Pub Date : 2026-02-12DOI: 10.1038/s41588-026-02528-8
Petra Gross
{"title":"Functional dissection of m6A in cancer","authors":"Petra Gross","doi":"10.1038/s41588-026-02528-8","DOIUrl":"10.1038/s41588-026-02528-8","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"240-240"},"PeriodicalIF":29.0,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146162896","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 : 2026-02-12DOI: 10.1038/s41588-026-02527-9
Tiago Faial
{"title":"Endogenous retroviruses help activate the human zygotic genome","authors":"Tiago Faial","doi":"10.1038/s41588-026-02527-9","DOIUrl":"10.1038/s41588-026-02527-9","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"240-240"},"PeriodicalIF":29.0,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146162895","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 : 2026-02-12DOI: 10.1038/s41588-026-02530-0
Wei Li
{"title":"Exploring the mammalian metabolome with DeepMet","authors":"Wei Li","doi":"10.1038/s41588-026-02530-0","DOIUrl":"10.1038/s41588-026-02530-0","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"240-240"},"PeriodicalIF":29.0,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146162897","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 : 2026-02-11DOI: 10.1038/s41588-025-02482-x
Somnath Tagore, Samuel Tsang, Carla Tangermann, Lucas ZhongMing Hu, Sven Diederichs, Gordon B. Mills, Andrea Califano
Although the functional effects of many recurrent cancer mutations have been characterized, The Cancer Genome Atlas contains more than 10 million functionally uncharacterized, nonrecurrent events. It is proposed that the context-specific activity of transcription factors assessed through the expression of their transcriptional targets serves as a sensitive and accurate reporter assay for evaluating the functional roles of oncogene mutations. Analysis of transcription factor activity in samples with mutations of unknown significance, compared to established gain-of-function (hypermorph) or loss-of-function (hypomorph) mutations in the same gene, enabled functional characterization of 583,089 individual mutational events across TCGA. This approach facilitated the identification of neomorphic mutations (gain of new function) or mutations that phenocopy mutations in other genes (mutational mimicry). Validation using exogenous mutation expression assays confirmed the majority of predicted loss-of-function, gain-of-function, neomorphic and neutral (no predicted functional effect) mutations in PIK3CA and FGFR2. These findings may inform targeted therapy decisions for patients with mutations of unknown significance in established oncogenes. Protein-activity-based identification of hypermorphic, hypomorphic, neomorphic effectors and therapeutically relevant mutations uses transcriptomic data to categorize variants of unknown significance into hypermorphic, hypomorphic and neomorphic mutations based on their effects on transcription factor activity and subsequent gene expression.
{"title":"Pan-cancer inference and validation of hypermorphic, hypomorphic and neomorphic mutations","authors":"Somnath Tagore, Samuel Tsang, Carla Tangermann, Lucas ZhongMing Hu, Sven Diederichs, Gordon B. Mills, Andrea Califano","doi":"10.1038/s41588-025-02482-x","DOIUrl":"10.1038/s41588-025-02482-x","url":null,"abstract":"Although the functional effects of many recurrent cancer mutations have been characterized, The Cancer Genome Atlas contains more than 10 million functionally uncharacterized, nonrecurrent events. It is proposed that the context-specific activity of transcription factors assessed through the expression of their transcriptional targets serves as a sensitive and accurate reporter assay for evaluating the functional roles of oncogene mutations. Analysis of transcription factor activity in samples with mutations of unknown significance, compared to established gain-of-function (hypermorph) or loss-of-function (hypomorph) mutations in the same gene, enabled functional characterization of 583,089 individual mutational events across TCGA. This approach facilitated the identification of neomorphic mutations (gain of new function) or mutations that phenocopy mutations in other genes (mutational mimicry). Validation using exogenous mutation expression assays confirmed the majority of predicted loss-of-function, gain-of-function, neomorphic and neutral (no predicted functional effect) mutations in PIK3CA and FGFR2. These findings may inform targeted therapy decisions for patients with mutations of unknown significance in established oncogenes. Protein-activity-based identification of hypermorphic, hypomorphic, neomorphic effectors and therapeutically relevant mutations uses transcriptomic data to categorize variants of unknown significance into hypermorphic, hypomorphic and neomorphic mutations based on their effects on transcription factor activity and subsequent gene expression.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"329-340"},"PeriodicalIF":29.0,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02482-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146152316","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 : 2026-02-10DOI: 10.1038/s41588-026-02513-1
Ahmed Alfares, Faiqa Imtiaz, Sateesh Maddirevula, Nabil Moghrabi, Monther Alhamdoosh, Anas M. Alazami, Mohammed Alowain, Abdullah Alsuwaidan, Sultan Alsedairy, Brian F. Meyer, Mohamed Abouelhoda, Ibtisam Bindayel, Fowzan S. Alkuraya, Salah M. Baz, Yaseen Mallawi
Genomic medicine can transform diagnosis and treatment, particularly in populations with high rates of inherited disorders. Here we describe the Genomic Medicine Center of Excellence at King Faisal Specialist Hospital & Research Centre, launched to strengthen Saudi genomic infrastructure and highlight lessons for underrepresented populations.
