Pub Date : 2025-07-28DOI: 10.1038/s41576-025-00869-4
Zheng Li, Xiang Zhou
Fine-mapping in genome-wide association studies aims to identify potentially causal genetic variants among a set of candidate variants that are often highly correlated with each other owing to linkage disequilibrium. A variety of statistical approaches are used in fine-mapping, almost all of which are based on a multiple regression framework to model the relationship between genotype and phenotype, while accommodating specific assumptions about the distribution of variant effect sizes and using different inference algorithms. Owing to their modelling flexibility and the ease of making inferential statements, these approaches are predominantly Bayesian in nature. Recently, these approaches have been improved by refining modelling assumptions, integrating additional information, accommodating summary statistics, and developing scalable computational algorithms that improve computation efficiency and fine-mapping resolution. Fine-mapping aims to distinguish between the causal and non-causal genetic variants identified in genome-wide association studies of complex traits. In this Review, Li and Zhou cover the recent methodological advances of fine-mapping, including the refined modelling assumptions, improved computational efficiency and incorporation of additional information to expand biological insights.
{"title":"Towards improved fine-mapping of candidate causal variants","authors":"Zheng Li, Xiang Zhou","doi":"10.1038/s41576-025-00869-4","DOIUrl":"10.1038/s41576-025-00869-4","url":null,"abstract":"Fine-mapping in genome-wide association studies aims to identify potentially causal genetic variants among a set of candidate variants that are often highly correlated with each other owing to linkage disequilibrium. A variety of statistical approaches are used in fine-mapping, almost all of which are based on a multiple regression framework to model the relationship between genotype and phenotype, while accommodating specific assumptions about the distribution of variant effect sizes and using different inference algorithms. Owing to their modelling flexibility and the ease of making inferential statements, these approaches are predominantly Bayesian in nature. Recently, these approaches have been improved by refining modelling assumptions, integrating additional information, accommodating summary statistics, and developing scalable computational algorithms that improve computation efficiency and fine-mapping resolution. Fine-mapping aims to distinguish between the causal and non-causal genetic variants identified in genome-wide association studies of complex traits. In this Review, Li and Zhou cover the recent methodological advances of fine-mapping, including the refined modelling assumptions, improved computational efficiency and incorporation of additional information to expand biological insights.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 12","pages":"847-861"},"PeriodicalIF":52.0,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144715315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-25DOI: 10.1038/s41576-025-00881-8
Samira Musah
Samira Musah highlights a recent study by Ward et al., who generated isogenic human induced pluripotent stem cell lines to analyse the transcriptional and epigenetic effects of SMAD2 variants identified in patients with congenital heart disease.
{"title":"Decoding cell fate: human models reveal how SMAD2 variants shape development","authors":"Samira Musah","doi":"10.1038/s41576-025-00881-8","DOIUrl":"10.1038/s41576-025-00881-8","url":null,"abstract":"Samira Musah highlights a recent study by Ward et al., who generated isogenic human induced pluripotent stem cell lines to analyse the transcriptional and epigenetic effects of SMAD2 variants identified in patients with congenital heart disease.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 9","pages":"586-586"},"PeriodicalIF":52.0,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144701413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-21DOI: 10.1038/s41576-025-00871-w
Simon Roux, Clement Coclet
Viruses are found across all ecosystems and infect every type of organism on Earth. Traditional culture-based methods have proven insufficient to explore this viral diversity at scale, driving the development of viromics, the sequence-based analysis of uncultivated viruses. Viromics approaches have been particularly useful for studying viruses of microorganisms, which can act as crucial regulators of microbiomes across ecosystems. They have already revealed the broad geographic distribution of viral communities and are progressively uncovering the expansive genetic and functional diversity of the global virome. Moving forward, large-scale viral ecogenomics studies combined with new experimental and computational approaches to identify virus activity and host interactions will enable a more complete characterization of global viral diversity and its effects. In this Review, Roux and Coclet outline current viromics approaches and discuss how they have contributed to our growing understanding of viral genomic diversity, focusing on uncultivated viruses of microorganisms.
