Accurate information flow is central to living systems. The continuity of genomes through generations as well as the reproducible functioning and survival of the individual organisms require a faithful information transfer during replication, transcription and translation. The differential efficiency of natural selection against “mistakes” results in decreasing fidelity rates for replication, transcription and translation. At each level in the information flow chain (replication, transcription, translation), numerous complex molecular systems have evolved and been selected for preventing, identifying and, when possible, correcting or removing such “mistakes” arising during information transfer.

However, fidelity cannot be improved ad infinitum. First, because of the limits imposed by the physical nature of the processes of copying and recoding information over different molecular supports: all mechanisms ensuring fidelity during biological information transfer ultimately rely on chemical kinetics and thermodynamics. The more accurate a copying process is, the lower the synthesis rate and the higher the energetic cost of correcting errors. Second, because of the limits imposed by random genetic drift: natural selection cannot effectively act on an allele that contributes with a small differential advantage unless effective population size is large. If s <1/Ne (or s <1/(2Ne) in diploids) the allele frequency in the population is de facto subject to neutral drift processes.

In their preprint “Random genetic drift sets an upper limit on mRNA splicing accuracy in metazoans”, Bénitière, Necsulea and Duret explore the validity of this last mentioned “drift barrier” hypothesis for the case study of alternative splicing diversity in eukaryotes (Bénitière et al. 2022). Splicing refers to an ensemble of eukaryotic molecular processes mediated by a large number of proteins and ribonucleoproteins and involving nucleotide sequence recognition, that uses as a molecular substrate a precursor messenger RNA (mRNA), directly transcribed from the DNA, and produces a mature mRNA by removing introns and joining exons (Chow et al. 1977). Alternative splicing refers to the case in which different molecular species of mature mRNAs can be produced, either by cis-splicing processes acting on the same precursor mRNA, e.g. by varying the presence/absence of different exons or by varying the exon-exon boundaries, or by trans-splicing processes, joining exons from different precursor mRNA molecules.

The diversity of mRNA molecular species generated by alternative splicing enlarges the molecular phenotypic space that can be generated from the same genotype. In humans, alternative splicing occurs in around 95% of the ca. 20,000 genes, resulting in ca. 100,000 medium-to-high abundance transcripts (Pan et al. 2008). In multicellular organisms, the frequency of alternatively spliced mRNAs varies between tissues and across ontogeny, often in a switch-like pattern (Wang et al. 2008). In the molecular and cell biology community, it is commonly accepted that splice variants contribute with specific functions (Marasco and Kornblihtt 2023) although there exists a discussion around the functional nature of low-frequency splice variants (see for instance the debate between Tress et al. 2017 and Blencowe 2017). The origin, diversity, regulation and evolutionary advantage of alternative splicing constitutes thus a playground of the selectionist-neutralist debate, with one extreme considering that most splice variants are mere “mistakes” of the splicing process (Pickrell et al. 2010), and the other extreme considering that alternative splicing is at the core of complexity in multicellular organisms, as it increases the genome coding potential and allows for a large repertoire of cell types (Chen et al. 2014).

In their manuscript, Bénitière, Necsulea and Duret set the cursor towards the neutralist end of the gradient and test the hypothesis of whether the high alternative splice rate in “complex” organisms corresponds to a high rate of splicing “mistakes”, arising from the limit imposed by the drift barrier effect on the power of natural selection to increase accuracy (Bush et al. 2017). In their preprint, the authors convincingly show that in metazoans a fraction of the variation of alternative splicing rate is explained by variation in proxies of population size, so that species with smaller Ne display higher alternative splice rates. They communicate further that abundant splice variants tend to preserve the reading frame more often than low-frequency splice variants, and that the nucleotide splice signals in abundant splice variants display stronger evidence of purifying selection than those in low-frequency splice variants. From all the evidence presented in the manuscript, the authors interpret that “variation in alternative splicing rate is entirely driven by variation in the efficacy of selection against splicing errors”.

