Pub Date : 2025-11-06DOI: 10.1038/s41576-025-00904-4
Robert Chen, Áine Duffy, Ron Do
Drug development faces persistent challenges, with high attrition rates and unexpected adverse effects contributing to clinical trial failures. The recent convergence of large-scale biobanks, multi-omics data and computational methods, including machine learning, has led to advances in genetics-driven drug discovery, offering new opportunities to refine target selection and reduce late-stage risk. Integrating multiple lines of evidence centred on human genetics within a probabilistic framework enables the systematic prioritization of drug targets, prediction of adverse effects, and identification of drug repurposing opportunities. In this Review, we explore how these integrative approaches can address unmet clinical needs in diverse disease contexts, focusing on complex diseases. In this Review, Chen et al. discuss how the advancement and integration of large-scale genetic resources, multi-omics data and sophisticated computational tools are improving drug development pipelines.
{"title":"Genomics of drug target prioritization for complex diseases","authors":"Robert Chen, Áine Duffy, Ron Do","doi":"10.1038/s41576-025-00904-4","DOIUrl":"10.1038/s41576-025-00904-4","url":null,"abstract":"Drug development faces persistent challenges, with high attrition rates and unexpected adverse effects contributing to clinical trial failures. The recent convergence of large-scale biobanks, multi-omics data and computational methods, including machine learning, has led to advances in genetics-driven drug discovery, offering new opportunities to refine target selection and reduce late-stage risk. Integrating multiple lines of evidence centred on human genetics within a probabilistic framework enables the systematic prioritization of drug targets, prediction of adverse effects, and identification of drug repurposing opportunities. In this Review, we explore how these integrative approaches can address unmet clinical needs in diverse disease contexts, focusing on complex diseases. In this Review, Chen et al. discuss how the advancement and integration of large-scale genetic resources, multi-omics data and sophisticated computational tools are improving drug development pipelines.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 3","pages":"231-245"},"PeriodicalIF":52.0,"publicationDate":"2025-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145447222","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 : 2025-11-04DOI: 10.1038/s41576-025-00903-5
Tomas Kay, Patrick K. Piekarski, Daniel J. C. Kronauer
{"title":"Convergent evolution of a conserved molecular network underlies parenting and sociality","authors":"Tomas Kay, Patrick K. Piekarski, Daniel J. C. Kronauer","doi":"10.1038/s41576-025-00903-5","DOIUrl":"https://doi.org/10.1038/s41576-025-00903-5","url":null,"abstract":"","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"88 1","pages":""},"PeriodicalIF":42.7,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145434677","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 : 2025-11-03DOI: 10.1038/s41576-025-00909-z
Kathryn E. Holt
The scale-up of microbial genomics has seen notable advances in understanding the dynamics of antimicrobial resistance (AMR) across species, environments and ecosystems. To gain meaningful insights that can ultimately inform AMR control strategies, stronger analytical frameworks are needed that integrate data across temporal, spatial and molecular scales. Microbial genomics can improve our understanding of antimicrobial resistance dynamics across ecosystems. In this Comment, Kathryn Holt emphasizes the interconnectedness of human, animal and environmental health and calls for greater integration of microbial genomic data through robust analytical frameworks to unravel the complexity of antimicrobial resistance dynamics.
{"title":"Microbial genomics for antimicrobial resistance ecology and action","authors":"Kathryn E. Holt","doi":"10.1038/s41576-025-00909-z","DOIUrl":"10.1038/s41576-025-00909-z","url":null,"abstract":"The scale-up of microbial genomics has seen notable advances in understanding the dynamics of antimicrobial resistance (AMR) across species, environments and ecosystems. To gain meaningful insights that can ultimately inform AMR control strategies, stronger analytical frameworks are needed that integrate data across temporal, spatial and molecular scales. Microbial genomics can improve our understanding of antimicrobial resistance dynamics across ecosystems. In this Comment, Kathryn Holt emphasizes the interconnectedness of human, animal and environmental health and calls for greater integration of microbial genomic data through robust analytical frameworks to unravel the complexity of antimicrobial resistance dynamics.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 1","pages":"7-8"},"PeriodicalIF":52.0,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145427382","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 : 2025-11-03DOI: 10.1038/s41576-025-00914-2
Peter K. Koo
In this Journal Club, Peter Koo reflects on the 2021 publication of Enformer and its impact on the use of deep learning for modelling the regulatory genome.