{"title":"Viromics approaches for the study of viral diversity and ecology in microbiomes","authors":"Simon Roux, Clement Coclet","doi":"10.1038/s41576-025-00871-w","DOIUrl":"10.1038/s41576-025-00871-w","url":null,"abstract":"Viruses are found across all ecosystems and infect every type of organism on Earth. Traditional culture-based methods have proven insufficient to explore this viral diversity at scale, driving the development of viromics, the sequence-based analysis of uncultivated viruses. Viromics approaches have been particularly useful for studying viruses of microorganisms, which can act as crucial regulators of microbiomes across ecosystems. They have already revealed the broad geographic distribution of viral communities and are progressively uncovering the expansive genetic and functional diversity of the global virome. Moving forward, large-scale viral ecogenomics studies combined with new experimental and computational approaches to identify virus activity and host interactions will enable a more complete characterization of global viral diversity and its effects. In this Review, Roux and Coclet outline current viromics approaches and discuss how they have contributed to our growing understanding of viral genomic diversity, focusing on uncultivated viruses of microorganisms.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 1","pages":"32-46"},"PeriodicalIF":52.0,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144677315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-21DOI: 10.1038/s41576-025-00875-6
Josué Barrera-Redondo, Susana M. Coelho
In this Journal Club, Josué Barrera-Redondo and Susana Coelho recount a 2012 paper by Carvunis et al. that provided a powerful framework for studying de novo gene evolution.
{"title":"An evolutionary continuum between non-coding and coding DNA","authors":"Josué Barrera-Redondo, Susana M. Coelho","doi":"10.1038/s41576-025-00875-6","DOIUrl":"10.1038/s41576-025-00875-6","url":null,"abstract":"In this Journal Club, Josué Barrera-Redondo and Susana Coelho recount a 2012 paper by Carvunis et al. that provided a powerful framework for studying de novo gene evolution.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 9","pages":"584-584"},"PeriodicalIF":52.0,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144677308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-21DOI: 10.1038/s41576-025-00870-x
Abbye E. McEwen, Malvika Tejura, Shawn Fayer, Lea M. Starita, Douglas M. Fowler
The rapid expansion of clinical genetic testing has markedly improved the detection of genetic variants. However, most variants lack the evidence needed to classify them as pathogenic or benign, resulting in the accumulation of variants of uncertain significance that cannot be used to diagnose or guide treatment of disease. Moreover, targeted therapy for cancer treatment increasingly depends on correctly identifying oncogenic driver mutations, but the oncogenicity of many variants identified in tumours remains unclear. To address these challenges, efforts to classify variants are increasingly using multiplexed assays of variant effect (MAVEs), which are massively scaled experiments that can generate functional data for thousands of variants simultaneously. The rise of MAVEs is accompanied by better guidance on the use of MAVE data for classifying germline variants to aid their clinical implementation. Here, we overview MAVE technologies from their inception to their increased use in the clinic, including their roles in uncovering mechanisms for variant pathogenicity and guiding targeted therapy and drug development. Multiplexed assays of variant effect (MAVEs) are highly scalable experimental approaches used to generate functional data for genetic variants. In this Review, McEwen et al. discuss the advances in MAVE technologies and guidance on how to use MAVE data in the clinic, which is helping to reveal variant pathogenicity, develop personalized drugs and inform targeted therapies.
