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Multimodal analysis of CD38 in T-cell Acute Lymphoblastic Leukemia Identifies Combinatorial Therapeutic Strategies.

Outcomes for pediatric patients with refractory or relapsed T-cell acute lymphoblastic leukemia (T-ALL) are poor, underscoring the need for improved therapeutic strategies. CD38, a type II transmembrane glycoprotein, is a promising target in T-ALL, with clinical trials evaluating CD38-targeting immunotherapies in frontline and relapsed settings. However, the biological role of CD38 in T-ALL has not been systematically defined. We interrogated CD38 biology through multimodal profiling of pediatric T-ALL samples. Bulk RNA sequencing of 1,335 primary tumors revealed that CD38 expression varies across genomic and immunophenotypic subtypes in T-ALL. Flow cytometry of 150 primary samples and CITE-sequencing of 40 cases demonstrated broad surface expression of CD38. A transcription factor CRISPR-screen identified RUNX1, RUNX3, and TP53 as candidate positive regulators of CD38. Metabolomic profiling of cell lines further revealed disruption of the polyamine pathway following CD38 perturbation. Supporting this finding, co-targeting CD38 with difluoromethylornithine (DFMO), a polyamine metabolism disruptor, improved survival in preclinical models. Across transcriptomic datasets, including primary tumors, cell lines, and patient-derived xenograft models, IL32 expression consistently decreased following CD38 loss or negativity, supporting an association between CD38 and inflammatory signaling pathways. Additionally, CD38 and LCK expression were positively correlated across majority of genomic subtypes, implicating SRC kinase signaling. Consistent with this, daratumumab in cell lines increased LCK phosphorylation, and combination therapy with dasatinib improved survival compared to monotherapy. Collectively, these findings define previously unrecognized interactions between CD38 and targetable pathways and genes in T-ALL and identify rational combinatorial strategies to enhance CD38-directed therapies and reduce relapse risk.

Journal Article↗

Identification of genes selectively regulated by IFNs in endothelial cells.

IFNs are highly pleiotropic cytokines also endowed with marked antiangiogenic activity. In this study, the mRNA expression profiles of endothelial cells (EC) exposed in vitro to IFN-alpha, IFN-beta, or IFN-gamma were determined. We found that in HUVEC as well as in other EC types 175 genes were up-regulated (>2-fold increase) by IFNs, including genes involved in the host response to RNA viruses, inflammation, and apoptosis. Interestingly, 41 genes showed a >5-fold higher induction by IFN-alpha in EC compared with human fibroblasts; among them, the gene encoding the angiostatic chemokine CXCL11 was selectively induced by IFN-alpha in EC along with other genes associated with angiogenesis regulation, including CXCL10, TRAIL, and guanylate-binding protein 1. These transcriptional changes were confirmed and extended by quantitative PCR analysis and ELISA; whereas IFN-alpha and IFN-beta exerted virtually identical effects on transcriptome modulation, a differential gene regulation by type I and type II IFN emerged, especially as far as quantitative aspects were concerned. In vivo, IFN-alpha-producing tumors overexpressed murine CXCL10 and CXCL11, guanylate-binding protein 1, and TRAIL, with evidence of CXCL11 production by tumor-associated EC. Overall, these findings improve our understanding of the antiangiogenic effects of IFNs by showing that these cytokines trigger an antiangiogenic transcriptional program in EC. Moreover, we suggest that quantitative differences in the magnitude of the transcriptional activation of IFN-responsive genes could form the basis for cell-specific transcriptional signatures.

Animals↗

Virus-mediated fate of antimicrobial resistance genes in livestock manure anaerobic digestion.