{"title":"Building genomic medicine in Saudi Arabia","authors":"Ahmed Alfares, Faiqa Imtiaz, Sateesh Maddirevula, Nabil Moghrabi, Monther Alhamdoosh, Anas M. Alazami, Mohammed Alowain, Abdullah Alsuwaidan, Sultan Alsedairy, Brian F. Meyer, Mohamed Abouelhoda, Ibtisam Bindayel, Fowzan S. Alkuraya, Salah M. Baz, Yaseen Mallawi","doi":"10.1038/s41588-026-02513-1","DOIUrl":"10.1038/s41588-026-02513-1","url":null,"abstract":"Genomic medicine can transform diagnosis and treatment, particularly in populations with high rates of inherited disorders. Here we describe the Genomic Medicine Center of Excellence at King Faisal Specialist Hospital & Research Centre, launched to strengthen Saudi genomic infrastructure and highlight lessons for underrepresented populations.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 3","pages":"463-466"},"PeriodicalIF":29.0,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146157820","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 : 2026-02-10DOI: 10.1038/s41588-026-02506-0
Xuebo Zhao, Jingyin Yu, Jie Zhang, Honghe Sun, Shan Wu, Jiantao Zhao, Yao Zhou, Sue A. Hammar, Ying-Chen Lin, Zhonghua Zhang, Sanwen Huang, Ronald T. Dymerski, Feifan Chen, Yiqun Weng, Rebecca Grumet, Yong Xu, Zhangjun Fei
Structural variants (SVs) represent an important yet underexplored component of plant genome diversity. Here we present a graph-based cucumber pangenome constructed from 39 reference-quality genomes, including 27 newly assembled and 12 previously published. The pangenome captures 171,892 high-confidence SVs, which were genotyped across 447 wild and cultivated accessions. Our analyses reveal that, during cucumber domestication, a substantial portion of mildly deleterious SNPs were retained, whereas SVs were consistently purged, highlighting their highly deleterious nature. During geographical expansion, a reduced SV burden and a younger age of SVs compared to SNPs were observed, suggesting stronger purifying selection acting on SVs. Introgressions from wild populations increased SV burden, potentially due to hitchhiking. Notably, incorporating SV burden into genomic prediction models improved prediction accuracy for several agronomically important traits. This study illuminates SV dynamics during cucumber domestication and range expansion and underscores the implications of SVs for future cucumber breeding. A graph-based pangenome constructed from 39 reference-quality genomes of wild and cultivated cucumber accessions, including 27 newly assembled, highlights the dynamics of structural variants during cucumber domestication and range expansion.
