Pub Date : 2026-02-02DOI: 10.1038/s41588-026-02501-5
James L. Li, Haoyu Zhang, Xiaoyu Wang, Guochong Jia, Julian C. McClellan, Wenji Guo, Yijia Sun, Peter N. Fiorica, Stefan Ambs, Mollie E. Barnard, Yu Chen, Montserrat Garcia-Closas, Jian Gu, Jennifer J. Hu, Esther M. John, Katherine L. Nathanson, Barbara Nemesure, Tuya Pal, Xiao-Ou Shu, Michael F. Press, Maureen Sanderson, Dale P. Sandler, Melissa A. Troester, Song Yao, Jirong Long, Thomas U. Ahearn, Abenaa M. Brewster, Adeyinka Falusi, Peter Kraft, Anselm J. M. Hennis, Timothy Makumbi, Berthe S. E. Mapoko, Katie M. O’Brien, Oladosu Ojengbede, Andrew F. Olshan, Sonya Reid, Gary Zirpoli, Qiuyin Cai, Eboneé N. Butler, Maosheng Huang, John Obafunwa, Clarice R. Weinberg, Christine Ambrosone, Jie Ping, Ran Tao, Bingshan Li, Xingyi Guo, Guimin Gao, David V. Conti, Nilanjan Chatterjee, Julie R. Palmer, Olufunmilayo I. Olopade, Wei Zheng
Polygenic risk score (PRS) models effectively predict breast cancer (BC) risk in European-ancestry women but have limited accuracy for African-ancestry women, particularly for aggressive subtypes. We developed PRS models for overall BC, estrogen receptor (ER)-positive, ER-negative and triple-negative BC (TNBC) in African-ancestry women using data from the African Ancestry Breast Cancer Genetics consortium (17,391 cases and 18,800 controls). We applied several PRS methods and integrated information across ancestries and BC subtypes. The best models for overall, ER-positive, ER-negative and TNBC showed an area under the receiving operating curve of 0.612, 0.621, 0.611 and 0.639, respectively, and maintained predictive accuracy in external validation studies with area under the receiving operating curves of 0.612, 0.640, 0.605 and 0.652. We further introduce a parsimonious 162-variant PRS for TNBC with comparable accuracy (0.626). These findings demonstrate markedly improved PRS accuracy for BC risk prediction in African-ancestry women. Using these PRS models for screening will help promote more equitable cancer prevention efforts.
{"title":"Improved polygenic risk prediction models for breast cancer subtypes in women of African ancestry","authors":"James L. Li, Haoyu Zhang, Xiaoyu Wang, Guochong Jia, Julian C. McClellan, Wenji Guo, Yijia Sun, Peter N. Fiorica, Stefan Ambs, Mollie E. Barnard, Yu Chen, Montserrat Garcia-Closas, Jian Gu, Jennifer J. Hu, Esther M. John, Katherine L. Nathanson, Barbara Nemesure, Tuya Pal, Xiao-Ou Shu, Michael F. Press, Maureen Sanderson, Dale P. Sandler, Melissa A. Troester, Song Yao, Jirong Long, Thomas U. Ahearn, Abenaa M. Brewster, Adeyinka Falusi, Peter Kraft, Anselm J. M. Hennis, Timothy Makumbi, Berthe S. E. Mapoko, Katie M. O’Brien, Oladosu Ojengbede, Andrew F. Olshan, Sonya Reid, Gary Zirpoli, Qiuyin Cai, Eboneé N. Butler, Maosheng Huang, John Obafunwa, Clarice R. Weinberg, Christine Ambrosone, Jie Ping, Ran Tao, Bingshan Li, Xingyi Guo, Guimin Gao, David V. Conti, Nilanjan Chatterjee, Julie R. Palmer, Olufunmilayo I. Olopade, Wei Zheng","doi":"10.1038/s41588-026-02501-5","DOIUrl":"https://doi.org/10.1038/s41588-026-02501-5","url":null,"abstract":"Polygenic risk score (PRS) models effectively predict breast cancer (BC) risk in European-ancestry women but have limited accuracy for African-ancestry women, particularly for aggressive subtypes. We developed PRS models for overall BC, estrogen receptor (ER)-positive, ER-negative and triple-negative BC (TNBC) in African-ancestry women using data from the African Ancestry Breast Cancer Genetics consortium (17,391 cases and 18,800 controls). We applied several PRS methods and integrated information across ancestries and BC subtypes. The best models for overall, ER-positive, ER-negative and TNBC showed an area under the receiving operating curve of 0.612, 0.621, 0.611 and 0.639, respectively, and maintained predictive accuracy in external validation studies with area under the receiving operating curves of 0.612, 0.640, 0.605 and 0.652. We further introduce a parsimonious 162-variant PRS for TNBC with comparable accuracy (0.626). These findings demonstrate markedly improved PRS accuracy for BC risk prediction in African-ancestry women. Using these PRS models for screening will help promote more equitable cancer prevention efforts.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"8 1","pages":""},"PeriodicalIF":30.8,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102120","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 : 2026-02-02DOI: 10.1038/s41588-025-02496-5