Antimicrobial resistance (AMR) poses a critical global health challenge, with livestock manure acting as a significant environmental reservoir for antimicrobial resistance genes (ARGs). Anaerobic digestion (AD) is a pivotal process for mitigating ARG dissemination at the livestock-environment-human interface. This study aims to elucidate the global dynamics of ARGs in AD systems, focusing on virus-host interactions and arms race, to identify actionable strategies for AMR control. We analyzed 205 metagenomic (4.5 Tb) and 36 meta-transcriptomic (640 Gb) datasets, including 15 newly generated datasets, revealing that pig manure AD harbors the highest ARG abundance (0.668 ARGs/16S rRNA), while AD systems generally exhibit limited transcriptional activation of ARGs. We constructed a viral dataset for livestock manure AD (GVD_LMAD), comprising 59,316 DNA and 727 RNA viral operational taxonomic units (vOTUs). Virus-host interactions established by CRISPR-Cas spacer, tRNA and homology matches revealed 889 lytic infections of antimicrobial-resistant bacteria (ARB) compared to only 18 ARG transduction events. Further analysis showed that the relative abundance of vOTUs assigned to the reduction role (4.11% ± 3.19%) was substantially higher than that of reproduction (0.72% ± 0.64%) and transduction (0.19% ± 0.30%), demonstrating that, among viral processes, lysis outweighs transduction in contributing to ARG abundance reduction in AD. Furthermore, an antiviral defense system (ADS) catalogue (GADSC_LMAD), derived from 2760 high-quality metagenome-assembled genomes (MAGs) containing 39,307 ADS, with ADS prevalence in ARB (7.8 ± 6.0 per MAG), indicating an intensified virus-host arms race in AD that may shield ARB from phage lysis. The resulting CRISPR-Cas immune network with expressed spacers targets foreign ARG-carrying sequences (primarily plasmids and ICEs), suggesting a mechanism that restricts horizontal gene transfer (HGT) via conjugation and transformation, despite shielding ARB from phage lysis. Collectively, these findings highlight that viral communities significantly contribute to ARG reduction through phage lysis relative to transduction, while the ADS-mediated arms race, despite protecting ARB, constructs a biological firewall that potentially limits HGT of ARGs. This study provides novel insights into virus-host dynamics as a key mechanism for controlling ARG dissemination in AD systems.

Animals↗

Transcriptome profiling of lung schistosomula,in vitro cultured schistosomula and adult Schistosoma japonicum.

The schistosomulum is the main target of vaccine-induced protective immunity; however, most studies have utilized schistosomula produced by mechanical transformation of infective larvae followed by in vitro culture rather than larvae isolated directly from the lungs of infected mammals. Using transmission electron microscopy, we demonstrated that there was little difference in the ultrastructure of Schistosoma japonicum schistosomula obtained by the two methods. However, significant differences in gene expression profiles were apparent when we used an oligonucleotide microarray to compare the gene expression profiles of schistosomula obtained in vivo from lung tissue with those maintained in vitro, and with adult worms of S. japonicum. It is likely that host environmental factors, which cannot be reliably reproduced in vitro, do influence the growth, development and overall biology of schistosomes. Thus caution is urged when using in vitro-cultured schistosomes and mechanically transformed/cultured schistosomula in molecular, biochemical and immunological studies.

Animals↗

The potato tuber transcriptome: analysis of 6077 expressed sequence tags.

This is the first report of the biosynthetic potential of a tuber storage organ investigated by expressed sequence tag sequencing. A cDNA library was generated from the mature tuber of field grown potato (Solanum tuberosum var. Kuras). Partial sequences obtained from 6077 clones were assembled into 828 clusters and 1533 singletons. The average read length was 592 bp, and 2254 clones were full length. 5717 clones showed homology to genes from other organisms. Genes involved in protein synthesis, protein destination and cell defense predominated in tuber compared to stolon, shoot and leaf organs. 1063 clones were unique to tuber. Transcripts of starch metabolizing enzymes showed similar relative levels in tuber and stolon.

Expressed Sequence Tags↗

A method for automated detection of gene expression required for the establishment of a digital transcriptome-wide gene expression atlas.

