Biology subjects

An, L.

Publications and source records attributed to An, L..

7 recordsLinked to original sources

bioRxiv2018

Substrate-assisted Enzymatic Formation of Lysinoalanine in Duramycin

Duramycin is a heavily post-translationally modified peptide that binds phosphatidylethanolamine. It has been investigated as an antibiotic, inhibitor of viral entry, therapeutic for cystic fibrosis, and tumor and vasculature imaging agent. Duramycin contains a {beta}-hydroxylated Asp (Hya) and four macrocycles, including an essential lysinoalanine (Lal) crosslink. The mechanism of Lal formation is not known. We here show that Lal is installed stereospecifically by DurN via addition of Lys19 to a dehydroalanine. The structure of DurN reveals an unusual dimer with a new fold. Surprisingly, in the structure of duramycin bound to DurN, no residues of the enzyme are near the Lal. Instead, Hya15 of the substrate makes interactions with Lal suggesting it acts as a base to deprotonate Lys19 during catalysis. Biochemical data suggest that DurN preorganizes the reactive conformation of the substrate, such that the Hya15 of the substrate can serve as the catalytic base for Lal formation.

biochemistry↗

bioRxiv2018

Hierarchical Domain Structure Reveals the Divergence of Activity among TADs and Boundaries

The spatial organization of chromatin in the nucleus has been implicated in many aspects of regulated gene expression. Maps of high frequency interactions between different segments of chromatin have revealed Topologically Associating Domains (TADs), within which most of the regulatory interactions are thought to occur. Recent studies have shown that TADs are not homogeneous structural units, but rather they appear to be organized into a hierarchy. However, precise identification of hierarchical TAD structures remains a challenge. We present OnTAD, an Optimized Nested TAD caller from Hi-C data, to identify hierarchical TADs. Compared to existing methods, OnTAD has significantly improved accuracy and running speed. Results from OnTAD reveal new biological insights on the role of different TAD levels, boundary usage in gene regulation, the loop extrusion model, and compartmental domains. The software and documentation for OnTAD are available at: https://github.com/anlin00007/OnTAD

bioinformatics↗

bioRxiv2018

Snapshot: clustering and visualizing epigenetic history during cell differentiation

Epigenetic modification of chromatin plays a pivotal role in regulating gene expression during cell differentiation. The scale and complexity of epigenetic data pose significant challenges for biologists to identify the regulatory events controlling cell differentiation. Here, we present a new method, called Snapshot, that uses epigenetic data to generate a hierarchical visualization for DNA regions with epigenetic features segregating along any given cell differentiation hierarchy of interest. Different hierarchies of cell types may be used to highlight the epigenetic history specific to any particular cell lineage. We demonstrate the utility of Snapshot using data from the VISION project, an international project for ValIdated Systematic IntegratiON of epigenomic data in mouse and human hematopoiesis.\n\nAvailability and implementation: https://github.com/guanjue/snapshot

bioinformatics↗

bioRxiv2018

A stable mode of bookmarking by TBP recruits RNA Polymerase II to mitotic chromosomes

How a cell maintains transcriptional fidelity across mitosis has remained an enduring mystery in biology. One challenge arises during mitosis when chromatin becomes condensed and transcription is shut off. How do the daughter cells re-establish the original transcription program? Here, we report that the TATA-binding protein (TBP), a key component of the core transcriptional machinery, remains bound globally to active promoters in ES cells during mitosis. Using live-cell single-molecule imaging, we observed that TBP mitotic binding is highly stable, with an average residence time of minutes. This stable binding is in stark contrast to typical TFs with residence times of seconds. To test the functional effect of mitotic TBP binding, we used a drug-inducible degron system and found that TBP promotes the association of RNA Polymerase II with mitotic chromosomes, and facilitates transcriptional reactivation following mitosis. These results suggest that the core transcriptional machinery maintains global transcriptional memory during mitosis.

molecular biology↗

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

HiCPlus: Resolution Enhancement of Hi-C interaction heatmap

MotivationThe Hi-C technology has become an efficient tool to measure the spatial organization of the genome. With the recent advance of 1Kb resolution Hi-C experiment, some of the essential regulatory features have been uncovered. However, most available Hi-C datasets are in coarse-resolution due to the extremely high cost for generating high-resolution data. Therefore, a computational method to maximum the usage of the current available Hi-C data is urgently desired.\n\nResultsInspired by the super-resolution image technique, we develop a computational approach to impute the high-resolution Hi-C data from low-resolution Hi-C data using the deep convolutional neural network. We hypothesize that the Hi-C interaction heatmap contains the repeating features, and develop an end-to-end framework to map these features from low-resolution Hi-C heatmap to high-resolution Hi-C heatmap at the feature level. Our approach successfully reconstructs the high-resolution Hi-C interaction map from the low-resolution counterpart, which also proves that the Hi-C interaction matrix is a combination of the regional features. Besides, our approach is highly expandable, and we can also increase prediction accuracy by incorporating ChIA-PET data.\n\nAvailabilitySource code is publicly available at https://github.com/zhangyan32/HiCPlus\n\nContactjtang@cse.sc.edu, fyue@hmc.psu.edu

bioinformatics↗

bioRxiv2017

The 3D Genome Browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactions

Recent advent of 3C-based technologies such as Hi-C and ChIA-PET provides us an opportunity to explore chromatin interactions and 3D genome organization in an unprecedented scale and resolution. However, it remains a challenge to visualize chromatin interaction data due to its size and complexity. Here, we introduce the 3D Genome Browser (http://3dgenome.org), which allows users to conveniently explore both publicly available and their own chromatin interaction data. Users can also seamlessly integrate other \"omics\" data sets, such as ChIP-Seq and RNA-Seq for the same genomic region, to gain a complete view of both regulatory landscape and 3D genome structure for any given gene. Finally, our browser provides multiple methods to link distal cis-regulatory elements with their potential target genes, including virtual 4C, ChIA-PET, Capture Hi-C and cross-cell-type correlation of proximal and distal DNA hypersensitive sites, and therefore represents a valuable resource for the study of gene regulation in mammalian genomes.

bioinformatics↗