Applying Bioinformatics to Research in Immune, Muscle, and Bone Diseases

National Institute Of Arthritis And Musculoskeletal And Skin Diseases

Investigators

Linked publications & trials

Abstract

The Biodata Mining and Discovery Section projects are: - Investigation of genetic causes for Systemic Lupus Erythematous through whole genome sequencing - Somatic mutation analysis in Keratoacanthoma - Mutation analysis in the NIAMS WES cohort - Mutation Analysis in patients with inflammatory pustular diseases enrolled in anakinra study - Mutation analysis in patients with early onset Merkel cell carcinoma - Evaluation of new single cell and sequencing technology - Investigation of the mechanism of age-resistant genuine quiescent stem-cell state - Investigation of epigenetic modules governing epidermal homeostasis - The effect of Jakinibs on gene expression in Lupus patient whole blood - Function of microRNA-221/222 in regulating gut homeostasis - Role of hepatic BMAL1 and FXR signaling in feeding-induced resistance to acute lethal sepsis - DLX3 tumor suppressive function in progression of cutaneous squamous cell carcinoma - Role of FoxO in maintaining muscle stem-cell quiescent stage until geriatric age - The regulation of skeletal muscle stem cell function by EZH 1 - Exploration on the lineage specification through epigenetic regulation of Pax 7 - Analysis of a muscle-specific enhancer RNA via ATAC-seq & ChIP-seq - Study on the functions of Psat1 in MuSCs activation - Development of a scRNA-seq pipeline to analyze circulating human neutrophils - Gene expression profiles of cancer cells treated with copper and disulfiram - Investigation of U12-type intron containing genes in Lupus cells - Role of BACH2 in the transcriptional and epigenetic programs of stem-like CD8+ T cells - Enhancer remodeling and transcription factor repurposing in acute activation of NK cells - Elucidating the trans-regulatory mechanisms of a long non-coding RNA during Myogenesis - Study of cholesterol 25-hydroxylase in T cell-mediated inflammation in the skin Major accomplishments are highlighted below. - Investigation of genetic causes for Systemic Lupus Erythematous through whole genome sequencing: Processed 59 new WGS samples sequenced by Novogene. Performed monozygotic twin-based mutation analysis. Identified a likely mutation in a biologically interesting gene (RELA). Evaluated bioinformatic tools for HLA typing from the WGS data. Analyzed 192 WGS samples for HLA types in both class I and class II HLA genes. - Somatic mutation analysis in Keratoacanthoma: Evaluated bioinformatic tools for Whole Exome Sequencing (WES) Copy Number Variant (CNV) detection. Performed additional data analysis using CNVkit and detected more than 8K somatic CNVs in 24 patients. - Mutation analysis in the NIAMS WES cohort: Performed trio-based mutation analysis in more than 20 NIAMS patients with various diseases including sJIA, AOSD, Takayasus arteritis, Relapsing Polychondritis, and Melorheostosis. Identified potentially disease-causing mutations in several genes such as TRIM21, LMTK2, and APPL2. Performed joint variant call on more than 3000 WES Relapsing Polychondritis and control samples. Provided guidance on variant enrichment analysis for the cohort. - Mutation analysis in patients with inflammatory pustular diseases enrolled in anakinra study: Performed WGS analysis for 18 patients sequenced in NIAMS sequencing core. Identified mutations in genes involved in pustular or plaque psoriasis. - Mutation analysis in patients with early onset Merkel cell carcinoma: Performed WGS analysis for 37 patients sequenced in NIAMS sequencing core. Identified more than 300 rare, non-silent coding variants from target genes including a known MAGT1 nonsense mutation. - Transcriptome of healing: Furthered the understanding of the transcriptome of healing by examining SOX2 overexpression in epidermis, looking at effect of mitomycin C on corneal wound healing, and comparing diabetic foot ulcers with normal diabetic skin. - Clinical studies of JAK inhibitors: Examined the effect of JAK inhibitors on patients with Systemic Lupus Erythematosus, including reduction in type I interferon responsive genes in whole blood after treatment. - Modulation of acute lethal sepsis: Feeding schedule affects the susceptibility of mice to acute lethal sepsis. Deletion of hepatic but not myeloid BMAL1 results in LPS susceptibility independent of feeding. RNA-seq analysis identified FXR signaling as a potential mechanism and functional studies verified that mechanism, therefore hepatocyte BMAL1 and FXR signaling integrate nutritional cues to regulate survival in response to innate immune stimuli. - MicroRNA-221 and -222 modulate transcriptome of intestinal Th17 cells: miR-221 and miR-222 are induced by proinflammatory cytokines and repressed by TGF-beta and these miRNAs regulate downstream effects. Maintenance of intestinal Th17 homeostasis is not affected by loss of these miRNAs but such Th17 cells expand more efficiently in response to IL-23. Mice in which these miRNAs are globally or specifically deleted in T cells are more prone to mucosal barrier damage. miR-221 and miR-222 are important repressors of proinflammatory response in intestinal Th17 cells. - 3D genome conformation analysis with Hi-C: The three-dimensional conformation of genomes analysis tools JUICER and hiCPro have been implemented to analyze Hi-C data at various resolutions. Compartments, contact domains, and locally enriched peaks can be defined. The meta data generated with the pipeline may be visualized in 2D together with 1D data generated from ATAC-seq, ChIP-seq, and RNA-seq pipelines. - CUT&RUN data analysis tool implementation: CUTRUNTOOLS has been implemented and updated to analyze in histone and transcription factor ChIP-seq data generated from muscle and skin cells. H3K4Me3 works well with limited cell numbers and much less sequencing depth. The data generated with both MACS and SEACR peak calling tools were compared. However, interpretation of the data could be tricky. Each of the histone marks needed to be adjusted accordingly. - Spatial transcriptomics data analysis pipeline implementation: Tested and established the pipeline for spatial transcriptomics data analysis with cell ranger and loupe for both HE and IF images. Manually generated the alignment file, estimated the sample quality and evaluated the reproducibility. - Tailored analysis of RNA-seq data from cancer cells treated with Cu and DSF: Developed a data analysis method tailored to RNA-seq data from cancer cells to deal with the dominant variability associated with the sample preparation batches (biological duplicates). To avoid the batch effects which are larger than the biological effects, this method calculates both statistical significance (p-values) and biological significance (fold changes) based on paired comparisons within the same sample preparation, making it possible to identify a number of differentially expressed genes to continue the downstream analysis, which is otherwise impossible. The pathway analysis of these DEGs generated interesting results that make biological sense. - Implementation of a novel data integration software package Taiji: Implemented a sophisticated data analysis package Taiji for integrated analysis of data from both ATAC-seq and RNA-seq, ranking transcription factors based on their calculated and predicted effects on gene expression profile changes. - Method development for study of U12 intron genes in Lupus: A scRNA-seq data based method has been developed to study the roles of U12 intron genes in Lupus. The method has been used to investigate the gene expression profiles in single cell clusters of a group of genes sharing a common feature, such as the U12 intron genes. The method is currently under further development to be used in the establishment of a scoring system to compare the group based gene expression profiles.