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Fernandez-Espinosa, M. G.

Publications and source records attributed to Fernandez-Espinosa, M. G..

2 recordsLinked to original sources

TGA family of transcription factors are nitric oxide sensors in the root stem cell niche

Plant root development is tightly regulated and depends on the coordination among different cell types located in the root stem cell niche (SCN). A complex network of regulators includes the gasotransmitter nitric oxide (NO) known to inhibit primary root growth, modify root architecture and alter meristem organisation. However, little is known about the molecular targets and the mechanistic insights of this signalling molecule during root SCN homeostasis. Here, genetic, molecular and physiological evidence support that TGA transcription factors of the bZIP family, and specifically PERIANTHIA (PAN), contribute to NO-mediated root stem cell regulation. NO induces reversible S-nitrosylation of PAN, thereby inhibiting its binding to DNA and associated transcriptional activation. In turn, the protein-SNO reductase activity of TRXh5 is able to denitrosylate PAN. This switch on and off mechanism of PAN activation modulates WOX5 expression and quiescent centre activity, which alters columella stem cell maintenance through a NO-dependent mechanism. Different TGA members interact with PAN and are also S-nitrosylated, whose expression in the root SCN together with their accumulated mutations contribute to NO sensing during root apical meristem development. Collectively, these findings reveal a molecular framework where NO controls the ability of PAN to bind to its targets as a master regulator of the root SCN.

plant biology↗

An Inference Approach Combines Spatial And Temporal Gene Expression Data To Predict Gene Regulatory Networks In Arabidopsis Stem Cells

Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is key for understanding the initiation and growth of plant tissues and organs. Although many TFs have been shown to have a role in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. In this work, we used spatial and temporal transcriptomic data to predict interactions among the genes involved in stem cell regulation. For this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network (GRN) inference algorithm that combines clustering with Dynamic Bayesian Network (DBN) inference. We leveraged the topology of our networks to infer potential key regulators. The results presented in this work show that our combination of molecular biology approaches, computational biology and mathematical modeling was key to identify candidate factors that function in the stem cells. Specifically, through experimental validation and mathematical modeling, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center (QC) function.

plant biology↗