Pub Date : 2026-01-07DOI: 10.1038/s41588-025-02449-y
Jinghui Li, Yang I. Li, Xuanyao Liu
Most genetic variants influence complex traits by affecting gene regulation. Yet, despite comprehensive catalogs of molecular quantitative trait loci (QTLs), linking trait-associated variants to biological functions remains difficult. By re-analyzing large maps of protein QTLs (pQTLs), we found that genes with trans-pQTLs but no cis-pQTLs are under strong selective constraints and are particularly informative in interpreting genome-wide association study (GWAS) loci. We observed that trans-pQTLs and their target proteins are frequently involved in protein–protein interactions (PPIs). Notably, trans-pQTLs are enriched in missense variants and at PPI interfaces, suggesting a key role of PPIs in the trans-regulation of proteome. Using PPI annotations to guide trans-pQTL mapping, we identified 17,662 trans-pQTLs affecting 961 PPI clusters after accounting for blood cell composition effects. These trans-pQTLs colocalized with 36% GWAS loci per trait on average for 27 complex traits, helping in many cases to link GWAS loci to cellular function. Finally, we identified trans-pQTL effects at multiple autoimmune GWAS loci that converge to the same PPIs, pinpointing protein complexes and signaling pathways that show promising therapeutic target potential. Protein quantitative trait loci show enrichment of trans effects among proteins in the same interaction networks and among missense variants at interaction interfaces, highlighting pathways impacted by trait-associated variants.
{"title":"Protein–protein interactions shape trans-regulatory impact of genetic variation on protein expression and complex traits","authors":"Jinghui Li, Yang I. Li, Xuanyao Liu","doi":"10.1038/s41588-025-02449-y","DOIUrl":"10.1038/s41588-025-02449-y","url":null,"abstract":"Most genetic variants influence complex traits by affecting gene regulation. Yet, despite comprehensive catalogs of molecular quantitative trait loci (QTLs), linking trait-associated variants to biological functions remains difficult. By re-analyzing large maps of protein QTLs (pQTLs), we found that genes with trans-pQTLs but no cis-pQTLs are under strong selective constraints and are particularly informative in interpreting genome-wide association study (GWAS) loci. We observed that trans-pQTLs and their target proteins are frequently involved in protein–protein interactions (PPIs). Notably, trans-pQTLs are enriched in missense variants and at PPI interfaces, suggesting a key role of PPIs in the trans-regulation of proteome. Using PPI annotations to guide trans-pQTL mapping, we identified 17,662 trans-pQTLs affecting 961 PPI clusters after accounting for blood cell composition effects. These trans-pQTLs colocalized with 36% GWAS loci per trait on average for 27 complex traits, helping in many cases to link GWAS loci to cellular function. Finally, we identified trans-pQTL effects at multiple autoimmune GWAS loci that converge to the same PPIs, pinpointing protein complexes and signaling pathways that show promising therapeutic target potential. Protein quantitative trait loci show enrichment of trans effects among proteins in the same interaction networks and among missense variants at interaction interfaces, highlighting pathways impacted by trait-associated variants.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"77-87"},"PeriodicalIF":29.0,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02449-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145907949","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/s41588-025-02500-y
Vicente A. Yépez, German Demidov, Kornelia Ellwanger, Steven Laurie, Rebeka Luknárová, Midhuna Immaculate Joseph Maran, Thomas Hentrich, Lydia Sagath, Bart van der Sanden, Galuh Astuti, Kornelia Neveling, Laura Batlle-Masó, Danique Beijer, Felix Brechtmann, Andrés Caballero-Oteyza, Marc Dabad, Anne-Sophie Denommé-Pichon, Cenna Doornbos, Zakaria Eddafir, Berta Estévez-Arias, Ozge Aksel Kilicarslan, Ingrid H. M. Kolen, Leon Kraß, Katja Lohmann, Shubhankar Londhe, Estrella López-Martín, Kars Maassen, William Macken, Beatriz Martínez-Delgado, Davide Mei, Christian Mertes, Raffaella Minardi, Heba Morsy, Juliane S. Mueller, Daniel Natera-de Benito, Isabelle Nelson, Machteld M. Oud, Ida Paramonov, Daniel Picó, Davide Piscia, Kiran Polavarapu, Emanuele Raineri, Marco Savarese, Noor Smal, Marloes Steehouwer, Wouter Steyaert, Morris A. Swertz, Mirja Thomsen, Ana Töpf, Liedewei Van de Vondel, Gerben van der Vries, Antonio Vitobello, Carlo Wilke, Birte Zurek, Solve-RD DITF-EPICARE, Solve-RD DITF-ITHACA, Solve-RD DITF-EURO-NMD, Solve-RD DITF-RITA, Solve-RD DITF-RND, Solve-RD consortium, Peter-Bram t’ Hoen, Leslie Matalonga, Lisenka E. L. M. Vissers, Christian Gilissen, Julia Schulze-Hentrich, Sergi Beltran, Anna Esteve-Codina, Alexander Hoischen, Julien Gagneur, Holm Graessner
