Biology subjects

Adey, A. C.

Publications and source records attributed to Adey, A. C..

At least 19 recordsLinked to original sources

bioRxiv2026

Epigenetic progression of pancreatic cancer to aggressive subtypes involves alternate routes of lineage reprogramming in subtype-intermediate progenitor cells

Pancreatic ductal adenocarcinoma (PDAC) progression involves malignant cell state plasticity. Epigenetic changes underlie this plasticity, yet the PDAC cis-regulatory landscape remains understudied. To address this, we profiled 33 primary tumors and 7 metastases from 39 patients with single-cell ATAC-seq, paired with 10 single-cell RNA-seq profiles. We found that epigenetic GATA6+/KRT17+ co-accessibility identifies a classical-basal subtype-intermediate progenitor state (SIP) associated with better clinical outcomes. SIP cells display limited epigenetic reprogramming from premalignant epithelium and retain gastric-intestinal differentiation reminiscent of neoplastic precursors. Lineages without GATA6+/KRT17+ co-accessibility exhibit greater lineage and epithelial-mesenchymal plasticity. Classical PDACs that repress basal gene accessibility activate neural-like progenitor (NRP) and tuft lineage enhancers, whereas basal committed tumors display esophageal transdifferentiation. Compared to SIP, classical-NRP and basal committed tumors have poorer outcomes, and show distinct PD-1/PD-L1 immune proteomic phenotypes and prognostic myofibroblast epigenetic states, respectively. Our work reveals links between lineage reprogramming, EMT, and epigenetic progression in human PDAC.

cancer biology↗

bioRxiv2026

Early postnatal DNA methylation dynamics define neuronal subtypes and are disrupted by MECP2 loss

DNA methylation is the foundational layer of epigenetic regulation underlying mammalian tissue specification. During synaptogenesis, neurons accumulate high levels of a unique type of methylation in which a cytosine precedes a C, A, or T (mCH) instead of the canonical guanine (mCG). Disruption of the mCH reader methyl-CpG binding protein 2 (MECP2) causes the devastating neurodevelopmental disorder Rett syndrome, yet the role of mCH in neurodevelopment remains unclear. In this study, we generated the first large-scale single-cell methylation atlas of the early postnatal mouse brain and resolved subtype-specific trajectories of canonical and noncanonical methylation changes underlying neuronal subtype specification. Each identified population undergoes a rapid maturation event of the noncanonical methylome occurring between the first and second postnatal weeks, with highly subtype-specific changes concentrated at genes involved in synaptic partner establishment. Trajectory analysis resolved that subtype diversification, such as the separation of parvalbumin and somatostatin-positive GABAergic interneurons, is further facilitated by a hierarchical sequence of methylation changes in genes involved in regulation of membrane potential. In parallel, we applied single-cell methylation analysis to a mouse model of Rett syndrome that recapitulates severe human symptoms. We show that while noncanonical methylation accumulation proceeds in each subtype in the absence of MECP2, populations that have been consistently implicated in Rett pathology such as GABAergic interneurons have an increasing number of differentially methylated regions with age and fail to accumulate typical global levels of mCH. Together, our study defines the methylation dynamics that facilitate neuronal subtype specification and resolves subtype-specific, global disruptions of noncanonical methylation in Rett syndrome.

neuroscience↗

bioRxiv2026

Cell fusion reprograms tumor cells and promotes RUNX1-mediated invasion and dissemination in colorectal cancer