{"title":"Graph-based pangenome reveals structural variation dynamics during cucumber breeding","authors":"Xuebo Zhao, Jingyin Yu, Jie Zhang, Honghe Sun, Shan Wu, Jiantao Zhao, Yao Zhou, Sue A. Hammar, Ying-Chen Lin, Zhonghua Zhang, Sanwen Huang, Ronald T. Dymerski, Feifan Chen, Yiqun Weng, Rebecca Grumet, Yong Xu, Zhangjun Fei","doi":"10.1038/s41588-026-02506-0","DOIUrl":"10.1038/s41588-026-02506-0","url":null,"abstract":"Structural variants (SVs) represent an important yet underexplored component of plant genome diversity. Here we present a graph-based cucumber pangenome constructed from 39 reference-quality genomes, including 27 newly assembled and 12 previously published. The pangenome captures 171,892 high-confidence SVs, which were genotyped across 447 wild and cultivated accessions. Our analyses reveal that, during cucumber domestication, a substantial portion of mildly deleterious SNPs were retained, whereas SVs were consistently purged, highlighting their highly deleterious nature. During geographical expansion, a reduced SV burden and a younger age of SVs compared to SNPs were observed, suggesting stronger purifying selection acting on SVs. Introgressions from wild populations increased SV burden, potentially due to hitchhiking. Notably, incorporating SV burden into genomic prediction models improved prediction accuracy for several agronomically important traits. This study illuminates SV dynamics during cucumber domestication and range expansion and underscores the implications of SVs for future cucumber breeding. A graph-based pangenome constructed from 39 reference-quality genomes of wild and cultivated cucumber accessions, including 27 newly assembled, highlights the dynamics of structural variants during cucumber domestication and range expansion.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 3","pages":"643-654"},"PeriodicalIF":29.0,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146152327","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 : 2026-02-09DOI: 10.1038/s41588-026-02531-z
Guocan Wang, Andrea Lunardi, Jiangwen Zhang, Zhenbang Chen, Ugo Ala, Kaitlyn A. Webster, Yvonne Tay, Enrique Gonzalez-Billalabeitia, Ainara Egia, David R. Shaffer, Brett Carver, Xue-Song Liu, Riccardo Taulli, Winston Patrick Kuo, Caterina Nardella, Sabina Signoretti, Carlos Cordon-Cardo, William L. Gerald, Pier Paolo Pandolfi
{"title":"Author Correction: Zbtb7a suppresses prostate cancer through repression of a Sox9-dependent pathway for cellular senescence bypass and tumor invasion","authors":"Guocan Wang, Andrea Lunardi, Jiangwen Zhang, Zhenbang Chen, Ugo Ala, Kaitlyn A. Webster, Yvonne Tay, Enrique Gonzalez-Billalabeitia, Ainara Egia, David R. Shaffer, Brett Carver, Xue-Song Liu, Riccardo Taulli, Winston Patrick Kuo, Caterina Nardella, Sabina Signoretti, Carlos Cordon-Cardo, William L. Gerald, Pier Paolo Pandolfi","doi":"10.1038/s41588-026-02531-z","DOIUrl":"10.1038/s41588-026-02531-z","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 3","pages":"674-674"},"PeriodicalIF":29.0,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-026-02531-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146150277","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 : 2026-02-09DOI: 10.1038/s41588-025-02475-w
Sybren L. N. Maas, Yiheng Tang, Eric Stutheit-Zhao, Ramin Rahmanzade, Christina Blume, Thomas Hielscher, Ferdinand Zettl, Salvatore Benfatto, Domenico Calafato, Martin Sill, Jasim Kada Benotmane, Yahaya A. Yabo, Felix Behling, Abigail Suwala, Helin Kardo, Michael Ritter, Matthieu Peyre, Roman Sankowski, Konstantin Okonechnikov, Philipp Sievers, Areeba Patel, David Reuss, Mirco J. Friedrich, Damian Stichel, Daniel Schrimpf, Thierry P. P. Van den Bosch, Katja Beck, Hans-Georg Wirsching, Gerhard Jungwirth, C. Oliver Hanemann, Katrin Lamszus, Nima Etminan, Andreas Unterberg, Christian Mawrin, Marc Remke, Olivier Ayrault, Peter Lichter, Guido Reifenberger, Michael Platten, Tim Kacprowski, Markus List, Josch K. Pauling, Jan Baumbach, Till Milde, Rachel Grossmann, Zvi Ram, Miriam Ratliff, Jan-Philipp Mallm, Marian C. Neidert, Eelke M. Bos, Marco Prinz, Michael Weller, Till Acker, Felix J. Hartmann, Matthias Preusser, Ghazaleh Tabatabai, Christel Herold-Mende, Sandro M. Krieg, David T. W. Jones, Stefan M. Pfister, Wolfgang Wick, Michel Kalamarides, Andreas von Deimling, Dieter Henrik Heiland, Volker Hovestadt, Moritz Gerstung, Matthias Schlesner, The German “Aggressive Meningiomas” Consortium (KAM), Felix Sahm
Classification of tumors in neuro-oncology today relies on molecular patterns (mostly DNA methylation) and their machine learning-supported interpretation. Understanding the process of algorithmic interpretation is essential for safe application in clinical routine. This is paradigmatically true for the most common primary intracranial tumor in adults, meningioma. Here, by applying multiomic profiling and multiple lines of orthogonal computational evaluation in multiple independent datasets, we found that not only tumor cell characteristics but also incremental changes in the tumor microenvironment (TME) have impact on epigenetic meningioma classification and clinical outcome. Besides revealing the decisive role of non-neoplastic cells in the CNS methylation classifier, this challenges the model of distinct meningioma subgroups toward a TME-determined risk continuum. This refines current controversies in molecular meningioma subtyping. In addition, we apply these learnings to devise and validate a simple diagnostic approach for increased clinical prediction accuracy based on immunohistochemistry, which is also applicable in resource-limited settings. This paper uses multiomics to profile a large cohort of meningioma samples to highlight the role of the tumor microenvironment in driving the epigenetic changes underpinning tumor classification and prediction of outcome.
