Pub Date : 2026-01-16DOI: 10.1038/s41587-025-02983-4
Megan Cully
First-in-human studies provide hope that islet replacement therapies derived from stem cells will prove safe and effective in people with type 1 diabetes, but hurdles remain.
首次人体研究为胰岛干细胞替代疗法对1型糖尿病患者的安全性和有效性提供了希望，但障碍仍然存在。
{"title":"Lab-made islet cell implants sail through diabetes trials, but are they ready yet?","authors":"Megan Cully","doi":"10.1038/s41587-025-02983-4","DOIUrl":"10.1038/s41587-025-02983-4","url":null,"abstract":"First-in-human studies provide hope that islet replacement therapies derived from stem cells will prove safe and effective in people with type 1 diabetes, but hurdles remain.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"44 1","pages":"6-8"},"PeriodicalIF":41.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145984057","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 : 2026-01-12DOI: 10.1038/s41587-025-02945-w
Wayne Ngo, Jamie L. Y. Wu, Kevin M. Wasko, Jennifer A. Doudna
Genome editing has revolutionized the treatment of genetic diseases, yet the difficulty of tissue-specific delivery currently limits applications of editing technology. In this Review, we discuss preclinical and clinical advances in delivering genome editors with both established and emerging delivery mechanisms. Targeted delivery promises to considerably expand the therapeutic applicability of genome editing, moving closer to the ideal of a precise ‘magic bullet’ that safely and effectively treats diverse genetic disorders. Doudna and colleagues discuss recent advances in the targeted delivery of genome editors in vivo, offering a framework for the rational design of delivery systems.
{"title":"Targeted delivery of genome editors in vivo","authors":"Wayne Ngo, Jamie L. Y. Wu, Kevin M. Wasko, Jennifer A. Doudna","doi":"10.1038/s41587-025-02945-w","DOIUrl":"10.1038/s41587-025-02945-w","url":null,"abstract":"Genome editing has revolutionized the treatment of genetic diseases, yet the difficulty of tissue-specific delivery currently limits applications of editing technology. In this Review, we discuss preclinical and clinical advances in delivering genome editors with both established and emerging delivery mechanisms. Targeted delivery promises to considerably expand the therapeutic applicability of genome editing, moving closer to the ideal of a precise ‘magic bullet’ that safely and effectively treats diverse genetic disorders. Doudna and colleagues discuss recent advances in the targeted delivery of genome editors in vivo, offering a framework for the rational design of delivery systems.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"44 1","pages":"49-59"},"PeriodicalIF":41.7,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955988","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 : 2026-01-06DOI: 10.1038/s41587-025-02990-5
Insights into regulatory T cell biology are accelerating therapeutic innovation in cancer immunotherapy, autoimmune diseases and transplant rejection.
对调节性T细胞生物学的深入了解正在加速癌症免疫治疗、自身免疫性疾病和移植排斥的治疗创新。
{"title":"Balancing immunity with Tregs","authors":"","doi":"10.1038/s41587-025-02990-5","DOIUrl":"10.1038/s41587-025-02990-5","url":null,"abstract":"Insights into regulatory T cell biology are accelerating therapeutic innovation in cancer immunotherapy, autoimmune diseases and transplant rejection.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"44 1","pages":"1-2"},"PeriodicalIF":41.7,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41587-025-02990-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145903114","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 : 2026-01-06DOI: 10.1038/s41587-025-02987-0
Cormac Sheridan
Developers have married gene-modulating oligonucleotides with the targeted precision of antibodies, and the first filings using such conjugates in Duchenne muscular dystrophy are imminent.
{"title":"Now with oligos: antibody–oligonucleotide conjugates are the new drug modality to watch","authors":"Cormac Sheridan","doi":"10.1038/s41587-025-02987-0","DOIUrl":"10.1038/s41587-025-02987-0","url":null,"abstract":"Developers have married gene-modulating oligonucleotides with the targeted precision of antibodies, and the first filings using such conjugates in Duchenne muscular dystrophy are imminent.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"44 1","pages":"3-5"},"PeriodicalIF":41.7,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145903113","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 : 2026-01-05DOI: 10.1038/s41587-025-02965-6
Jiayu Su, Yiming Qu, Megan Schertzer, Haochen Yang, Jiahao Jiang, Tenzin Lhakhang, Theodore M. Nelson, Stella Park, Qiliang Lai, Xi Fu, Seung-won Choi, David A. Knowles, Raul Rabadan
Transcript diversity including splicing and alternative 3′ end usage is crucial for cellular identity and adaptation, yet its spatial coordination remains poorly understood. Here we present SPLISOSM (spatial isoform statistical modeling), a method for detecting isoform-resolution patterns from spatial transcriptomics data. SPLISOSM uses multivariate testing with nonparametric kernels to account for spot-level and isoform-level dependencies, achieving high statistical power on sparse data. In the mouse brain, we identify over 1,000 spatially variable transcript diversity events, primarily in synaptic signaling pathways linked to neuropsychiatric disorders, and uncover both known and previously unknown regulatory relationships with region-specific RNA binding proteins. We further show that these patterns are evolutionarily conserved between mouse and human prefrontal cortex. Analysis of human glioblastoma highlights pervasive transcript diversity in antigen presentation and adhesion genes associated with specific microenvironmental conditions. Together, we present a comprehensive spatial splicing analysis in the brain under normal and neoplastic conditions.
