Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics
Carolin Grones, Thomas Eekhout, Dongbo Shi, Manuel Neumann, Lea S. Berg, Yuji Ke, Rachel Shahan, Kevin L. Cox, Fabio Gómez-Cano, Hilde Nelissen, Jan U. Lohmann, Stefania Giacomello, Olivier Martin, Benjamin Cole, Jiawei Wang, Kerstin Kaufmann, Michael T. Raissig, Gergő Pálfalvi, Thomas Greb, Marc Libault, Bert De Rybel
Abstract
Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation and to make the data readily available to the community in this fast-developing field of research.