The authors honestly present some of the limitations of the data used for the analyses, regarding i) the quality of the proxies used for Ne (i.e. body length, longevity and dN/dS ratio); ii) the heterogeneous nature of the RNA sequencing datasets (full organisms, organs or tissues; different life stages, sexes or conditions); and iii) mostly short RNA reads that do not fully span individual introns. Further, data from bacteria do not verify the herein communicated trends, as it has been shown that bacterial species with low population sizes do not display higher transcription error rates (Traverse and Ochman 2016). Finally, it will be extremely interesting to introduce a larger evolutionary perspective on alternative splicing rates encompassing unicellular eukaryotes, in which an intriguing interplay between alternative splicing and gene duplication has been communicated (Hurtig et al. 2020).

The manuscript from Bénitière, Necsulea and Duret makes a significant advance to our understanding of the diversity, the origin and the physiology of post-transcriptional and post-translational mechanisms by emphasising the fundamental role of non-adaptive evolutionary processes and the upper limits to splicing accuracy set by genetic drift.

References

Bénitière F, Necsulea A, Duret L. 2023. Random genetic drift sets an upper limit on mRNA splicing accuracy in metazoans. bioRxiv, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.12.09.519597 

Blencowe BJ. 2017. The Relationship between Alternative Splicing and Proteomic Complexity. Trends Biochem Sci 42:407–408. https://doi.org/10.1016/j.tibs.2017.04.001

Bush SJ, Chen L, Tovar-Corona JM, Urrutia AO. 2017. Alternative splicing and the evolution of phenotypic novelty. Philos Trans R Soc Lond B Biol Sci 372:20150474. https://doi.org/10.1098/rstb.2015.0474

Chen L, Bush SJ, Tovar-Corona JM, Castillo-Morales A, Urrutia AO. 2014. Correcting for differential transcript coverage reveals a strong relationship between alternative splicing and organism complexity. Mol Biol Evol 31:1402–1413. https://doi.org/10.1093/molbev/msu083

Chow LT, Gelinas RE, Broker TR, Roberts RJ. 1977. An amazing sequence arrangement at the 5’ ends of adenovirus 2 messenger RNA. Cell 12:1–8. https://doi.org/10.1016/0092-8674(77)90180-5

Hurtig JE, Kim M, Orlando-Coronel LJ, Ewan J, Foreman M, Notice L-A, Steiger MA, van Hoof A. 2020. Origin, conservation, and loss of alternative splicing events that diversify the proteome in Saccharomycotina budding yeasts. RNA 26:1464–1480. https://doi.org/10.1261/rna.075655.120

Marasco LE, Kornblihtt AR. 2023. The physiology of alternative splicing. Nat Rev Mol Cell Biol 24:242–254. https://doi.org/10.1038/s41580-022-00545-z

Pan Q, Shai O, Lee LJ, Frey BJ, Blencowe BJ. 2008. Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat Genet 40:1413–1415. https://doi.org/10.1038/ng.259

Pickrell JK, Pai AA, Gilad Y, Pritchard JK. 2010. Noisy splicing drives mRNA isoform diversity in human cells. PLoS Genet 6:e1001236. https://doi.org/10.1371/journal.pgen.1001236

Traverse CC, Ochman H. 2016. Conserved rates and patterns of transcription errors across bacterial growth states and lifestyles. Proc Natl Acad Sci U S A 113:3311–3316. https://doi.org/10.1073/pnas.1525329113

Tress ML, Abascal F, Valencia A. 2017. Alternative Splicing May Not Be the Key to Proteome Complexity. Trends Biochem Sci 42:98–110. https://doi.org/10.1016/j.tibs.2016.08.008

Wang ET, Sandberg R, Luo S, Khrebtukova I, Zhang L, Mayr C, Kingsmore SF, Schroth GP, Burge CB. 2008. Alternative isoform regulation in human tissue transcriptomes. Nature 456:470–476. https://doi.org/10.1038/nature07509

The evolution of cells within organisms can be an important determinant of disease. This is especially clear in the emergence of tumors and cancers from the underlying healthy tissue. In the healthy state, homeostasis is maintained through complex regulatory processes that ensure a relatively constant population size of cells, which is required for tissue function. Tumor cells escape this homeostasis, resulting in uncontrolled growth and consequent disease. Disease progression is driven by further evolutionary processes within the tumor, and so is the response of tumors to therapies. Therefore, evolutionary biology is an important component required for a better understanding of carcinogenesis and the treatment of cancers. In particular, evolutionary theory helps define the principles of mutant evolution and thus to obtain a clearer picture of the determinants of tumor emergence and therapy responses.     

