Biology subjects

Clock, B.

Publications and source records attributed to Clock, B..

3 recordsLinked to original sources

bioRxiv2022

Widespread Increase in Enhancer-Promoter Interactions during Developmental Enhancer Activation in Mammals

Remote enhancers are thought to interact with their target promoters via physical proximity, yet the importance of this proximity for enhancer function remains unclear. Here, we investigate the 3D conformation of enhancers during mammalian development by generating high-resolution tissue-resolved contact maps for nearly a thousand enhancers with characterized in vivo activities in ten murine embryonic tissues. 61% of developmental enhancers bypass their neighboring genes, which are often marked by promoter CpG methylation. The majority of enhancers display tissue-specific 3D conformations, and both enhancer-promoter and enhancer-enhancer interactions are moderately but consistently increased upon enhancer activation in vivo. Less than 14% of enhancer-promoter interactions form stably across tissues; however, these invariant interactions form in the absence of the enhancer and are likely mediated by adjacent CTCF binding. Our results highlight the general significance of enhancer- promoter physical proximity for developmental gene activation in mammals.

genomics↗

bioRxiv2022

Deciphering the Evolutionary History of Complex Rearrangements in Head and Neck Cancer Patients Using Multi-Omic Approach

Despite the large efforts in international cancer genome consortium studies, there are still a large proportion of tumors with complex genomic rearrangement often remained without a clinically relevant molecular characterization. Integration of multi-omic data helps elucidating evolutionary history of such cases and identifying predictive molecular markers. Here we present the findings of our proof-of-principle study that investigated the evolutionary history of complex rearrangements in primary head and neck tumor genomes integrating long-read whole-genome, Hi-C, and RNA sequencing. We report a HPV-positive case with development of complex genomic rearrangements tracing back to HPV-mediated genomic instability and a HPV-negative case with an enhancer hi-jacking in a region of chromothripsis predicted to co-occur with a neoloop and a super-enhancer. These structural alterations resulted in overexpression of the oncogenes CCND1 and ALK, respectively, validated with immunohistochemistry assay. Furthermore, we introduce a novel analytic approach utilizing long-read whole-genome data distinguishing somatic mutations before and after structural variants. Our findings highlight the need for multi-modal sequencing strategies to increase our understanding of cancer evolution and rare biomarkers in poorly understood cancers.

genomics↗

bioRxiv2020

DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution

Mammalian brain cells are remarkably diverse in gene expression, anatomy, and function, yet the regulatory DNA landscape underlying this extensive heterogeneity is poorly understood. We carried out a comprehensive assessment of the epigenomes of mouse brain cell types by applying single nucleus DNA methylation sequencing to profile 110,294 nuclei from 45 regions of the mouse cortex, hippocampus, striatum, pallidum, and olfactory areas. We identified 161 cell clusters with distinct spatial locations and projection targets. We constructed taxonomies of these epigenetic types, annotated with signature genes, regulatory elements, and transcription factors. These features indicate the potential regulatory landscape supporting the assignment of putative cell types, and reveal repetitive usage of regulators in excitatory and inhibitory cells for determining subtypes. The DNA methylation landscape of excitatory neurons in the cortex and hippocampus varied continuously along spatial gradients. Using this deep dataset, an artificial neural network model was constructed that precisely predicts single neuron cell-type identity and brain area spatial location. Integration of high-resolution DNA methylomes with single-nucleus chromatin accessibility data allowed prediction of high-confidence enhancer-gene interactions for all identified cell types, which were subsequently validated by cell-type-specific chromatin conformation capture experiments. By combining multi-omic datasets (DNA methylation, chromatin contacts, and open chromatin) from single nuclei and annotating the regulatory genome of hundreds of cell types in the mouse brain, our DNA methylation atlas establishes the epigenetic basis for neuronal diversity and spatial organization throughout the mouse brain.

genomics↗