Biology subjects

Tian, S. Z.

Publications and source records attributed to Tian, S. Z..

7 recordsLinked to original sources

bioRxiv2022

MCIBox: A Toolkit for Single-molecule Multi-way Chromatin Interaction Visualization and Micro-Domains Identification

The emerging ligation-free three-dimensional (3D) genome mapping technologies can identify multiplex chromatin interactions with single-molecule precision. These technologies offer new insight into high-dimensional chromatin organization and gene regulation, but also introduce new challenges in data visualization and analysis. To overcome these challenges, we developed MCIBox, a toolkit for Multi-way Chromatin Interaction (MCI) analysis, including a visualization tool and a platform for identifying micro-domains with clustered single-molecule chromatin complexes. MCIBox is based on various clustering algorithms integrated with dimensionality reduction methods that can display multiplex chromatin interactions at single-molecule level, allowing users to explore chromatin extrusion patterns and super-enhancers regulation modes in transcription, and to identify single-molecule chromatin complexes that are clustered into micro-domains. Furthermore, MCIBox incorporates a two-dimensional kernel density estimation algorithm to identify micro-domains boundaries automatically. These micro-domains were stratified with distinctive signatures of transcription activity and contained different cell cycle associated genes. MCIBox could potentially distinguish the specificity of single-molecule chromatin interaction patterns in various phases of a cell cycle or cell types.

genomics↗

bioRxiv2022

Pore-C Simultaneously Captures Genome-wide Multi-way Chromatin Interaction and Associated DNA Methylation Status in Arabidopsis

In the past decade, genome-wide characterization of the three-dimensional chromatin structure in plants using high-throughput methods has greatly advanced our knowledge in plant genome architecture (Liu and Weigel, 2015; Ouyang et al., 2020). However, due to the limitation of Illumina short-read sequencing, the genome-wide contact map obtained by Hi-C/ChIA-PET is pairwise, and the multi-way interaction can only be inferred from the two-way data. To directly capture multi-way interaction in Arabidopsis, we applied a long-read-based method called Pore-C that directly sequences the DNA fragments joined by proximity-based ligation (Ulahannan et al., 2019).

molecular biology↗

bioRxiv2020

Targeting nuclear pore protein, NUP210, reduces metastasis through heterochromatin-mediated silencing of mechanosensitive genes

Mechanical signals from the extracellular microenvironment have been implicated in tumor and metastatic progression. Here, we identified nucleoporin NUP210 as a metastasis susceptibility gene for human estrogen receptor positive (ER+) breast cancer and a cellular mechanosensor. Nup210 depletion suppresses lung metastasis in mouse models of breast cancer. Mechanistically, NUP210 interacts with LINC complex protein SUN2 which connects the nucleus to the cytoskeleton. In addition, the NUP210/SUN2 complex interacts with chromatin via the short isoform of BRD4 and histone H3.1/H3.2 at the nuclear periphery. In Nup210 knockout cells, mechanosensitive genes accumulate H3K27me3 heterochromatin modification, mediated by the polycomb repressive complex 2 and differentially reposition within the nucleus. Transcriptional repression in Nup210 knockout cells results in defective mechanotransduction and focal adhesion necessary for their metastatic capacity. Our study provides a new insight into the role of nuclear pore protein in cellular mechanosensation and metastasis.

cancer biology↗

bioRxiv2019

Multiplex chromatin interaction analysis by signal processing and statistical algorithms

The single-molecule multiplex chromatin interaction data generated by emerging non-ligation-based 3D genome mapping technologies provide novel insights into high dimensional chromatin organization, yet introduce new computational challenges. We developed MIA-Sig (https://github.com/TheJacksonLaboratory/mia-sig.git), an algorithmic framework to de-noise the data, assess the statistical significance of chromatin complexes, and identify topological domains and inter-domain contacts. On chromatin immunoprecipitation (ChIP)-enriched data, MIA-Sig can clearly distinguish the protein-associated interactions from the non-specific topological domains.

genomics↗

bioRxiv2019

ChIA-DropBox: a novel analysis and visualization pipeline for multiplex chromatin interactions

ChIA-Drop is a new experimental method for mapping multiplex chromatin interactions with single-molecule precision by barcoding chromatin complexes inside microfluidics droplets, followed by pooled DNA sequencing. The chromatin DNA reads with the same droplet-specific barcodes are inferred to be derived from the same chromatin interaction complex. Here, we describe an integrated computational pipeline, named ChIA-DropBox, that is specifically designed for reconstructing chromatin reads in each droplet and refining multiplex chromatin complexes from raw ChIA-Drop sequencing reads, and then visualizing the results. First, ChIA-DropBox maps and filters sequencing reads, and then reconstructs the \"chromatin droplets\" by parsing the barcode sequences and grouping together chromatin reads with the same barcode. Based on the concept of chromosome territories that most chromatin interactions take place within the same chromosome, potential mixing up of chromatin complexes derived from different chromosomes could be readily identified and separated. Accordingly, ChIA-DropBox refines these \"chromatin droplets\" into purely intra-chromosomal chromatin complexes, ready for downstream analysis. For visualization, ChIA-DropBox converts the ChIA-Drop data to pairwise format and automatically generates input files for viewing 2D contact maps in Juicebox and viewing loops in BASIC Browser. Finally, ChIA-DropBox introduces a new browser, named ChIA-View, for interactive visualization of multiplex chromatin interactions.

bioinformatics↗

bioRxiv2018

ChIA-PIPE: A fully automated pipeline for ChIA-PET data analysis and visualization

ChIA-PET enables the genome-wide discovery of chromatin interactions involving specific protein factors, with base-pair resolution. Interpreting ChIA-PET data depends on having a robust analytic pipeline. Here, we introduce ChIA-PIPE, a fully automated pipeline for ChIA-PET data processing, quality assessment, analysis, and visualization. ChIA-PIPE performs linker filtering, read mapping, peak calling, loop calling, chromatin-contact-domain calling, and can resolve allele-specific peaks and loops. ChIA-PIPE also automates quality-control assessment for each dataset. Furthermore, ChIA-PIPE generates input files for visualizing 2D contact maps with Juicebox and HiGlass, and provides a new dockerized visualization tool for high-resolution, browser-based exploration of peaks and loops. With minimal adjusting, ChIA-PIPE can also be suited for the analysis of other related chromatin-mapping data.

bioinformatics↗

bioRxiv2018

Multiplex Chromatin Interaction Analysis with Single-Molecule Precision

We describe a microfluidics-based strategy for genome-wide analysis of multiplex chromatin interactions with single-molecule precision. In multiplex chromatin interaction analysis (multi-ChIA), individual chromatin complexes are partitioned into droplets that contain a gel bead with unique DNA barcode, in which tethered chromatin DNA fragments are barcoded and amplified for sequencing and mapping to demarcate chromatin contacts. Thus, multi-ChIA has the unprecedented ability to uncover multiplex chromatin interactions at single-molecule level, which has been impossible using previous methods that rely on analyzing pairwise contacts via proximity ligation. We demonstrate that multiplex chromatin interactions predominantly contribute to topologically associated domains, and clusters of gene promoters and enhancers provide a fundamental topological framework for co-transcriptional regulation.

genomics↗