Anagha Krishna, Alison Meynert, Karamjit Singh Dolt, Martijn Kelder, Agavni Mesropian, Ailith Ewing, Conny Brouwers, Jill WC Claassens, Margot M. Linssen, Shahida Sheraz, Gillian CA Taylor, Philippe Gautier, Anna Ferrer-Vaquer, Graeme Grimes, Hannes Becher, Ryan Silk, Albert Gris-Oliver, Roser Pinyol, Colin A. Semple, Timothy J. Kendall, Thomas Graham Bird, Anna-Katerina Hadjantonakis, Joseph A. Marsh, Josep M. Llovet, Peter Hohenstein, Andrew J. Wood, Derya D. Ozdemir
CTNNB1, the gene encoding β-catenin, is a frequent target for oncogenic mutations activating the canonical Wnt signaling pathway, typically through missense mutations within a degron hotspot motif in exon 3. Here, we combine saturation genome editing with a fluorescent reporter assay to quantify signaling phenotypes for all 342 possible missense mutations in the mutation hotspot. Our data define the genetic requirements for β-catenin degron function, refine the consensus motif for substrate recognition by β-TRCP and reveal diverse levels of signal activation among known driver mutations. Tumorigenesis in different human tissues involves selection for CTNNB1 mutations spanning distinct ranges of predicted activity. In hepatocellular carcinoma, mutation effect scores distinguish two tumor subclasses with different levels of β-catenin signaling, and weaker mutations predict greater immune cell infiltration in the tumor microenvironment. Our work provides a resource to understand mutational diversity within a pan-cancer mutation hotspot, with potential implications for targeted therapy.
{"title":"Mutational scanning reveals oncogenic CTNNB1 mutations have diverse effects on signaling","authors":"Anagha Krishna, Alison Meynert, Karamjit Singh Dolt, Martijn Kelder, Agavni Mesropian, Ailith Ewing, Conny Brouwers, Jill WC Claassens, Margot M. Linssen, Shahida Sheraz, Gillian CA Taylor, Philippe Gautier, Anna Ferrer-Vaquer, Graeme Grimes, Hannes Becher, Ryan Silk, Albert Gris-Oliver, Roser Pinyol, Colin A. Semple, Timothy J. Kendall, Thomas Graham Bird, Anna-Katerina Hadjantonakis, Joseph A. Marsh, Josep M. Llovet, Peter Hohenstein, Andrew J. Wood, Derya D. Ozdemir","doi":"10.1038/s41588-025-02496-5","DOIUrl":"https://doi.org/10.1038/s41588-025-02496-5","url":null,"abstract":"CTNNB1, the gene encoding β-catenin, is a frequent target for oncogenic mutations activating the canonical Wnt signaling pathway, typically through missense mutations within a degron hotspot motif in exon 3. Here, we combine saturation genome editing with a fluorescent reporter assay to quantify signaling phenotypes for all 342 possible missense mutations in the mutation hotspot. Our data define the genetic requirements for β-catenin degron function, refine the consensus motif for substrate recognition by β-TRCP and reveal diverse levels of signal activation among known driver mutations. Tumorigenesis in different human tissues involves selection for CTNNB1 mutations spanning distinct ranges of predicted activity. In hepatocellular carcinoma, mutation effect scores distinguish two tumor subclasses with different levels of β-catenin signaling, and weaker mutations predict greater immune cell infiltration in the tumor microenvironment. Our work provides a resource to understand mutational diversity within a pan-cancer mutation hotspot, with potential implications for targeted therapy.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"275 1","pages":""},"PeriodicalIF":30.8,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102119","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 : 2026-01-27DOI: 10.1038/s41588-025-02479-6
