Genome BiologyPub Date : 2025-03-06DOI: 10.1186/s13059-025-03517-6
Qian Liu, Yang Liu, Congyang Yi, Zhi Gao, Zeyan Zhang, Congle Zhu, James A. Birchler, Fangpu Han
{"title":"Genome assembly of the maize B chromosome provides insight into its epigenetic characteristics and effects on the host genome","authors":"Qian Liu, Yang Liu, Congyang Yi, Zhi Gao, Zeyan Zhang, Congle Zhu, James A. Birchler, Fangpu Han","doi":"10.1186/s13059-025-03517-6","DOIUrl":"https://doi.org/10.1186/s13059-025-03517-6","url":null,"abstract":"B chromosomes contribute to the genetic variation in numerous eukaryotes. Yet their genetic and epigenetic characteristics, as well as their effects on the host genome remain poorly understood. Here, we present a comprehensive genome assembly of diploid maize B73 with two copies of B chromosomes using long-read sequencing. We annotate a total of 1124 high-confidence protein-coding genes and 119,579,190 bp repeat elements representing 88.55% of the B chromosome assembly. Using CENH3 ChIP-seq data, we accurately determined the position of the B chromosome centromere, which features a unique monomer-composed satellite array distinct from that found on the chromosome arms. Our research provides detailed genetic and epigenetic maps of the B chromosome, shedding light on its molecular landscape, including DNA sequence composition, DNA methylation patterns, histone modifications, and R-loop distributions across various chromatin regions. Consistent with the cytological morphology of the B chromosome, the less condensed euchromatin regions displayed high levels of H3K4me3, H3K9ac, gene expression, and dense R-loop distributions. DNA methylation on the B chromosome was primarily observed at CG sites. The centromeric region is notably enriched with H3K4me3 and H3K9ac histone modifications and has lower CHG methylation compared to the pericentromeric regions. Moreover, our findings reveal that B chromosome accumulation affects R-loop formation on A chromosomes, and exerts tissue-specific influences on A chromosome gene expression. The accurate assembly and detailed epigenetic maps of the maize B chromosome will help understand the drive mechanism, reveal its conflict with the host genome, and accelerate the construction of artificial chromosomes.\u0000","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"50 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560748","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}
Genome BiologyPub Date : 2025-03-04DOI: 10.1186/s13059-025-03514-9
Chen-Yang Li, Yong-Jia Hong, Bo Li, Xiao-Fei Zhang
{"title":"Benchmarking single-cell cross-omics imputation methods for surface protein expression","authors":"Chen-Yang Li, Yong-Jia Hong, Bo Li, Xiao-Fei Zhang","doi":"10.1186/s13059-025-03514-9","DOIUrl":"https://doi.org/10.1186/s13059-025-03514-9","url":null,"abstract":"Recent advances in single-cell multimodal omics sequencing have facilitated the simultaneous profiling of transcriptomes and surface proteomes within individual cells, offering insights into cellular functions and heterogeneity. However, the high costs and technical complexity of protocols like CITE-seq and REAP-seq constrain large-scale dataset generation. To overcome this limitation, surface protein data imputation methods have emerged to predict protein abundances from scRNA-seq data. We present a comprehensive benchmark of twelve state-of-the-art imputation methods across eleven datasets and six scenarios. Our analysis evaluates the methods’ accuracy, sensitivity to training data size, robustness across experiments, and usability in terms of running time, memory usage, popularity, and user-friendliness. With benchmark experiments in diverse scenarios and a comprehensive evaluation framework of the results, our study offers valuable insights into the performance and applicability of surface protein data imputation methods in single-cell omics research. Based on our results, Seurat v4 (PCA) and Seurat v3 (PCA) demonstrate exceptional performance, offering promising avenues for further research in single-cell omics.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"29 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143538297","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}
Genome BiologyPub Date : 2025-03-03DOI: 10.1186/s13059-025-03507-8
Josep Biayna, Gabrijela Dumbović
