Nature is complicated and humans often resort to categorization into simplified groups in order to comprehend and manage complex systems. The human mitochondrial genome and its phylogeny are quite complex. Many of those ~16600 base pairs mutated as humans spread across the planet and the resulting phylogeny can be used to illustrate many different aspects of human history and evolution. But it has too many branches and sub-branches to comprehend, which is why major lineages are considered haplogroups. On the highest level, these haplogroups receive capital letters which are then followed by integers and lowercase letters to designate a more fine-scale structure. This nomenclature even inspired semi-fictional literature, such as Bryan Sykes’ “The Seven Daughters of Eve” [1] from 2001 which includes fictional narratives for each of seven “clan mothers” representing seven major European haplogroups (e.g. Helene representing haplogroup H and Tara representing haplogroup T). But apart from categorizing things, humans also like to make exceptions to rules. For instance, not all haplogroup names consist only of letters and numbers but also special characters. And not everything seems logical or intuitive: the deepest split does not include haplogroup A but the most basal lineage is L0. The main letters also do not represent the same level of the tree structure, Sykes’ Katrine representing haplogroup K should not be considered a “daughter of Eve” but (at best) a granddaughter as K is a sub-haplogroup of U (represented by Ursula). This system and the number of haplogroups have not just reached a point where everything has become incredibly complicated despite supposedly simplifying categories. The inherent arbitrariness can also have serious effects on downstream analysis and the interpretation of results depending on how and on what level the authors of a specific study decide to group their individuals. 

This situation of potential biases introduced through the choice of haplogroup groupings is the motivation for the study by Bajić, Schulmann and Nowick who are using the quite fitting term “nomenclutter” in their title [2]. They are raising an important issue in the inconsistencies introduced by the practice of somewhat arbitrary haplotype groupings which varies across studies and has no common standards in place making comparisons between studies virtually impossible. The study shows that the outcome of certain standard analyses and the interpretation of results are very sensitive to the decision on how to group the different haplotypes. This effect is especially pronounced for populations of African ancestry where the haplotype nomenclature would cut the phylogenetic tree at higher levels and the definition of different lineages is generally more coarse than for other populations.

But the authors go beyond pointing out this issue, they also suggest solutions. Instead of grouping sequences by their haplogroup code, one could use “algorithm-based groupings” based on the sequence similarity itself or cutting the phylogenetic tree at a common level of the hierarchy. The analysis of the authors shows that this reduces potential biases substantially. But even such groupings would not be without the influence of the user or researcher’s choices as different parameters have to be set to define the level at which groupings are conducted. The authors propose a neat solution, lifting this issue to be resolved during future updates of the mitochondrial haplogroup nomenclature and the phylogeny. Ideally, the research community could agree on centrally defined haplogroup grouping levels (called “macro-”, “meso-”, and “micro-haplogroups” by the authors) which would all represent different scales of events in human history (from global, continental to local). Classifications like that could be provided through central databases and the classifications could be added to commonly used tools for that purpose. If everyone used these groupings, studies would be a lot more comparable and more fine-scale investigations could still resort to the sequences and the tree itself to avoid all grouping.

The experts who reviewed the study have all highlighted its importance of pointing at a very relevant issue. It will take a community effort to improve practices and the current status of this research area. This study provides an important first step and it should be in everyone’s interest to resolve the “nomenclutter”.

References

1. Sykes B. (2001) The seven daughters of Eve: the science that reveals our genetic ancestry. 1st American ed. New York: Norton.

2. Bajić V, Schulmann VH, Nowick K. (2024) mtDNA “Nomenclutter” and its Consequences on the Interpretation of Genetic Data. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2023.11.19.567721

