Pub Date : 2025-07-23DOI: 10.1038/s41437-025-00781-x
Luna Qingyang Li, Liisa Parts, Philip Madgwick, Kayla King, Anthony Flemming, Alison Woollard
Insecticide resistance poses a major challenge to sustainable agriculture, yet studying its evolution in laboratory settings is notoriously difficult due to challenges related to maintaining large populations of pest species. While theoretical models offer valuable predictions, an experimental system for validating insecticide resistance management strategies remains lacking. Here, we explore C. elegans as a model organism for studying insecticide resistance evolution. We developed an in silico population genetics model and tested its predictive power in laboratory experiments, comparing the computational predictions to experimental resistance selection dynamics. Two compounds with distinct modes of action were tested to assess the generalizability of this system across different resistance mechanisms. Our results showed that in silico predictions generally resembled multigenerational in vivo resistance selection outcomes, demonstrating the feasibility of integrating in vivo and in silico modelling approaches in resistance research. By bridging the gap between theoretical and empirical research, this framework paves the way for addressing a wide range of open questions in resistance management, permitting the development of better informed and more effective resistance management strategies for the agricultural industry.
{"title":"A proof-of-concept experimental-theoretical model to predict pesticide resistance evolution.","authors":"Luna Qingyang Li, Liisa Parts, Philip Madgwick, Kayla King, Anthony Flemming, Alison Woollard","doi":"10.1038/s41437-025-00781-x","DOIUrl":"10.1038/s41437-025-00781-x","url":null,"abstract":"<p><p>Insecticide resistance poses a major challenge to sustainable agriculture, yet studying its evolution in laboratory settings is notoriously difficult due to challenges related to maintaining large populations of pest species. While theoretical models offer valuable predictions, an experimental system for validating insecticide resistance management strategies remains lacking. Here, we explore C. elegans as a model organism for studying insecticide resistance evolution. We developed an in silico population genetics model and tested its predictive power in laboratory experiments, comparing the computational predictions to experimental resistance selection dynamics. Two compounds with distinct modes of action were tested to assess the generalizability of this system across different resistance mechanisms. Our results showed that in silico predictions generally resembled multigenerational in vivo resistance selection outcomes, demonstrating the feasibility of integrating in vivo and in silico modelling approaches in resistance research. By bridging the gap between theoretical and empirical research, this framework paves the way for addressing a wide range of open questions in resistance management, permitting the development of better informed and more effective resistance management strategies for the agricultural industry.</p>","PeriodicalId":12991,"journal":{"name":"Heredity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7619028/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144698417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-19DOI: 10.1038/s41437-025-00783-9
Ezekiel Ahn, Louis K. Prom, Sunchung Park, Dongho Lee, Jishnu Bhatt, Vishnutej Ellur, Seunghyun Lim, Jae Hee Jang, Dilip Lakshman, Clint Magill
Plant disease resistance is often a complex, polygenic trait, making its genetic dissection with traditional genome-wide association studies (GWAS) challenging. Grain mold in sorghum, a devastating disease caused by a fungal complex, exemplifies this complexity. We hypothesized that a machine learning (ML)-driven GWAS, employing diverse phenotypic representations from a panel of 306 sorghum accessions, could more effectively unravel the genetic basis of resistance. Phenotypic data, including raw disease scores, a ‘difference phenotype’ (inoculated vs. control), and principal components, were analyzed using Boosted Tree and Bootstrap Forest models, demonstrating strong explanatory power for phenotypic variance when trained on the entire dataset. This ML-GWAS approach confirmed a highly polygenic architecture for grain mold resistance, identifying numerous SNPs across the sorghum genome. Notably, several SNPs were consistently associated with resistance across multiple analytical models and phenotypic representations. These robustly identified SNPs were frequently located near genes with predicted functions integral to plant defense. Gene ontology (GO) analyses of the candidate gene set confirmed enrichment in categories supporting roles in pathogen recognition, DNA repair, and stress response modulation, indicating a multifaceted defense mechanism. This study provides valuable candidate genes for breeding sorghum with enhanced grain mold resistance and offers a refined methodological framework for dissecting complex traits in this crop. The successful application of this ML-based strategy in sorghum suggests its potential utility for studying similar complex traits in other plant species.