{"title":"Decoding the regulatory genome with large-scale deep learning","authors":"Peter K. Koo","doi":"10.1038/s41576-025-00914-2","DOIUrl":"10.1038/s41576-025-00914-2","url":null,"abstract":"In this Journal Club, Peter Koo reflects on the 2021 publication of Enformer and its impact on the use of deep learning for modelling the regulatory genome.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 2","pages":"117-117"},"PeriodicalIF":52.0,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145427381","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 : 2025-10-30DOI: 10.1038/s41576-025-00910-6
Jaime Martinez-Urtaza
Jaime Martinez-Urtaza reflects on two papers by Smith et al., who found that bacteria exist along a continuum from clonal to recombining populations, and introduced the concept of an ‘epidemic’ microbial population structure.
{"title":"From clonality to complexity: a journey through microbial ecology and evolution","authors":"Jaime Martinez-Urtaza","doi":"10.1038/s41576-025-00910-6","DOIUrl":"10.1038/s41576-025-00910-6","url":null,"abstract":"Jaime Martinez-Urtaza reflects on two papers by Smith et al., who found that bacteria exist along a continuum from clonal to recombining populations, and introduced the concept of an ‘epidemic’ microbial population structure.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 1","pages":"10-10"},"PeriodicalIF":52.0,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145397426","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 : 2025-10-30DOI: 10.1038/s41576-025-00911-5
Luis H. Orellana
In this Journal Club, Luis Orellana recalls a 2005 publication by Konstantinidis and Tiedje that introduced average nucleotide identity as a sequence-based metric to determine the relatedness between two genomes, which helped to operationally define bacterial species.
{"title":"Average nucleotide identity — the backbone of modern ecological genomics","authors":"Luis H. Orellana","doi":"10.1038/s41576-025-00911-5","DOIUrl":"10.1038/s41576-025-00911-5","url":null,"abstract":"In this Journal Club, Luis Orellana recalls a 2005 publication by Konstantinidis and Tiedje that introduced average nucleotide identity as a sequence-based metric to determine the relatedness between two genomes, which helped to operationally define bacterial species.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 1","pages":"9-9"},"PeriodicalIF":52.0,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145397424","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 : 2025-10-22DOI: 10.1038/s41576-025-00905-3
Jean Fan
Jean Fan recounts a 2015 paper by Martincorena et al. that revealed oncogenic mutations in normal tissues, also highlighting how the latest spatial technologies can now be used to study the spatial contextual impact of these mutations.
Jean Fan讲述了Martincorena等人在2015年发表的一篇论文，该论文揭示了正常组织中的致癌突变，并强调了现在如何使用最新的空间技术来研究这些突变的空间背景影响。
{"title":"Revisiting the somatic mutation theory of cancer pathogenesis","authors":"Jean Fan","doi":"10.1038/s41576-025-00905-3","DOIUrl":"10.1038/s41576-025-00905-3","url":null,"abstract":"Jean Fan recounts a 2015 paper by Martincorena et al. that revealed oncogenic mutations in normal tissues, also highlighting how the latest spatial technologies can now be used to study the spatial contextual impact of these mutations.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 2","pages":"116-116"},"PeriodicalIF":52.0,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145339430","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 : 2025-10-17DOI: 10.1038/s41576-025-00899-y
Samantha A. Morris
Manipulating cell identity through transcription factor-mediated reprogramming, induced pluripotency or directed differentiation holds promise for disease modelling and regenerative medicine. Yet the cells produced by these methods often do not fully recapitulate the molecular and functional characteristics of their native counterparts. Immaturity, low fidelity and heterogeneity remain barriers, limiting reliability for modelling human disease and therapeutic use. Recent advances in single-cell genomic technologies, integrative computational frameworks and emerging molecular recording tools are beginning to reveal the mechanisms underlying incomplete or inefficient reprogramming and highlight tractable failure points. Together, these approaches could support mechanism-guided protocol design and stepwise gains in fidelity, maturity and purity, potentially moving engineered cells towards clinical relevance and informing design principles for next-generation reprogramming strategies. Morris discusses how single-cell genomics and computational tools expose failure points in reprogramming and guide protocols that improve the fidelity, maturity and purity of engineered cells, advancing their use in regenerative medicine and disease modelling.
