Spatial genetic structure, i.e. the non-random spatial distribution of genotypes, arises in populations because of different processes including spatially limited dispersal and selection. Knowledge on the spatial genetic structure of plant populations is important to assess biological parameters such as gene dispersal distances and the potential for local adaptations, as well as for applications in conservation management and breeding. In their work, Niskanen and colleagues demonstrate a multifaceted approach to characterise the spatial genetic structure in two replicate sites of a continuously distributed Scots pine population in South-Eastern Finland. They mapped and assessed the ages of 469 naturally regenerated adults and genotyped them using a SNP array which resulted in 157 325 filtered polymorphic SNPs. Their dataset is remarkably powerful because of the large numbers of both individuals and SNPs genotyped. This made it possible to characterise precisely the decay of genetic relatedness between individuals with spatial distance despite the extensive dispersal capacity of Scots pine through pollen, and ensuing expectations of an almost panmictic population.

The authors’ data analysis was particularly thorough. They demonstrated that two metrics of pairwise relatedness, the genomic relationship matrix (GRM, Yang et al. 2011) and the kinship coefficient (Loiselle et al. 1995) were strongly correlated and produced very similar inference of family relationships: >99% of pairs of individuals were unrelated, and the remainder exhibited 2nd (e.g., half-siblings) to 4th degree relatedness. Pairwise relatedness decayed with spatial distance which resulted in extremely weak but statistically significant spatial genetic structure in both sites, quantified as Sp=0.0005 and Sp=0.0008. These estimates are at least an order of magnitude lower than estimates in the literature obtained in more fragmented populations of the same species or in other conifers. Estimates of the neighbourhood size, the effective number of potentially mating individuals belonging to a within-population neighbourhood (Wright 1946), were relatively large with Nb=1680-3210 despite relatively short gene dispersal distances, σg = 36.5–71.3m, which illustrates the high effective density of the population. 

The authors showed the implications of their findings for selection. The capacity for local adaptation depends on dispersal distances and the strength of the selection coefficient. In the study population, the authors inferred that local adaptation can only occur if environmental heterogeneity occurs over a distance larger than approximately one kilometre (or larger, if considering long-distance dispersal). Interestingly, in Scots pine, no local adaptation has been described on similar geographic scales, in contrast to some other European or Mediterranean conifers (Scotti et al. 2023).

The authors’ results are relevant for the management of conservation and breeding. They showed that related individuals occurred within sites only and that they shared a higher number of rare alleles than unrelated ones. Since rare alleles are enriched in new and recessive deleterious variants, selecting related individuals could have negative consequences in breeding programmes. The authors also showed, in their response to reviewers, that their powerful dataset was not suitable to obtain a robust estimate of effective population size, Ne, based on the linkage disequilibrium method (Do et al. 2014). This illustrated that the estimation of Ne used for genetic indicators supported in international conservation policy (Hoban et al. 2020, CBD 2022) remains challenging in large and continuous populations (see also Santo-del-Blanco et al. 2023, Gargiulo et al. 2024).

References

CBD (2022) Kunming-Montreal Global Biodiversity Framework. https://www.cbd.int/doc/decisions/cop-15/cop-15-dec-04-en.pdf

Do C, Waples RS, Peel D, Macbeth GM, Tillett BJ, Ovenden JR (2014). NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne ) from genetic data. Molecular Ecology Resources 14: 209–214. https://doi.org/10.1111/1755-0998.12157

Gargiulo R, Decroocq V, González-Martínez SC, Paz-Vinas I, Aury JM, Kupin IL, Plomion C, Schmitt S, Scotti I, Heuertz M (2024) Estimation of contemporary effective population size in plant populations: limitations of genomic datasets. Evolutionary Applications, in press, https://doi.org/10.1101/2023.07.18.549323

