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29 Sep 2022
![]() How many sirtuin genes are out there? evolution of sirtuin genes in vertebrates with a description of a new family memberJuan C. Opazo, Michael W. Vandewege, Federico G. Hoffmann, Kattina Zavala, Catalina Meléndez, Charlotte Luchsinger, Viviana A. Cavieres, Luis Vargas-Chacoff, Francisco J. Morera, Patricia V. Burgos, Cheril Tapia-Rojas, Gonzalo A. Mardones https://doi.org/10.1101/2020.07.17.209510Making sense of vertebrate sirtuin genesRecommended by Frédéric Delsuc based on reviews by Filipe Castro, Nicolas Leurs and 1 anonymous reviewerSirtuin proteins are class III histone deacetylases that are involved in a variety of fundamental biological functions mostly related to aging. These proteins are located in different subcellular compartments and are associated with different biological functions such as metabolic regulation, stress response, and cell cycle control [1]. In mammals, the sirtuin gene family is composed of seven paralogs (SIRT1-7) grouped into four classes [2]. Due to their involvement in maintaining cell cycle integrity, sirtuins have been studied as a way to understand fundamental mechanisms governing longevity [1]. Indeed, the downregulation of sirtuin genes with aging seems to explain much of the pathophysiology that accumulates with aging [3]. Biomedical studies have thus explored the potential therapeutic implications of sirtuins [4] but whether they can effectively be used as molecular targets for the treatment of human diseases remains to be demonstrated [1]. Despite this biomedical interest and some phylogenetic analyses of sirtuin paralogs mostly conducted in mammals, a comprehensive evolutionary analysis of the sirtuin gene family at the scale of vertebrates was still lacking. In this preprint, Opazo and collaborators [5] took advantage of the increasing availability of whole-genome sequences for species representing all main groups of vertebrates to unravel the evolution of the sirtuin gene family. To do so, they undertook a phylogenomic approach in its original sense aimed at improving functional predictions by evolutionary analysis [6] in order to inventory the full vertebrate sirtuin gene repertoire and reconstruct its precise duplication history. Harvesting genomic databases, they extracted all predicted sirtuin proteins and performed phylogenetic analyses based on probabilistic inference methods. Maximum likelihood and Bayesian analyses resulted in well-resolved and congruent phylogenetic trees dividing vertebrate sirtuin genes into three major clades. These analyses also revealed an additional eighth paralog that was previously overlooked because of its restricted phyletic distribution. This newly identified sirtuin family member (named SIRT8) was recovered with unambiguous statistical support as a sister-group to the SIRT3 clade. Comparative genomic analyses based on conserved gene synteny confirmed that SIRT8 was present in all sampled non-amniote vertebrate genomes (cartilaginous fish, bony fish, coelacanth, lungfish, and amphibians) except cyclostomes. SIRT8 has thus most likely been lost in the last common ancestor of amniotes (mammals, reptiles, and birds). Discovery of such previously unknown genes in vertebrates is not completely surprising given the plethora of high-quality genomes now available. However, this study highlights the importance of considering a broad taxonomic sampling to infer evolutionary patterns of gene families that have been mostly studied in mammals because of their potential importance for human biology. Based on its phylogenetic position as closely related to SIRT3 within class I, it could be predicted that the newly identified SIRT8 paralog likely has a deacetylase activity and is probably located in mitochondria. To test these evolutionary predictions, Opazo and collaborators [5] conducted further bioinformatics analyses and functional experiments using the elephant shark (Callorhinchus milii) as a model species. RNAseq expression data were analyzed to determine tissue-specific transcription of sirtuin genes in vertebrates, including SIRT8 found to be mainly expressed in the ovary, which suggests a potential role in biological processes associated with reproduction. The elephant shark SIRT8 protein sequence was used with other vertebrates for comparative analyses of protein structure modeling and subcellular localization prediction both pointing to a probable mitochondrial localization. The protein localization and its function were further characterized by immunolocalization in transfected cells, and enzymatic and functional assays, which all confirmed the prediction that SIRT8 proteins are targeted to the mitochondria and have deacetylase activity. The extensive experimental efforts made in this study to shed light on the function of this newly discovered gene are both rare and highly commendable. Overall, this work by Opazo and collaborators [5] provides a comprehensive phylogenomic study of the sirtuin gene family in vertebrates based on detailed evolutionary analyses using state-of-the-art phylogenetic reconstruction methods. It also illustrates the power of adopting an integrative comparative approach supplementing the reconstruction of the duplication history of the gene family with complementary functional experiments in order to elucidate the function of the newly discovered SIRT8 family member. These results provide a reference phylogenetic framework for the evolution of sirtuin genes and the further functional characterization of the eight vertebrate paralogs with potential relevance for understanding the cellular biology of aging and its associated diseases in human. References [1] Vassilopoulos A, Fritz KS, Petersen DR, Gius D (2011) The human sirtuin family: Evolutionary divergences and functions. Human Genomics, 5, 485. https://doi.org/10.1186/1479-7364-5-5-485 [2] Yamamoto H, Schoonjans K, Auwerx J (2007) Sirtuin Functions in Health and Disease. Molecular Endocrinology, 21, 1745–1755. https://doi.org/10.1210/me.2007-0079 [3] Morris BJ (2013) Seven sirtuins for seven deadly diseases ofaging. Free Radical Biology and Medicine, 56, 133–171. https://doi.org/10.1016/j.freeradbiomed.2012.10.525 [4] Bordo D Structure and Evolution of Human Sirtuins. Current Drug Targets, 14, 662–665. http://dx.doi.org/10.2174/1389450111314060007 [5] Opazo JC, Vandewege MW, Hoffmann FG, Zavala K, Meléndez C, Luchsinger C, Cavieres VA, Vargas-Chacoff L, Morera FJ, Burgos PV, Tapia-Rojas C, Mardones GA (2022) How many sirtuin genes are out there? evolution of sirtuin genes in vertebrates with a description of a new family member. bioRxiv, 2020.07.17.209510, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2020.07.17.209510 [6] Eisen JA (1998) Phylogenomics: Improving Functional Predictions for Uncharacterized Genes by Evolutionary Analysis. Genome Research, 8, 163–167. https://doi.org/10.1101/gr.8.3.163 | How many sirtuin genes are out there? evolution of sirtuin genes in vertebrates with a description of a new family member | Juan C. Opazo, Michael W. Vandewege, Federico G. Hoffmann, Kattina Zavala, Catalina Meléndez, Charlotte Luchsinger, Viviana A. Cavieres, Luis Vargas-Chacoff, Francisco J. Morera, Patricia V. Burgos, Cheril Tapia-Rojas, Gonzalo A. Mardones | <p style="text-align: justify;">Studying the evolutionary history of gene families is a challenging and exciting task with a wide range of implications. In addition to exploring fundamental questions about the origin and evolution of genes, disent... | ![]() | Molecular Evolution | Frédéric Delsuc | Filipe Castro, Anonymous, Nicolas Leurs | 2022-05-12 16:06:04 | View |
