Genome Biology最新文献

{"title":"ASPM mediates nuclear entrapment of FOXM1 via liquid-liquid phase separation to promote progression of hepatocarcinoma","authors":"Xunliang Jiang, Jun Liu, Ke Wang, Jianyong Sun, Huilong Yin, Yu Jiang, Yongkang Liu, Ningbo Wang, Xiaochen Ding, Pu Gao, Lin Li, Xiang Zhang, Jipeng Li, Rui Zhang","doi":"10.1186/s13059-025-03526-5","DOIUrl":"https://doi.org/10.1186/s13059-025-03526-5","url":null,"abstract":"Fork-head box protein M1 (FOXM1) plays critical roles in development and progression of multiple cancers, including hepatocellular carcinoma (HCC). However, the exact regulatory hierarchy of FOXM1 remains unclear. Here, a genome-wide screen is performed to identify intranuclear proteins that promote FOXM1 transcription activity via liquid–liquid phase separation (LLPS). Abnormal spindle-like microcephaly associated (ASPM) is identified to interact with FOXM1 protein via LLPS and enhance its stability by preventing proteasome-mediated degradation. ChIP-sequencing data show ASPM and FOXM1 co-occupy the promoters of multiple genes to promote their transcription, enhancing FOXM1-driven oncogenic progression. In functional experiments, inhibition of ASPM suppresses tumor growth of HCC cells in vivo and in vitro, while overexpression of ASPM has opposite effects. Importantly, reconstitution of FOXM1 partially compensates for the weakened proliferative capacity of HCC cells caused by ASPM silencing. Intriguingly, FOXM1 binds to the promoter region of ASPM and transcriptionally activates ASPM expression in HCC cells. Furthermore, we find that a higher co-expression of ASPM and FOXM1 significantly correlates with poor prognosis in HCC patients. It indicates a double positive feedback loop between ASPM and FOXM1 which coordinately promotes the aggressive progression of HCC. Collectively, we demonstrate that LLPS and transcriptional regulation form an oncogenic double positive feedback loop between ASPM and FOXM1. This provides a rationale strategy to treat HCC by targeting this mechanism.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"13 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143675237","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":"aurora: a machine learning gwas tool for analyzing microbial habitat adaptation","authors":"Dalimil Bujdoš, Jens Walter, Paul W. O’Toole","doi":"10.1186/s13059-025-03524-7","DOIUrl":"https://doi.org/10.1186/s13059-025-03524-7","url":null,"abstract":"A primary goal of microbial genome-wide association studies is identifying genomic variants associated with a particular habitat. Existing tools fail to identify known causal variants if the analyzed trait shaped the phylogeny. Furthermore, due to inclusion of allochthonous strains or metadata errors, the stated sources of strains in public databases are often incorrect, and strains may not be adapted to the habitat from which they were isolated. We describe a new tool, aurora, that identifies autochthonous strains and the genes associated with habitats while acknowledging the potential role of the habitat adaptation trait in shaping phylogeny.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"61 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143675234","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":"scVAEDer: integrating deep diffusion models and variational autoencoders for single-cell transcriptomics analysis","authors":"Mehrshad Sadria, Anita Layton","doi":"10.1186/s13059-025-03519-4","DOIUrl":"https://doi.org/10.1186/s13059-025-03519-4","url":null,"abstract":"Discovering a lower-dimensional embedding of single-cell data can improve downstream analysis. The embedding should encapsulate both the high-level features and low-level variations. While existing generative models attempt to learn such low-dimensional representations, they have limitations. Here, we introduce scVAEDer, a scalable deep-learning model that combines the power of variational autoencoders and deep diffusion models to learn a meaningful representation that retains both global structure and local variations. Using the learned embeddings, scVAEDer can generate novel scRNA-seq data, predict perturbation response on various cell types, identify changes in gene expression during dedifferentiation, and detect master regulators in biological processes.