Acquiring information about the expression of a gene in different cell populations and tissues can provide key insight into the function of the gene. A high-throughput in situ hybridization (ISH) method was recently developed for rapid and reproducible acquisition of gene expression patterns in serial tissue sections at cellular resolution. Characterizing and analysing expression patterns on thousands of sections requires efficient methods for locating cells and estimating the level of expression in each cell. Such cellular quantification is an essential step in both annotating and quantitatively comparing high-throughput ISH results. Here we describe a novel automated and efficient methodology for performing this quantification on postnatal mouse brain.

Animals↗

Gene expression analysis of ischemic and nonischemic cardiomyopathy: shared and distinct genes in the development of heart failure.

Cardiomyopathy can be initiated by many factors, but the pathways from unique inciting mechanisms to the common end point of ventricular dilation and reduced cardiac output are unclear. We previously described a microarray-based prediction algorithm differentiating nonischemic (NICM) from ischemic cardiomyopathy (ICM) using nearest shrunken centroids. Accordingly, we tested the hypothesis that NICM and ICM would have both shared and distinct differentially expressed genes relative to normal hearts and compared gene expression of 21 NICM and 10 ICM samples with that of 6 nonfailing (NF) hearts using Affymetrix U133A GeneChips and significance analysis of microarrays. Compared with NF, 257 genes were differentially expressed in NICM and 72 genes in ICM. Only 41 genes were shared between the two comparisons, mainly involved in cell growth and signal transduction. Those uniquely expressed in NICM were frequently involved in metabolism, and those in ICM more often had catalytic activity. Novel genes included angiotensin-converting enzyme-2 (ACE2), which was upregulated in NICM but not ICM, suggesting that ACE2 may offer differential therapeutic efficacy in NICM and ICM. In addition, a tumor necrosis factor receptor was downregulated in both NICM and ICM, demonstrating the different signaling pathways involved in heart failure pathophysiology. These results offer novel insight into unique disease-specific gene expression that exists between end-stage cardiomyopathy of different etiologies. This analysis demonstrates that transcriptome analysis offers insight into pathogenesis-based therapies in heart failure management and complements studies using expression-based profiling to diagnose heart failure of different etiologies.

Angiotensin-Converting Enzyme 2↗

Testing the neutral theory of molecular evolution using genomic data: a comparison of the human and bovine transcriptome.

Despite growing evidence of rapid evolution in protein coding genes, the contribution of positive selection to intra- and interspecific differences in protein coding regions of the genome is unclear. We attempted to see if genes coding for secreted proteins and genes with narrow expression, specifically those preferentially expressed in the mammary gland, have diverged at a faster rate between domestic cattle (Bos taurus) and humans (Homo sapiens) than other genes and whether positive selection is responsible. Using a large data set, we identified groups of genes based on secretion and expression patterns and compared them for the rate of nonsynonymous (dN) and synonymous (dS) substitutions per site and the number of radical (Dr) and conservative (Dc) amino acid substitutions. We found evidence of rapid evolution in genes with narrow expression, especially for those expressed in the liver and mammary gland and for genes coding for secreted proteins. We compared common human polymorphism data with human-cattle divergence and found that genes with high evolutionary rates in human-cattle divergence also had a large number of common human polymorphisms. This argues against positive selection causing rapid divergence in these groups of genes. In most cases dN/dS ratios were lower in human-cattle divergence than in common human polymorphism presumably due to differences in the effectiveness of purifying selection between long-term divergence and short-term polymorphism.

Animals↗

Integration of gene expression data into genome-scale metabolic models.