The study by Raatz and Traulsen [1] makes an important contribution in this respect. They use mathematical and computational models to investigate trait evolution in the context of evolutionary rescue, motivated by the dynamics of cancer, and also bacterial infections. This study views the establishment of tumors as cell dynamics in harsh environments, where the population is prone to extinction unless mutants emerge that increase evolutionary fitness, allowing them to expand (evolutionary rescue). The core processes of the model include growth, death, and mutations. Random mutations are assumed to give rise to cell lineages with different trait combinations, where the birth and death rates of cells can change.  The resulting evolutionary trajectories are investigated in the models, and interesting new results were obtained. For example, the turnover of the population was identified as an important determinant of trait evolution. Turnover is defined as the balance between birth and death, with large rates corresponding to fast turnover and small rates to slow turnover. It was found that for fast cell turnover, a given adaptive step in the trait space results in a smaller increase in survival probability than for cell populations with slower turnover. In other words, evolutionary rescue is more difficult to achieve for fast compared to slow turnover populations. While more mutants can be produced for faster cell turnover rates, the analysis showed that this is not sufficient to overcome the barrier to the evolutionary rescue. This result implies that aggressive tumors with fast cell birth and death rates are less likely to persist and progress than tumors with lower turnover rates. This work emphasizes the importance of measuring the turnover rate in different tumors to advance our understanding of the determinants of tumor initiation and progression. The authors discuss that the well-documented heterogeneity in tumors likely also applies to cellular turnover. If a tumor consists of sub-populations with faster and slower turnover, it is possible that a slower turnover cell clone (e.g. characterized by a degree of dormancy) would enjoy a selective advantage. Another source of heterogeneity in turnover could be given by the hierarchical organization of tumors. Similar to the underlying healthy tissue, many tumors are thought to be maintained by a population of cancer stem cells, while the tumor bulk is made up of more differentiated cells. Tissue stem cells tend to be characterized by a lower turnover than progenitor or transit-amplifying cells. Depending on the assumptions about the self-renewal capacity of these different cell populations, the potential for evolutionary rescue could be different depending on the cell compartment in which the mutant emerges. This might be interesting to explore in the future.

There are also implications for treatment. Two types of treatment were investigated: density-affecting treatments in which the density of cells is reduced without altering their trait parameters, and trait-affecting treatments in which the birth and/or death rates are altered. Both types of treatment were found to change the trajectories of trait adaptation, which has potentially important practical implications. Interestingly, it was found that competitive release during treatment can result in situations where after treatment cessation, the non-extinct populations recover to reach sizes that were higher than in the absence of treatment. This points towards the potential of adaptive therapy approaches, where sensitive cells are maintained to some extent to suppress resistant clones [2] competitively. In this context, it is interesting that the success of such approaches might also depend on the turnover of the tumor cell population, as shown by a recent mathematical modeling study [3]. In particular, it was found that adaptive therapy is less likely to work for slow compared to fast turnover tumors. Yet, the current study by Raatz and Traulsen [1] suggests that tumors are more likely to evolve in a slow turnover setting.

While there is strong relevance of this analysis for tumor evolution, the results generated in this study have more general relevance. Besides tumors, the paper discusses applications to bacterial disease dynamics in some detail, which is also interesting to compare and contrast to evolutionary processes in cancer. Overall, this study provides insights into the dynamics of evolutionary rescue that represent valuable additions to evolutionary theory.  