{"title":"Author Correction: The Solve-RD Solvathons as a pan-European interdisciplinary collaboration to diagnose patients with rare disease","authors":"Vicente A. Yépez, German Demidov, Kornelia Ellwanger, Steven Laurie, Rebeka Luknárová, Midhuna Immaculate Joseph Maran, Thomas Hentrich, Lydia Sagath, Bart van der Sanden, Galuh Astuti, Kornelia Neveling, Laura Batlle-Masó, Danique Beijer, Felix Brechtmann, Andrés Caballero-Oteyza, Marc Dabad, Anne-Sophie Denommé-Pichon, Cenna Doornbos, Zakaria Eddafir, Berta Estévez-Arias, Ozge Aksel Kilicarslan, Ingrid H. M. Kolen, Leon Kraß, Katja Lohmann, Shubhankar Londhe, Estrella López-Martín, Kars Maassen, William Macken, Beatriz Martínez-Delgado, Davide Mei, Christian Mertes, Raffaella Minardi, Heba Morsy, Juliane S. Mueller, Daniel Natera-de Benito, Isabelle Nelson, Machteld M. Oud, Ida Paramonov, Daniel Picó, Davide Piscia, Kiran Polavarapu, Emanuele Raineri, Marco Savarese, Noor Smal, Marloes Steehouwer, Wouter Steyaert, Morris A. Swertz, Mirja Thomsen, Ana Töpf, Liedewei Van de Vondel, Gerben van der Vries, Antonio Vitobello, Carlo Wilke, Birte Zurek, Solve-RD DITF-EPICARE, Solve-RD DITF-ITHACA, Solve-RD DITF-EURO-NMD, Solve-RD DITF-RITA, Solve-RD DITF-RND, Solve-RD consortium, Peter-Bram t’ Hoen, Leslie Matalonga, Lisenka E. L. M. Vissers, Christian Gilissen, Julia Schulze-Hentrich, Sergi Beltran, Anna Esteve-Codina, Alexander Hoischen, Julien Gagneur, Holm Graessner","doi":"10.1038/s41588-025-02500-y","DOIUrl":"10.1038/s41588-025-02500-y","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"231-231"},"PeriodicalIF":29.0,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02500-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145912445","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/s41588-025-02448-z
Julia-Star Darnold, Jos Jonkers
{"title":"Insights from three decades of BRCA1/2 modeling in mice","authors":"Julia-Star Darnold, Jos Jonkers","doi":"10.1038/s41588-025-02448-z","DOIUrl":"https://doi.org/10.1038/s41588-025-02448-z","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"41 1","pages":""},"PeriodicalIF":30.8,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902711","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/s41588-025-02450-5
Jordan Rossen, Huwenbo Shi, Benjamin J. Strober, Martin Jinye Zhang, Masahiro Kanai, Zachary R. McCaw, Liming Liang, Omer Weissbrod, Alkes L. Price
Leveraging multi-ancestry data can improve fine-mapping power. We propose MultiSuSiE, an extension of Sum of Single Effects (SuSiE), to multiple ancestries that allows causal effect sizes to vary across ancestries. We evaluated MultiSuSiE using whole-genome sequencing data from 47,000 African-ancestry, 36,000 Latino-ancestry and 116,000 European-ancestry individuals from All of Us. In simulations, MultiSuSiE applied to Afr36k + Lat36k + Eur36k was well-calibrated and attained higher power than SuSiE applied to Eur109k; compared to recent multi-ancestry methods (SuSiEx and MESuSiE), MultiSuSiE attained higher power and lower computational cost. In analyses of 14 quantitative traits, MultiSuSiE applied to Afr47k + Lat36k + Eur116k identified 348 fine-mapped variants with posterior inclusion probability (PIP) > 0.9, and MultiSuSiE applied to Afr36k + Lat36k + Eur36k identified 59% more PIP > 0.9 variants than SuSiE applied to Eur109k; MultiSuSiE identified 29% more PIP > 0.9 variants than SuSiEx, and MESuSiE was not included due to its high computational cost. We validated these findings through functional enrichment of fine-mapped variants and highlighted examples implicating biologically plausible fine-mapped variants. MultiSuSiE is an extension of the Sum of Single Effects fine-mapping model that allows causal effect sizes to vary across ancestries. Applying MultiSuSiE to quantitative traits in All of Us identifies fine-mapped variants not implicated by other methods.
