Pub Date : 2024-10-21DOI: 10.1038/s41576-024-00780-4
Benjamin R. Sabari, Anthony A. Hyman, Denes Hnisz
Biomolecular condensates are thought to create subcellular microenvironments that regulate specific biochemical activities. Extensive in vitro work has helped link condensate formation to a wide range of cellular processes, including gene expression, nuclear transport, signalling and stress responses. However, testing the relationship between condensate formation and function in cells is more challenging. In particular, the extent to which the cellular functions of condensates depend on the nature of the molecular interactions through which the condensates form is a major outstanding question. Here, we review results from recent genetic complementation experiments in cells, and highlight how genetic complementation provides important insights into cellular functions and functional specificity of biomolecular condensates. Combined with observations from human genetic disease, these experiments suggest that diverse condensate-promoting regions within cellular proteins confer different condensate compositions, biophysical properties and functions.
{"title":"Functional specificity in biomolecular condensates revealed by genetic complementation","authors":"Benjamin R. Sabari, Anthony A. Hyman, Denes Hnisz","doi":"10.1038/s41576-024-00780-4","DOIUrl":"https://doi.org/10.1038/s41576-024-00780-4","url":null,"abstract":"<p>Biomolecular condensates are thought to create subcellular microenvironments that regulate specific biochemical activities. Extensive in vitro work has helped link condensate formation to a wide range of cellular processes, including gene expression, nuclear transport, signalling and stress responses. However, testing the relationship between condensate formation and function in cells is more challenging. In particular, the extent to which the cellular functions of condensates depend on the nature of the molecular interactions through which the condensates form is a major outstanding question. Here, we review results from recent genetic complementation experiments in cells, and highlight how genetic complementation provides important insights into cellular functions and functional specificity of biomolecular condensates. Combined with observations from human genetic disease, these experiments suggest that diverse condensate-promoting regions within cellular proteins confer different condensate compositions, biophysical properties and functions.</p>","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"215 1","pages":""},"PeriodicalIF":42.7,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142452395","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 : 2024-10-18DOI: 10.1038/s41576-024-00789-9
Vasiliki Rahimzadeh, Sarah C. Nelson, Adrian Thorogood, Jonathan Lawson, Stephanie M. Fullerton
Cloud platforms offer distinct advantages, but questions remain about how to ethically and efficiently manage human genomic data in the cloud. Data governance needs to be adapted to ensure transparency and security for research participants, as well as equitable and sustainable access for researchers. Rahimzadeh et al. discuss the ethical, legal and social implications of storing and analysing human genomic data in the cloud and provide recommendations and new research directions for future, trustworthy cloud-based genomic data access and management.
{"title":"Ethical governance for genomic data science in the cloud","authors":"Vasiliki Rahimzadeh, Sarah C. Nelson, Adrian Thorogood, Jonathan Lawson, Stephanie M. Fullerton","doi":"10.1038/s41576-024-00789-9","DOIUrl":"10.1038/s41576-024-00789-9","url":null,"abstract":"Cloud platforms offer distinct advantages, but questions remain about how to ethically and efficiently manage human genomic data in the cloud. Data governance needs to be adapted to ensure transparency and security for research participants, as well as equitable and sustainable access for researchers. Rahimzadeh et al. discuss the ethical, legal and social implications of storing and analysing human genomic data in the cloud and provide recommendations and new research directions for future, trustworthy cloud-based genomic data access and management.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 2","pages":"75-77"},"PeriodicalIF":39.1,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142448156","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 : 2024-10-16DOI: 10.1038/s41576-024-00790-2
Berna Sozen
In this Journal Club, Berna Sozen recalls the metabolic gradient theory proposed by Charles Manning Child in the early 20th century, which posited that metabolic gradients drive cellular differentiation and tissue patterning.
{"title":"A brief history of metabolic gradient theory","authors":"Berna Sozen","doi":"10.1038/s41576-024-00790-2","DOIUrl":"10.1038/s41576-024-00790-2","url":null,"abstract":"In this Journal Club, Berna Sozen recalls the metabolic gradient theory proposed by Charles Manning Child in the early 20th century, which posited that metabolic gradients drive cellular differentiation and tissue patterning.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 1","pages":"5-5"},"PeriodicalIF":39.1,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142440503","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 : 2024-10-09DOI: 10.1038/s41576-024-00787-x
Shila Ghazanfar
In this Journal Club, Shila Ghazanfar highlights a seminal paper by Levsky et al. that paved the way for contemporary single-cell spatial transcriptomics.
