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Aryee, M. J.

Publications and source records attributed to Aryee, M. J..

17 recordsLinked to original sources

Intraductal Papillary Mucinous Neoplasm Cellular Plasticity linked with Repeat Element Dysregulation

BackgroundIntraductal papillary mucinous neoplasms (IPMNs) are preinvasive pancreatic lesions with a spectrum of histologic phenotypes and variable risk in progressing to invasive cancer. Aberrant repetitive element expression has been shown to be functionally linked to cell state changes in pancreatic cancer. ObjectiveThis study utilized spatial transcriptomics with customized repeat element probes to better understand the relationship of histologic subtypes, repeat element dysregulation, and molecular profiles of different cell populations in IPMN. DesignA total of 52 lesions from 18 patients with resected IPMNs of different histologies and degrees of dysplasia were analyzed with whole transcriptome spatial analysis (GeoMx). Of these, 50 lesions from 17 patients were also processed for single-cell spatial molecular imaging (CosMx). Repeat element probes for LINE1, HSATII, HERVK, and HERVH were used for GeoMx and CosMx. ResultsPancreaticobiliary-type IPMN was enriched for basal-like epithelium and infiltration of Treg cells. Intestinal-type IPMN was enriched for classical epithelium and macrophage infiltrates. Gastric-type IPMN was found to have equal basal-like and classical epithelium with a diverse immune infiltrate. Repeat RNAs were expressed at high levels across IPMN phenotypes and enriched in high-grade dysplasia. Single-cell transcriptional trajectory analysis revealed a phylogeny starting from gastric toward intestinal and pancreaticobiliary branches associated with higher-grade dysplasia and repeat RNA expression. ConclusionSpatial transcriptomics of IPMN identified a molecular continuum between histological subtypes supporting a common gastric-type origin that transitions to intestinal and pancreatobiliary phenotypes. This cell state plasticity is linked with repeat element expression that can be a potential biomarker for IPMN progression. What is already known on this topicO_LIMolecular characterization of IPMN subtypes using regional spatial transcriptomics has described the differences between histologies C_LIO_LIRepeat element expression is associated with cell state changes in pancreatic ductal neoplasm C_LI What this study addsO_LISingle cell spatial molecular imaging of IPMN subtypes reveals a cellular and molecular continuum starting from gastric histology with distinct branches to Intestinal and pancreatobiliary subtypes C_LIO_LIRepeat element expression is associated with higher grade IPMN histology C_LIO_LIRepeat element expression is elevated in the histologic and molecular continuum from gastric to intestinal and pancreatobiliary-type IPMN C_LI How this study might affect research, practice, or policyO_LIThese results support a common gastric histology origin of IPMN subtypes with different molecular trajectories towards higher grade disease C_LIO_LIOur findings suggest that repeat RNA expression can be used in conjunction with other transcriptional markers of cell state as a biomarker for IPMN progression C_LI

cancer biology↗

High-resolution CTCF footprinting reveals impact of chromatin state on cohesin extrusion dynamics

DNA looping is vital for establishing many enhancer-promoter interactions. While CTCF is known to anchor many cohesin-mediated loops, the looped chromatin fiber appears to predominantly exist in a poorly characterized actively extruding state. To better characterize extruding chromatin loop structures, we used CTCF MNase HiChIP data to determine both CTCF binding at high resolution and 3D contact information. Here we present FactorFinder, a tool that identifies CTCF binding sites at near base-pair resolution. We leverage this substantial advance in resolution to determine that the fully extruded (CTCF-CTCF) state is rare genome-wide with locus-specific variation from ~1-10%. We further investigate the impact of chromatin state on loop extrusion dynamics, and find that active enhancers and RNA Pol II impede cohesin extrusion, facilitating an enrichment of enhancer-promoter contacts in the partially extruded loop state. We propose a model of topological regulation whereby the transient, partially extruded states play active roles in transcription.

