Nature genetics最新文献

{"title":"Human intestinal immuno-organoids","authors":"Chiara Anania","doi":"10.1038/s41588-024-01927-z","DOIUrl":"10.1038/s41588-024-01927-z","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 9","pages":"1765-1765"},"PeriodicalIF":31.7,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142170379","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}

{"title":"X chromosome dosage shapes renal cell carcinoma risk","authors":"Tiago Faial","doi":"10.1038/s41588-024-01924-2","DOIUrl":"10.1038/s41588-024-01924-2","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 9","pages":"1765-1765"},"PeriodicalIF":31.7,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142170376","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}

{"title":"The genomics of childhood T-lineage acute lymphoblastic leukemia","authors":"Safia Danovi","doi":"10.1038/s41588-024-01928-y","DOIUrl":"10.1038/s41588-024-01928-y","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 9","pages":"1765-1765"},"PeriodicalIF":31.7,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142170397","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}

{"title":"Disease prediction with multi-omics and biomarkers empowers case–control genetic discoveries in the UK Biobank","authors":"Manik Garg, Marcin Karpinski, Dorota Matelska, Lawrence Middleton, Oliver S. Burren, Fengyuan Hu, Eleanor Wheeler, Katherine R. Smith, Margarete A. Fabre, Jonathan Mitchell, Amanda O’Neill, Euan A. Ashley, Andrew R. Harper, Quanli Wang, Ryan S. Dhindsa, Slavé Petrovski, Dimitrios Vitsios","doi":"10.1038/s41588-024-01898-1","DOIUrl":"10.1038/s41588-024-01898-1","url":null,"abstract":"The emergence of biobank-level datasets offers new opportunities to discover novel biomarkers and develop predictive algorithms for human disease. Here, we present an ensemble machine-learning framework (machine learning with phenotype associations, MILTON) utilizing a range of biomarkers to predict 3,213 diseases in the UK Biobank. Leveraging the UK Biobank’s longitudinal health record data, MILTON predicts incident disease cases undiagnosed at time of recruitment, largely outperforming available polygenic risk scores. We further demonstrate the utility of MILTON in augmenting genetic association analyses in a phenome-wide association study of 484,230 genome-sequenced samples, along with 46,327 samples with matched plasma proteomics data. This resulted in improved signals for 88 known (P < 1 × 10−8) gene–disease relationships alongside 182 gene–disease relationships that did not achieve genome-wide significance in the nonaugmented baseline cohorts. We validated these discoveries in the FinnGen biobank alongside two orthogonal machine-learning methods built for gene–disease prioritization. All extracted gene–disease associations and incident disease predictive biomarkers are publicly available ( http://milton.public.cgr.astrazeneca.com ). MILTON uses phenotype information in the UK Biobank to identify clinical biomarkers and other quantitative traits that characterize diseases. It then constructs augmented cohorts by predicting undiagnosed individuals, improving power to discover gene–disease relationships.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 9","pages":"1821-1831"},"PeriodicalIF":31.7,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41588-024-01898-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142166305","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}

{"title":"Stepwise de novo establishment of inactive X chromosome architecture in early development","authors":"Zhenhai Du, Liangjun Hu, Zhuoning Zou, Meishuo Liu, Zihan Li, Xukun Lu, Clair Harris, Yunlong Xiang, Fengling Chen, Guang Yu, Kai Xu, Feng Kong, Qianhua Xu, Bo Huang, Ling Liu, Qiang Fan, Haifeng Wang, Sundeep Kalantry, Wei Xie","doi":"10.1038/s41588-024-01897-2","DOIUrl":"10.1038/s41588-024-01897-2","url":null,"abstract":"X chromosome inactivation triggers a dramatic reprogramming of transcription and chromosome architecture. However, how the chromatin organization of inactive X chromosome is established de novo in vivo remains elusive. Here, we identified an Xist-separated megadomain structure (X-megadomains) on the inactive X chromosome in mouse extraembryonic lineages and extraembryonic endoderm (XEN) cell lines, and transiently in the embryonic lineages, before Dxz4-delineated megadomain formation at later stages in a strain-specific manner. X-megadomain boundary coincides with strong enhancer activities and cohesin binding in an Xist regulatory region required for proper Xist activation in early embryos. Xist regulatory region disruption or cohesin degradation impaired X-megadomains in extraembryonic endoderm cells and caused ectopic activation of regulatory elements and genes near Xist, indicating that cohesin loading at regulatory elements promotes X-megadomains and confines local gene activities. These data reveal stepwise X chromosome folding and transcriptional regulation to achieve both essential gene activation and global silencing during the early stages of X chromosome inactivation. Hi-C analysis identifies Xist-separated megadomains (X-megadomains) on the inactive X chromosome in mouse early embryos. Cohesin loading at Xist regulatory elements promotes X-megadomain formation and restricts nearby gene activity.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 10","pages":"2185-2198"},"PeriodicalIF":31.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142160474","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}