A framework for integration of transcriptome data into stoichiometric metabolic models to obtain improved flux predictions is presented. The key idea is to exploit the regulatory information in the expression data to give additional constraints on the metabolic fluxes in the model. Measurements of gene expression from chemostat and batch cultures of Saccharomyces cerevisiae were combined with a recently developed genome-scale model, and the computed metabolic flux distributions were compared to experimental values from carbon labeling experiments and metabolic network analysis. The integration of expression data resulted in improved predictions of metabolic behavior in batch cultures, enabling quantitative predictions of exchange fluxes as well as qualitative estimations of changes in intracellular fluxes. A critical discussion of correlation between gene expression and metabolic fluxes is given.

Databases, Genetic↗

DGKH-mediated phosphatidic acid oncometabolism as a driver of self-renewal and therapy resistance in HCC.

BACKGROUND AND AIMS: HCC is characterized by metabolic pathway aberrations, which enable cancer cells to meet their energy demands and accelerate malignant progression. Identifying novel metabolic players governing therapy resistance and self-renewal in HCC is crucial, as these properties are likely responsible for tumor recurrence. APPROACH AND RESULTS: Clinical traits and RNA-seq of patients with HCC in The Cancer Genome Atlas were used for weighted gene coexpression network analysis, where 1 module was significantly correlated with advanced pathological stage and stem cell population maintenance. Further analysis of this module by integrating data obtained from HCC patient nonresponders to tyrosine kinase inhibitors identified 361 commonly deregulated genes. Intriguingly, these genes are significantly enriched in the intracellular signal transduction pathway, with diacylglycerol kinase eta (DGKH) ranked as the most enriched gene in poorly differentiated HCC tumors. Clinically, DGKH was elevated in tumor tissues compared to nontumor tissues. Patients with higher DGKH expression exhibited a more undifferentiated state and were less responsive to tyrosine kinase inhibitors. Functional assays using DGKH-manipulated HCC cell lines demonstrated that DGKH augmented aggressive features, including cancer stemness, therapy resistance, and metastasis. Upstream of DGKH , we discovered that the E1A-associated protein p300 (EP300) binds to DGKH's promoter region, thereby increasing its transcriptomic expression. Mechanistically, DGKH promotes mTOR signaling by producing phosphatidic acid. In an immunocompetent mouse model, cotreatment with sorafenib and liver-directed AAV8-mediated Dgkh depletion significantly reduced tumor burden, self-renewal, phosphatidic acid production, and mTOR signaling. CONCLUSIONS: Our research demonstrated that DGKH is a crucial oncometabolic regulator of cancer stemness and therapy resistance, suggesting that inhibiting DGKH may lead to more effective HCC treatment.

Humans↗

Impact of Tumor Genomic Profile on Adjuvant Chemotherapy Efficacy in Resected Pancreatic Adenocarcinoma: Results From the PRODIGE-24/CCTG PA6 Study.

PURPOSE: Modified fluorouracil, leucovorin, irinotecan, and oxaliplatin (mFOLFIRINOX/mFFX) is the standard adjuvant chemotherapy for resected pancreatic ductal adenocarcinoma (PDAC), offering survival benefits over gemcitabine (GEM). However, the contribution of molecular biomarkers to treatment selection remains unclear. Here, we characterize the molecular landscape of tumors from the PRODIGE-24/CCTG PA6 trial and assess the clinical impact of genomic alterations and molecular subtypes. PATIENTS AND METHODS: Tumor DNA sequencing was successfully performed in 317/350 tumors (168 mFFX; 149 GEM), complemented by transcriptomic subtyping using the PurIST classifier. Mutational status of four key PDAC driver genes and 24 homologous recombination repair (HRR)-associated genes was analyzed, alongside single-base substitution (SBS) mutational signatures. Primary and secondary end points were disease-free survival (DFS) and cancer-specific survival (CSS), respectively. RESULTS: In the mFFX group, the PurIST subtype was prognostic, with classical tumors showing superior DFS compared with basal-like tumors (stratified hazard ratio [sHR], 0.48 [95% CI, 0.31 to 0.77]). Among KRAS-mutated patients, mFFX significantly improved DFS compared with GEM (sHR, 0.60 [95% CI, 0.45 to 0.79]; P < .001), while no benefit was observed in KRAS wild-type tumors (interaction test, Pint. = 0.010). HRR and BRCA status were not predictive (Pint. = .568 and Pint. = .785, respectively). The benefit of mFFX was consistent across SBS-positive and SBS-negative subgroups. CONCLUSION: Overall, these results do not support a change in current adjuvant treatment strategies. mFFX remains the standard adjuvant regimen in PDAC, and the observed lack of benefit in KRAS wild-type tumors should be considered hypothesis-generating and warrants further investigation.

