In this study, Ishigohoka and colleagues tackle an important, yet often overlooked, question on the causes of genetic variation. While genome-wide patterns represent population structure, local variation is often associated with selection. Authors propose that an alternative cause for variation in individual loci is reduced recombination rate.

To test this hypothesis, authors perform local Principal Component Analysis (PCA) (Li & Ralph, 2019) to identify local deviations in population structure in the Eurasian blackcap (Sylvia atricapilla) (Ishigohoka et al. 2022). This approach is typically used to detect chromosomal rearrangements or any long region of linked loci (e.g., due to reduced recombination or selection) (Mérot et al. 2021). While other studies investigated the effect of low recombination on genetic variation (Booker et al. 2020), here authors provide a comprehensive analysis of the effect of recombination to local PCA patterns both in empirical and simulated data sets. Findings demonstrate that low recombination (and not selection) can be the sole explanatory variable for outlier windows. The study also describes patterns of genetic variation along the genome of Eurasian blackcaps, localising at least two polymorphic inversions (Ishigohoka et al. 2022).

Further investigations on the effect of model parameters (e.g., window sizes and thresholds for defining low-recombining regions), as well as the use of powerful neutrality tests are in need to clearly assess whether outlier regions experience selection and reduced recombination, and to what extent.

References

Booker, T. R., Yeaman, S., & Whitlock, M. C. (2020). Variation in recombination rate affects detection of outliers in genome scans under neutrality. Molecular Ecology, 29 (22), 4274–4279. https://doi.org/10.1111/mec.15501

Ishigohoka, J., Bascón-Cardozo, K., Bours, A., Fuß, J., Rhie, A., Mountcastle, J., Haase, B., Chow, W., Collins, J., Howe, K., Uliano-Silva, M., Fedrigo, O., Jarvis, E. D., Pérez-Tris, J., Illera, J. C., Liedvogel, M. (2022) Distinct patterns of genetic variation at low-recombining genomic regions represent haplotype structure. bioRxiv 2021.12.22.473882, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.12.22.473882

Li, H., & Ralph, P. (2019). Local PCA Shows How the Effect of Population Structure Differs Along the Genome. Genetics, 211 (1), 289–304. https://doi.org/10.1534/genetics.118.301747

Mérot, C., Berdan, E. L., Cayuela, H., Djambazian, H., Ferchaud, A.-L., Laporte, M., Normandeau, E., Ragoussis, J., Wellenreuther, M., & Bernatchez, L. (2021). Locally Adaptive Inversions Modulate Genetic Variation at Different Geographic Scales in a Seaweed Fly. Molecular Biology and Evolution, 38 (9), 3953–3971. https://doi.org/10.1093/molbev/msab143

Not all genetic elements composing genomes are there for the benefit of their carrier. Many have no consequences on fitness, or too mild ones to be eliminated by selection, and thus stem from neutral processes. Many others are indeed the product of selection, but one acting at a different level, increasing the fitness of some elements of the genome only, at the expense of the “organism” as a whole. These can be called selfish genetic elements, and come into a wide variety of flavours [1], illustrating many possible means to cheat with “fair” reproductive processes such as meiosis, and thus get overrepresented in the offspring of their hosts. Producing copies of itself through transposition is one such strategy; a very successful one indeed, explaining a large part of the genomic content of many organisms. Killing non carrier gametes following meiosis in heterozygous carriers is another one. Less know and less common is the ability of some elements to turn heterozygous carriers into homozygous ones, that will thus transmit the selfish elements to all offspring instead of half. This is achieved by nucleic sequences encoding so-called “Homing endonucleases” (HEs). These proteins tend to induce double strand breaks of DNA specifically in regions homologous to their own insertion sites. The recombination machinery is such that the intact homologous region, that is, the one carrying the HE sequence, is then used as a template for the reparation of the break, resulting in the effective conversion of a non-carrier allele into a carrier allele. Such elements can also occur in the mitochondrial genomes of organisms where mitochondria are not strictly transmitted by one parent only, offering mitochondrial HEs some opportunities for “homing” into new non carrier genomes. This is the case in yeasts, where HEs were first reported [2,3].
In this new study, based on genomic experimental data from the fungal maize pathogen Ustilago maydis, Julien Dutheil and colleagues [4] document one possible evolutionary pathway for which little evidence existed before: the passage of a mitochondrial HE into the nuclear genome. The GC content of this region leaves little doubt on its mitochondrial origin, and homologs can indeed be found in the mitochondrial genomes of close relatives. Strangely enough, U. maydis itself does not appear to carry this selfish element in its own mitochondria, suggesting it may have been acquired from a different species, or be subject to a sufficiently rapid turnover to have been recently lost.
Many elements of the story uncovered by this study remain mysterious. How, in the first place, was this HE gene inserted in a nuclear genomic region that shows no apparent homology with its original insertion site, making typical “homing” a not-so-likely explanation? This question may in fact be generalised to many HE systems: is the first insertion into a homing site always the product of a typical homing event, which implies the presence of an homologous template DNA fragment, or can HE genes insert through other means? But then, why specifically in regions that would be targeted by the nuclease they encode? What is the evolutionary fate of this newly inserted element? The new gene may well be on its way to pseudogenisation, as suggested by the truncation of its upper part, precluding its functioning as a HE, and the lack of evidence of selective constraints through dN/dS analysis; but the mutation generated by the insertion event may have phenotypic implications, possibly through the partial truncation of another gene, encoding a helicase. How old is this insertion? The fact that it has accumulated some mutations makes a very recent event rather unlikely, but this insertion has been detected in only one isolate of U. maydis, suggesting it is not so frequent in natural populations.
Whatever the answers to these open questions, that will hopefully be addressed by further work on this system, the present study has revealed that horizontal transmission enlarges the scope of possible evolutionary consequences of HE genes, that may move not only between mitochondrial genomes, but also occasionally into a nucleus.

