New York Genome Center (NYGC) has received a USD 2.68 million NIH R01 grant from the National Human Genome Research Institute to develop a cost-accessible platform for spatial multi-omic profiling — addressing a persistent technical and financial bottleneck in tissue biology research.
Current single-cell methods can capture epigenomic, transcriptomic, and proteomic data simultaneously, but lose spatial context when tissues are dissociated. Spatial transcriptomics preserves tissue architecture, but remains largely unimodal and expensive, requiring specialized consumables and capital equipment that limit adoption. The NYGC project, led by Sanja Vickovic, aims to resolve this by building sequencing-based capture surfaces with 1-micron spatial resolution, an integrated multi-omic readout validated in aging brain tissue, and a PCR-free method called spatial inference via localized concatemerization (SILC) that encodes spatial information through sequencing alone — removing the need for costly imaging hardware.
The approach is designed modularly: each component can function independently to augment existing spatial platforms or operate as an integrated system, lowering barriers to adoption across laboratories with varying resources.
The spatial biology field is increasingly crowded. 10x Genomics dominates with its Visium and Xenium platforms, while companies including Vizgen, Akoya Biosciences, and Bruker’s spatial biology division compete on resolution and multiplexing. NYGC’s focus on cost reduction and user-friendliness, rather than resolution alone, positions this effort differently — targeting the accessibility gap rather than competing on instrument performance.
The five-year award, running through May 2030, reflects NHGRI’s sustained interest in next-generation genomic tools that extend beyond sequencing throughput to spatial and multimodal data integration. Vickovic’s laboratory has previously contributed to spatial transcriptomics method development, and NYGC’s infrastructure as a dedicated genomics research institute supports the sequencing-intensive workflows the platform requires. If validated, the platform could expand spatial multi-omic profiling to laboratories currently priced out of existing commercial solutions.
This write-up has been adapted from allsci
