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}
Genome BiologyPub Date : 2025-02-25DOI: 10.1186/s13059-025-03498-6
Sonia Cruciani, Anna Delgado-Tejedor, Leszek P. Pryszcz, Rebeca Medina, Laia Llovera, Eva Maria Novoa
{"title":"De novo basecalling of RNA modifications at single molecule and nucleotide resolution","authors":"Sonia Cruciani, Anna Delgado-Tejedor, Leszek P. Pryszcz, Rebeca Medina, Laia Llovera, Eva Maria Novoa","doi":"10.1186/s13059-025-03498-6","DOIUrl":"https://doi.org/10.1186/s13059-025-03498-6","url":null,"abstract":"RNA modifications influence RNA function and fate, but detecting them in individual molecules remains challenging for most modifications. Here we present a novel methodology to generate training sets and build modification-aware basecalling models. Using this approach, we develop the m6ABasecaller, a basecalling model that predicts m6A modifications from raw nanopore signals. We validate its accuracy in vitro and in vivo, revealing stable m6A modification stoichiometry across isoforms, m6A co-occurrence within RNA molecules, and m6A-dependent effects on poly(A) tails. Finally, we demonstrate that our method generalizes to other RNA and DNA modifications, paving the path towards future efforts detecting other modifications.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"27 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143485841","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/s13059-025-03508-7
Zhuoyi Song, Bongmin Bae, Simon Schnabl, Fei Yuan, Thareendra De Zoysa, Maureen V. Akinyi, Charlotte A. Le Roux, Karine Choquet, Amanda J. Whipple, Eric L. Van Nostrand
{"title":"Mapping snoRNA-target RNA interactions in an RNA-binding protein-dependent manner with chimeric eCLIP","authors":"Zhuoyi Song, Bongmin Bae, Simon Schnabl, Fei Yuan, Thareendra De Zoysa, Maureen V. Akinyi, Charlotte A. Le Roux, Karine Choquet, Amanda J. Whipple, Eric L. Van Nostrand","doi":"10.1186/s13059-025-03508-7","DOIUrl":"https://doi.org/10.1186/s13059-025-03508-7","url":null,"abstract":"Small nucleolar RNAs (snoRNAs) are non-coding RNAs that function in ribosome and spliceosome biogenesis, primarily by guiding modifying enzymes to specific sites on ribosomal RNA (rRNA) and spliceosomal RNA (snRNA). However, many orphan snoRNAs remain uncharacterized, with unidentified or unvalidated targets, and studies on additional snoRNA-associated proteins are limited. We adapted an enhanced chimeric eCLIP approach to comprehensively profile snoRNA-target RNA interactions using both core and accessory snoRNA-binding proteins as baits. Using core snoRNA-binding proteins, we confirmed most annotated snoRNA-rRNA and snoRNA-snRNA interactions in mouse and human cell lines and called novel, high-confidence interactions for orphan snoRNAs. While some of these interactions result in chemical modification, others may have modification-independent functions. We showed that snoRNA ribonucleoprotein complexes containing certain accessory proteins, like WDR43 and NOLC1, enriched for specific subsets of snoRNA-target RNA interactions with distinct roles in ribosome and spliceosome biogenesis. Notably, we discovered that SNORD89 guides 2′-O-methylation at two neighboring sites in U2 snRNA that fine-tune splice site recognition. Chimeric eCLIP of snoRNA-associating proteins enables a comprehensive framework for studying snoRNA-target interactions in an RNA-binding protein-dependent manner, revealing novel interactions and regulatory roles in RNA biogenesis.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"39 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143485942","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 : 2025-02-24DOI: 10.1186/s13059-025-03484-y
Manvendra Singh, Sabrina M. Leddy, Luis Pedro Iñiguez, Matthew L. Bendall, Douglas F. Nixon, Cédric Feschotte
{"title":"Transposable elements may enhance antiviral resistance in HIV-1 elite controllers","authors":"Manvendra Singh, Sabrina M. Leddy, Luis Pedro Iñiguez, Matthew L. Bendall, Douglas F. Nixon, Cédric Feschotte","doi":"10.1186/s13059-025-03484-y","DOIUrl":"https://doi.org/10.1186/s13059-025-03484-y","url":null,"abstract":"Less than 0.5% of people living with HIV-1 are elite controllers (ECs)—individuals who maintain undetectable plasma viremia without antiretroviral therapy, despite having replication-competent viral reservoirs. While EC CD4+ T cells have been investigated for gene expression signatures associated with HIV-1 resistance, the expression and regulatory activity of transposable elements (TEs) remain unexplored. TEs can directly impact host immune responses to pathogens, including HIV-1, suggesting their activities could contribute to HIV-1 elite control. To begin testing this hypothesis, we conduct a TE-centric analysis of public multi-omics data from ECs and other populations. We find the CD4+ T cell transcriptome and retrotranscriptome of ECs are distinct from healthy controls, from people living with HIV-1 on antiretroviral therapy, and from viremic progressors. However, there is substantial transcriptomic heterogeneity among ECs. We categorize ECs into four clusters with distinct expression and chromatin accessibility profiles of TEs and antiviral factors. Several TE families with known immuno-regulatory activity are differentially expressed among ECs. Their expression positively correlates with their chromatin accessibility in ECs and negatively correlates with the expression of their KRAB zinc-finger (KZNF) repressors. This coordinated, locus-level variation forms a network of putative cis-regulatory elements for genes involved in HIV-1 restriction. We propose that the EC phenotype is driven in part by reduced KZNF-mediated repression of specific TE-derived cis-regulatory elements for antiviral genes, heightening their resistance against HIV-1. Our study reveals heterogeneity in the EC CD4+ T cell transcriptome, including variable expression of TEs and their KZNF controllers, that must be considered when deciphering HIV-1 control mechanisms.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"17 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143477666","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 : 2025-02-21DOI: 10.1186/s13059-025-03500-1
