Biology subjects

O'Connell, B. L.

Publications and source records attributed to O'Connell, B. L..

10 recordsLinked to original sources

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

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

Atlas-scale Single-cell DNA Methylation Profiling with sciMETv3

Single-cell methods to assess DNA methylation have not yet achieved the same level of cell throughput compared to other modalities. Here, we describe sciMETv3, a combinatorial indexing-based technique that builds on our prior technology, sciMETv2. SciMETv3 achieves nearly a 100-fold improvement in cell throughput by increasing the index space while simultaneously reducing hands-on time and total costs per experiment. To reduce the sequencing burden of the assay, we demonstrate compatibility of sciMETv3 with capture techniques that enrich for regulatory regions, as well as the ability to leverage enzymatic conversion which can yield higher library diversity. We showcase the throughput of sciMETv3 by producing a >140k cell library from human middle frontal gyrus split across four multiplexed individuals using both Illumina and Ultima sequencing instrumentation. This library was prepared over two days by one individual and required no expensive equipment (e.g. a flow sorter, as required by sciMETv2). The same experiment produced an estimated 650k additional cells that were not sequenced, representing the power of sciMETv3 to meet the throughput needs of the most demanding atlas-scale projects. Finally, we demonstrate the compatibility of sciMETv3 with multimodal assays by introducing sciMET+ATAC, which will enable high- throughput exploration of the interplay between two layers of epigenetic regulation within the same cell, as well as the ability to directly integrate single-cell methylation datasets with existing single-cell ATAC-seq. HighlightsO_LIAtlas-scale production of single-cell DNA methylation libraries in a single experiment C_LIO_LIProtocols and evaluation using both Illumina and Ultima Genomics sequencing platforms C_LIO_LICompatibility of sciMETv3 with capture techniques to reduce sequencing burden C_LIO_LICompatibility of sciMETv3 with enzymatic conversion methods C_LIO_LIGeneration of an integrated >140,000 cell dataset from human middle frontal gyrus across four individuals C_LIO_LIAbility to profile both ATAC and genome-wide DNA methylation from the same cells and integration with datasets from each modality C_LIO_LIA novel implementation of the s3-ATAC technology that leverages a nanowell chip for increased throughput C_LI MotivationDNA methylation forms a basal layer of epigenomic regulatory control, shaping the genomic permissiveness of mammalian cells during lineage specification and development. Aberrant DNA methylation has been associated with myriad health conditions ranging from developmental disorders to cancer. The high cell type specificity necessitates analysis at the single-cell level, much like transcription or other epigenomic properties. However, robust and cost-effective techniques to produce atlas-scale datasets have not been realized for DNA methylation. Here, we directly meet this need by introducing sciMETv3, a high-throughput protocol capable of producing hundreds of thousands of single-cell DNA methylation profiles in a single experiment.

genetics↗

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

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↗

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

Erosion of the Epigenetic Landscape and Loss of Cellular Identity as a Cause of Aging in Mammals

All living things experience entropy, manifested as a loss of inherited genetic and epigenetic information over time. As budding yeast cells age, epigenetic changes result in a loss of cell identity and sterility, both hallmarks of yeast aging. In mammals, epigenetic information is also lost over time, but what causes it to be lost and whether it is a cause or a consequence of aging is not known. Here we show that the transient induction of genomic instability, in the form of a low number of non-mutagenic DNA breaks, accelerates many of the chromatin and tissue changes seen during aging, including the erosion of the epigenetic landscape, a loss of cellular identity, advancement of the DNA methylation clock and cellular senescence. These data support a model in which a loss of epigenetic information is a cause of aging in mammals.\n\nOne Sentence SummaryThe act of repairing DNA breaks induces chromatin reorganization and a loss of cell identity that may contribute to mammalian aging

molecular biology↗

bioRxiv2018

EquCab3, an Updated Reference Genome for the Domestic Horse

EquCab2, a high-quality reference genome for the domestic horse, was released in 2007. Since then, it has served as the foundation for nearly all genomic work done in equids. Recent advances in genomic sequencing technology and computational assembly methods have allowed scientists to improve reference assemblies of large animal and plant genomes in terms of contiguity and composition. In 2014, the equine genomics research community began a project to improve the reference sequence for the horse, building upon the solid foundation of EquCab2 and incorporating new short-read data, long-read data, and proximity ligation data. The result, EquCab3, is presented here. The count of non-N bases in the incorporated chromosomes is improved from 2.33Gb in EquCab2 to 2.41Gb from EquCab3. Contiguity has also been improved nearly 40-fold with a contig N50 of 4.5Mb and scaffold contiguity enhanced to where all but one of the 32 chromosomes is comprised of a single scaffold.

genomics↗

bioRxiv2017

Natural selection shaped the rise and fall of passenger pigeon genomic diversity

The extinct passenger pigeon was once the most abundant bird in North America, and possibly the world. While theory predicts that large populations will be more genetically diverse and respond more efficiently to selection, passenger pigeon genetic diversity was surprisingly low. To investigate this we analysed 41 mitochondrial and 4 nuclear genomes from passenger pigeons, and 2 genomes from band-tailed pigeons, passenger pigeons closest living relatives. We find that passenger pigeons large population size allowed for faster adaptive evolution and removal of harmful mutations, but that this drove a huge loss in neutral genetic diversity. These results demonstrate how great an impact selection can have on a vertebrate genome, and invalidate previous results that suggested population instability contributed to this species surprisingly rapid extinction.

genomics↗