利用多祖先数据可以提高精细映射的能力。我们提出MultiSuSiE，这是单一效应总和（Sum of Single Effects, SuSiE）的扩展，它允许多个祖先的因果效应大小在不同祖先之间变化。我们使用来自我们所有人的47,000名非洲血统，36,000名拉丁血统和116,000名欧洲血统的全基因组测序数据来评估MultiSuSiE。在模拟中，应用于Afr36k + Lat36k + Eur36k的MultiSuSiE得到了良好的校准，并且比应用于Eur109k的SuSiE获得了更高的功率；与最近的多祖先方法（SuSiEx和MESuSiE）相比，MultiSuSiE具有更高的功率和更低的计算成本。在对14个数量性状的分析中，应用于Afr47k + Lat36k + Eur116k的MultiSuSiE鉴定出348个精细映射变异，后验包含概率（PIP） > 0.9，应用于Afr36k + Lat36k + Eur36k的MultiSuSiE鉴定出的PIP >； 0.9变异比应用于Eur109k的多59%；MultiSuSiE比SuSiEx多识别出29%的PIP >； 0.9变体，MESuSiE由于计算成本高而未被纳入。我们通过精细映射变异的功能富集验证了这些发现，并强调了生物学上合理的精细映射变异的例子。MultiSuSiE是单一效应精细映射模型的扩展，该模型允许因果效应大小在不同祖先之间变化。将MultiSuSiE应用于《All of Us》的数量性状，可以识别出其他方法无法识别的精细映射变异。
{"title":"MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data","authors":"Jordan Rossen, Huwenbo Shi, Benjamin J. Strober, Martin Jinye Zhang, Masahiro Kanai, Zachary R. McCaw, Liming Liang, Omer Weissbrod, Alkes L. Price","doi":"10.1038/s41588-025-02450-5","DOIUrl":"10.1038/s41588-025-02450-5","url":null,"abstract":"Leveraging multi-ancestry data can improve fine-mapping power. We propose MultiSuSiE, an extension of Sum of Single Effects (SuSiE), to multiple ancestries that allows causal effect sizes to vary across ancestries. We evaluated MultiSuSiE using whole-genome sequencing data from 47,000 African-ancestry, 36,000 Latino-ancestry and 116,000 European-ancestry individuals from All of Us. In simulations, MultiSuSiE applied to Afr36k + Lat36k + Eur36k was well-calibrated and attained higher power than SuSiE applied to Eur109k; compared to recent multi-ancestry methods (SuSiEx and MESuSiE), MultiSuSiE attained higher power and lower computational cost. In analyses of 14 quantitative traits, MultiSuSiE applied to Afr47k + Lat36k + Eur116k identified 348 fine-mapped variants with posterior inclusion probability (PIP) > 0.9, and MultiSuSiE applied to Afr36k + Lat36k + Eur36k identified 59% more PIP > 0.9 variants than SuSiE applied to Eur109k; MultiSuSiE identified 29% more PIP > 0.9 variants than SuSiEx, and MESuSiE was not included due to its high computational cost. We validated these findings through functional enrichment of fine-mapped variants and highlighted examples implicating biologically plausible fine-mapped variants. MultiSuSiE is an extension of the Sum of Single Effects fine-mapping model that allows causal effect sizes to vary across ancestries. Applying MultiSuSiE to quantitative traits in All of Us identifies fine-mapped variants not implicated by other methods.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"67-76"},"PeriodicalIF":29.0,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902712","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 : 2026-01-02DOI: 10.1038/s41588-025-02434-5
Cheng-Zhong Zhang, Carlos Mendez-Dorantes, Kathleen H. Burns, David Pellman
Segmental copy-number gains are major contributors to human genetic variation and disease, but how these alterations arise remains incompletely understood. Here, based on the analyses of both experimental evolution and human disease genomes, we describe a general mechanism of segmental copy-number gain from a rearrangement process termed ‘breakage–replication/fusion’. The hallmark genomic feature of breakage–replication/fusion is adjacent parallel breakpoints: two or more rearrangement breakpoints derived from replication of a single ancestral DNA end. We show that adjacent parallel breakpoints are a widespread feature of DNA duplications in human disease genomes and experimental models of chromothripsis. In addition to adjacent parallel breakpoints, breakage–replication/fusion also explains two other patterns of complex rearrangements with unclear provenance: chains of short (≤1 kb) insertions and high-level amplification consisting of inverted segments. Together, these findings revise the mechanistic model for chromothripsis and provide a new conceptual framework for understanding the origin of segmental DNA duplication during genome evolution. This paper introduces breakage–replication/fusion, a genomic rearrangement process underpinning three patterns of copy-number gains found in cancer and other diseases.