Wenliang Wang, Manoj Hariharan, Wubin Ding, Anna Bartlett, Cesar Barragan, Rosa Castanon, Ruoxuan Wang, Vince Rothenberg, Haili Song, Joseph R. Nery, Andrew Aldridge, Jordan Altshul, Mia Kenworthy, Hanqing Liu, Wei Tian, Jingtian Zhou, Qiurui Zeng, Huaming Chen, Bei Wei, Irem B. Gündüz, Todd Norell, Timothy J. Broderick, Micah T. McClain, Lisa L. Satterwhite, Thomas W. Burke, Elizabeth A. Petzold, Xiling Shen, Christopher W. Woods, Vance G. Fowler Jr., Felicia Ruffin, Parinya Panuwet, Dana B. Barr, Jennifer L. Beare, Anthony K. Smith, Rachel R. Spurbeck, Sindhu Vangeti, Irene Ramos, German Nudelman, Stuart C. Sealfon, Flora Castellino, Anna Maria Walley, Thomas Evans, Fabian Müller, William J. Greenleaf, Joseph R. Ecker
The epigenome of human immune cells is shaped by both genetics and environmental factors, yet the relative contributions of these influences remain incompletely characterized. Here we use single-nucleus methylation sequencing and assay for transposase-accessible chromatin using sequencing (ATAC–seq) to systematically explore how pathogen and chemical exposures, along with genetic variation, are associated with changes in the immune cell epigenome. Distinct exposure-associated differentially methylated regions (eDMRs) and differentially accessible regions were identified, and a significant correlation between these two modalities was observed. Additionally, genotype-associated DMRs (gDMRs) were detected, indicating that eDMRs are enriched in regulatory regions, whereas gDMRs are preferentially located within gene body marks. Disease-associated single-nucleotide polymorphisms were frequently colocalized with methylation quantitative trait loci, providing cell-type-specific insights into the genetic basis of diseases. These findings highlight the complex interplay between genetic and environmental factors in shaping the immune cell epigenome and advance understanding of immune cell regulation in health and disease.
{"title":"Genetics and environment distinctively shape the human immune cell epigenome","authors":"Wenliang Wang, Manoj Hariharan, Wubin Ding, Anna Bartlett, Cesar Barragan, Rosa Castanon, Ruoxuan Wang, Vince Rothenberg, Haili Song, Joseph R. Nery, Andrew Aldridge, Jordan Altshul, Mia Kenworthy, Hanqing Liu, Wei Tian, Jingtian Zhou, Qiurui Zeng, Huaming Chen, Bei Wei, Irem B. Gündüz, Todd Norell, Timothy J. Broderick, Micah T. McClain, Lisa L. Satterwhite, Thomas W. Burke, Elizabeth A. Petzold, Xiling Shen, Christopher W. Woods, Vance G. Fowler Jr., Felicia Ruffin, Parinya Panuwet, Dana B. Barr, Jennifer L. Beare, Anthony K. Smith, Rachel R. Spurbeck, Sindhu Vangeti, Irene Ramos, German Nudelman, Stuart C. Sealfon, Flora Castellino, Anna Maria Walley, Thomas Evans, Fabian Müller, William J. Greenleaf, Joseph R. Ecker","doi":"10.1038/s41588-025-02479-6","DOIUrl":"https://doi.org/10.1038/s41588-025-02479-6","url":null,"abstract":"The epigenome of human immune cells is shaped by both genetics and environmental factors, yet the relative contributions of these influences remain incompletely characterized. Here we use single-nucleus methylation sequencing and assay for transposase-accessible chromatin using sequencing (ATAC–seq) to systematically explore how pathogen and chemical exposures, along with genetic variation, are associated with changes in the immune cell epigenome. Distinct exposure-associated differentially methylated regions (eDMRs) and differentially accessible regions were identified, and a significant correlation between these two modalities was observed. Additionally, genotype-associated DMRs (gDMRs) were detected, indicating that eDMRs are enriched in regulatory regions, whereas gDMRs are preferentially located within gene body marks. Disease-associated single-nucleotide polymorphisms were frequently colocalized with methylation quantitative trait loci, providing cell-type-specific insights into the genetic basis of diseases. These findings highlight the complex interplay between genetic and environmental factors in shaping the immune cell epigenome and advance understanding of immune cell regulation in health and disease.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"102 1","pages":""},"PeriodicalIF":30.8,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146057203","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 : 2026-01-27DOI: 10.1038/s41588-025-02490-x