{"title":"Decoding subcellular RNA localization one molecule at a time","authors":"Josep Biayna, Gabrijela Dumbović","doi":"10.1186/s13059-025-03507-8","DOIUrl":"https://doi.org/10.1186/s13059-025-03507-8","url":null,"abstract":"Eukaryotic cells are highly structured and composed of multiple membrane-bound and membraneless organelles. Subcellular RNA localization is a critical regulator of RNA function, influencing various biological processes. At any given moment, RNAs must accurately navigate the three-dimensional subcellular environment to ensure proper localization and function, governed by numerous factors, including splicing, RNA stability, modifications, and localizing sequences. Aberrant RNA localization can contribute to the development of numerous diseases. Here, we explore diverse RNA localization mechanisms and summarize advancements in methods for determining subcellular RNA localization, highlighting imaging techniques transforming our ability to study RNA dynamics at the single-molecule level.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"17 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143532504","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}
Genome BiologyPub Date : 2025-02-28DOI: 10.1186/s13059-025-03509-6
Nicolas Antonio da Silva, Onur Özer, Magdalena Haller-Caskie, Yan-Rong Chen, Daniel Kolbe, Sabine Schade-Lindig, Joachim Wahl, Carola Berszin, Michael Francken, Irina Görner, Kerstin Schierhold, Joachim Pechtl, Gisela Grupe, Christoph Rinne, Johannes Müller, Tobias L. Lenz, Almut Nebel, Ben Krause-Kyora
{"title":"Admixture as a source for HLA variation in Neolithic European farming communities","authors":"Nicolas Antonio da Silva, Onur Özer, Magdalena Haller-Caskie, Yan-Rong Chen, Daniel Kolbe, Sabine Schade-Lindig, Joachim Wahl, Carola Berszin, Michael Francken, Irina Görner, Kerstin Schierhold, Joachim Pechtl, Gisela Grupe, Christoph Rinne, Johannes Müller, Tobias L. Lenz, Almut Nebel, Ben Krause-Kyora","doi":"10.1186/s13059-025-03509-6","DOIUrl":"https://doi.org/10.1186/s13059-025-03509-6","url":null,"abstract":"The northern European Neolithic is characterized by two major demographic events: immigration of early farmers from Anatolia at 7500 years before present, and their admixture with local western hunter-gatherers forming late farmers, from around 6200 years before present. The influence of this admixture event on variation in the immune-relevant human leukocyte antigen (HLA) region is understudied. We analyzed genome-wide data of 125 individuals from seven archeological early farmer and late farmer sites located in present-day Germany. The late farmer group studied here is associated with the Wartberg culture, from around 5500–4800 years before present. We note that late farmers resulted from sex-biased admixture from male western hunter-gatherers. In addition, we observe Y-chromosome haplogroup I as the dominant lineage in late farmers, with site-specific sub-lineages. We analyze true HLA genotypes from 135 Neolithic individuals, the majority of which were produced in this study. We observe significant shifts in HLA allele frequencies from early farmers to late farmers, likely due to admixture with western hunter-gatherers. Especially for the haplotype DQB1*04:01-DRB1*08:01, there is evidence for a western hunter-gatherer origin. The HLA diversity increased from early farmers to late farmers. However, it is considerably lower than in modern populations. Both early farmers and late farmers exhibit a relatively narrow HLA allele spectrum compared to today. This coincides with sparse traces of pathogen DNA, potentially indicating a lower pathogen pressure at the time.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"28 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143518778","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}
Genome BiologyPub Date : 2025-02-28DOI: 10.1186/s13059-025-03510-z
Xue Yang, Li Cheng, Ye Xin, Jianxiang Zhang, Xinfeng Chen, Jinchao Xu, Mengli Zhang, Ruopeng Feng, Judith Hyle, Wenjie Qi, Wojciech Rosikiewicz, Beisi Xu, Chunliang Li, Peng Xu
{"title":"CTCF is selectively required for maintaining chromatin accessibility and gene expression in human erythropoiesis","authors":"Xue Yang, Li Cheng, Ye Xin, Jianxiang Zhang, Xinfeng Chen, Jinchao Xu, Mengli Zhang, Ruopeng Feng, Judith Hyle, Wenjie Qi, Wojciech Rosikiewicz, Beisi Xu, Chunliang Li, Peng Xu","doi":"10.1186/s13059-025-03510-z","DOIUrl":"https://doi.org/10.1186/s13059-025-03510-z","url":null,"abstract":"CTCF is considered as the most essential transcription factor regulating chromatin architecture and gene expression. However, genome-wide impact of CTCF on erythropoiesis has not been extensively investigated. Using a state-of-the-art human erythroid progenitor cell model (HUDEP-2 and HEL cell lines), we systematically investigate the effects of acute CTCF loss by an auxin-inducible degron system on transcriptional programs, chromatin accessibility, CTCF genome occupancy, and genome architecture. By integrating multi-omics datasets, we reveal that acute CTCF loss notably disrupts genome-wide chromatin accessibility and the transcription network. We detect