{"title":"A breakage–replication/fusion process explains complex rearrangements and segmental DNA amplification","authors":"Cheng-Zhong Zhang, Carlos Mendez-Dorantes, Kathleen H. Burns, David Pellman","doi":"10.1038/s41588-025-02434-5","DOIUrl":"10.1038/s41588-025-02434-5","url":null,"abstract":"Segmental copy-number gains are major contributors to human genetic variation and disease, but how these alterations arise remains incompletely understood. Here, based on the analyses of both experimental evolution and human disease genomes, we describe a general mechanism of segmental copy-number gain from a rearrangement process termed ‘breakage–replication/fusion’. The hallmark genomic feature of breakage–replication/fusion is adjacent parallel breakpoints: two or more rearrangement breakpoints derived from replication of a single ancestral DNA end. We show that adjacent parallel breakpoints are a widespread feature of DNA duplications in human disease genomes and experimental models of chromothripsis. In addition to adjacent parallel breakpoints, breakage–replication/fusion also explains two other patterns of complex rearrangements with unclear provenance: chains of short (≤1 kb) insertions and high-level amplification consisting of inverted segments. Together, these findings revise the mechanistic model for chromothripsis and provide a new conceptual framework for understanding the origin of segmental DNA duplication during genome evolution. This paper introduces breakage–replication/fusion, a genomic rearrangement process underpinning three patterns of copy-number gains found in cancer and other diseases.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"88-99"},"PeriodicalIF":29.0,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02434-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145892675","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 : 2026-01-02DOI: 10.1038/s41588-025-02462-1
Zhaoen Yang, Zuoren Yang, Chenxu Gao, Mingjun Zhang, Guanjing Hu, Lan Yang, Yihao Zhang, Meng Ma, Renju Liu, Zhi Wang, Baibai Gao, Zhibin Zhang, Hang Zhao, Xuan Liu, Xiongfeng Ma, Jonathan F. Wendel, Xiaoyang Ge, Fuguang Li
Upland cotton (Gossypium hirsutum), one of the world’s major fiber crops, faces challenges from the genetic homogeneity of modern varieties. Here we present 107 gold-standard genome assemblies spanning the wild-to-domesticated continuum, revealing six large-scale structural variations, including a chromosomal reciprocal translocation and five inversions tracing the evolutionary history of cultivated cotton in the Americas. This history also involved continuous introgression from Gossypium barbadense, shaping the genetic diversity of G. hirsutum landraces and cultivars. Leveraging the graph pan-genome, we capture the sequence and structural diversity of nucleotide-binding site–leucine-rich repeat genes, uncovering pathogen-driven selection signatures and loci associated with disease resistance. A presence–absence variation genome-wide association study (GWAS) identified previously overlooked loci for key fiber traits, complementing single-nucleotide polymorphism–GWAS findings. Additionally, we construct a detailed map of large inversions, offering insights into hybridization dynamics and strategies to mitigate linkage drag. This study enhances our understanding of cotton evolution and domestication while delivering a valuable resource to enhance breeding. Genome assemblies of 100 cultivated and seven semi-wild Gossypium hirsutum accessions provide insights into the evolutionary history of upland cotton and the genetic basis of fiber trait variation.