{"title":"A microenvironment-determined risk continuum refines subtyping in meningioma and reveals determinants of machine learning-based tumor classification","authors":"Sybren L. N. Maas, Yiheng Tang, Eric Stutheit-Zhao, Ramin Rahmanzade, Christina Blume, Thomas Hielscher, Ferdinand Zettl, Salvatore Benfatto, Domenico Calafato, Martin Sill, Jasim Kada Benotmane, Yahaya A. Yabo, Felix Behling, Abigail Suwala, Helin Kardo, Michael Ritter, Matthieu Peyre, Roman Sankowski, Konstantin Okonechnikov, Philipp Sievers, Areeba Patel, David Reuss, Mirco J. Friedrich, Damian Stichel, Daniel Schrimpf, Thierry P. P. Van den Bosch, Katja Beck, Hans-Georg Wirsching, Gerhard Jungwirth, C. Oliver Hanemann, Katrin Lamszus, Nima Etminan, Andreas Unterberg, Christian Mawrin, Marc Remke, Olivier Ayrault, Peter Lichter, Guido Reifenberger, Michael Platten, Tim Kacprowski, Markus List, Josch K. Pauling, Jan Baumbach, Till Milde, Rachel Grossmann, Zvi Ram, Miriam Ratliff, Jan-Philipp Mallm, Marian C. Neidert, Eelke M. Bos, Marco Prinz, Michael Weller, Till Acker, Felix J. Hartmann, Matthias Preusser, Ghazaleh Tabatabai, Christel Herold-Mende, Sandro M. Krieg, David T. W. Jones, Stefan M. Pfister, Wolfgang Wick, Michel Kalamarides, Andreas von Deimling, Dieter Henrik Heiland, Volker Hovestadt, Moritz Gerstung, Matthias Schlesner, The German “Aggressive Meningiomas” Consortium (KAM), Felix Sahm","doi":"10.1038/s41588-025-02475-w","DOIUrl":"10.1038/s41588-025-02475-w","url":null,"abstract":"Classification of tumors in neuro-oncology today relies on molecular patterns (mostly DNA methylation) and their machine learning-supported interpretation. Understanding the process of algorithmic interpretation is essential for safe application in clinical routine. This is paradigmatically true for the most common primary intracranial tumor in adults, meningioma. Here, by applying multiomic profiling and multiple lines of orthogonal computational evaluation in multiple independent datasets, we found that not only tumor cell characteristics but also incremental changes in the tumor microenvironment (TME) have impact on epigenetic meningioma classification and clinical outcome. Besides revealing the decisive role of non-neoplastic cells in the CNS methylation classifier, this challenges the model of distinct meningioma subgroups toward a TME-determined risk continuum. This refines current controversies in molecular meningioma subtyping. In addition, we apply these learnings to devise and validate a simple diagnostic approach for increased clinical prediction accuracy based on immunohistochemistry, which is also applicable in resource-limited settings. This paper uses multiomics to profile a large cohort of meningioma samples to highlight the role of the tumor microenvironment in driving the epigenetic changes underpinning tumor classification and prediction of outcome.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"341-354"},"PeriodicalIF":29.0,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02475-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146150291","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 : 2026-02-09DOI: 10.1038/s41588-025-02476-9
By investigating single-cell gene expression and DNA methylation profiles of meningiomas, we found that the composition of the tumor microenvironment and cellular activation status both correlate with tumor aggressiveness. These findings explain the outcomes of previous DNA methylation-based classification approaches to meningioma and have direct clinical applicability.
{"title":"Stromal immune cell signatures predict risk of progression in meningioma","authors":"","doi":"10.1038/s41588-025-02476-9","DOIUrl":"10.1038/s41588-025-02476-9","url":null,"abstract":"By investigating single-cell gene expression and DNA methylation profiles of meningiomas, we found that the composition of the tumor microenvironment and cellular activation status both correlate with tumor aggressiveness. These findings explain the outcomes of previous DNA methylation-based classification approaches to meningioma and have direct clinical applicability.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"245-246"},"PeriodicalIF":29.0,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146150204","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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