Genome BiologyPub Date : 2025-09-29DOI: 10.1186/s13059-025-03742-z
Erica Dinatale, Rory J. Craig, Claudia Martinho, Hajk-Georg Drost, Susana M. Coelho
{"title":"Characterization of the transposable element landscape shaping the Ectocarpus genome","authors":"Erica Dinatale, Rory J. Craig, Claudia Martinho, Hajk-Georg Drost, Susana M. Coelho","doi":"10.1186/s13059-025-03742-z","DOIUrl":"https://doi.org/10.1186/s13059-025-03742-z","url":null,"abstract":"Comprising up to 90% of eukaryotic genomes, transposable elements (TEs) are mobile genetic units that play fundamental roles in evolution. Brown algae, one of the most complex multicellular eukaryotic groups that evolved independently from plants, fungi, and animals, are particularly underexplored in their transposon biology, especially when studied in a developmental context. Here, we explore the TE landscape of the model brown alga Ectocarpus, using a high-quality genome assembly complemented by extensive manual curation. TEs account for 28% of the genome, with a predominance of evolutionarily young elements. DNA transposons represent the most abundant and diverse TE subclass. Notably, TEs are significantly enriched along the sex chromosomes, a pattern potentially driven by local transposition events from the non-recombining sex-determining region into the pseudoautosomal regions. The genome harbors a high density of intronic TEs, which show minimal impact on host gene expression; however, intronic TEs tend to be shorter and more degraded than intergenic copies, suggesting selective pressures on their retention in the genome. Intact and potentially active TEs are preferentially associated with small RNAs and the histone modification H3K79me2, with over 70% of H3K79me2-marked intact TEs also enriched in small RNAs. This stable association indicates tight and sustained silencing of intact TEs throughout the life cycle of Ectocarpus. Our study highlights the genetic diversity of the Ectocarpus mobilome and presents a complex, multilayered landscape of TE regulation mechanisms which involves small RNAs and chromatin modifications in the absence of an epigenetic silencing machinery that would be comparable to animals or plants.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"96 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145182832","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 : 2025-09-29DOI: 10.1186/s13059-025-03727-y
Guillermo Palou-Márquez, Fran Supek
{"title":"Variable efficiency of nonsense-mediated mRNA decay across human tissues, tumors and individuals","authors":"Guillermo Palou-Márquez, Fran Supek","doi":"10.1186/s13059-025-03727-y","DOIUrl":"https://doi.org/10.1186/s13059-025-03727-y","url":null,"abstract":"Nonsense-mediated mRNA decay (NMD) is a quality-control pathway that degrades mRNA bearing premature termination codons (PTCs) resulting from mutation or mis-splicing, and that additionally participates in gene regulation of unmutated transcripts. While NMD activity is known to differ between examples of PTCs, it is less well studied if human tissues differ in NMD activity, or if individuals differ. We analyzed exomes and matched transcriptomes from Human tumors and healthy tissues to quantify individual-level NMD efficiency, and assess its variability between tissues, tumors, and individuals. This was done by monitoring mRNA levels of endogenous NMD target transcripts, and additionally supported by allele-specific expression of germline PTCs. Nervous system and reproductive system tissues have lower NMD efficiency than other tissues, such as the digestive tract. Next, there is systematic inter-individual variability in NMD efficiency, and we identify two underlying mechanisms. First, somatic copy number alterations can robustly associate with NMD efficiency, prominently the commonly-occurring gain at chromosome 1q that encompasses two core NMD genes: SMG5 and SMG7 and additional functionally interacting genes such as PMF1 and GON4L. Second, deleterious germline variants in genes such as the KDM6B chromatin modifier can associate with higher or lower NMD efficiency in individuals. Variable NMD efficiency modulates positive selection upon somatic nonsense mutations in tumor suppressor genes, and is associated with cancer patient survival and immunotherapy responses. NMD efficiency is variable across human tissues, and it is additionally variable across individuals and tumors thereof due to germline and somatic genetic alterations.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"11 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145182836","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 : 2025-09-29DOI: 10.1186/s13059-025-03741-0
Ziming Zhong, Mark Bailey, Yong-In Kim, Nazanin P. Afsharyan, Briony Parker, Louise Arathoon, Xiaowei Li, Chelsea A. Rundle, Andrew Behrens, Danny Nedialkova, Gancho Slavov, Keywan Hassani-Pak, Kathryn S. Lilley, Frederica L. Theodoulou, Richard Mott
