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Dixon, J. R.

Publications and source records attributed to Dixon, J. R..

10 recordsLinked to original sources

Oncogenic drivers shape the tumor microenvironment in human gliomas

Gliomas are aggressive and heterogeneous brain tumors with limited treatment options. While oncogenic mutations in gliomas have been well-characterized, their impact on the tumor microenvironment remains poorly understood. To investigate how genomic alterations may influence the glioma microenvironment, we performed an integrative multiomic and spatial transcriptomic analysis of 93 glioma samples (46 IDH-mutant gliomas and 47 IDH-wildtype glioblastoma) from 69 patients representing both primary and recurrent stages. Using whole-genome sequencing, chromatin conformation capture (Hi-C), RNA-seq, and single-cell spatial transcriptomics (Xenium), we defined how major driver mutations influence spatial tumor organization. We found that IDH-mutant gliomas frequently harbored inflammatory microglia expressing CX3CR1 specifically within their astrocyte-like malignant neighborhoods. In contrast, glioblastomas demonstrated relatively higher T-cell infiltration and enrichment of immunosuppressive myeloid cell populations. We further compared glioblastomas harboring EGFR amplifications due to extrachromosomal DNA (ecDNA) amplifications versus linear chromosomal 7 gains. Tumors with EGFR ecDNA displayed increased presence of mesenchymal-like malignant cells, and higher interactions between pericytes and mesenchymal-like malignant cells, likely driven by hypoxia-associated vascular proliferation. Our findings reveal that the mode of oncogene amplification--linear versus ecDNA--shapes distinct tumor architectures and transcriptional dynamics. Taken together, our study highlights the role of oncogenic drivers in shaping the glioma microenvironment, revealing subtype-specific cellular ecosystems that could inform targeted therapeutic strategies.

genomics↗

Human Body Single-Cell Atlas of 3D Genome Organization and DNA Methylation

Higher-order chromatin structure and DNA methylation are critical for gene regulation, but how these vary across the human body remains unclear. We performed multi-omic profiling of 3D genome structure and DNA methylation for 86,689 single nuclei across 16 human tissues, identifying 35 major and 206 cell subtypes. We revealed extensive changes in CG and non-CG methylation across almost all cell types and characterized 3D chromatin structure at an unprecedented cellular resolution. Intriguingly, extensive discrepancies exist between cell types delineated by DNA methylation and genome structure, indicating that the role of distinct epigenomic features in maintaining cell identity may vary by lineage. This study expands our understanding of the diversity of DNA methylation and chromatin structure and offers an extensive reference for exploring gene regulation in human health and disease.

genomics↗

Heterogeneity in chromatin structure drives core regulatory pathways in B-cell Acute Lymphoblastic Leukemia

B-cell acute lymphoblastic leukemia (B-ALL) is the most common pediatric malignancy. Based on gene expression profiling, B-ALL can be classified into distinct transcriptional subtypes with differing disease outcomes. Many of these transcriptional subtypes are defined by mutations in transcription factors and chromatin-modifying enzymes, but how such diverse mutations lead to distinct transcriptional subtypes remains unclear. To illuminate the chromatin regulatory landscape in B-ALL, we analyzed 3D genome organization, open chromatin, and gene expression in 53 primary patient samples. At the level of 3D genome organization, we identified chromatin interactions that vary across transcriptional subtypes. These sites of variable 3D chromatin interactions correlate with local gene expression changes and are enriched for core drivers of B-ALL observed in genome-wide CRISPR knock-out screens. Sites of variable 3D genome interactions are frequently shared across multiple transcriptional subtypes and are enriched for open chromatin sites found in normal B-cell development but repressed in mature B-cells. Within an individual patient sample, the chromatin landscape can resemble progenitor chromatin states at some loci and mature B-cell chromatin at others, suggesting that the chromatin in B-ALL patient tumor cells is in a partially arrested immature state. By analyzing transcriptomic data from large cohorts of B-ALL patients, we identify gene expression programs that are shared across transcriptional subtypes, associated with B-cell developmental stages, and predictive of patient survival. In combination, these results show that the 3D genome organization of B-ALL reflects B-cell developmental stages and helps illustrate how B-cell developmental arrest interacts with transcriptional subtypes to drive B-ALL.

