ABSTRACT

Rapid climate change and other environmental factors are increasing societal demands for plant-based solutions from scientists and engineers. The long-term goal of the Plant Cell Atlas (PCA) community is to build a comprehensive map of the locations, interactions, and functions of molecules in plant cells and tissues to accelerate both fundamental research and meeting societal challenges. The PCA community will set standards for generating and integrating large plant data sets that will ultimately contribute to the foundation of synthesizing how biology works at the cellular level. The RCN will establish and nurture the community that will ultimately generate data and infrastructure for the PCA. This RCN will also provide excellent networking and interdisciplinary training opportunities for early career scientists and outreach to K-12 students and the general public about the importance and fascination of plants.

Many questions in fundamental, translational, and applied plant biology await answers, requiring both new data and analytical frameworks that make connections among disparate data types. Rapid advances in technologies are being made in synthetic biology, genome engineering, robotics, artificial intelligence, structural biology, mass spectrometry, and microscopy. These technologies are being applied to plants to dissect the functions and interactions of specialized cell types and their capacity to respond to environmental stresses, host symbioses, and to produce useful products. However, the information provided by these new technologies will be most powerful if it is integrated and standardized to provide fresh insights into the functional connections among diverse biomolecules, to suggest new hypotheses for cellular functions, and to model cellular processes. The community established through this RCN will pioneer the integration of large, diverse plant datasets into a Plant Cell Atlas that will ultimately enable innovative and sustainable solutions to the challenges expected from climate change. The RCN will: 1) develop rubrics for defining plant cell types; 2) provision networking and training opportunities for the PCA community, especially for early career participants through workshops, webinars, and symposia; 3) establish guidelines and best practices for data integration, resulting in standardized data collection protocols and analysis methods; 4) facilitate the generation of new methods for image annotation/analysis driven by connections to the artificial intelligence community; 5) develop the PCA website as a central platform where scientists can find experimental protocols, community standards, and links to available resources; and 6) foster collaborations on research and grant applications for generating data, developing tools, and creating computational infrastructures. This award is being co-funded by the Cellular Dynamics and Function and the Genetic Mechanisms clusters of the Division of Molecular and Cellular Biosciences, along with the Plant, Fungal and Microbial Developmental Mechanisms Program and the Plant Genome Research Program of the Division of Integrative and Organismal Systems.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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