Biology subjects

Ma, J.

Publications and source records attributed to Ma, J..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

MIMYR: Generative modeling of missing tissue in spatial transcriptomics

Spatial transcriptomics enables the study of how gene expression is organized across tissues, revealing how cells interact within their native microenvironments in health and disease. However, tissue damage during sectioning and the allocation of intermediate slices to other assays often result in regions or entire planes missing from the data, limiting downstream analysis. Here, we introduce MO_SCPLOWIMYRC_SCPLOW, a generative framework for reconstructing realistic spatial transcriptomics data in unmeasured tissue regions. MO_SCPLOWIMYRC_SCPLOW addresses this challenge through three coupled components: predicting cell locations via guided diffusion, assigning cell types through supervised classification, and generating gene expression profiles with a transformer conditioned on spatial and cellular context. MO_SCPLOWIMYRC_SCPLOW accurately reconstructs held-out regions in mouse brain data and generalizes across experimental conditions, including variations in gene panels and slicing orientations. After finetuning on limited Alzheimers disease data, MO_SCPLOWIMYRC_SCPLOW captures disease-associated transcriptional changes in unmeasured brain regions. By enabling high-fidelity spatial imputation from limited training data, MO_SCPLOWIMYRC_SCPLOW extends the utility of spatial transcriptomics, allowing researchers to recover unmeasured tissue states and deepen investigations into tissue spatial organization and dynamics.

bioinformatics↗

bioRxiv2025

TissueNarrator: Generative Modeling of Spatial Transcriptomics with Large Language Models

The intricate spatial organization and molecular communication among cells are fundamental to multicellular systems. Spatial transcriptomics (ST) enables gene expression profiling while preserving spatial context, providing rich data for studying cellular interactions and tissue dynamics. However, most existing computational approaches focus on embedding-based tasks and provide limited generative capacity for simulating cell behavior in situ. Moreover, accurately interpreting spatial interactions requires extensive biological knowledge, which current models do not incorporate. Here, we introduce TO_SCPLOWISSUEC_SCPLOWNO_SCPLOWARRATORC_SCPLOW, a framework that reformulates spatial omics analysis as a language modeling problem. By representing tissue sections as spatial sentences - rank-based gene lists augmented with spatial coordinates and metadata - TO_SCPLOWISSUEC_SCPLOWNO_SCPLOWARRATORC_SCPLOW leverages pretrained large language models (LLMs) to learn spatially conditioned gene expression patterns. The model generates realistic, context-aware cellular profiles, predicts intercellular interactions, and performs in silico perturbation analyses. Across multiple ST technologies (MERFISH, Perturb-FISH, and CosMx SMI), TO_SCPLOWISSUEC_SCPLOWNO_SCPLOWARRATORC_SCPLOW achieves superior quantitative performance and recovers biologically meaning-ful ligand-receptor and signaling pathways. Furthermore, a conversational inference mode enables natural-language querying of tissue organization. By integrating pretrained biological knowledge with spatial context, TO_SCPLOWISSUEC_SCPLOWNO_SCPLOWARRATORC_SCPLOW establishes a new, scalable generative paradigm for modeling, simulating, and reasoning about tissue systems.

bioinformatics↗

bioRxiv2025

Patient induced pluripotent stem cells identify specificities of a reticular pseudodrusen phenotype in age-related macular degeneration

BackgroundAge-related macular degeneration (AMD) is a leading cause of vision loss. Reticular pseudodrusen (RPD), deposits on the apical side of the retinal pigment epithelium (RPE), signify a distinctive and critical AMD phenotype. Yet, their molecular basis and relationship to the conventional drusen seen in AMD remain unclear. ResultsWe generated induced pluripotent stem cell-derived RPE cells from a clinically phenotyped cohort comprising only individuals with conventional drusen (AMD/RPD-) or drusen coexisting with RPD (AMD/RPD+). From these cells, we generated single-cell transcriptomics, proteomics, and functional data to identify differences between the two cohorts. We show that AMD/RPD+ RPE cells exhibit enrichment in extracellular matrix (ECM) remodelling, cytoskeletal, and hypoxia-responsive programs, whereas AMD/RPD- RPE cells display a relatively greater representation of mitochondrial and protein homeostasis pathways. Both subtypes engaged pathways classically linked to ageing, including ECM remodelling and mitochondrial function, but differed in the direction and extent of these changes. Expression and protein quantitative trait loci (QTLs) highlight shared genetic influences on mitochondrial and iron-handling pathways, while disease-interacting eQTLs and transcriptome-wide association study identify regulatory signals that are distinctive of the RPD subtype within AMD, including through regulation of ECM. Functionally, all iPSC-derived RPE formed drusen-like deposits in vitro: AMD/RPD-lines generated more basal deposits, whereas AMD/RPD+ cells exhibited greater structural instability under bisretinoid-induced stress. ConclusionsThese findings indicate that AMD with and without RPD represent mechanistically distinct entities and provide novel insight into the molecular mechanisms underlying disease heterogeneity in AMD.

