Skip to main content
ARS Home » Northeast Area » Ithaca, New York » Robert W. Holley Center for Agriculture & Health » Plant, Soil and Nutrition Research » Research » Publications at this Location » Publication #397014
Research Project: Mapping Crop Genome Functions for Biology-Enabled Germplasm Improvement

Location: Plant, Soil and Nutrition Research

Title: A data infrastructure for the plant cell atlas

Author
item FAHLGREN, NOAH - Donald Danforth Plant Science Center
item KAPOOR, MUSKAN - Iowa State University
item YORDANOVA, GALABINA - Embl-Ebi
item WAESE, JAMIE - University Of Toronto
item COLE, BENJAMIN - Lawrence Berkeley National Laboratory
item HARRISON, PETER - Embl-Ebi
item Ware, Doreen
item TICKLE, TIMOTHY - Harvard University
item PATEN, BENEDICT - University Of California Santa Cruz
item BURDETT, TONY - Embl-Ebi
item ELSIK, CHRISTINE - University Of Missouri
item TUGGLE, CHRISTOPHER - Iowa State University
item PROVART, NICHOLAS - University Of Toronto

Submitted to: Plant Physiology
Publication Type: Review Article
Publication Acceptance Date: 9/10/2022
Publication Date: N/A
Citation: N/A

Interpretive Summary: In the last decade, technologies to improve resolution of plant cell types have improved. The infrastructure to support these data sets and integrate across them is still in the early phases. This document provides a high-level summary of the existing databases and how they may be utilized to contribute to data infrastructure for a plant cell atlas.

Technical Abstract: We review how a data infrastructure for the Plant Cell Atlas might be built using existing infrastructure and platforms, and how such an infrastructure will enable biologists and data scientists to glean new insights into plant biology in the coming decades. Advances: High-throughput single cell assays have led to efforts to produce comprehensive atlases of cell types and localization and organization of molecules, cells, and tissues. Databases, visualization, and modeling tools are being developed for exploring, analyzing, and visualizing multi-scale and multi-modal data. Development of data and metadata standards and vocabularies and consistent analysis pipelines will be key for data sharing, annotation, curation, and integration. Cloud computing and cyberinfrastructure will enable us to build community-based data infrastructure platforms.