genomics↗

Integrative PTEN Enhancer Discovery Reveals a New Model of Enhancer Organization

Enhancers possess both structural elements mediating promoter looping and functional elements mediating gene expression. Traditional models of enhancer-mediated gene regulation imply genomic overlap or immediate adjacency of these elements. We test this model by combining densely-tiled CRISPRa screening with nucleosome-resolution Region Capture Micro-C topology analysis. Using this integrated approach, we comprehensively define the cis-regulatory landscape for the tumor suppressor PTEN, identifying and validating 10 distinct enhancers and defining their 3D spatial organization. Unexpectedly, we identify several long-range functional enhancers whose promoter proximity is facilitated by chromatin loop anchors several kilobases away, and demonstrate that accounting for this spatial separation improves the computational prediction of validated enhancers. Thus, we propose a new model of enhancer organization incorporating spatial separation of essential functional and structural components.

genomics↗

Spatial analysis of human lung cancer reveals organized immune hubs enriched for stem-like CD8 T cells and associated with immunotherapy response

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially-localized multicellular immunity hubs defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens, and found that they were associated with beneficial responses to PD-1-blockade. Immunity hubs were enriched for many interferon-stimulated genes, T cells in multiple differentiation states, and CXCL9/10/11+ macrophages that preferentially interact with CD8 T cells. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcomes, distinct from mature tertiary lymphoid structures, and enriched for stem-like TCF7+PD-1+ CD8 T cells and activated CCR7+LAMP3+ dendritic cells, as well as chemokines that organize these cells. These results elucidate the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

immunology↗

Polycomb-lamina antagonism partitions heterochromatin at the nuclear periphery

The genome can be divided into two spatially segregated compartments, A and B,1,2 which broadly partition active and inactive chromatin states, respectively. Constitutive heterochromatin is predominantly located within the B compartment and comprises chromatin that is in close contact with the nuclear lamina.3-5 By contrast, facultative heterochromatin marked by H3K27me3 can span both compartments.2-5 How epigenetic modifications, A/B compartmentalization, and lamina association collectively maintain heterochromatin architecture and function remains unclear.6,7 Here we developed an approach termed Lamina-Inducible Methylation and Hi-C (LIMe-Hi-C) that jointly measures chromosome conformation, DNA methylation, and nuclear lamina positioning. Through this approach, we identified topologically distinct A/B sub-compartments characterized by high levels of H3K27me3 and differing degrees of lamina association. To study the regulation of these sub-compartments, we inhibited Polycomb repressive complex 2 (PRC2), revealing that H3K27me3 is an essential factor in sub-compartment segregation. Unexpectedly, PRC2 inhibition also elicited broad gains in lamina association and constitutive heterochromatin spreading into H3K27me3-marked B sub-compartment regions. Consistent with repositioning to the lamina, genes originally marked with H3K27me3 in the B compartment, but not in the A compartment, remained largely repressed, suggesting that constitutive heterochromatin spreading can compensate for loss of H3K27me3 at a transcriptional level. These findings demonstrate that Polycomb sub-compartments and their antagonism with nuclear lamina association are fundamental organizational features of genome structure. More broadly, by jointly measuring nuclear position and Hi-C contacts, our study demonstrates how dynamic changes in compartmentalization and nuclear lamina association represent distinct but interdependent modes of heterochromatin regulation.

genomics↗

Detection of allele-specific expression in spatial transcriptomics with spASE

Allele-specific expression (ASE), or the preferential expression of one allele, can be observed in transcriptomics data from early development throughout the lifespan. However, the prevalence of spatial and cell type-specific ASE variation remains unclear. Spatial transcriptomics technologies permit the study of spatial ASE patterns genome-wide at near-single-cell resolution. However, the data are highly sparse, and confounding between cell type and spatial location present further statistical challenges. Here, we introduce spASE (https://github.com/lulizou/spase), a computational framework for detecting spatial patterns in ASE within and across cell types from spatial transcriptomics data. To tackle the challenge presented by the low signal to noise ratio due to the sparsity of the data, we implement a spatial smoothing approach that greatly improves statistical power. We generated Slide-seqV2 data from the mouse hippocampus and detected ASE in X-chromosome genes, both within and across cell type, validating our ability to recover known ASE patterns. We demonstrate that our method can also identify cell type-specific effects, which we find can explain the majority of the spatial signal for autosomal genes. The findings facilitated by our method provide new insight into the uncharacterized landscape of spatial and cell type-specific ASE in the mouse hippocampus.

