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Hormone-activated proteolysis is a recurring theme of plant hormone signaling mechanisms. In strigolactone signaling, the enzyme-receptor DWARF14 (D14) and an F-box protein, MORE AXILLARY GROWTH2 (MAX2), mark SUPPRESSOR OF MAX2 1- LIKE (SMXL) family proteins SMXL6, SMXL7, and SMXL8 for rapid degradation. Removal of these transcriptional corepressors initiates downstream growth responses. The homologous proteins SMXL3, SMXL4, and SMXL5, however, are resistant to MAX2- mediated degradation. We discovered that the smxl4 smxl5 mutant has enhanced responses to strigolactone. SMXL5 attenuates strigolactone signaling by interfering with AtD14-SMXL7 interactions. SMXL5 interacts with AtD14 and SMXL7, providing two possible ways to inhibit SMXL7 degradation. SMXL5 function is partially dependent on an EAR motif that typically mediates interactions with the TOPLESS family of transcriptional corepressors. However, we find that loss of the EAR motif reduces SMXL5-SMXL7 interactions and the attenuation of strigolactone signaling by SMXL5. We hypothesize that integration of SMXL5 into heteromeric SMXL complexes reduces the susceptibility of SMXL6/7/8 proteins to strigolactone-activated degradation, and that the EAR motif promotes the formation or stability of these complexes. This mechanism may provide a way to spatially or temporally fine-tune strigolactone signaling through the regulation of SMXL5 expression or translation. 

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.