12 Apr 2017
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Genetic drift, purifying selection and vector genotype shape dengue virus intra-host genetic diversity in mosquitoesLequime S, Fontaine A, Gouilh MA, Moltini-Conclois I and Lambrechts L https://doi.org/10.1371/journal.pgen.1006111Vectors as motors (of virus evolution)Recommended by Frédéric Fabre and Benoit MouryMany viruses are transmitted by biological vectors, i.e. organisms that transfer the virus from one host to another. Dengue virus (DENV) is one of them. Dengue is a mosquito-borne viral disease that has rapidly spread around the world since the 1940s. One recent estimate indicates 390 million dengue infections per year [1]. As many arthropod-borne vertebrate viruses, DENV has to cross several anatomical barriers in the vector, to multiply in its body and to invade its salivary glands before getting transmissible. As a consequence, vectors are not passive carriers but genuine hosts of the viruses that potentially have important effects on the composition of virus populations and, ultimately, on virus epidemiology and virulence. Within infected vectors, virus populations are expected to acquire new mutations and to undergo genetic drift and selection effects. However, the intensity of these evolutionary forces and the way they shape virus genetic diversity are poorly known. In their study, Lequime et al. [2] finely disentangled the effects of genetic drift and selection on DENV populations during their infectious cycle within mosquito (Aedes aegypti) vectors. They evidenced that the genetic diversity of viruses within their vectors is shaped by genetic drift, selection and vector genotype. The experimental design consisted in artificial acquisition of purified virus by mosquitoes during a blood meal. The authors monitored the diversity of DENV populations in Ae. aegypti individuals at different time points by high-throughput sequencing (HTS). They estimated the intensity of genetic drift and selection effects exerted on virus populations by comparing the DENV diversity at these sampling time points with the diversity in the purified virus stock (inoculum). Disentangling the effects of genetic drift and selection remains a methodological challenge because both evolutionary forces operate concomitantly and both reduce genetic diversity. However, selection reduces diversity in a reproducible manner among experimental replicates (here, mosquito individuals): the fittest variants are favoured at the expense of the weakest ones. In contrast, genetic drift reduces diversity in a stochastic manner among replicates. Genetic drift acts equally on all variants irrespectively of their fitness. The strength of genetic drift is frequently evaluated with the effective population size Ne: the lower Ne, the stronger the genetic drift [3]. The estimation of the effective population size of DENV populations by Lequime et al. [2] was based on single-nucleotide polymorphisms (SNPs) that were (i) present both in the inoculum and in the virus populations sampled at the different time points and (ii) that were neutral (or nearly-neutral) and therefore subjected to genetic drift only and insensitive to selection. As expected for viruses that possess small and constrained genomes, such neutral SNPs are extremely rare. Starting from a set of >1800 SNPs across the DENV genome, only three SNPs complied with the neutrality criteria and were enough represented in the sequence dataset for a precise Ne estimation. Using the method described by Monsion et al. [4], Lequime et al. [2] estimated Ne values ranging from 5 to 42 viral genomes (95% confidence intervals ranged from 2 to 161 founding viral genomes). Consequently, narrow bottlenecks occurred at the virus acquisition step, since the blood meal had allowed the ingestion of ca. 3000 infectious virus particles, on average. Interestingly, bottleneck sizes did not differ between mosquito genotypes. Monsion et al.’s [4] formula provides only an approximation of Ne. A corrected formula has been recently published [5]. We applied this exact Ne formula to the means and variances of the frequencies of the three neutral markers estimated before and after the bottlenecks (Table 1 in [2]), and nearly identical Ne estimates were obtained with both formulas. Selection intensity was estimated from the dN/dS ratio between the nonsynonymous and synonymous substitution rates using the HTS data on DENV populations. DENV genetic diversity increased following initial infection but was restricted by strong purifying selection during virus expansion in the midgut. Again, no differences were detected between mosquito genotypes. However and importantly, significant differences in DENV genetic diversity were detected among mosquito genotypes. As they could not be related to differences in initial genetic drift or to selection intensity, the authors raise interesting alternative hypotheses, including varying rates of de novo mutations due to differences in replicase fidelity or differences in the balancing selection regime. Interestingly, they also suggest that this observation could simply result from a methodological issue linked to the detection threshold of low-frequency SNPs. References [1] Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, Drake JM, et al. 2013. The global distribution and burden of dengue. Nature 496: 504–7 doi: 10.1038/nature12060 [2] Lequime S, Fontaine A, Gouilh MA, Moltini-Conclois I and Lambrechts L. 2016. Genetic drift, purifying selection and vector genotype shape dengue virus intra-host genetic diversity in mosquitoes. PloS Genetics 12: e1006111 doi: 10.1371/journal.pgen.1006111 [3] Charlesworth B. 2009. Effective population size and patterns of molecular evolution and variation. Nature Reviews Genetics 10: 195-205 doi: 10.1038/nrg2526 [4] Monsion B, Froissart R, Michalakis Y and Blanc S. 2008. Large bottleneck size in cauliflower mosaic virus populations during host plant colonization. PloS Pathogens 4: e1000174 doi: 10.1371/journal.ppat.1000174 [5] Thébaud G and Michalakis Y. 2016. Comment on ‘Large bottleneck size in cauliflower mosaic virus populations during host plant colonization’ by Monsion et al. (2008). PloS Pathogens 12: e1005512 doi: 10.1371/journal.ppat.1005512 | Genetic drift, purifying selection and vector genotype shape dengue virus intra-host genetic diversity in mosquitoes | Lequime S, Fontaine A, Gouilh MA, Moltini-Conclois I and Lambrechts L | <p>Due to their error-prone replication, RNA viruses typically exist as a diverse population of closely related genomes, which is considered critical for their fitness and adaptive potential. Intra-host demographic fluctuations that stochastically... | ![]() | Evolutionary Dynamics, Molecular Evolution, Population Genetics / Genomics | Frédéric Fabre | 2017-04-10 14:26:04 | View | |