cancer biology↗

A STAG2-PAXIP1/PAGR1 axis suppresses lung tumorigenesis

The cohesin complex is a critical regulator of gene expression. STAG2 is the most frequently mutated cohesin subunit across several cancer types and is a key tumor suppressor in lung cancer. Here, we coupled somatic CRISPR-Cas9 genome editing and tumor barcoding with an autochthonous oncogenic KRAS-driven lung cancer model and show that STAG2 is uniquely tumor suppressive among all core and auxiliary cohesin components. The heterodimeric complex components PAXIP1 and PAGR1 have highly correlated effects with STAG2 in human lung cancer cell lines, are tumor suppressors in vivo, and are epistatic to STAG2 in oncogenic KRAS-driven lung tumorigenesis in vivo. STAG2 inactivation elicits changes in gene expression, chromatin accessibility and 3D genome conformation that impact cancer cell state. Gene expression and chromatin accessibility similarities between STAG2- and PAXIP1-deficient neoplastic cells further relates STAG2-cohesin to PAXIP1/PAGR1. These findings reveal a STAG2-PAXIP1/PAGR1 tumor-suppressive axis and uncover novel PAXIP1-dependent and PAXIP1-independent STAG2-cohesin mediated mechanisms of lung tumor suppression. SUMMARYSTAG2 is a frequently mutated cohesin subunit across several cancers and one of the most important functional suppressors of lung adenocarcinoma. Our findings underscore important roles of STAG2 in suppressing lung tumorigenesis and highlight a STAG2-PAXIP1/PAGR1 tumor-suppressive program that may transcend cancer type.

cancer biology↗

Single-cell DNA Methylome and 3D Multi-omic Atlas of the Adult Mouse Brain

Cytosine DNA methylation is essential in brain development and has been implicated in various neurological disorders. A comprehensive understanding of DNA methylation diversity across the entire brain in the context of the brains 3D spatial organization is essential for building a complete molecular atlas of brain cell types and understanding their gene regulatory landscapes. To this end, we employed optimized single-nucleus methylome (snmC-seq3) and multi-omic (snm3C-seq1) sequencing technologies to generate 301,626 methylomes and 176,003 chromatin conformation/methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell type taxonomy that contains 4,673 cell groups and 261 cross-modality-annotated subclasses. We identified millions of differentially methylated regions (DMRs) across the genome, representing potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide multiplexed error-robust fluorescence in situ hybridization (MERFISH2) data validated the association of this spatial epigenetic diversity with transcription and allowed the mapping of the DNA methylation and topology information into anatomical structures more precisely than our dissections. Furthermore, multi-scale chromatin conformation diversities occur in important neuronal genes, highly associated with DNA methylation and transcription changes. Brain-wide cell type comparison allowed us to build a regulatory model for each gene, linking transcription factors, DMRs, chromatin contacts, and downstream genes to establish regulatory networks. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a companion whole-brain SMART-seq3 dataset. Our study establishes the first brain-wide, single-cell resolution DNA methylome and 3D multi-omic atlas, providing an unparalleled resource for comprehending the mouse brains cellular-spatial and regulatory genome diversity.

genomics↗

DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution

Mammalian brain cells are remarkably diverse in gene expression, anatomy, and function, yet the regulatory DNA landscape underlying this extensive heterogeneity is poorly understood. We carried out a comprehensive assessment of the epigenomes of mouse brain cell types by applying single nucleus DNA methylation sequencing to profile 110,294 nuclei from 45 regions of the mouse cortex, hippocampus, striatum, pallidum, and olfactory areas. We identified 161 cell clusters with distinct spatial locations and projection targets. We constructed taxonomies of these epigenetic types, annotated with signature genes, regulatory elements, and transcription factors. These features indicate the potential regulatory landscape supporting the assignment of putative cell types, and reveal repetitive usage of regulators in excitatory and inhibitory cells for determining subtypes. The DNA methylation landscape of excitatory neurons in the cortex and hippocampus varied continuously along spatial gradients. Using this deep dataset, an artificial neural network model was constructed that precisely predicts single neuron cell-type identity and brain area spatial location. Integration of high-resolution DNA methylomes with single-nucleus chromatin accessibility data allowed prediction of high-confidence enhancer-gene interactions for all identified cell types, which were subsequently validated by cell-type-specific chromatin conformation capture experiments. By combining multi-omic datasets (DNA methylation, chromatin contacts, and open chromatin) from single nuclei and annotating the regulatory genome of hundreds of cell types in the mouse brain, our DNA methylation atlas establishes the epigenetic basis for neuronal diversity and spatial organization throughout the mouse brain.

genomics↗

Incorporation of a nucleoside analog maps genome repair sites in post-mitotic human neurons

Neurons are the longest-living cells in our bodies, becoming post-mitotic in early development upon terminal differentiation. Their lack of DNA replication makes them reliant on DNA repair mechanisms to maintain genome fidelity. These repair mechanisms decline with age, potentially giving rise to genomic dysfunction that may influence cognitive decline and neurodegenerative diseases. Despite this challenge, our knowledge of how genome instability emerges and what mechanisms neurons and other long-lived cells may have evolved to protect their genome integrity over the human life span is limited. Using a targeted sequencing approach, we demonstrate that neurons consolidate much of their DNA repair efforts into well-defined hotspots that protect genes that are essential for their identity and function. Our findings provide a basis to understand genome integrity as it relates to aging and disease in the nervous system. One Sentence SummaryRecurrent DNA repair hotspots in neurons are linked to genes essential for identity and function.

