Genome Biology最新文献

{"title":"Widespread impact of transposable elements on the evolution of post-transcriptional regulation in the cotton genus Gossypium","authors":"Xuehan Tian, Ruipeng Wang, Zhenping Liu, Sifan Lu, Xinyuan Chen, Zeyu Zhang, Fang Liu, Hongbin Li, Xianlong Zhang, Maojun Wang","doi":"10.1186/s13059-025-03534-5","DOIUrl":"https://doi.org/10.1186/s13059-025-03534-5","url":null,"abstract":"Transposable element (TE) expansion has long been known to mediate genome evolution and phenotypic diversity in organisms, but its impact on the evolution of post-transcriptional regulation following species divergence remains unclear. To address this issue, we perform long-read direct RNA sequencing, polysome profiling sequencing, and small RNA sequencing in the cotton genus Gossypium, the species of which range more than three folds in genome size. We find that TE expansion contributes to the turnover of transcription splicing sites and regulatory sequences, leading to changes in alternative splicing patterns and the expression levels of orthologous genes. We also find that TE-derived upstream open reading frames and microRNAs serve as regulatory elements mediating differences in the translation levels of orthologous genes. We further identify genes that exhibit lineage-specific divergence at the transcriptional, splicing, and translational levels, and showcase the high flexibility of gene expression regulation in the evolutionary process. Our work highlights the significant role of TE in driving post-transcriptional regulation divergence in the cotton genus. It offers insights for deciphering the evolutionary mechanisms of cotton species and the formation of biological diversity.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"16 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635706","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 single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients","authors":"Yered Pita-Juarez, Dimitra Karagkouni, Nikolaos Kalavros, Johannes C. Melms, Sebastian Niezen, Toni M. Delorey, Adam L. Essene, Olga R. Brook, Deepti Pant, Disha Skelton-Badlani, Pourya Naderi, Pinzhu Huang, Liuliu Pan, Tyler Hether, Tallulah S. Andrews, Carly G. K. Ziegler, Jason Reeves, Andriy Myloserdnyy, Rachel Chen, Andy Nam, Stefan Phelan, Yan Liang, Mark Gregory, Shanshan He, Michael Patrick, Tushar Rane, Aster Wardhani, Amit Dipak Amin, Jana Biermann, Hanina Hibshoosh, Molly Veregge, Zachary Kramer, Christopher Jacobs, Yusuf Yalcin, Devan Phillips, Michal Slyper, Ayshwarya Subramanian, Orr Ashenberg, Zohar Bloom-Ackermann, Victoria M. Tran, James Gomez, Alexander Sturm, Shuting Zhang, Stephen J. Fleming, Sarah Warren, Joseph Beechem, Deborah Hung, Mehrtash Babadi, Robert F. Padera, Sonya A. MacParland, Gary D. Bader, Nasser Imad, Isaac H. Solomon, Eric Miller, Stefan Riedel, Caroline B. M. Porter, Alexandra-Chloé Villani, Linus T.-Y. Tsai, Winston Hide, Gyongyi Szabo,..","doi":"10.1186/s13059-025-03499-5","DOIUrl":"https://doi.org/10.1186/s13059-025-03499-5","url":null,"abstract":"The molecular underpinnings of organ dysfunction in severe COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we perform single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identify hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells, and a central role in a pro-fibrotic TGFβ signaling cell–cell communications network. Integrated analysis and comparisons with healthy controls reveal extensive changes in the cellular composition and expression states in COVID-19 liver, providing the underpinning of hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis characteristic of COVID-19 cholangiopathy. We also observe Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition is dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"8 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143618471","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":"mRNA m6A regulates gene expression via H3K4me3 shift in 5’ UTR","authors":"Yuna Yang, Yuqing Huang, Tian Wang, Song Li, Jiafu Jiang, Sumei Chen, Fadi Chen, Likai Wang","doi":"10.1186/s13059-025-03515-8","DOIUrl":"https://doi.org/10.1186/s13059-025-03515-8","url":null,"abstract":"N6-methyladenosine (m6A) is a prevalent and conserved RNA modification in eukaryotes. While its roles in the 3’ untranslated regions (3’ UTR) are well-studied, its role in the 5' UTR and its relationship with histone modifications remain underexplored. We demonstrate that m6A methylation in the 5’ UTR of mRNA triggers a downstream shift in H3K4me3 modification. This regulatory mechanism is conserved in Arabidopsis, rice, and