Artificial selection experiments are key experiments in evolutionary biology. The demonstration that application of selective pressure across multiple generations results in heritable phenotypic changes is a tangible and reproducible proof of the evolution by natural selection.
Artificial selection experiments are used to evaluate the joint effects of selection on multiple traits, their genetic covariances and differences in responses in different environments. Most studies on artificial selection experiments report and base their analyses on phenotypic changes [1]. More recently, changes in allele frequency and other patterns of molecular genetic diversity have been used to identify genomic locations where selection has had an effect. However, so far the changes in gene expression have not been in the focus of artificial selection experiment studies (see [2] for an example though).
In plants, one of the most famous artificial selection experiments is the Illinois Corn Experiment where maize (Zea mays) is selected for oil and protein content [3], but in addition, similar experiments have been conducted also for other traits in maize. In Saclay divergent selection experiment [4] two maize inbred lines (F252 and MBS847) have been selected for early and late flowering for 13 generations, resulting in two week difference in flowering time.
In ”Transcriptomic response to divergent selection for flowering time in maize reveals convergence and key players of the underlying gene regulatory network ” [5] Maud Tenaillon and her coworkers study the gene expression differences among these two independently selected maize populations. Their experiments cover two years in field conditions and they use samples of shoot apical meristem at three different developmental stages: vegetative, transitioning and reproductive. They use RNA-seq transcriptome level differences and qRT-PCR for gene expression pattern investigation. The work is continuation to earlier genetic and phenotypic studies on the same material [4, 6].
The reviewers and I agree that dataset is unique and its major benefit is that it has been obtained from field conditions similar to those that species may face under natural setting during selection. Their tissue sampling is supported by flowering time phenotypic observations and covers the developmental transition stage, making a good effort to identify key transcriptional and phenotypic changes and their timing affected by selection.
Tenaillon et al. [5] identify more than 2000 genes that are differentially expressed among early and late flowering populations. Expectedly, they are enriched for known flowering time genes. As they point out, differential expression of thousands of genes does not mean that they all were independently affected by selection, but rather that the whole transcriptional network has shifted, possibly due to just few upstream or hub-genes. Also, the year-to-year variation had smaller effect in gene expression compared to developmental stage or genetic background, possibly indicating selection for stability across environmental fluctuation for such an important phenotype as flowering time.
Another noteworthy observation is that they find convergent patterns of transcriptional changes among the two selected lines. 115 genes expression patterns are shifted due to selection in both genetic backgrounds. This convergent pattern can be a result of either selection on standing variation or de novo mutations. The data does not allow testing which process is underlying the observed convergence. However, their results show that this is an interesting future question that can be addressed using genotype and gene expression data from the same ancestral and derived material and possibly their hybrids.

References

[1] Hill, W. G., & Caballero, A. (1992). Artificial selection experiments. Annual Review of Ecology and Systematics, 23(1), 287-310. doi: 10.1146/annurev.es.23.110192.001443
[2] Konczal, M., Babik, W., Radwan, J., Sadowska, E. T., & Koteja, P. (2015). Initial molecular-level response to artificial selection for increased aerobic metabolism occurs primarily through changes in gene expression. Molecular biology and evolution, 32(6), 1461-1473. doi: 10.1093/molbev/msv038
[3] Moose, S. P., Dudley, J. W., & Rocheford, T. R. (2004). Maize selection passes the century mark: a unique resource for 21st century genomics. Trends in plant science, 9(7), 358-364. doi: 10.1016/j.tplants.2004.05.005
[4] Durand, E., Tenaillon, M. I., Ridel, C., Coubriche, D., Jamin, P., Jouanne, S., Ressayre, A., Charcosset, A. and Dillmann, C. (2010). Standing variation and new mutations both contribute to a fast response to selection for flowering time in maize inbreds. BMC evolutionary biology, 10(1), 2. doi: 10.1186/1471-2148-10-2
[5] Tenaillon, M. I., Seddiki, K., Mollion, M., Le Guilloux, M., Marchadier, E., Ressayre, A. and Dillmann C. (2019). Transcriptomic response to divergent selection for flowering time in maize reveals convergence and key players of the underlying gene regulatory network. BioRxiv, 461947 ver. 5 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/461947
[6] Durand, E., Tenaillon, M. I., Raffoux, X., Thépot, S., Falque, M., Jamin, P., Bourgais A., Ressayre, A. and Dillmann, C. (2015). Dearth of polymorphism associated with a sustained response to selection for flowering time in maize. BMC evolutionary biology, 15(1), 103. doi: 10.1186/s12862-015-0382-5

The preprint by Pratlong et al. [1] is a well thought quest for genomic regions involved in local adaptation to depth in a species a red coral living the Mediterranean Sea. It first describes a pattern of structuration and then attempts to find candidate genes involved in local adaptation by contrasting deep with shallow populations. Although the pattern of structuration is clear and meaningful, the candidate genomic regions involved in local adaptation remain to be confirmed. Two external reviewers and myself found this preprint particularly interesting regarding the right-mindedness of the authors in front of the difficulties they encounter during their experiments. The discussions on the pros and cons of the approach are very sound and can be easily exported to a large number of studies that hunt for local adaptation. In this sense, the lessons one can learn by reading this well documented manuscript are certainly valuable for a wide range of evolutionary biologists.
More precisely, the authors RAD-sequenced 6 pairs of 'shallow vs deep' samples located in 3 geographical sea areas (Banyuls, Corsica and Marseilles). They were hoping to detect genes involved in the adaptation to depth, if there were any. They start by assessing the patterns of structuration of the 6 samples using PCA and AMOVA [2] and also applied the STRUCTURE [3] assignment software. They show clearly that the samples were mostly differentiated between geographical areas and that only 1 out the 3 areas shows a pattern of isolation by depth (i.e. Marseille). They nevertheless went on and scanned for variants that are highly differentiated in the deep samples when compared to the shallow paired samples in Marseilles, using an Fst outliers approach [4] implemented in the BayeScEnv software [5]. No clear functional signal was in the end detected among the highly differentiated SNPs, leaving a list of candidates begging for complementary data.
The scan for local adaptation using signatures of highly divergent regions is a classical problem of population genetics. It has been applied on many species with various degrees of success. This study is a beautiful example of a well-designed study that did not give full satisfactory answers. Readers will especially appreciate the honesty and the in-depth discussions of the authors while exposing their results and their conclusions step by step.