genomics↗

Data-driven polymer model for mechanistic exploration of diploid genome organization

Chromosomes are positioned non-randomly inside the nucleus to coordinate with their transcriptional activity. The molecular mechanisms that dictate the global genome organization and the nuclear localization of individual chromosomes are not fully understood. We introduce a polymer model to study the organization of the diploid human genome: it is data-driven as all parameters can be derived from Hi-C data; it is also a mechanistic model since the energy function is explicitly written out based on a few biologically motivated hypotheses. These two features distinguish the model from existing approaches and make it useful both for reconstructing genome structures and for exploring the principles of genome organization. We carried out extensive validations to show that simulated genome structures reproduce a wide variety of experimental measurements, including chromosome radial positions and spatial distances between homologous pairs. Detailed mechanistic investigations support the importance of both specific inter-chromosomal interactions and centromere clustering for chromosome positioning. We anticipate the polymer model, when combined with Hi-C experiments, to be a powerful tool for investigating large scale rearrangements in genome structure upon cell differentiation and tumor progression.

biophysics↗

CRISPR adenine and cytosine base editors with reduced RNA off-target activities

CRISPR-guided DNA base editors enable the efficient installation of targeted single-nucleotide changes. Cytosine or adenine base editors (CBEs or ABEs), which are fusions of cytidine or adenosine deaminases to CRISPR-Cas nickases, can efficiently induce DNA C-to-T or A-to-G alterations in DNA, respectively1-4. We recently demonstrated that both the widely used CBE BE3 (harboring a rat APOBEC1 cytidine deaminase) and the optimized ABEmax editor can induce tens of thousands of guide RNA-independent, transcriptome-wide RNA base edits in human cells with high efficiencies5. In addition, we showed the feasibility of creating SElective Curbing of Unwanted RNA Editing (SECURE)-BE3 variants that exhibit substantially reduced unwanted RNA editing activities while retaining robust and more precise on-target DNA editing5. Here we describe structure-guided engineering of SECURE-ABE variants that not only possess reduced off-target RNA editing with comparable on-target DNA activities but are also the smallest Streptococcus pyogenes Cas9 (SpCas9) base editors described to date. In addition, we tested CBEs composed of cytidine deaminases other than APOBEC1 and found that human APOBEC3A (hA3A) cytidine deaminase CBE induces substantial transcriptome-wide RNA base edits with high efficiencies. By contrast, a previously described \"enhanced\" A3A (eA3A) cytidine deaminase CBE or a human activation-induced cytidine deaminase (hAID) CBE induce substantially reduced or near background levels of RNA edits. In sum, our work describes broadly useful SECURE-ABE and -CBE base editors and reinforces the importance of minimizing RNA editing activities of DNA base editors for research and therapeutic applications.

molecular biology↗

Droplet-based combinatorial indexing for massive scale single-cell epigenomics

While recent technical advancements have facilitated the mapping of epigenomes at single-cell resolution, the throughput and quality of these methods have limited the widespread adoption of these technologies. Here, we describe a droplet microfluidics platform for single-cell assay for transposase accessible chromatin (scATAC-seq) for high-throughput single-cell profiling of chromatin accessibility. We use this approach for the unbiased discovery of cell types and regulatory elements within the mouse brain. Further, we extend the throughput of this approach by pairing combinatorial indexing with droplet microfluidics, enabling single-cell studies at a massive scale. With this approach, we measure chromatin accessibility across resting and stimulated human bone marrow derived cells to reveal changes in the cis- and trans- regulatory landscape across cell types and upon stimulation conditions at single-cell resolution. Altogether, we describe a total of 502,207 single-cell profiles, demonstrating the scalability and flexibility of this droplet-based platform.

genomics↗

Feature Selection and Dimension Reduction for Single Cell RNA-Seq based on a Multinomial Model