Luis B Barreiro,Musa M Mhlanga
{"title":"Written in our genes, epigenetically edited by infection.","authors":"Luis B Barreiro,Musa M Mhlanga","doi":"10.1038/s41588-025-02490-x","DOIUrl":"https://doi.org/10.1038/s41588-025-02490-x","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"1 1","pages":""},"PeriodicalIF":30.8,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146056763","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 : 2026-01-26DOI: 10.1038/s41588-025-02472-z
Michael E. Belloy, Jonathan Graff-Radford, Michael D. Greicius
{"title":"A quantitative trait locus for reduced microglial APOE expression associates with reduced cerebral amyloid angiopathy","authors":"Michael E. Belloy, Jonathan Graff-Radford, Michael D. Greicius","doi":"10.1038/s41588-025-02472-z","DOIUrl":"https://doi.org/10.1038/s41588-025-02472-z","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"8 1","pages":""},"PeriodicalIF":30.8,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146048413","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 : 2026-01-26DOI: 10.1038/s41588-025-02473-y
Lincoln M. P. Shade, Qi Qiao, Yuriko Katsumata, Shubhabrata Mukherjee, Jai G. Broome, Lance A. Johnson, Mark T. W. Ebbert, Peter T. Nelson, David W. Fardo
{"title":"Reply to: a quantitative trait locus for reduced microglial APOE expression associates with reduced cerebral amyloid angiopathy","authors":"Lincoln M. P. Shade, Qi Qiao, Yuriko Katsumata, Shubhabrata Mukherjee, Jai G. Broome, Lance A. Johnson, Mark T. W. Ebbert, Peter T. Nelson, David W. Fardo","doi":"10.1038/s41588-025-02473-y","DOIUrl":"https://doi.org/10.1038/s41588-025-02473-y","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"31 1","pages":""},"PeriodicalIF":30.8,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146048414","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 : 2026-01-23DOI: 10.1038/s41588-025-02480-z
Yuening Zhang,Huanhuan Wei,Jessica Nouws,Wenhao Jiang,Reginald M Brewster,Jenny P Nguyen,SiRu Liang,Samuel M Pass,Weiwei Wang,Florine Collin,Angela Taravella Oill,Sang-Hun Kim,Saul S Siller,Jinjiang Liu,Amy Y Zhao,Phillip Hansbro,Charles Dela Cruz,Clemente Britto,Jose Gomez,Suzanne M Cloonan,Erica L Herzog,TuKiet T Lam,Nicholas E Banovich,Micha Sam B Raredon,Xuchen Zhang,Stefano Mangiola,Robert J Homer,Naftali Kaminski,John McDonough,Francesca Polverino,Xiting Yan,Maor Sauler
Chronic obstructive pulmonary disease (COPD) is clinically and molecularly heterogeneous. To investigate COPD heterogeneity, we profiled lung tissue by single-nucleus RNA sequencing from 141 study participants (1,516,727 nuclei) and identified shifts in cell composition and emergent cell states that correlated with lung function, emphysema and composite symptom scores. Epithelial regenerative states peaked in early COPD and declined thereafter, whereas inflamed nonimmune cells and profibrotic/remodeling states, together with select immune populations, expanded with disease progression. Clustering study participants by the proportion of pathologic cells coupled with spatial transcriptomics identified distinct patterns of cellular co-occurrence within spatially localized niches. Proteomic analyses identified plasma biomarkers of cell states and their impact on the extracellular matrix. Mediation and cell communication analyses revealed cell-autonomous and intercellular communication networks associated with disease. These data define the cellular landscape of COPD heterogeneity, revealing molecular drivers and biomarkers that could inform therapeutic strategies.
