Nextgen spatial multi-omics technologies

The National Institutes of Health National Human Genome Research Institute awarded New York Genome Center, Inc., $2,677,663 on June 22, 2026, under the Human Genome Research program (CFDA 93.172, Assistance Listing designation R01HG014032) to develop next-generation spatial multi-omics technologies.

The recipient will design a cost-effective, user-friendly platform for spatial multi-omic profiling that integrates chromatin states, transcriptional activity, and other modalities simultaneously in tissue samples with spatial resolution. Current methods either lack spatial information or are prohibitively expensive; the project addresses this gap by devising innovations in fabrication techniques and integrated analysis capabilities such that each new capability can be employed independently to enhance existing spatial technologies or jointly as a unified platform.

Work performs in New York, New York from the award date through May 31, 2030. The obligation of $2,677,663 represents the total funding commitment for the period of performance.

Abstract

Tissue organization and function requires an intricate and dynamic interplay of multiple cell types and cell states. Such local and tissue scale cellular relationships are the product of interacting gene regulatory networks within cells and signal transduction between cells. This complexity must be both finely tuned to maintain homeostasis and reconfigurable in response to changing environmental or physiological needs. Epigenetic marks, transcriptional activity, RNA processing, translation, post-translational modification, and regulated degradation are all required to achieve this. Although such multimodal profiling can be conducted at a single cell level, current methods are not able to map these modalities simultaneously in tissues with spatial resolution. On the other hand, the methods that do provide spatial information, like spatial transcriptomics, are not only unimodal, but also prohibitively expensive, requiring costly consumables or specialized capital equipment. Therefore, we currently lack spatial information needed for understanding the cellular microenvironment and tissue architecture. As such, our understanding of how chromatin states relate to gene expression is limited, and we have yet to measure how tissue-specific and -independent factors influence these processes. Here, we propose to overcome these technical challenges, as well as financial barriers, by devising the first cost-effective, user-friendly platform for spatial multi-omic profiling. We will achieve this by implementing a technology development strategy that is carefully designed such that each new capability we build can be employed independently to enhance capabilities of spatial technologies already in widespread use, as well as jointly as an integrated platform. Towards this overarching goal we plan to introduce several significant innovations by: (1) developing cost- effective and easy-to-use fabrication techniques for nucleic acid capture surfaces that encode spatial information at 1ΜM resolution across a large field of view and can easily and cheaply be tailored to the tissue and biological question under study; (2) establishing a novel all-sequencing based approach for spatially resolved multi-omics profiling and validating its performance by profiling the aging brain; and (3) building a new spatial PCR-free sequencing method we termed spatial inference via localized concatemerization (silc). Silc will obtain spatial information by sequencing alone, thereby dramatically lowering barriers to entry for use of spatial technologies. Overall, our efforts will democratize research involving spatial profiling, and catalyze advances across a broad swath of biological investigation.