09 Dec 2019
![]() Trait-specific trade-offs prevent niche expansion in two parasitesEva JP Lievens, Yannis Michalakis, Thomas Lenormand https://doi.org/10.1101/621581Trade-offs in fitness components and ecological source-sink dynamics affect host specialisation in two parasites of Artemia shrimpsRecommended by Frédéric GuillaumeEcological specialisation, especially among parasites infecting a set of host species, is ubiquitous in nature. Host specialisation can be understood as resulting from trade-offs in parasite infectivity, virulence and growth. However, it is not well understood how variation in these trade-offs shapes the overall fitness trade-off a parasite faces when adapting to multiple hosts. For instance, it is not clear whether a strong trade-off in one fitness component may sufficiently constrain the evolution of a generalist parasite despite weak trade-offs in other components. A second mechanism explaining variation in specialisation among species is habitat availability and quality. Rare habitats or habitats that act as ecological sinks will not allow a species to persist and adapt, preventing a generalist phenotype to evolve. Understanding the prevalence of those mechanisms in natural systems is crucial to understand the emergence and maintenance of host specialisation, and biodiversity in general. In their study "Trait-specific trade-offs prevent niche expansion in two parasites", Lievens *et al.* [1] report the results of an evolution experiment involving two parasitic microsporidians, *Anostracospora rigaudi* and *Enterocytospora artemiae*, infecting two sympatric species of brine shrimp, *Artemia franciscana* and *Artemia parthenogenetica*. The two parasites were originally specialised on their primary host: *A. rigaudi* on *A. parthenogenetica* and *E. artemiae* on *A. franciscana*, although they encounter both species in the wild but at different rates. After passaging each parasite on each single host and on both hosts alternatively, Lievens *et al.* asked how host specialisation evolved. They found no change in specialisation at the fitness level in *A. rigaudi* in either treatment, while *E. artemiae* became more of a generalist after having been exposed to its secondary host, *A. parthenogenetica*. The most interesting part of the study is the decomposition of the fitness trade-off into its underlying trade-offs in spore production, infectivity and virulence. Both species remained specialised for spore production on their primary host, interpreted as caused by a strong trade-off between hosts preventing improvements on the secondary host. *A. rigaudi* evolved reduced virulence on its primary host without changes in the overall fitness trad-off, while *E. artemiae* evolved higher infectivity on its secondary host making it a more generalist parasite and revealing a weak trade-off for this trait and for fitness. Nevertheless, both parasites retained higher fitness on their primary host because of the lack of an evolutionary response in spore production. This study made two important points. First, it showed that despite apparent strong trade-off in spore production, a weak trade-off in infectivity allowed *E. artemiae* to become less specialised. In contrast, *A. rigaudi* remained specialised, presumably because the strong trade-off in spore production was the overriding factor. The fitness trade-off that results from the superposition of multiple underlying trade-offs is thus difficult to predict, yet crucial to understand potential evolutionary outcomes. A second insight is related to the ecological context of the evolution of specialisation. The results showed that *E. artemiae* should be less specialised than observed, which points to a role played by source-sink dynamics on *A. parthenogenetica* in the wild. The experimental approach of Lievens *et al.* thus allowed them to nicely disentangle the various sources of constraints on the evolution of host adaptation in the *Artemia* system. **References** [1] Lievens, E.J.P., Michalakis, Y. and Lenormand, T. (2019). Trait-specific trade-offs prevent niche expansion in two parasites. bioRxiv, 621581, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: [10.1101/621581](https://dx.doi.org/10.1101/621581) | Trait-specific trade-offs prevent niche expansion in two parasites | Eva JP Lievens, Yannis Michalakis, Thomas Lenormand | <p>The evolution of host specialization has been studied intensively, yet it is still often difficult to determine why parasites do not evolve broader niches – in particular when the available hosts are closely related and ecologically similar. He... | ![]() | Adaptation, Evolutionary Ecology, Evolutionary Epidemiology, Experimental Evolution, Life History, Species interactions | Frédéric Guillaume | 2019-05-13 13:44:34 | View | |
31 Mar 2022
![]() Gene network robustness as a multivariate characterArnaud Le Rouzic https://doi.org/10.48550/arXiv.2101.01564Genetic and environmental robustness are distinct yet correlated evolvable traits in a gene networkRecommended by Frédéric GuillaumeOrganisms often show robustness to genetic or environmental perturbations. Whether these two components of robustness can evolve separately is the focus of the paper by Le Rouzic [1]. Using theoretical analysis and individual-based computer simulations of a gene regulatory network model, he shows that multiple aspects of robustness can be investigated as a set of pleiotropically linked quantitative traits. While genetically correlated, various robustness components (e.g., mutational, developmental, homeostasis) of gene expression in the regulatory network evolved more or less independently from each other under directional selection. The quantitative approach of Le Rouzic could explain both how unselected robustness components can respond to selection on other components and why various robustness-related features seem to have their own evolutionary history. Moreover, he shows that all components were evolvable, but not all to the same extent. Robustness to environmental disturbances and gene expression stability showed