Cell genomics最新文献

{"title":"Embryo and prejudice: From diverse first transcriptional impressions to a common developmental path.","authors":"Guillaume Giraud Collet, Nicola Festuccia, Pablo Navarro","doi":"10.1016/j.xgen.2025.100919","DOIUrl":"10.1016/j.xgen.2025.100919","url":null,"abstract":"<p><p>Pre-implantation mammalian development culminates in the blastocyst, where embryonic and extra-embryonic tissue founders reside. However, species variations in the underlying mechanisms, starting from zygotic genome activation (ZGA), remain underexplored. In this issue of Cell Genomics, Zhang et al.¹ studied RNA Pol II in bovine embryos and discovered super RNA Pol II domains, a regulatory architecture promoting transcription in species with delayed ZGA.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"5 6","pages":"100919"},"PeriodicalIF":11.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12230233/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144287411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating methods for the prediction of cell-type-specific enhancers in the mammalian cortex.","authors":"Nelson J Johansen, Niklas Kempynck, Nathan R Zemke, Saroja Somasundaram, Seppe De Winter, Marcus Hooper, Deepanjali Dwivedi, Ruchi Lohia, Fabien Wehbe, Bocheng Li, Darina Abaffyová, Ethan J Armand, Julie De Man, Eren Can Ekşi, Nikolai Hecker, Gert Hulselmans, Vasilis Konstantakos, David Mauduit, John K Mich, Gabriele Partel, Tanya L Daigle, Boaz P Levi, Kai Zhang, Yoshiaki Tanaka, Jesse Gillis, Jonathan T Ting, Yoav Ben-Simon, Jeremy Miller, Joseph R Ecker, Bing Ren, Stein Aerts, Ed S Lein, Bosiljka Tasic, Trygve E Bakken","doi":"10.1016/j.xgen.2025.100879","DOIUrl":"10.1016/j.xgen.2025.100879","url":null,"abstract":"<p><p>Identifying cell-type-specific enhancers is critical for developing genetic tools to study the mammalian brain. We organized the \"Brain Initiative Cell Census Network (BICCN) Challenge: Predicting Functional Cell Type-Specific Enhancers from Cross-Species Multi-Omics\" to evaluate machine learning and feature-based methods for nominating enhancer sequences targeting mouse cortical cell types. Methods were assessed using in vivo data from hundreds of adeno-associated virus (AAV)-packaged, retro-orbitally delivered enhancers. Open chromatin was the strongest predictor of functional enhancers, while sequence models improved prediction of non-functional enhancers and identified cell-type-specific transcription factor codes to inform in silico enhancer design. This challenge establishes a benchmark for enhancer prioritization and highlights computational and molecular features critical for identifying functional cortical enhancers, advancing efforts to map and manipulate gene regulation in the mammalian cortex.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100879"},"PeriodicalIF":11.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12230242/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144129592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Morphogenesis, starvation, and light responses in a mushroom-forming fungus revealed by long-read sequencing and extensive expression profiling.","authors":"Botond Hegedüs, Neha Sahu, Balázs Bálint, Sajeet Haridas, Viktória Bense, Zsolt Merényi, Máté Virágh, Hongli Wu, Xiao-Bin Liu, Robert Riley, Anna Lipzen, Maxim Koriabine, Emily Savage, Jie Guo, Kerrie Barry, Vivian Ng, Péter Urbán, Attila Gyenesei, Michael Freitag, Igor V Grigoriev, László G Nagy","doi":"10.1016/j.xgen.2025.100853","DOIUrl":"10.1016/j.xgen.2025.100853","url":null,"abstract":"<p><p>Mushroom-forming fungi (Agaricomycetes) are emerging as pivotal players in several fields of science and industry. Genomic data for Agaricomycetes are accumulating rapidly; however, this is not paralleled by improvements of gene annotations, which leave gene function notoriously poorly understood. We set out to improve our functional understanding of the model mushroom Coprinopsis cinerea by integrating a new, chromosome-level assembly, high-quality gene predictions, and functional information derived from broad gene-expression profiling data. The new annotation includes 5' and 3' untranslated regions (UTRs), polyadenylation sites (PASs), upstream open reading frames (uORFs), splicing isoforms, and microexons, as well as core gene sets corresponding to carbon starvation, light response, and hyphal differentiation. As a result, the genome of C. cinerea has now become the most comprehensively annotated genome among mushroom-forming fungi, which will contribute to multiple rapidly expanding fields, including research on their life history, light and stress responses, as well as multicellular development.