Moses Nyine, Dwight Davidson, Elina Adhikari, Marshall Clinesmith, Huan Wang, Alina Akhunova, Allan Fritz, Eduard Akhunov
{"title":"Genomic signals of ecogeographic adaptation in a wild relative are associated with improved wheat performance under drought stress","authors":"Moses Nyine, Dwight Davidson, Elina Adhikari, Marshall Clinesmith, Huan Wang, Alina Akhunova, Allan Fritz, Eduard Akhunov","doi":"10.1186/s13059-025-03500-1","DOIUrl":"https://doi.org/10.1186/s13059-025-03500-1","url":null,"abstract":"Prioritizing wild relative diversity for improving crop adaptation to emerging drought-prone environments is challenging. Here, we combine the genome-wide environmental scans (GWES) in wheat diploid ancestor Aegilops tauschii (Ae. tauschii) with allele testing in the genetic backgrounds of adapted cultivars to identify diversity for improving wheat adaptation to water-limiting conditions. We evaluate the adaptive allele effects in Ae. tauschii-wheat introgression lines phenotyped for multiple traits under irrigated and water-limiting conditions using both unmanned aerial system-based imaging and conventional approaches. The GWES show that climatic gradients alone explain more than half of genomic variation in Ae. tauschii, with many alleles associated with climatic factors in Ae. tauschii being linked with improved performance of introgression lines under water-limiting conditions. We find that the most significant GWES signals associated with temperature annual range in the wild relative are linked with reduced canopy temperature in introgression lines and increased yield. Our results suggest that introgression of climate-adaptive alleles from Ae. tauschii has the potential to improve wheat performance under water-limiting conditions, and that variants controlling physiological processes responsible for maintaining leaf temperature are likely among the targets of adaptive selection in a wild relative. Adaptive variation uncovered by GWES in wild relatives has the potential to improve climate resilience of crop varieties.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"15 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462863","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 : 2025-02-20DOI: 10.1186/s13059-025-03497-7
Michele Monti, Jonathan Fiorentino, Dimitrios Miltiadis-Vrachnos, Giorgio Bini, Tiziana Cotrufo, Natalia Sanchez de Groot, Alexandros Armaos, Gian Gaetano Tartaglia
{"title":"catGRANULE 2.0: accurate predictions of liquid-liquid phase separating proteins at single amino acid resolution","authors":"Michele Monti, Jonathan Fiorentino, Dimitrios Miltiadis-Vrachnos, Giorgio Bini, Tiziana Cotrufo, Natalia Sanchez de Groot, Alexandros Armaos, Gian Gaetano Tartaglia","doi":"10.1186/s13059-025-03497-7","DOIUrl":"https://doi.org/10.1186/s13059-025-03497-7","url":null,"abstract":"Liquid-liquid phase separation (LLPS) enables the formation of membraneless organelles, essential for cellular organization and implicated in diseases. We introduce catGRANULE 2.0 ROBOT, an algorithm integrating physicochemical properties and AlphaFold-derived structural features to predict LLPS at single-amino-acid resolution. The method achieves high performance and reliably evaluates mutation effects on LLPS propensity, providing detailed predictions of how specific mutations enhance or inhibit phase separation. Supported by experimental validations, including microscopy data, it predicts LLPS across diverse organisms and cellular compartments, offering valuable insights into LLPS mechanisms and mutational impacts. The tool is freely available at https://tools.tartaglialab.com/catgranule2 and https://doi.org/10.5281/zenodo.14205831 .","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"9 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451832","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 : 2025-02-20DOI: 10.1186/s13059-025-03503-y
Ke Xu, Yu Xu, Zirui Wang, Xin Maizie Zhou, Lu Zhang
{"title":"stDyer enables spatial domain clustering with dynamic graph embedding","authors":"Ke Xu, Yu Xu, Zirui Wang, Xin Maizie Zhou, Lu Zhang","doi":"10.1186/s13059-025-03503-y","DOIUrl":"https://doi.org/10.1186/s13059-025-03503-y","url":null,"abstract":"Spatially resolved transcriptomics (SRT) data provide critical insights into gene expression patterns within tissue contexts, necessitating effective methods for identifying spatial domains. We introduce stDyer, an end-to-end deep learning framework for spatial domain clustering in SRT data. stDyer combines Gaussian Mixture Variational AutoEncoder with graph attention networks to learn embeddings and perform clustering. Its dynamic graphs adaptively link units based on Gaussian Mixture assignments, improving clustering and producing smoother domain boundaries. stDyer’s mini-batch strategy and multi-GPU support facilitate scalability to large datasets. Benchmarking against state-of-the-art tools, stDyer demonstrates superior performance in spatial domain clustering, multi-slice analysis, and large-scale dataset handling.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"29 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451830","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}