Metastasis remains the primary cause of cancer-related morbidity and mortality, despite significant advances in targeted therapies. Although metastatic dissemination requires tumor cells to escape the primary lesion and colonize distant organs, the mechanisms by which primary tumor cells gain metastatic competence remain poorly understood. Increasing evidence demonstrates that fusion of tumor (i.e., neoplastic) and immune (e.g., macrophages) cells generate a distinct population of tumor-immune hybrid cells with enhanced functional ability to migrate and disseminate into peripheral blood. Herein, our study investigates tumor-macrophage hybrid cells, an underexplored population of disseminated tumor cells, and their inherent heterogeneity and acquisition of molecular mechanisms underlying their dissemination as metastatic effectors in colorectal cancer (CRC). Through hybrid cell phenotyping utilizing integrative single-cell RNA sequencing (scRNA-seq), cyclic immunofluorescence (cyCIF) and functional assays with an in vitro model of CRC hybrid cells, we identify Runt-related transcription factor 1 (Runx1) as a central regulator of hybrid cell motility and invasion. Runx1 depletion in hybrid cells suppressed functional protease expression, chemotactic activity and extracellular matrix (ECM) invasion. Furthermore, pharmacologic inhibition of RUNX1 in an in vivo model reduced hybrid tumor growth and dissemination into peripheral blood, key attributes of metastatic spread of disease. In patients with CRC, RUNX1+ hybrid cells were identified in both primary tumor and peripheral blood, where circulating hybrid cells (CHCs) exhibited enriched migratory and epithelial-to-mesenchymal transition (EMT) phenotypes. Taken together, these findings reveal a mechanistic role for RUNX1 in driving invasive behavior of tumor-immune hybrids and highlight disseminated CHCs as an under-recognized contributor to metastatic spread and a promising noninvasive biomarker for tumor progression.

cancer biology↗

bioRxiv2026

PU.1 inhibition sensitizes stem-monocytic AML to BCL2 blockade

Acute myeloid leukemia (AML) exhibits substantial transcriptional heterogeneity across differentiation states that influences therapeutic response to BCL2 inhibition with venetoclax. While hematopoietic stem cell (HSC)-like AMLs show high sensitivity to venetoclax and monocytic-like AMLs demonstrate resistance, the therapeutic behavior of leukemias harboring both transcriptional programs remains poorly defined. Analysis of a large AML cohort reveals a distinct patient population exhibiting concurrent HSC- and monocyte-like transcriptional signatures, which we term stem-monocytic AML. Ex vivo drug sensitivity profiling demonstrates that stem-monocytic AMLs exhibit venetoclax resistance comparable to pure monocytic disease, despite expressing HSC-like transcriptional features. Using a leukemia cell line model that recapitulates stem-monocytic AML characteristics, we show through immunophenotyping and single-cell lineage tracing that venetoclax preferentially depletes immature blasts while sparing differentiated monocytic populations. Single-cell transcriptomic and chromatin accessibility analyses identify enrichment of myeloid differentiation transcription factors, particularly PU.1, in resistant populations. A targeted CRISPR knockout screen confirms that PU.1 disruption induces differentiation arrest and enhances venetoclax sensitivity primarily in the immature immunophenotypic compartments. Pharmacologic PU.1 inhibition with the small molecule DB2313 synergizes with venetoclax in both cell line models and primary patient samples. These findings establish stem-monocytic AML as a transcriptionally and functionally distinct subtype and nominate combined PU.1 and BCL2 inhibition as a rational therapeutic strategy for improving venetoclax response in this patient population.

cancer biology↗

bioRxiv2026

Mutant ASXL1 Drives Transcriptional Activation and Repression in Human Hematopoiesis