{"title":"Machine learning reveals complex genetics of fungal resistance in sorghum grain mold","authors":"Ezekiel Ahn, Louis K. Prom, Sunchung Park, Dongho Lee, Jishnu Bhatt, Vishnutej Ellur, Seunghyun Lim, Jae Hee Jang, Dilip Lakshman, Clint Magill","doi":"10.1038/s41437-025-00783-9","DOIUrl":"10.1038/s41437-025-00783-9","url":null,"abstract":"Plant disease resistance is often a complex, polygenic trait, making its genetic dissection with traditional genome-wide association studies (GWAS) challenging. Grain mold in sorghum, a devastating disease caused by a fungal complex, exemplifies this complexity. We hypothesized that a machine learning (ML)-driven GWAS, employing diverse phenotypic representations from a panel of 306 sorghum accessions, could more effectively unravel the genetic basis of resistance. Phenotypic data, including raw disease scores, a ‘difference phenotype’ (inoculated vs. control), and principal components, were analyzed using Boosted Tree and Bootstrap Forest models, demonstrating strong explanatory power for phenotypic variance when trained on the entire dataset. This ML-GWAS approach confirmed a highly polygenic architecture for grain mold resistance, identifying numerous SNPs across the sorghum genome. Notably, several SNPs were consistently associated with resistance across multiple analytical models and phenotypic representations. These robustly identified SNPs were frequently located near genes with predicted functions integral to plant defense. Gene ontology (GO) analyses of the candidate gene set confirmed enrichment in categories supporting roles in pathogen recognition, DNA repair, and stress response modulation, indicating a multifaceted defense mechanism. This study provides valuable candidate genes for breeding sorghum with enhanced grain mold resistance and offers a refined methodological framework for dissecting complex traits in this crop. The successful application of this ML-based strategy in sorghum suggests its potential utility for studying similar complex traits in other plant species.","PeriodicalId":12991,"journal":{"name":"Heredity","volume":"134 8","pages":"485-499"},"PeriodicalIF":3.9,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144667536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Despite many examples of balanced inversion polymorphisms, little is known about how they affect fitness-related traits. This knowledge gap hampers our understanding of how they are selectively maintained as protected polymorphisms. Here, we study the effects of a cosmopolitan balanced inversion polymorphism in D. melanogaster, In(3R)Payne, on fitness components, including traits related to development, growth, reproduction, stress resistance, and adult survival. We find that the non-inverted standard (STD) chromosomal arrangement and the inverted (INV) arrangement behave like Mendelian alleles of a supergene, which affect a suite of complex fitness-related phenotypes. While the STD arrangement tends to have positive, mostly dominant effects on size-related traits, fecundity, fertility, stress resistance, and lifespan, the INV arrangement exhibits mostly recessive effects that are indicative of fitness costs. Yet, in favor of the balanced polymorphism, we observe overdominance for egg hatchability, egg-to-adult survival, pupal survival at 18 °C, developmental time, and male desiccation resistance. The most parsimonious explanation for these heterotic effects is that they are due to some form of multi-locus heterokaryotype advantage. We also find several instances of trait-, sex-, and temperature-dependent changes in the degree of dominance, suggesting a possible role of antagonistic selection with context-specific dominance reversals in maintaining the polymorphism. Moreover, genotype-by-environment interactions and parental effects appear to contribute as well. Together, our results suggest that multiple phenotypic modes of balancing selection are involved in maintaining the inversion polymorphism.