Humans↗

Early oligodendrocyte dysfunction signature in Alzheimer's disease: Insights from DNA methylomics and transcriptomics.

Much research into the aetiology of Alzheimer's disease (AD) has focused on neuronal cell types, while studies on the contribution of glial cells, particularly oligodendrocytes (OLGs), are only starting to emerge. Altered brain DNA methylation, an epigenetic modification that provides the interplay between genetics and environmental cues to tightly regulate gene expression, is well documented in AD. Yet, cell-type-specific investigations remain limited. Here, we examine the role of DNA methylation and OLGs in AD, and how such changes may impact gene expression. We performed weighted-gene correlation network analysis (WGCNA) on multiple brain omics AD datasets across species: human DNA methylation data from 4 brain regions, human brain single-nuclei RNA sequencing data and mouse brain RNA sequencing data. We compared AD-associated network modules enriched for OLG genes across AD brain regions, as well as with other neurodegenerative disease DNA methylation datasets. We identified a DNA methylation signature associated with AD, enriched for OLGs, and preserved across brain regions representing early and late AD pathology stages. Genes within this signature showed altered expression in AD OLGs, confirming cell-type specificity and relevance to AD. This OLG signature was also preserved in transgenic mice with early A&#x3b2; pathology and in other neurodegenerative diseases without A&#x3b2; pathology. We reveal a consistent pattern of OLG dysfunction spanning early to late stages of AD, across DNA methylation and gene expression. Our findings highlight OLG-associated DNA methylation changes as important in AD pathogenesis, and possibly in other neurodegenerative diseases, opening new avenues for therapeutic development.

Alzheimer Disease↗

Single-cell transcriptomics on FFPE placenta: A novel method for comprehensive exploration of an entire placental section.

INTRODUCTION: The placenta's complex cellular diversity challenges traditional transcriptomic analyses. Single-cell RNA sequencing (scRNA-seq) offers breakthrough capabilities by enabling transcriptome profiling at the single-cell level. However, traditional scRNA-seq relies on fresh or frozen samples, which present practical storage and quality challenges. Applying scRNA-seq to Formalin-Fixed, Paraffin-Embedded (FFPE) placentas could harness archived samples for clinical insights. METHODS: We used 10x Genomics Flex technology to analyze 8 non-pathological placentas ranging from 21&#xa0;+&#xa0;6 weeks of gestation (WoG) to 39&#xa0;+&#xa0;4 WoG. RESULTS: Our approach identifies diverse cell populations and allows us to discern maternal from fetal cells. Despite sample size limitations, the method yields comparable data to prior fresh/frozen tissue studies and we complete these data by integrating new molecular markers. The potential to correlate single-cell results with histopathology enables us to conduct an in-depth analysis across entire placental sections by concurrently addressing both fetal and maternal cells. We could thus confirm molecular markers like KRT5/6 using immunohistochemistry by revisiting the slide. DISCUSSION: This innovation could aid in understanding focal anomalies observed on standard histology slides, thereby enhancing traditional histopathological assessments. Given its practicality, integrating our method into routine practice is both feasible and promising.

Differentially expressed genes (DEG)↗

Central role of a bacterial two-component gene regulatory system of previously unknown function in pathogen persistence in human saliva.

