NICHD Bioinformatics and Scientific Programming Core

Eunice Kennedy Shriver National Institute Of Child Health & Human Development

Investigators

Linked publications & trials

Abstract

NICHD's Bioinformatics and Scientific Programming Core (BSPC) consists of a central core of staff who coordinate with embedded bioinformaticians working directly in laboratories. This results in centralized infrastructure that is reusable across many projects while also providing focused and custom local support. Analyses performed by BSPC make extensive use of NIH's Biowulf high-performance computing cluster. Projects continued from last reporting period include: identification of 3' ends of bacterial transcripts; single-cell RNA-seq analysis of zebrafish in various tissues and developmental stages; integration of single-cell ATAC-seq and single-cell RNA-seq to identify poised enhancers related to neuronal development; detection of random monoallelic expression using single-cell RNA-seq in zebrafish brain; development of track hubs to visualize genomic data across many different experiment types; differential methylation in Cushings disease patients; variant calling in patients in several rare diseases; insertion of HIV into the human genome and its relationship with LEDGF chromatin binding protein; differential expression, translational efficiency changes, and nucleosome occupancy in a wide variety of mutant yeast strains using RNA-seq, Ribo-seq, and ChIP-seq; bulk and single-cell RNA-seq analysis of differentially expressed genes during Xenopus tropicalis development; regulation of development by thyroid hormone receptor in X. tropicalis using RNA-seq and ChIP-seq; identification of genome-wide RNA-RNA interactomes in E. coli using RNA-seq and RIL-seq; extended developmental time course transcriptomic analysis using scRNA-seq in zebrafish; integrated analysis of RNA-seq and reduced-representation bisulfite sequencing (RRBS) in a time course during and after prolonged glucose exposure in zebrafish; mass spectrometry analysis of different mutations of RHOA protein and their effect on other proteins' abundances in a human cell line; scRNA-seq analysis to characterize GABAergic neurons; differential methylation in brain tissue of Zika patients; and development of a software tool for NICHDs Zebrafish Core that identifies optimal CRISPR/Cas9 oligos for designing custom zebrafish models for rare diseases. We performed RNA-seq analysis to detect differentially expressed genes in a wide variety of experimental designs, model systems, and biological perturbations. We also performed various RNA-seq analyses on osteogenesis imperfecta, ciliopathy, and NPC1 patients as well as in model systems for Cushings disease, neuron injury, and osteogenesis imperfecta. New projects this year include pilot analysis of multiome (scRNA-seq + scATAC-seq) data from mouse brain; evaluation of a fluorescent assay to find transposon integration events genome-wide; an integrative analysis of 5 and 3 ends of bacterial transcripts in multiple species and conditions; CUT&RUN analysis in several model systems; CRISPRi screens in various neuronal systems; multidimensional scRNA-seq analysis on the effects of age in fly guts; reimplementing and extending software for the TRIP assay; deep RNA-seq of single or several hand-picked neurons; large-scale aggregation of many experiments looking at perturbations of basket nucleoporins; analysis and tool development for various ribosomal profiling assays; and an R package for working with proximity extension assay data. BSPC continues to develop and maintain lcdb-wf, a system of workflows and pipelines to process high-throughput sequencing data, run extensive quality control, and perform differential ChIP-seq or RNA-seq analyses and which runs on NIHs Biowulf high-performance computing cluster. We develop custom web applications using R Shiny that allow our collaborators to explore and compare their data in powerful ways without requiring bioinformatics expertise. We train users in NICHD and other ICs to use these tools and others on their own data. We have also continued to contribute to the Bioconda project, a system used by bioinformaticians worldwide to easily install biology-related software tools.