{"title":"Mapping isoforms and regulatory mechanisms from spatial transcriptomics data with SPLISOSM","authors":"Jiayu Su, Yiming Qu, Megan Schertzer, Haochen Yang, Jiahao Jiang, Tenzin Lhakhang, Theodore M. Nelson, Stella Park, Qiliang Lai, Xi Fu, Seung-won Choi, David A. Knowles, Raul Rabadan","doi":"10.1038/s41587-025-02965-6","DOIUrl":"https://doi.org/10.1038/s41587-025-02965-6","url":null,"abstract":"Transcript diversity including splicing and alternative 3′ end usage is crucial for cellular identity and adaptation, yet its spatial coordination remains poorly understood. Here we present SPLISOSM (spatial isoform statistical modeling), a method for detecting isoform-resolution patterns from spatial transcriptomics data. SPLISOSM uses multivariate testing with nonparametric kernels to account for spot-level and isoform-level dependencies, achieving high statistical power on sparse data. In the mouse brain, we identify over 1,000 spatially variable transcript diversity events, primarily in synaptic signaling pathways linked to neuropsychiatric disorders, and uncover both known and previously unknown regulatory relationships with region-specific RNA binding proteins. We further show that these patterns are evolutionarily conserved between mouse and human prefrontal cortex. Analysis of human glioblastoma highlights pervasive transcript diversity in antigen presentation and adhesion genes associated with specific microenvironmental conditions. Together, we present a comprehensive spatial splicing analysis in the brain under normal and neoplastic conditions.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"29 1","pages":""},"PeriodicalIF":46.9,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145903118","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 : 2026-01-05DOI: 10.1038/s41587-025-02974-5
Wenkai Wang, Baoquan Su, Zhenling Peng, Jianyi Yang
{"title":"Integrated experimental and AI innovations for RNA structure determination","authors":"Wenkai Wang, Baoquan Su, Zhenling Peng, Jianyi Yang","doi":"10.1038/s41587-025-02974-5","DOIUrl":"https://doi.org/10.1038/s41587-025-02974-5","url":null,"abstract":"","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"21 1","pages":""},"PeriodicalIF":46.9,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145903122","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 : 2026-01-05DOI: 10.1038/s41587-025-02950-z
Qin Zhu, Zuzhi Jiang, Binyamin Zuckerman, Leor Weinberger, Matt Thomson, Zev J. Gartner
Revealing the underlying cell-state landscape from single-cell data requires overcoming the critical obstacles of batch integration, denoising and dimensionality reduction. Here we present CONCORD, a unified framework that simultaneously addresses these challenges within a single self-supervised model. At its core, CONCORD implements a probabilistic sampling strategy that corrects batch effects through dataset-aware sampling and enhances biological resolution through hard-negative sampling. Using only a minimalist neural network with a single hidden layer and contrastive learning, CONCORD surpasses state-of-the-art performance without relying on deep architectures, auxiliary losses or external supervision. It seamlessly integrates data across batches, technologies and even species to generate high-resolution cell atlases. The resulting latent representations are denoised and biologically meaningful, capturing gene coexpression programs, revealing detailed lineage trajectories and preserving both local geometric relationships and global topological structures. We demonstrate CONCORD’s broad applicability across diverse datasets, establishing it as a general-purpose framework for learning unified, high-fidelity representations of cellular identity and dynamics.
{"title":"Revealing a coherent cell-state landscape across single-cell datasets with CONCORD","authors":"Qin Zhu, Zuzhi Jiang, Binyamin Zuckerman, Leor Weinberger, Matt Thomson, Zev J. Gartner","doi":"10.1038/s41587-025-02950-z","DOIUrl":"https://doi.org/10.1038/s41587-025-02950-z","url":null,"abstract":"Revealing the underlying cell-state landscape from single-cell data requires overcoming the critical obstacles of batch integration, denoising and dimensionality reduction. Here we present CONCORD, a unified framework that simultaneously addresses these challenges within a single self-supervised model. At its core, CONCORD implements a probabilistic sampling strategy that corrects batch effects through dataset-aware sampling and enhances biological resolution through hard-negative sampling. Using only a minimalist neural network with a single hidden layer and contrastive learning, CONCORD surpasses state-of-the-art performance without relying on deep architectures, auxiliary losses or external supervision. It seamlessly integrates data across batches, technologies and even species to generate high-resolution cell atlases. The resulting latent representations are denoised and biologically meaningful, capturing gene coexpression programs, revealing detailed lineage trajectories and preserving both local geometric relationships and global topological structures. We demonstrate CONCORD’s broad applicability across diverse datasets, establishing it as a general-purpose framework for learning unified, high-fidelity representations of cellular identity and dynamics.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"9 1","pages":""},"PeriodicalIF":46.9,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145903119","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 : 2026-01-05DOI: 10.1038/s41587-025-02931-2
Anders Kämpe, Oda Blomqvist Picard, Jesper Eisfeldt, Anna Lindstrand
Our understanding of the genetic mechanisms underlying rare diseases has rapidly advanced over the past decade, largely because of technological innovations. Yet clinical practice still has a strong monogenic focus, leaving many individuals undiagnosed. This Comment outlines how technological advances such as long-read sequencing should be adopted to increase multivariant testing in the clinic.
{"title":"Moving beyond monogenic disorders in clinical healthcare","authors":"Anders Kämpe, Oda Blomqvist Picard, Jesper Eisfeldt, Anna Lindstrand","doi":"10.1038/s41587-025-02931-2","DOIUrl":"10.1038/s41587-025-02931-2","url":null,"abstract":"Our understanding of the genetic mechanisms underlying rare diseases has rapidly advanced over the past decade, largely because of technological innovations. Yet clinical practice still has a strong monogenic focus, leaving many individuals undiagnosed. This Comment outlines how technological advances such as long-read sequencing should be adopted to increase multivariant testing in the clinic.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"44 1","pages":"21-25"},"PeriodicalIF":41.7,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145903120","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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