Mutations in the epigenetic regulator ASXL1 are common in myeloid malignancies and portend a near-universally poor prognosis. While multiple mechanisms for mutant ASXL1-dependent oncogenesis have been proposed, none have been functionally validated in the context of the human hematopoietic stem cell, where these mutations almost certainly arise. Here, we extensively characterized a CRISPR-engineered human hematopoietic stem and progenitor cell model of ASXL1 mutations. In this context, mutant ASXL1 expression decreases differentiation, increases clonogenicity in serial replating experiments, and improves engraftment in immunodeficient mice. We also show that endogenous truncating mutations in ASXL1 drive protein stabilization and confirm that mutant ASXL1 is resistant to proteasomal degradation. At the transcriptional level, these phenotypes are driven by significant repression of the stress-response genes and by increased expression of bromodomain and extra-terminal family protein targets. Using protein-interaction screens, genomic and functional approaches, we link the positive transcriptional changes in ASXL1-mutant cells to BRD4-dependent RNA polymerase II pause release and identify a mechanism for transcriptional repression via a previously uncharacterized interaction with the transcription factor MECOM. Finally, we demonstrate that ASXL1-mutant AML exhibits increased MECOM activity consistent with our gene-editing models. Collectively, these studies highlight a highly reproducible model of mutant ASXL1 in the appropriate cell context. Further, they are the first to functionally describe the mutant ASXL1 interactome in the context of the human HSC, identifying new dependencies with therapeutic potential.

cancer biology↗

bioRxiv2024

Single-cell DNA methylation analysis tool Amethyst reveals distinct noncanonical methylation patterns in human glial cells

Single-cell sequencing technologies have revolutionized biomedical research by enabling deconvolution of cell type-specific properties in highly heterogeneous tissue. While robust tools have been developed to handle bioinformatic challenges posed by single-cell RNA and ATAC data, options for emergent modalities such as methylation are much more limited, impeding the utility of results. Here we present Amethyst, a comprehensive R package for atlas-scale single-cell methylation sequencing data analysis. Amethyst begins with base-level methylation calls and expedites batch integration, doublet detection, dimensionality reduction, clustering, cell type annotation, differentially methylated region calling, and interpretation of results, facilitating rapid data interaction in a local environment. We introduce the workflow using published single-cell methylation human peripheral blood mononuclear cell (PBMC) and human cortex data. We further leverage Amethyst on an atlas-scale brain dataset to describe a noncanonical methylation pattern in human astrocytes and oligodendrocytes, challenging the notion that this form of methylation is principally relevant to neurons in the brain. Tools such as Amethyst will increase accessibility to single-cell methylation data analysis, catalyzing research progress across diverse contexts.

neuroscience↗

bioRxiv2023

Longitudinal and multimodal auditing of tumor adaptation to CDK4/6 inhibitors in HR+ metastatic breast cancers

CDK4/6 inhibitors (CDK4/6i) have transformed the treatment of hormone receptor-positive (HR+), HER2-negative (HR+) breast cancers as they are effective across all clinicopathological, age, and ethnicity subgroups for metastatic HR+ breast cancer. In metastatic ER+ breast cancer, CDK4/6i lead to strong and consistent improvement in survival across different lines of therapy. To improve understanding of how metastatic HR+ breast cancers become refractory to CDK4/6i, we have created a multimodal and longitudinal tumor atlas to investigate therapeutic adaptations in malignant cells and in the tumor immune microenvironment. This atlas is part of the NCI Cancer Moonshot Human Tumor Atlas Network and includes seven pairs of pre- and on-progression biopsies from five metastatic HR+ breast cancer patients treated with CDK4/6i. Biopsies were profiled with bulk genomics, transcriptomics, and proteomics as well as single-cell ATAC-seq and multiplex tissue imaging for spatial, single-cell resolution. These molecular datasets were then linked with detailed clinical metadata to create an atlas for understanding tumor adaptations during therapy. Analysis of our atlas datasets suggests a diverse set of tumor adaptations to CDK4/6i therapy. Malignant cells may adapt to therapy via mTORC1 activation, cell cycle bypass, and increased replication stress. The tumor immune microenvironment displayed evidence of both immune activation and immune suppression during therapy. Together, our metastatic ER+ breast cancer atlas represents a rich multimodal resource to better understand HR+ breast cancer tumor therapeutic adaptations to CDK4/6i therapy.

cancer biology↗

bioRxiv2023

sciMET-cap: High-throughput single-cell methylation analysis with a reduced sequencing burden