Hoban S, Bruford M, D’Urban Jackson J, Lopes-Fernandes M, Heuertz M, Hohenlohe PA, Paz-Vinas I, et al. (2020) Genetic diversity targets and indicators in the CBD post-2020 Global Biodiversity Framework must be improved. Biological Conservation 248: 108654. https://doi.org/10.1016/j.biocon.2020.108654

Loiselle BA, Sork VL, Nason J & Graham C (1995) Spatial genetic structure of a tropical understorey shrub, Psychotria officinalis (Rubiaceae). American Journal of Botany 82: 1420–1425. https://doi.org/10.1002/j.1537-2197.1995.tb12679.x

Santos-del-Blanco L, Olsson S, Budde KB, Grivet D, González-Martínez SC, Alía R, Robledo-Arnuncio JJ (2022). On the feasibility of estimating contemporary effective population size (Ne) for genetic conservation and monitoring of forest trees. Biological Conservation 273: 109704. https://doi.org/10.1016/j.biocon.2022.109704

Scotti I, Lalagüe H, Oddou-Muratorio S, Scotti-Saintagne C, Ruiz Daniels R, Grivet D, et al. (2023) Common microgeographical selection patterns revealed in four European conifers. Molecular Ecology 32: 393-411. https://doi.org/10.1111/mec.16750

Wright S (1946) Isolation by distance under diverse systems of mating. Genetics 31: 39–59. https://doi.org/10.1093/genetics/31.1.39

Yang J, Lee SH, Goddard ME & Visscher PM (2011) GCTA: a tool for genome-wide complex trait analysis. The American Journal of Human Genetics 88: 76–82. https://www.cell.com/ajhg/pdf/S0002-9297(10)00598-7.pdf