{"title":"Aberrant cellular communities underlying disease heterogeneity in chronic obstructive pulmonary disease.","authors":"Yuening Zhang,Huanhuan Wei,Jessica Nouws,Wenhao Jiang,Reginald M Brewster,Jenny P Nguyen,SiRu Liang,Samuel M Pass,Weiwei Wang,Florine Collin,Angela Taravella Oill,Sang-Hun Kim,Saul S Siller,Jinjiang Liu,Amy Y Zhao,Phillip Hansbro,Charles Dela Cruz,Clemente Britto,Jose Gomez,Suzanne M Cloonan,Erica L Herzog,TuKiet T Lam,Nicholas E Banovich,Micha Sam B Raredon,Xuchen Zhang,Stefano Mangiola,Robert J Homer,Naftali Kaminski,John McDonough,Francesca Polverino,Xiting Yan,Maor Sauler","doi":"10.1038/s41588-025-02480-z","DOIUrl":"https://doi.org/10.1038/s41588-025-02480-z","url":null,"abstract":"Chronic obstructive pulmonary disease (COPD) is clinically and molecularly heterogeneous. To investigate COPD heterogeneity, we profiled lung tissue by single-nucleus RNA sequencing from 141 study participants (1,516,727 nuclei) and identified shifts in cell composition and emergent cell states that correlated with lung function, emphysema and composite symptom scores. Epithelial regenerative states peaked in early COPD and declined thereafter, whereas inflamed nonimmune cells and profibrotic/remodeling states, together with select immune populations, expanded with disease progression. Clustering study participants by the proportion of pathologic cells coupled with spatial transcriptomics identified distinct patterns of cellular co-occurrence within spatially localized niches. Proteomic analyses identified plasma biomarkers of cell states and their impact on the extracellular matrix. Mediation and cell communication analyses revealed cell-autonomous and intercellular communication networks associated with disease. These data define the cellular landscape of COPD heterogeneity, revealing molecular drivers and biomarkers that could inform therapeutic strategies.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"7 1","pages":""},"PeriodicalIF":30.8,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033861","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 : 2026-01-23DOI: 10.1038/s41588-025-02454-1
Jin Li,Jun Wang,Ignacio L Ibarra,Xuesen Cheng,Malte D Luecken,Jiaxiong Lu,Aboozar Monavarfeshani,Wenjun Yan,Yiqiao Zheng,Zhen Zuo,Samantha Lynn Zayas Colborn,Berenice Sarahi Cortez,Leah A Owen,Brittney Wick,Xuan Bao,Maximilian Haeussler,Nicholas M Tran,Karthik Shekhar,Joshua R Sanes,J Timothy Stout,Shiming Chen,Yumei Li,Margaret M DeAngelis,Fabian J Theis,Rui Chen
Single-cell sequencing has revolutionized the scale and resolution of molecular profiling of tissues and organs. Here we present an integrated dual-modal reference atlas of the most accessible portion of the mammalian central nervous system, the retina. We compiled around 3.9 million cells from 125 donors of diverse ancestral backgrounds, including 8 published studies and 2.7 million unpublished data points, to create a comprehensive human retina cell atlas (HRCA) with more than 130 cell types identified. We annotated each cluster, identified marker genes and characterized cis-regulatory elements and gene regulatory networks. Our analysis uncovered differences in transcriptome, chromatin and gene regulatory networks across cell types. We modeled changes in gene expression and chromatin accessibility across age, ancestry and tissue region. This integrated atlas enhanced the fine-mapping of genome-wide association study and expression quantitative trait loci variants. Accessible through interactive browsers, this multimodal multidonor and multilab HRCA can facilitate a better understanding of retinal function and pathology.
