Biology subjects

Hook, P. W.

Publications and source records attributed to Hook, P. W..

11 recordsLinked to original sources

bioRxiv2025

Ultrafast CTCF dynamics control cohesin barrier function

Genomes are organized into chromatin loops through cohesin-mediated extrusion, with CTCF acting as a polar boundary element. As cohesin approaches CTCF at kilobase-per-second speeds, it must rapidly choose whether to stall or bypass. How CTCF encodes this probabilistic decision within a brief encounter window has remained unclear. Here we show that CTCF governs this probabilistic outcome by rapidly sampling a dynamic ensemble of conformations generated by spontaneous rearrangements of its DNA-binding zinc fingers. This ensemble is tuned by DNA sequence, CpG methylation, nearby nucleosomes, and the cohesin regulator PDS5A before cohesin engagement. Upon cohesin binding, PDS5A enhances loop-anchor mechanical stability, reinforcing orientation-dependent boundaries. These findings establish conformational ensemble tuning, rather than static occupancy, as a regulatory principle linking base pair-scale motions to megabase-scale genome organization. One sentence summaryChromatin boundary function is governed not by CTCF occupancy alone, but by a tunable ensemble of DNA-bound conformations that probabilistically gates cohesin capture.

biophysics↗

bioRxiv2025

Single-cell long-read sequencing of the experience-induced transcriptome

Neural activity drives transcriptional events that are critical for learning. Activity-induced transcript isoform expression and alternative splicing are cell-type specific events typically obscured by sequencing approaches that restrict read length. We combined single-cell transcriptomics with Nanopore long-read sequencing to resolve these phenomena, generating the first dataset profiling learning-induced gene and isoform expression in individual mouse hippocampal cells. Due to their length, the majority of reads we generated could be uniquely mapped to their respective gene and isoform features in the mouse reference. [~]20k cells from 16 mouse samples were sequenced and clustered on the basis of gene expression, yielding 21 hippocampal cell types. Differential expression analysis revealed 1,266 significantly experience-variable isoforms, revealing novel splicing behavior in many synaptic genes. This work is the first to comprehensively profile activity-induced isoform expression, demonstrating that single cell long-read sequencing can reveal new layers of transcriptional complexity.

neuroscience↗

bioRxiv2025

Epigenetically dynamic human centromeres are maintained within a stable DNA methylation signature

Centromere location is specified by CENP-A, a centromere-specific histone that epigenetically defines centromere identity. How CENP-A is maintained at one location in rapidly evolving centromeric DNA is unknown. Using single-cell-derived clones of human cell lines, we demonstrate single-cell heterogeneity in CENP-A position within cell populations at neocentromeres and a native centromere. CENP-A heterogeneity is accompanied by unique DNA methylation and H3K9me3 patterns, with DNA methylation shifting according to CENP-A position. We further demonstrate centromere epigenetic evolution over prolonged proliferation, with native centromeres maintaining stable heterochromatin boundaries, but neocentromeres exhibiting DNA methylation instability, H3K9me3 gain, boundary loss and fragility. Lastly, prolonged CENP-A and HJURP overexpression leads to centromere and neocentromere expansion, gradual CENP-A depletion, neocentromere destabilization and CENP-A re-localization that is accompanied by local heterochromatin remodeling. This study reveals the naturally evolving epigenetic plasticity of human centromeres and neocentromeres and highlights the importance of repressive chromatin boundaries in maintaining centromere stability.

cell biology↗

bioRxiv2024

Nanopore Decoding with Speed and Versatility for Data Storage

MotivationAs nanopore technology reaches ever higher throughput and accuracy, it becomes an increasingly viable candidate for reading out DNA data storage. Nanopore sequencing offers considerable flexibility by allowing long reads, real-time signal analysis, and the ability to read both DNA and RNA. We need flexible and efficient designs that match nanopores capabilities, but relatively few designs have been explored and many have significant inefficiency in read density, error rate, or compute time. To address these problems, we designed a new single-read per-strand decoder that achieves low byte error rates, offers high throughput, scales to long reads, and works well for both DNA and RNA molecules. We achieve these results through a novel soft decoding algorithm that can be effectively parallelized on a GPU. Our faster decoder allows us to study a wider range of system designs. ResultsWe demonstrate our approach on HEDGES, a state-of-the-art DNA-constrained convolutional code. We implement one hard decoder that runs serially and two soft decoders that run on GPUs. Our evaluation for each decoder is applied to the same population of nanopore reads collected from a synthesized library of strands. These same strands are synthesized with a T7 promoter to enable RNA transcription and decoding. Our results show that the hard decoder has a byte error rate over 25%, while the prior state of the art soft decoder can achieve error rates of 2.25%. However, that design also suffers a low throughput of 183 seconds/read. Our new Alignment Matrix Trellis soft decoder improves throughput by 257x with the trade off of a higher byte error rate of 3.52% compared to the state-of-the-art. Furthermore, we use the faster speed of our algorithm to explore more design options. We show that read densities of 0.33 bits/base can be achieved, which is 4x larger than prior MSA-based decoders. We also compare RNA to DNA, and find that RNA has 85% as many error free reads as compared to DNA. Availability and implementationSource code for our soft decoder and data used to generate figures is available publicly in the Github repository https://github.com/dna-storage/hedges-soft-decoder (10.5281/zenodo.11454877). All raw FAST5/FASTQ data is available at 10.5281/zenodo.11985454 and 10.5281/zenodo.12014515. Contackvolkel@ncsu.edu or jtuck@ncsu.edu