How do phenotypic plasticity and adaptive evolution interact in a novel or changing environment? Does evolution by natural selection generally reinforce initially plastic phenotypic responses, or does it instead oppose them? And to what extent does evolution of a trait involve evolution of its plasticity? These questions have lied at the heart of research on phenotypic evolution in heterogeneous environments ever since it was realized that the environment is likely to affect the expression of many (perhaps most) characters of an individual. Importantly, this broad definition of phenotypic plasticity as change in the average phenotype of a given genotype in response to its environment of development (or expression) does not involve any statement about the adaptiveness of the plastic changes. Theory on the evolution of plasticity has devoted much effort to understanding how reaction norm should evolve under different regimes of environmental change in space and time, and depending on genetic constraints on reaction norm shapes. However on an empirically ground, the questions above have mostly been addressed for individual traits, often chosen a priori for their likeliness to exhibit adaptive plasticity, and we still lack more systematic answers. These can be provided by so-called ‘phenomic’ approaches, where a large number of traits are tracked without prior information on their biological or ecological function. A problem is that the number of phenotypic characters that can be measured in an organism is virtually infinite (and to some extent arbitrary), and that scaling issues makes it difficult to compare different sets of traits. Gene-expression levels offer a partial solution to this dilemma, as they can be considered as a very large number of traits (one per typed gene) that can be measured easily and uniformly (fold change in the number of reads in RNAseq). As for any traits, expression levels of different genes may be genetically correlated, to an extent that depends on their regulation mechanism: cis-regulatory sequences that only affect expression of neighboring genes are likely to cause independent gene expression, while more systematic modifiers of expression (e.g. trans-regulators such as transcription factors) may cause correlated genetic responses of the expression of many genes. Huang and Agrawal [1] have studied plasticity and evolution of gene expression level in young larvae of populations of Drosophila melanogaster that have evolved for about 130 generations under either a constant environment (salt or cadmium), or an environment that is heterogeneous in time or space (combining salt and cadmium). They report a wealth of results, of which we summarize the most striking here. First, among genes that (i) were initially highly plastic and (ii) evolved significant divergence in expression levels between constant environment treatments, the evolved divergence is predominantly in the opposite direction to the initial plastic response. This suggests that either plasticity was initially maladaptive, or the selective pressure changed during the evolutionary process (see below). This somewhat unexpected result strikingly mirrors that from a study published last year in Nature [2], where the same pattern was found for responses of guppies to the presence of predators. However, Huang and Agrawal [1] went beyond this study by deciphering the underlying mechanisms in several interesting ways. First, they showed that change in gene expression often occurred at genes close to SNPs with differentiated frequencies across treatments (but not at genes with differentiated SNPs in their coding sequences), suggesting that cis-regulatory sequences are involved. This is also suggested by the fact that changes in gene expression are mostly caused by the increased expression of only one allele at polymorphic loci, and is a first step towards investigating the genetic underpinnings of (co)variation in gene expression levels. Another interesting set of findings concerns evolution of plasticity in treatments with variable environments. To compare the gene-expression plasticity that evolved in these treatments to an expectation, the authors considered that the expression levels in populations maintained for a long time under constant salt or cadmium had reached an optimum. The differences between these expression levels were thus assumed to predict the level of plasticity that should evolve in a heterogeneous environment (with both cadmium and salt) under perfect environmental predictability. The authors showed that plasticity did evolve more in the expected direction in heterogeneous than in constant environments, resulting in better adapted final expression levels across environments. Taken collectively, these results provide an unprecedented set of patterns that are greatly informative on how plasticity and evolution interact in constant versus changing environments. But of course, interpretations in terms of adaptive versus maladaptive plasticity are more challenging, as the authors themselves admit. Even though environmentally determined gene expression is the basic mechanism underlying the phenotypic plasticity of most traits, it is extremely difficult to relate to more integrated phenotypes for which we can understand the selection pressures, especially in multicellular organisms. The authors have recently investigated evolutionary change of quantitative traits in these selected lines, so it might be possible to establish links between reaction norms for macroscopic traits to those for gene expression levels. Such an approach would also involve tracking gene expression throughout life, rather than only in young larvae as done here, thus putting phenotypic complexity back in the picture also for expression levels. Another difficulty is that a plastic response that was originally adaptive may be replaced by an opposite evolutionary response in the long run, without having to invoke initially maladaptive plasticity. For instance, the authors mention the possibility that a generic stress response is initially triggered by cadmium, but is eventually unnecessary and costly after evolution of genetic mechanisms for cadmium detoxification (a case of so-called genetic accommodation). In any case, this study by Huang and Agrawal [1], together with the one by Ghalambor et al. last year [2], reports novel and unexpected results, which are likely to stimulate researchers interested in plasticity and evolution in heterogeneous environments for the years to come.

References

[1] Huang Y, Agrawal AF. 2016. Experimental Evolution of Gene Expression and Plasticity in Alternative Selective Regimes. PLoS Genetics 12:e1006336. doi: 10.1371/journal.pgen.1006336

[2] Ghalambor CK, Hoke KL, Ruell EW, Fischer EK, Reznick DN, Hughes KA. 2015. Non-adaptive plasticity potentiates rapid adaptive evolution of gene expression in nature. Nature 525: 372-375. doi: 10.1038/nature15256

