Realizing the promise of precision medicine will require the highest standards of accuracy in genome sequencing and analysis. Here we describe challenges and opportunities for the field through the lens of genome data qu...Realizing the promise of precision medicine will require the highest standards of accuracy in genome sequencing and analysis. Here we describe challenges and opportunities for the field through the lens of genome data quality. We present recommendations in the context of specific areas of application for genomic sequencing in which isolated standards have arisen: germline sequencing, tumour sequencing, cell-free DNA testing, and sequencing for quality control in genetic therapy. Despite these distinct clinical contexts, technical challenges are often similar; for example, accurately detecting low-frequency genetic variants in tumour sequencing or gene-edited cells. We call for increased synchronization among these communities to establish new medical genome standards that promote confidence in genomic diagnostics and genetic therapies in a time of rapid technology-driven change. We suggest practical approaches for implementing these genome standards across contexts, and identify key areas that require further development.
Qian L, Zhou Z, Zhou P
… +64 more, Dong Z, Zhang X, Dai Z, Gao Z, Sun S, Roy KR, Wang S, Zamboni N, Boone C, Costanzo M, Li J, Liti G, Yue JX, Ralser M, Williams E, Zampieri M, Jiang H, Wu T, Wang Y, Li F, Schacherer J, Sun R, Li Z, Deng Y, Chen Y, Xie Z, Lou H, Wang X, Xie L, Wen H, Chen L, Lei K, Rosenberger G, Cai X, Wang Y, Xiao Q, Shen H, Liu G, Ma L, Andrews B, Lu H, Piatkevich K, Zhu Y, Bai L, Cai Y, Chen Y, E W, Gao G, He F, Chen L, Li SZ, Ma H, Qiao L, Steinmetz LM, Tang L, Tang T, Zhang X, Yang J, Yang Y, Yu K, Zeng J, Zheng Y, Zhou B, Guo T
To advance the computational simulation of cellular life, we propose a virtual yeast, an artificial intelligence (AI)-driven agent that models eukaryotic cellular behaviours by integrating multimodal biological data, mec...To advance the computational simulation of cellular life, we propose a virtual yeast, an artificial intelligence (AI)-driven agent that models eukaryotic cellular behaviours by integrating multimodal biological data, mechanistic reasoning and active experimentation using Saccharomyces cerevisiae as a genetically tractable and data-rich model system. Cellular complexity is decomposed into eight function-centred modules, spanning genetic, metabolic and structural systems, each realized as a domain-specific AI tool coordinated through a large language model-based orchestration layer. Built on three data pillars, namely, mechanistic knowledge, subcellular architecture and dynamic states, the system integrates representation learning and generative modelling within a closed-loop learning pipeline that autonomously designs and executes experiments. The virtual yeast serves as both a conceptual and an operational platform to optimize biosynthetic pathways, support the generation and prioritization of hypotheses across diverse cellular processes, and accelerate target discovery. By coupling biological realism with autonomous AI reasoning, the virtual yeast establishes a generalizable blueprint for constructing virtual eukaryotic cells and advancing synthetic biology.
Mitochondria regulate cellular processes through direct and indirect interactions with other organelles. A well-studied example has been contact with the endoplasmic reticulum at mitochondrial-associated endoplasmic reti...Mitochondria regulate cellular processes through direct and indirect interactions with other organelles. A well-studied example has been contact with the endoplasmic reticulum at mitochondrial-associated endoplasmic reticulum membranes, which control pathways including redox and calcium homeostasis. Recent studies have also reported direct mitochondria-nuclear membrane contacts in cancer cells and yeast that promote pro-survival signalling. Here we identify direct interactions between mitochondria and nuclear pores. Using two unbiased proteomic screens, GST pulldown and BioID, we found that VDAC1 was the top mitochondrial candidate that interacts with the filamentous nuclear pore protein RANBP2. In vitro RANBP2 CRISPR knockout, RANBP2 truncation or site-directed mutagenesis of RANBP2-VDAC1 interacting amino acids resulted in reduced mitochondria-nucleus proximity and decreased nuclear ATP and phosphocreatine levels. This was accompanied by a decline in the levels of the nuclear phosphoproteome and downregulation of pathways involved in histone modification, cellular differentiation and transcriptional regulation in vitro. Moreover, deletion of the RANBP2 C-terminal domain in vivo in mice resulted in embryonic lethality due to cardiac and neural crest differentiation defects. Collectively, these results describe a mechanism by which mitochondria directly interact with the nuclear pore complex, a phenomenon critical for regulation of nuclear energetics and cellular differentiation. Undoubtedly, additional roles of this interaction remain to be revealed.