{"title":"Multiple forms of balancing selection maintain inversion polymorphism","authors":"Margot Paris, Esra Durmaz Mitchell, Envel Kerdaffrec, Doriane Rubin, Cécile Spichtig, Felicitas Zurbriggen, Joël Becker, Hannah Augustijnen, Harshavardhan Thyagarajan, Eliane Zinn, Fanny Gagliardi, Elliot Gobet, Tristan Rey, Yvan Rime, Sofia Ribeiro Machado, Jeremias Bachmann, Noemi Sgammeglia, Paul Schmidt, Thomas Flatt","doi":"10.1038/s41437-025-00780-y","DOIUrl":"10.1038/s41437-025-00780-y","url":null,"abstract":"Despite many examples of balanced inversion polymorphisms, little is known about how they affect fitness-related traits. This knowledge gap hampers our understanding of how they are selectively maintained as protected polymorphisms. Here, we study the effects of a cosmopolitan balanced inversion polymorphism in D. melanogaster, In(3R)Payne, on fitness components, including traits related to development, growth, reproduction, stress resistance, and adult survival. We find that the non-inverted standard (STD) chromosomal arrangement and the inverted (INV) arrangement behave like Mendelian alleles of a supergene, which affect a suite of complex fitness-related phenotypes. While the STD arrangement tends to have positive, mostly dominant effects on size-related traits, fecundity, fertility, stress resistance, and lifespan, the INV arrangement exhibits mostly recessive effects that are indicative of fitness costs. Yet, in favor of the balanced polymorphism, we observe overdominance for egg hatchability, egg-to-adult survival, pupal survival at 18 °C, developmental time, and male desiccation resistance. The most parsimonious explanation for these heterotic effects is that they are due to some form of multi-locus heterokaryotype advantage. We also find several instances of trait-, sex-, and temperature-dependent changes in the degree of dominance, suggesting a possible role of antagonistic selection with context-specific dominance reversals in maintaining the polymorphism. Moreover, genotype-by-environment interactions and parental effects appear to contribute as well. Together, our results suggest that multiple phenotypic modes of balancing selection are involved in maintaining the inversion polymorphism.","PeriodicalId":12991,"journal":{"name":"Heredity","volume":"135 3","pages":"138-151"},"PeriodicalIF":3.9,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41437-025-00780-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144659046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-03DOI: 10.1038/s41437-025-00777-7
Nitin Ravikanthachari, Carol L. Boggs
Specialist phytophagous insects have a narrow hostplant range for optimal development and survival. Mismatches between female oviposition preference and larval performance can lead to high fitness costs. Understanding the mechanistic basis of this decoupling can help us understand evolutionary constraints and aid in predicting outcomes of error-prone oviposition. We investigated the causes for preference-performance mismatches in a specialist native herbivore laying eggs on an invasive toxic plant. Transcriptomic analyses revealed host-plant-specific gene expression signatures in larvae feeding on different plants, while there was no differential gene expression in gustatory/olfactory organs of adult females with different oviposition preferences. However, genomic analysis revealed significant genetic differentiation in several genes underlying signal transduction in adult females with different oviposition preferences. The larvae feeding on toxic plants showed lower expression of specialized detoxification enzymes and higher expression of general digestive enzymes, indicating the inability of larvae to detoxify toxic compounds present in the toxic plants. We additionally found that genes related to successful detoxification and adaptive feeding were enriched in larvae feeding on native plants, while genes related to toxic responses, apoptosis, and accelerated development were enriched in larvae feeding on toxic plants. Our findings dissect the underlying mechanisms behind a preference-performance mismatch, quantifying the impact of error-prone oviposition on larval performance in a specialized species interaction.
