Translational Genomics Research Branch
Division of Extramural Research
The purpose of this initiative is to encourage investigators to apply recent advances in spatial transcriptomics, imaging, and high-throughput single-cell sequencing approaches to understand the complex spatiotemporal context of the developing embryo.
Over the last several years, use of single-cell RNA-sequencing (scRNA-seq) and related single-cell technologies has become a routine tool for obtaining a snapshot of genomic-level events occurring in groups of dissociated cells. These genomic approaches have driven insights into the identities of cell populations in the developing embryo and computational analysis and modeling tools can now link these identities across time in a developmental trajectory. In craniofacial developmental biology, NIDCR has supported projects to define cell expression profiles in zebrafish, chick, and mouse embryos in a variety of settings such as the neural crest lineage, cranial sutures, and palate. While these approaches have been valuable for understanding the cellular players, there remains a gap in knowledge of how these cells are situated in the landscape of the embryo. This is of particular importance due to the dynamic nature of the developing embryo. New technologies to facilitate the connection between cell identity and location are growing, including several approaches within the emerging field of spatial transcriptomics. These newer technologies complement other cell labeling approaches that enable real-time assessment of cellular movement and together can generate a more complete picture of development.
Gaps and Opportunities
Research programs funded by NIDCR have generated scRNA-seq data in a variety of settings, but most studies to date focus on dissociated cells rather than intact tissue. While these studies have led to impressive gains in characterizing the diverse cell populations in the developing embryo, there is a marked lack of information about how these cells are placed in space, in relation to other cells or cell types, and how spatial relationships unfold over developmental time. Pursuit of knowledge in this area will provide insight into the lifetime trajectory of a given cell, cell-cell interactions, and how gene expression and fate might be regulated through these interactions. As spatial transcriptomics becomes established, it will be more accessible to the community, along with related technologies. Further, tools and approaches already well-utilized in the dental and craniofacial developmental biology community will also support proposed investigations. For example, embryos with disruptions in development (e.g. genetic or pharmacologic) will provide a useful platform to learn how deletion or depletion of specific cell types or interactions impact the embryo.
Responsive applications will include high-throughput approaches that link ‘omics data to spatial information and address a fundamental process in dental and craniofacial developmental biology. The scope of projects may incorporate existing genomic data, cell labeling and visualization, and computational approaches to integrate these data over space and across one or more stages of development. All dental and craniofacial embryonic cell types or tissues are of interest and projects may utilize wild type and genetically modified backgrounds. Achievement of the objectives will lead to the definition of new cell types, maps of cell movement and differentiation, and identification of loci of important cell-cell interactions. Key scientific components will include developmental biology, computational, bioinformatics, and imaging expertise; collaborative approaches within or across institutions are highly encouraged.
Advancements will generate 3D/4D information and promote a deeper functional understanding about cell identity and movement during critical developmental events in both wild type animals and in the context of mutations, including those in non-coding regions. Pursuit of this priority will likely generate data across many data types, including imaging, genomic, transcriptomic, epigenomic, proteomic, and bioinformatic data, as well as computational methodology. With the implementation of the upcoming Data Sharing and Management Policy (NOT-OD-21-013), sharing of all data types according to FAIR principles will be required, which will be a valuable resource for the entire scientific community.
This initiative can leverage NIDCR investment in high-throughput genome-wide sequencing over the last decade to inform hypothesis development and data validation. The Genomic Data Sharing Policy (NOT-OD-14-124) ensures that these data are broadly available through public repositories such as GEO and FaceBase, so as to support and accelerate research conducted by the dental, oral, and craniofacial developmental biology community at-large. Development of technologies in spatial transcriptomics and genetic manipulation with CRISPR make this an opportune time to move forward.
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