{"title":"The distinct roles of genome, methylation, transcription, and translation on protein expression in Arabidopsis thaliana resolve the Central Dogma’s information flow","authors":"Ziming Zhong, Mark Bailey, Yong-In Kim, Nazanin P. Afsharyan, Briony Parker, Louise Arathoon, Xiaowei Li, Chelsea A. Rundle, Andrew Behrens, Danny Nedialkova, Gancho Slavov, Keywan Hassani-Pak, Kathryn S. Lilley, Frederica L. Theodoulou, Richard Mott","doi":"10.1186/s13059-025-03741-0","DOIUrl":"https://doi.org/10.1186/s13059-025-03741-0","url":null,"abstract":"We investigate the flow of genetic information from DNA to RNA to protein as described by the Central Dogma in molecular biology, to determine the impact of intermediate genomic levels on plant protein expression. We perform genomic profiling of rosette leaves in two Arabidopsis accessions, Col-0 and Can-0, and assemble their genomes using long reads and chromatin interaction data. We measure gene and protein expression in biological replicates grown in a controlled environment, also measuring CpG methylation, ribosome-associated transcript levels, and tRNA abundance. Each omic level is highly reproducible between biological replicates and between accessions despite their ~1% sequence divergence; the single best predictor of any level in one accession is the corresponding level in the other. Within each accession, gene codon frequencies accurately model both mRNA and protein expression. The effects of a codon on mRNA and protein expression are highly correlated but independent of genome-wide codon frequencies or tRNA levels which instead match genome-wide amino acid frequencies. Ribosome-associated transcripts closely track mRNA levels. DNA codon frequencies and mRNA expression levels are the main predictors of protein abundance. In the absence of environmental perturbation neither gene-body methylation, tRNA abundance nor ribosome-associated transcript levels add appreciable information. The impact of constitutive gene-body methylation is mostly explained by gene codon composition. tRNA abundance tracks overall amino acid demand. However, genetic differences between accessions associate with differential gene-body methylation by inflating differential expression variation. Our data show that the dogma holds only if both sequence and abundance information in mRNA are considered.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"53 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145182808","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 : 2025-09-29DOI: 10.1186/s13059-025-03772-7
Blythe G. Hospelhorn, Benjamin K. Kesler, Hossein Jashnsaz, Gregor Neuert
{"title":"TrueSpot: a robust automated tool for quantifying signal puncta in fluorescent imaging","authors":"Blythe G. Hospelhorn, Benjamin K. Kesler, Hossein Jashnsaz, Gregor Neuert","doi":"10.1186/s13059-025-03772-7","DOIUrl":"https://doi.org/10.1186/s13059-025-03772-7","url":null,"abstract":"Characterizing the movement of biomolecules in single cells quantitatively is essential to understanding fundamental biological mechanisms. RNA fluorescent in situ hybridization (RNA-FISH) is a technique for visualizing RNA in fixed cells using fluorescent probes. Automated processing of the resulting images is essential for large datasets. Here we demonstrate that our RNA-FISH image processing tool, TrueSpot, is useful for automatically detecting the locations of RNA at single molecule resolution. TrueSpot also performs well on images with immunofluorescent and GFP-tagged clustered protein targets. Additionally, we show that our 3D spot detection approach substantially outperforms current 2D spot detection algorithms.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"28 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145182835","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 : 2025-09-29DOI: 10.1186/s13059-025-03809-x
Zhigang Ma, Jiazi Zhang, Hongcui Pei, Yanhong Liu, Hongning Tong, Lei Wang, Zefu Lu
{"title":"DeepWheat: predicting the effects of genomic variants on gene expression and regulatory activities across tissues and varieties in wheat using deep learning","authors":"Zhigang Ma, Jiazi Zhang, Hongcui Pei, Yanhong Liu, Hongning Tong, Lei Wang, Zefu Lu","doi":"10.1186/s13059-025-03809-x","DOIUrl":"https://doi.org/10.1186/s13059-025-03809-x","url":null,"abstract":"Spatiotemporal gene expression shapes key agronomic traits, yet tissue-specific prediction remains challenging in complex crops. We present DeepWheat, a broadly applicable deep learning framework comprising DeepEXP and DeepEPI, for accurate, tissue-specific gene expression prediction. DeepEXP integrates sequence and epigenomic features to predict gene expression (PCC 0.82–0.88), while DeepEPI predicts epigenomic maps from DNA sequence to support model transfer across varieties. Validations in five wheat cultivars confirm robustness and accuracy. DeepWheat also identifies regulatory variants with strong expression effects, enabling targeted cis-regulatory elements editing and offering a powerful tool for crop functional genomics and breeding.