chrysanthemum. The observed shift in H3K4me3 is genetically controlled by m6A modifiers and influences gene expression. MTA, the m6A methylase, preferentially binds to phosphorylated serine 5 (Ser5P)-CTD of RNA Pol II during transcription, leading to the displacement of ATX1, the H3K4me3 methylase. This dynamic binding of MTA and ATX1 to RNA Pol II ultimately results in the shift of H3K4me3 modification. Genetic evidence demonstrates that m6A in the 5' UTR controls H3K4me3 shift, thereby affecting SEDOHEPTULOSE-BISPHOSPHATASE expression and leaf senescence. Our study provides new insights into the roles of m6A modification and its crosstalk with histone modification in 5’ UTRs, shedding light on the mechanism of m6A-mediated gene expression regulation.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"22 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143599898","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":"Integrative phenomics, metabolomics and genomics analysis provides new insights for deciphering the genetic basis of metabolism in polished rice","authors":"Hui Feng, Yufei Li, Guoxin Dai, Zhuang Yang, Jingyan Song, Bingjie Lu, Yuan Gao, Yongqi Chen, Jiawei Shi, Luis A. J. Mur, Lejun Yu, Jie Luo, Wanneng Yang","doi":"10.1186/s13059-025-03513-w","DOIUrl":"https://doi.org/10.1186/s13059-025-03513-w","url":null,"abstract":"Metabolomics is one of the most widely used omics tools for deciphering the functional networks of the metabolites for crop improvement. However, it is technically demanding and costly. We propose a relatively inexpensive approach for metabolomics analysis in which metabolomics is combined with hyperspectral imaging via machine learning. This approach can be used to target important steps in flavonoid and lipid biosynthesis in rice. We extract 1848 hyperspectral indices and 887 metabolites from polished grains of 533 Oryza sativa accessions. Hyperspectral indices are then linked to metabolites through correlation analysis and modelling. Based on this, a total of 554 metabolites and 1313 hyperspectral indices are identified for further genome-wide association study (GWAS). By GWAS, we detect 17,509 significant locus-trait associations with 2882 single nucleotide polymorphisms (SNPs). Colocalization analysis links these SNPs to the corresponding metabolites and hyperspectral indices. We detect 6415 pairs of metabolites and hyperspectral indices within a linkage disequilibrium of 300 kb in the Oryza sativa genome. We then characterize 1761 candidate genes colocalized to these loci by transcriptomic analysis. We further verify novel candidate genes encoding a novel flavonoid (LOC_Os09g18450) and a flavonoid/lipid (LOC_Os07g11020) respectively by gene editing and overexpression in rice. Our findings indicate that hyperspectral imaging combined with machine learning methods could serve as a powerful tool for quickly and inexpensively assessing crop metabolites.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"14 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143608417","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":"Single-cell RNA-seq data have prevalent blood contamination but can be rescued by Originator, a computational tool separating single-cell RNA-seq by genetic and contextual information","authors":"Thatchayut Unjitwattana, Qianhui Huang, Yiwen Yang, Leyang Tao, Youqi Yang, Mengtian Zhou, Yuheng Du, Lana X. Garmire","doi":"10.1186/s13059-025-03495-9","DOIUrl":"https://doi.org/10.1186/s13059-025-03495-9","url":null,"abstract":"Single-cell RNA sequencing (scRNA-seq) data from complex human tissues have prevalent blood cell contamination during the sample preparation process. They may also comprise cells of different genetic makeups. We propose a new computational framework, Originator, which deciphers single cells by genetic origin and separates immune cells of blood contamination from those of expected tissue-resident cells. We demonstrate the accuracy of Originator at separating immune cells from the blood and tissue as well as cells of different genetic origins, using a variety of artificially mixed and real datasets, including pancreatic cancer and placentas as examples.