DNA methylation is a key component of the mammalian epigenome, playing a regulatory role in development, disease, and other processes. Robust, high-throughput single-cell DNA methylation assays are now possible (sciMET); however, the genome-wide nature of DNA methylation results in a high sequencing burden per cell. Here, we leverage target enrichment with sciMET to capture sufficient information per cell for cell type assignment using substantially fewer sequence reads (sciMET-cap). Sufficient off-target coverage further enables the production of near-complete methylomes for individual cell types. We characterize sciMET-cap on human PBMCs and brain (middle frontal gyrus).

genetics↗

bioRxiv2023

txci-ATAC-seq, a massive-scale single-cell technique to profile chromatin accessibility

Measuring chromatin accessibility is a powerful method to identify cell types and states. Performed at single-cell resolution, this assay has generated catalogs of genome-wide DNA regulatory sites, whole-organism cell atlases, and dynamic chromatin reorganization through development. However, the limited throughput of current single-cell approaches poses a challenge for implementing proper study designs, population-scale profiling, and/or very deep profiling of complex samples. To this end, we developed a 10X-compatible combinatorial indexing ATAC sequencing ("txci-ATAC-seq"), which is a combinatorial indexing framework that initially indexes ("pre-indexes") chromatin within nuclei with barcoded transposases followed by encapsulation and further barcoding using a commercialized droplet-based microfluidics platform (10X Genomics). Leveraging this molecular hashing strategy, we demonstrate that txci-ATAC-seq enables the indexing of up to 200,000 nuclei across multiple samples in a single emulsion reaction, representing a [~]22-fold increase in throughput compared to the standard workflow at the same collision rate. To improve the efficiency of this new technique, we further developed a faster version of the protocol ("Fast-txci-ATAC-seq") that separates sample pre-processing from library generation and has the potential to profile up to 96 samples simultaneously. We initially benchmarked our assay by generating chromatin accessibility profiles for 230,018 cells from five native tissues across three experiments, including human cortex (28,513 cells), mouse brain (48,997 cells), human lung (15,799 cells), mouse lung (73,280 cells), and mouse liver (63,429 cells). We also applied our method to a club cell secretory protein knockout (CC16-/-) mouse model to examine the biological and technical limitations of the mouse line. By characterizing DNA regulatory landscapes in 76,498 wild-type and 77,638 CC16-/- murine lung nuclei, our investigations uncovered previously unappreciated residual genetic deviations from the reference strain that resulted from the method of gene targeting, which employed embryonic stem cells from the 129 strain. We found that these genetic remnants from the 129 strain led to profound cell-type-specific changes in chromatin accessibility in regulatory elements near a host of genes. Collectively, we defined single-cell chromatin signatures in 384,154 nuclei from 13 primary samples across different species, organs, biological replicates, and genetic backgrounds, establishing txci-ATAC-seq as a robust, high-quality, and highly multiplexable single-cell assay for large-scale chromatin studies.

genomics↗

bioRxiv2023

Supervised learning of high-confidence phenotypic subpopulations from single-cell data

Accurately identifying phenotype-relevant cell subsets from heterogeneous cell populations is crucial for delineating the underlying mechanisms driving biological or clinical phenotypes. Here, by deploying a learning with rejection strategy, we developed a novel supervised learning framework called PENCIL to identify subpopulations associated with categorical or continuous phenotypes from single-cell data. By embedding a feature selection function into this flexible framework, for the first time, we were able to select informative features and identify cell subpopulations simultaneously, which enables the accurate identification of phenotypic subpopulations otherwise missed by methods incapable of concurrent gene selection. Furthermore, the regression mode of PENCIL presents a novel ability for supervised phenotypic trajectory learning of subpopulations from single-cell data. We conducted comprehensive simulations to evaluate PENCILs versatility in simultaneous gene selection, subpopulation identification and phenotypic trajectory prediction. PENCIL is fast and scalable to analyze 1 million cells within 1 hour. Using the classification mode, PENCIL detected T-cell subpopulations associated with melanoma immunotherapy outcomes. Moreover, when applied to scRNA-seq of a mantle cell lymphoma patient with drug treatment across multiple time points, the regression mode of PENCIL revealed a transcriptional treatment response trajectory. Collectively, our work introduces a scalable and flexible infrastructure to accurately identify phenotype-associated subpopulations from single-cell data.

