Two antagonistic gene regulatory networks drive Arabidopsis root hair growth at low temperature linked to a low‐nutrient environment

Copyright and License

© 2025 The Author(s). New Phytologist © 2025 New Phytologist Foundation.

Acknowledgement

We thank the Arabidopsis Biological Research Center (ABRC) at The Ohio State University for providing T-DNA seed lines, Dr Andrés Rossi and Dr Esteban Miglietta from FIL microscopy facility for technical support with confocal microscopy. We also thanks Dr Martiniano M Ricardi for the BiFC plasmids. JME, FA and RLC are investigators of the National Research Council (CONICET) from Argentina. MAI is supported by ANID FONDECYT POSTDOCTORADO [grant 3220138]. This work was supported by grants from ANPCyT (PICT2019-0015 and PICT2021-0514), by ANID – Programa Iniciativa Científica Milenio ICN17_022, NCN2021_010 and Fondo Nacional de Desarrollo Científico y Tecnológico [1200010] to J.M.E. J.M.A lab is supported by ANID FONDECYT 1210389, Programa Iniciativa Científica Milenio ICN17_022, and NSF Plant Genome Grant NSF-PGRP: IOS-1840761. We are grateful to the Research Computing Group at Harvard Medical School for access to the O2 High Performance Compute Cluster. AK was supported by the Postdoctoral Fellowship Program (Nurturing Next-generation Researchers) through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2021R1A6A3A14039622). N.P. is an investigator of Howard Hughes Medical Institute.

Contributions

TUL, VBG, MAI and HS-G performed most of the experiments, analyzed the data and helped in the writing process of the manuscript. JP-D and RA performed some experiments and helped in the writing process. DRR-G helped in the writing process. GN-L and CM performed the RNA-Seq analysis, TCM and JMA performed the gene network analysis and GTL1 ChIP analysis. JMA also helped with the writing process. LF and FA carried out the ChIP experiment of RSL4 and helped on the writing process. AK and NP performed the AlphaFold-Multimer analysis. MAR and KAS carried out the root hair characterization in monocots. AAM helped in the writing process. MS and KS provided seeds and helped in the writing process. MFP, VNM and FPS carried out preliminary phenotypic assays and provided several HB mutants, transgenic, promoters for AtHB genes. A-RK and NP performed the alpha fold analysis. TN provided multiple HBs mutants. RLC provide most of the AtHBs lines and help in the writing process. JME designed research, analyzed the data, supervised the project, and wrote the paper. All authors commented on the results and the manuscript. This manuscript has not been published and is not under consideration for publication elsewhere. All the authors have read the manuscript and have approved this submission. TUL, VBG, MAI and HS-G contributed equally to this work. Correspondence and requests for materials should be addressed to JME (Email: jose.estevez@unab.cl). HD-Zip single mutants and overexpressor lines must be requested to RLC unless those lines developed by TN. TUL, VBG, MAI and HS-G co-first authors.

Supplemental Material

• Dataset S1 Quantification of RH length in all phenotypes in all conditions.
• Dataset S2 Quantification of gene expression by qPCR in all phenotypes in all conditions.
• Fig. S1 Influence of room temperature pretreatment time length on low-temperature RH growth in Arabidopsis thaliana.
• Fig. S2 Differential expression analysis between Col-0, rsl2, rsl4 and rsl2 rsl4 mutants under low-temperature treatment and expression of RSLs under low-temperature treatment.
• Fig. S3 DEG analysis between Col-0 and rsl2, rsl4 and rsl2 rsl4 mutants at low temperature at 2 and 6 h.
• Fig. S4 GO analysis of the 5 clusters identified from the DEG analysis between Col-0 and rsl2, rsl4 and rsl2 rsl4 mutants at low temperature at 2 and 6 h.
• Fig. S5 Characterization of AtHB13 and MYB-like.
• Fig. S6 Characterization of GTL1 and RSLs
• Fig. S7 Characterization of AtHB16 and AtHB23
• Fig. S8 Characterization of AtHB3, AtHB13, AtHB20, AtHB23
• Fig. S9 Characterization of ERD7 and ERD10
• Fig. S10 Characterization of genotypes growth at low-nutrient media
• Fig. S11 Expression levels of the main RSL4-gene RH regulatory network nodes
• Fig. S12 Expression levels of the RSL4-downstream RH gene regulatory network nodes
• Fig. S13 Expression levels of the main RSL4-gene RH regulatory network nodes
• Fig. S14 Expression levels of the RSL4-downstream genes ERD7/ERD10 and AtHB16/AtHB23 in Wt and in the overexpression lines EXP7:RSL4-GFP, EXP7:GTL1-GFP, 35S:AtHB13 and 35S:AtHB16
• Fig. S15 Predicted aligned error maps of the best 35 positive protein–protein interactions identified by AFM predictions.
• Table S1 Normalized expression values of candidate genes belonging to Cluster 1 to Cluster 5 (Fig. S3).
• Table S2 Root hair genes based on single-cell RNA-Seq published data.
• Table S3 Overlap of genes controlled by RSL4.
• Table S4 Gene regulatory network controlled by GTL1, AtHB13 and MYB-like TFs.
• Table S5 GRN controlled by RSL4
• Table S6 Mutants and transgenic lines used and generated in this study
• Table S7 Oligonucleotide list for RT-qPCR analysis.
• Table S8 FM protein–protein interaction predictions.