Wang J, Li X, Wang Y
… +43 more, Lin J, Chen S, Liu H, Chen X, Chai K, Dong A, Zhao T, Feng C, Wu R, Zhao P, Zheng Y, Xia Z, Zhang S, Liu Y, Qu S, Ye Z, Song Y, Deng Q, Zeng X, Yu G, Kong R, Zhang B, Zhang W, Zhao P, Mao J, Lu X, Jia H, Zhao X, Zhang Q, Zhang S, Cai W, Huo D, Li L, Gong Y, Huang S, Huang Y, Yu Z, Deng Z, Chen B, Zhang Y, Zhang M, Ming R, Zhang X
Sugarcane (Saccharum spp.) is a vital sugar and bioenergy crop with an exceptionally complex polyploid genome (10-12 sets of chromosomes). This complexity resulted from nobilization-a historical breeding process involvin...Sugarcane (Saccharum spp.) is a vital sugar and bioenergy crop with an exceptionally complex polyploid genome (10-12 sets of chromosomes). This complexity resulted from nobilization-a historical breeding process involving interspecific hybridization and repeated backcrossing. However, the extreme ploidy has long impeded efforts to elucidate the genetic basis of its considerable sucrose-storing capacity. Here we present a fully phased genome assembly of the foundational cultivar POJ2878, achieved using a Pore-C-based assembly algorithm. This assembly resolved 118 chromosomes, revealing extensive subgenome recombination and non-homologous chromosomal rearrangements. Using identity-by-descent and allele-specific expression profiling, we identified breeder-favoured haplotypes, including a SUS2 haplotype with enhanced sucrose content. Resequencing of 981 Saccharum accessions traced POJ2878's pervasive contribution to modern cultivars and identified key domestication and improvement sweeps. Genes under selection include CBL1 for cold tolerance, TIP1 for cell size regulation and TB1 for tillering control. A genome-wide association study tailored for polyploid genomes resolved loci associated with parenchyma cell size and sucrose storage capacity, including the functionally validated sucrose transporter Saccharum hybrid SUT2. These findings clarify the genetic architecture underlying sugarcane's biomass productivity and sugar yield, offering a genomic foundation for accelerating improvement in sugarcane and other polyploid crops critical for global food and bioenergy security.
Aygün E, Belyaeva A, Comanici G
… +39 more, Coram M, Cui H, Garrison J, Johnston R, Kast A, McLean CY, Norgaard P, Shamsi Z, Smalling D, Thompson J, Venugopalan S, Williams BP, He C, Martinson S, Plomecka M, Wei L, Zhou Y, Zhu QZ, Abraham M, Brand E, Bulanova A, Cardille JA, Co C, Ellsworth S, Joseph G, Kane M, Krueger R, Kartiwa J, Liebling D, Lueckmann JM, Raccuglia P, Wang XJ, Chou K, Manyika J, Matias Y, Platt JC, Dorfman L, Mourad S, Brenner MP
The cycle of scientific discovery is frequently bottlenecked by the slow, manual creation of software to support computational experiments. To address this, we present Empirical Research Assistance (ERA), an artificial i...The cycle of scientific discovery is frequently bottlenecked by the slow, manual creation of software to support computational experiments. To address this, we present Empirical Research Assistance (ERA), an artificial intelligence (AI) system that creates expert-level scientific software whose goal is to maximize a quality metric. The system uses a large language model (LLM) and tree search to systematically improve the quality metric and intelligently navigate the large space of possible solutions. ERA achieves expert-level results when it explores and integrates complex research ideas from external sources. The effectiveness of tree search is demonstrated across a diverse range of tasks. In bioinformatics, ERA discovered 40 new methods for single-cell data analysis that outperformed the top human-developed methods on a public leaderboard. In epidemiology, ERA generated 14 models that outperformed the Centers for Disease Control and Prevention (CDC) ensemble and all other individual models for forecasting COVID-19 hospitalizations. ERA also produced expert-level software for geospatial analysis, neural activity prediction in zebrafish and numerical solution of integrals, as well as a new rule-based construction for time-series forecasting. By devising and implementing new solutions to diverse tasks, ERA represents a notable step towards accelerating scientific progress.