the largest responses while increased robustness to genetic disturbances was slower. Interestingly, all components were positively correlated and remained so after selection for increased or decreased robustness. This study is an important contribution to the discussion of the evolution of robustness in biological systems. While it has long been recognized that organisms possess the ability to buffer genetic and environmental perturbations to maintain homeostasis (e.g., canalization [2]), the genetic basis and evolutionary routes to robustness and canalization are still not well understood. Models of regulatory gene networks have often been used to address aspects of robustness evolution (e.g., [3]). Le Rouzic [1] used a gene regulatory network model derived from Wagner’s model [4]. The model has as end product the expression level of a set of genes influenced by a set of regulatory elements (e.g., transcription factors). The level and stability of expression are a property of the regulatory interactions in the network. Le Rouzic made an important contribution to the study of such gene regulation models by using a quantitative genetics approach to the evolution of robustness. He crafted a way to assess the mutational variability and selection response of the components of robustness he was interested in. Le Rouzic’s approach opens avenues to investigate further aspects of gene network evolutionary properties, for instance to understand the evolution of phenotypic plasticity. Le Rouzic also discusses ways to measure his different robustness components in empirical studies. As the model is about gene expression levels at a set of protein-coding genes influenced by a set of regulatory elements, it naturally points to the possibility of using RNA sequencing to measure the variation of gene expression in know gene networks and assess their robustness. Robustness could then be studied as a multidimensional quantitative trait in an experimental setting. References [1] Le Rouzic, A (2022) Gene network robustness as a multivariate character. arXiv: 2101.01564, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://arxiv.org/abs/2101.01564 [2] Waddington CH (1942) Canalization of Development and the Inheritance of Acquired Characters. Nature, 150, 563–565. https://doi.org/10.1038/150563a0 [3] Draghi J, Whitlock M (2015) Robustness to noise in gene expression evolves despite epistatic constraints in a model of gene networks. Evolution, 69, 2345–2358. https://doi.org/10.1111/evo.12732 [4] Wagner A (1994) Evolution of gene networks by gene duplications: a mathematical model and its implications on genome organization. Proceedings of the National Academy of Sciences, 91, 4387–4391. https://doi.org/10.1073/pnas.91.10.4387 | Gene network robustness as a multivariate character | Arnaud Le Rouzic | <p style="text-align: justify;">Robustness to genetic or environmental disturbances is often considered as a key property of living systems. Yet, in spite of being discussed since the 1950s, how robustness emerges from the complexity of genetic ar... | ![]() | Bioinformatics & Computational Biology, Evolutionary Theory, Genotype-Phenotype, Quantitative Genetics | Frédéric Guillaume | Charles Mullon, Charles Rocabert, Diogo Melo | 2021-01-11 17:48:20 | View |
20 Nov 2023
Phenotypic stasis with genetic divergenceFrançois Mallard, Luke Noble, Thiago Guzella, Bruno Afonso, Charles F. Baer, Henrique Teotónio https://doi.org/10.1101/2022.05.28.493856Phenotypic stasis despite genetic divergence and differentiation in Caenorhabditis elegans.Recommended by Frédéric GuillaumeExplaining long periods of evolutionary stasis, the absence of change in trait means over geological times, despite the existence of abundant genetic variation in most traits has challenged evolutionary theory since Darwin's theory of evolution by gradual modification (Estes & Arnold 2007). Stasis observed in contemporary populations is even more daunting since ample genetic variation is usually coupled with the detection of selection differentials (Kruuk et al. 2002, Morrissey et al. 2010). Moreover, rapid adaptation to environmental changes in contemporary populations, fuelled by standing genetic variation provides evidence that populations can quickly respond to an adaptive challenge. Explanations for evolutionary stasis usually invoke stabilizing selection as a main actor, whereby optimal trait values remain roughly constant over long periods of time despite small-scale environmental fluctuations. Genetic correlation among traits may also play a significant role in constraining evolutionary changes over long timescales (Schluter 1996). Yet, genetic constraints are rarely so strong as to completely annihilate genetic changes, and they may evolve. Patterns of genetic correlations among traits, as captured in estimates of the G-matrix of additive genetic co-variation, are subject to changes over generations under the action of drift, migration, or selection, among other causes (Arnold et al. 2008). Therefore, under the assumption of stabilizing selection on a set of traits, phenotypic stasis and genetic divergence in patterns of trait correlations may both be observed when selection on trait correlations is weak relative to its effect on trait means. Mallard et al. (2023) set out to test whether selection or drift may explain the divergence in genetic correlation among traits in experimental lines of the nematode Caenorhabditis elegans and whether stabilizing selection may be a driver of phenotypic stasis. To do so, they analyzed the evolution of locomotion behavior traits over 100 generations of lab evolution in a constant and homogeneous environment after 140 generations of domestication from a largely differentiated set of founder populations. The locomotion traits were transition rates between movement states and direction (still, forward or backward movement). They could estimate the traits' broad-sense G-matrix in three populations at two generations (50 and 100), and in the ancestral mixed population. Similarly, they estimated the shape of the selection surface by regressing locomotion behavior on fertility. Armed with both G-matrix and surface estimates, they could test whether the G's orientation matched selection's orientation and whether changes in G were constrained by selection. They found stasis in trait mean over 100 generations but divergence in the amount and orientation of the genetic variation of the traits relative to the ancestral population. The selected populations changed orientation of their G-matrices and lost genetic variation during the experiment in agreement with a model of genetic drift on quantitative traits. Their estimates of selection also point to mostly stabilizing selection on trait combinations with weak evidence of disruptive selection, suggesting a saddle-shaped selection surface. The