Biology subjects

Dixon, J.

Publications and source records attributed to Dixon, J..

22 records · Page 2Linked to original sources

bioRxiv2018

HiCluster: A Robust Single-Cell Hi-C Clustering Method Based on Convolution and Random Walk

3D genome structure plays a pivotal role in gene regulation and cellular function. Single-cell analysis of genome architecture has been achieved using imaging and chromatin conformation capture methods such as Hi-C. To study variation in chromosome structure between different cell types, computational approaches are needed that can utilize sparse and heterogeneous single-cell Hi-C data. However, few methods exist that are able to accurately and efficiently cluster such data into constituent cell types. Here, we describe HiCluster, a single-cell clustering algorithm for Hi-C contact matrices that is based on imputations using linear convolution and random walk. Using both simulated and real data as benchmarks, HiCluster significantly improves clustering accuracy when applied to low coverage Hi-C datasets compared to existing methods. After imputation by HiCluster, structures similar to topologically associating domains (TADs) could be identified within single cells, and their consensus boundaries among cells were enriched at the TAD boundaries observed in bulk samples. In summary, HiCluster facilitates visualization and comparison of single-cell 3D genomes.\n\nAvailabilityhttps://github.com/zhoujt1994/HiCluster.git

bioinformatics↗

bioRxiv2018

cis-Regulatory Chromatin Contacts in Neural Cells Reveal Contributions of Genetic Variants to Complex Neurological Disorders

Mutations in gene regulatory elements have been associated with a wide range of complex neurological disorders. However, due to their inherent cell type-specificity and difficulties in characterizing their regulatory targets, our ability to identify causal genetic variants has remained limited. To address these constraints, we perform integrative analysis of chromatin interactions using promoter capture Hi-C (pcHi-C), open chromatin regions using ATAC-seq, and transcriptomes using RNA-seq in four functionally distinct neural cell types: iPSC-induced excitatory neurons and lower motor neurons, iPSC-derived hippocampal dentate gyrus (DG)-like neurons, and primary astrocytes. We identify hundreds of thousands of long-range cis interactions between promoters and distal promoter-interacting regions (PIRs), enabling us to link regulatory elements to their target genes and reveal putative pathways that are dysregulated in disease. We validate several novel PIRs using CRISPR techniques in human excitatory neurons, demonstrating that CDK5RAP3, STRAP, and DRD2 are transcriptionally regulated by physically linked enhancers. Finally, we show that physical chromatin interactions mediate genetic interactions in autism spectrum disorder (ASD). Our study illustrates how characterizing the 3D epigenome elucidates novel regulatory relationships in the central nervous system (CNS), shedding light on previously unknown functions for noncoding variants in complex neurological disorders.

genomics↗

bioRxiv2017

An Integrative Framework For Detecting Structural Variations In Cancer Genomes

Structural variants can contribute to oncogenesis through a variety of mechanisms, yet, despite their importance, the identification of structural variants in cancer genomes remains challenging. Here, we present an integrative framework for comprehensively identifying structural variation in cancer genomes. For the first time, we apply next-generation optical mapping, high-throughput chromosome conformation capture (Hi-C), and whole genome sequencing to systematically detect SVs in a variety of cancer cells.\n\nUsing this approach, we identify and characterize structural variants in up to 29 commonly used normal and cancer cell lines. We find that each method has unique strengths in identifying different classes of structural variants and at different scales, suggesting that integrative approaches are likely the only way to comprehensively identify structural variants in the genome. Studying the impact of the structural variants in cancer cell lines, we identify widespread structural variation events affecting the functions of non-coding sequences in the genome, including the deletion of distal regulatory sequences, alteration of DNA replication timing, and the creation of novel 3D chromatin structural domains.\n\nThese results underscore the importance of comprehensive structural variant identification and indicate that non-coding structural variation may be an underappreciated mutational process in cancer genomes.

genomics↗

bioRxiv2017

Preservation of Chromatin Organization after Acute Loss of CTCF in Mouse Embryonic Stem Cells

The CCCTC-binding factor (CTCF) is widely regarded as a key player in chromosome organization in mammalian cells, yet direct assessment of the impact of loss of CTCF on genome architecture has been difficult due to its essential role in cell proliferation and early embryogenesis. Here, using auxin-inducible degron techniques to acutely deplete CTCF in mouse embryonic stem cells, we show that cell growth is severely slowed yet chromatin organization remains largely intact after loss of CTCF. Depletion of CTCF reduces interactions between chromatin loop anchors, diminishes occupancy of cohesin complex genome-wide, and slightly weakens topologically associating domain (TAD) structure, but the active and inactive chromatin compartments are maintained and the vast majority of TAD boundaries persist. Furthermore, transcriptional regulation and histone marks associated with enhancers are broadly unchanged upon CTCF depletion. Our results suggest CTCF-independent mechanisms in maintenance of chromatin organization.

genomics↗