{"title":"Differences in gene expression and genetic variation underlying preference-performance mismatches: insights from a specialized native herbivore on an invasive toxic plant","authors":"Nitin Ravikanthachari, Carol L. Boggs","doi":"10.1038/s41437-025-00777-7","DOIUrl":"10.1038/s41437-025-00777-7","url":null,"abstract":"Specialist phytophagous insects have a narrow hostplant range for optimal development and survival. Mismatches between female oviposition preference and larval performance can lead to high fitness costs. Understanding the mechanistic basis of this decoupling can help us understand evolutionary constraints and aid in predicting outcomes of error-prone oviposition. We investigated the causes for preference-performance mismatches in a specialist native herbivore laying eggs on an invasive toxic plant. Transcriptomic analyses revealed host-plant-specific gene expression signatures in larvae feeding on different plants, while there was no differential gene expression in gustatory/olfactory organs of adult females with different oviposition preferences. However, genomic analysis revealed significant genetic differentiation in several genes underlying signal transduction in adult females with different oviposition preferences. The larvae feeding on toxic plants showed lower expression of specialized detoxification enzymes and higher expression of general digestive enzymes, indicating the inability of larvae to detoxify toxic compounds present in the toxic plants. We additionally found that genes related to successful detoxification and adaptive feeding were enriched in larvae feeding on native plants, while genes related to toxic responses, apoptosis, and accelerated development were enriched in larvae feeding on toxic plants. Our findings dissect the underlying mechanisms behind a preference-performance mismatch, quantifying the impact of error-prone oviposition on larval performance in a specialized species interaction.","PeriodicalId":12991,"journal":{"name":"Heredity","volume":"134 8","pages":"461-472"},"PeriodicalIF":3.9,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41437-025-00777-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144560005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-26DOI: 10.1038/s41437-025-00776-8
Ourania Grigoriadou Zormpa, Selina Wilhelmi, Boban Vucetic, Mihnea-Ioan-Cezar Ciocîrlan, Markus Mueller, Elena Ciocîrlan, Alexandru Lucian Curtu, Mehdi Ben Targem, Henning Wildhagen, Oliver Gailing, Katharina B. Budde
Differences in environmental conditions can shape the level and distribution of intraspecific genetic variation between and within populations. Elevational gradients are characterised by strong variation in environmental conditions on a short spatial scale and provide an ideal setting to study the spatial distribution of genetic diversity. Therefore, we investigated the genetic diversity, fine-scale spatial genetic structure (FSGS) and spring phenology (bud burst) as a proxy for flowering of five European beech (Fagus sylvatica L.) populations along an elevational gradient, ranging from about 550 m to 1450 m a.s.l. in the Romanian Carpathians. Using microsatellite and genome-wide single nucleotide polymorphism (SNP) markers, we observed a slight decrease in genetic diversity with increasing elevation and low population differentiation. Furthermore, levels of FSGS decreased with elevation along the gradient. We could not detect any significant effects of spring phenological traits on the level of FSGS probably because many different environmental factors and processes vary over the years and contribute to shaping the FSGS. The slightly lower genetic diversity in high elevation populations may indicate stronger drift effects and could be due to the marginal ecological conditions and the lower abundance of beech. However, in these stands with less competing crowns and a more open forest structure, pollen dispersal might be longer ranging in this wind pollinated species which could contribute to a weaker FSGS. The knowledge about the level and structure of genetic variation along environmental gradients is crucial to inform forest and conservation management especially in the face of climate change.
{"title":"Genetic diversity and fine-scale spatial genetic structure of European beech populations along an elevational gradient","authors":"Ourania Grigoriadou Zormpa, Selina Wilhelmi, Boban Vucetic, Mihnea-Ioan-Cezar Ciocîrlan, Markus Mueller, Elena Ciocîrlan, Alexandru Lucian Curtu, Mehdi Ben Targem, Henning Wildhagen, Oliver Gailing, Katharina B. Budde","doi":"10.1038/s41437-025-00776-8","DOIUrl":"10.1038/s41437-025-00776-8","url":null,"abstract":"Differences in environmental conditions can shape the level and distribution of intraspecific genetic variation between and within populations. Elevational gradients are characterised by strong variation in environmental conditions on a short spatial scale and provide an ideal setting to study the spatial distribution of genetic diversity. Therefore, we investigated the genetic diversity, fine-scale spatial genetic structure (FSGS) and spring phenology (bud burst) as a proxy for flowering of five European beech (Fagus sylvatica L.) populations along an elevational gradient, ranging from about 550 m to 1450 m a.s.l. in the Romanian Carpathians. Using microsatellite and genome-wide single nucleotide polymorphism (SNP) markers, we observed a slight decrease in genetic diversity with increasing elevation and low population differentiation. Furthermore, levels of FSGS decreased with elevation along the gradient. We could not detect any significant effects of spring phenological traits on the level of FSGS probably because many different environmental factors and processes vary over the years and contribute to shaping the FSGS. The slightly lower genetic diversity in high elevation populations may indicate stronger drift effects and could be due to the