Single cell RNA-Seq (scRNA-Seq) profiles gene expression of individual cells. Recent scRNA-Seq datasets have incorporated unique molecular identifiers (UMIs). Using negative controls, we show UMI counts follow multinomial sampling with no zero-inflation. Current normalization pro-cedures such as log of counts per million and feature selection by highly variable genes produce false variability in dimension reduction. We pro-pose simple multinomial methods, including generalized principal component analysis (GLM-PCA) for non-normal distributions, and feature selection using deviance. These methods outperform current practice in a downstream clustering assessment using ground-truth datasets.

genomics↗

“Global Transcriptional Response to CRISPR/CAS9-AAV6 Based Genome Editing” Matches Transcriptional Response to Specific Small Molecule Perturbations

Cromer et al. [1] recently reported global transcriptional changes occuring in cells in response to CRISPR/Cas9 gene editing. Using a CD34+ hematopoietic and progenitor stem cell model, they observed differentially expressed genes enriched for immune, stress and apoptotic processes following treatment with a CRISPR/Cas9-AAV6 genome-editing system. Following treatment with Cas9s mRNA they observed transcriptional changes enriched for viral response as well as a downregulation of metabolic and cell cycle processes. Similarly, they observed a downregulation of metabolic processes in response to electroporation. Surprisingly, no enrichment for viral response genes was observed following treatment with AAV6 while minor transcriptional changes enriched for DNA damage signature occurred in response to Cas9/sgRNA ribonucleoprotein.

molecular biology↗

STREAM: Single-cell Trajectories Reconstruction, Exploration And Mapping of omics data

Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data.

genomics↗

In vivo CRISPR-Cas gene editing with no detectable genome-wide off-target mutations

CRISPR-Cas genome-editing nucleases hold substantial promise for human therapeutics1-5 but identifying unwanted off-target mutations remains an important requirement for clinical translation6, 7. For ex vivo therapeutic applications, previously published cell-based genome-wide methods provide potentially useful strategies to identify and quantify these off-target mutation sites8-12. However, a well-validated method that can reliably identify off-targets in vivo has not been described to date, leaving the question of whether and how frequently these types of mutations occur. Here we describe Verification of In Vivo Off-targets (VIVO), a highly sensitive, unbiased, and generalizable strategy that we show can robustly identify genome-wide CRISPR-Cas nuclease off-target effects in vivo. To our knowledge, these studies provide the first demonstration that CRISPR-Cas nucleases can induce substantial off-target mutations in vivo, a result we obtained using a deliberately promiscuous guide RNA (gRNA). More importantly, we used VIVO to show that appropriately designed gRNAs can direct efficient in vivo editing without inducing detectable off-target mutations. Our findings provide strong support for and should encourage further development of in vivo genome editing therapeutic strategies.

molecular biology↗

Interrogation of human hematopoiesis at single-cell and single-variant resolution

Incomplete annotation of cell-to-cell state variance and widespread linkage disequilibrium in the human genome represent significant challenges to elucidating mechanisms of trait-associated genetic variation. Here, using data from the UK Biobank, we perform genetic fine-mapping for 16 blood cell traits to quantify posterior probabilities of association while allowing for multiple independent signals per region. We observe an enrichment of fine-mapped variants in accessible chromatin of lineage-committed hematopoietic progenitor cells. Further, we develop a novel analytic framework that identifies \"core gene\" cell type enrichments and show that this approach uniquely resolves relevant cell types within closely related populations. Applying our approach to single cell chromatin accessibility data, we discover significant heterogeneity within classically defined multipotential progenitor populations. Finally, using several lines of empirical evidence, we identify relevant cell types, predict target genes, and propose putative causal mechanisms for fine-mapped variants. In total, our study provides an analytic framework for single-variant and single-cell analyses to elucidate putative causal variants and cell types from GWAS and high-resolution epigenomic assays.