The molecular genetic mechanisms used by bacteria to persist in humans are poorly understood. Group A Streptococcus (GAS) causes the majority of bacterial pharyngitis cases in humans and is prone to persistently inhabit the upper respiratory tract. To gain information about how GAS survives in and infects the oropharynx, we analyzed the transcriptome of a serotype M1 strain grown in saliva. The dynamic pattern of changes in transcripts of genes [spy0874/0875, herein named sptR and sptS (sptR/S), for saliva persistence] encoding a two-component gene regulatory system of unknown function suggested that SptR/S contributed to persistence of GAS in saliva. Consistent with this idea, an isogenic nonpolar mutant strain (DeltasptR) was dramatically less able to survive in saliva compared with the parental strain. Iterative expression microarray analysis of bacteria grown in saliva revealed that transcripts of several known and putative GAS virulence factor genes were decreased significantly in the DeltasptR mutant strain. Compared with the parental strain, the isogenic mutant strain also had altered transcripts of multiple genes encoding proteins involved in complex carbohydrate acquisition and utilization pathways. Western immunoblot analysis and real-time PCR analysis of GAS in throat swabs taken from humans with pharyngitis confirmed the findings. We conclude that SptR/S optimizes persistence of GAS in human saliva, apparently by strategically influencing metabolic pathways and virulence factor production. The discovery of a genetic program that significantly increased persistence of a major human pathogen in saliva enhances understanding of how bacteria survive in the host and suggests new therapeutic strategies.

Bacteria↗

Genome topology analysis and transcriptomics of human osteoclasts reveals enhancer-promoter interactions at loci for bone traits and diseases.

Genome-wide association studies (GWAS) relevant to osteoporosis have identified hundreds of loci; however, understanding how these variants influence the phenotype is complicated because most reside in non-coding DNA sequence that serves as transcriptional enhancers and repressors. To advance knowledge on these regulatory elements in osteoclasts (OCs), we performed Micro-C analysis, which informs on the genome topology of these cells and integrated the results with transcriptome and GWAS data to further define loci linked to BMD. Using blood cells isolated from 4 healthy participants aged 31-61&#xa0;yr, we cultured OC in vitro and generated a Micro-C chromatin conformation capture dataset. We characterized chromatin loops (CLs) in OC from among more than 69 million chromatin interactions identified in the genome. Of the CL identified in OC, >16&#x2009;000 were unique compared to precursor cells. When sentinel single nucleotide polymorphisms from osteoporosis and bone-related GWAS and those in linkage disequilibrium at r 2&#x2009;>&#x2009;0.6 were mapped to CL for OC, 12&#x2009;588 of these variants were observed within chromatin contact regions. Notable in differential gene ontology enrichment analyses of the topology data for OC and precursors were pathways regulating pluripotency of stem cells, Wnt signaling, nucleotide-binding oligomerization domain (NOD)-like receptor signaling and chemokine signaling. These data, in combination with other 3D genome architecture and epigenetic data (eg, histone modifications and chromatin accessibility), will be useful in modeling to predict genome-wide, which enhancers regulate which genes in OC. This data will therefore also be informative for resolving GWAS hits. In conclusion, we have generated a high-resolution genome topology dataset for human OC and have used this to identify CLs relevant to studies of the genetics of osteoporosis. This data will serve as a powerful resource to inform future functional studies of OC biology.

BMD↗

PATTY corrects open chromatin bias for improved bulk and single-cell CUT&Tag profiling.