bioinformatics↗

bioRxiv2022

Dual states of Bmi1-expressing intestinal stem cells drive epithelial development and tissue regeneration

Intestinal development, response to injury and disease states rely upon balanced stem cell proliferation. Historically, two subtypes of intestinal epithelial stem cells (ISCs)--slow-cycling/label-retaining, and actively-cycling/canonical Wnt-dependent--coordinate to drive proliferation and regulate epithelial renewal during adult tissue homeostasis and injury response. Recent studies focused on Bmi1-expressing cells revealed that differentiated Bmi1+ enteroendocrine cells could dedifferentiate towards a canonical Wnt-dependent stem cell state, calling into question the dogma that a dual stem cell axis regulates epithelial proliferation. Herein, we identify stem cell function in a Bmi1+ cell population in early murine intestinal development prior to the establishment of canonical Wnt-dependent, Lgr5-expressing ISCs. In-depth analyses of developmental Bmi1+ ISCs using lineage-tracing and single cell RNA-sequencing reveal their distinct identity and capacity to differentiate into Lgr5+ ISCs and other differentiated lineages. Further, during in utero development, the Bmi1+ ISCs initially exists in a highly proliferative state then transitions to a slow-cycling state, with the emergence of actively-cycling Lgr5+ ISCs. In adult tissue, Bmi1+ ISCs are a distinct population that re-express developmental gene and protein profiles, and a non-canonical Wnt signaling signature in response to injury and in human colorectal tumors. Further, developmental Bmi1+ ISCs are distinct from Lgr5+ ISCs and the previously identified differentiated Bmi1+ progenitor cells. Re-evaluation of an under-appreciated Bmi1+ ISC population with fundamental importance in intestinal development re-establishes the importance of the dynamic interplay between discrete ISC populations that are regulated by opposing Wnt signaling pathways. This finding opens opportunities and targetable pathways to augment regeneration or inhibit tumorigenesis.

developmental biology↗

bioRxiv2022

Shared and distinct functional effects of patient-specific Tbr1 mutations on cortical development

Predicted loss-of-function and missense heterozygous de novo mutations of TBR1 are strongly associated with intellectual disability and autism. The functional effects of these heterogeneous mutations on cortical development and genotype-phenotype relationships have yet to be explored. We characterized mouse models carrying patient mutations A136PfsX80 and K228E, finding convergent and discordant phenotypes. The A136PfsX80 mutation is loss-of-function and allelic to the Tbr1 knockout. In contrast, K228E causes significant upregulation of TBR1. Heterozygosity of either mutation produces axon defects, including reduction of the anterior commissure, and CTIP2 downregulation in adult cortex. While mice lacking TBR1 show extensive cortical apoptosis and inverted layering, K228E homozygotes show normal apoptosis levels and a complex layering phenotype--suggesting partial, yet abnormal, function of the allele. The construct and face validity of these Tbr1 patient mutation mice suggests they will be valuable translational models for studying the function of this essential brain transcription factor.

neuroscience↗

bioRxiv2021

High-content single-cell combinatorial indexing

Single-cell genomics assays have emerged as a dominant platform for interrogating complex biological systems. Methods to capture various properties at the single-cell level typically suffer a tradeoff between cell count and information content, which is defined by the number of unique and usable reads acquired per cell. We and others have described workflows that utilize single-cell combinatorial indexing (sci)1, leveraging transposase-based library construction2 to assess a variety of genomic properties in high throughput; however, these techniques often produce sparse coverage for the property of interest. Here, we describe a novel adaptor-switching strategy, s3, capable of producing one-to-two order-of-magnitude improvements in usable reads obtained per cell for chromatin accessibility (s3-ATAC), whole genome sequencing (s3-WGS), and whole genome plus chromatin conformation (s3-GCC), while retaining the same high-throughput capabilities of predecessor sci technologies. We apply s3 to produce high-coverage single-cell ATAC-seq profiles of mouse brain and human cortex tissue; and whole genome and chromatin contact maps for two low-passage patient-derived cell lines from a primary pancreatic tumor.