References

[1] Burt, A., and Trivers, R. (2006). Genes in Conflict: The Biology of Selfish Genetic Elements. Belknap Press.
[2] Coen, D., Deutch, J., Netter, P., Petrochillo, E., and Slonimski, P. (1970). Mitochondrial genetics. I. Methodology and phenomenology. Symposia of the Society for Experimental Biology, 24, 449-496.
[3] Colleaux, L., D’Auriol, L., Betermier, M., Cottarel, G., Jacquier, A., Galibert, F., and Dujon, B. (1986). Universal code equivalent of a yeast mitochondrial intron reading frame is expressed into E. coli as a specific double strand endonuclease. Cell, 44, 521–533. doi: 10.1016/0092-8674(86)90262-X
[4] Dutheil, J. Y., Münch, K., Schotanus, K., Stukenbrock, E. H., and Kahmann, R. (2020). The insertion of a mitochondrial selfish element into the nuclear genome and its consequences. bioRxiv, 787044, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/787044

In this manuscript [1], Francisco J. Novo proposes candidate non-coding genomic elements regulating neurodevelopmental genes.

What is very nice about this study is the way in which public molecular data, including physical interaction data, is used to leverage recent advances in our understanding to molecular mechanisms of gene regulation in an evolutionary context. More specifically, evolutionarily conserved non coding sequences are combined with enhancers from the FANTOM5 project, DNAse hypersensitive sites, chromatin segmentation, ChIP-seq of transcription factors and of p300, gene expression and eQTLs from GTEx, and physical interactions from several Hi-C datasets. The candidate regulatory regions thus identified are linked to candidate regulated genes, and the author shows their potential implication in brain development.

While the results are focused on a small number of genes, this allows to verify features of these candidates in great detail. This study shows how functional genomics is increasingly allowing us to fulfill the promises of Evo-Devo: understanding the molecular mechanisms of conservation and differences in morphology.

References

[1] Novo, FJ. 2017. Evolutionary analysis of candidate non-coding elements regulating neurodevelopmental genes in vertebrates. bioRxiv, 150482, ver. 4 of Sept 29th, 2017. doi: 10.1101/150482