{"title":"Single-cell expression profiling has its roots in in situ techniques","authors":"Shila Ghazanfar","doi":"10.1038/s41576-024-00787-x","DOIUrl":"10.1038/s41576-024-00787-x","url":null,"abstract":"In this Journal Club, Shila Ghazanfar highlights a seminal paper by Levsky et al. that paved the way for contemporary single-cell spatial transcriptomics.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"25 12","pages":"828-828"},"PeriodicalIF":39.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142385114","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 : 2024-10-08DOI: 10.1038/s41576-024-00785-z
Edroaldo Lummertz da Rocha
In this Journal Club article, Edroaldo Lummertz da Rocha discusses two papers that provided important insights into how tumour cells communicate with distant organs to establish pre-metastatic niches.
在这篇期刊俱乐部文章中，Edroaldo Lummertz da Rocha讨论了两篇论文，这两篇论文提供了关于肿瘤细胞如何与远处器官交流以建立转移前龛位的重要见解。
{"title":"Systemic cell–cell communication in cancer","authors":"Edroaldo Lummertz da Rocha","doi":"10.1038/s41576-024-00785-z","DOIUrl":"10.1038/s41576-024-00785-z","url":null,"abstract":"In this Journal Club article, Edroaldo Lummertz da Rocha discusses two papers that provided important insights into how tumour cells communicate with distant organs to establish pre-metastatic niches.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 1","pages":"4-4"},"PeriodicalIF":39.1,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142384360","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 : 2024-10-07DOI: 10.1038/s41576-024-00778-y
Laura Harris, Ellen M. McDonagh, Xiaolei Zhang, Katherine Fawcett, Amy Foreman, Petr Daneck, Panagiotis I. Sergouniotis, Helen Parkinson, Francesco Mazzarotto, Michael Inouye, Edward J. Hollox, Ewan Birney, Tomas Fitzgerald
Decades of genetic association testing in human cohorts have provided important insights into the genetic architecture and biological underpinnings of complex traits and diseases. However, for certain traits, genome-wide association studies (GWAS) for common SNPs are approaching signal saturation, which underscores the need to explore other types of genetic variation to understand the genetic basis of traits and diseases. Copy number variation (CNV) is an important source of heritability that is well known to functionally affect human traits. Recent technological and computational advances enable the large-scale, genome-wide evaluation of CNVs, with implications for downstream applications such as polygenic risk scoring and drug target identification. Here, we review the current state of CNV-GWAS, discuss current limitations in resource infrastructure that need to be overcome to enable the wider uptake of CNV-GWAS results, highlight emerging opportunities and suggest guidelines and standards for future GWAS for genetic variation beyond SNPs at scale. With SNP-based genome-wide association studies (GWAS) nearing signal saturation, exploring copy number variation (CNV) can offer new insights into the genetic architecture of complex traits. The authors review recent advances that enable large-scale CNV-based GWAS and their likely impact on downstream analyses, such as polygenic risk scoring and drug target identification.
{"title":"Genome-wide association testing beyond SNPs","authors":"Laura Harris, Ellen M. McDonagh, Xiaolei Zhang, Katherine Fawcett, Amy Foreman, Petr Daneck, Panagiotis I. Sergouniotis, Helen Parkinson, Francesco Mazzarotto, Michael Inouye, Edward J. Hollox, Ewan Birney, Tomas Fitzgerald","doi":"10.1038/s41576-024-00778-y","DOIUrl":"10.1038/s41576-024-00778-y","url":null,"abstract":"Decades of genetic association testing in human cohorts have provided important insights into the genetic architecture and biological underpinnings of complex traits and diseases. However, for certain traits, genome-wide association studies (GWAS) for common SNPs are approaching signal saturation, which underscores the need to explore other types of genetic variation to understand the genetic basis of traits and diseases. Copy number variation (CNV) is an important source of heritability that is well known to functionally affect human traits. Recent technological and computational advances enable the large-scale, genome-wide evaluation of CNVs, with implications for downstream applications such as polygenic risk scoring and drug target identification. Here, we review the current state of CNV-GWAS, discuss current limitations in resource infrastructure that need to be overcome to enable the wider uptake of CNV-GWAS results, highlight emerging opportunities and suggest guidelines and standards for future GWAS for genetic variation beyond SNPs at scale. With SNP-based genome-wide association studies (GWAS) nearing signal saturation, exploring copy number variation (CNV) can offer new insights into the genetic architecture of complex traits. The authors review recent advances that enable large-scale CNV-based GWAS and their likely impact on downstream analyses, such as polygenic risk scoring and drug target identification.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 3","pages":"156-170"},"PeriodicalIF":39.1,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142383638","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 : 2024-10-07DOI: 10.1038/s41576-024-00776-0
Zornitza Stark, David Glazer, Oliver Hofmann, Augusto Rendon, Christian R. Marshall, Geoffrey S. Ginsburg, Chris Lunt, Naomi Allen, Mark Effingham, Jillian Hastings Ward, Sue L. Hill, Raghib Ali, Peter Goodhand, Angela Page, Heidi L. Rehm, Kathryn N. North, Richard H. Scott