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"56 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665978","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":"Global profiling of CPL3-mediated alternative splicing reveals regulatory mechanisms of DGK5 in plant immunity and phosphatidic acid homeostasis","authors":"Sung-Il Kim, Xiyu Ma, Liang Kong, Wenbin Guo, Lahong Xu, Libo Shan, Runxuan Zhang, Ping He","doi":"10.1186/s13059-025-03529-2","DOIUrl":"https://doi.org/10.1186/s13059-025-03529-2","url":null,"abstract":"Alternative splicing of precursor mRNAs serves as a crucial mechanism to enhance gene expression plasticity for organismal adaptation. However, the precise regulation and function of alternative splicing in plant immune gene regulation remain elusive. Here, by deploying in-depth transcriptome profiling with deep genome coverage coupled with differential expression, differential alternative splicing, and differential transcript usage analysis, we reveal profound and dynamic changes in alternative splicing following treatment with microbial pattern flg22 peptides in Arabidopsis. Our findings highlight RNA polymerase II C-terminal domain phosphatase-like 3 (CPL3) as a key regulator of alternative splicing, preferentially influencing the splicing patterns of defense genes rather than their expression levels. CPL3 mediates the production of a flg22-induced alternative splicing variant, diacylglycerol kinase 5α (DGK5α), which differs from the canonical DGK5β in its interaction with the upstream kinase BIK1 and subsequent phosphorylation, resulting in reduced flg22-triggered production of phosphatidic acid and reactive oxygen species. Furthermore, our functional analysis suggests that DGK5β, but not DGK5α, contributes to plant resistance against virulent and avirulent bacterial infections. These findings underscore the role of CPL3 in modulating alternative splicing dynamics of defense genes and DGK5 isoform-mediated phosphatidic acid homeostasis, shedding light on the intricate mechanisms underlying plant immune gene regulation.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"70 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143666021","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":"Analysis of 30 chromosome-level Drosophila genome assemblies reveals dynamic evolution of centromeric satellite repeats","authors":"Daniel Gebert, Amir D. Hay, Jennifer P. Hoang, Adam E. Gibbon, Ian R. Henderson, Felipe Karam Teixeira","doi":"10.1186/s13059-025-03527-4","DOIUrl":"https://doi.org/10.1186/s13059-025-03527-4","url":null,"abstract":"The Drosophila genus is ideal for studying genome evolution due to its relatively simple chromosome structure and small genome size, with rearrangements mainly restricted to within chromosome arms, such as Muller elements. However, work on the rapidly evolving repetitive genomic regions, composed of transposons and tandem repeats, have been hampered by the lack of genus-wide chromosome-level assemblies. Integrating long-read genomic sequencing and chromosome capture technology, here we produce and annotate 30 chromosome-level genome assemblies within the Drosophila genus. Based on this dataset, we reveal the evolutionary dynamics of genome rearrangements across the Drosophila phylogeny, including the identification of genomic regions that show comparatively high structural stability throughout evolution. Moreover, within the ananassae subgroup, we uncover the emergence of new chromosome conformations and the rapid expansion of novel satellite DNA sequence families, which form large and continuous pericentromeric domains with higher-order repeat structures that are reminiscent of those observed in the human and Arabidopsis genomes. These chromosome-level genome assemblies present a valuable resource for future research, the power of which is demonstrated by our analysis of genome rearrangements and chromosome evolution. In addition, based on our findings, we propose the ananassae subgroup as an ideal model system for studying the evolution of centromere structure.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"55 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143640499","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":"Systematic interrogation of functional genes underlying cholesterol and lipid homeostasis","authors":"Haihuan Shan, Shuangshuang Fan, Quanrun Li, Ruipu Liang, Zhisong Chen, Shengnan Wang, Xiaofeng Wang, Yurong Li, Shuai Chen, Kun Yu, Teng Fei","doi":"10.1186/s13059-025-03531-8","DOIUrl":"https://doi.org/10.1186/s13059-025-03531-8","url":null,"abstract":"Dyslipidemia or hypercholesterolemia are among the main risk factors for cardiovascular diseases. Unraveling the molecular basis of lipid or cholesterol homeostasis would help to identify novel drug targets and develop effective therapeutics. Here, we adopt a systematic approach to catalog the genes underlying lipid and cholesterol homeostasis by combinatorial use of high-throughput CRISPR screening, RNA sequencing, human genetic variant association analysis, and proteomic and metabolomic profiling. Such integrative multi-omics efforts identify gamma-glutamyltransferase GGT7 as an intriguing potential cholesterol and lipid regulator. As a SREBP2-dependent target, GGT7 positively regulates cellular cholesterol levels and affects the expression of several cholesterol metabolism genes. Furthermore, GGT7 interacts with actin-dependent motor protein MYH10 to control low-density lipoprotein cholesterol (LDL-C) uptake into the cells. Genetic ablation of Ggt7 in mice leads to reduced serum cholesterol levels, supporting an in vivo role of Ggt7 during cholesterol homeostasis. Our study not only provides a repertoire of lipid or cholesterol regulatory genes from multiple angles but also reveals a causal link between a gamma-glutamyltransferase and cholesterol metabolism.