PROJECT SUMMARY/ABSTRACT
Protein-DNA interactions control access to genes in chromatins and regulate the spatial- and temporal-specific
gene expression. These interactions are crucial for cell differentiation and the maintenance of cellular diversity.
Dysregulated patterns of protein-DNA interactions are often associated with disease states. Applications of next-
generation epigenomic sequencing techniques have enabled deconvolution of protein-DNA interactions at
single-cell level. However, it remains challenging to define how cell-to-cell heterogeneity in protein-DNA
interactions impacts gene expression variability. Currently available methods for joint profiling protein-DNA
interactions and gene expression from single cells require laborious genetic manipulation, suffer relatively low
throughput, and are impossible to specifically map proteins with post-translational modifications, such as histone
marks. To address these unmet needs, we propose to develop PRODIGE – a high-throughput tool for joint
profiling of protein-DNA interactions and gene expression in the same single cells without the need of genetic
manipulations. It is enabled by a strategic integration of reversible cell fixation, antibody-guided chromatin
tagmentation, novel deformable and degradable barcoded hydrogel beads, droplet microfluidics, and next-
generation sequencing technology. In Aim 1, we will develop technical components and analytical pipelines of
PRODIGE. We will prepare protein A-Tn5 transposome for antibody-guided Tn5 tagmentation, fabricate
microfluidic devices for single-cell PRODIGE assay, and synthesize a barcoded library of deformable and
degradable barcoded hydrogel beads for single-cell barcoding. In Aim 2, we will optimize the method in bulk and
single-cell levels, and assess the performance of PRODIGE (joint analysis) in comparison to other stand-alone
counterparts. In Aim 3, we will benchmark PRODIGE to established tools for joint single-cell profiling of protein-
DNA interactions and transcriptome. Successful implementation of the proposed program will deliver a high-
throughput tool to quantify how cell-to-cell heterogeneity in protein-DNA binding influences gene expression
variability, decipher cell-type-specific patterns of upstream protein-DNA interactions and their transcriptional
outputs, and identify protein-mediated mechanisms that regulate cell-type-associated transcriptional programs
in heterogeneous cell populations and under different developmental and/or disease conditions.