References

[1] Pratlong, M., Haguenauer, A., Brener, K., Mitta, G., Toulza, E., Garrabou, J., Bensoussan, N., Pontarotti P., & Aurelle, D. (2018). Separate the wheat from the chaff: genomic scan for local adaptation in the red coral Corallium rubrum. bioRxiv, 306456, ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/306456
[2] Excoffier, L., Smouse, P. E. & Quattro, J. M. (1992). Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics, 131(2), 479-491.
[3] Pritchard, J. K., Stephens, M., & Donnelly, P. (2000). Inference of population structure using multilocus genotype data. Genetics, 155(2), 945-959.
[4] Lewontin, R. C., & Krakauer, J. (1973). Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms. Genetics, 74(1), 175-195.
[5] de Villemereuil, P., & Gaggiotti, O. E. (2015). A new FST‐based method to uncover local adaptation using environmental variables. Methods in Ecology and Evolution, 6(11), 1248-1258. doi: 10.1111/2041-210X.12418

Evolution is usually studied via two distinct approaches: by inferring evolutionary processes from relatedness patterns among living species or by observing evolution in action in the laboratory or field. A recent study by Baym and colleagues in Science [1] has now combined these approaches by taking advantage of the pattern left behind by spatially evolving bacterial populations.

Evolution is often considered too slow to see, and can only be inferred by studying patterns of relatedness using phylogenetic trees. Increasingly, however, researchers are moving nature into the lab and watching as evolution unfolds under their noses. The field of experimental evolution follows evolutionary change in the laboratory over 10s to 1000s of generations, yielding insights into bacterial, viral, plant, or fly evolution (among many other species) that are simply not possible in the field. Yet, as powerful as experimental evolution is, it lacks a posterchild. There is no Galapagos finch radiation, nor a stunning series of cichlids to showcase to our students to pique their interests. Let’s face it, E. coli is no stickleback! And while practitioners of experimental evolution can explain the virtues of examining 60,000 generations of bacterial evolution in action, appreciating this nevertheless requires a level of insight and imagination that often eludes students, who need to see “it” to get it.

Enter MEGA, an idea and a film that could become the new face of experimental evolution. It replaces big numbers of generations or images of scientists, with an actual picture of the scientific result. MEGA, or Microbial Evolution and Growth Arena, is essentially an enormous petri dish and is the brainchild of Michael Baym, Tami Leiberman and their colleagues in Roy Kishony’s lab at Technion Israel Institute of Technology and Harvard Medical School. The idea of MEGA is to allow bacteria to swim over a spatially defined landscape while adapting to the local conditions, in this case antibiotics. When bacteria are inoculated onto one end of the plate they consume resources while swarming forward from the plate edge. In a few days, the bacteria grow into an area with antibiotics to which they are susceptible. This stops growth until a mutation arises that permits the bacteria to jump this hurdle, after which growth proceeds until the next hurdle of a 10-fold higher antibiotic concentration, and so on. By this simple approach, Baym et al. [1] evolved E. coli that were nearly 105-fold more resistant to two different antibiotics in just over 10 days. In addition, they identified the mutations that were required for these changes, showed that mutations conferring smaller benefits were required before bacteria could evolve maximal resistance, observed changes to the mutation rate, and demonstrated the importance of spatial structure in constraining adaptation.

For one thing, the rate of resistance evolution is impressive, and also quite scary given the mounting threat of antibiotic-resistant pathogens. However, MEGA also offers a uniquely visual insight into evolutionary change. By taking successive images of the MEGA plate, the group was able to watch the bacteria move, get trapped because of their susceptibility to the antibiotic, and then get past these traps as new mutations emerged that increased resistance. Each transition showcases evolution in real time. In addition, by leaving a spatial pattern of evolutionary steps behind, the MEGA plate offers unique opportunities to thoroughly investigate these steps when the experiment is finished. For instance, subsequent steps in mutational pathways can be characterized, but also their effects on fitness can be quantified in situ by measuring changes in survival and reproduction. This new method is undoubtedly a boon to the field of experimental evolution and offers endless opportunities for experimental elaboration. Perhaps of equal importance, MEGA is a tool that is portable to the classroom and to the public at large. Don’t believe in evolution? Watch this. You only have time for a short internship or lab practical? No problem. Don’t worry much about antibiotic resistance? Check this out. Like the best experimental tools, MEGA is simple but allows for complicated insights. And even if it is less charismatic than a finch, it still allows for the kinds of “gee-whiz” insights that will get students hooked on evolutionary biology.