Deutsch EW, Kok LW, Mudge JM
… +61 more, Valls CF, Jungreis I, Ruiz-Orera J, Sun Z, Kusebauch U, Fierro-Monti I, Abelin JG, Alba MM, Aspden JL, Bandyopadhyay S, Banerjee K, Baranov PV, Bazzini AA, Bourassa F, Bruford EA, Calviello L, Carr SA, Carvunis AR, Chothani S, Clauwaert J, Dean K, Faridi P, Frankish A, Goodale A, Green T, Hubner N, Ingolia NT, Kellis M, Magrane M, Martin MJ, Martinez TF, Menschaert G, Ohler U, Orchard S, Potter A, Rackham OJL, Rees MG, Root DE, Roth JA, Roucou X, Sialana FJ, Slavoff SA, Świrski MI, Tierney JAS, Trifiro FA, Valen E, Vasylieva V, Wacholder A, Wang S, Wang L, Weissman JS, Wu W, Xie Z, Choudhary JS, Bassani-Sternberg M, Vizcaíno JA, Ternette N, Brunet MA, Moritz RL, Prensner JR, van Heesch S
A major scientific drive is to characterize the protein-coding genome, which is a primary basis for studying human health. But the fundamental question remains of what has been missed in previous analyses. Over the past...A major scientific drive is to characterize the protein-coding genome, which is a primary basis for studying human health. But the fundamental question remains of what has been missed in previous analyses. Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for biomedical science. However, a key gap in knowledge has been which ncORFs produce small microproteins or alternative protein molecules that contribute to the human proteome. Here we report the collaborative efforts of the TransCODE Consortium to produce a consensus landscape of protein-level evidence for ncORFs. We show that about 25% of a set of 7,264 ncORFs gives rise to detectable peptides in a large-scale analysis of 95,520 proteomics experiments. We develop an annotation framework for ncORF-encoded microproteins as human proteins and codify the new conceptual model of 'peptideins' as microproteins that have indeterminate potential as functional proteins. To probe the biological implications of peptideins, we create an evolutionary analysis approach, termed ORF relative branch length (ORBL), and determine that evolutionary constraint is common and associates with observation of ncORF-derived peptides. We then characterize a pan-essential cellular phenotype for one peptidein from the OLMALINC long non-coding RNA. Overall, we generate public research tools supported by GENCODE and PeptideAtlas and advance biomedical discovery for understudied components of the human proteome.
Targeted insertion of large DNA fragments has promising applications for genome engineering and gene therapy. Twin prime-editing guide RNAs have enabled relatively large insertions, but the efficiency remains low for ins...Targeted insertion of large DNA fragments has promising applications for genome engineering and gene therapy. Twin prime-editing guide RNAs have enabled relatively large insertions, but the efficiency remains low for insertions greater than 400 base pairs. Here we describe a prime assembly (PA) approach for the insertion of large DNA donor fragments, of which the ends are designed to overlap with the flaps generated by twin prime editing (twinPE). We used PA to insert one or multiple overlapping DNA fragments, with total insertion sizes ranging from 0.1 kb to 11 kb. An inhibitor of non-homologous end joining enhanced both the efficiency and precision of insertions. PA relies on DNA templates that are easily produced, does not require co-delivery of exogenous DNA-dependent DNA polymerases and proceeds in non-cycling cells, suggesting independence from canonical homology-directed repair pathways. Our study demonstrates that PA can initiate Gibson-like assembly in cells to generate gene insertions without double-stranded DNA breaks, recombinases or homology-directed repair.
