Genome Biology最新文献

{"title":"SQUiD: ultra-secure storage and analysis of genetic data for the advancement of precision medicine","authors":"Jacob Blindenbach, Jiayi Kang, Seungwan Hong, Caline Karam, Thomas Lehner, Gamze Gürsoy","doi":"10.1186/s13059-024-03447-9","DOIUrl":"https://doi.org/10.1186/s13059-024-03447-9","url":null,"abstract":"Cloud computing allows storing the ever-growing genotype-phenotype datasets crucial for precision medicine. Due to the sensitive nature of this data and varied laws and regulations, additional security measures are needed to ensure data privacy. We develop SQUiD, a secure queryable database for storing and analyzing genotype-phenotype data. SQUiD allows storage and secure querying of data in a low-security, low-cost public cloud using homomorphic encryption in a multi-client setting. We demonstrate SQUiD’s practical usability and scalability using synthetic and UK Biobank data.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"58 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142849046","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":"Increased spatial coupling of integrin and collagen IV in the immunoresistant clear-cell renal-cell carcinoma tumor microenvironment","authors":"Alex C. Soupir, Mitchell T. Hayes, Taylor C. Peak, Oscar Ospina, Nicholas H. Chakiryan, Anders E. Berglund, Paul A. Stewart, Jonathan Nguyen, Carlos Moran Segura, Natasha L. Francis, Paola M. Ramos Echevarria, Jad Chahoud, Roger Li, Kenneth Y. Tsai, Jodi A. Balasi, Yamila Caraballo Peres, Jasreman Dhillon, Lindsey A. Martinez, Warren E. Gloria, Nathan Schurman, Sean Kim, Mark Gregory, James Mulé, Brooke L. Fridley, Brandon J. Manley","doi":"10.1186/s13059-024-03435-z","DOIUrl":"https://doi.org/10.1186/s13059-024-03435-z","url":null,"abstract":"Immunotherapy has improved survival for patients with advanced clear cell renal cell carcinoma (ccRCC), but resistance to therapy develops in most patients. We use cellular-resolution spatial transcriptomics in patients with immunotherapy naïve and exposed primary ccRCC tumors to better understand immunotherapy resistance. Spatial molecular imaging of tumor and adjacent stroma samples from 21 tumors suggests that viable tumors following immunotherapy harbor more stromal CD8 + T cells and neutrophils than immunotherapy naïve tumors. YES1 is significantly upregulated in immunotherapy exposed tumor cells. Spatial GSEA shows that the epithelial-mesenchymal transition pathway is spatially enriched and the associated ligand-receptor transcript pair COL4A1-ITGAV has significantly higher autocorrelation in the stroma after exposure to immunotherapy. More integrin αV + cells are observed in immunotherapy exposed stroma on multiplex immunofluorescence validation. Compared to other cancers in TCGA, ccRCC tumors have the highest expression of both COL4A1 and ITGAV. Assessing bulk RNA expression and proteomic correlates in CPTAC databases reveals that collagen IV protein is more abundant in advanced stages of disease. Spatial transcriptomics of samples of 3 patient cohorts with cRCC tumors indicates that COL4A1 and ITGAV are more autocorrelated in immunotherapy-exposed stroma compared to immunotherapy-naïve tumors, with high expression among fibroblasts, tumor cells, and endothelium. Further research is needed to understand changes in the ccRCC tumor immune microenvironment and explore potential therapeutic role of integrin after immunotherapy treatment.\u0000","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"53 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142776470","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":"Systemic evaluation of various CRISPR/Cas13 orthologs for knockdown of targeted transcripts in plants","authors":"Lu Yu, Jiawei Zou, Amjad Hussain, Ruoyu Jia, Yibo Fan, Jinhang Liu, Xinhui Nie, Xianlong Zhang, Shuangxia Jin","doi":"10.1186/s13059-024-03448-8","DOIUrl":"https://doi.org/10.1186/s13059-024-03448-8","url":null,"abstract":"CRISPR/Cas13 system, recognized for its compact size and specificity in targeting RNA, is currently employed for RNA degradation. However, the potential of various CRISPR/Cas13 subtypes, particularly concerning the knockdown of endogenous transcripts, remains to be comprehensively characterized in plants. Here we present a full spectrum of editing profiles for seven Cas13 orthologs from five distinct subtypes: VI-A (LwaCas13a), VI-B (PbuCas13b), VI-D (RfxCas13d), VI-X (Cas13x.1 and Cas13x.2), and VI-Y (Cas13y.1 and Cas13y.2). A systematic evaluation of the knockdown effects on two endogenous transcripts (GhCLA and GhPGF in cotton) as well as an RNA virus (TMV in tobacco) reveals that RfxCas13d, Cas13x.1, and Cas13x.2 exhibit enhanced stability with editing efficiencies ranging from 58 to 80%, closely followed by Cas13y.1 and Cas13y.2. Notably, both Cas13x.1 and Cas13y.1 can simultaneously degrade two endogenous transcripts through a tRNA-crRNA cassette approach, achieving editing efficiencies of up to 50%. Furthermore, different Cas13 orthologs enable varying degrees of endogenous transcript knockdown with minimal off-target effects, generating germplasms that exhibit a diverse spectrum of mutant phenotypes. Transgenic tobacco plants show significant reductions in damage, along with mild oxidative stress and minimal accumulation of viral particles after TMV infection. In conclusion, our study presents an efficient and reliable platform for transcriptome editing that holds promise for plant functional research and future crop improvement.