marginal ecological conditions and the lower abundance of beech. However, in these stands with less competing crowns and a more open forest structure, pollen dispersal might be longer ranging in this wind pollinated species which could contribute to a weaker FSGS. The knowledge about the level and structure of genetic variation along environmental gradients is crucial to inform forest and conservation management especially in the face of climate change.","PeriodicalId":12991,"journal":{"name":"Heredity","volume":"134 8","pages":"451-460"},"PeriodicalIF":3.9,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41437-025-00776-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144505473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inducible defences in response to predation risk are a well-known example of adaptive phenotypic plasticity. Although inducible defences have been studied mainly within a generation (within-generational plasticity), there is now clear evidence that ancestral exposure to predation risk can influence the defences expressed by offspring, even if they have not been exposed themselves (transgenerational plasticity). The molecular mechanisms allowing the transmission of environmental information across generations are not well understood. In this study, we combined measures of antipredator responses (behavioural and morphological) with transcriptomic investigations across two generations in the freshwater snail Physa acuta. We hypothesised that both within- and transgenerational plasticity would induce phenotypic changes associated with differential gene expression. Our results confirmed within- and transgenerational plasticity: F1 snails respond to predator-cue exposure by increasing escape behaviour, reducing shell length, and developing thicker and slenderer shells, whereas F2 snails from exposed parents have longer and thicker shells with narrower apertures. Within- and transgenerational plasticity were accompanied by the differential expression of 112 genes (101 up- and 11 downregulated) and 23 differentially expressed genes (17 up- and 6 downregulated), respectively. Within- and transgenerational plasticity did not share common differentially expressed genes, but the associated molecular functions, involving metabolism and transcription regulation, were similar. These results suggest that predator-induced within-generational plasticity and transgenerational plasticity may result from different genomic pathways and may evolve independently.
{"title":"Transcriptomic basis of within- and trans-generational predator-induced plasticity in the freshwater snail Physa acuta","authors":"Léo Dejeux, Nathanaëlle Saclier, Juliette Tariel-Adam, Maxime Hoareau, Tristan Lefébure, Lara Konecny, Sandrine Plénet, Emilien Luquet","doi":"10.1038/s41437-025-00775-9","DOIUrl":"10.1038/s41437-025-00775-9","url":null,"abstract":"Inducible defences in response to predation risk are a well-known example of adaptive phenotypic plasticity. Although inducible defences have been studied mainly within a generation (within-generational plasticity), there is now clear evidence that ancestral exposure to predation risk can influence the defences expressed by offspring, even if they have not been exposed themselves (transgenerational plasticity). The molecular mechanisms allowing the transmission of environmental information across generations are not well understood. In this study, we combined measures of antipredator responses (behavioural and morphological) with transcriptomic investigations across two generations in the freshwater snail Physa acuta. We hypothesised that both within- and transgenerational plasticity would induce phenotypic changes associated with differential gene expression. Our results confirmed within- and transgenerational plasticity: F1 snails respond to predator-cue exposure by increasing escape behaviour, reducing shell length, and developing thicker and slenderer shells, whereas F2 snails from exposed parents have longer and thicker shells with narrower apertures. Within- and transgenerational plasticity were accompanied by the differential expression of 112 genes (101 up- and 11 downregulated) and 23 differentially expressed genes (17 up- and 6 downregulated), respectively. Within- and transgenerational plasticity did not share common differentially expressed genes, but the associated molecular functions, involving metabolism and transcription regulation, were similar. These results suggest that predator-induced within-generational plasticity and transgenerational plasticity may result from different genomic pathways and may evolve independently.","PeriodicalId":12991,"journal":{"name":"Heredity","volume":"134 7","pages":"439-449"},"PeriodicalIF":3.1,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144293665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a fundamentally important genetic parameter and evolutionary force, germline mutation rates have many applications in evolutionary biology. However, accurate estimates of de novo mutation (DNM) rates are still relatively scarce, even for extensively studied evolutionary biology models. We estimated DNM rates for the three-spined stickleback (Gasterosteus aculeatus), the ‘supermodel’ of ecology and evolutionary biology. Using a large number of family trios sequenced to 45x coverage, we identified 115 unique mutations genome-wide and estimated the DNM rate at µ = 5.11 × 10−9/bp/gen without any detectable sex bias. The localised DNM rate was found to be positively correlated with the recombination rate, supporting the notion that recombination is a mutagenic process. Correlations between µ and genomic characteristics of studied species and the related nine-spined stickleback (Pungitius pungitius) revealed a high degree of similarity, suggesting that despite 17.5 million years of independent evolution, the mutational processes in the two species appear to have been conserved.