synthetic biology↗

bioRxiv2024

Uncalled4 improves nanopore DNA and RNA modification detection via fast and accurate signal alignment

Nanopore signal analysis enables detection of nucleotide modifications from native DNA and RNA sequencing, providing both accurate genetic/transcriptomic and epigenetic information without additional library preparation. Presently, only a limited set of modifications can be directly basecalled (e.g. 5-methylcytosine), while most others require exploratory methods that often begin with alignment of nanopore signal to a nucleotide reference. We present Uncalled4, a toolkit for nanopore signal alignment, analysis, and visualization. Uncalled4 features an efficient banded signal alignment algorithm, BAM signal alignment file format, statistics for comparing signal alignment methods, and a reproducible de novo training method for k-mer-based pore models, revealing potential errors in ONTs state-of-the-art DNA model. We apply Uncalled4 to RNA 6-methyladenine (m6A) detection in seven human cell lines, identifying 26% more modifications than Nanopolish using m6Anet, including in several genes where m6A has known implications in cancer. Uncalled4 is available open-source at github.com/skovaka/uncalled4.

bioinformatics↗

bioRxiv2023

Evaluating the mouse neural precursor line, SN4741, as a suitable proxy for midbrain dopaminergic neurons

To overcome the ethical and technical limitations of in vivo human disease models, the broader scientific community frequently employs model organism-derived cell lines to investigate of disease mechanisms, pathways, and therapeutic strategies. Despite the widespread use of certain in vitro models, many still lack contemporary genomic analysis supporting their use as a proxy for the affected human cells and tissues. Consequently, it is imperative to determine how accurately and effectively any proposed biological surrogate may reflect the biological processes it is assumed to model. One such cellular surrogate of human disease is the established mouse neural precursor cell line, SN4741, which has been used to elucidate mechanisms of neurotoxicity in Parkinson disease for over 25 years. Here, we are using a combination of classic and contemporary genomic techniques - karyotyping, RT-qPCR, single cell RNA-seq, bulk RNA-seq, and ATAC-seq - to characterize the transcriptional landscape, chromatin landscape, and genomic architecture of this cell line, and evaluate its suitability as a proxy for midbrain dopaminergic neurons in the study of Parkinson disease. We find that SN4741 cells possess an unstable triploidy and consistently exhibits low expression of dopaminergic neuron markers across assays, even when the cell line is shifted to the non-permissive temperature that drives differentiation. The transcriptional signatures of SN4741 cells suggest that they are maintained in an undifferentiated state at the permissive temperature and differentiate into immature neurons at the non-permissive temperature; however, they may not be dopaminergic neuron precursors, as previously suggested. Additionally, the chromatin landscapes of SN4741 cells, in both the differentiated and undifferentiated states, are not concordant with the open chromatin profiles of ex vivo, mouse E15.5 forebrain- or midbrain-derived dopaminergic neurons. Overall, our data suggest that SN4741 cells may reflect early aspects of neuronal differentiation but are likely not a suitable a proxy for dopaminergic neurons as previously thought. The implications of this study extend broadly, illuminating the need for robust biological and genomic rationale underpinning the use of in vitro models of molecular processes.

genetics↗

bioRxiv2022

The complete sequence of a human Y chromosome

The human Y chromosome has been notoriously difficult to sequence and assemble because of its complex repeat structure including long palindromes, tandem repeats, and segmental duplications1-3. As a result, more than half of the Y chromosome is missing from the GRCh38 reference sequence and it remains the last human chromosome to be finished4, 5. Here, the Telomere-to-Telomere (T2T) consortium presents the complete 62,460,029 base pair sequence of a human Y chromosome from the HG002 genome (T2T-Y) that corrects multiple errors in GRCh38-Y and adds over 30 million base pairs of sequence to the reference, revealing the complete ampliconic structures of TSPY, DAZ, and RBMY gene families; 41 additional protein-coding genes, mostly from the TSPY family; and an alternating pattern of human satellite 1 and 3 blocks in the heterochromatic Yq12 region. We have combined T2T-Y with a prior assembly of the CHM13 genome4 and mapped available population variation, clinical variants, and functional genomics data to produce a complete and comprehensive reference sequence for all 24 human chromosomes.