genetics↗

bioRxiv2025

OPUS-ET: Resolving Compositional and Conformational Heterogeneities of Biomolecules in Cryo-Electron Tomography

Structural heterogeneity in biomolecules, arising from both compositional and conformational variability, limits resolution and interpretability of cryo-electron tomography (cryo-ET). Here, we present OPUS-ET, a deep learning framework that resolves multiscale heterogeneity throughout the cryo-ET workflow. OPUS-ET combines a composition decoder that captures compositional differences with a conformation decoder that models large-scale motions, thereby providing a hierarchical representation of structural heterogeneity. Starting from noisy template-matching candidates with templates of varying similarity or quality, OPUS-ET efficiently enriches target particle populations and delivers sub-nanometer in situ reconstructions in a single round. It leads to improved resolutions by up to 4.5 [A] over expert annotations or existing deep-learning approaches in four benchmark systems, and reveals continuous conformational landscapes capturing F-F flexible coupling in mitochondrial ATP synthase and tRNA-translocation intermediates in eukaryotic and bacterial ribosomes. Together, these results establish OPUS-ET as a powerful computational tool for linking particle purification, high-resolution reconstruction, and analysis of structural heterogeneity in cryo-ET, with demonstrated robustness to template quality, initial pose noise, and clustering parameters.

molecular biology↗

bioRxiv2025

The Human-In-the-Loop Drug Design Framework with Equivariant Rectified Flow

Advancements in AI-based drug design often face obstacles due to incomplete datasets, hindering progress to clinical trials. Human experts bring invaluable expertise and nuanced contextual understanding to drug design. There are two main difficulties in integrating human knowledge into the drug development process. First, human annotations are costly, and traditional machine learning algorithms require a large number of samples to be effective. Second, human experts are unable to accurately describe their expertise using natural language, nor can they precisely specify what kind of molecule is needed before seeing the generated molecules. To address these problems, we propose a new platform, called HIL-DD, for experts to infuse their experience by selecting molecules generated by AI that meet their criteria, or discarding those that do not. The core generative technology utilizes an Equivariant Rectified Flow Model (ERFM), which offers faster generation speeds than conventional diffusion models, enabling efficient human-AI collaboration. More importantly, we provide a user-friendly interface to ensure smooth and effective collaboration between human experts and AI systems. Rigorous experiments demonstrate that our system can produce 3D molecules that align with expert expectations in minimal interactive sessions. These generated molecules maintain drug-like qualities comparable to those created by current state-of-the-art models.

bioinformatics↗

bioRxiv2025

A Syngeneic Immunocompetent Mouse Model of Gallbladder Cancer Reveals Tumorigenesis and Therapeutic Response