Precise profiling of epigenomes is essential for better understanding chromatin biology and gene regulation. Cleavage Under Targets & Tagmentation (CUT&Tag) is an efficient epigenomic profiling technique that can be performed on a low number of cells and at the single-cell level. With its growing adoption, CUT&Tag datasets spanning diverse biological systems are rapidly accumulating in the field. CUT&Tag assays use the hyperactive transposase Tn5 for DNA tagmentation. Tn5's preference toward accessible chromatin alters CUT&Tag sequence read distributions in the genome and introduces open chromatin bias that can confound downstream analysis, an issue more substantial in sparse single-cell data. We show that open chromatin bias extensively exists in published CUT&Tag datasets, including those generated with recently optimized high-salt protocols. To address this challenge, we present PATTY (Propensity Analyzer for Tn5 Transposase Yielded bias), a comprehensive computational method that corrects open chromatin bias in CUT&Tag data by leveraging accompanying ATAC-seq. By integrating transcriptomic and epigenomic data using machine learning and integrative modeling, we demonstrate that PATTY enables accurate and robust detection of occupancy sites for both active and repressive histone modifications, including H3K27ac, H3K27me3, and H3K9me3, with experimental validation. We further develop a single-cell CUT&Tag analysis framework built on PATTY and show improved cell clustering when using bias-corrected single-cell CUT&Tag data compared to using uncorrected data. Beyond CUT&Tag, PATTY sets a foundation for further development of bias correction methods for improving data analysis for all Tn5-based high-throughput assays.

Journal Article↗

Quantitative proteomics reveals posttranslational control as a regulatory factor in primary hematopoietic stem cells.

The proteome is determined by rates of transcription, translation, and protein turnover. Definition of stem cell populations therefore requires a stem cell proteome signature. However, the limit to the number of primary cells available has restricted extensive proteomic analysis. We present a mass spectrometric method using an isobaric covalent modification of peptides for relative quantification (iTRAQ), which was employed to compare the proteomes of approximately 1 million long-term reconstituting hematopoietic stem cells (Lin(-)Sca(+)Kit(+); LSK(+)) and non-long-term reconstituting progenitor cells (Lin(-)Sca(+)Kit(-); LSK(-)), respectively. Extensive 2-dimensional liquid chromatography (LC) peptide separation prior to mass spectrometry (MS) enabled enhanced proteome coverage with relative quantification of 948 proteins. Of the 145 changes in the proteome, 54% were not seen in the transcriptome. Hypoxia-related changes in proteins controlling metabolism and oxidative protection were observed, indicating that LSK(+) cells are adapted for anaerobic environments. This approach can define proteomic changes in primary samples, thereby characterizing the molecular signature of stem cells and their progeny.

Animals↗

PATTY corrects open-chromatin bias for improved bulk and single-cell CUT&Tag profiling.

Precise profiling of epigenomes is essential for better understanding chromatin biology and gene regulation. Cleavage Under Targets & Tagmentation (CUT&Tag) is an efficient epigenomic profiling technique that can be performed on a low number of cells and at the single-cell level. With its growing adoption, CUT&Tag datasets spanning diverse biological systems are rapidly accumulating in the field. CUT&Tag assays use the hyperactive transposase Tn5 for DNA tagmentation. Tn5's preference toward accessible chromatin alters CUT&Tag sequence read distributions in the genome and introduces open-chromatin bias that can confound downstream analysis, an issue more substantial in sparse single-cell data. We show that open-chromatin bias extensively exists in published CUT&Tag datasets, including those generated with recently optimized high-salt protocols. To address this challenge, we present PATTY (Propensity Analyzer for Tn5 Transposase Yielded bias), a comprehensive computational method that corrects open-chromatin bias in CUT&Tag data by leveraging accompanying ATAC-seq. By integrating transcriptomic and epigenomic data using machine learning and integrative modeling, we demonstrate that PATTY enables accurate and robust detection of occupancy sites for both active and repressive histone modifications, including H3K27ac, H3K27me3, and H3K9me3, with experimental validation. We further develop a single-cell CUT&Tag analysis framework built on PATTY and show improved cell clustering when using bias-corrected single-cell CUT&Tag data compared to using uncorrected data. Beyond CUT&Tag, PATTY sets a foundation for further development of bias correction methods for improving data analysis for all Tn5-based high-throughput assays.

Journal Article↗