Reference

[1] Baym M, Lieberman TD, Kelsic ED, Chait R, Gross R, Yelin I, Kishony R. 2016. Spatiotemporal microbial evolution on antibiotic landscapes. Science 353:1147-1151. doi: 10.1126/science.aag0822

Despite a vast array of ways in which organisms can reproduce (Bell, 1982), most animals engage in sexual reproduction (Otto & Lenormand, 2002). A fascinating alternative to sex is parthenogenesis, where offspring are produced asexually from a gamete, typically the egg, without receiving genetic material from another gamete (Simon, Delmotte, Rispe, & Crease, 2003). One of the long-standing questions in the field is why parthenogenesis is not more widespread, given the costs associated with sex (Otto & Lenormand, 2002).  Natural populations of most species appear to be reproducing either sexually or parthenogenetically, even if a species can employ both reproductive modes (Larose et al 2023). Larose et al (2023) highlight the conundrum in this pattern, as organisms that are capable of employing parthenogenesis facultatively would be able to gain the benefits of both modes of reproduction. Why then, is facultative parthenogenesis not more common?

Larose et al (2023) propose that constraints on being efficient in both sexual and asexual reproduction could cause a trade-off between reproductive modes that favours an obligate strategy of either sex or no sex. This would provide an explanation for why facultative parthenogenesis is rare. Timema stick insects provide an excellent system to investigate reproductive strategies, as some species have parthenogenetic females, while other species are sexual, and they show repeated transitions from sexual reproduction to obligate parthenogenesis (Schwander & Crespi, 2009). The authors performed comprehensive and complementary studies in a recently discovered species T. douglasi, in which populations show both modes of reproduction, with some populations consisting only of females and others showing equal proportions of males and females. The sex ratio varied significantly, with the proportion of females ranging between 43-100% across 29 populations. These populations form a monophyletic clade with clustering into three genetic lineages and only a few cases of admixture. Females from all populations were capable of producing unfertilized eggs, but the hatching success varied hugely among populations and lineages (3-100%). Parthenogenetically produced offspring were homozygous, showing that parthenogenesis causes a complete loss of heterozygosity in a single generation. After producing eggs as virgins, females were mated to assess the capacity to also reproduce sexually, and fertilization increased the hatching success of eggs in two lineages. In one lineage, in which the hatching success of unfertilized eggs is similar to that of other sexually reproducing Timema species, fertilization reduced egg-hatching success, indicating a trade-off between reproductive modes with parthenogenetic reproduction performing best. Approximately 58% of the offspring produced after mating were fertilized, demonstrating the capacity of females to reproduce parthenogenetically also after mating has occurred, however with huge variation among individuals.

This wonderful and meticulously performed study produces strong and complementary evidence for facultative parthenogenesis in T. douglasi populations. The study shows large variation in how reproductive mode is employed, supporting the existence of a trade-off between sexual and parthenogenetic reproduction. This might be an example of an ongoing transition from sexual to asexual reproduction, which indicates that obligate parthenogenesis may derive via transient facultative parthenogenesis. 

REFERENCES

Bell, G. (1982) The Masterpiece of Nature: The Evolution and Genetics of Sexuality. University of California Press. 635 p.

Otto, S. P., & Lenormand, T. (2002). Resolving the paradox of sex and recombination. Nature Reviews Genetics, 3(4), 252-261. https://doi.org/10.1038/nrg761

Schwander, T., & Crespi, B. J. (2009). Multiple direct transitions from sexual reproduction to apomictic parthenogenesis in Timema stick insects. Evolution, 63(1), 84-103. 
https://doi.org/10.1111/j.1558-5646.2008.00524.x

Simon, J.-C., Delmotte, F., Rispe, C., & Crease, T. (2003). Phylogenetic relationships between parthenogens and their sexual relatives: the possible routes to parthenogenesis in animals. Biological Journal of the Linnean Society, 79(1), 151-163. https://doi.org/10.1046/j.1095-8312.2003.00175.x

Larose, C., Lavanchy,  G., Freitas, S., Parker, D.J., Schwander, T. (2023) Facultative parthenogenesis: a transient state in transitions between sex and obligate asexuality in stick insects? bioRxiv, 2022.03.25.485836, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.03.25.485836