmann et al. 2000; Kuzdzal-Fick et al. 2011; Strassmann and Queller 2011). However, much remains unknown with respect to how the interactions between individual cells, their neighbors, and their environment produce cooperative behavior at the scale of whole groups or collectives. In this preprint, Forget et al. (2021) describe how the D. discoideum system is crucial in this respect because it allows these cellular-level interactions to be studied in a systematic and tractable manner.
Spore bias, which is the tendency of a particular genotype or strain to disproportionately migrate to the spore instead of the stalk, is often used to define which strains are "cheaters" (positive spore bias) and which are "cooperative" (negative spore bias). Forget et al. (2021) note that spore bias depends on a number of stochastic factors including external drivers such as variation in environmental (or nutrient) quality and internal drivers like cell-cycle phase at the time of starvation. Spore bias is also affected by the social environment where the fraction of cheater strains in a spore may be limited by the ability of the remaining stalk cells to support the spore. The social environment can also affect cells through their differential responsiveness to the chemical factors that induce differentiation into stalk cells; responsiveness is partly a function of nutrient quality (Thompson and Kay 2000), which in turn can be a function of cell density. Thus, Forget et al. (2021) highlight a number of mechanisms that could generate frequency-dependent selection that would lead to the stable maintenance of multiple strains with different spore biases; in other words, both cheater and cooperative strains might stably coexist due to these cellular-level interactions.
The cellular-level interactions that Forget et al. (2021) highlight are particularly important because they pose a challenge evolutionary theory: some evolutionary models of social and collective behavior neglect or simplify these interactions. For example, Forget et al. (2021) note that the developmental, behavior, and environmental timescales relevant for Dictyostelium fruiting body formation all overlap. Evolutionary analyses often assume some of these timescales, for example developmental and behavior, are separate in order to simplify the analysis of any interactions. Thus, new theoretical work that allows these timescales to overlap may shed light on how cellular-level interactions can produce environmental, physiological, and behavioral feedbacks that drive the evolution of cooperation and other collective behaviors.

References

Forget, M., Adiba, S. and De Monte, S.(2021) Social conflicts in *Dictyostelium discoideum *: a matter of scales. HAL, hal-03088868, ver. 2 peer-reviewed and recommended by PCI Evolutionary Biology. https://hal.archives-ouvertes.fr/hal-03088868/

Hamilton, W. D. (1964). The genetical evolution of social behaviour. II. Journal of theoretical biology, 7(1), 17-52. doi: https://doi.org/10.1016/0022-5193(64)90039-6

Kuzdzal-Fick, J. J., Fox, S. A., Strassmann, J. E., and Queller, D. C. (2011). High relatedness is necessary and sufficient to maintain multicellularity in Dictyostelium. Science, 334(6062), 1548-1551. doi: https://doi.org/10.1126/science.1213272

Lehmann, L., and Rousset, F. (2014). The genetical theory of social behaviour. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1642), 20130357. doi: https://doi.org/10.1098/rstb.2013.0357

Strassmann, J. E., and Queller, D. C. (2011). Evolution of cooperation and control of cheating in a social microbe. Proceedings of the National Academy of Sciences, 108(Supplement 2), 10855-10862. doi: https://doi.org/10.1073/pnas.1102451108

Strassmann, J. E., Zhu, Y., & Queller, D. C. (2000). Altruism and social cheating in the social amoeba Dictyostelium discoideum. Nature, 408(6815), 965-967. doi: https://doi.org/10.1038/35050087

Thompson, C. R., & Kay, R. R. (2000). Cell-fate choice in Dictyostelium: intrinsic biases modulate sensitivity to DIF signaling. Developmental biology, 227(1), 56-64. doi: https://doi.org/10.1006/dbio.2000.9877

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.

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

References

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