{"title":"Multiplexed assays of variant effect for clinical variant interpretation","authors":"Abbye E. McEwen, Malvika Tejura, Shawn Fayer, Lea M. Starita, Douglas M. Fowler","doi":"10.1038/s41576-025-00870-x","DOIUrl":"10.1038/s41576-025-00870-x","url":null,"abstract":"The rapid expansion of clinical genetic testing has markedly improved the detection of genetic variants. However, most variants lack the evidence needed to classify them as pathogenic or benign, resulting in the accumulation of variants of uncertain significance that cannot be used to diagnose or guide treatment of disease. Moreover, targeted therapy for cancer treatment increasingly depends on correctly identifying oncogenic driver mutations, but the oncogenicity of many variants identified in tumours remains unclear. To address these challenges, efforts to classify variants are increasingly using multiplexed assays of variant effect (MAVEs), which are massively scaled experiments that can generate functional data for thousands of variants simultaneously. The rise of MAVEs is accompanied by better guidance on the use of MAVE data for classifying germline variants to aid their clinical implementation. Here, we overview MAVE technologies from their inception to their increased use in the clinic, including their roles in uncovering mechanisms for variant pathogenicity and guiding targeted therapy and drug development. Multiplexed assays of variant effect (MAVEs) are highly scalable experimental approaches used to generate functional data for genetic variants. In this Review, McEwen et al. discuss the advances in MAVE technologies and guidance on how to use MAVE data in the clinic, which is helping to reveal variant pathogenicity, develop personalized drugs and inform targeted therapies.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 2","pages":"137-154"},"PeriodicalIF":52.0,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144669634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-21DOI: 10.1038/s41576-025-00867-6
Joao A. Ascensao, Michael M. Desai
Laboratory evolution experiments in microbial and viral populations have provided great insight into the dynamics and predictability of evolution. The rise of high-throughput sequencing technologies over the past two decades has driven a massive expansion in the scale and power of these experiments. However, until recently our abilities to connect genetic with phenotypic changes and analyse the molecular basis of adaptation have remained limited. Rapid technical advances to measure and manipulate both genotypes and phenotypes are now providing opportunities to investigate the genetic basis of phenotypic evolution and the forces that drive evolutionary dynamics. Here we review how these methodological advances are being used to predict and manipulate the course of laboratory evolution, analyse eco-evolutionary interactions, and how they are beginning to bridge the gap between laboratory and natural evolution. In this Review, Ascensao and Desai discuss how methodological advances in genotype and phenotype manipulation are transforming experimental evolution approaches and providing new insights into the underlying genetics and forces that shape phenotypic evolution.
{"title":"Experimental evolution in an era of molecular manipulation","authors":"Joao A. Ascensao, Michael M. Desai","doi":"10.1038/s41576-025-00867-6","DOIUrl":"10.1038/s41576-025-00867-6","url":null,"abstract":"Laboratory evolution experiments in microbial and viral populations have provided great insight into the dynamics and predictability of evolution. The rise of high-throughput sequencing technologies over the past two decades has driven a massive expansion in the scale and power of these experiments. However, until recently our abilities to connect genetic with phenotypic changes and analyse the molecular basis of adaptation have remained limited. Rapid technical advances to measure and manipulate both genotypes and phenotypes are now providing opportunities to investigate the genetic basis of phenotypic evolution and the forces that drive evolutionary dynamics. Here we review how these methodological advances are being used to predict and manipulate the course of laboratory evolution, analyse eco-evolutionary interactions, and how they are beginning to bridge the gap between laboratory and natural evolution. In this Review, Ascensao and Desai discuss how methodological advances in genotype and phenotype manipulation are transforming experimental evolution approaches and providing new insights into the underlying genetics and forces that shape phenotypic evolution.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 1","pages":"81-95"},"PeriodicalIF":52.0,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144669693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-16DOI: 10.1038/s41576-025-00878-3
Jian Shu
In this Journal Club, Jian Shu recalls a 2006 publication by Takahashi and Yamanaka as well as a 2021 paper introducing AlphaFold to discuss the fascinating potential of cellular reprogramming in the age of artificial intelligence.