{"title":"Single-cell atlas of the transcriptome and chromatin accessibility in the human retina.","authors":"Jin Li,Jun Wang,Ignacio L Ibarra,Xuesen Cheng,Malte D Luecken,Jiaxiong Lu,Aboozar Monavarfeshani,Wenjun Yan,Yiqiao Zheng,Zhen Zuo,Samantha Lynn Zayas Colborn,Berenice Sarahi Cortez,Leah A Owen,Brittney Wick,Xuan Bao,Maximilian Haeussler,Nicholas M Tran,Karthik Shekhar,Joshua R Sanes,J Timothy Stout,Shiming Chen,Yumei Li,Margaret M DeAngelis,Fabian J Theis,Rui Chen","doi":"10.1038/s41588-025-02454-1","DOIUrl":"https://doi.org/10.1038/s41588-025-02454-1","url":null,"abstract":"Single-cell sequencing has revolutionized the scale and resolution of molecular profiling of tissues and organs. Here we present an integrated dual-modal reference atlas of the most accessible portion of the mammalian central nervous system, the retina. We compiled around 3.9 million cells from 125 donors of diverse ancestral backgrounds, including 8 published studies and 2.7 million unpublished data points, to create a comprehensive human retina cell atlas (HRCA) with more than 130 cell types identified. We annotated each cluster, identified marker genes and characterized cis-regulatory elements and gene regulatory networks. Our analysis uncovered differences in transcriptome, chromatin and gene regulatory networks across cell types. We modeled changes in gene expression and chromatin accessibility across age, ancestry and tissue region. This integrated atlas enhanced the fine-mapping of genome-wide association study and expression quantitative trait loci variants. Accessible through interactive browsers, this multimodal multidonor and multilab HRCA can facilitate a better understanding of retinal function and pathology.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 1","pages":""},"PeriodicalIF":30.8,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033862","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}
The host genetics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have previously been studied based on cases from the earlier waves of the pandemic in 2020 and 2021, identifying 51 genomic loci associated with infection and/or severity. SARS-CoV-2 has shown rapid sequence evolution, increasing transmissibility, particularly for Omicron variants, which raises the question of whether this affected the host genetic factors. We performed a genome-wide association study of SARS-CoV-2 infection with Omicron variants, including more than 150,000 cases from four cohorts. We identified 13 genome-wide significant loci, of which only five were previously described as associated with SARS-CoV-2 infection. The strongest signal was a single nucleotide polymorphism in an intron of ST6GAL1, a gene affecting immune development and function, connected to three other associated loci (harboring MUC1, MUC5AC and MUC16) through O-glycan biosynthesis. Our study provides robust evidence for individual genetic variation related to glycosylation, translating into susceptibility to SARS-CoV-2 infections with Omicron variants.
{"title":"Central role of glycosylation processes in human genetic susceptibility to SARS-CoV-2 infections with Omicron variants.","authors":"Frank Geller,Xiaoping Wu,Vilma Lammi,Erik Abner,Jesse Tyler Valliere,Katerina Nastou,Angus Burns,Morten Rasmussen,Niklas Worm Andersson,Liam Quinn, ,Bitten Aagaard,Karina Banasik,Sofie Bliddal,Lasse Boding,Søren Brunak,Nanna Brøns,Jonas Bybjerg-Grauholm,Lea Arregui Nordahl Christoffersen,Maria Didriksen,Khoa Manh Dinh,Christian Erikstrup,Ulla Feldt-Rasmussen,Kirsten Grønbæk,Kathrine Agergård Kaspersen,Christina Mikkelsen,Claus Henrik Nielsen,Henriette Svarre Nielsen,Susanne Dam Nielsen,Janna Nissen,Celia Burgos Sequeros,Niels Tommerup,Henrik Ullum, , ,Lampros Spiliopoulos,Peter Bager,Anders Hviid,Erik Sørensen,Ole Birger Pedersen,Jacqueline M Lane,Ria Lassaunière,Hanna M Ollila,Sisse Rye Ostrowski,Bjarke Feenstra","doi":"10.1038/s41588-025-02484-9","DOIUrl":"https://doi.org/10.1038/s41588-025-02484-9","url":null,"abstract":"The host genetics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have previously been studied based on cases from the earlier waves of the pandemic in 2020 and 2021, identifying 51 genomic loci associated with infection and/or severity. SARS-CoV-2 has shown rapid sequence evolution, increasing transmissibility, particularly for Omicron variants, which