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100853"},"PeriodicalIF":11.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12230235/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144029705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of parental autoimmune diseases on type 1 diabetes in offspring can be partially explained by HLA and non-HLA polymorphisms.","authors":"Feiyi Wang, Aoxing Liu, Zhiyu Yang, Pekka Vartiainen, Sakari Jukarainen, Satu Koskela, Richard Oram, Lowri Allen, Jarmo Ritari, Jukka Partanen, Markus Perola, Tiinamaija Tuomi, Andrea Ganna","doi":"10.1016/j.xgen.2025.100854","DOIUrl":"10.1016/j.xgen.2025.100854","url":null,"abstract":"<p><p>Type 1 diabetes (T1D) and other autoimmune diseases (AIDs) often co-occur in families. Leveraging data from 58,284 family trios in Finnish nationwide registers (FinRegistry), we identified that, of 50 parental AIDs examined, 15 were associated with an increased T1D risk in offspring. These identified epidemiological associations were further assessed in 470,000 genotyped Finns from the FinnGen study through comprehensive genetic analyses, partitioned into human leukocyte antigen (HLA) and non-HLA variations. Using FinnGen's 12,563 trios, a within-family polygenic transmission analysis demonstrated that the aggregation of many parental AIDs with offspring T1D can be partially explained by HLA and non-HLA polymorphisms in a disease-dependent manner. We therefore proposed a parental polygenic score (PGS), incorporating both HLA and non-HLA polymorphisms, to characterize the cumulative risk pattern of T1D in offspring. This raises an intriguing possibility of using parental PGS, in conjunction with clinical diagnoses, to inform individuals about T1D risk in their offspring.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100854"},"PeriodicalIF":11.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12230240/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144054174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incorporating multiple functional annotations to improve polygenic risk prediction accuracy.","authors":"Zhonghe Shao, Wangxia Tang, Hongji Wu, Yifan Kong, Xingjie Hao","doi":"10.1016/j.xgen.2025.100850","DOIUrl":"10.1016/j.xgen.2025.100850","url":null,"abstract":"<p><p>We present OmniPRS, a scalable biobank-scale framework that improves genetic risk prediction for complex traits by integrating genome-wide association study (GWAS) summary statistics and functional annotations. It employs a mixed model incorporating tissue-specific genetic variance components from annotations to re-estimate single-nucleotide polymorphism (SNP) effects and constructs tissue-specific polygenic risk scores (PRSs) and aggregates them into the final OmniPRS. Our experiments, encompassing 135 simulation scenarios and 11 representative traits, demonstrate that OmniPRS is flexible and robust, delivering efficient and accurate predictions comparable to ten leading PRS methods. For quantitative (binary) traits, OmniPRS achieved an average improvement of 52.31% (19.83%) versus the clumping and thresholding (C+T) method, 3.92% (1.31%) versus the annotation-integrated PRSs (LDpred-funct), and 8.44% (2.27%) versus the Bayesian-based PRSs (PRScs). Notably, it achieved 35× faster computation than the PRScs. This rapid, precise framework enables efficient polygenic risk scoring with multi-annotation integration for large-scale genomic studies.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100850"},"PeriodicalIF":11.