{"title":"Graph pan-genome illuminates evolutionary trajectories and agronomic trait architecture in allotetraploid cotton","authors":"Zhaoen Yang, Zuoren Yang, Chenxu Gao, Mingjun Zhang, Guanjing Hu, Lan Yang, Yihao Zhang, Meng Ma, Renju Liu, Zhi Wang, Baibai Gao, Zhibin Zhang, Hang Zhao, Xuan Liu, Xiongfeng Ma, Jonathan F. Wendel, Xiaoyang Ge, Fuguang Li","doi":"10.1038/s41588-025-02462-1","DOIUrl":"10.1038/s41588-025-02462-1","url":null,"abstract":"Upland cotton (Gossypium hirsutum), one of the world’s major fiber crops, faces challenges from the genetic homogeneity of modern varieties. Here we present 107 gold-standard genome assemblies spanning the wild-to-domesticated continuum, revealing six large-scale structural variations, including a chromosomal reciprocal translocation and five inversions tracing the evolutionary history of cultivated cotton in the Americas. This history also involved continuous introgression from Gossypium barbadense, shaping the genetic diversity of G. hirsutum landraces and cultivars. Leveraging the graph pan-genome, we capture the sequence and structural diversity of nucleotide-binding site–leucine-rich repeat genes, uncovering pathogen-driven selection signatures and loci associated with disease resistance. A presence–absence variation genome-wide association study (GWAS) identified previously overlooked loci for key fiber traits, complementing single-nucleotide polymorphism–GWAS findings. Additionally, we construct a detailed map of large inversions, offering insights into hybridization dynamics and strategies to mitigate linkage drag. This study enhances our understanding of cotton evolution and domestication while delivering a valuable resource to enhance breeding. Genome assemblies of 100 cultivated and seven semi-wild Gossypium hirsutum accessions provide insights into the evolutionary history of upland cotton and the genetic basis of fiber trait variation.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"218-229"},"PeriodicalIF":29.0,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145892659","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 : 2025-12-30DOI: 10.1038/s41588-025-02453-2
Guida Landouré
Being an African scientist, I had to overcome several challenges to generate substantial data that shed light on the complexity of genomic medicine in African populations and abroad.
作为一名非洲科学家，我必须克服几个挑战，生成大量数据，揭示非洲人口和国外基因组医学的复杂性。
{"title":"An accidental scientist’s journey from an uncertain beginning to advancing neurogenetics research in Africa","authors":"Guida Landouré","doi":"10.1038/s41588-025-02453-2","DOIUrl":"10.1038/s41588-025-02453-2","url":null,"abstract":"Being an African scientist, I had to overcome several challenges to generate substantial data that shed light on the complexity of genomic medicine in African populations and abroad.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"2-2"},"PeriodicalIF":29.0,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145863840","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 : 2025-12-29DOI: 10.1038/s41588-025-02444-3
Samuel F. Bakhoum
A study reveals how chromosomal instability and resultant TP53 loss enhance fatty acid metabolism to drive breast cancer brain metastasis. This metabolic dependency provides new insights into therapeutic vulnerabilities of aneuploid tumors.