evolutionary responses of the experimental populations were mostly consistent with small differentiation in the shape of G-matrices during the 100 generations of stabilizing selection. Mallard et al. (2023) conclude that phenotypic stasis was maintained by stabilizing selection and drift in their experiment. They argue that their findings are consistent with a "table-top mountain" model of stabilizing selection, whereby the population is allowed some wiggle room around the trait optimum, leaving space for random fluctuations of trait variation, and especially trait co-variation. The model is an interesting solution that might explain how stasis can be maintained over contemporary times while allowing for random differentiation of trait genetic co-variation. Whether such differentiation can then lead to future evolutionary divergence once replicated populations adapt to a new environment is an interesting idea to follow. References Arnold, S. J., Bürger, R., Hohenlohe, P. A., Ajie, B. C. and Jones, A. G. 2008. Understanding the evolution and stability of the G-matrix. Evolution 62(10): 2451-2461. | Phenotypic stasis with genetic divergence | François Mallard, Luke Noble, Thiago Guzella, Bruno Afonso, Charles F. Baer, Henrique Teotónio | <p style="text-align: justify;">Whether or not genetic divergence in the short-term of tens to hundreds of generations is compatible with phenotypic stasis remains a relatively unexplored problem. We evolved predominantly outcrossing, genetically ... | Adaptation, Behavior & Social Evolution, Experimental Evolution, Quantitative Genetics | Frédéric Guillaume | 2022-09-01 14:32:53 | View | ||
24 Mar 2025
![]() On the potential for GWAS with phenotypic population means and allele-frequency data (popGWAS)Markus Pfenninger https://doi.org/10.1101/2024.06.12.598621popGWAS: Data-efficient trait mapping in natural populations for biodiversity researchRecommended by Frédéric GuillaumeThe study by Pfenninger (2025) addresses the critical need to understand the genomic basis of ecologically important traits to better predict and respond to the impacts of global change on biodiversity (Gienapp et al. 2017). It introduces the popGWAS, a novel GWAS approach, which utilizes phenotypic population means and genome-wide allele frequency data, obtainable through methods like Pool-sequencing (Pool-Seq), to identify the genetic loci underlying quantitative polygenic traits in natural populations and predict their mean. The core idea is that trait-increasing alleles should exhibit higher frequencies in populations with higher mean trait values. popGWAS then maps mean allele frequencies across populations to their trait means. Working with as many allele frequency values as populations sampled, popGWAS potentially has more power to find significant associations at genomic loci than individual-based GWAS working with three genotypes at a locus. This new method addresses some of the problems faced by traditional genome-wide association studies (GWAS), which require extensive resources and large sample sizes, posing challenges for biodiversity research on non-model species in natural populations. To evaluate the effectiveness of popGWAS, Pfenninger (2025) conducted extensive population genetic forward simulations, examining scenarios with varying numbers of populations, ranging from 12 to 60. The results indicated that popGWAS performance improved with increasing sample size, showing a diminishing return above 36 populations. In a direct comparison across all simulation scenarios, popGWAS consistently outperformed individual-based GWAS (iGWAS). On average, popGWAS identified more true positive loci than iGWAS. In addition, when combined with minimum entropy feature selection (MEFS), popGWAS achieved large predictive accuracy of population means of 0.8 or better in over 97% of simulations with 36 or more populations, regardless of other parameters. In contrast, iGWAS failed to generate valid phenotypic predictions in over 70% of the simulations. Also, unlike iGWAS, popGWAS did not suffer from p-value inflation. Yet, population structure or varying levels of relatedness among individuals were not fully accounted for in the simulations. The extent to which popGWAS would be sensitive to such individual covariates remains to be shown. Finally, popGWAS was relatively insensitive to low trait heritability because random individual variation gets averaged out when calculating the population mean trait value. The study demonstrates that popGWAS is a promising approach, particularly for oligogenic and moderately polygenic traits. The method performs more poorly for polygenic traits with large genetic redundancy, where different alleles contribute to the same trait mean in different populations. The method thus performs better when large-effect loci contribute to genetic differentiation in parallel across populations, as expected when gene flow is moderate to high (Yeaman & Whitlock 2011). Low genomic predictability is reached when drift dominates or when genetic architectures are highly polygenic. The popGWAS method proved effective with a moderate number of sampled populations and, when combined with machine learning for genomic prediction, exhibited strong performance in predicting population means, even for low-heritability traits. Notably, popGWAS consistently outperformed iGWAS in terms of identifying true positive loci and prediction accuracy. This suggests that popGWAS can make GWAS studies more accessible for biodiversity genomics research, providing a valuable tool for dissecting the genetic basis of complex traits in natural populations. A key aspect contributing to the efficiency of popGWAS is its compatibility with pooled sequencing (Pool-Seq). Pool-Seq provides estimates of allele frequencies within a population by sequencing a mixed DNA sample representing multiple individuals from that population (Futschik & Schlötterer 2010). This approach is significantly more cost-effective than sequencing each individual separately, allowing researchers to obtain genome-wide allele frequency data across multiple populations with a substantially reduced budget. This data efficiency makes GWAS more accessible to a wider range of researchers, particularly those working in biodiversity genomics where financial resources may be limited. Furthermore, popGWAS can be coupled with bulk phenotyping methods, such as automatic video recording, remote sensing, metabolomics/transcriptomics, etc., to efficiently obtain population-level phenotypic data, further streamlining the research process. Ultimately, popGWAS represents a valuable addition to the geneticist's toolkit, offering a complementary approach to iGWAS that can be particularly advantageous in specific research contexts where predicting trait mean is more important than resolving the precise genetic basis of a trait.