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"10 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142776471","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":"Chromatin loops gather targets of upstream regulators together for efficient gene transcription regulation during vernalization in wheat","authors":"Yanyan Liu, Xintong Xu, Chao He, Liujie Jin, Ziru Zhou, Jie Gao, Minrong Guo, Xin Wang, Chuanye Chen, Mohammed H. Ayaad, Xingwang Li, Wenhao Yan","doi":"10.1186/s13059-024-03437-x","DOIUrl":"https://doi.org/10.1186/s13059-024-03437-x","url":null,"abstract":"Plants respond to environmental stimuli by altering gene transcription that is highly related with chromatin status, including histone modification, chromatin accessibility, and three-dimensional chromatin interaction. Vernalization is essential for the transition to reproductive growth for winter wheat. How wheat reshapes its chromatin features, especially chromatin interaction during vernalization, remains unknown. Combinatory analysis of gene transcription and histone modifications in winter wheat under different vernalization conditions identifies 17,669 differential expressed genes and thousands of differentially enriched peaks of H3K4me3, H3K27me3, and H3K9ac. We find dynamic gene expression across the vernalization process is highly associated with H3K4me3. More importantly, the dynamic H3K4me3- and H3K9ac-associated chromatin-chromatin interactions demonstrate that vernalization leads to increased chromatin interactions and gene activation. Remarkably, spatially distant targets of master regulators like VRN1 and VRT2 are gathered together by chromatin loops to achieve efficient transcription regulation, which is designated as a “shepherd” model. Furthermore, by integrating gene regulatory network for vernalization and natural variation of flowering time, TaZNF10 is identified as a negative regulator for vernalization-related flowering time in wheat. We reveal dynamic gene transcription network during vernalization and find that the spatially distant genes can be recruited together via chromatin loops associated with active histone mark thus to be more efficiently found and bound by upstream regulator. It provides new insights into understanding vernalization and response to environmental stimuli in wheat and other plants.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"25 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142760480","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":"EpiCHAOS: a metric to quantify epigenomic heterogeneity in single-cell data","authors":"Katherine Kelly, Michael Scherer, Martina Maria Braun, Pavlo Lutsik, Christoph Plass","doi":"10.1186/s13059-024-03446-w","DOIUrl":"https://doi.org/10.1186/s13059-024-03446-w","url":null,"abstract":"Epigenetic heterogeneity is a fundamental property of biological systems and is recognized as a potential driver of tumor plasticity and therapy resistance. Single-cell epigenomics technologies have been widely employed to study epigenetic variation between—but not within—cellular clusters. We introduce epiCHAOS: a quantitative metric of cell-to-cell heterogeneity, applicable to any single-cell epigenomics data type. After validation in synthetic datasets, we apply epiCHAOS to investigate global and region-specific patterns of epigenetic heterogeneity across diverse biological systems. EpiCHAOS provides an excellent approximation of stemness and plasticity in development and malignancy, making it a valuable addition to single-cell cancer epigenomics analyses.\u0000","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"103 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142760533","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":"Functional screening reveals genetic dependencies and diverging cell cycle control in atypical teratoid rhabdoid tumors","authors":"Daniel J. Merk, Foteini Tsiami, Sophie Hirsch, Bianca Walter, Lara A. Haeusser, Jens D. Maile, Aaron Stahl, Mohamed A. Jarboui, Anna Lechado-Terradas, Franziska Klose, Sepideh Babaei, Jakob Admard, Nicolas Casadei, Cristiana Roggia, Michael Spohn, Jens Schittenhelm, Stephan Singer, Ulrich Schüller, Federica Piccioni, Nicole S. Persky, Manfred Claassen, Marcos Tatagiba, Philipp J. Kahle, David E. Root, Markus Templin, Ghazaleh Tabatabai","doi":"10.1186/s13059-024-03438-w","DOIUrl":"https://doi.org/10.1186/s13059-024-03438-w","url":null,"abstract":"Atypical teratoid rhabdoid tumors (ATRT) are incurable high-grade pediatric brain tumors. Despite intensive research efforts, the prognosis for ATRT patients under currently established treatment protocols is poor. While novel therapeutic strategies are urgently needed, the generation of molecular-driven treatment concepts is a challenge mainly due to the absence of actionable genetic alterations. We here use a functional genomics approach to identify genetic dependencies in ATRT, validate selected hits using a functionally instructed small molecule drug library, and observe preferential activity in ATRT cells without subgroup-specific selectivity. CDK4/6 inhibitors are among the most potent drugs and display anti-tumor efficacy due to mutual exclusive dependency on CDK4 or CDK6. Chemogenetic interactor screens reveal a broad spectrum of G1 phase cell cycle regulators that differentially enable cell cycle progression and modulate response to CDK4/6 inhibition in ATRT cells. In this regard, we find that the ubiquitin ligase substrate receptor AMBRA1 acts as a context-specific inhibitor of cell cycle progression by regulating key components of mitosis including aurora kinases. Our data provide a comprehensive resource of genetic and chemical dependencies in ATRTs, which will inform further preclinical evaluation of novel targeted therapies for this tumor entity. Furthermore, this study reveals a unique mechanism of cell cycle inhibition as the basis for tumor suppressive functions of AMBRA1.