PurposeGallbladder cancer (GBC) is a rare but highly lethal malignancy with one of the poorest prognoses among cancers of the digestive system cancers. However, current experimental models of GBC face critical limitations, particularly their dependence on immunodeficient hosts, which precludes the investigation of the tumor microenvironment. We aimed to establish a novel syngeneic immunocompetent mouse model that recapitulates human GBC and enables the investigation of tumor-immune interactions. Experimental DesignWe engineered a murine cell line (mGBC1-ZH) from normal mouse gallbladder organoids expressing Kras and Trp53 (encoding mouse p53) mutations. Tumorigenic potential of mGBC1-ZH was evaluated by subcutaneous and orthotopic implantation. RNA-Seq and WES was used to demonstrate its characterization and similarity with human GBC. Immunohistochemistry, CCK8, and transwell assays wereused to investigate the role of CXCL5 in GBC. Therapeutic responses to standard first-line chemotherapeutic agents was evaluated in the syngeneic GBC model. ResultsThis model supports both subcutaneous and orthotopic tumor growth in immunocompetent C57BL/6J hosts while preserving hallmark features of human GBC, including biliary epithelial differentiation (CK7+/CK19+), aggressive histopathology, and an immunosuppressive "cold" tumor microenvironment. Genomic characterization revealed recurrent chromosomal instability and copy number alterations mirroring human GBC. Comprehensive transcriptomic profiling revealed profound gene expression changes during the model development, and resembled transcriptional features between mGBC1-ZH and human GBC cell lines and samples. CXCL5 was found to be upregulated in human GBC, and promote proliferation, metastasis, and neutrophils infiltration of GBC in the syngeneic mouse model. Functional validation of the syngeneic GBC model demonstrated therapeutic responsiveness to frontline chemotherapeutics gemcitabine and cisplatin with significant in vivo tumor regression. ConclusionsIn summary, we establised a novel syngeneic GBC mouse model, overcoming the limitations of traditional models by enabling studies in immunocompetent hosts. This model provides valuable insights into the molecular evolution from normal gallbladder cells to transformed cancer cells and establishes a robust platform for both mechanistic studies and therapeutic development.

cancer biology↗

bioRxiv2025

Hepatocyte FGFR2 Mediates the Antifibrotic Effects of FGF10 in Advanced Liver Fibrosis.

Fibroblast growth factor 10 (FGF10) supports epithelial repair, but its role in liver fibrogenesis remains uncertain. Here we found that hepatic FGF10 and its receptor FGFR2 decline with progression to advanced fibrosis in patient biopsies and in carbon tetrachloride (CCl4)- and diet-induced mouse models. Restoring hepatic FGF10 with recombinant human FGF10 or adeno-associated virus mediated liver-targeted expression attenuated and partially reversed established advanced bridging fibrosis, reduced inflammation, and decreased hepatocyte apoptosis, and these benefits required hepatocyte FGFR2 because hepatocyte-specific Fgfr2 deletion abolished protection. In primary hepatocytes, FGF10 activated FGFR2-FRS2, increased inhibitory GSK3{beta}(Ser9) phosphorylation, and suppressed NF-{kappa}B activation, reducing TGF-{beta}1 and other cytokines and thereby limiting paracrine hepatic stellate cells activation. The molecular and histologic benefits extended to metabolically primed steatohepatitis, supporting translatability beyond toxicant injury. Mechanistic signaling readouts confirm FGFR2 engagement, while the main text centers on the hepatocyte FGF10-FGFR2 axis as an intrinsic brake on fibrogenesis. Together, these data identify a hepatocyte-centric FGF10-FGFR2 axis as a negative regulator and potential regressor of fibrogenesis, highlighting it as a tractable therapeutic target in advanced liver fibrosis.

pharmacology and toxicology↗

bioRxiv2025

Modular mRNA lipid nanoparticle platform rescues diverse genetic male infertility

Genetic male infertility arises from diverse mutations that disrupt spermatogenesis, yet therapeutic strategies capable of restoring germ-cell function remain limited. Messenger RNA (mRNA) therapeutics offer a programmable and non-integrating approach, but their functional compatibility in structured and immune-privileged tissues remains unclear. Here we identify a temporal mismatch between mRNA delivery kinetics and the progression of spermatogenesis as a key barrier to functional rescue. We show that delivery efficiency does not predict outcome: formulations with high peak expression but short duration fail to support spermiogenesis, whereas sustained expression aligned with developmental timing enables recovery. Guided by this principle, we establish a testis-targeted mRNA delivery platform that restores spermatogenesis across multiple genetic models and generates functional sperm capable of supporting embryo development and multigenerational inheritance. The approach is modular, extends to human seminiferous tubules ex vivo, and is supported by comprehensive safety analyses. Together, these findings define a design constraint for RNA therapeutics in structured tissues: functional rescue requires temporal alignment between delivery kinetics and the therapeutic window defined by tissue-specific biological programs.

