Pub Date : 2025-10-08DOI: 10.1038/s41576-025-00896-1
Manfred Kayser
Recent advances in forensic genetics, driven by technological innovation coupled with the use of an expanding range of nucleic acid markers, have markedly improved the scope, accuracy and reliability of evidential information obtainable from human biological traces recovered at crime scenes. The majority of these biomarkers have been identified using non-targeted omics approaches, including genomics, transcriptomics, epigenomics and microbiome profiling. Moreover, targeted massively parallel sequencing, in some cases non-targeted whole-genome sequencing, are being applied to the analyses of biological trace material. These approaches and methods are being used for the identification of perpetrators (including monozygotic twins), their relatives or victims of criminal activities; the prediction of phenotypic and behavioural traits of unknown individuals; and the determination of trace characteristics, including tissue type and time of deposition. Recent advances in forensic genetics have improved the range, precision and reliability of forensic information obtainable from biological trace material. The author reviews how non-targeted and targeted omics approaches and methods are improving crime scene analyses being applied for the identification of perpetrators and their relatives or victims, the prediction of phenotypic traits, and the determination of trace characteristics.
{"title":"Forensic genetics in the omics era","authors":"Manfred Kayser","doi":"10.1038/s41576-025-00896-1","DOIUrl":"10.1038/s41576-025-00896-1","url":null,"abstract":"Recent advances in forensic genetics, driven by technological innovation coupled with the use of an expanding range of nucleic acid markers, have markedly improved the scope, accuracy and reliability of evidential information obtainable from human biological traces recovered at crime scenes. The majority of these biomarkers have been identified using non-targeted omics approaches, including genomics, transcriptomics, epigenomics and microbiome profiling. Moreover, targeted massively parallel sequencing, in some cases non-targeted whole-genome sequencing, are being applied to the analyses of biological trace material. These approaches and methods are being used for the identification of perpetrators (including monozygotic twins), their relatives or victims of criminal activities; the prediction of phenotypic and behavioural traits of unknown individuals; and the determination of trace characteristics, including tissue type and time of deposition. Recent advances in forensic genetics have improved the range, precision and reliability of forensic information obtainable from biological trace material. The author reviews how non-targeted and targeted omics approaches and methods are improving crime scene analyses being applied for the identification of perpetrators and their relatives or victims, the prediction of phenotypic traits, and the determination of trace characteristics.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 2","pages":"170-186"},"PeriodicalIF":52.0,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145246592","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 : 2025-10-07DOI: 10.1038/s41576-025-00902-6
Tzachi Hagai
In this Journal Club, Tzachi Hagai highlights a 2005 paper by Sawyer et al. that tested the functional relationship of evolutionary changes in immune genes with infection outcomes.
{"title":"Host–pathogen interactions shape human evolution and future pandemics","authors":"Tzachi Hagai","doi":"10.1038/s41576-025-00902-6","DOIUrl":"10.1038/s41576-025-00902-6","url":null,"abstract":"In this Journal Club, Tzachi Hagai highlights a 2005 paper by Sawyer et al. that tested the functional relationship of evolutionary changes in immune genes with infection outcomes.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 2","pages":"115-115"},"PeriodicalIF":52.0,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145241094","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 : 2025-10-01DOI: 10.1038/s41576-025-00901-7
Sara Suliman
Sara Suliman describes a seminal 2013 publication by Comas et al. that investigated the origins of the tuberculosis-causing bacteria and its coevolution with diverse human populations.
Sara Suliman描述了Comas等人在2013年发表的一篇开创性论文，该论文调查了导致结核病的细菌的起源及其与不同人群的共同进化。
{"title":"The evolution of Mycobacterium tuberculosis as humans migrated out of Africa","authors":"Sara Suliman","doi":"10.1038/s41576-025-00901-7","DOIUrl":"10.1038/s41576-025-00901-7","url":null,"abstract":"Sara Suliman describes a seminal 2013 publication by Comas et al. that investigated the origins of the tuberculosis-causing bacteria and its coevolution with diverse human populations.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 1","pages":"11-11"},"PeriodicalIF":52.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145203856","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 : 2025-09-30DOI: 10.1038/s41576-025-00892-5
Enikő Lázár, Joakim Lundeberg
Tissue architecture is a product of a multilayered molecular landscape, where even subtle disruptions in the spatial context can initiate or reflect disease processes. Recent advances in high-throughput spatial omics technologies have enabled the investigation of this complexity in stunning detail, providing groundbreaking insights into how spatial molecular organization shapes health and disease. Spatial analysis empowers the discovery of developmental and disease-associated molecular signatures, cell states and multicellular niches, as well as the evaluation of disease heterogeneity within and across organs. This Review examines spatially resolved pathological molecular alterations in a wide range of disease processes, such as developmental disorders, tumorigenesis, fibrosis and injury responses, neurodegeneration, infection and inflammation, through the lens of these universal biological frameworks. We discuss challenges, opportunities and promising examples in advancing these technologies to clinical applications, including the increasing importance of artificial intelligence. Finally, we explore possible avenues for a more comprehensive, multidimensional assessment of tissues. Spatial omics has empowered the discovery of developmental and disease-associated molecular signatures, cell states and multicellular niches, as well as the evaluation of disease heterogeneity within and across organs. The authors review spatially resolved molecular changes across diseases and discuss the potential of spatial multi-omics for clinical applications, including the recent impact of artificial intelligence.