Parasitoid wasps have developed different mechanisms to increase their parasitic success, usually at the expense of host survival (Fellowes and Godfray, 2000). Eggs of these insects are deposited inside the juvenile stages of their hosts, which in turn deploy several immune response strategies to eliminate or disable them (Yang et al., 2020). Drosophila melanogaster protects itself against parasitoid attacks through the production of specific elongated haemocytes called lamellocytes which form a capsule around the invading parasite (Lavine and Strand, 2002; Rizki and Rizki, 1992) and the subsequent activation of the phenol-oxidase cascade leading to the release of toxic radicals (Nappi et al., 1995). On the parasitoid side, robust responses have evolved to evade host immune defenses as for example the Drosophila-specific endoparasite Leptopilina boulardi, which releases venom during oviposition that modifies host behaviour (Varaldi et al., 2006) and inhibits encapsulation (Gueguen et al., 2011; Martinez et al., 2012).
Studies have shown that the wasp parasitic capacity is correlated to venom presence and its content (Colinet et al., 2009; Poirié et al., 2014), including that evolution of venom protein composition is driven by different levels of host susceptibility to infection (Cavigliasso et al., 2019). However, it had not been determined to this day, if and how parasitic range can affect venom protein composition and to which extent host specialization requires broad-spectrum factors or a plethora of specialized components.
These outstanding questions are now approached in a study by Cavigliasso and colleagues (Cavigliasso et al., 2021), where they perform experimental evolution of L. boulardi for 9 generations exposing it to different Drosophila host species and genetic backgrounds (two strains of D. melanogaster, D. simulans and D. yakuba). The authors tested whether the parasitic success of each selection regime was host-specific and how they influenced venom composition in parasitoids. For the first part, infection outcomes were assayed for each selection regime when cross-infecting different hosts. To get a finer measurement of the mechanisms under selection, the authors differentiated three phenotypes: overall parasitic success, encapsulation inhibition and escape from capsule. Throughout the course of experimental evolution, only encapsulation inhibition did not show an improved response upon selection on any host. Importantly, the cross-infection scenario revealed a clear specificity to the selected host for each evolved resistance.
As for venom composition, a trend of differential evolution was detected between host species, although a significant part of that was due to a larger differentiation in the D. yakuba regime, which showed a completely different directionality. Importantly, the authors could identify some of the specific proteins targeted by the several selection regimes, whether selected or counter-selected for. Interestingly, the D. yakuba regime is the only case where the key parasitoid protein LbSPNy (Colinet et al., 2009) was not counter-selected and the only regime in which the overall venom composition did not evolve towards the Ism strain, one of the two ancestral strains of L. boulardi used in the study. It is possible that these two results are correlated, since LbSPNy has been described to inhibit activation of the phenoloxidase cascade in D. yakuba and is one of the most abundant proteins in the ISy venom, making it a good target for selection (Colinet et al., 2013). The authors also discuss the possibility that this difference is related to the geographical distribution of the strains of L. boulardi, since each coincide with either D. melanogaster or D. yakuba.
This methodologically broad work by Cavigliasso and colleagues constitutes an important experimental contribution towards the understanding of how parasitoid adaptation to specific hosts is achieved at different phenotypic and mechanistic levels. It provides compelling evidence that venom composition evolves differently in response to specific parasitic ranges, particularly considering the evolutionary difference between the selective hosts. In line with this result, it is also concluded that the majority of venom proteins selected are lineage-specific, although a few broad-spectrum factors could also be detected. 
The question of whether parasitic range can affect venom composition and parasitic success is still open to more contributions. A potentially interesting long-term direction will be to use a similar setup of experimental evolution on the generalist L. heterotoma (Schlenke et al., 2007) . On a more immediate horizon, comparing the venom evolution of both L. heterotoma and L. boulardi under selection with different hosts and under cross-infection scenarios could reveal interesting patterns. The recent sequencing of the L. boulardi genome together with the vast number of studies addressing mechanisms of Drosophila resistance to parasitoid infection, will enable the thorough characterization of the genetic basis of host-parasitoid interactions and the deeper understanding of these ubiquitous and economically-relevant relationships.
 
*This recommendation text has been co-written with Tânia F. Paulo who is not a recommender of PCI Evol Biol

References

Cavigliasso, F., Mathé-Hubert, H., Gatti, J.-L., Colinet, D. and Poirié, M. (2021) Parasitic success and venom composition evolve upon specialization of parasitoid wasps to different host species. bioRxiv, 2020.10.24.353417, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2020.10.24.353417

Cavigliasso, F., Mathé-Hubert, H., Kremmer, L., Rebuf, C., Gatti, J.-L., Malausa, T., Colinet, D., Poiré, M. and  Léne. (2019). Rapid and Differential Evolution of the Venom Composition of a Parasitoid Wasp Depending on the Host Strain. Toxins, 11(629). https://doi.org/10.3390/toxins11110629

Colinet, D., Deleury, E., Anselme, C., Cazes, D., Poulain, J., Azema-Dossat, C., Belghazi, M., Gatti, J. L. and  Poirié, M. (2013). Extensive inter- and intraspecific venom variation in closely related parasites targeting the same host: The case of Leptopilina parasitoids of Drosophila. Insect Biochemistry and Molecular Biology, 43(7), 601–611. https://doi.org/10.1016/j.ibmb.2013.03.010

Colinet, D., Dubuffet, A., Cazes, D., Moreau, S., Drezen, J. M. and  Poirié, M. (2009). A serpin from the parasitoid wasp Leptopilina boulardi targets the Drosophila phenoloxidase cascade. Developmental and Comparative Immunology, 33(5), 681–689. https://doi.org/10.1016/j.dci.2008.11.013