over thousands of decreased chromatin accessibility regions but only a few hundred increased regions after CTCF depletion in HUDEP-2 and HEL lines, suggesting the role of CTCF in maintaining proper chromatin openness in the erythroid lineage. CTCF depletion in the erythroid context notably disrupts the boundary integrity of topologically associating domains and chromatin loops but does not affect nuclear compartmentalization. We find erythroid lineage-specific genes, including some metabolism-related genes, are suppressed at immature and mature stages. Notably, we find a subset of genes whose transcriptional levels increase upon CTCF depletion, accompanied by decreased chromatin accessibility regions enriched with the GATA motif. We further decipher the molecular mechanism underlying the CTCF/GATA2 repression axis through distal non-coding chromatin regions. These results suggest a suppressive role of CTCF in gene expression during erythroid lineage specification. Our study reveals a novel role of CTCF in regulating erythroid differentiation by maintaining its proper chromatin openness and gene expression network, which extends our understanding of CTCF biology.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"4 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143518773","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}
Genome BiologyPub Date : 2025-02-28DOI: 10.1186/s13059-025-03501-0
Thomas Cantore, Paola Gasperini, Riccardo Bevilacqua, Yari Ciani, Sanju Sinha, Eytan Ruppin, Francesca Demichelis
{"title":"PRODE recovers essential and context-essential genes through neighborhood-informed scores","authors":"Thomas Cantore, Paola Gasperini, Riccardo Bevilacqua, Yari Ciani, Sanju Sinha, Eytan Ruppin, Francesca Demichelis","doi":"10.1186/s13059-025-03501-0","DOIUrl":"https://doi.org/10.1186/s13059-025-03501-0","url":null,"abstract":"Gene context-essentiality assessment supports precision oncology opportunities. The variability of gene effects inference from loss-of-function screenings across models and technologies limits identifying robust hits. We propose a computational framework named PRODE that integrates gene effects with protein–protein interactions to generate neighborhood-informed essential (NIE) and neighborhood-informed context essential (NICE) scores. It outperforms the canonical gene effect approach in recovering missed essential genes in shRNA screens and prioritizing context-essential hits from CRISPR-KO screens, as supported by in vitro validations. Applied to Her2 + breast cancer tumor samples, PRODE identifies oxidative phosphorylation genes as vulnerabilities with prognostic value, highlighting new therapeutic opportunities.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"44 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143518781","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}
Genome BiologyPub Date : 2025-02-26DOI: 10.1186/s13059-025-03488-8
Henri Schmidt, Minsi Zhang, Dimitar Chakarov, Vineet Bansal, Haralambos Mourelatos, Francisco J. Sánchez-Rivera, Scott W. Lowe, Andrea Ventura, Christina S. Leslie, Yuri Pritykin
{"title":"Genome-wide CRISPR guide RNA design and specificity analysis with GuideScan2","authors":"Henri Schmidt, Minsi Zhang, Dimitar Chakarov, Vineet Bansal, Haralambos Mourelatos, Francisco J. Sánchez-Rivera, Scott W. Lowe, Andrea Ventura, Christina S. Leslie, Yuri Pritykin","doi":"10.1186/s13059-025-03488-8","DOIUrl":"https://doi.org/10.1186/s13059-025-03488-8","url":null,"abstract":"We present GuideScan2 for memory-efficient, parallelizable construction of high-specificity CRISPR guide RNA (gRNA) databases and user-friendly design and analysis of individual gRNAs and gRNA libraries for targeting coding and non-coding regions in custom genomes. GuideScan2 analysis identifies widespread confounding effects of low-specificity gRNAs in published CRISPR screens and enables construction of a gRNA library that reduces off-target effects in a gene essentiality screen. GuideScan2 also enables the design and experimental validation of allele-specific gRNAs in a hybrid mouse genome. GuideScan2 will facilitate CRISPR experiments across a wide range of applications.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"24 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143495232","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}
Genome BiologyPub Date : 2025-02-26DOI: 10.1186/s13059-025-03493-x
Ran Zhang, Mu Yang, Jacob Schreiber, Diana R. O’Day, James M. A. Turner, Jay Shendure, William Stafford Noble, Christine M. Disteche, Xinxian Deng