bioengineering↗

bioRxiv2025

HEIMDALL: A Modular Framework for Tokenization in Single-Cell Foundation Models

Foundation models for single-cell RNA-sequencing (scRNA-seq) data are emerging as powerful tools for single-cell analysis, yet their performance depends critically on how cells are tokenized into model inputs. Single-cell data lack a canonical tokenization scheme, and many design choices in current single-cell foundation models (scFMs) remain heuristic, entangled, and difficult to evaluate. Here, we introduce HO_SCPLOWEIMDALLC_SCPLOW, a unified framework for dissecting and redesigning tokenizers in scFMs. By decomposing existing tokenization strategies into individual design choices, HO_SCPLOWEIMDALLC_SCPLOW enables attribution of the components that underlie robust generalization, allowing more principled design of improved tokenizers. Combining HO_SCPLOWEIMDALLC_SCPLOW with a minimal transformer backbone, we find that tokenizer design is instrumental for generalization in challenging distribution-shift settings such as cross-tissue, cross-species, and cross-gene-panel cell type classification, as well as reverse perturbation prediction. We show that, while tokenizer choice has little effect in scenarios with matched train and test data, it becomes imperative under distribution shift. Rather than identifying a single globally optimal tokenizer, HO_SCPLOWEIMDALLC_SCPLOW reveals that robust transfer depends on a small number of tokenization design axes - especially gene identity, expression encoding, and ordering - that expose different biological priors to the model. In this sense, universal transferability in scFMs still depends on a non-universal tokenizer interface. Together, these findings establish tokenization as a critical design axis in scFMs and provide design principles and reusable infrastructure for more robust scFMs.

bioinformatics↗

bioRxiv2025

SpecLig: Energy-Guided Hierarchical Model for Target-Specific 3D Ligand Design

Structure-based generative models often optimize single-target affinity with ignorance of specificity, resulting in the generation of high-affinity candidates that exhibit promiscuous binding across unrelated targets. This decoupling of affinity and specificity not only compromises therapeutic efficacy but also elevates off-target risks that constrain translational potential. Therefore, we introduce SpecLig, a unified structure-based framework that jointly generates small molecules and peptides with improved target affinity and specificity. SpecLig represents a complex as a block-based graph, combining a hierarchical SE(3)-equivariant variational autoencoder with an energy-guided geometric latent-diffusion model. Chemical priors derived from block-block contact statistics are explicitly incorporated, biasing generation towards pocket-complementary fragment combinations. We benchmark SpecLig on peptide and small-molecule tasks using standard public datasets and propose precision/breadth testing paradigms to quantify specificity. Across multiple evaluations, ligand candidates generated by SpecLig usually bind to the target pocket with high specificity and affinity while maintaining competitive advantages in other attributes. Ablations indicate that both hierarchical representation and energy guidance contribute to success. Finally, we present multiple real applications that demonstrate how SpecLig improves ligands in natural complexes to mitigate potential off-target risks. SpecLig, therefore, provides a practical route to prioritize higher-specificity designs for downstream experimental validation. The codes are available at: https://github.com/CQ-zhang-2016/SpecLig.

bioinformatics↗

bioRxiv2025

Structural basis of HSV-1 DNA replication origin-binding protein UL9

The herpesvirus DNA replication machinery comprises a battery of viral enzymes that orchestrate viral genome synthesis. In herpes simplex virus type 1 (HSV-1), the machinery consists of seven essential components, including the origin-binding protein UL9, the single-stranded DNA (ssDNA)-binding protein ICP8, the heterodimeric DNA polymerase complex UL30-UL42, and the heterotrimeric helicase-primase complex UL5-UL8-UL52. UL9, a superfamily 2 (SF2) helicase, functions as a dimer that specifically recognizes replication origins and unwinds duplex DNA to initiate replication. Furthermore, UL9 recruits the replication machinery through interactions with viral components and engages cellular proteins that regulate its function. However, the molecular mechanisms underlying UL9s multifunctionality remain incompletely understood due to the lack of structural information. Here, we present cryo-electron microscopy structures of UL9 in both apo and DNA-bound states. Together with biochemical and enzymatic assays, we elucidate the molecular basis of UL9 dimerization, origin recognition and allosteric regulation by ICP8.