Fellowes, M. D. E. and  Godfray, H. C. J. (2000). The evolutionary ecology of resistance to parasitoids by Drosophila. Heredity, 84(1), 1–8. https://doi.org/10.1046/j.1365-2540.2000.00685.x

Gueguen, G., Rajwani, R., Paddibhatla, I., Morales, J. and  Govind, S. (2011). VLPs of Leptopilina boulardi share biogenesis and overall stellate morphology with VLPs of the heterotoma clade. Virus Research, 160(1–2), 159–165. https://doi.org/10.1016/j.virusres.2011.06.005

Lavine, M. D. and  Strand, M. R. (2002). Insect hemocytes and their role in immunity. Insect Biochemistry and Molecular Biology, 32(10), 1295–1309. https://doi.org/10.1016/S0965-1748(02)00092-9

Martinez, J., Duplouy, A., Woolfit, M., Vavre, F., O’Neill, S. L. and  Varaldi, J. (2012). Influence of the virus LbFV and of Wolbachia in a host-parasitoid interaction. PloS One, 7(4), e35081. https://doi.org/10.1371/journal.pone.0035081

Nappi, A. J., Vass, E., Frey, F. and  Carton, Y. (1995). Superoxide anion generation in Drosophila during melanotic encapsulation of parasites. European Journal of Cell Biology, 68(4), 450–456.

Poirié, M., Colinet, D. and  Gatti, J. L. (2014). Insights into function and evolution of parasitoid wasp venoms. Current Opinion in Insect Science, 6, 52–60. https://doi.org/10.1016/j.cois.2014.10.004

Rizki, T. M. and  Rizki, R. M. (1992). Lamellocyte differentiation in Drosophila larvae parasitized by Leptopilina. Developmental and Comparative Immunology, 16(2–3), 103–110. https://doi.org/10.1016/0145-305X(92)90011-Z

Schlenke, T. A., Morales, J., Govind, S. and  Clark, A. G. (2007). Contrasting infection strategies in generalist and specialist wasp parasitoids of Drosophila melanogaster. PLoS Pathogens, 3(10), 1486–1501. https://doi.org/10.1371/journal.ppat.0030158

Varaldi, J., Petit, S., Boulétreau, M. and  Fleury, F. (2006). The virus infecting the parasitoid Leptopilina boulardi exerts a specific action on superparasitism behaviour. Parasitology, 132(Pt 6), 747–756. https://doi.org/10.1017/S0031182006009930

Yang, L., Qiu, L., Fang, Q., Stanley, D. W. and  Gong‐Yin, Y. (2020). Cellular and humoral immune interactions between Drosophila and its parasitoids. Insect Science. https://doi.org/10.1111/1744-7917.12863

Although most mutations are deleterious, the strongly deleterious ones do not spread in a very large population as their chance of fixation is very small. Another mechanism via which the deleterious mutations can be eliminated is via recombination or sexual reproduction. However, in a finite asexual population, the subpopulation without any deleterious mutation will eventually acquire a deleterious mutation resulting in the reduction of the population size or in other words, an increase in the genetic drift. This, in turn, will lead the population to acquire deleterious mutations at a faster rate eventually leading to a mutational meltdown.

This irreversible (or, at least over some long time scales) accumulation of deleterious mutations is especially relevant to RNA viruses due to their high mutation rate, and while the prior work has dealt with bacteriophages and RNA viruses, the study by Lafforgue et al. [1] makes an interesting contribution to the existing literature by focusing on plants.

In this study, the authors enquire how despite the repeated increase in the strength of genetic drift, how the RNA viruses manage to survive in plants. Following a series of experiments and some numerical simulations, the authors find that as expected, after severe bottlenecks, the fitness of the population decreases significantly. But if the bottlenecks are followed by population expansion, the Muller’s ratchet can be halted due to the genetic diversity generated during population growth. They hypothesize this mechanism as a potential way by which the RNA viruses can survive the mutational meltdown.

As a theoretician, I find this investigation quite interesting and would like to see more studies addressing, e.g., the minimum population growth rate required to counter the potential extinction for a given bottleneck size and deleterious mutation rate. Of course, it would be interesting to see in future work if the hypothesis in this article can be tested in natural populations.

References

[1] Guillaume Lafforgue, Marie Lefebvre, Thierry Michon, Santiago F. Elena (2024) How do plant RNA viruses overcome the negative effect of Muller s ratchet despite strong transmission bottlenecks? bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community In Evolutionary Biology
https://doi.org/10.1101/2023.08.01.550272