{"title":"Rate of de novo mutations in the three-spined stickleback","authors":"Chaowei Zhang, Kerry Reid, Mikkel Heide Schierup, Hongbo Wang, Ulrika Candolin, Juha Merilä","doi":"10.1038/s41437-025-00767-9","DOIUrl":"10.1038/s41437-025-00767-9","url":null,"abstract":"As a fundamentally important genetic parameter and evolutionary force, germline mutation rates have many applications in evolutionary biology. However, accurate estimates of de novo mutation (DNM) rates are still relatively scarce, even for extensively studied evolutionary biology models. We estimated DNM rates for the three-spined stickleback (Gasterosteus aculeatus), the ‘supermodel’ of ecology and evolutionary biology. Using a large number of family trios sequenced to 45x coverage, we identified 115 unique mutations genome-wide and estimated the DNM rate at µ = 5.11 × 10−9/bp/gen without any detectable sex bias. The localised DNM rate was found to be positively correlated with the recombination rate, supporting the notion that recombination is a mutagenic process. Correlations between µ and genomic characteristics of studied species and the related nine-spined stickleback (Pungitius pungitius) revealed a high degree of similarity, suggesting that despite 17.5 million years of independent evolution, the mutational processes in the two species appear to have been conserved.","PeriodicalId":12991,"journal":{"name":"Heredity","volume":"134 7","pages":"387-395"},"PeriodicalIF":3.1,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41437-025-00767-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144283737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-06DOI: 10.1038/s41437-025-00773-x
Arnaud Quelin, Frédéric Austerlitz, Flora Jay
The ever-increasing availability of high-throughput DNA sequences and the development of numerous computational methods have led to considerable advances in our understanding of the evolutionary and demographic history of populations. Several demographic inference methods have been developed to take advantage of these massive genomic data. Simulation-based approaches, such as approximate Bayesian computation (ABC), have proved particularly efficient for complex demographic models. However, taking full advantage of the comprehensive information contained in massive genomic data remains a challenge for demographic inference methods, which generally rely on partial information from these data. Using advanced computational methods, such as machine learning, is valuable for efficiently integrating more comprehensive information. Here, we showed how simulation-based supervised machine learning methods applied to an extensive range of summary statistics are effective in inferring demographic parameters for connected populations. We compared three machine learning (ML) methods: a neural network, the multilayer perceptron (MLP), and two ensemble methods, random forest (RF) and the gradient boosting system XGBoost (XGB), to infer demographic parameters from genomic data under a standard isolation with migration model and a secondary contact model with varying population sizes. We showed that MLP outperformed the other two methods and that, on the basis of permutation feature importance, its predictions involved a larger combination of summary statistics. Moreover, they outperformed all three tested ABC algorithms. Finally, we demonstrated how a method called SHAP, from the field of explainable artificial intelligence, can be used to shed light on the contribution of summary statistics within the ML models.