genetics↗

Varying-Censoring Aware Matrix Factorization for Single Cell RNA-Sequencing

Single cell RNA-Seq (scRNA-Seq) has become the most widely used high-throughput technology for gene expression profiling of individual cells. The potential of being able to measure cell-to-cell variability at a high-dimensional genomic scale opens numerous new lines of investigation in basic and clinical research. For example, by identifying groups of cells with expression profiles unlike those observed in cells with known phenotypes, new cell types may be discovered. Dimension reduction followed by unsupervised clustering are the quantitative approaches typically used to facilitate such discoveries. However, a challenge for this approach is that most scRNA-Seq datasets are sparse, with the percentages of measurements reported as zero ranging from 35% to 99% across cells, and these zeros are partially explained by experimental inefficiencies that lead to censored data. Furthermore, the observed across-cell differences in the percentages of zeros are partly due to technical artifacts rather than biological differences. Unfortunately, standard dimension reduction approaches treat these censored values as true zeros, which leads to the identification of distorted low-dimensional factors. When these factors are used for clustering, the distortion leads to incorrect identification of biological groups. Here, we propose an approach that accounts for cell-specific censoring with a varying-censoring aware matrix factorization (VAMF) model that permits the identification of factors in the presence of the above described systematic bias. We demonstrate the advantages of our approach on published scRNA-Seq data and confirm these on simulated data.

genomics↗

"Unexpected mutations after CRISPR-Cas9 editing in vivo" are most likely pre-existing sequence variants and not nuclease-induced mutations

Schaefer et al. recently advanced the provocative conclusion that CRISPR-Cas9 nuclease can induce off-target alterations at genomic loci that do not resemble the intended on-target site.1 Using high-coverage whole genome sequencing (WGS), these authors reported finding SNPs and indels in two CRISPR-Cas9-treated mice that were not present in a single untreated control mouse. On the basis of this association, Schaefer et al. concluded that these sequence variants were caused by CRISPR-Cas9. This new proposed CRISPR-Cas9 off-target activity runs contrary to previously published work2-8 and, if the authors are correct, could have profound implications for research and therapeutic applications. Here, we demonstrate that the simplest interpretation of Schaefer et al.s data is that the two CRISPR-Cas9-treated mice are actually more closely related genetically to each other than to the control mouse. This strongly suggests that the so-called \"unexpected mutations\" simply represent SNPs and indels shared in common by these mice prior to nuclease treatment. In addition, given the genomic and sequence distribution profiles of these variants, we show that it is challenging to explain how CRISPR-Cas9 might be expected to induce such changes. Finally, we argue that the lack of appropriate controls in Schaefer et al.s experimental design precludes assignment of causality to CRISPR-Cas9. Given these substantial issues, we urge Schaefer et al. to revise or re-state the original conclusions of their published work so as to avoid leaving misleading and unsupported statements to persist in the literature.

molecular biology↗

The early pregnancy human placenta shares hypomethylation patterns characteristic of solid tumors

BackgroundThe placenta relies on phenotypes that are characteristic of cancer to successfully implant the embryo in the uterus during early pregnancy. Notably, it has to invade its host tissues, promote angiogenesis, while surviving hypoxia, and escape the immune system. Similarities in DNA methylation patterns between the placenta and cancers suggest that common epigenetic mechanisms may be involved in regulating these behaviors.\n\nResultsWe show here that megabase-scale patterns of hypomethylation distinguish first from third trimester chorionic villi in the placenta, and that these patterns mirror those that distinguish many tumors from corresponding normal tissues. We confirmed these findings in villous cytotrophoblasts isolated from the placenta and identified a time window at the end of the first trimester, when these cells come into contact with maternal blood as the likely time period for the methylome alterations. Furthermore, the large genomic regions affected by these patterns of hypomethylation encompass genes involved in pathways related to epithelial-mesenchymal transition (EMT), immune response and inflammation. Analyses of expression profiles corresponding to genes in these hypomethylated regions in colon adenocarcinoma tumors point to networks of differentially expressed genes previously implicated in carcinogenesis and placentogenesis, where nuclear factor kappa B (NF-kB) is a key hub.\n\nConclusionTaken together, our results suggest the existence of epigenetic switches involving large-scale changes of methylation in the placenta during pregnancy and in tumors during neoplastic transformation. The characterization of such epigenetic switches might lead to the identification of biomarkers and drug targets in oncology as well as in obstetrics and gynecology.

genomics↗