Epigenomics Core

The Epigenomics Core facility offers integrated high-throughput multi-omics technologies spanning bulk epigenomics, single-cell and spatial genomics, and comprehensive bioinformatics support to enable in-depth insights into gene regulation, cellular heterogeneity, and human disease mechanisms.

Core Technologies/Services

Epigenomic Profiling:

NGS libraries can be generated from a range of complementary epigenomic techniques, including RRBS, WGBS, and EM-seq for DNA methylation analysis, as well as 5-base methylation approaches. Libraries can also be prepared for ChIP-seq and CUT&RUN to study protein–DNA interactions, and for ATAC-seq to assess chromatin accessibility from cells or tagmented DNA, enabling comprehensive sequencing-based analysis of epigenetic regulation.

Single Cell Transcriptomics:

Single cell or single nuclei 3' gene expression with options for cell multiplexing (10X OCM), targeted gene expression and feature barcoding, such as cell surface protein, CRISPR screening, 3' CITE-seq and/or Cell Hashing. Single Cell Gene Expression Flex, fixed RNA profiling, with or without multiplexing is also an option for fixed cell state or FFPE samples.

Single Cell Immune Profiling:

Single cell 5' gene expression with options for V(D)J profiling, TCR and/or BCR, as well as feature barcoding, such as cell surface protein, CRISPR screening, 5' CITE-seq and/or Cell Hashing.

Single Cell Spatial Transcriptomics:

Tissue-scale spatial gene expression profiling is available using the sequencing-based Visium HD workflow with CytAssist support, including both High Definition (HD) and 3′HD workflows. For single-cell and subcellular spatial analysis, we offer imaging-based spatial transcriptomics services using the CosMx Spatial Molecular Imager and Xenium Analyzer platforms, enabling highly multiplexed in situ RNA detection with precise cellular localization.

Bioinformatics Analysis:

Data analysis services and consultation on a per project basis. Publications and/or presentations enabled by custom data analysis through core personnel require author credit for the bioinformatician.

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