A5041969204- Genomics and Chromatin Dynamics
- RNA Research and Splicing
- Epigenetics and DNA Methylation
- Single-cell and spatial transcriptomics
- RNA modifications and cancer
- Chromosomal and Genetic Variations
- Gene expression and cancer classification
- Machine Learning in Bioinformatics
- Genomics and Phylogenetic Studies
- Genetic Mapping and Diversity in Plants and Animals
- Pluripotent Stem Cells Research
- Algorithms and Data Compression
- RNA and protein synthesis mechanisms
- CRISPR and Genetic Engineering
- Genomic variations and chromosomal abnormalities
- Neural dynamics and brain function
- Cardiac Fibrosis and Remodeling
- Neurogenesis and neuroplasticity mechanisms
- Genetics and Neurodevelopmental Disorders
- RNA regulation and disease
- Cancer-related gene regulation
- Plant Molecular Biology Research
- Ubiquitin and proteasome pathways
- Cell Image Analysis Techniques
- Gene Regulatory Network Analysis
Cleveland Clinic
2018-2025
Cleveland Clinic Lerner College of Medicine
2020
American Rock Mechanics Association
2019
Washington State University Spokane
2018
Washington State University
2015-2016
Hi-C and chromatin immunoprecipitation (ChIP) have been combined to identify long-range interactions genome-wide at reduced cost enhanced resolution, but extracting information from the resulting datasets has challenging. Here we describe a computational method, MAPS, Model-based Analysis of PLAC-seq HiChIP, process data such experiments interactions. MAPS adopts zero-truncated Poisson regression framework explicitly remove systematic biases in HiChIP datasets, then uses normalized contact...
Abstract Single-cell Hi-C (scHi-C) analysis has been increasingly used to map chromatin architecture in diverse tissue contexts, but computational tools define loops at high resolution from scHi-C data are still lacking. Here, we describe Single-Nucleus Analysis Pipeline for (SnapHiC), a method that can identify and accuracy data. Using 742 mouse embryonic stem cells, benchmark SnapHiC against number of developed mapping interactions bulk Hi-C. We further demonstrate its use by analyzing...
Significance Development of cortical areas begins in stem cells through the action morphogens controlling graded expression transcription factors (TFs). Here, we have systematically identified TFs and gene regulatory elements (REs) that together control regional pattering progenitor zone; these data led us to propose a regionalization TF network. To identify REs active this network, performed chromatin immunoprecipitation followed by sequencing (ChIP-seq) chromatin-looping conformation...
Hi-C experiments have been widely adopted to study chromatin spatial organization, which plays an essential role in genome function. We recently identified frequently interacting regions (FIREs) and found that they are closely associated with cell-type-specific gene regulation. However, computational tools for detecting FIREs from data still lacking. In this work, we present FIREcaller, a stand-alone, user-friendly R package data. FIREcaller takes raw contact matrices as input, performs...
Current pooled CRISPR screens for cis-regulatory elements (CREs), based on transcriptional output changes, are typically limited to characterizing CREs of only one gene. Here, we describe CRISPRpath, a scalable screening strategy parallelly genes linked the same biological pathway and converging phenotypes. We demonstrate ability CRISPRpath simultaneously identifying functional enhancers six in 6-thioguanine–induced DNA mismatch repair using both interference (CRISPRi) nuclease (CRISPRn)...
Single cell Hi-C (scHi-C) technologies enable the study of chromatin spatial organization directly from complex tissues at single resolution. However, identification loops cells is challenging, largely due to extremely sparse data. Our recently developed SnapHiC pipeline provides first tool map scHi-C data, but it computationally intensive. Here we introduce SnapHiC2, which adapts a sliding window approximation when imputing missing contacts in each and reduces both memory usage...
Abstract While a rich set of putative cis -regulatory sequences involved in mouse fetal development have been annotated recently on the basis chromatin accessibility and histone modification patterns, delineating their role developmentally regulated gene expression continues to be challenging. To fill this gap, here we mapped contacts between promoters distal across genome seven tissues six developmental stages forebrain. We identified 248,620 long-range interactions centered at 14,138...
Abstract Lineage-specific epigenomic changes during human corticogenesis have previously remained elusive due to challenges with tissue heterogeneity and sample availability. Here, we analyze cis-regulatory chromatin interactions, open regions, transcriptomes for radial glia, intermediate progenitor cells, excitatory neurons, interneurons isolated from mid-gestational brain samples. We show that looping underlies transcriptional regulation lineage-specific genes, transcription factor motifs,...
Abstract Single cell Hi-C (scHi-C) analysis has been increasingly used to map the chromatin architecture in diverse tissue contexts, but computational tools define contacts at high resolution from scHi-C data are still lacking. Here, we describe SnapHiC, a method that can identify loops and accuracy data. We benchmark SnapHiC against HiCCUPS, common tool for mapping bulk data, using 742 mouse embryonic stem cells. further demonstrate its utility by analyzing single-nucleus methyl-3C-seq...
The three-dimensional organization of chromatin plays a critical role in gene regulation. Recently developed technologies, such as HiChIP and proximity ligation-assisted ChIP-Seq (PLAC-seq) (hereafter referred to HP for brevity), can measure chromosome spatial by interrogating interactions mediated protein interest. While offering cost-efficiency over genome-wide unbiased high-throughput conformation capture (Hi-C) data, data remain sparse at kilobase (Kb) resolution with the current...
Abstract Hi-C experiments have been widely adopted to study chromatin spatial organization, which plays an essential role in genome function. We recently identified frequently interacting regions (FIREs) and found that they are closely associated with cell-type-specific gene regulation. However, computational tools for detecting FIREs from data still lacking. In this work, we present FIREcaller, a stand-alone, user-friendly R package data. FIREcaller takes raw contact matrices as input,...
ABSTRACT Transcription factors (TFs) bind combinatorially to genomic cis-regulatory elements (cREs), orchestrating transcription programs. While studies of chromatin state and chromosomal interactions have revealed dynamic neurodevelopmental cRE landscapes, parallel understanding the underlying TF binding lags. To elucidate combinatorial TF-cRE driving mouse basal ganglia development, we integrated ChIP-seq for twelve TFs, H3K4me3-associated enhancer-promoter interactions, transcriptional...
Identifying conserved regions in protein sequences is a fundamental operation that recurrent numerous sequence-driven analysis pipelines. It used as way to decode domain-rich within proteins, compute clusters, annotate with function, and evolutionary relationships among sequences. Current approaches clustering annotating based on depend either prior knowledge of domains or computing pairwise sequence similarity, which not feasible for very large collections In this paper we present new...
Abstract Hi-C and chromatin immunoprecipitation (ChIP) have been combined to identify long-range interactions genome-wide at reduced cost enhanced resolution, but extracting the information from resulting datasets has challenging. Here we describe a computational method, MAPS, Model-based Analysis of PLAC-seq HiChIP, process data such experiments interactions. MAPS adopts zero-truncated Poisson regression framework explicitly remove systematic biases in HiChIP datasets, then uses normalized...
Background Identifying conserved regions in protein sequences is a fundamental operation, occurring numerous sequence-driven analysis pipelines. It used as way to decode domain-rich within proteins, compute clusters, annotate sequence function, and evolutionary relationships among sequences. A number of approaches exist for identifying characterizing families based on their domains, because domains represent portions sequence, the primary computation involved family characterization...