microbiology↗

bioRxiv2025

Adeno-Associated Virus-Induced Neurotoxicity is Prevented by CpG Depletion

Adeno-associated viruses (AAVs) are the vector of choice for gene delivery to the nervous system. While AAVs have a strong safety profile, recent studies show that AAV causes dendritic loss and synaptic weakening in mouse somatosensory cortex, impacts that are prevented by systemic administration of blockers of Toll-like receptor 9 (TLR9), an innate immunoreceptor that detects unmethylated cytosine-guanine (CpG) motifs. However, TLR9 blockers are immunosuppressive and costly. To realize AAVs full potential, it is critical to identify strategies to protect neurons without compromising immunity. Here we find that partially depleting CpG motifs from the AAV genome prevents AAV-induced dendritic loss and synaptic weakening. CpG depletion of transgene and intronic regions via codon-optimized synonymous mutations was protective and did not impair transgene expression in vivo. To facilitate the production and use of lower-CpG AAVs, we created a web-facing application, CpG-Assist Tool (CpG-AT), which allows researchers to quantify the CpG content of any sequence, explore the CpG content of commonly used AAV components, and generate CpG-depleted coding and non-coding sequences. This study identifies CpG depletion as a practical strategy to prevent AAV-induced neural circuit disruption, and provides tools to facilitate CpG reduction to enhance the safety and efficacy of AAV-mediated gene delivery.

neuroscience↗

bioRxiv2025

Fixing Hybrid Rice: >99% Efficient Apomixis with Near-Normal Seed Set

Apomixis, a form of clonal seed reproduction, offers a transformative approach to agriculture by enabling the stable fixation of hybrid vigor and elite heterozygosity across generations. However, the practical implementation of synthetic apomixis has been hindered by highly variable clonal efficiency or significant yield penalties. In this study, through integrated transcriptomic analyses, we identified a sperm-specific transcription factor in rice that likely functions as a key initiator of embryogenesis. Ectopic expression of this factor in egg cells effectively induces parthenogenesis and produces haploid progeny. When combined with clonal gametogenesis, this system achieved nearly complete synthetic apomixis, with clonal seed production rates exceeding 99% across all derived hybrid rice lines. Moreover, we generated apomictic hybrid lines that not only consistently produced over 99% clonal seeds but also exhibited seed yields comparable to conventional F1 hybrids. These findings establish a scalable and agriculturally viable platform for synthetic apomixis, achieving stable fixation of heterosis through clonal seeds and paving the way for the commercial deployment of self-perpetuating hybrid crops.

plant biology↗

bioRxiv2025

A Population-scale Single-cell Spatial Transcriptomic Atlas of the Human Cortex

The genetic and spatial determinants of cell type diversity in human cerebral cortices remain poorly defined. Here, we present a population-level single-cell spatial transcriptomic atlas of human cortices from 71 donors across the lifespan. We identified 906 layer-specific genes showing conserved and divergent laminar expression patterns between humans and other species. Spatial analysis revealed neuronal vulnerability and glial activation during aging, together with a decline in the proportion of superficial SST neurons and their interactions with other cells. Disease-associated genes exhibited high cell-type and layer-specific expression, implicating the pathogenic role of spatially specific gene expression. Spatial cis-eQTL analysis identified regulatory variants linked to genes related to diseases like Tourette syndrome. Cross-species comparison demonstrated glial expansion in the human cortex, accompanied by enhanced neuron-glia communication via the neuregulin signaling. Together, we provide a comprehensive single-cell atlas of the human cortex that is essential for understanding aging, evolution, and disease pathogenesis.

neuroscience↗

bioRxiv2025

Adipocyte Leptin Signaling Regulates Glycemia and Cardiovascular Function via Enhancing Brown Adipose Tissue Thermogenesis in Obese Male Mice.