References Futschik, A. and Schlötterer, C. 2010. The Next Generation of Molecular Markers From Massively Parallel Sequencing of Pooled DNA Samples. Genetics 186(1): 207-218. https://doi.org/10.1534/genetics.110.114397 Gienapp, P., Fior, S., Guillaume, F., Lasky, J. R., Sork, V. L. and Csilléry, K. 2017. Genomic Quantitative Genetics to Study Evolution in the Wild. Trends Ecol. Evol. 32(12): 897-908. https://doi.org/10.1016/j.tree.2017.09.004 Markus Pfenninger (2025) On the potential for GWAS with phenotypic population means and allele-frequency data (popGWAS). bioRxiv, ver.3 peer-reviewed and recommended by PCI Evol Biol https://doi.org/10.1101/2024.06.12.598621 Yeaman, S. and Whitlock, M. C. 2011. The genetic architecture of adaptation under migration-selection balance. Evolution 65(7): 1897-1911. https://doi.org/10.1111/j.1558-5646.2011.01269.x
| On the potential for GWAS with phenotypic population means and allele-frequency data (popGWAS) | Markus Pfenninger | <p>It is vital to understand the genomic basis of differences in ecologically important traits if we are to understand the impact of global change on biodiversity and enhance our ability for targeted intervention. This study explores the potential... | ![]() | Bioinformatics & Computational Biology, Evolutionary Applications, Genotype-Phenotype, Population Genetics / Genomics | Frédéric Guillaume | 2024-06-15 08:41:14 | View | |
15 Sep 2022
![]() Bimodal breeding phenology in the Parsley Frog Pelodytes punctatus as a bet-hedging strategy in an unpredictable environment despite strong priority effectsHelene Jourdan-Pineau, Pierre-Andre Crochet, Patrice David https://doi.org/10.1101/2022.02.24.481784Spreading the risk of reproductive failure when the environment is unpredictable and ephemeralRecommended by Gabriele Sorci based on reviews by Thomas Haaland and Zoltan RadaiMany species breed in environments that are unpredictable, for instance in terms of the availability of resources needed to raise the offspring. Organisms might respond to such spatial and temporal unpredictability by adopting plastic responses to adjust their reproductive investment according to perceived cues of environmental quality. Some species such as the amphibians might also face the problem of ephemeral habitats, when the ponds where they breed have a chance of drying up before metamorphosis has occurred. In this case, maximizing long-term fitness might involve a strategy of spreading the risk, even though the reproductive success of a single reproductive bout might be lower. Understanding how animals (and plants) get adapted to stochastic environments is particularly crucial in the current context of rapid environmental changes. In this article, Jourdan-Pineau et al. report the results of field surveys of the Parsley Frog (Pelodytes punctatus) in Southern France. This frog has peculiar breeding phenology with females breeding in autumn and spring. The authors provide quite an extensive amount of information on the reproductive success of eggs laid in each season and the possible ecological factors accounting for differences between seasons. Although the presence of interspecific competitors and predators does not seem to account for pond-specific reproductive success, the survival of tadpoles hatching from eggs laid in spring is severely impaired when tadpoles from the autumn cohort have managed to survive. This intraspecific competition takes the form of a “priority” effect where tadpoles from the autumn cohort outcompete the smaller larvae from the spring cohort. Given this strong priority effect, one might tentatively predict that females laying in spring should avoid ponds with tadpoles from the autumn cohort. Surprisingly, however, the authors did not find any evidence for such avoidance, which might indicate strong constraints on the availability of ponds where females might possibly lay. Assuming that each female can indeed lay both in autumn and spring, how is this bimodal phenology maintained? Would not be worthier to allocate all the eggs to the autumn (or the spring) laying season? Eggs laid in autumn and spring have to face different environmental hazards, reducing their hatching success and the probability to produce metamorphs (for instance, tadpoles hatching from eggs laid in autumn have to overwinter which might be a particularly risky phase). Jourdan-Pineau and coworkers addressed this question by adapting a bet-hedging model that was initially developed to investigate the strategy of allocation into seed dormancy of annual plants (Cohen 1966) to the case of the bimodal phenology of the Parsley Frog. By feeding the model with the parameter values obtained from the field surveys, they found that the two breeding strategies (laying in autumn and in spring) can coexist as long as the probability of breeding success in the autumn cohort is between 20% and 80% (the range of values allowing the coexistence of a bimodal phenology shrinking a little bit when considering that frogs can reproduce 5 times during their lifespan instead of three times). This paper provides a very nice illustration of the importance of combining approaches (here field monitoring to gather data that can be used to feed models) to understand the evolution of peculiar breeding strategies. Although future work should attempt to gather individual-based data (in addition to population data), this work shows that spreading the risk can be an adaptive strategy in environments characterized by strong stochastic variation. References Cohen D (1966) Optimizing reproduction in a randomly varying environment. Journal of Theoretical Biology, 12, 119–129. https://doi.org/10.1016/0022-5193(66)90188-3 Jourdan-Pineau H., Crochet P.-A., David P. (2022) Bimodal breeding phenology in the Parsley Frog Pelodytes punctatus as a bet-hedging strategy in an unpredictable environment despite strong priority effects. bioRxiv, 2022.02.24.481784, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.02.24.481784 | Bimodal breeding phenology in the Parsley Frog Pelodytes punctatus as a bet-hedging strategy in an unpredictable environment despite strong priority effects | Helene Jourdan-Pineau, Pierre-Andre Crochet, Patrice David | <p style="text-align: justify;">When environmental conditions are unpredictable, expressing alternative phenotypes spreads the risk of failure, a mixed strategy called bet-hedging. In the southern part of its range, the Parsley Frog <em>Pelodytes ... | ![]() | Adaptation, Evolutionary Ecology, Life History | Gabriele Sorci | 2022-02-28 11:53:00 | View | |
24 Jan 2017