{"title":"Custom microfluidic chip design enables cost-effective three-dimensional spatiotemporal transcriptomics with a wide field of view","authors":"Junjie Zhu, Kun Pang, Beiyu Hu, Ruiqiao He, Ning Wang, Zewen Jiang, Peifeng Ji, Fangqing Zhao","doi":"10.1038/s41588-024-01906-4","DOIUrl":"10.1038/s41588-024-01906-4","url":null,"abstract":"Spatial transcriptomic techniques offer unprecedented insights into the molecular organization of complex tissues. However, integrating cost-effectiveness, high throughput, a wide field of view and compatibility with three-dimensional (3D) volumes has been challenging. Here we introduce microfluidics-assisted grid chips for spatial transcriptome sequencing (MAGIC-seq), a new method that combines carbodiimide chemistry, spatial combinatorial indexing and innovative microfluidics design. This technique allows sensitive and reproducible profiling of diverse tissue types, achieving an eightfold increase in throughput, minimal cost and reduced batch effects. MAGIC-seq breaks conventional microfluidics limits by enhancing barcoding efficiency and enables analysis of whole postnatal mouse sections, providing comprehensive cellular structure elucidation at near single-cell resolution, uncovering transcriptional variations and dynamic trajectories of mouse organogenesis. Our 3D transcriptomic atlas of the developing mouse brain, consisting of 93 sections, reveals the molecular and cellular landscape, serving as a valuable resource for neuroscience and developmental biology. Overall, MAGIC-seq is a high-throughput, cost-effective, large field of view and versatile method for spatial transcriptomic studies. Microfluidics-assisted grid chips for spatial transcriptome sequencing (MAGIC-seq) is a spatial transcriptomics method combining multiple-grid microfluidic design and prefabricated DNA arrays for increased throughput and reduced cost, with applications for large fields of view and 3D spatial mapping.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 10","pages":"2259-2270"},"PeriodicalIF":31.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41588-024-01906-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142160458","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}

{"title":"Variants in tubule epithelial regulatory elements mediate most heritable differences in human kidney function","authors":"Gabriel B. Loeb, Pooja Kathail, Richard W. Shuai, Ryan Chung, Reinier J. Grona, Sailaja Peddada, Volkan Sevim, Scot Federman, Karl Mader, Audrey Y. Chu, Jonathan Davitte, Juan Du, Alexander R. Gupta, Chun Jimmie Ye, Shawn Shafer, Laralynne Przybyla, Radu Rapiteanu, Nilah M. Ioannidis, Jeremy F. Reiter","doi":"10.1038/s41588-024-01904-6","DOIUrl":"10.1038/s41588-024-01904-6","url":null,"abstract":"Kidney failure, the decrease of kidney function below a threshold necessary to support life, is a major cause of morbidity and mortality. We performed a genome-wide association study (GWAS) of 406,504 individuals in the UK Biobank, identifying 430 loci affecting kidney function in middle-aged adults. To investigate the cell types affected by these loci, we integrated the GWAS with human kidney candidate cis-regulatory elements (cCREs) identified using single-cell assay for transposase-accessible chromatin sequencing (scATAC–seq). Overall, 56% of kidney function heritability localized to kidney tubule epithelial cCREs and an additional 7% to kidney podocyte cCREs. Thus, most heritable differences in adult kidney function are a result of altered gene expression in these two cell types. Using enhancer assays, allele-specific scATAC–seq and machine learning, we found that many kidney function variants alter tubule epithelial cCRE chromatin accessibility and function. Using CRISPRi, we determined which genes some of these cCREs regulate, implicating NDRG1, CCNB1 and STC1 in human kidney function. Integration of genome-wide association analysis of 406,504 individuals in the UK Biobank and scATAC–seq data reveals that variants in tubule epithelial regulatory elements mediate most heritable differences in human kidney function.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 10","pages":"2078-2092"},"PeriodicalIF":31.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142160475","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}

{"title":"Defining and pursuing diversity in human genetic studies","authors":"Maili C. Raven-Adams, Tina Hernandez-Boussard, Yann Joly, Bartha Maria Knoppers, Subhashini Chandrasekharan, Adrian Thorogood, Judit Kumuthini, Calvin Wai Loon Ho, Ariana Gonzlez, Sarah C. Nelson, Yvonne Bombard, Donrich Thaldar, Hanshi Liu, Alessia Costa, Vijaytha Muralidharan, Sasha Henriques, Jamal Nasir, Aimé Lumaka, Beatrice Kaiser, Saumya Shekhar Jamuar, Anna C. F. Lewis","doi":"10.1038/s41588-024-01903-7","DOIUrl":"10.1038/s41588-024-01903-7","url":null,"abstract":"Calls for more diverse data in genetics studies typically fall short of offering further guidance. Here we summarize a policy framework from the Global Alliance for Genomics and Health designed to fill this gap. The framework prompts researchers to consider both what types of diversity are needed and why, and how aims can be achieved through choices made throughout the data life cycle.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 10","pages":"1985-1988"},"PeriodicalIF":31.7,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142158749","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}

