The Mount Sinai Skin Biology and Diseases Resource-based Center (SBDRC) operates several research cores. These cores address skin disease modeling; skin genomics, transcriptomics, and epigenetics; and data analysis and integration.
The Sinai SBDRC Resource Cores capitalize on: (i) strong expertise in skin epigenetics, mouse models of genetic disease, sophisticated methods for marking, visualizing, isolating and transcriptionally profiling subpopulations of skin cells, including at the single cell level, visualization of skin cell behavior in real time both ex vivo and in vivo, and iPS derivation and gene editing and (ii) institutionally-supported and highly innovative technological infrastructure and expertise.
Resource Core B “Modeling of Skin Disease for Mechanistic Analysis and Therapeutic Discovery” helps to perform cutting edge imaging methods; assists with isolation of skin cell subpopulations for analysis; consults and aids in the generation and analysis of genetically altered mice for mechanistic studies and disease modeling; and provides sophisticated CRISPR technologies for gene editing and gene expression manipulation screens in human iPSC-derived skin cells to model disease, explore mechanisms, and establish therapeutic screening platforms. Learn more.
Resource Core C “Skin Genomics, Transcriptomics, and Epigenetics Core” provides access to methods for genomics (exome sequencing, whole genome sequencing, and targeted capture), transcriptomics (RNA-seq, ISO-seq, small RNA seq), epigenetic (ATAC-seq, ChIP-seq, CUT&RUN, Hi-C), and single-cell (scRNA-seq, scATAC-seq, spatial transcriptomics) analysis of normal and diseased skin. Learn more.
Resource Core D “Data Analysis and Integration Core” provides a reduced cost, start-to-finish standardization of bioinformatic and statistical services for Cores B and C and integrates generated datasets to provide information in a manner that is easily accessible to the research community. Core D will also release Skin-GLOW (Skin-Gene Level Omic Web Tool), an online tool to allow an interactive gene- and sample-centric visualization of multi-omic datasets from multiple platforms (RNA-seq, ATAC-seq, ChIP-seq, HiC, scRNA-seq and scATAC-seq). Learn more.