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Birth of a W sex chromosome by horizontal transfer of Wolbachia bacterial symbiont genomeSébastien Leclercq, Julien Thézé, Mohamed Amine Chebbi, Isabelle Giraud, Bouziane Moumen, Lise Ernenwein, Pierre Grève, Clément Gilbert, and Richard Cordaux https://doi.org/10.1073/pnas.1608979113A newly evolved W(olbachia) sex chromosome in pillbug!Recommended by Gabriel Marais and Sylvain CharlatIn some taxa such as fish and arthropods, closely related species can have different mechanisms of sex determination and in particular different sex chromosomes, which implies that new sex chromosomes are constantly evolving [1]. Several models have been developed to explain this pattern but empirical data are lacking and the causes of the fast sex chromosome turn over remain mysterious [2-4]. Leclerq et al. [5] in a paper that just came out in PNAS have focused on one possible explanation: Wolbachia. This widespread intracellular symbiont of arthropods can manipulate its host reproduction in a number of ways, often by biasing the allocation of resources toward females, the transmitting sex. Perhaps the most spectacular example is seen in pillbugs, where Wolbachia commonly turns infected males into females, thus doubling its effective transmission to grandchildren. Extensive investigations on this phenomenon were initiated 30 years ago in the host species Armadillidium vulgare. The recent paper by Leclerq et al. beautifully validates an hypothesis formulated in these pioneer studies [6], namely, that a nuclear insertion of the Wolbachia genome caused the emergence of new female determining chromosome, that is, a new sex chromosome. Many populations of A. vulgare are infected by the feminising Wolbachia strain wVulC, where the spread of the bacterium has also induced the loss of the ancestral female determining W chromosome (because feminized ZZ individuals produce females without transmitting any W). In these populations, all individuals carry two Z chromosomes, so that the bacterium is effectively the new sex-determining factor: specimens that received Wolbachia from their mother become females, while the occasional loss of Wolbachia from mothers to eggs allows the production of males. Intriguingly, studies from natural populations also report that some females are devoid both of Wolbachia and the ancestral W chromosome, suggesting the existence of new female determining nuclear factor, the hypothetical “f element”. Leclerq et al. [5] found the f element and decrypted its origin. By sequencing the genome of a strain carrying the putative f element, they found that a nearly complete wVulC genome got inserted in the nuclear genome and that the chromosome carrying the insertion has effectively become a new W chromosome. The insertion is indeed found only in females, PCRs and pedigree analysis tell. Although the Wolbachia-derived gene(s) that became sex-determining gene(s) remain to be identified among many possible candidates, the genomic and genetic evidence are clear that this Wolbachia insertion is determining sex in this pillbug strain. Leclerq et al. [5] also found that although this insertion is quite recent, many structural changes (rearrangements, duplications) have occurred compared to the wVulC genome, which study will probably help understand which bacterial gene(s) have retained a function in the nucleus of the pillbug. Also, in the future, it will be interesting to understand how and why exactly the nuclear inserted Wolbachia rose in frequency in the pillbug population and how the cytoplasmic Wolbachia was lost, and to tease apart the roles of selection and drift in this event. We highly recommend this paper, which provides clear evidence that Wolbachia has caused sex chromosome turn over in one species, opening the conjecture that it might have done so in many others. References [1] Bachtrog D, Mank JE, Peichel CL, Kirkpatrick M, Otto SP, Ashman TL, Hahn MW, Kitano J, Mayrose I, Ming R, Perrin N, Ross L, Valenzuela N, Vamosi JC. 2014. Tree of Sex Consortium. Sex determination: why so many ways of doing it? PLoS Biology 12: e1001899. doi: 10.1371/journal.pbio.1001899 [2] van Doorn GS, Kirkpatrick M. 2007. Turnover of sex chromosomes induced by sexual conflict. Nature 449: 909-912. doi: 10.1038/nature06178 [3] Cordaux R, Bouchon D, Grève P. 2011. The impact of endosymbionts on the evolution of host sex-determination mechanisms. Trends in Genetics 27: 332-341. doi: 10.1016/j.tig.2011.05.002 [4] Blaser O, Neuenschwander S, Perrin N. 2014. Sex-chromosome turnovers: the hot-potato model. American Naturalist 183: 140-146. doi: 10.1086/674026 [5] Leclercq S, Thézé J, Chebbi MA, Giraud I, Moumen B, Ernenwein L, Grève P, Gilbert C, Cordaux R. 2016. Birth of a W sex chromosome by horizontal transfer of Wolbachia bacterial symbiont genome. Proceeding of the National Academy of Science USA 113: 15036-15041. doi: 10.1073/pnas.1608979113 [6] Legrand JJ, Juchault P. 1984. Nouvelles données sur le déterminisme génétique et épigénétique de la monogénie chez le crustacé isopode terrestre Armadillidium vulgare Latr. Génétique Sélection Evolution 16: 57–84. doi: 10.1186/1297-9686-16-1-57 | Birth of a W sex chromosome by horizontal transfer of Wolbachia bacterial symbiont genome | Sébastien Leclercq, Julien Thézé, Mohamed Amine Chebbi, Isabelle Giraud, Bouziane Moumen, Lise Ernenwein, Pierre Grève, Clément Gilbert, and Richard Cordaux | <p>Sex determination is an evolutionarily ancient, key developmental pathway governing sexual differentiation in animals. Sex determination systems are remarkably variable between species or groups of species, however, and the evolutionary forces ... | ![]() | Bioinformatics & Computational Biology, Genome Evolution, Molecular Evolution, Reproduction and Sex, Species interactions | Gabriel Marais | 2017-01-13 15:15:51 | View | |
29 Jul 2020
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The Y chromosome may contribute to sex-specific ageing in DrosophilaEmily J Brown, Alison H Nguyen, Doris Bachtrog https://doi.org/10.1101/156042Y chromosome makes fruit flies die youngerRecommended by Gabriel Marais, Jean-François Lemaitre and Cristina VieiraIn most animal species, males and females display distinct survival prospect, a phenomenon known as sex gap in longevity (SGL, Marais et al. 2018). The study of SGLs is crucial not only for having a full picture of the causes underlying organisms’ health, aging and death but also to initiate the development of sex-specific anti-aging interventions in humans (Austad and Bartke 2015). Three non-mutually evolutionary causes have been proposed to underlie SGLs (Marais et al. 2018). First, SGLs could be the consequences of sex-differences in life history strategies. For example, evolving dimorphic traits (e.g. body size, ornaments or armaments) may imply unequal physiological costs (e.g. developmental, maintenance) between the sexes and this may result in differences in longevity and aging. Second, mitochondria are usually transmitted by the mother and thus selection is blind to mitochondrial deleterious mutations affecting only males. Such mutations can freely accumulate in the mitochondrial genome and may reduce male longevity, a phenomenon called the mother’s curse (Frank and Hurst 1996). Third, in species with sex chromosomes, all recessive deleterious mutations will be expressed on the single X chromosome in XY males and may reduce their longevity (the unguarded X effect). In addition, the numerous transposable elements (TEs) on the Y chromosome may affect aging. TE activity is normally repressed by epigenetic regulation (DNA methylation, histone modifications and small RNAs). However, it is known that this regulation is disrupted with increasing age. Because of the TE-rich Y chromosome, more TEs may become active in old males than in old females, generating more somatic mutations, accelerating aging and reducing longevity in males (the toxic Y effect, Marais et al. 2018). References Austad, S. N., and Bartke, A. (2015). Sex differences in longevity and in responses to anti-aging interventions: A Mini-Review. Gerontology, 62(1), 40–46. 10.1159/000381472 | The Y chromosome may contribute to sex-specific ageing in Drosophila | Emily J Brown, Alison H Nguyen, Doris Bachtrog | <p>Heterochromatin suppresses repetitive DNA, and a loss of heterochromatin has been observed in aged cells of several species, including humans and *Drosophila*. Males often contain substantially more heterochromatic DNA than females, due to the ... | ![]() | Bioinformatics & Computational Biology, Expression Studies, Genetic conflicts, Genome Evolution, Genotype-Phenotype, Molecular Evolution, Reproduction and Sex | Gabriel Marais | 2020-07-28 15:06:18 | View | |