The emergence of new political and social structures in Western and Central Europe during the transition from Antiquity to the Middle Ages has long been attributed to large-scale migrations. Yet emerging evidence increas...The emergence of new political and social structures in Western and Central Europe during the transition from Antiquity to the Middle Ages has long been attributed to large-scale migrations. Yet emerging evidence increasingly emphasizes the role of small-group mobility in reshaping the Roman world. Here we present 258 ancient genomes from the former Roman frontier of southern Germany, which we analyse alongside 2,500 ancient and 379 modern genomes. Population genetic analyses reveal a major demographic shift coinciding with the late fifth century collapse of Roman state structures, when a founding population of northern European ancestry mixed with genetically diverse Roman provincial groups. Pedigree reconstruction and filia, a method for inferring the ancestry of unsampled relatives, indicate widespread intermarriage and minimal cultural differentiation. Genetic structure persisted through the sixth century, with admixture forming a population resembling modern Central Europeans by the early seventh century. Using Chronograph to refine the chronology of genealogically linked individuals, we estimate a generation time of 28 years, life expectancies of 39.8 years for women and 43.3 years for men, high infant mortality, and a society in which nearly one quarter of children lost at least one parent by age 10, yet most still grew up with grandparents. Pedigrees further reveal a society centred on nuclear families that practiced lifelong monogamy, strict incest avoidance, flexible lineage continuation and no levirate unions, indicating continuity with Late Roman social practices that later shaped the European family.
Telomere-to-telomere phased assemblies are emerging as a benchmark for reference-quality genomes, although they remain technically and financially demanding, particularly at scale. Generating such assemblies for diploid...Telomere-to-telomere phased assemblies are emerging as a benchmark for reference-quality genomes, although they remain technically and financially demanding, particularly at scale. Generating such assemblies for diploid and polyploid genomes typically involves combining high-accuracy long reads, such as PacBio HiFi or the now-deprecated Oxford Nanopore Technologies (ONT) Duplex reads, with ultra-long ONT Simplex reads. Using multiple platforms or methods increases the cost and the required amount of genomic DNA. Here we show that comparable results are possible using error correction of ultra-long Simplex reads and then assembling them using state-of-the-art de novo assembly methods. To achieve this, we developed the deep learning-based HERRO (haplotype-aware error correction) framework, which corrects Simplex reads while carefully preserving differences in related genomic sequences. Taking into account informative positions that differentiate the haplotypes or genomic repeat copies, HERRO achieves an increase of read accuracy of up to 100-fold for diploid human genomes. By combining HERRO with the Verkko assembler, we reconstruct up to 32 chromosomes telomere-to-telomere, including chromosomes X and Y, and consistently achieve NGA50 (normalized genome assembly 50) values of 100 Mb or higher across several human genomes. HERRO supports both R9.4.1 and R10.4.1 Simplex reads and generalizes well to other species. These results show that error-corrected ONT reads can lower sequencing costs and improve the quality of genomic analyses.
Wu L, Mu DS, An J
… +21 more, Wang Y, Fan X, Lu DC, Zhang Y, Xie Y, Michael J, Curtis D, Fan Y, Wang Y, Guo X, Tu Q, Yan Q, Gao Q, He Z, Deng Y, Xue K, Wu L, Ning D, Tao X, Yang Y, Zhou J
Soils are critical reservoirs of antibiotic-resistance genes (ARGs), which are strongly shaped by microbial interactions and environmental conditions and are therefore highly sensitive to disturbance. Although climate wa...Soils are critical reservoirs of antibiotic-resistance genes (ARGs), which are strongly shaped by microbial interactions and environmental conditions and are therefore highly sensitive to disturbance. Although climate warming is recognized as one of the most significant disturbances to microbial communities and their functions, its impacts on soil resistomes remain poorly understood. Here we investigated the effects of decade-long experimental warming on ARGs in grassland soils using integrated experimental and computational approaches. Our results revealed that ARG abundance substantially increased (23.9%) under warming-particularly glycopeptide- and rifamycin-resistance genes. Warming specifically enriched Actinomycetota hosts, including various potential plant pathogens, and enhanced ARG mobility. Large-scale unprecedented isolates-based phenotypic analyses also validated that warming increased bacterial resistance to multiple antibiotics. Further mechanistic analyses revealed that warming increased ARG abundance primarily through co-selection of resistance genes physically linked to adaptive traits (for example, thermal tolerance and nitrogen assimilation) and positive selection for thermal tolerance genes, which could be further amplified via horizontal gene transfer. Together, these findings convincingly demonstrate that climate warming substantially accelerates soil antibiotic resistance at genomic, ecological and evolutionary levels, with broad implications for public health and environmental sustainability in a warming world.