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"40 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143589834","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":"Recruitment and rejoining of remote double-strand DNA breaks for enhanced and precise chromosome editing","authors":"Mingyao Wang, Pengchong Fu, Ziheng Chen, Xiangnan Wang, Hanhui Ma, Xuedi Zhang, Guanjun Gao","doi":"10.1186/s13059-025-03523-8","DOIUrl":"https://doi.org/10.1186/s13059-025-03523-8","url":null,"abstract":"Chromosomal rearrangements, such as translocations, deletions, and inversions, underlie numerous genetic diseases and cancers, yet precise engineering of these rearrangements remains challenging. Here, we present a CRISPR-based homologous recombination-mediated rearrangement (HRMR) strategy that leverages homologous donor templates to align and repair broken chromosome ends. HRMR improves efficiency by approximately 80-fold compared to non-homologous end joining, achieving over 95% homologous recombination. Validated across multiple loci and cell lines, HRMR enables efficient and accurate chromosomal rearrangements. Live-cell imaging reveals that homologous donors mediate chromosome end proximity, enhancing rearrangement efficiency. Thus, HRMR provides a powerful tool for disease modeling, chromosomal biology, and therapeutic applications.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"14 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143589832","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":"Trans-ancestral rare variant association study with machine learning-based phenotyping for metabolic dysfunction-associated steatotic liver disease","authors":"Robert Chen, Ben Omega Petrazzini, Áine Duffy, Ghislain Rocheleau, Daniel Jordan, Meena Bansal, Ron Do","doi":"10.1186/s13059-025-03518-5","DOIUrl":"https://doi.org/10.1186/s13059-025-03518-5","url":null,"abstract":"Genome-wide association studies (GWAS) have identified common variants associated with metabolic dysfunction-associated steatotic liver disease (MASLD). However, rare coding variant studies have been limited by phenotyping challenges and small sample sizes. We test associations of rare and ultra-rare coding variants with proton density fat fraction (PDFF) and MASLD case–control status in 736,010 participants of diverse ancestries from the UK Biobank, All of Us, and BioMe and performed a trans-ancestral meta-analysis. We then developed models to accurately predict PDFF and MASLD status in the UK Biobank and tested associations with these predicted phenotypes to increase statistical power. The trans-ancestral meta-analysis with PDFF and MASLD case–control status identifies two single variants and two gene-level associations in APOB, CDH5, MYCBP2, and XAB2. Association testing with predicted phenotypes, which replicates more known genetic variants from GWAS than true phenotypes, identifies 16 single variants and 11 gene-level associations implicating 23 additional genes. Two variants were polymorphic only among African ancestry participants and several associations showed significant heterogeneity in ancestry and sex-stratified analyses. In total, we identified 27 genes, of which 3 are monogenic causes of steatosis (APOB, G6PC1, PPARG), 4 were previously associated with MASLD (APOB, APOC3, INSR, PPARG), and 23 had supporting clinical, experimental, and/or genetic evidence. Our results suggest that trans-ancestral association analyses can identify ancestry-specific rare and ultra-rare coding variants in MASLD pathogenesis. Furthermore, we demonstrate the utility of machine learning in genetic investigations of difficult-to-phenotype diseases in trans-ancestral biobanks.\u0000","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"192 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143582920","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":"Precise engineering of gene expression by editing plasticity","authors":"Yang Qiu, Lifen Liu, Jiali Yan, Xianglei Xiang, Shouzhe Wang, Yun Luo, Kaixuan Deng, Jieting Xu, Minliang Jin, Xiaoyu Wu, Liwei Cheng, Ying Zhou, Weibo Xie, Hai-Jun Liu, Alisdair R. Fernie, Xuehai Hu, Jianbing Yan","doi":"10.1186/s13059-025-03516-7","DOIUrl":"https://doi.org/10.1186/s13059-025-03516-7","url":null,"abstract":"Identifying transcriptional cis-regulatory elements (CREs) and understanding their role in gene expression are essential for the precise manipulation of gene expression and associated phenotypes. This knowledge is fundamental for advancing genetic engineering and improving crop traits. We here demonstrate that CREs can be accurately predicted and utilized to precisely regulate gene expression beyond the range of natural variation. We firstly build two sequence-to-expression deep learning models to respectively identify distal and proximal CREs by combining them with interpretability methods in multiple crops. A large number of distal CREs are verified for enhancer activity in vitro using UMI-STARR-seq on 12,000 synthesized sequences. These comprehensively characterized CREs and their precisely