Genomic data from millions of individuals have been generated worldwide to drive discovery and clinical impact in precision medicine. Lowering the barriers to using these data collectively is needed to equitably realize the benefits of the diversity and scale of population data. We examine the current landscape of global genomic data sharing, including the evolution of data sharing models from data aggregation through to data visiting, and for certain use cases, cross-cohort analysis using federated approaches across multiple environments. We highlight emerging examples of best practice relating to participant, patient and community engagement; evolution of technical standards, tools and infrastructure; and impact of research and health-care policy. We outline 12 actions we can all take together to scale up efforts to enable safe global data sharing and move beyond projects demonstrating feasibility to routinely cross-analysing research and clinical data sets, optimizing benefit. Global genomic data sharing enhances precision medicine. In this Roadmap, the authors outline evolving data-sharing models, best practices and policy impacts, and propose 12 actions to systematically scale up genomic data sharing.
{"title":"A call to action to scale up research and clinical genomic data sharing","authors":"Zornitza Stark, David Glazer, Oliver Hofmann, Augusto Rendon, Christian R. Marshall, Geoffrey S. Ginsburg, Chris Lunt, Naomi Allen, Mark Effingham, Jillian Hastings Ward, Sue L. Hill, Raghib Ali, Peter Goodhand, Angela Page, Heidi L. Rehm, Kathryn N. North, Richard H. Scott","doi":"10.1038/s41576-024-00776-0","DOIUrl":"10.1038/s41576-024-00776-0","url":null,"abstract":"Genomic data from millions of individuals have been generated worldwide to drive discovery and clinical impact in precision medicine. Lowering the barriers to using these data collectively is needed to equitably realize the benefits of the diversity and scale of population data. We examine the current landscape of global genomic data sharing, including the evolution of data sharing models from data aggregation through to data visiting, and for certain use cases, cross-cohort analysis using federated approaches across multiple environments. We highlight emerging examples of best practice relating to participant, patient and community engagement; evolution of technical standards, tools and infrastructure; and impact of research and health-care policy. We outline 12 actions we can all take together to scale up efforts to enable safe global data sharing and move beyond projects demonstrating feasibility to routinely cross-analysing research and clinical data sets, optimizing benefit. Global genomic data sharing enhances precision medicine. In this Roadmap, the authors outline evolving data-sharing models, best practices and policy impacts, and propose 12 actions to systematically scale up genomic data sharing.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 2","pages":"141-147"},"PeriodicalIF":39.1,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41576-024-00776-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142383639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-10-03DOI: 10.1038/s41576-024-00784-0
Shengbao Suo
In this Journal Club, Shengbao Suo highlights two publications that underscore the importance of genetic regulation of endogenous retrovirus expression in tumours.
{"title":"Endogenous retroviruses: unveiling new targets for cancer immunotherapy","authors":"Shengbao Suo","doi":"10.1038/s41576-024-00784-0","DOIUrl":"10.1038/s41576-024-00784-0","url":null,"abstract":"In this Journal Club, Shengbao Suo highlights two publications that underscore the importance of genetic regulation of endogenous retrovirus expression in tumours.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"25 12","pages":"827-827"},"PeriodicalIF":39.1,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142369081","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 : 2024-10-02DOI: 10.1038/s41576-024-00774-2
Charlotte Capitanchik, Oscar G. Wilkins, Nils Wagner, Julien Gagneur, Jernej Ule
Since the discovery of RNA splicing and its role in gene expression, researchers have sought a set of rules, an algorithm or a computational model that could predict the splice isoforms, and their frequencies, produced from any transcribed gene in a specific cellular context. Over the past 30 years, these models have evolved from simple position weight matrices to deep-learning models capable of integrating sequence data across vast genomic distances. Most recently, new model architectures are moving the field closer to context-specific alternative splicing predictions, and advances in sequencing technologies are expanding the type of data that can be used to inform and interpret such models. Together, these developments are driving improved understanding of splicing regulatory mechanisms and emerging applications of the splicing code to the rational design of RNA- and splicing-based therapeutics. This Review describes how increasingly sophisticated omics data and computational models of the splicing code are paving the way to more accurate, context-specific splicing predictions, while also providing insights into the regulatory mechanisms and therapeutic applications of alternative splicing.