genetics↗

bioRxiv2020

Cas12a-Capture: a novel, low-cost, and scalable method for targeted sequencing

Targeted sequencing remains a valuable technique for clinical and research applications. However, many existing technologies suffer from pervasive GC sequence content bias, high input DNA requirements, and high cost for custom panels. We have developed Cas12a-Capture, a low-cost and highly scalable method for targeted sequencing. The method utilizes preprogramed guide RNAs to direct CRISPR-Cas12a cleavage of double stranded DNA in vitro and then takes advantage of the resulting four to five nucleotide overhangs for selective ligation with a custom sequencing adapter. Addition of a second sequencing adapter and enrichment for ligation products generates a targeted sequence library. We first performed a pilot experiment with 7,176 guides targeting 3.5 megabases of DNA. Using these data, we modeled the sequence determinants of Cas12a-Capture efficiency, then designed an optimized set of 11,438 guides targeting 3.0 megabases. The optimized guide set achieves an average 64-fold enrichment of targeted regions with minimal GC bias. Cas12a-Capture variant calls had strong concordance with Illumina Platinum Genome calls, especially for SNVs, which could be improved by applying basic variant quality heuristics. We believe Cas12a-Capture has a wide variety of potential clinical and research applications and is amendable for selective enrichment for any double stranded DNA template or genome.

genomics↗

bioRxiv2019

Spatially-mapped single-cell chromatin accessibility

High-throughput single-cell epigenomic assays can resolve the heterogeneity of cell types and states in complex tissues, however, spatial orientation within the network of interconnected cells is lost. Here, we present a novel method for highly scalable, spatially resolved, single-cell profiling of chromatin states. We use high-density multiregional sampling to perform single-cell combinatorial indexing on Microbiopsies Assigned to Positions for the Assay for Transposase Accessible Chromatin (sciMAP-ATAC) to produce single-cell data of an equivalent quality to non-spatially resolved single-cell ATAC-seq, where each cell is localized to a three-dimensional position within the tissue. A typical experiment comprises between 96 and 384 spatially mapped tissue positions, each producing 10s to over 100 individual single-cell ATAC-seq profiles, and a typical resolution of 214 cubic microns; with the ability to tune the resolution and cell throughput to suit each target application. We apply sciMAP-ATAC to the adult mouse primary somatosensory cortex, where we profile cortical lamination and demonstrate the ability to analyze data from a single tissue position or compare a single cell type in adjacent positions. We also profile the human primary visual cortex, where we produce spatial trajectories through the cortex. Finally, we characterize the spatially progressive nature of cerebral ischemic infarct in the mouse brain using a model of transient middle cerebral artery occlusion. We leverage the spatial information to identify novel and known transcription factor activities that vary by proximity to the ischemic infarction core with cell type specificity.

genetics↗

bioRxiv2019

Improved single-cell ATAC-seq reveals chromatin dynamics of in vitro corticogenesis

