# Spatial resolution of syncytial nuclear gene regulation > **NIH NIH F32** · BROAD INSTITUTE, INC. · 2020 · $19,101 ## Abstract Syncytial cells, multinucleate cells sharing a cytoplasm1, are a transcriptional enigma. How do nuclei within syncytial cells impact each other, regulate and coordinate transcription, and titrate transcription to deal with variation in the number of nuclei per syncytia? Skeletal muscle, harboring myofibers (muscle syncytial cells) containing hundreds of nuclei, is the most abundant syncytial cell type in the body2,3. In the uninjured muscle, myonuclei are positioned along the periphery of the cell along the long axis4. It has been postulated that each myonucleus’s transcriptional output governs a defined volume of cytoplasm surrounding it, i.e. the myonuclear domain2,5-9. To date, it remains unclear whether myonuclei are transcriptionally synchronous or asynchronous10. Is there a transcript bias across particular syncytial nuclei? If so, how does a nucleus’s spatial position govern its transcriptional diversity? Which transcripts are spatially expressed versus pan-expressed? Do some nuclei outcompete others (hyper- versus hypo-transcribe)? In order to address the myriad of questions, I will apply a combination of laser capture microdissection (LCM)11-16 and single myofiber isolation17-19 in conjunction with single nucleus RNA-sequencing (snRNA-seq)20,21. The results of findings herein will demystify syncytial cell gene regulation resulting from nuclear heterogeneity, allowing for the generation and visualization of computational models describing these specialized transcriptional networks. The models in combination with in situ hybridization-based strategies, MERFISH22,23 and CODEX24, will enable spatial reconstruction of the transcriptional networks within the syncytium. I therefore aim to employ novel genomic tools and computational analysis to characterize the gene regulatory mechanisms enacted in syncytial cells in vivo. I hypothesize that syncytial nuclei are transcriptionally heterogeneous and asynchronous despite sharing a common cytoplasm, and that this affords regional nuclear specifications within the myofiber space. This effort will exploit recent technical developments, largely pioneered by my sponsor, for profiling nuclei on high-content platforms20 and pooling samples by hashing21. A strength of this approach is the purity and scale that syncytial nuclei can be purified from myofibers for profiling17-19,25. Parallel analysis employing the human iPSC system26 and select human tissue samples will complement in vivo murine efforts. Technologies and analysis established in this work will be applicable for studying other syncytial cell types, such as placental syncytiotrophoblast cells27-29. A key objective of this study is to answer of how syncytial cells delegate gene expression across their population of nuclei. Together, this proposal will address whether some nuclei specialize their transcriptional output, and if so, which loci are dedicated and their spatial locale, address the long-standing debate regarding synchrony of individual... ## Key facts - **NIH application ID:** 10066008 - **Project number:** 1F32AR077970-01 - **Recipient organization:** BROAD INSTITUTE, INC. - **Principal Investigator:** Tyler Nelson Harvey - **Activity code:** F32 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $19,101 - **Award type:** 1 - **Project period:** 2020-08-01 → 2020-10-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10066008 ## Citation > US National Institutes of Health, RePORTER application 10066008, Spatial resolution of syncytial nuclear gene regulation (1F32AR077970-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10066008. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*