{"title":"Aneuploidy-driven vulnerabilities in breast cancer metastasis","authors":"Samuel F. Bakhoum","doi":"10.1038/s41588-025-02444-3","DOIUrl":"10.1038/s41588-025-02444-3","url":null,"abstract":"A study reveals how chromosomal instability and resultant TP53 loss enhance fatty acid metabolism to drive breast cancer brain metastasis. This metabolic dependency provides new insights into therapeutic vulnerabilities of aneuploid tumors.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"14-15"},"PeriodicalIF":29.0,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145857391","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 : 2025-12-29DOI: 10.1038/s41588-025-02442-5
The BioDIGS Consortium, Tristen Alberts, Claude F. Albritton, Rosa Alcazar, Zainab Aljabri, Maria Alvarez, Anish Aradhey, Mentewab Ayalew, Nareh Azizian, Yasmeen Balayah, Destiny D. Ball, Efren Barragan, Corey Beshoar, Lyle Best, Emily Biggane, Joseph Biggane, Jesse Blick, Myron Blosser, Alex Kenneth Brown, Michael C. Campbell, Zoe Canizares, Faith N. Chanhuhwa, Yu Chen, Daniel R. Chin, Kamal Chowdhury, Tyler Collins, Blair Compton, Jefferson Da Silva, Nia R. Davis, Natalie DeCaro, Frida Delgadillo, Youping Deng, Joceph Duncan, Arinzechukwu C. Egwu, Grace D. Ekalle, Noha Elnawam, Ray Enke, Naomi Ewhe, Marco A. Ferrel, Janna Fierst, Grace Freymiller, Karla Fuller, Lena Fulton-Wright, Valeriya Gaysinskaya, Torrence Gill, Ellie Gillespie, Perla Gonzalez Moreno, Sara Goodwin, Natajha Graham, Madeline E. Graham, Joseph L. Graves Jr., Emily Grob, Rachael Gutierrez, Aisha Hager, Shazia Tabassum Hakim, Aaliyah Harris, Ava M. Hoffman, Tobias Hoffmann, Alani M. Horton, Allison Hughes, Elizabeth M. Humphries, Josh-Samuel Ikechi-Konkwo, Aadil Ishtiaq, Ryan Jackson, Joshua Ronnie James, Kaitlan James, Sydney A. Jamison, Armando Jimenez, Rachel Johnson, Abigail Kauffman, Harkiran Kaur, Kritika Kc, Analyse Keeton, Olivia E. Kelly, Jennifer Kerr, Nataliya Kucher, Donna Lee Kuehu, Wendy A. Larson, Joslynn Lee, Andrew Lee, Jeffrey T. Leek, Danilo Lemaic, Lincoln E. Liburd II, Alan Fernando Lopez, Mohammadamin Mahmanzar, Karwitha Mamae, Raffi Manjikian, Michael Marone, Katerin Marquez, Amara Martinson, Senem Mavruk Eskipehlivan, Ashley Medrano, Melanie Melendrez-Vallard, Robert Meller, Loyda B. Méndez, Miguel P. Mendez Gonzalez, Nicolli Mesquita, Concepcion Martinez Miller, Isam Mohd-Ibrahim, Peter Mortensen, Stephen Mosher, Alketa Muja, Nadia Nasrin, Masaki Nasu, Matthew H. Nguyen, Ba Thong Nguyen, Michele Nishiguchi, Lance M. O’Connor, Disomi Okie, Tolulope Olowookorun, Alex Ostrovsky, Keyan Ozuna, Asmita Pandey, Shiv B. Patel, Gauri Paul, Shrikant Pawar, Andrea Pearson, Deborah Petrik, Jordan Platero, Carl Pontino, Arjun P. Pratap, Siddharth Pratap, Yujia Qin, Sudhir Kumar Rai, Nisttha Ray, Ethan Repesh, Kristen Rhinehardt, Brennan Roche, Ariana Rodriguez, Shriya Roy, Sourav Roy, Alexa Sawa, Michael C. Schatz, Shurjo K. Sen, Randon Serikawa, Tyler Smith, Loraye Smith, James Sniezek, Ryley D. Stewart, Edu B. Suarez-Martinez, Joelle Taganna, Frederick J. Tan, Nikolaos Tsotakos, Nwanneka Udolisa, Katherine Ulbricht, Tanner Veo, Jennifer Vessio, Lia Walker, Oscar Wang, Qingguo Wang, Robert Wappel, Kalynn Wesby, Malachi Whitford, Nicole Wild, Xianfa Xie, Hua Yang, Sayumi York, Lindsay Zirkle
The BioDIGS project is a nationwide initiative involving students, researchers and educators across more than 40 research and teaching institutions. Participants lead sample collection, computational analysis and results interpretation to understand the relationships between the soil microbiome, environment and health.