genomics↗

bioRxiv2022

Modbamtools: Analysis of single-molecule epigenetic data for long-range profiling, heterogeneity, and clustering

The advent of long-read sequencing methods provides new opportunities for profiling the epigenome - especially as the methylation signature comes for "free" when native DNA is sequenced on either Oxford Nanopore or Pacific Biosciences instruments. However, we lack tools to visualize and analyze data generated from these new sources. Recent efforts from the GA4GH consortium have standardized methods to encode modification location and probabilities in the BAM format. Leveraging this standard format, we developed a technology-agnostic tool, modbamtools to visualize, manipulate and compare base modification/methylation data in a fast and robust way. modbamtools can produce high quality, interactive, and publication-ready visualizations as well as provide modules for downstream analysis of base modifications. Modbamtools comprehensive manual and tutorial can be found at https://rrazaghi.github.io/modbamtools/.

bioinformatics↗

bioRxiv2021

Epigenetic Patterns in a Complete Human Genome

The completion of the first telomere-to-telomere human genome, T2T-CHM13, enables exploration of the full epigenome, removing limitations previously imposed by the missing reference sequence. Existing epigenetic studies omit unassembled and unmappable genomic regions (e.g. centromeres, pericentromeres, acrocentric chromosome arms, subtelomeres, segmental duplications, tandem repeats). Leveraging the new assembly, we were able to measure enrichment of epigenetic marks with short reads using k-mer assisted mapping methods. This granted array-level enrichment information to characterize the epigenetic regulation of these satellite repeats. Using nanopore sequencing data, we generated base level maps of the most complete human methylome ever produced. We examined methylation patterns in satellite DNA and revealed organized patterns of methylation along individual molecules. When exploring the centromeric epigenome, we discovered a distinctive dip in centromere methylation consistent with active sites of kinetochore assembly. Through long-read chromatin accessibility measurements (nanoNOMe) paired to CUT&RUN data, we found the hypomethylated region was extremely inaccessible and paired to CENP-A/B binding. With long-reads we interrogated allele-specific, longrange epigenetic patterns in complex macro-satellite arrays such as those involved in X chromosome inactivation. Using the single molecule measurements we can clustered reads based on methylation status alone distinguishing epigenetically heterogeneous and homogeneous areas. The analysis provides a framework to investigate the most elusive regions of the human genome, applying both long and short-read technology to grant new insights into epigenetic regulation.

genomics↗

bioRxiv2018

Heritability enrichment in open chromatin reveals cortical layer contributions to schizophrenia

Genome-wide association studies have implicated thousands of non-coding variants across human phenotypes. However, they cannot directly inform the cellular context in which disease-associated variants act. Here, we use open chromatin profiles from discrete mouse cell populations to address this challenge. We applied stratified linkage disequilibrium score regression and evaluated heritability enrichment in 64 genome-wide association studies, emphasizing schizophrenia. We provide evidence that mouse-derived human open chromatin profiles can serve as powerful proxies for difficult to obtain human cell populations, facilitating the illumination of common disease heritability enrichment across an array of human phenotypes. We demonstrate signatures from discrete subpopulations of cortical excitatory and inhibitory neurons are significantly enriched for schizophrenia heritability with maximal enrichment in discrete cortical layer V excitatory neurons. We also show differences between schizophrenia and bipolar disorder are concentrated in excitatory neurons in layers II-III, IV, V as well as the dentate gyrus. Finally, we use these data to fine-map variants in 177 schizophrenia loci, nominating variants in 104/177 loci, and place them in the cellular context where they may modulate risk.

genetics↗

bioRxiv2018

Parkinson-associated SNCA enhancer variants revealed by open chromatin in mouse dopamine neurons

The progressive loss of midbrain (MB) dopaminergic (DA) neurons defines the motor features of Parkinson disease (PD) and modulation of risk by common variation in PD has been well established through GWAS. Anticipating that a fraction of PD-associated genetic variation mediates their effects within this neuronal population, we acquired open chromatin signatures of purified embryonic mouse MB DA neurons. Correlation with >2,300 putative enhancers assayed in mice reveals enrichment for MB cis-regulatory elements (CRE), data reinforced by transgenic analyses of six additional sequences in zebrafish and mice. One CRE, within intron 4 of the familial PD gene SNCA, directs reporter expression in catecholaminergic neurons of transgenic mice and zebrafish. Sequencing of this CRE in 986 PD patients and 992 controls reveals two common variants associated with elevated PD risk. To assess potential mechanisms of action, we screened >20,000 DNA interacting proteins and identify a subset whose binding is impacted by these enhancer variants. Additional genotyping across the SNCA locus identifies a single PD-associated haplotype, containing the minor alleles of both of the aforementioned PD-risk variants. Our work posits a model for how common variation at SNCA may modulate PD risk and highlights the value of cell context-dependent guided searches for functional non-coding variation.

genetics↗