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"79 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758451","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":"MoCHI: neural networks to fit interpretable models and quantify energies, energetic couplings, epistasis, and allostery from deep mutational scanning data","authors":"Andre J. Faure, Ben Lehner","doi":"10.1186/s13059-024-03444-y","DOIUrl":"https://doi.org/10.1186/s13059-024-03444-y","url":null,"abstract":"We present MoCHI, a tool to fit interpretable models using deep mutational scanning data. MoCHI infers free energy changes, as well as interaction terms (energetic couplings) for specified biophysical models, including from multimodal phenotypic data. When a user-specified model is unavailable, global nonlinearities (epistasis) can be estimated from the data. MoCHI also leverages ensemble, background-averaged epistasis to learn sparse models that can incorporate higher-order epistatic terms. MoCHI is freely available as a Python package ( https://github.com/lehner-lab/MoCHI ) relying on the PyTorch machine learning framework and allows biophysical measurements at scale, including the construction of allosteric maps of proteins.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"26 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758455","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":"SMART: spatial transcriptomics deconvolution using marker-gene-assisted topic model","authors":"Chen Xi Yang, Don D. Sin, Raymond T. Ng","doi":"10.1186/s13059-024-03441-1","DOIUrl":"https://doi.org/10.1186/s13059-024-03441-1","url":null,"abstract":"While spatial transcriptomics offer valuable insights into gene expression patterns within the spatial context of tissue, many technologies do not have a single-cell resolution. Here, we present SMART, a marker gene-assisted deconvolution method that simultaneously infers the cell type-specific gene expression profile and the cellular composition at each spot. Using multiple datasets, we show that SMART outperforms the existing methods in realistic settings. It also provides a two-stage approach to enhance its performance on cell subtypes. The covariate model of SMART enables the identification of cell type-specific differentially expressed genes across conditions, elucidating biological changes at a single-cell-type resolution.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"82 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758506","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":"HTAD: a human-in-the-loop framework for supervised chromatin domain detection","authors":"Wei Shen, Ping Zhang, Yiwei Jiang, Hailin Tao, Zhike Zi, Li Li","doi":"10.1186/s13059-024-03445-x","DOIUrl":"https://doi.org/10.1186/s13059-024-03445-x","url":null,"abstract":"Topologically associating domains (TADs) are essential units of genome architecture, influencing transcriptional regulation and diseases. Despite numerous methods proposed for TAD identification, it remains challenging due to complex background and nested TAD structures. We introduce HTAD, a human-in-the-loop TAD caller that combines machine learning with human supervision to achieve high accuracy. HTAD begins with feature extraction for potential TAD border pairs, followed by an interactive labeling process through active learning. Performance assessments using public curation and synthetic datasets demonstrate HTAD’s superiority over other state-of-the-art methods and reveal highly hierarchical TAD structures, offering a human-in-the-loop solution for detecting complex genomic patterns.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"49 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758168","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":"Hierarchical annotation of eQTLs by H-eQTL enables identification of genes with cell type-divergent regulation","authors":"Pawel F. Przytycki, Katherine S. Pollard","doi":"10.1186/s13059-024-03440-2","DOIUrl":"https://doi.org/10.1186/s13059-024-03440-2","url":null,"abstract":"While context-type-specific regulation of genes is largely determined by cis-regulatory regions, attempts to identify cell type-specific eQTLs are complicated by the nested nature of cell types. We present hierarchical eQTL (H-eQTL), a network-based model for hierarchical annotation of bulk-derived eQTLs to levels of a cell type tree using single-cell chromatin accessibility data and no clustering of cells into discrete cell types. Using our model, we annotate bulk-derived eQTLs from the developing brain with high specificity to levels of a cell type hierarchy, which allows sensitive detection of genes with multiple distinct non-coding elements regulating their expression in different cell types.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"256 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142697031","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}