Precise, site-specific insertion of large gene sequences holds great promise for the treatment of diverse genetic disorders. Although prime editing using paired guide RNAs (pegRNAs) can mediate targeted integration, inse...Precise, site-specific insertion of large gene sequences holds great promise for the treatment of diverse genetic disorders. Although prime editing using paired guide RNAs (pegRNAs) can mediate targeted integration, insertion efficiency drops sharply for payloads exceeding 300 base pairs. Here we present a rationally designed quadruple pegRNA strategy (QuadPE) for efficient and programmable insertion of large DNA fragments. Through screening different designs, we identified that combinations of two genome-targeting pegRNAs in a PAM-out or PAM-in orientation, when paired with two donor-targeting pegRNAs in linear or circular form, yield optimal efficiency. Using QuadPE, we achieved stable integration efficiency of DNA fragments ranging from 1.6 to 26 kb, with efficiencies of around 40% at multiple loci with minimal off-target insertion activity. QuadPE substantially outperformed recombinase-mediated (PASSIGE and PASTE) and transposase-mediated (CAST) insertion systems, particularly for larger payloads, showing a 11-fold, 61-fold and 12-fold improvement for a 9.5 kb insertion, respectively. Notably, QuadPE was effective in both dividing and non-dividing primary cells such as human primary T cells and post-mitotic neurons, establishing QuadPE as a powerful and precise platform for large-fragment gene insertion without the need for double-stranded breaks or recombinases.
Indigenous peoples of America represent the last principal expansion of humans across the globe, yet their genetic history remains one of the least explored. Although these populations have inhabited the continent for th...Indigenous peoples of America represent the last principal expansion of humans across the globe, yet their genetic history remains one of the least explored. Although these populations have inhabited the continent for thousands of years, their evolutionary history remains largely unresolved, owing to the limited availability of genomic data. Here we present data on 128 high-coverage Indigenous American genomes and show they harbour extensive and previously uncharacterized genetic diversity, reflecting at least three dispersals into South America, followed by regional differentiation and long-term continuity. We identified widespread natural selection signals in genes associated with immunity, metabolism, reproduction and development, which were shaped by adaptation to diverse environmental conditions. Notably, several genomic regions exhibit a remarkable allele sharing with Australasian populations, probably originating from an ancient admixture event and partly maintained by selection for more than 10,000 years. We also detected distinct contributions from archaic humans with adaptive introgression affecting key biological functions. The limited overlap between the regions of Australasian affinity and archaic ancestry indicates independent evolutionary origins of these signals. These findings challenge simplified models of continental settlements and show a more dynamic and complex evolutionary history for the Indigenous peoples in America.
Anticancer drugs are frequently used off-label for tumours that are genetically similar to the approved indication. However, outcomes are rarely captured systematically, limiting evidence-based decision-making and riskin...Anticancer drugs are frequently used off-label for tumours that are genetically similar to the approved indication. However, outcomes are rarely captured systematically, limiting evidence-based decision-making and risking repeated futile treatment. The Drug Rediscovery Protocol (DRUP; ClinicalTrials.gov ID: NCT02925234 ) prospectively evaluates such off-label use in patients in the Netherlands with advanced solid tumours who lack standard treatment options and harbour actionable genomic alterations. Here we present results of 1,610 patients who began treatment with 37 different off-label drugs between July 2016 and May 2024 in the DRUP trial. Of these patients, 1,363 were response-evaluable, including 533 (39.1%) with rare cancers. The clinical benefit rate (confirmed response or stable disease for at least 16 weeks) was 34.9% (95% confidence interval, 32.2-37.6) and the objective response rate was 15.7% (95% confidence interval, 13.7-17.9). Median progression-free and overall survival were 3.4 months (95% confidence interval, 2.8-3.5) and 8.2 months (95% confidence interval, 7.6-8.8), respectively. Grade 3 or higher treatment-related adverse events occurred in 28.4% of patients. Notably, evidence generated in DRUP was used for reimbursement decisions by the regulatory bodies in the Netherlands. Although activity across all tumour-drug combinations was modest, defined molecular subgroups and exceptional responders (7.0%) achieved meaningful benefit. To maximize patient benefit, we recommend that off-label precision medicines should be used only within frameworks that systematically evaluate efficacy and toxicity, support biomarker refinement and enable stepwise assessment toward potential future label expansion. These frameworks should prioritize high-confidence targets, early intervention, regulatory-aligned end-points and international collaboration.