References

[1] Raatz M, Traulsen A (2023) Promoting extinction or minimizing growth? The impact of treatment on trait trajectories in evolving populations. bioRxiv, 2022.06.17.496570, ver. 2 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.06.17.496570

[2] Gatenby RA, Silva AS, Gillies RJ, Frieden BR (2009) Adaptive Therapy. Cancer Research, 69, 4894–4903. https://doi.org/10.1158/0008-5472.CAN-08-3658

[3] Strobl MAR, West J, Viossat Y, Damaghi M, Robertson-Tessi M, Brown JS, Gatenby RA, Maini PK, Anderson ARA (2021) Turnover Modulates the Need for a Cost of Resistance in Adaptive Therapy. Cancer Research, 81, 1135–1147. https://doi.org/10.1158/0008-5472.CAN-20-0806

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

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

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

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

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

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

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

References

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

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

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

The observed levels of genomic diversity in contemporary populations are the result of changes imposed by several evolutionary processes. Among them, natural selection is known to dramatically shape the genetic diversity of loci associated with phenotypes which affect the fitness of carriers. As such, many efforts have been dedicated towards developing methods to detect signatures of natural selection from genomes of contemporary samples [1].
Recent technological advances made the generation of large-scale genomic data from temporal samples, either from experimental populations or historical or ancient samples, accessible to a wide scientific community [2]. Notably, temporal population genomic data allow for a direct observation and study of how, for instance, allele frequencies change through time in response to evolutionary stimuli. Such information can be exploited to detect loci under natural selection, either via mathematical modelling or by investigating empirical distributions [3].
However, most of current methods to detect selection from temporal genomic data have largely ignored selfing populations, despite the latter comprising a significant proportion of species with social and economic importance. Selfing changes genomic patterns by reducing the effective recombination rate, which makes distinguishing between neutral evolution and natural selection even more challenging than for the case of outcrossing populations [4]. Nevertheless, an outlier-approach based on temporal genomic data for the selfing Arabidopsis thaliana population revealed loci under selection [5].
This study suggested the promise of detecting selection for selfing populations and encouraged further investigations to test the power of selection scans under different mating systems.
To address this question, Navascués et al. [6] extended a previously proposed approach for temporal genome scan [7] to incorporate partial self-fertilization. In the original implementation [7], it is assumed that, under neutrality, all loci provide levels of genetic differentiation drawn from the same distribution. If some of the loci are under selection, such distribution should show heterogeneity. Navascués et al. [6] proposed a test for the homogeneity between loci-specific and genome-wide differentiation by deriving a null distribution of FST via simulations using SLiM [8]. After filtering for low-frequency variants and correct for multiple tests, authors derived a statistical test for selection and assess its power under a wide range of scenarios of selfing rate, selection coefficient, duration and type of selection [6].
The newly proposed test achieved good performance to distinguish between neutral and selected loci in most tested scenarios.
As expected, the test's performance significantly drops for scenarios of high selfing rates and selection from standing variation. Additionally, the probability to correctly detect selection decreases with increasing distance from the causal variant. Intriguingly, the test showed high power when the selected ancestral allele had an initial low frequency, and when the selected derived allele had a high initial frequency. When applied to a data set of around 1,000 SNPs from the highly selfing Medicago truncatula population, an annual plant of the legume family [9], the test did not provide any candidate loci under selection [6].
In summary, the detection of loci under selection in selfing populations is and largely remains a challenging task even when explictly account for the different mating system. However, recombination events that occurred before the selective pressure allow ancestral beneficial alleles to exhibit a detectable pattern of non-neutrality. As such, in partially selfing populations, the strength of the footprint of selection depends on several factors, mostly on the selfing rate, the time of onset and type of selection.
One major assumption of this study is that the model implies unstructured population and continuity between samples obtained from the same geographical location over time. As such assumptions are typically violated in real populations, further research into the effect of more complex demographic scenarios is desired to fully understand the power to detect selection in selfing populations. Furthermore, more power could be gained by including additional genomic information at each time point. In this context, recent approaches that make full use of genomic data based on deep learning [10] may contribute significantly towards this goal. Similarly, the effect of data filtering on the power to detect selection should be further explored, especially in the context of DNA resequencing experiments. These analyses will help elucidate the power offered by selection scans from temporal genomic data in selfing populations.