31 Oct 2022
![]() Genotypic sex shapes maternal care in the African Pygmy mouse, Mus minutoidesLouise D Heitzmann, Marie Challe, Julie Perez, Laia Castell, Evelyne Galibert, Agnes Martin, Emmanuel Valjent, Frederic Veyrunes https://doi.org/10.1101/2022.04.05.487174Effect of sex chromosomes on mammalian behaviour: a case study in pygmy miceRecommended by Gabriel Marais and Trine BildeIn mammals, it is well documented that sexual dimorphism and in particular sex differences in behaviour are fine-tuned by gonadal hormonal profiles. For example, in lemurs, where female social dominance is common, the level of testosterone in females is unusually high compared to that of other primate females (Petty and Drea 2015). Recent studies however suggest that gonadal hormones might not be the only biological factor involved in establishing sexual dimorphism, sex chromosomes might also play a role. The four core genotype (FCG) model and other similar systems allowing to decouple phenotypic and genotypic sex in mice have provided very convincing evidence of such a role (Gatewood et al. 2006; Arnold and Chen 2009; Arnold 2020a, 2020b). This however is a new field of research and the role of sex chromosomes in establishing sexually dimorphic behaviours has not been studied very much yet. Moreover, the FCG model has some limits. Sry, the male determinant gene on the mammalian Y chromosome might be involved in some sex differences in neuroanatomy, but Sry is always associated with maleness in the FCG model, and this potential role of Sry cannot be studied using this system. Heitzmann et al. have used a natural system to approach these questions. They worked on the African Pygmy mouse, Mus minutoides, in which a modified X chromosome called X* can feminize X*Y individuals, which offers a great opportunity for elegant experiments on the effects of sex chromosomes versus hormones on behaviour. They focused on maternal care and compared pup retrieval, nest quality, and mother-pup interactions in XX, X*X and X*Y females. They found that X*Y females are significantly better at retrieving pups than other females. They are also much more aggressive towards the fathers than other females, preventing paternal care. They build nests of poorer quality but have similar interactions with pups compared to other females. Importantly, no significant differences were found between XX and X*X females for these traits, which points to an effect of the Y chromosome in explaining the differences between X*Y and other females (XX, X*X). Also, another work from the same group showed similar gonadal hormone levels in all the females (Veyrunes et al. 2022). Heitzmann et al. made a number of predictions based on what is known about the neuroanatomy of rodents which might explain such behaviours. Using cytology, they looked for differences in neuron numbers in the hypothalamus involved in the oxytocin, vasopressin and dopaminergic pathways in XX, X*X and X*Y females, but could not find any significant effects. However, this part of their work relied on very small sample sizes and they used virgin females instead of mothers for ethical reasons, which greatly limited the analysis. Interestingly, X*Y females have a higher reproductive performance than XX and X*X ones, which compensate for the cost of producing unviable YY embryos and certainly contribute to maintaining a high frequency of X* in many African pygmy mice populations (Saunders et al. 2014, 2022). X*Y females are probably solitary mothers contrary to other females, and Heitzmann et al. have uncovered a divergent female strategy in this species. Their work points out the role of sex chromosomes in establishing sex differences in behaviours. References Arnold AP (2020a) Sexual differentiation of brain and other tissues: Five questions for the next 50 years. Hormones and Behavior, 120, 104691. https://doi.org/10.1016/j.yhbeh.2020.104691 Arnold AP (2020b) Four Core Genotypes and XY* mouse models: Update on impact on SABV research. Neuroscience & Biobehavioral Reviews, 119, 1–8. https://doi.org/10.1016/j.neubiorev.2020.09.021 Arnold AP, Chen X (2009) What does the “four core genotypes” mouse model tell us about sex differences in the brain and other tissues? Frontiers in Neuroendocrinology, 30, 1–9. https://doi.org/10.1016/j.yfrne.2008.11.001 Gatewood JD, Wills A, Shetty S, Xu J, Arnold AP, Burgoyne PS, Rissman EF (2006) Sex Chromosome Complement and Gonadal Sex Influence Aggressive and Parental Behaviors in Mice. Journal of Neuroscience, 26, 2335–2342. https://doi.org/10.1523/JNEUROSCI.3743-05.2006 Heitzmann LD, Challe M, Perez J, Castell L, Galibert E, Martin A, Valjent E, Veyrunes F (2022) Genotypic sex shapes maternal care in the African Pygmy mouse, Mus minutoides. bioRxiv, 2022.04.05.487174, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.04.05.487174 Petty JMA, Drea CM (2015) Female rule in lemurs is ancestral and hormonally mediated. Scientific Reports, 5, 9631. https://doi.org/10.1038/srep09631 Saunders PA, Perez J, Rahmoun M, Ronce O, Crochet P-A, Veyrunes F (2014) Xy Females Do Better Than the Xx in the African Pygmy Mouse, Mus Minutoides. Evolution, 68, 2119–2127. https://doi.org/10.1111/evo.12387 Saunders PA, Perez J, Ronce O, Veyrunes F (2022) Multiple sex chromosome drivers in a mammal with three sex chromosomes. Current Biology, 32, 2001-2010.e3. https://doi.org/10.1016/j.cub.2022.03.029 Veyrunes F, Perez J, Heitzmann L, Saunders PA, Givalois L (2022) Separating the effects of sex hormones and sex chromosomes on behavior in the African pygmy mouse Mus minutoides, a species with XY female sex reversal. bioRxiv, 2022.07.11.499546. https://doi.org/10.1101/2022.07.11.499546 | Genotypic sex shapes maternal care in the African Pygmy mouse, Mus minutoides | Louise D Heitzmann, Marie Challe, Julie Perez, Laia Castell, Evelyne Galibert, Agnes Martin, Emmanuel Valjent, Frederic Veyrunes | <p>Sexually dimorphic behaviours, such as parental care, have long been thought to be driven mostly, if not exclusively, by gonadal hormones. In the past two decades, a few studies have challenged this view, highlighting the direct influence of th... | ![]() | Behavior & Social Evolution, Evolutionary Ecology, Reproduction and Sex | Gabriel Marais | 2022-04-08 20:09:58 | View |
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