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12230236/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144045624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Parental autoimmunity genetics and offspring type 1 diabetes risk.","authors":"Anthony M Gacita, Struan F A Grant","doi":"10.1016/j.xgen.2025.100895","DOIUrl":"10.1016/j.xgen.2025.100895","url":null,"abstract":"<p><p>Many children presenting with type 1 diabetes have a family history of the disorder or another autoimmune disease. In this issue of Cell Genomics, Wang et al.¹ use extensive clinical and genetic databases to identify the genetic factors contributing to this familial aggregation and develop polygenic risk scores that predict pediatric type 1 diabetes pathogenesis with high accuracy.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"5 6","pages":"100895"},"PeriodicalIF":11.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12230232/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144287413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Indels allow antiviral proteins to evolve functional novelty inaccessible by missense mutations.","authors":"Jeannette L Tenthorey, Serena Del Banco, Ishrak Ramzan, Hayley Klingenberg, Chang Liu, Michael Emerman, Harmit S Malik","doi":"10.1016/j.xgen.2025.100818","DOIUrl":"10.1016/j.xgen.2025.100818","url":null,"abstract":"<p><p>Antiviral proteins often evolve rapidly at virus-binding interfaces to defend against new viruses. We investigated whether antiviral adaptation via missense mutations might face limits, which insertion or deletion mutations (indels) could overcome. Using high-throughput saturation missense mutagenesis, we identify one such case of a nearly insurmountable evolutionary challenge: the human anti-retroviral protein TRIM5α requires more than five missense mutations in its specificity-determining v1 loop to restrict a divergent simian immunodeficiency virus (SIV). However, through a novel saturating indel scanning methodology, we find that duplicating just one amino acid in v1 enables human TRIM5α to potently restrict SIV in a single evolutionary step. Moreover, natural primate TRIM5α v1 loops have evolved indels that confer novel antiviral specificities. Thus, indels enable antiviral proteins to overcome viral challenges otherwise inaccessible by missense mutations. Our findings reveal the potential of often-overlooked indel mutations in driving protein innovation.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100818"},"PeriodicalIF":11.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12230231/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143733475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of targetable vulnerabilities of PLK1-overexpressing cancers by synthetic dosage lethality.","authors":"Chelsea E Cunningham, Frederick S Vizeacoumar, Yue Zhang, Liliia Kyrylenko, Simon Both, Vincent Maranda, He Dong, Jared D W Price, Peng Gao, Konrad Wagner, Yingwen Wu, Mary Lazell-Wright, Ashtalakshmi Ganapathysamy, Rithik Hari, Kalpana K Bhanumathy, Connor Denomy, Anjali Saxena, Jeff P Vizeacoumar, Alain Morejon Morales, Faizaan Khan, Shayla Mosley, Angie Chen, Tetiana Katrii, Ben G E Zoller, Karthic Rajamanickam, Prachi Walke, Lihui Gong, Hardikkumar Patel, Hussain Elhasasna, Renuka Dahiya, Omar Abuhussein, Anton Dmitriev, Tanya Freywald, Erika Prando Munhoz, Eytan Ruppin, Joo Sang Lee, Katharina Rox, Martin Koebel, Laura Hopkins, Cheng Han Lee, Sunil Yadav, Gilles Gasparoni, Jörn Walter, Anand Krishnan, Raju Datla, Behzad Toosi, Kristi Baker, Jalna Meens, David W Cescon, Laurie Ailles, Scot C Leary, Yuliang Wu, Martin Empting, Alexandra K Kiemer, Andrew Freywald, Franco J Vizeacoumar","doi":"10.1016/j.xgen.2025.100876","DOIUrl":"10.1016/j.xgen.2025.100876","url":null,"abstract":"<p><p>Chromosomal instability (CIN) drives tumor heterogeneity, complicating cancer therapy. Although Polo-like kinase 1 (PLK1) overexpression induces CIN, direct inhibition of PLK1 has shown limited clinical benefits. We therefore performed a genome-wide synthetic dosage lethality (SDL) screen to identify effective alternative targets and validated over 100 candidates using in vivo and in vitro secondary CRISPR screens. We employed direct-capture Perturb-seq to assess the transcriptional consequences and viability of each SDL perturbation at a single-cell resolution. This revealed IGF2BP2 as a critical genetic dependency that, when targeted, downregulated PLK1 and significantly restricted tumor growth. Mechanistic analyses showed that IGF2BP2 loss disrupted cellular energy metabolism and mitochondrial ATP production by downregulating PLK1 levels as well as genes associated with oxidative phosphorylation. Consistent with this, pharmacological inhibition of IGF2BP2 severely impacts the viability of PLK1-overexpressing cancer cells addicted to higher metabolic rates. Our work offers a novel therapeutic strategy against PLK1-driven heterogeneous malignancies.