References

[1] Stern AJ, Nielsen R (2019) Detecting Natural Selection. In: Handbook of Statistical Genomics , pp. 397–40. John Wiley and Sons, Ltd. https://doi.org/10.1002/9781119487845.ch14
[2] Leonardi M, Librado P, Der Sarkissian C, Schubert M, Alfarhan AH, Alquraishi SA, Al-Rasheid KAS, Gamba C, Willerslev E, Orlando L (2017) Evolutionary Patterns and Processes: Lessons from Ancient DNA. Systematic Biology, 66, e1–e29. https://doi.org/10.1093/sysbio/syw059
[3] Dehasque M, Ávila‐Arcos MC, Díez‐del‐Molino D, Fumagalli M, Guschanski K, Lorenzen ED, Malaspinas A-S, Marques‐Bonet T, Martin MD, Murray GGR, Papadopulos AST, Therkildsen NO, Wegmann D, Dalén L, Foote AD (2020) Inference of natural selection from ancient DNA. Evolution Letters, 4, 94–108. https://doi.org/10.1002/evl3.165
[4] Vitalis R, Couvet D (2001) Two-locus identity probabilities and identity disequilibrium in a partially selfing subdivided population. Genetics Research, 77, 67–81. https://doi.org/10.1017/S0016672300004833
[5] Frachon L, Libourel C, Villoutreix R, Carrère S, Glorieux C, Huard-Chauveau C, Navascués M, Gay L, Vitalis R, Baron E, Amsellem L, Bouchez O, Vidal M, Le Corre V, Roby D, Bergelson J, Roux F (2017) Intermediate degrees of synergistic pleiotropy drive adaptive evolution in ecological time. Nature Ecology and Evolution, 1, 1551–1561. https://doi.org/10.1038/s41559-017-0297-1
[6] Navascués M, Becheler A, Gay L, Ronfort J, Loridon K, Vitalis R (2020) Power and limits of selection genome scans on temporal data from a selfing population. bioRxiv, 2020.05.06.080895, ver. 4 peer-reviewed and recommended by PCI Evol Biol. https://doi.org/10.1101/2020.05.06.080895
[7] Goldringer I, Bataillon T (2004) On the Distribution of Temporal Variations in Allele Frequency: Consequences for the Estimation of Effective Population Size and the Detection of Loci Undergoing Selection. Genetics, 168, 563–568. https://doi.org/10.1534/genetics.103.025908
[8] Messer PW (2013) SLiM: Simulating Evolution with Selection and Linkage. Genetics, 194, 1037–1039. https://doi.org/10.1534/genetics.113.152181
[9] Siol M, Prosperi JM, Bonnin I, Ronfort J (2008) How multilocus genotypic pattern helps to understand the history of selfing populations: a case study in Medicago truncatula. Heredity, 100, 517–525. https://doi.org/10.1038/hdy.2008.5
[10] Sanchez T, Cury J, Charpiat G, Jay F Deep learning for population size history inference: Design, comparison and combination with approximate Bayesian computation. Molecular Ecology Resources, n/a. https://doi.org/10.1111/1755-0998.13224