Development is a complex process that requires the precise modulation of regulatory gene networks controlled through dynamic changes in the epigenome. Single-cell-omic technologies provide an avenue for understanding the mechanisms of these processes by capturing the progression of epigenetic cell states during the course of cellular differentiation using in vitro or in vivo models1. However, current single-cell epigenomic methods are limited in the information garnered per individual cell, which in turn limits their ability to measure chromatin dynamics and state shifts. Single-cell combinatorial indexing (sci-) has been applied as a strategy for identifying single-cell-omic originating libraries and removes the necessity of single-cell, single-compartment chemistry2. Here, we report an improved sci-assay for transposase accessible chromatin by sequencing (ATAC-seq), which utilizes the small molecule inhibitor Pitstop 2 (scip-ATAC-seq)3. We demonstrate that these improvements, which theoretically could be applied to any in situ transposition method for single-cell library preparation, significantly increase the ability of transposase to enter the nucleus and generate highly complex single-cell libraries, without altering biological signal. We applied sci-ATAC-seq and scip-ATAC-seq to characterize the chromatin dynamics of developing forebrain-like organoids, an in vitro model of human corticogenesis4. Using these data, we characterized novel putative regulatory elements, compared the epigenome of the organoid model to human cortex data, generated a high-resolution pseudotemporal map of chromatin accessibility through differentiation, and measured epigenomic changes coinciding with a neurogenic fate decision point. Finally, we combined transcription factor motif accessibility with gene activity (GA) scores to directly observe the dynamics of complex regulatory programs that regulate neurogenesis through developmental pseudotime. Overall, scip-ATAC-seq increases information content per cell and bolsters the potential for future single-cell studies into complex developmental processes.

genomics↗

bioRxiv2018

The accessible chromatin landscape of the hippocampus at single-cell resolution

Here we present a comprehensive map of the accessible chromatin landscape of the mouse hippocampus at single-cell resolution. Substantial advances of this work include the optimization of single-cell combinatorial indexing assay for transposase accessible chromatin (sci-ATAC-seq), a software suite, scitools, for the rapid processing and visualization of single-cell combinatorial indexing datasets, and a valuable resource of hippocampal regulatory networks at single-cell resolution. We utilized sci-ATAC-seq to produce 2,346 high-quality single-cell chromatin accessibility maps with a mean unique read count per cell of 29,201 from both fresh and frozen hippocampi, observing little difference in accessibility patterns between the preparations. Using this dataset, we identified eight distinct major clusters of cells representing both neuronal and non-neuronal cell types and characterized the driving regulatory factors and differentially accessible loci that define each cluster. We then applied a recently described co-accessibility framework, Cicero, which identified 146,818 links between promoters and putative distal regulatory DNA. Identified co-accessibility networks showed cell-type specificity, shedding light on key dynamic loci that reconfigure to specify hippocampal cell lineages. Lastly, we carried out an additional sci-ATAC-seq preparation from cultured hippocampal neurons (899 high-quality cells, 43,532 mean unique reads) that revealed substantial alterations in their epigenetic landscape compared to nuclei from hippocampal tissue. This dataset and accompanying analysis tools provide a new resource that can guide subsequent studies of the hippocampus.

neuroscience↗

bioRxiv2018

High-throughput mapping of meiotic crossover and chromosome mis-segregation events in interspecific hybrid mice

We developed \"sci-LIANTI\", a high-throughput, high-coverage single-cell DNA sequencing method that combines single-cell combinatorial indexing (\"sci\") and linear amplification via transposon insertion (\"LIANTI\"). To characterize rare chromosome mis-segregation events in male meiosis and their relationship to the landscape of meiotic crossovers, we applied sci-LIANTI to profile the genomes of 6,928 sperm and sperm precursors from infertile, interspecific F1 male mice. From 1,663 haploid and 292 diploid cells, we mapped 24,672 crossover events and identified genomic and epigenomic contexts that influence crossover hotness. Surprisingly, we observed frequent mitotic chromosome segregation during meiosis. Moreover, segregation during meiosis in individual cells was highly biased towards either mitotic or meiotic events. We anticipate that sci-LIANTI can be applied to fully characterize various recombination landscapes, as well as to other fields requiring high-throughput, high-coverage single-cell genome sequencing.\n\nOne Sentence SummarySingle-cell genome sequencing maps crossover and non-meiotic chromosome segregation during spermatogenesis in interspecific hybrid mice.

genetics↗