{"title":"From computational models of the splicing code to regulatory mechanisms and therapeutic implications","authors":"Charlotte Capitanchik, Oscar G. Wilkins, Nils Wagner, Julien Gagneur, Jernej Ule","doi":"10.1038/s41576-024-00774-2","DOIUrl":"10.1038/s41576-024-00774-2","url":null,"abstract":"Since the discovery of RNA splicing and its role in gene expression, researchers have sought a set of rules, an algorithm or a computational model that could predict the splice isoforms, and their frequencies, produced from any transcribed gene in a specific cellular context. Over the past 30 years, these models have evolved from simple position weight matrices to deep-learning models capable of integrating sequence data across vast genomic distances. Most recently, new model architectures are moving the field closer to context-specific alternative splicing predictions, and advances in sequencing technologies are expanding the type of data that can be used to inform and interpret such models. Together, these developments are driving improved understanding of splicing regulatory mechanisms and emerging applications of the splicing code to the rational design of RNA- and splicing-based therapeutics. This Review describes how increasingly sophisticated omics data and computational models of the splicing code are paving the way to more accurate, context-specific splicing predictions, while also providing insights into the regulatory mechanisms and therapeutic applications of alternative splicing.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 3","pages":"171-190"},"PeriodicalIF":39.1,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142362739","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 : 2024-09-30DOI: 10.1038/s41576-024-00772-4
Rasmus Nielsen, Andrew H. Vaughn, Yun Deng
Ancestral recombination graphs (ARGs) summarize the complex genealogical relationships between individuals represented in a sample of DNA sequences. Their use is currently revolutionizing the field of population genetics and is leading to the development of powerful new methods to elucidate individual and population genetic processes, including population size history, migration, admixture, recombination, mutation and selection. In this Review, we introduce the readers to the structure of ARGs and discuss how they relate to processes such as recombination and genetic drift. We explore differences and similarities between methods of estimating ARGs and provide concrete illustrative examples of how ARGs can be used to elucidate population-level processes. Ancestral recombination graphs (ARGs) are revolutionizing population genetics by elucidating genetic processes such as demography, migration and selection. This Review introduces ARG structure, compares estimation methods and illustrates their application to understanding population dynamics.
祖先重组图（ARGs）概括了 DNA 序列样本中个体之间复杂的系谱关系。目前，ARG 的使用正在给群体遗传学领域带来革命性的变化，并促使人们开发出功能强大的新方法来阐明个体和群体的遗传过程，包括群体规模历史、迁移、混杂、重组、变异和选择。在这篇综述中，我们将向读者介绍ARGs的结构，并讨论它们与重组和遗传漂变等过程的关系。我们探讨了 ARGs 估算方法的异同，并提供了具体的示例，说明如何利用 ARGs 阐明种群水平的过程。
{"title":"Inference and applications of ancestral recombination graphs","authors":"Rasmus Nielsen, Andrew H. Vaughn, Yun Deng","doi":"10.1038/s41576-024-00772-4","DOIUrl":"10.1038/s41576-024-00772-4","url":null,"abstract":"Ancestral recombination graphs (ARGs) summarize the complex genealogical relationships between individuals represented in a sample of DNA sequences. Their use is currently revolutionizing the field of population genetics and is leading to the development of powerful new methods to elucidate individual and population genetic processes, including population size history, migration, admixture, recombination, mutation and selection. In this Review, we introduce the readers to the structure of ARGs and discuss how they relate to processes such as recombination and genetic drift. We explore differences and similarities between methods of estimating ARGs and provide concrete illustrative examples of how ARGs can be used to elucidate population-level processes. Ancestral recombination graphs (ARGs) are revolutionizing population genetics by elucidating genetic processes such as demography, migration and selection. This Review introduces ARG structure, compares estimation methods and illustrates their application to understanding population dynamics.","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"26 1","pages":"47-58"},"PeriodicalIF":39.1,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142329578","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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