Metabolomics has matured into a powerful approach for probing metabolism, offering readouts that closely reflect cellular and organismal function in health and disease. Here we highlight two rapidly advancing frontiers:...Metabolomics has matured into a powerful approach for probing metabolism, offering readouts that closely reflect cellular and organismal function in health and disease. Here we highlight two rapidly advancing frontiers: single-cell metabolomics and population-scale metabolomics. Single-cell metabolomics resolves the metabolic states of individual cells, uncovering cell-to-cell heterogeneity and spatial organization within tissues. Population-scale profiling profiles metabolites across large cohorts, enabling the discovery of markers of disease, environmental exposures and genetic variation. Although these approaches operate at different scales, they face shared challenges-including metabolite identification, quantification and multimodal data integration-and offer common advantages, such as the ability to capture non-genetic influences on phenotype and to scale to high throughput. We propose that continued advances in scalability will bring these domains together, enabling the construction of comprehensive metabolic atlases that chart cellular and interindividual variation and provide training data for foundation models of metabolism. By integrating cellular and population-level insights, single-cell and population-scale metabolomics promise to advance our understanding of metabolism across biology, medicine and pharmacology.
Liu BB, Jessa S, Kim SH
… +18 more, Ng YT, Higashino SI, Marinov GK, Chen DC, Parks BE, Li L, Nguyen TC, Wang AT, Wang SK, Tan MH, Tan SY, Kosicki M, Pennacchio LA, Ben-David E, Pasca AM, Kundaje A, Farh KKH, Greenleaf WJ
Transcription factors establish cell identity during development by binding regulatory DNA in a sequence-specific manner, often promoting local chromatin accessibility and regulating gene expression. Mapping accessible c...Transcription factors establish cell identity during development by binding regulatory DNA in a sequence-specific manner, often promoting local chromatin accessibility and regulating gene expression. Mapping accessible chromatin offers critical insights into transcriptional control, but available datasets for human development are restricted to bulk tissue, single organs or single modalities. Here we present the Human Development Multiomic Atlas, a single-cell atlas of chromatin accessibility and gene expression from 817,740 fetal cells across 12 organs, spanning 203 cell types and more than 1 million candidate cis-regulatory elements, many of which exhibit organ-specific in vivo enhancer activity. Deep learning models trained to predict accessibility from local DNA sequence unravel a comprehensive lexicon of motifs that influence accessibility, including composite motifs exhibiting distinct syntactic constraints that are predicted to mediate transcription factor cooperativity. We identify 'hard' syntactic rules requiring precise motif spacing and orientation, 'soft' rules allowing flexible motif arrangements, and ubiquitous motifs inhibiting accessibility. Model-based interpretation of genetic variants reveals that disruption of motifs with positive and negative effects is associated with concordant effects on gene expression. Our work delineates how motif syntax governs cell-type-specific chromatin accessibility and provides a foundational resource for decoding cis-regulatory logic and interpreting genetic variation during human development.