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"23 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145182750","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":"Benchmarking multi-slice integration and downstream applications in spatial transcriptomics data analysis","authors":"Kejing Dong, Yicheng Gao, Qi Zou, Yan Cui, Chuangyi Han, Senlin Lin, Zhikang Wang, Chen Tang, Xiaojie Cheng, Fangliangzi Meng, Xiaohan Chen, Shuguang Wang, Xuan Jin, Jingya Yang, Chen Zhang, Guohui Chuai, Zhiyuan Yuan, Qi Liu","doi":"10.1186/s13059-025-03796-z","DOIUrl":"https://doi.org/10.1186/s13059-025-03796-z","url":null,"abstract":"Spatial transcriptomics preserves spatial context of tissues while capturing gene expression. As the technology advances, researchers are increasingly generating data from multiple tissue sections, creating a growing demand for multi-slice integration methods. These methods aim to generate spatially aware embeddings that jointly capture spatial and transcriptomic information, preserving biological signals while mitigating technical artifacts such as batch effects. However, the reliability of these methods varies, and the growing diversity of technologies makes integration even more challenging. This underscores the need for a comprehensive benchmark to evaluate their performance, which is still lacking. To systematically evaluate the performance of multi-slice integration methods, we propose a comprehensive benchmarking framework covering four key tasks that form an upstream-to-downstream pipeline: multi-slice integration, spatial clustering, spatial alignment, slice representation. For each task, we perform detailed analyses of the methods and provide actionable recommendations. Our results reveal substantial data-dependent variation in performance across tasks. We further investigate the relationships between upstream and downstream tasks, showing that downstream performance often depends on upstream quality. Our study provides a comprehensive benchmark of 12 multi-slice integration methods across four key tasks using 19 diverse datasets. Our results reveal that method performance is highly dependent on application context, dataset size, and technology. We also identified strong interdependencies between upstream and downstream tasks, highlighting the importance of robust early-stage analysis.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"29 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145182833","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 : 2025-09-27DOI: 10.1186/s13059-025-03800-6
Lina Worpenberg, Cédric Gobet, Felix Naef
{"title":"Codon-specific ribosome stalling reshapes translational dynamics during branched-chain amino acid starvation","authors":"Lina Worpenberg, Cédric Gobet, Felix Naef","doi":"10.1186/s13059-025-03800-6","DOIUrl":"https://doi.org/10.1186/s13059-025-03800-6","url":null,"abstract":"Cells regulate protein synthesis in response to fluctuating nutrient availability through mechanisms that affect both translation initiation and elongation. Branched-chain amino acids, leucine, isoleucine, and valine, are essential nutrients. However, how their depletion affects translation remains largely unclear. Here, we investigate the immediate effects of single, double, and triple branched-chain amino acid deprivation on translational dynamics in NIH3T3 cells using RNA-seq and ribosome profiling. All starvation conditions increased ribosome dwell times, with pronounced stalling at all valine codons during valine and triple starvation, whereas leucine and isoleucine starvation produced milder, codon-specific effects. Notably, stalling under isoleucine deprivation largely decreased under triple starvation. Positional enrichment of valine codons near the 5′ end and downstream isoleucine codons potentially contributes to these patterns, suggesting a possible elongation bottleneck that influences translational responses under branched-chain amino acid starvation. The presence of multiple valine stalling sites was associated with decreased protein levels. Finally, codon-specific dwell time changes correlated strongly with patterns of tRNA isoacceptor charging. Together, these findings suggest that differential ribosome stalling under branched-chain amino acid starvation reflects a balance between amino acid supply, tRNA charging dynamics, codon position, and stress-response signaling.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"16 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181138","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 : 2025-09-27DOI: 10.1186/s13059-025-03775-4
Samuel K. Sheppard, Nicolas Arning, David W. Eyre, Daniel J. Wilson