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"19 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635702","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":"A special short-wing petal faba genome and genetic dissection of floral and yield-related traits accelerate breeding and improvement of faba bean","authors":"Rong Liu, Chaoqin Hu, Dan Gao, Mengwei Li, Xingxing Yuan, Liyang Chen, Qin Shu, Zonghe Wang, Xin Yang, Zhengming Dai, Haitian Yu, Feng Yang, Aiqing Zheng, Meiyuan Lv, Vanika Garg, Chengzhi Jiao, Hongyan Zhang, Wanwei Hou, Changcai Teng, Xianli Zhou, Chengzhang Du, Chao Xiang, Dongxu Xu, Yongsheng Tang, Annapurna Chitikineni, Yinmei Duan, Fouad Maalouf, Shiv Kumar Agrawal, Libin Wei, Na Zhao, Rutwik Barmukh, Xiang Li, Dong Wang, Hanfeng Ding, Yujiao Liu, Xin Chen, Rajeev K. Varshney, Yuhua He, Xuxiao Zong, Tao Yang","doi":"10.1186/s13059-025-03532-7","DOIUrl":"https://doi.org/10.1186/s13059-025-03532-7","url":null,"abstract":"A comprehensive study of the genome and genetics of superior germplasms is fundamental for crop improvement. As a widely adapted protein crop with high yield potential, the improvement in breeding and development of the seeds industry of faba bean have been greatly hindered by its giant genome size and high outcrossing rate. To fully explore the genomic diversity and genetic basis of important agronomic traits, we first generate a de novo genome assembly and perform annotation of a special short-wing petal faba bean germplasm (VF8137) exhibiting a low outcrossing rate. Comparative genome and pan-genome analyses reveal the genome evolution characteristics and unique pan-genes among the three different faba bean genomes. In addition, the genome diversity of 558 accessions of faba bean germplasm reveals three distinct genetic groups and remarkable genetic differences between the southern and northern germplasms. Genome-wide association analysis identifies several candidate genes associated with adaptation- and yield-related traits. We also identify one candidate gene related to short-wing petals by combining quantitative trait locus mapping and bulked segregant analysis. We further elucidate its function through multiple lines of evidence from functional annotation, sequence variation, expression differences, and protein structure variation. Our study provides new insights into the genome evolution of Leguminosae and the genomic diversity of faba bean. It offers valuable genomic and genetic resources for breeding and improvement of faba bean.\u0000","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"17 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635701","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":"Multi-task benchmarking of spatially resolved gene expression simulation models","authors":"Xiaoqi Liang, Marni Torkel, Yue Cao, Jean Yee Hwa Yang","doi":"10.1186/s13059-025-03505-w","DOIUrl":"https://doi.org/10.1186/s13059-025-03505-w","url":null,"abstract":"Computational methods for spatially resolved transcriptomics (SRT) are often developed and assessed using simulated data. The effectiveness of these evaluations relies on the ability of simulation methods to accurately reflect experimental data. However, a systematic evaluation framework for spatial simulators is currently lacking. Here, we present SpatialSimBench, a comprehensive evaluation framework that assesses 13 simulation methods using ten distinct STR datasets. We introduce simAdaptor, a tool that extends single-cell simulators by incorporating spatial variables, enabling them to simulate spatial data. SimAdaptor ensures SpatialSimBench is backwards compatible, facilitating direct comparisons between spatially aware simulators and existing non-spatial single-cell simulators through the adaption. Using SpatialSimBench, we demonstrate the feasibility of leveraging existing single-cell simulators for SRT data and highlight performance differences among methods. Additionally, we evaluate the simulation methods based on a total of 35 metrics across data property estimation, various downstream analyses, and scalability. In total, we generated 4550 results from 13 simulation methods, ten spatial datasets, and 35 metrics. Our findings reveal that model estimation can be influenced by distribution assumptions and dataset characteristics. In summary, our evaluation framework provides guidelines for selecting appropriate methods for specific scenarios and informs future method development.