{"title":"Redefining cellular reprogramming with advanced genomic technologies","authors":"Samantha A. Morris","doi":"10.1038/s41576-025-00899-y","DOIUrl":"10.1038/s41576-025-00899-y","url":null,"abstract":"Manipulating cell identity through transcription factor-mediated reprogramming, induced pluripotency or directed differentiation holds promise for disease modelling and regenerative medicine. Yet the cells produced by these methods often do not fully recapitulate the molecular and functional characteristics of their native counterparts. Immaturity, low fidelity and heterogeneity remain barriers, limiting reliability for modelling human disease and therapeutic use. Recent advances in single-cell genomic technologies, integrative computational frameworks and emerging molecular recording tools are beginning to reveal the mechanisms underlying incomplete or inefficient reprogramming and highlight tractable failure points. Together, these approaches could support mechanism-guided protocol design and stepwise gains in fidelity, maturity and purity, potentially moving engineered cells towards clinical relevance and informing design principles for next-generation reprogramming strategies. Morris discusses how single-cell genomics and computational tools expose failure points in reprogramming and guide protocols that improve the fidelity, maturity and purity of engineered cells, advancing their use in regenerative medicine and disease modelling.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 3","pages":"193-211"},"PeriodicalIF":52.0,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145311243","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 : 2025-10-16DOI: 10.1038/s41576-025-00906-2
Nicole S. Webster
Microorganisms are central to climate stability, food security and biodiversity, yet they remain absent from global sustainability frameworks. Recognizing and mobilizing their power is essential if we are to meet the challenges of the coming decades. Microorganisms are central to climate stability, food security and biodiversity, yet they remain absent from global sustainability frameworks. In this Comment, Nicole Webster highlights the power of eco-evolutionary genomics in transforming sustainability science and calls for the inclusion of microbes in global policies.
{"title":"Microorganisms as architects of a sustainable future","authors":"Nicole S. Webster","doi":"10.1038/s41576-025-00906-2","DOIUrl":"10.1038/s41576-025-00906-2","url":null,"abstract":"Microorganisms are central to climate stability, food security and biodiversity, yet they remain absent from global sustainability frameworks. Recognizing and mobilizing their power is essential if we are to meet the challenges of the coming decades. Microorganisms are central to climate stability, food security and biodiversity, yet they remain absent from global sustainability frameworks. In this Comment, Nicole Webster highlights the power of eco-evolutionary genomics in transforming sustainability science and calls for the inclusion of microbes in global policies.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 1","pages":"5-6"},"PeriodicalIF":52.0,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145305593","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 : 2025-10-10DOI: 10.1038/s41576-025-00900-8
Iftikhar J. Kullo
Genome-wide association studies have identified thousands of single-nucleotide variants that are associated with complex traits, including cardiometabolic diseases, cancers and neurological disorders. Polygenic risk scores (PRSs), which aggregate the effects of these variants, can help to identify individuals who are at increased risk of developing such diseases. As PRSs are typically only weakly associated with conventional risk factors for these diseases, they have incremental predictive value and are beginning to be incorporated into clinical practice to guide early detection and preventive strategies. However, challenges to their use — such as suboptimal precision, poor transferability across diverse populations and low familiarity among patients and providers with the concept of polygenic risk — must be addressed before their broader clinical adoption. This Review explores the current state of the field, highlights key challenges and outlines future directions for the use of PRSs to improve risk prediction and to advance personalized prevention in clinical care. This article reviews the current state of implementation of polygenic risk scores in the clinical setting, highlights key challenges and outlines future directions for the use of such scores to improve disease risk prediction and to enable personalized prevention.
{"title":"Clinical use of polygenic risk scores: current status, barriers and future directions","authors":"Iftikhar J. Kullo","doi":"10.1038/s41576-025-00900-8","DOIUrl":"10.1038/s41576-025-00900-8","url":null,"abstract":"Genome-wide association studies have identified thousands of single-nucleotide variants that are associated with complex traits, including cardiometabolic diseases, cancers and neurological disorders. Polygenic risk scores (PRSs), which aggregate the effects of these variants, can help to identify individuals who are at increased risk of developing such diseases. As PRSs are typically only weakly associated with conventional risk factors for these diseases, they have incremental predictive value and are beginning to be incorporated into clinical practice to guide early detection and preventive strategies. However, challenges to their use — such as suboptimal precision, poor transferability across diverse populations and low familiarity among patients and providers with the concept of polygenic risk — must be addressed before their broader clinical adoption. This Review explores the current state of the field, highlights key challenges and outlines future directions for the use of PRSs to improve risk prediction and to advance personalized prevention in clinical care. This article reviews the current state of implementation of polygenic risk scores in the clinical setting, highlights key challenges and outlines future directions for the use of such scores to improve disease risk prediction and to enable personalized prevention.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 3","pages":"246-263"},"PeriodicalIF":52.0,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261296","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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