predicted effects further contribute to the design of in silico editing schemes for precise engineering of gene expression. We introduce a novel concept of “editingplasticity” to evaluate the potential of promoter editing to alter expression of each gene. As a proof of concept, both exhaustive prediction and random knockout mutants are analyzed within the promoter region of ZmVTE4, a key gene affecting α-tocopherol content in maize. A high degree of agreement between predicted and observed expression is observed, extending the range of natural variation and thereby allowing the creation of an optimal phenotype. Our study provides a robust computational framework that advances knowledge-guided gene editing for precise regulation of gene expression and crop improvement. By reliably predicting and validating CREs, we offer a tool for targeted genetic modifications, enhancing desirable traits in crops.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"33 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143582919","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":"DAGIP: alleviating cell-free DNA sequencing biases with optimal transport","authors":"Antoine Passemiers, Stefania Tuveri, Tatjana Jatsenko, Adriaan Vanderstichele, Pieter Busschaert, An Coosemans, Dirk Timmerman, Sabine Tejpar, Peter Vandenberghe, Diether Lambrechts, Daniele Raimondi, Joris Robert Vermeesch, Yves Moreau","doi":"10.1186/s13059-025-03511-y","DOIUrl":"https://doi.org/10.1186/s13059-025-03511-y","url":null,"abstract":"Cell-free DNA (cfDNA) is a rich source of biomarkers for various pathophysiological conditions. Preanalytical variables, such as the library preparation protocol or sequencing platform, are major confounders of cfDNA analysis. We present DAGIP, a novel data correction method that builds on optimal transport theory and deep learning, which explicitly corrects for the effect of such preanalytical variables and can infer technical biases. Our method improves cancer detection and copy number alteration analysis by alleviating the sources of variation that are not of biological origin. It also enhances fragmentomic analysis of cfDNA. DAGIP allows the integration of cohorts from different studies.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"17 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143569558","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":"Ultra-sensitive detection of transposon insertions across multiple families by transposable element display sequencing","authors":"Pol Vendrell-Mir, Basile Leduque, Leandro Quadrana","doi":"10.1186/s13059-025-03512-x","DOIUrl":"https://doi.org/10.1186/s13059-025-03512-x","url":null,"abstract":"Mobilization of transposable elements (TEs) can generate large effect mutations. However, due to the difficulty of detecting new TE insertions in genomes and the typically rare occurrence of transposition, the actual rate, distribution, and population dynamics of new insertions remain largely unexplored. We present a TE display sequencing approach that leverages target amplification of TE extremities to detect non-reference TE insertions with high specificity and sensitivity, enabling the detection of insertions at frequencies as low as 1 in 250,000 within a DNA sample. Moreover, this method allows the simultaneous detection of insertions for distinct TE families, including both retrotransposons and DNA transposons, enhancing its versatility and cost-effectiveness for investigating complex “mobilomes.” When combined with nanopore sequencing, this approach enables the identification of insertions using long-read information and achieves a turnaround time from DNA extraction to insertion identification of less than 24 h, significantly reducing the time-to-answer. By analyzing a population of Arabidopsis thaliana plants undergoing a transposition burst, we demonstrate the power of the multiplex TE display sequencing to analyze “evolve and resequence” experiments. Notably, we find that 3–4% of de novo TE insertions exhibit recurrent allele frequency changes indicative of either positive or negative selection. TE display sequencing is an ultra-sensitive, specific, simple, and cost-effective approach for investigating the rate and landscape of new TE insertions across multiple families in large-scale population experiments. We provide a step-by-step experimental protocol and ready-to-use bioinformatic pipelines to facilitate its straightforward implementation.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"15 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560689","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}