Wang Y, Duan Z, Chen D
… +18 more, Shi D, Ding Y, Wang Z, Li B, Wang Z, Guo M, Yang W, Hou J, Chen W, Guo Y, Wei W, Cao Y, Sun X, Bai W, Lu M, Qi T, Shen X, Yang J
Pangenomes are revolutionizing our ability to resolve genomic regions with complex variations. However, existing human pangenomes, constrained by small sample sizes, provide limited utility for medical and population gen...Pangenomes are revolutionizing our ability to resolve genomic regions with complex variations. However, existing human pangenomes, constrained by small sample sizes, provide limited utility for medical and population genetic applications. Here we generated 1,116 diploid genome assemblies (55 de novo and 1,061 pangenome-informed) with an average size of 2.98 Gb and a mean quality value of 46 as part of the 1000 Chinese Pangenome (1KCP) project. On the basis of these assemblies, we constructed a pangenome comprising 405.3 million base pairs of sequences absent from the current references GRCh38 and CHM13, including 26.2 million base pairs of functional genic and predicted regulatory elements. We catalogued a full spectrum of genetic variation, including 35.4 million small variants, 110,530 structural variants (SVs), 485,575 tandem repeats (TRs) and 0.86 million nested variants embedded in non-reference sequences. This extensive dataset enabled detailed characterization of multiscale genic variations relevant to medical genetics, including gene-altering SVs, TR expansions, gene cluster variations and HLA gene haplotypes. Coupled with the 1KCP gene expression data, we conducted pan-variant expression quantitative trait locus (eQTL) mapping to analyse diverse variant types. We identified 3,256 eQTLs involving complex variants (SVs, TRs and nested variants) and elucidated their regulatory complexity. Finally, we developed a 1KCP pan-variant imputation reference panel, which provides multitype genetic markers to enhance the resolution of future association studies. This resource advances our understanding of complex variants and their functional implications to provide new insights into human health.
Cellular diversity is governed not only by the transcriptome but also by multiple layers of epigenomic regulation, including nucleosome occupancy, chromatin states and genome architecture. Here, to comprehensively unders...Cellular diversity is governed not only by the transcriptome but also by multiple layers of epigenomic regulation, including nucleosome occupancy, chromatin states and genome architecture. Here, to comprehensively understand how these regulatory modalities converge to shape cellular identity, we developed a single-cell four-omics sequencing method that enables parallel profiling of genome conformation, histone modifications, chromatin accessibility and gene expression within the same cell (CHARM). Applying CHARM to mouse embryonic stem cells and cortical tissues, we reconstructed integrated epigenome profiles, uncovering distinct cell-cycle dynamics of chromatin accessibility and histone modification, and spatial clustering of regulatory elements in three-dimensional nuclear space. Leveraging an interpretable machine learning model, we further identified thousands of enhancer-promoter linkages with high accuracy that modulate gene expression in a cell-type- and subtype-specific manner. Together, CHARM enables integrative dissection of the three-dimensional epigenome at single-cell resolution, providing a versatile platform for decoding the regulatory landscape across diverse cells in complex tissues.
ZFTA-RELA is the most recurrent genetic alteration seen in paediatric supratentorial ependymoma (EPN) and is sufficient to initiate tumours in mice. Despite its oncogenic potential, ZFTA-RELA (ZR) is observed nearly excl...ZFTA-RELA is the most recurrent genetic alteration seen in paediatric supratentorial ependymoma (EPN) and is sufficient to initiate tumours in mice. Despite its oncogenic potential, ZFTA-RELA (ZR) is observed nearly exclusively in childhood EPN, with tumours located distinctly in the supratentorial brain of the central nervous system. We proposed that specific chromatin modules accessible during brain development would render distinct cell lineage programs at direct risk of transformation by ZR. To test this hypothesis, we performed combined single-nucleus assay for transposase-accessible chromatin and RNA (snMultiome) sequencing of the developing mouse forebrain compared with ZR-driven mouse and human EPN. We demonstrated that specific developmental lineage programs present in transient progenitor cells and regulated by PLAG/L family transcription factors were at risk of neoplastic transformation. Binding of this chromatin network by ZR or other PLAG/L family motifs targeting fusion oncoproteins led to persistent chromatin accessibility at oncogenic loci and oncogene expression. Cross-species analysis of mouse and human ZR EPN revealed significant cell type heterogeneity indicating incomplete neurogenic and gliogenic differentiation, with a small percentage of cycling progenitor-like or radial glial-like cells that established a putative tumour cell hierarchy. In vivo lineage tracing studies identified neoplastic clones that aggressively dominated tumour growth and established the entire EPN cellular hierarchy. These findings identify developmental epigenomic states that are critical for fusion-oncoprotein-driven transformation and show how these states continue to shape tumour progression.