Plants display an amazing diversity of reproductive strategies with and without sex. This diversity is particularly remarkable in flowering plants, as highlighted by Charles Darwin, who wrote several botanical books scrutinizing plant reproduction. One particularly influential work concerned floral variation [1]. Darwin recognized that flowers may present different forms within a single population, with or without sex specialization. The number of species concerned is small, but they display recurrent patterns, which made it possible for Darwin to invoke natural and sexual selection to explain them. Most of early evolutionary theory on the evolution of reproductive strategies was developed in the first half of the 20th century and was based on animals. However, the pioneering work by David Lloyd from the 1970s onwards excited interest in the diversity of plant sexual strategies as models for testing adaptive hypotheses and predicting reproductive outcomes [2]. The sex specialization of individual flowers and plants has since become one of the favorite topics of evolutionary biologists. However, attention has focused mostly on cases related to sex differentiation (dioecy and associated conditions [3]). Separate unisexual flower types on the same plant (monoecy and related cases, rendering the plant functionally hermaphroditic) have been much less studied, apart from their possible role in the evolution of dioecy [4] or their association with particular modes of pollination [5].
Two specific non-mutually exclusive hypotheses on the evolution of separate sexes in flowers (dicliny) have been proposed, both anchored in Lloyd’s views and Darwin’s legacy, with selfing avoidance and optimal limited resource allocation. Intermediate sex separation, in which sex morphs have different combinations of unisexual and hermaphrodite flowers, has been crucial for testing these hypotheses through comparative analyses of optimal conditions in suggested transitions. Again, cases in which floral unisexuality does not lead to sex separation have been studied much less than dioecious plants, at both the microevolutionary and macroevolutionary levels. It is surprising that the increasing availability of plant phylogenies and powerful methods for testing evolutionary transitions and correlations have not led to more studies, even though the frequency of monoecy is probably highest among diclinous species (those with unisexual flowers in any distribution among plants within a population [6]).
The study by Torices et al. [7] aims to fill this gap, offering a different perspective to that provided by Diggle & Miller [8] on the evolution of monoecious conditions. The authors use heads of a number of species of the sunflower family (Asteraceae) to test specifically the effect of resource limitation on the expression of sexual morphs within the head. They make use of the very particular and constant architecture of inflorescences in these species (the flower head or “capitulum”) and the diversity of sexual conditions (hermaphrodite, gynomonoecious, monoecious) and their spatial pattern within the flower head in this plant family to develop an elegant means of testing this hypothesis. Their results are consistent with their expectations on the effect of resource limitation on the head, as determined by patterns of fruit size within the head, assuming that female fecundity is more strongly limited by resource availability than male function.
The authors took on a huge challenge in choosing to study the largest plant family (about 25 thousand species). Their sample was limited to only about a hundred species, but species selection was very careful, to ensure that the range of sex conditions and the available phylogenetic information were adequately represented. The analytical methods are robust and cast no doubt on the reported results. However, I can’t help but wonder what would happen if the antiselfing hypothesis was tested simultaneously. This would require self-incompatibility (SI) data for the species sample, as the presence of SI is usually invoked as a powerful antiselfing mechanism, rendering the unisexuality of flowers unnecessary. However, SI is variable and frequently lost in the sunflower family [9]. I also wonder to what extent the very specific architecture of flower heads imposes an idiosyncratic resource distribution that may have fixed these sexual systems in species and lineages of the family. Although not approached in this study, intraspecific variation seems to be low. It would be very interesting to use similar approaches in other plant groups in which inflorescence architecture is lax and resource distribution may differ. A whole-plant approach might be required, rather than investigations of single inflorescences as in this study. This study has no flaws, but instead paves the way for further testing of a long-standing dual hypothesis, probably with different outcomes in different ecological and evolutionary settings. In the end, sex is not only in the head.

References

[1] Darwin, C. (1877). The different forms of flowers on plants of the same species. John Murray.
[2] Barrett, S. C. H., and Harder, L. D. (2006). David G. Lloyd and the evolution of floral biology: from natural history to strategic analysis. In L.D. Harder, L. D., and Barrett, S. C. H. (eds) Ecology and Evolution of Flowers. OUP, Oxford. Pp 1-21.
[3] Geber, M. A., Dawson, T. E., and Delph, L. F. (eds) (1999). Gender and sexual dimorphism in flowering plants. Springer, Berlin.
[4] Charlesworth, D. (1999). Theories of the evolution of dioecy. In Geber, M. A., Dawson T. E. and Delph L. F. (eds) (1999). Gender and sexual dimorphism in flowering plants. Springer, Berlin. Pp. 33-60.
[5] Friedman, J., and Barrett, S. C. (2008). A phylogenetic analysis of the evolution of wind pollination in the angiosperms. International Journal of Plant Sciences, 169(1), 49-58. doi: 10.1086/523365
[6] Renner, S. S. (2014). The relative and absolute frequencies of angiosperm sexual systems: dioecy, monoecy, gynodioecy, and an updated online database. American Journal of botany, 101(10), 1588-1596. doi: 10.3732/ajb.1400196
[7] Torices, R., Afonso, A., Anderberg, A. A., Gómez, J. M., and Méndez, M. (2019). Architectural traits constrain the evolution of unisexual flowers and sexual segregation within inflorescences: an interspecific approach. bioRxiv, 356147, ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/356147
[8] Diggle, P. K., and Miller, J. S. (2013). Developmental plasticity, genetic assimilation, and the evolutionary diversification of sexual expression in Solanum. American journal of botany, 100(6), 1050-1060. doi: 10.3732/ajb.1200647
[9] Ferrer, M. M., and Good‐Avila, S. V. (2007). Macrophylogenetic analyses of the gain and loss of self‐incompatibility in the Asteraceae. New Phytologist, 173(2), 401-414. doi: 10.1111/j.1469-8137.2006.01905.x