{"title":"Cross-species imputation and comparison of single-cell transcriptomic profiles","authors":"Ran Zhang, Mu Yang, Jacob Schreiber, Diana R. O’Day, James M. A. Turner, Jay Shendure, William Stafford Noble, Christine M. Disteche, Xinxian Deng","doi":"10.1186/s13059-025-03493-x","DOIUrl":"https://doi.org/10.1186/s13059-025-03493-x","url":null,"abstract":"Cross-species comparison and prediction of gene expression profiles are important to understand regulatory changes during evolution and to transfer knowledge learned from model organisms to humans. Single-cell RNA-seq (scRNA-seq) profiles enable us to capture gene expression profiles with respect to variations among individual cells; however, cross-species comparison of scRNA-seq profiles is challenging because of data sparsity, batch effects, and the lack of one-to-one cell matching across species. Moreover, single-cell profiles are challenging to obtain in certain biological contexts, limiting the scope of hypothesis generation. Here we developed Icebear, a neural network framework that decomposes single-cell measurements into factors representing cell identity, species, and batch factors. Icebear enables accurate prediction of single-cell gene expression profiles across species, thereby providing high-resolution cell type and disease profiles in under-characterized contexts. Icebear also facilitates direct cross-species comparison of single-cell expression profiles for conserved genes that are located on the X chromosome in eutherian mammals but on autosomes in chicken. This comparison, for the first time, revealed evolutionary and diverse adaptations of X-chromosome upregulation in mammals.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"14 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143495231","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}
Genome BiologyPub Date : 2025-02-25DOI: 10.1186/s13059-025-03504-x
Peter Micallef, Manuel Luna Santamaría, Mandy Escobar, Daniel Andersson, Tobias Österlund, Pia Mouhanna, Stefan Filges, Gustav Johansson, Henrik Fagman, Christoffer Vannas, Anders Ståhlberg
{"title":"Digital sequencing is improved by using structured unique molecular identifiers","authors":"Peter Micallef, Manuel Luna Santamaría, Mandy Escobar, Daniel Andersson, Tobias Österlund, Pia Mouhanna, Stefan Filges, Gustav Johansson, Henrik Fagman, Christoffer Vannas, Anders Ståhlberg","doi":"10.1186/s13059-025-03504-x","DOIUrl":"https://doi.org/10.1186/s13059-025-03504-x","url":null,"abstract":"Digital sequencing uses unique molecular identifiers (UMIs) to correct for polymerase induced errors and amplification biases. Here, we design 19 different structured UMIs to minimize the capacity of primers to form non-specific PCR products during library construction using SiMSen-Seq, a PCR-based digital sequencing approach with flexible multiplexing capabilities suitable for tumor-informed mutation analysis. All structured UMI designs demonstrate enhanced assay performance compared with an unstructured reference UMI. The best performing structured UMI design shows significant improvements in all tested aspects of assay and sequencing performance with the ability to reliable detect low variant allele frequencies.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"65 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143485842","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}
Genome BiologyPub Date : 2025-02-25DOI: 10.1186/s13059-025-03479-9
Nghia Millard, Jonathan H. Chen, Mukta G. Palshikar, Karin Pelka, Maxwell Spurrell, Colles Price, Jiang He, Nir Hacohen, Soumya Raychaudhuri, Ilya Korsunsky
{"title":"Batch correcting single-cell spatial transcriptomics count data with Crescendo improves visualization and detection of spatial gene patterns","authors":"Nghia Millard, Jonathan H. Chen, Mukta G. Palshikar, Karin Pelka, Maxwell Spurrell, Colles Price, Jiang He, Nir Hacohen, Soumya Raychaudhuri, Ilya Korsunsky","doi":"10.1186/s13059-025-03479-9","DOIUrl":"https://doi.org/10.1186/s13059-025-03479-9","url":null,"abstract":"Spatial transcriptomics facilitates gene expression analysis of cells in their spatial anatomical context. Batch effects hinder visualization of gene spatial patterns across samples. We present the Crescendo algorithm to correct for batch effects at the gene expression level and enable accurate visualization of gene expression patterns across multiple samples. We show Crescendo’s utility and scalability across three datasets ranging from 170,000 to 7 million single cells across spatial and single-cell RNA sequencing technologies. By correcting for batch effects, Crescendo enhances spatial transcriptomics analyses to detect gene colocalization and ligand-receptor interactions and enables cross-technology information transfer.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"89 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143485843","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}