While leptin control of metabolism is primarily viewed as centrally mediated, leptin has also been shown to directly regulate adipocyte function. However, the impact of the peripheral effects of leptin on systemic metabolism, especially in the context of obesity, remains unclear. To address this question, we selectively restored adipocyte leptin receptor (LEPR) expression in obese male and female LEPR conditional KO mice. Adipocyte LEPR restoration did not affect body weight but selectively increased brown adipose tissue (BAT) mass in male mice. This was associated with increased energy expenditure, smaller BAT adipocytes, lower triglycerides content, and increased markers of browning and lipolysis exclusively in males. Additionally, adipocyte LEPR restoration enhanced the expression of markers of endothelial cell and angiogenesis in male BAT, supporting increased local vascularization. Improved BAT function in males was also associated with lower HbA1c, better insulin sensitivity, reduced systolic blood pressure, decreased arterial stiffness and improved endothelial function. Lastly, adipocyte LEPR restoration lowered circulating pro-inflammatory cytokines and reduced tissue inflammation in the aorta and the heart, again in males only. These findings reveal a critical role for adipocyte leptin signaling in regulating BAT function and emphasize its importance in maintaining glycemic and cardiovascular health in males with obesity. Article HighlightsLeptin is known to enhance BAT activity through sympathetic stimulation. However, in vitro studies suggest leptin could also act directly on adipocytes to promote lipolysis. Whether these peripheral effects of leptin are relevant to systemic metabolic control, in obesity, remain ill-defined. We addressed this question by selectively restoring leptin receptor (LEPR) in adipocytes of obese LEPR conditional KO mice. LEPR restoration selectively enhanced BAT activity in male mice, which led to improved glycemic control and cardiovascular function. These findings revealed a crucial role for BAT leptin signaling in regulating energy expenditure, glycemic and cardiovascular health, primarily in males. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/681380v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@ed0b30org.highwire.dtl.DTLVardef@79ba56org.highwire.dtl.DTLVardef@1b86d93org.highwire.dtl.DTLVardef@1220a46_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2025

Triplet Quenching by Active Site Cysteine Residues Improves Photostability in Fatty Acid Photodecarboxylase

Enzyme photobiocatalysis uses light to drive high-energy transformations but is limited by the rarity of photoenzymes. Fatty acid photodecarboxylase (FAP), a recently discovered photoenzyme, enables fatty acid conversion to alkanes/alkenes via excitation of an FAD cofactor, though its poor photostability and photoinactivation has hindered industrial applications. Here, we combine protein engineering approaches with biocatalytic and biophysical techniques, as well as computational chemistry, to demonstrate that additional active site cysteine residues can suppress oxygen-mediated inactivation processes that are driven by the FAD triplet-excited state. We identify a number of positions close to the FAD for cysteine residues that lead to a significant enhancement in activity as a result of an increase in the number of catalytic turnovers and improved photostability. The additional cysteine residues quench the triplet excited state of the FAD cofactor via a proposed proton-coupled electron transfer mechanism, resulting in lower levels of harmful reactive oxygen species. Our study highlights promising routes to mitigate non-productive, photoinactivation pathways in FAP and informs the rational design of new flavin-based photoenzymes.

biochemistry↗

bioRxiv2025

Interaction of Carbamoyl-Phosphate Synthase 1 with Agmatinase in the Liver of Torpid Bats

Mammalian torpor imposes unique metabolic constraints, yet the mechanisms of nitrogen metabolism during this state remain unclear. In this study, we show that the urea cycle is selectively regulated rather than broadly suppressed in torpid bats. A significantly increased abundance of carbamoyl-phosphate synthase 1 (CPS1) maintained its functional capacity during torpor and arousal in Myotis ricketti. Proteomic analyses and confocal microscopy identified a specific association and co-localization between CPS1 and agmatinase (AGMAT), an ATP-independent enzyme involved in nitrogen metabolism. Co-localization of CPS1 and AGMAT was also observed in torpid Rhinolophus ferrumequinum, a phylogenetically distant species. Fluorescence resonance energy transfer (FRET) further supported an indirect CPS1-AGMAT interaction. Most urea cycle enzymes exhibited stable or only moderately reduced expression during bat torpor, and metabolic profiling demonstrated sustained nitrogen flux. Together, these findings reveal a conserved adaptive mechanism that maintains urea cycle function, potentially enhancing osmotic stability and energy efficiency during prolonged fasting and water scarcity.

zoology↗

bioRxiv2025

A protocol for high-throughput microplate-based CUT&Tag

Cleavage Under Targets & Tagmentation (CUT&Tag) is a versatile method for measuring genomic occupancy of chromatin-associated proteins with high sensitivity and specificity. CUT&Tag has low sequencing requirements and is therefore suitable for highly multiplexed experiments, but methods to process samples at throughput without specialized equipment are lacking. Here we present a method for simultaneous parallel processing of 96 CUT&Tag samples in a standard microplate. Plate-CUT&Tag can be carried out in a similar time frame to benchtop CUT&Tag and yields data of comparable quality. We present data from cell culture and patient leukemia samples processed with Plate-CUT&Tag to illustrate its utility in large-scale preclinical and translational studies.

genomics↗