{"title":"Unearthing soil biodiversity through collaborative genomic research and education","authors":"The BioDIGS Consortium, Tristen Alberts, Claude F. Albritton, Rosa Alcazar, Zainab Aljabri, Maria Alvarez, Anish Aradhey, Mentewab Ayalew, Nareh Azizian, Yasmeen Balayah, Destiny D. Ball, Efren Barragan, Corey Beshoar, Lyle Best, Emily Biggane, Joseph Biggane, Jesse Blick, Myron Blosser, Alex Kenneth Brown, Michael C. Campbell, Zoe Canizares, Faith N. Chanhuhwa, Yu Chen, Daniel R. Chin, Kamal Chowdhury, Tyler Collins, Blair Compton, Jefferson Da Silva, Nia R. Davis, Natalie DeCaro, Frida Delgadillo, Youping Deng, Joceph Duncan, Arinzechukwu C. Egwu, Grace D. Ekalle, Noha Elnawam, Ray Enke, Naomi Ewhe, Marco A. Ferrel, Janna Fierst, Grace Freymiller, Karla Fuller, Lena Fulton-Wright, Valeriya Gaysinskaya, Torrence Gill, Ellie Gillespie, Perla Gonzalez Moreno, Sara Goodwin, Natajha Graham, Madeline E. Graham, Joseph L. Graves Jr., Emily Grob, Rachael Gutierrez, Aisha Hager, Shazia Tabassum Hakim, Aaliyah Harris, Ava M. Hoffman, Tobias Hoffmann, Alani M. Horton, Allison Hughes, Elizabeth M. Humphries, Josh-Samuel Ikechi-Konkwo, Aadil Ishtiaq, Ryan Jackson, Joshua Ronnie James, Kaitlan James, Sydney A. Jamison, Armando Jimenez, Rachel Johnson, Abigail Kauffman, Harkiran Kaur, Kritika Kc, Analyse Keeton, Olivia E. Kelly, Jennifer Kerr, Nataliya Kucher, Donna Lee Kuehu, Wendy A. Larson, Joslynn Lee, Andrew Lee, Jeffrey T. Leek, Danilo Lemaic, Lincoln E. Liburd II, Alan Fernando Lopez, Mohammadamin Mahmanzar, Karwitha Mamae, Raffi Manjikian, Michael Marone, Katerin Marquez, Amara Martinson, Senem Mavruk Eskipehlivan, Ashley Medrano, Melanie Melendrez-Vallard, Robert Meller, Loyda B. Méndez, Miguel P. Mendez Gonzalez, Nicolli Mesquita, Concepcion Martinez Miller, Isam Mohd-Ibrahim, Peter Mortensen, Stephen Mosher, Alketa Muja, Nadia Nasrin, Masaki Nasu, Matthew H. Nguyen, Ba Thong Nguyen, Michele Nishiguchi, Lance M. O’Connor, Disomi Okie, Tolulope Olowookorun, Alex Ostrovsky, Keyan Ozuna, Asmita Pandey, Shiv B. Patel, Gauri Paul, Shrikant Pawar, Andrea Pearson, Deborah Petrik, Jordan Platero, Carl Pontino, Arjun P. Pratap, Siddharth Pratap, Yujia Qin, Sudhir Kumar Rai, Nisttha Ray, Ethan Repesh, Kristen Rhinehardt, Brennan Roche, Ariana Rodriguez, Shriya Roy, Sourav Roy, Alexa Sawa, Michael C. Schatz, Shurjo K. Sen, Randon Serikawa, Tyler Smith, Loraye Smith, James Sniezek, Ryley D. Stewart, Edu B. Suarez-Martinez, Joelle Taganna, Frederick J. Tan, Nikolaos Tsotakos, Nwanneka Udolisa, Katherine Ulbricht, Tanner Veo, Jennifer Vessio, Lia Walker, Oscar Wang, Qingguo Wang, Robert Wappel, Kalynn Wesby, Malachi Whitford, Nicole Wild, Xianfa Xie, Hua Yang, Sayumi York, Lindsay Zirkle","doi":"10.1038/s41588-025-02442-5","DOIUrl":"10.1038/s41588-025-02442-5","url":null,"abstract":"The BioDIGS project is a nationwide initiative involving students, researchers and educators across more than 40 research and teaching institutions. Participants lead sample collection, computational analysis and results interpretation to understand the relationships between the soil microbiome, environment and health.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"3-8"},"PeriodicalIF":29.0,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145857431","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 : 2025-12-29DOI: 10.1038/s41588-025-02446-1
Kathrin Laue, Sabina Pozzi, Johanna Zerbib, Rebecca Bertolio, Yonatan Eliezer, Yael Cohen-Sharir, Tom Winkler, Manuel Caputo, Alessia A. Ricci, Lital Adler, Rami Khoury, Giuseppe Longobardi, Rachel Slutsky, Alicia I. Leikin-Frenkel, Shai Ovadia, Katharina Lange, Alessandra Rustighi, Silvano Piazza, Andrea Sacconi, Rayna Y. Magesh, Faith N. Keller, Jean Berthelet, Alexander Schäffer, Ron Saad, Sahar Israeli Dangoor, Karolina Szczepanowska, Iris Barshack, Yang Liao, Sergey Malitsky, Alexander Brandis, Thomas Broggini, Marcus Czabanka, Wei Shi, Delphine Merino, Emma V. Watson, Giovanni Blandino, Ayelet Erez, Ruth Ashery-Padan, Hind Medyouf, Luca Bertero, Giannino Del Sal, Ronit Satchi-Fainaro, Uri Ben-David
