Next-generation single-cell multiomic methods for quantifying cellular identity

The National Institute of General Medical Sciences awarded The Wistar Institute of Anatomy and Biology $506,550 on September 2, 2026, under the Biomedical Research and Research Training program (CFDA 93.859) to develop next-generation single-cell multiomic methods for quantifying cellular identity and regulatory processes.

The award funds development of a comprehensive suite of single-cell analysis technologies that simultaneously profile diverse regulatory processes—including DNA methylation, histone modification, and alternative RNA splicing—and integrate data related to chromatin states and transcript isoform expression. The research leverages particle-templated instant partitioning (PIP) barcoding technology to enhance reproducibility and efficiency in multi-omic applications, with the goal of improving transcript profiling and quantification through simultaneous short- and long-read sequencing methods. The work addresses a significant gap in identifying abnormal interaction patterns specific to disease-related cell subpopulations, with potential applications to autoimmune diseases, neurodegenerative conditions, and cancers.

Work is performed in Philadelphia, Pennsylvania, with a period of performance extending through June 30, 2031. This is a Project Grant, an assistance type providing time-limited support for discrete research projects under peer review.

Abstract

In multicellular organisms, the interplay between epigenetic and transcriptomic processes creates a complex regulatory network crucial for determining cellular fate. Disruptions to these networks are often linked to various diseases, including autoimmune diseases, neurodegenerative conditions, and cancers. Despite advancements in understanding these interactions, identifying abnormal interaction patterns specific to disease-related cell subpopulations remains a significant challenge. This proposal seeks to address this GAP by leveraging novel single-cell barcoding technologies. These technologies enable mapping cell-type-specific regulatory processes, including DNA methylation, histone modification, and alternative RNA splicing. Current technologies have limitations, primarily in single-omic measurements, failing to adequately capture complex interactions within regulatory networks. To overcome these limitations, we propose a comprehensive suite of multi-omic single-cell methods that can simultaneously profile diverse regulatory processes and integrate data related to chromatin states and transcript isoform expression. Recent advancements, such as particle- templated instant partitioning (PIP), promise to overcome traditional barcoding limitations. PIP enhances reproducibility and efficiency in multi-omic applications, leading US to our preliminary results, which indicate a new ERA in single-cell analysis with potential revolutionary impacts on the study of cellular behavior and disease progression. This proposal aims to establish advanced single-cell epigenetic and transcriptomic analysis technologies that enhance scalability, cost-effectiveness, and portability. Using the PIP barcoding system, we intend to improve transcript profiling and quantification through simultaneous short- and long-read sequencing methods. Our research will utilize a probabilistic model to quantify transcripts from diverse sequencing platforms, addressing current analytical challenges. This approach is designed to yield detailed insights into splicing events and transcriptional diversity across various cell types. Moreover, our investigation aims to utilize pips for single-cell multiomics to measure histone modifications and DNA methylation. We include a proof-of-concept study that can profile transposase-accessible chromatin regions, enhancing epigenetic assays with optimized techniques. We will tackle the challenges of quantifying multiomics data using bayesian methods, increasing statistical power and allowing US to capture chromatin states at the single-cell level. This will provide insights into epigenomic features across millions of cells. The study will identify regulatory elements by examining histone and DNA modifications alongside RNA splicing. Given the broad implications of our research, this work can potentially affect the understanding and treatment of autoimmune diseases, neurodegenerative conditions, and cancers. The NIH maximizing investigators' research award will support our efforts to advance novel multiomics techniques rapidly and facilitate the identification of new therapeutic targets for various diseases.