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100876"},"PeriodicalIF":11.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12230241/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144065377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The fine art of chromatin folding: Revealing the path of DNA inside mitotic chromosomes.","authors":"Marina Vitoria Gomes, Christian H Haering","doi":"10.1016/j.xgen.2025.100921","DOIUrl":"10.1016/j.xgen.2025.100921","url":null,"abstract":"<p><p>How chromatin fibers fold into rod-shaped mitotic chromosomes has long been a central question in genome biology. Two new studies now reconstruct the path of DNA in human chromosomes at nanoscale resolution and reveal how loop-extruding molecular machines fold chromatin into compact, rod-shaped structures at the onset of mitosis. Using microscopy- or sequencing-based approaches, respectively, both studies converge on similar models of chromosome organization yet differ in key mechanistic details. The findings further challenge textbook hypotheses of higher-order chromatin structures and reignite the quest for a detailed understanding of genome architecture inside living cells.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"5 6","pages":"100921"},"PeriodicalIF":11.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12230230/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144287414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic-based stemness score measures oncogenic dedifferentiation and enables the identification of druggable targets.","authors":"Iga Kołodziejczak-Guglas, Renan L S Simões, Emerson de Souza Santos, Elizabeth G Demicco, Rossana N Lazcano Segura, Weiping Ma, Pei Wang, Yifat Geffen, Erik Storrs, Francesca Petralia, Antonio Colaprico, Felipe da Veiga Leprevost, Pietro Pugliese, Michele Ceccarelli, Houtan Noushmehr, Alexey I Nesvizhskii, Bożena Kamińska, Waldemar Priebe, Jan Lubiński, Bing Zhang, Alexander J Lazar, Paweł Kurzawa, Mehdi Mesri, Ana I Robles, Li Ding, Tathiane M Malta, Maciej Wiznerowicz","doi":"10.1016/j.xgen.2025.100851","DOIUrl":"10.1016/j.xgen.2025.100851","url":null,"abstract":"<p><p>Cancer progression and therapeutic resistance are closely linked to a stemness phenotype. Here, we introduce a protein-expression-based stemness index (PROTsi) to evaluate oncogenic dedifferentiation in relation to histopathology, molecular features, and clinical outcomes. Utilizing datasets from the Clinical Proteomic Tumor Analysis Consortium across 11 tumor types, we validate PROTsi's effectiveness in accurately quantifying stem-like features. Through integration of PROTsi with multi-omics, including protein post-translational modifications, we identify molecular features associated with stemness and proteins that act as active nodes within transcriptional networks, driving tumor aggressiveness. Proteins highly correlated with stemness were identified as potential drug targets, both shared and tumor specific. These stemness-associated proteins demonstrate predictive value for clinical outcomes, as confirmed by immunohistochemistry in multiple samples. The findings emphasize PROTsi's efficacy as a valuable tool for selecting predictive protein targets, a crucial step in customizing anti-cancer therapy and advancing the clinical development of cures for cancer patients.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100851"},"PeriodicalIF":11.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12230239/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144059354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}