{"title":"Spatial architecture of development and disease","authors":"Enikő Lázár, Joakim Lundeberg","doi":"10.1038/s41576-025-00892-5","DOIUrl":"10.1038/s41576-025-00892-5","url":null,"abstract":"Tissue architecture is a product of a multilayered molecular landscape, where even subtle disruptions in the spatial context can initiate or reflect disease processes. Recent advances in high-throughput spatial omics technologies have enabled the investigation of this complexity in stunning detail, providing groundbreaking insights into how spatial molecular organization shapes health and disease. Spatial analysis empowers the discovery of developmental and disease-associated molecular signatures, cell states and multicellular niches, as well as the evaluation of disease heterogeneity within and across organs. This Review examines spatially resolved pathological molecular alterations in a wide range of disease processes, such as developmental disorders, tumorigenesis, fibrosis and injury responses, neurodegeneration, infection and inflammation, through the lens of these universal biological frameworks. We discuss challenges, opportunities and promising examples in advancing these technologies to clinical applications, including the increasing importance of artificial intelligence. Finally, we explore possible avenues for a more comprehensive, multidimensional assessment of tissues. Spatial omics has empowered the discovery of developmental and disease-associated molecular signatures, cell states and multicellular niches, as well as the evaluation of disease heterogeneity within and across organs. The authors review spatially resolved molecular changes across diseases and discuss the potential of spatial multi-omics for clinical applications, including the recent impact of artificial intelligence.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 2","pages":"118-136"},"PeriodicalIF":52.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145194676","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 : 2025-09-26DOI: 10.1038/s41576-025-00898-z
Gerald Mboowa
Gerald Mboowa reflects on the dual legacy of a 2021 study by Frangoul et al., which demonstrated safe and effective CRISPR-based editing to treat sickle-cell disease and β-thalassemia, as both a triumph of modern science and a call to action for global health.
{"title":"A clinical milestone for CRISPR in sickle-cell disease","authors":"Gerald Mboowa","doi":"10.1038/s41576-025-00898-z","DOIUrl":"10.1038/s41576-025-00898-z","url":null,"abstract":"Gerald Mboowa reflects on the dual legacy of a 2021 study by Frangoul et al., which demonstrated safe and effective CRISPR-based editing to treat sickle-cell disease and β-thalassemia, as both a triumph of modern science and a call to action for global health.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 12","pages":"810-810"},"PeriodicalIF":52.0,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145153413","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 : 2025-09-24DOI: 10.1038/s41576-025-00895-2
Quan Sun, Yun Li
Haplotype phasing — to determine which genetic variants reside on the same chromosome — and genotype imputation — to infer unobserved genotypes — have become indispensable steps to improve genome coverage for genomic analyses such as genome-wide association studies. Several tools exist for haplotype phasing and genotype imputation, all of which have continuously evolved to accommodate the increasing sample sizes of genomic studies and rapidly improving sequencing technologies. To fully leverage these recent advances, researchers must deliberate several practical considerations, including tool choice, quality control filters, data privacy concerns and reference panel choice. Looking ahead, long-read sequencing technologies are poised to bring novel opportunities to this field and drive methodological development. Haplotype phasing and genotype imputation improve genomic analyses by determining which variants occur together on a chromosome and inferring unobserved varants, respectively. In this Review, Sun and Li describe how tools for haplotype phasing and genotype imputation have evolved to accommodate increasingly larger genomic datasets and new sequencing technologies.
{"title":"Advances in haplotype phasing and genotype imputation","authors":"Quan Sun, Yun Li","doi":"10.1038/s41576-025-00895-2","DOIUrl":"10.1038/s41576-025-00895-2","url":null,"abstract":"Haplotype phasing — to determine which genetic variants reside on the same chromosome — and genotype imputation — to infer unobserved genotypes — have become indispensable steps to improve genome coverage for genomic analyses such as genome-wide association studies. Several tools exist for haplotype phasing and genotype imputation, all of which have continuously evolved to accommodate the increasing sample sizes of genomic studies and rapidly improving sequencing technologies. To fully leverage these recent advances, researchers must deliberate several practical considerations, including tool choice, quality control filters, data privacy concerns and reference panel choice. Looking ahead, long-read sequencing technologies are poised to bring novel opportunities to this field and drive methodological development. Haplotype phasing and genotype imputation improve genomic analyses by determining which variants occur together on a chromosome and inferring unobserved varants, respectively. In this Review, Sun and Li describe how tools for haplotype phasing and genotype imputation have evolved to accommodate increasingly larger genomic datasets and new sequencing technologies.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"27 2","pages":"155-169"},"PeriodicalIF":52.0,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145134339","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 : 2025-09-16DOI: 10.1038/s41576-025-00887-2
Sarthak Tiwari, Alireza Karbalayghareh, Christina S. Leslie
Deep learning models have made impressive strides in decoding the regulatory genome, but key challenges remain unsolved. In this Comment, the authors overview the latest deep learning models for predicting regulatory function from genomic sequence and highlight key topics going forward, including the trade-off between specialized and general models, multitasking across cell types, and training on genetic variation and diverse species.