neuroscience↗

Single nucleus multi-omics links human cortical cell regulatory genome diversity to disease risk variants

Single-cell technologies enable measure of unique cellular signatures, but are typically limited to a single modality. Computational approaches allow integration of diverse single-cell datasets, but their efficacy is difficult to validate in the absence of authentic multi-omic measurements. To comprehensively assess the molecular phenotypes of single cells in tissues, we devised single-nucleus methylCytosine, Chromatin accessibility and Transcriptome sequencing (snmC2T-seq) and applied it to post-mortem human frontal cortex tissue. We developed a computational framework to validate fine-grained cell types using multi-modal information and assessed the effectiveness of computational integration methods. Correlation analysis in individual cells revealed distinct relations between methylation and gene expression. Our integrative approach enabled joint analyses of the methylome, transcriptome, chromatin accessibility and conformation for 63 human cortical cell types. We reconstructed regulatory lineages for cortical cell populations and found specific enrichment of genetic risk for neuropsychiatric traits, enabling prediction of cell types with causal roles in disease.

genomics↗

Single-cell multi-omic profiling of chromatin conformation and DNA methylome

Recent advances in the development of single cell epigenomic assays have facilitated the analysis of gene regulatory landscapes in complex biological systems. Methods for detection of single-cell epigenomic variation such as DNA methylation sequencing and ATAC-seq hold tremendous promise for delineating distinct cell types and identifying their critical cis-regulatory sequences. Emerging evidence has shown that in addition to cis-regulatory sequences, dynamic regulation of 3D chromatin conformation is a critical mechanism for the modulation of gene expression during development and disease. It remains unclear whether single-cell Chromatin Conformation Capture (3C) or Hi-C profiles are suitable for cell type identification and allow the reconstruction of cell-type specific chromatin conformation maps. To address these challenges, we have developed a multi-omic method single-nucleus methyl-3C sequencing (sn-m3C-seq) to profile chromatin conformation and DNA methylation from the same cell. We have shown that bulk m3C-seq and sn-m3C-seq accurately capture chromatin organization information and robustly separate mouse cell types. We have developed a fluorescent-activated nuclei sorting strategy based on DNA content that eliminates nuclei multiplets caused by crosslinking. The sn-m3C-seq method allows high-resolution cell-type classification using two orthogonal types of epigenomic information and the reconstruction of cell-type specific chromatin conformation maps.

genomics↗

Process-specific somatic mutation distributions vary with three-dimensional genome structure

Somatic mutations arise during the life history of a cell. Mutations occurring in cancer driver genes may ultimately lead to the development of clinically detectable disease. Nascent cancer lineages continue to acquire somatic mutations throughout the neoplastic process and during cancer evolution (Martincorena and Campbell, 2015). Extrinsic and endogenous mutagenic factors contribute to the accumulation of these somatic mutations (Zhang and Pellman, 2015). Understanding the underlying factors generating somatic mutations is crucial for developing potential preventive, therapeutic and clinical decisions. Earlier studies have revealed that DNA replication timing (Stamatoyannopoulos et al., 2009) and chromatin modifications (Schuster-Bockler and Lehner, 2012) are associated with variations in mutational density. What is unclear from these early studies, however, is whether all extrinsic and exogenous factors that drive somatic mutational processes share a similar relationship with chromatin state and structure. In order to understand the interplay between spatial genome organization and specific individual mutational processes, we report here a study of 3000 tumor-normal pair whole genome datasets from more than 40 different human cancer types. Our analyses revealed that different mutational processes lead to distinct somatic mutation distributions between chromatin folding domains. APOBEC- or MSI-related mutations are enriched in transcriptionally-active domains while mutations occurring due to tobacco-smoke, ultraviolet (UV) light exposure or a signature of unknown aetiology (signature 17) enrich predominantly in transcriptionally-inactive domains. Active mutational processes dictate the mutation distributions in cancer genomes, and we show that mutational distributions shift during cancer evolution upon mutational processes switch. Moreover, a dramatic instance of extreme chromatin structure in humans, that of the unique folding pattern of the inactive X-chromosome leads to distinct somatic mutation distribution on X chromosome in females compared to males in various cancer types. Overall, the interplay between three-dimensional genome organization and active mutational processes has a substantial influence on the large-scale mutation rate variations observed in human cancer.

genomics↗