{"title":"Assessing simulation-based supervised machine learning for demographic parameter inference from genomic data","authors":"Arnaud Quelin, Frédéric Austerlitz, Flora Jay","doi":"10.1038/s41437-025-00773-x","DOIUrl":"10.1038/s41437-025-00773-x","url":null,"abstract":"The ever-increasing availability of high-throughput DNA sequences and the development of numerous computational methods have led to considerable advances in our understanding of the evolutionary and demographic history of populations. Several demographic inference methods have been developed to take advantage of these massive genomic data. Simulation-based approaches, such as approximate Bayesian computation (ABC), have proved particularly efficient for complex demographic models. However, taking full advantage of the comprehensive information contained in massive genomic data remains a challenge for demographic inference methods, which generally rely on partial information from these data. Using advanced computational methods, such as machine learning, is valuable for efficiently integrating more comprehensive information. Here, we showed how simulation-based supervised machine learning methods applied to an extensive range of summary statistics are effective in inferring demographic parameters for connected populations. We compared three machine learning (ML) methods: a neural network, the multilayer perceptron (MLP), and two ensemble methods, random forest (RF) and the gradient boosting system XGBoost (XGB), to infer demographic parameters from genomic data under a standard isolation with migration model and a secondary contact model with varying population sizes. We showed that MLP outperformed the other two methods and that, on the basis of permutation feature importance, its predictions involved a larger combination of summary statistics. Moreover, they outperformed all three tested ABC algorithms. Finally, we demonstrated how a method called SHAP, from the field of explainable artificial intelligence, can be used to shed light on the contribution of summary statistics within the ML models.","PeriodicalId":12991,"journal":{"name":"Heredity","volume":"134 7","pages":"417-426"},"PeriodicalIF":3.1,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41437-025-00773-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144233970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-06DOI: 10.1038/s41437-025-00774-w
Collin W. Ahrens, Josh Griffiths, Al Danger, Rhys Coleman, Anthony van Rooyen, Elise Furlan, Andrew R. Weeks
The platypus is an evolutionary unique mammal on the east coast of mainland Australia and throughout Tasmania. The species is dependent on freshwater ecosystems, is declining throughout its range, and is listed as Vulnerable in the state of Victoria, and Near Threatened on the IUCN Red List. This relatively long-lived species is cryptic and nocturnal making it difficult to study in natural populations. Relatively little is known about its demographic history or the forces that shape genetic variation. We use a unique genomic dataset comprising 2715 single-nucleotide polymorphisms from 545 individual platypuses sampled from five catchments across Melbourne, Victoria. This dataset enabled us to describe the genetic variation across the catchments and test hypotheses relating to migration, effective population size, and potential negative effects of anthropogenic barriers. We found relatively consistent levels of genetic diversity in platypuses across Melbourne’s catchments, moderate levels of within-catchment migration, and genetic differentiation both between and within catchments. This genetic structure is explained by several factors, including isolation-by-river-distance, isolation-by-environment and within-catchment sex biased dispersal at short distances. These patterns are likely explained by a temporal lag between indirect and direct anthropogenic changes to the environmental and genetic variation, and these contemporary analyses likely reflect historical demographic patterns. In addition, we find that anthropogenic barriers such as dams have not measurably affected migration in these catchments. Our study highlights future evolutionary challenges that exist for platypuses in Melbourne’s catchments, which could be representative of their entire range along the east coast of Australia.
{"title":"Genetic diversity and structure lag the effects of contemporary environmental changes in a platypus meta-population","authors":"Collin W. Ahrens, Josh Griffiths, Al Danger, Rhys Coleman, Anthony van Rooyen, Elise Furlan, Andrew R. Weeks","doi":"10.1038/s41437-025-00774-w","DOIUrl":"10.1038/s41437-025-00774-w","url":null,"abstract":"The platypus is an evolutionary unique mammal on the east coast of mainland Australia and throughout Tasmania. The species is dependent on freshwater ecosystems, is declining throughout its range, and is listed as Vulnerable in the state of Victoria, and Near Threatened on the IUCN Red List. This relatively long-lived species is cryptic and nocturnal making it difficult to study in natural populations. Relatively little is known about its demographic history or the forces that shape genetic variation. We use a unique genomic dataset comprising 2715 single-nucleotide polymorphisms from 545 individual platypuses sampled from five catchments across Melbourne, Victoria. This dataset enabled us to describe the genetic variation across the catchments and test hypotheses relating