{"title":"High-quality genome of a modern soybean cultivar and resequencing of 547 accessions provide insights into the role of structural variation","authors":"Caiying Zhang, Zhenqi Shao, Youbin Kong, Hui Du, Wenlong Li, Zhanwu Yang, Xiangkong Li, Huifeng Ke, Zhengwen Sun, Jiabiao Shao, Shiliang Chen, Hua Zhang, Jiahao Chu, Xinzhu Xing, Rui Tian, Ning Qin, Junru Li, Meihong Huang, Yaqian Sun, Xiaobo Huo, Chengsheng Meng, Guoning Wang, Yuan Liu, Zhiying Ma, Shilin Tian, Xihuan Li","doi":"10.1038/s41588-024-01901-9","DOIUrl":"10.1038/s41588-024-01901-9","url":null,"abstract":"Soybean provides protein, oil and multiple health-related compounds. Understanding the effects of structural variations (SVs) on economic traits in modern breeding is important for soybean improvement. Here we assembled the high-quality genome of modern cultivar Nongdadou2 (NDD2) and identified 25,814 SV–gene pairs compared to 29 reported genomes, with 13 NDD2-private SVs validated in 547 deep-resequencing (average = 18.05-fold) accessions, which advances our understanding of genomic variation biology. We found some insertions/deletions involved in seed protein and weight formation, an inversion related to adaptation to drought and a large intertranslocation implicated in a key divergence event in soybean. Of 749,714 SVs from 547 accessions, 6,013 were significantly associated with 22 yield-related and seed-quality-related traits determined in ten location × year environments. We uncovered 1,761 associated SVs that hit genes or regulatory regions, with 12 in GmMQT influencing oil and isoflavone contents. Our work provides resources and insights into SV roles in soybean improvement. High-quality genome of the modern soybean cultivar Nongdadou2 and deep resequencing of 547 accessions provide insights into the role of structural variations in soybean improvement.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 10","pages":"2247-2258"},"PeriodicalIF":31.7,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142158751","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}

{"title":"NSD2 is a requisite subunit of the AR/FOXA1 neo-enhanceosome in promoting prostate tumorigenesis","authors":"Abhijit Parolia, Sanjana Eyunni, Brijesh Kumar Verma, Eleanor Young, Yihan Liu, Lianchao Liu, James George, Shweta Aras, Chandan Kanta Das, Rahul Mannan, Reyaz ur Rasool, Erick Mitchell-Velasquez, Somnath Mahapatra, Jie Luo, Sandra E. Carson, Lanbo Xiao, Prathibha R. Gajjala, Sharan Venkatesh, Mustapha Jaber, Xiaoju Wang, Tongchen He, Yuanyuan Qiao, Matthew Pang, Yuping Zhang, Jean Ching-Yi Tien, Micheala Louw, Mohammed Alhusayan, Xuhong Cao, Fengyun Su, Omid Tavana, Caiyun Hou, Zhen Wang, Ke Ding, Arul M. Chinnaiyan, Irfan A. Asangani","doi":"10.1038/s41588-024-01893-6","DOIUrl":"10.1038/s41588-024-01893-6","url":null,"abstract":"Androgen receptor (AR) is a ligand-responsive transcription factor that drives terminal differentiation of the prostatic luminal epithelia. By contrast, in tumors originating from these cells, AR chromatin occupancy is extensively reprogrammed to activate malignant phenotypes, the molecular mechanisms of which remain unknown. Here, we show that tumor-specific AR enhancers are critically reliant on H3K36 dimethyltransferase activity of NSD2. NSD2 expression is abnormally induced in prostate cancer, where its inactivation impairs AR transactivation potential by disrupting over 65% of its cistrome. NSD2-dependent AR sites distinctively harbor the chimeric FOXA1:AR half-motif, which exclusively comprise tumor-specific AR enhancer circuitries defined from patient specimens. NSD2 inactivation also engenders increased dependency on the NSD1 paralog, and a dual NSD1/2 PROTAC degrader is preferentially cytotoxic in AR-dependent prostate cancer models. Altogether, we characterize NSD2 as an essential AR neo-enhanceosome subunit that enables its oncogenic activity, and position NSD1/2 as viable co-targets in advanced prostate cancer. CRISPR screen identifies coactivators of the androgen receptor (AR) complex, including NSD2. NSD2 contributes to AR cistrome reprogramming during prostate cancer progression, and its degradation via a novel PROTAC reduces prostate cancer cell viability in vitro.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 10","pages":"2132-2143"},"PeriodicalIF":31.7,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41588-024-01893-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142158750","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}