\u0000","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"89 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635704","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":"Exploring and mitigating shortcomings in single-cell differential expression analysis with a new statistical paradigm","authors":"Chih-Hsuan Wu, Xiang Zhou, Mengjie Chen","doi":"10.1186/s13059-025-03525-6","DOIUrl":"https://doi.org/10.1186/s13059-025-03525-6","url":null,"abstract":"Differential expression analysis is pivotal in single-cell transcriptomics for unraveling cell-type–specific responses to stimuli. While numerous methods are available to identify differentially expressed genes in single-cell data, recent evaluations of both single-cell–specific methods and methods adapted from bulk studies have revealed significant shortcomings in performance. In this paper, we dissect the four major challenges in single-cell differential expression analysis: excessive zeros, normalization, donor effects, and cumulative biases. These “curses” underscore the limitations and conceptual pitfalls in existing workflows. To address the limitations of current single-cell differential expression analysis methods, we propose GLIMES, a statistical framework that leverages UMI counts and zero proportions within a generalized Poisson/Binomial mixed-effects model to account for batch effects and within-sample variation. We rigorously benchmarked GLIMES against six existing differential expression methods using three case studies and simulations across different experimental scenarios, including comparisons across cell types, tissue regions, and cell states. Our results demonstrate that GLIMES is more adaptable to diverse experimental designs in single-cell studies and effectively mitigates key shortcomings of current approaches, particularly those related to normalization procedures. By preserving biologically meaningful signals, GLIMES offers improved performance in detecting differentially expressed genes. By using absolute RNA expression rather than relative abundance, GLIMES improves sensitivity, reduces false discoveries, and enhances biological interpretability. This paradigm shift challenges existing workflows and highlights the need for careful consideration of normalization strategies, ultimately paving the way for more accurate and robust single-cell transcriptomic analyses.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"61 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635703","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 haplotype-resolved genome assembly of an ancient citrus variety provides insights into the domestication history and fruit trait formation of loose-skin mandarins","authors":"Minqiang Yin, Xiaochan Song, Chao He, Xiyuan Li, Mengyuan Li, Jiangbo Li, Hao Wu, Chuanwu Chen, Li Zhang, Zhenmei Cai, Liqing Lu, Yanhui Xu, Xin Wang, Hualin Yi, Juxun Wu","doi":"10.1186/s13059-025-03535-4","DOIUrl":"https://doi.org/10.1186/s13059-025-03535-4","url":null,"abstract":"Loose-skin mandarins (LSMs) are among the oldest domesticated horticultural crops, yet their domestication history and the genetic basis underlying the formation of key selected traits remain unclear. We provide a chromosome-scale and haplotype-resolved assembly for the ancient Chinese citrus variety Nanfengmiju tangerine. Through the integration of 77 resequenced and 114 published citrus germplasm genomes, we categorize LSMs into 12 distinct groups based on population genomic analyses. We infer that the ancestors of modern cultivated mandarins diverged from wild mandarins in Daoxian approximately 500,000 years ago, when they entered the Yangtze and Pearl River Basins. There, they were domesticated into four ancient cultivation groups, forming the cornerstone of modern Chinese LSM cultivation. We identify selective sweeps underlying quantitative trait loci and genes related to important fruit quality traits, including sweetness and size. We reveal that the co-selection of sugar transporter and metabolism genes are associated with increased fruit sweetness. Significant alterations in the auxin and gibberellin signaling networks may contribute to the enlargement of LSM fruits. We also provide a comprehensive, high-spatiotemporal-resolution atlas of allelic gene expression during citrus fruit development. We detect 5890 allele pairs showing specific expression patterns and a significant increase in variation levels. Our study provides valuable genomic resources and further revises the origin and domestication history of LSMs, offering insights for genetic improvement of citrus plants.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"89 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635692","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}