raises the question of whether this affected the host genetic factors. We performed a genome-wide association study of SARS-CoV-2 infection with Omicron variants, including more than 150,000 cases from four cohorts. We identified 13 genome-wide significant loci, of which only five were previously described as associated with SARS-CoV-2 infection. The strongest signal was a single nucleotide polymorphism in an intron of ST6GAL1, a gene affecting immune development and function, connected to three other associated loci (harboring MUC1, MUC5AC and MUC16) through O-glycan biosynthesis. Our study provides robust evidence for individual genetic variation related to glycosylation, translating into susceptibility to SARS-CoV-2 infections with Omicron variants.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"35 1","pages":""},"PeriodicalIF":30.8,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146021635","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 : 2026-01-22DOI: 10.1038/s41588-025-02468-9
Haochen Zhang, Palash Sashittal, Elias-Ramzey Karnoub, Akhil Jakatdar, Shigeaki Umeda, Jungeui Hong, Anne Marie Noronha, Agustin Cardenas, Amanda Erakky, Caitlin A McIntyre, Akimasa Hayashi, Nicolas Lecomte, Marc Hilmi, Wungki Park, Nan Pang, Eileen M O'Reilly, Alice C Wei, Benjamin J Raphael, Christine A Iacobuzio-Donahue
Most evolutionary studies on pancreatic cancer rely on bulk sequencing, yet clonal evolution happens at the single-cell level. We used single-nucleus DNA sequencing to study 137,491 single nuclei from 24 pancreatic neoplasms reflecting various clinical scenarios. We found higher frequencies of somatic alterations to driver genes that bulk studies indicate; many manifest as copy number alterations and account for the majority of spatial heterogeneity. In pancreatic cancers with canonical KRAS oncogenic mutations, we found likely varied dependence on the genotype that may signify differential response to KRAS inhibition. In pancreatic cancers with germline heterozygous BRCA2 mutations, we discovered varied mechanisms and timing of inactivation of the wild-type allele that sculpted differential evolutionary trajectories. Inactivation of tumor-intrinsic response to transforming growth factor-β happens through various mechanisms, takes place after oncogenesis and coincides with invasion and metastasis, reflecting increasing selective pressure for the phenotype later in pancreatic ductal adenocarcinoma development.
{"title":"Genomic evolution of pancreatic cancer at single-cell resolution.","authors":"Haochen Zhang, Palash Sashittal, Elias-Ramzey Karnoub, Akhil Jakatdar, Shigeaki Umeda, Jungeui Hong, Anne Marie Noronha, Agustin Cardenas, Amanda Erakky, Caitlin A McIntyre, Akimasa Hayashi, Nicolas Lecomte, Marc Hilmi, Wungki Park, Nan Pang, Eileen M O'Reilly, Alice C Wei, Benjamin J Raphael, Christine A Iacobuzio-Donahue","doi":"10.1038/s41588-025-02468-9","DOIUrl":"10.1038/s41588-025-02468-9","url":null,"abstract":"<p><p>Most evolutionary studies on pancreatic cancer rely on bulk sequencing, yet clonal evolution happens at the single-cell level. We used single-nucleus DNA sequencing to study 137,491 single nuclei from 24 pancreatic neoplasms reflecting various clinical scenarios. We found higher frequencies of somatic alterations to driver genes that bulk studies indicate; many manifest as copy number alterations and account for the majority of spatial heterogeneity. In pancreatic cancers with canonical KRAS oncogenic mutations, we found likely varied dependence on the genotype that may signify differential response to KRAS inhibition. In pancreatic cancers with germline heterozygous BRCA2 mutations, we discovered varied mechanisms and timing of inactivation of the wild-type allele that sculpted differential evolutionary trajectories. Inactivation of tumor-intrinsic response to transforming growth factor-β happens through various mechanisms, takes place after oncogenesis and coincides with invasion and metastasis, reflecting increasing selective pressure for the phenotype later in pancreatic ductal adenocarcinoma development.</p>","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":" ","pages":""},"PeriodicalIF":29.0,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146030388","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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