to migration, effective population size, and potential negative effects of anthropogenic barriers. We found relatively consistent levels of genetic diversity in platypuses across Melbourne’s catchments, moderate levels of within-catchment migration, and genetic differentiation both between and within catchments. This genetic structure is explained by several factors, including isolation-by-river-distance, isolation-by-environment and within-catchment sex biased dispersal at short distances. These patterns are likely explained by a temporal lag between indirect and direct anthropogenic changes to the environmental and genetic variation, and these contemporary analyses likely reflect historical demographic patterns. In addition, we find that anthropogenic barriers such as dams have not measurably affected migration in these catchments. Our study highlights future evolutionary challenges that exist for platypuses in Melbourne’s catchments, which could be representative of their entire range along the east coast of Australia.","PeriodicalId":12991,"journal":{"name":"Heredity","volume":"134 7","pages":"427-438"},"PeriodicalIF":3.1,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144247648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Feliform carnivores face dual threats from habitat fragmentation and climate change, but unresolved phylogenetic relationships and unclear adaptive mechanisms hinder the development of conservation strategies. This study integrates mitochondrial genome data from 75 extant species (including three newly obtained taxa: Helogale parvula, Suricata suricatta, and Neofelis diardi) to resolve taxonomic controversies and reveal adaptive evolutionary mechanisms. Bayesian phylogenetic reconstruction strongly supports a sister-group relationship between Felidae and Prionodontidae (posterior probability PP = 1.0), overturning traditional morphological classifications. Divergence time estimation indicates that the crown group of Feliformia originated in the Middle Eocene (46 Ma), with key radiation events synchronized with Oligocene-Miocene climatic upheavals and continental collisions. Adaptive evolution analyses show that mitochondrial protein-coding genes (PCGs) are predominantly under purifying selection. However, significant positive selection signals were detected in the ND4 gene of Nandinia binotata and the COX2 gene of Pantherinae, potentially linked to arid adaptation and predatory energy demands, respectively. The frequent use of GTG start codons in the COX1 gene of Neofelis diardi suggests metabolic fine-tuning for island ecosystems. Conservation genomics identifies Prionodon pardicolor and Neofelis nebulosa as Evolutionarily Significant Units (ESUs) with heightened vulnerability to habitat fragmentation. By integrating mitogenomic architecture, deep-time biogeography, and contemporary selection pressures, this study establishes a unified framework bridging molecular systematics and conservation strategies, providing scientific guidance for protecting rapidly evolving lineages.
{"title":"Mitogenomic resolution of phylogenetic conflicts and adaptive signatures in feliform carnivorans","authors":"Xiaoyang Wu, Yamin Xing, Xibao Wang, Yongquan Shang, Yao Chen, Liangkai Wang, Mingke Han, Weilai Sha, Honghai Zhang","doi":"10.1038/s41437-025-00772-y","DOIUrl":"10.1038/s41437-025-00772-y","url":null,"abstract":"Feliform carnivores face dual threats from habitat fragmentation and climate change, but unresolved phylogenetic relationships and unclear adaptive mechanisms hinder the development of conservation strategies. This study integrates mitochondrial genome data from 75 extant species (including three newly obtained taxa: Helogale parvula, Suricata suricatta, and Neofelis diardi) to resolve taxonomic controversies and reveal adaptive evolutionary mechanisms. Bayesian phylogenetic reconstruction strongly supports a sister-group relationship between Felidae and Prionodontidae (posterior probability PP = 1.0), overturning traditional morphological classifications. Divergence time estimation indicates that the crown group of Feliformia originated in the Middle Eocene (46 Ma), with key radiation events synchronized with Oligocene-Miocene climatic upheavals and continental collisions. Adaptive evolution analyses show that mitochondrial protein-coding genes (PCGs) are predominantly under purifying selection. However, significant positive selection signals were detected in the ND4 gene of Nandinia binotata and the COX2 gene of Pantherinae, potentially linked to arid adaptation and predatory energy demands, respectively. The frequent use of GTG start codons in the COX1 gene of Neofelis diardi suggests metabolic fine-tuning for island ecosystems. Conservation genomics identifies Prionodon pardicolor and Neofelis nebulosa as Evolutionarily Significant Units (ESUs) with heightened vulnerability to habitat fragmentation. By integrating mitogenomic architecture, deep-time biogeography, and contemporary selection pressures, this study establishes a unified framework bridging molecular systematics and conservation strategies, providing scientific guidance for protecting rapidly evolving lineages.","PeriodicalId":12991,"journal":{"name":"Heredity","volume":"134 7","pages":"408-416"},"PeriodicalIF":3.1,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144173718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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