{"title":"When cellular reprogramming meets AI: towards de novo cell design","authors":"Jian Shu","doi":"10.1038/s41576-025-00878-3","DOIUrl":"10.1038/s41576-025-00878-3","url":null,"abstract":"In this Journal Club, Jian Shu recalls a 2006 publication by Takahashi and Yamanaka as well as a 2021 paper introducing AlphaFold to discuss the fascinating potential of cellular reprogramming in the age of artificial intelligence.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 9","pages":"585-585"},"PeriodicalIF":52.0,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144640359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-15DOI: 10.1038/s41576-025-00877-4
Liyang Song (, )
Liyang Song presents gsMap, which integrates spatial transcriptomics (ST) data with GWAS summary statistics to assess whether genetic variants in or near genes specifically expressed in an ST data spot are enriched for genetic associations with a trait of interest.
{"title":"Mapping trait-associated cells with spatial transcriptomics","authors":"Liyang Song \u0000 (, )","doi":"10.1038/s41576-025-00877-4","DOIUrl":"10.1038/s41576-025-00877-4","url":null,"abstract":"Liyang Song presents gsMap, which integrates spatial transcriptomics (ST) data with GWAS summary statistics to assess whether genetic variants in or near genes specifically expressed in an ST data spot are enriched for genetic associations with a trait of interest.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 11","pages":"739-739"},"PeriodicalIF":52.0,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144640200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-09DOI: 10.1038/s41576-025-00864-9
Maxwell C. Coyle, Nicole King
The development of a single-celled zygote into a complex, multicellular animal is directed by transcription factors and regulatory RNAs that coordinate spatio-temporal gene expression patterns. Given the morphological complexity of animals, some prior work has hypothesized that the origin of animals required the evolution of unique and markedly complex transcriptional regulatory mechanisms. Such postulated animal innovations include the evolution of greater numbers of transcription factors, new transcription factor families, distal enhancers and the emergence of long non-coding RNAs. Here, we revisit these explanations in light of new genomic and functional data from diverse early-branching animals and close relatives of animals, which provide essential phylogenetic context for reconstructing the origin of animals. These experimental models also offer examples of how some animal developmental pathways were built from core mechanisms inherited from their protistan ancestors. These new data provide fresh perspectives on whether animal origins entailed fundamental innovations in transcriptional regulation or whether, alternatively, a gradual accumulation of smaller changes sufficed to generate the complex developmental and cell differentiation mechanisms of early animals. In this Review, Coyle and King explore how genomic and functional data from diverse species are providing new insights into the types of mechanistic changes that accompanied the evolutionary origin of animals.
{"title":"The evolutionary foundations of transcriptional regulation in animals","authors":"Maxwell C. Coyle, Nicole King","doi":"10.1038/s41576-025-00864-9","DOIUrl":"10.1038/s41576-025-00864-9","url":null,"abstract":"The development of a single-celled zygote into a complex, multicellular animal is directed by transcription factors and regulatory RNAs that coordinate spatio-temporal gene expression patterns. Given the morphological complexity of animals, some prior work has hypothesized that the origin of animals required the evolution of unique and markedly complex transcriptional regulatory mechanisms. Such postulated animal innovations include the evolution of greater numbers of transcription factors, new transcription factor families, distal enhancers and the emergence of long non-coding RNAs. Here, we revisit these explanations in light of new genomic and functional data from diverse early-branching animals and close relatives of animals, which provide essential phylogenetic context for reconstructing the origin of animals. These experimental models also offer examples of how some animal developmental pathways were built from core mechanisms inherited from their protistan ancestors. These new data provide fresh perspectives on whether animal origins entailed fundamental innovations in transcriptional regulation or whether, alternatively, a gradual accumulation of smaller changes sufficed to generate the complex developmental and cell differentiation mechanisms of early animals. In this Review, Coyle and King explore how genomic and functional data from diverse species are providing new insights into the types of mechanistic changes that accompanied the evolutionary origin of animals.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 12","pages":"812-827"},"PeriodicalIF":52.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144586308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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