{"title":"Machine learning and statistical inference in microbial population genomics","authors":"Samuel K. Sheppard, Nicolas Arning, David W. Eyre, Daniel J. Wilson","doi":"10.1186/s13059-025-03775-4","DOIUrl":"https://doi.org/10.1186/s13059-025-03775-4","url":null,"abstract":"The availability of large genome datasets has changed the microbiology research landscape. Analyzing such data requires computationally demanding analyses, and new approaches have come from different data analysis philosophies. Machine learning and statistical inference have overlapping knowledge discovery aims and approaches. However, machine learning focuses on optimizing prediction, whereas statistical inference focuses on understanding the processes relating variables. In this review, we outline the different aspirations, precepts, and resulting methodologies, with examples from microbial genomics. Emphasizing complementarity, we argue that the combination and synthesis of machine learning and statistics has potential for pathogen research in the big data era.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"1 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181140","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 : 2025-09-27DOI: 10.1186/s13059-025-03790-5
Siran Li, Joan Alexander, Jude Kendall, Peter Andrews, Elizabeth Rose, Hope Orjuela, Sarah Park, Craig Podszus, Liam Shanley, Nissim Ranade, Patrick Morris, Danielle Stauder, Daniel Bradford, Zachary Laster, Michael Ronemus, Arvind Rishi, Marina Frimer, Rong Ma, David L. Donoho, Gary L. Goldberg, Michael Wigler, Dan Levy
{"title":"Hybrid BAG-seq: DNA and RNA from the same single nucleus reveals interactions between genomic and transcriptomic landscapes in human tumor samples","authors":"Siran Li, Joan Alexander, Jude Kendall, Peter Andrews, Elizabeth Rose, Hope Orjuela, Sarah Park, Craig Podszus, Liam Shanley, Nissim Ranade, Patrick Morris, Danielle Stauder, Daniel Bradford, Zachary Laster, Michael Ronemus, Arvind Rishi, Marina Frimer, Rong Ma, David L. Donoho, Gary L. Goldberg, Michael Wigler, Dan Levy","doi":"10.1186/s13059-025-03790-5","DOIUrl":"https://doi.org/10.1186/s13059-025-03790-5","url":null,"abstract":"We introduce hybrid BAG-seq: a high-throughput, multi-omic method that simultaneously captures DNA and RNA from single nuclei. We apply this protocol to 65,499 single nuclei from samples of five uterine cancer patients and validate the clustering using RNA-only and DNA-only protocols from the same tissues. Multiple tumor genome or expression clusters are often present within a patient, with different tumor clones projecting into distinct or shared expression states, demonstrating nearly all possible genome-transcriptome correlations. We also identify mutant stroma with significant X chromosome loss in various cell types and patient-specific stromal subtypes exhibiting aberrant expression patterns.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"15 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181132","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 : 2025-09-26DOI: 10.1186/s13059-025-03792-3
Congyang Yi, Qian Liu, Congle Zhu, Chang Liu, Chen Zhou, Wanna He, Chunhui Wang, Jing Yuan, Yang Liu, Fangpu Han
{"title":"High-resolution genome assembly reveals retrotransposon-mediated centromere dynamics in rye","authors":"Congyang Yi, Qian Liu, Congle Zhu, Chang Liu, Chen Zhou, Wanna He, Chunhui Wang, Jing Yuan, Yang Liu, Fangpu Han","doi":"10.1186/s13059-025-03792-3","DOIUrl":"https://doi.org/10.1186/s13059-025-03792-3","url":null,"abstract":"The genome of rye, Secale cereale, is distinguished by large repetitive regions including subtelomeric heterochromatin and retrotransposon-dominant centromeres, which contrast with the satellite-repeat-based centromeres in most characterized plant genome assemblies. This study aims to decode the architecture and evolution of these elusive regions through high-resolution genome assembly, with a focus on centromere dynamics and chromatin regulation. Using PacBio HiFi and Nanopore sequencing, we generate a chromosome-scale assembly encompassing three complete centromeres and resolving subtelomeric heterochromatin. We identify terminal tandem repeat arrays as key determinants in establishing specialized chromatin environments linked to retrotransposon deposition. Notably, rye centromeres exhibit an unconventional epigenetic signature depleted of conventional activation and repression marks but displaying unique DNA hypomethylation patterns. This retrotransposon-enriched landscape promotes both the integration of young LTR retrotransposons and the recruitment of CENH3. Cross-species CENH3 ChIP-seq analyses reveal that Cereba retrotransposons are associated with enhanced CENH3 loading in cultivated and wild rye lineages, particularly through their conserved protease and integrase domains, suggesting a potential positive feedback loop for centromere evolution. Our findings establish retrotransposons as autonomous organizers of centromere chromatin and identity in rye, challenging the paradigm of satellite-dependent centromere specification. The dual role of retrotransposons in maintaining CENH3 recruitment while facilitating genomic innovation provides a mechanistic basis for centromere plasticity. This work advances functional genomics of Triticeae crops and opens new avenues for centromere engineering to manipulate meiotic stability and chromosome transmission in crop breeding.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"21 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145141385","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}