Koutsovoulos et al. [1] have generated and analysed the first population genomic dataset in root-knot nematode Meloidogyne incognita. Why is this interesting? For two major reasons. First, M. incognita has been documented to be apomictic, i.e., to lack any form of sex. This is a trait of major evolutionary importance, with implications on species adaptive potential. The study of genome evolution in asexuals is fascinating and has the potential to inform on the forces governing the evolution of sex and recombination. Even small amounts of sex, however, are sufficient to restore most of the population genetic properties of true sexuals [2]. Because rare events of sex can remain undetected in the field, to confirm asexuality in M. incognita using genomic data is an important step. The second reason why M. incognita is of interest is that this nematode is one of the most harmful pests currently living on earth. M. incognita feeds on the roots of many cultivated plants, including tomato, bean, and cotton, and has been of major agricultural importance for decades. A number of races were defined based on host specificity. These have played a key role in attempts to control the dynamic of M. incognita populations via crop rotations. Races and management strategies so far lack any genetic basis, hence the second major interest of this study.
The authors newly sequenced the full genome of eleven strains from Brazil and added nine already available samples from Africa and North-America. They report that, in all likelihood, M. incognita is indeed a purely asexual species. This is supported by (i) the confirmation that the genome is in its major part haploid, and (ii) a spectacularly high level of linkage disequilibrium, which does not decline with genetic distance between loci at a 100kb scale. The absence of sex and recombination is associated in M. incognita with a remarkably low amount of genetic diversity - one order of magnitude less than in typical sexual nematodes - and an heavy load of deleterious mutations, as measured by the ratio of non-synonymous (=amino-acid changing) to synonymous (=amino-acid conservative) diversity in coding sequences. The other important result of this study is that the population substructure in M. incognita is in no way related to host races or geography. The tree genetic clusters that are identified include strains from several continents and feeding on a diversity of host plants.
The implications of this work are numerous. First, the results suggest that M. incognita is an ancient asexual. Asexuality, which was here demonstrated via linkage disequilibrium analysis, must be ancient enough for diploidy (or, in this case, maybe triploidy) to have been lost - i.e., formerly homologous chromosomes have accumulated enough mutations to be assembled as distinct entities. So we are not talking about a highly successful clone having recently spread the world - rather a long-term obligate parthenogen. Asexual organisms are deprived of the source of genetic variation offered by recombination, which is why asexuality is thought to be an evolutionary dead-end. Long-term asexuals are uncommon and even the most famous ones, bdelloid rotifers, are suspected to experience between-individual genetic transfers [3]. M. incognita is apparently a true 'evolutionary scandal', and as such deserves particular attention from molecular evolutionary geneticists.
The lack of any host race effect on the genetic diversity of M. incognita is another important finding. So-called 'races' have largely contributed to shape researchers' view of the structure of the species so far. This study demonstrates that a mental effort is now needed to forget about races, and consider host-specificity for what it is - a phenotypic trait. This result implies that many host shifts must have independently occurred in the three M. incognita genetic lineages, suggesting an arms race between plants and nematodes, which in the absence of sex and recombination must be entirely mutation-driven on the nematode side. Genes functionally involved in the arms race might therefore be expected to have experienced convergent evolution, if distinct M. incognita lineages have adopted the same solutions to overcome plant defenses. The present study paves the way for such a genome scan. The authors rightly discuss that the strong adaptive potential of M. incognita, at least in terms of host shift, despite no sex and tiny amounts of genetic diversity, is a paradox that would deserve to be further investigated.

References

[1] Koutsovoulos, G. D., Marques, E., Arguel, M. J., Duret, L., Machado, A. C. Z., Carneiro, R. M. D. G., Kozlowski, D. K., Bailly-Bechet, M., Castagnone-Sereno, P., Albuquerque, E. V., & Danchin, E. G. J. (2019). Population genomics supports clonal reproduction and multiple gains and losses of parasitic abilities in the most devastating nematode plant pest. bioRxiv, 362129, ver. 5, peer-reviewed and recommended by Peer Community in Evolutionary Biology. doi: 10.1101/362129
[2] Hartfield, M. (2016). Evolutionary genetic consequences of facultative sex and outcrossing. Journal of evolutionary biology, 29(1), 5-22. doi: 10.1111/jeb.12770
[3] Debortoli, N., Li, X., Eyres, I., Fontaneto, D., Hespeels, B., Tang, C. Q., Flot, J. F. & Van Doninck, K. (2016). Genetic exchange among bdelloid rotifers is more likely due to horizontal gene transfer than to meiotic sex. Current Biology, 26(6), 723-732. doi: 10.1016/j.cub.2016.01.031