We live both in a worrying and fascinating time. Worrying because human-induced global change has dramatic consequences on biodiversity around the world. Fascinating because these changes enable us to witness evolutionary processes unfolding on relatively short time scales. One such process is biological invasion. An intriguing evolutionary question is to understand which factor facilitates the success of an invasive species. In particular, serial bottlenecks at the expanding front should reduce the effective population size and decrease genetic diversity. Theoretically, this will increase the fixation of deleterious mutations due to the effect of genetic drift and overall affect the evolutionary potential of the invading species. In the short term, reduced genetic diversity and inbreeding in small populations increases the number of recessive deleterious variants exposed in a homozygous state. This may generate a reduction in mean fitness of the population. However, in the long term and under specific demographic scenarios recessive deleterious alleles may be more efficiently removed by purifying selection. Such purging may explain the success of invasion by reducing inbreeding depression and minimizing loss of fitness. Here, Lombaert et al. estimate the genetic load in two invasive insect species, a predator species, the harlequin ladybird (Harmonia axyridis) and a crop pest species, the western corn rootworm (Diabrotica virgifera virgifera). 

The authors smartly took advantage of a pool-seq transcriptome-based exome capture method to estimate genetic load and assess the purge hypothesis using standard population genetic statistics, such as the ratio of nonsynonymous over synonymous expected heterozygosity, the frequency of derived alleles, and their excess or deficit.

The results revealed different patterns in the two species:

In the western corn rootworm, the authors find a clear signal of reduced genetic diversity in invasive populations. This was associated with a slightly reduced genetic load. However, there was only marginal evidence of purging regarding the most deleterious mutations, and in a single population, with moderately deleterious variants being weakly purged, as theoretically expected. 

In the harlequin ladybird, in contrast, the reduction of genetic diversity in invasive populations has been small, a result related to the mild severity of the bottlenecks. In this species, the authors found a tendency toward fixation of the genetic load and no signal of purging. 

Such results are intriguing, showing that different species seem to exhibit contrasted fate of genetic load. Differences in the invasion history and ecology of the species may explain these patterns. This is one of the first studies to use a population genomics approach to study the genetic load associated with biological invasion. Future studies based on whole genome data collected at the individual level across multiple species are needed to better understand the dynamics of genetic load during biological invasion and to draw more general conclusions. Advances in forward simulations may also be used to shed light on the evolution of the genetic load at different stages of the invasion process and under different strengths of bottlenecks.

References

Eric Lombaert, Aurelie Blin, Barbara Porro, Thomas Guillemaud, Julio S Bernal, Gary Chang, Natalia Kirichenko, Thomas W Sappington, Stefan Toepfer, Emeline Deleury (2025) Unraveling genetic load dynamics during biological invasion: insights from two invasive insect species. bioRxiv, ver.3 peer-reviewed and recommended by PCI Evol Biol https://doi.org/10.1101/2024.09.02.610743

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