Brain metastasis (BM) carries a poor prognosis, yet the molecular basis of brain tropism remains unclear. Analysis of breast cancer BM (BCBM) revealed pervasive p53 inactivation through mutations and/or aneuploidy, with pathway disruption already present in primary tumors. Functionally, p53 inactivation markedly increased BCBM formation and growth in vivo, causally linking p53 perturbation to BM. Mechanistically, p53 inactivation upregulated SCD1 and fatty acid synthesis (FAS), essential for brain-metastasizing cells; SCD1 knockout abolished the p53-dependent growth advantage. Molecularly, p53 suppressed SCD1 directly through promoter binding and indirectly by downregulating its co-activator DEPDC1. Astrocytes further enhanced FAS by secreting factors that were metabolized in a p53-dependent manner, promoting tumor survival, proliferation and migration. Finally, p53-deficient tumors were sensitive to FAS inhibition ex vivo and in vivo. Thus, we identify p53 inactivation as a driver of BCBM, reveal p53-dependent and astrocyte-dependent FAS modulation and highlight FAS as a therapeutically targetable BCBM vulnerability. This study associates p53 loss and brain metastasis in breast cancer. Mechanistically, p53-null tumors recruit astrocytes that provide substrates for enhanced fatty acid synthesis via upregulated SCD1 expression, representing a targetable axis in the disease.
{"title":"p53 inactivation drives breast cancer metastasis to the brain through SCD1 upregulation and increased fatty acid metabolism","authors":"Kathrin Laue, Sabina Pozzi, Johanna Zerbib, Rebecca Bertolio, Yonatan Eliezer, Yael Cohen-Sharir, Tom Winkler, Manuel Caputo, Alessia A. Ricci, Lital Adler, Rami Khoury, Giuseppe Longobardi, Rachel Slutsky, Alicia I. Leikin-Frenkel, Shai Ovadia, Katharina Lange, Alessandra Rustighi, Silvano Piazza, Andrea Sacconi, Rayna Y. Magesh, Faith N. Keller, Jean Berthelet, Alexander Schäffer, Ron Saad, Sahar Israeli Dangoor, Karolina Szczepanowska, Iris Barshack, Yang Liao, Sergey Malitsky, Alexander Brandis, Thomas Broggini, Marcus Czabanka, Wei Shi, Delphine Merino, Emma V. Watson, Giovanni Blandino, Ayelet Erez, Ruth Ashery-Padan, Hind Medyouf, Luca Bertero, Giannino Del Sal, Ronit Satchi-Fainaro, Uri Ben-David","doi":"10.1038/s41588-025-02446-1","DOIUrl":"10.1038/s41588-025-02446-1","url":null,"abstract":"Brain metastasis (BM) carries a poor prognosis, yet the molecular basis of brain tropism remains unclear. Analysis of breast cancer BM (BCBM) revealed pervasive p53 inactivation through mutations and/or aneuploidy, with pathway disruption already present in primary tumors. Functionally, p53 inactivation markedly increased BCBM formation and growth in vivo, causally linking p53 perturbation to BM. Mechanistically, p53 inactivation upregulated SCD1 and fatty acid synthesis (FAS), essential for brain-metastasizing cells; SCD1 knockout abolished the p53-dependent growth advantage. Molecularly, p53 suppressed SCD1 directly through promoter binding and indirectly by downregulating its co-activator DEPDC1. Astrocytes further enhanced FAS by secreting factors that were metabolized in a p53-dependent manner, promoting tumor survival, proliferation and migration. Finally, p53-deficient tumors were sensitive to FAS inhibition ex vivo and in vivo. Thus, we identify p53 inactivation as a driver of BCBM, reveal p53-dependent and astrocyte-dependent FAS modulation and highlight FAS as a therapeutically targetable BCBM vulnerability. This study associates p53 loss and brain metastasis in breast cancer. Mechanistically, p53-null tumors recruit astrocytes that provide substrates for enhanced fatty acid synthesis via upregulated SCD1 expression, representing a targetable axis in the disease.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"116-131"},"PeriodicalIF":29.0,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145857415","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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