Bergström A, Furtwängler A, Johnston S
… +65 more, Rosengren E, Breidenstein A, Booth T, McCabe JB, Peto J, Williams M, Kelly M, Tait F, Baumann C, Radzeviciute R, Barrington C, Anastasiadou K, Gilardet A, Glocke I, Sherman M, Brativnyk A, Herbig A, Prüfer K, Pfrengle S, Gretzinger J, Feuerborn TR, Reiter E, Linderholm A, Charlton S, Racimo F, Mikkola L, Anderson-Whymark H, Baird D, Gotfredsen AB, Bocherens H, Bridault A, Brocke R, Drucker DG, Fairbairn AS, Frantz L, Gasparyan B, Giemsch L, Germonpré M, Janssens L, Kandel AW, Kjær K, Lázničková-Galetová M, Loponte D, Magnell O, Martin L, Münzel SC, Mustafaoğlu G, Måge B, Perri A, Pfenninger F, Roblíčková M, Roman-Binois A, Sarıtaş Ö, Schäppi K, Sheridan JA, Sjögren KG, Storå J, Sørensen LV, Tafelmaier Y, Ter-Nedden F, Thalmann O, Larson G, Schuenemann VJ, Krause J, Skoglund P
The earliest morphologically identifiable dogs are from Europe and date to at least 14,000 years ago, although early remains are also found in other regions. The origin of early dogs in Europe, and their relationships to...The earliest morphologically identifiable dogs are from Europe and date to at least 14,000 years ago, although early remains are also found in other regions. The origin of early dogs in Europe, and their relationships to other dogs, has remained elusive in the absence of genome-wide data. Similarly, although dogs were the only domestic animal to predate agriculture, little is known about how the arrival of Neolithic farmers from Southwest Asia affected the dogs living with European Mesolithic hunter-gatherers. Here we analysed 216 canid remains, including 181 from Palaeolithic and Mesolithic Europe. We developed a genome-wide capture approach that enriched endogenous DNA by 10-100-fold and could distinguish dog from wolf ancestry for 141 of 216 remains. The oldest dog data that we recovered are from a 14,200-year-old dog from the Kesslerloch site in Switzerland, and we find that it shares ancestry with later worldwide dogs-inconsistent with the hypothesis that European Upper Palaeolithic dogs derived wholly from a separate domestication process. The Kesslerloch dog already displays more affinity to Mesolithic, Neolithic and present-day European dogs than to Asian dogs, demonstrating that dog genetic diversification had started well before 14,200 years ago. We find a Neolithic influx of Southwest Asian ancestry into Europe, but this seems to have been of smaller magnitude than in humans, suggesting that Mesolithic dogs contributed substantially to Neolithic, and, ultimately, probably also modern, European dogs.
An B, Tang TC, Zhang Q
… +17 more, Wang T, Wang Y, Gan K, Liu K, Zhang DL, Liu Y, Pan YK, Yu M, Shaw WM, Liang Q, Wang Y, Vaiana CA, Lou C, Voigt CA, Lu TK, Church GM, Zhong C
Recent advances in genetic engineering have provided diverse tools for artificially diversifying both prokaryotic and eukaryotic cell populations. However, achieving precise control over the ratios of multiple cell types...Recent advances in genetic engineering have provided diverse tools for artificially diversifying both prokaryotic and eukaryotic cell populations. However, achieving precise control over the ratios of multiple cell types within a population derived from a single founder remains a major challenge. Here we introduce a suite of recombinase-mediated genetic devices designed to accurately control population ratios, enabling the distribution of distinct functionalities across multiple cell types. We systematically evaluated key parameters that influence recombination efficiency and developed data-driven models to reliably predict binary differentiation outcomes. Using these devices, we constructed parallel and series circuit topologies to implement user-defined, multistep cell-fate branching programs. The branching devices facilitated the autonomous differentiation of precision fermentation consortia from a single founder yeast strain, optimizing cell-type ratios for applications such as pigmentation and cellulose degradation. Similar effects were obtained with mammalian cells. We also engineered multicellular aggregates with genetically encoded morphologies by coordinating self-organization through cell adhesion molecules. Our work provides a comprehensive characterization of recombinase-based cell-fate branching mechanisms and introduces an approach for constructing synthetic consortia and multicellular assemblies.