{"title":"Predicting the regulatory genome","authors":"Sarthak Tiwari, Alireza Karbalayghareh, Christina S. Leslie","doi":"10.1038/s41576-025-00887-2","DOIUrl":"10.1038/s41576-025-00887-2","url":null,"abstract":"Deep learning models have made impressive strides in decoding the regulatory genome, but key challenges remain unsolved. In this Comment, the authors overview the latest deep learning models for predicting regulatory function from genomic sequence and highlight key topics going forward, including the trade-off between specialized and general models, multitasking across cell types, and training on genetic variation and diverse species.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 10","pages":"659-660"},"PeriodicalIF":52.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145067697","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 : 2025-09-16DOI: 10.1038/s41576-025-00882-7
Yi Xiang See, Tim Stuart, Jay W. Shin
Recent advances in single-cell profiling technologies now enable routine and scalable measurements of cis-regulatory element activity across diverse cell types, disease states and genetic backgrounds. It is time to coordinate a global effort to systematically map cis-regulatory element function at single-cell resolution. In this Comment, the authors outline some key next steps to advance our understanding of cis-regulatory elements at single-cell resolution, which includes harmonizing global efforts to construct a comprehensive single-cell atlas of gene regulation.
{"title":"Cis-regulatory elements at cellular resolution","authors":"Yi Xiang See, Tim Stuart, Jay W. Shin","doi":"10.1038/s41576-025-00882-7","DOIUrl":"10.1038/s41576-025-00882-7","url":null,"abstract":"Recent advances in single-cell profiling technologies now enable routine and scalable measurements of cis-regulatory element activity across diverse cell types, disease states and genetic backgrounds. It is time to coordinate a global effort to systematically map cis-regulatory element function at single-cell resolution. In this Comment, the authors outline some key next steps to advance our understanding of cis-regulatory elements at single-cell resolution, which includes harmonizing global efforts to construct a comprehensive single-cell atlas of gene regulation.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 10","pages":"653-654"},"PeriodicalIF":52.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145067699","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 : 2025-09-16DOI: 10.1038/s41576-025-00885-4
Sushant Kumar, Mark Gerstein
Large-scale annotation efforts over the past two decades have identified regulatory regions and networks through functional genomics and evolutionary analyses. The challenge now will be to incorporate the many ‘heterogeneities’ of gene regulation — across cell types, developmental stages and individuals — into regulatory annotation based on new experimental and computational approaches. After more than two decades of large-scale efforts to annotate the regulatory genome, Sushant Kumar and Mark Gerstein forecast how new technologies and experimental approaches will pave the way in mapping regulatory elements across cell types, developmental stages and genetically diverse individuals.
{"title":"Regulatory genome annotation","authors":"Sushant Kumar, Mark Gerstein","doi":"10.1038/s41576-025-00885-4","DOIUrl":"10.1038/s41576-025-00885-4","url":null,"abstract":"Large-scale annotation efforts over the past two decades have identified regulatory regions and networks through functional genomics and evolutionary analyses. The challenge now will be to incorporate the many ‘heterogeneities’ of gene regulation — across cell types, developmental stages and individuals — into regulatory annotation based on new experimental and computational approaches. After more than two decades of large-scale efforts to annotate the regulatory genome, Sushant Kumar and Mark Gerstein forecast how new technologies and experimental approaches will pave the way in mapping regulatory elements across cell types, developmental stages and genetically diverse individuals.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 10","pages":"661-662"},"PeriodicalIF":52.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145067700","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 : 2025-09-16DOI: 10.1038/s41576-025-00879-2
Stephen B. Montgomery
Biobank-scale studies of gene expression and proteomics are providing new opportunities to study gene regulation and its effect on traits and diseases. Moving from small cohorts to studies of thousands of people with regulatory genomics data will accelerate the use of gene regulation and non-coding variation in precision health. Studies of human regulatory genomics are being performed at biobank scales, with data from tens of thousands of individuals. Stephen Montgomery describes how these datasets will advance our understanding of how variation in gene regulation shapes human traits and disease.
{"title":"Regulatory genomics at biobank scales","authors":"Stephen B. Montgomery","doi":"10.1038/s41576-025-00879-2","DOIUrl":"10.1038/s41576-025-00879-2","url":null,"abstract":"Biobank-scale studies of gene expression and proteomics are providing new opportunities to study gene regulation and its effect on traits and diseases. Moving from small cohorts to studies of thousands of people with regulatory genomics data will accelerate the use of gene regulation and non-coding variation in precision health. Studies of human regulatory genomics are being performed at biobank scales, with data from tens of thousands of individuals. Stephen Montgomery describes how these datasets will advance our understanding of how variation in gene regulation shapes human traits and disease.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 10","pages":"657-658"},"PeriodicalIF":52.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145067756","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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