Biology subjects

de Luis Balaguer, M. A.

Publications and source records attributed to de Luis Balaguer, M. A..

6 recordsLinked to original sources

bioRxiv2025

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↗

bioRxiv2021

Analysis of phloem trajectory links tissue maturation to cell specialization.

The mechanisms that allow cells in the plant meristem to coordinate tissue-wide maturation gradients with specialized cell networks are critical for indeterminate growth. Here, we reconstructed the protophloem developmental trajectory of 19 cells from cell birth to terminal differentiation at single cell resolution in the Arabidopsis root. We found that cellular specification is mediated near the stem cell niche by PHLOEM EARLY DOF (PEAR) transcription factors. However, the PEAR dependent differentiation program is repressed by a broad gradient of PLETHORA (PLT) transcription factors, which directly inhibit PEARs own direct target ALTERED PHLOEM DEVELOPMENT (APL). The dissipation of PLT gradient around 7 cells from the stem cell activates APL expression, and a subsequent transitional network that results in a "seesaw" pattern of mutual inhibition over developmental time. Together, we provide a mechanistic understanding of how morphogen-like maturation gradients interface with cell-type specific transcriptional regulators to stage cellular differentiation.

plant biology↗

bioRxiv2019

Stem-cell-ubiquitous genes spatiotemporally coordinate division through regulation of stem-cell-specific gene networks

Stem cells are responsible for generating all of the differentiated cells, tissues, and organs in a multicellular organism and, thus, play a crucial role in cell renewal, regeneration, and organization. A number of stem cell type-specific genes have a known role in stem cell maintenance, identity, and/or division. Yet, how genes expressed across different stem cell types, referred here as stem-cell-ubiquitous genes, contribute to stem cell regulation is less understood. Here, we find that, in the Arabidopsis root, a stem-cell-ubiquitous gene, TESMIN-LIKE CXC2 (TCX2), controls stem cell division by regulating stem cell-type specific networks. Development of a mathematical model of TCX2 expression allowed us to show that TCX2 orchestrates the coordinated division of different stem cell types. Our results highlight that genes expressed across different stem cell types ensure cross-communication among cells, allowing them to divide and develop harmonically together.

systems biology↗

bioRxiv2018

TuxNet: A simple interface to process RNA sequencing data and infer gene regulatory networks

Predicting gene regulatory networks (GRNs) from gene expression profiles has become a common approach for identifying important biological regulators. Despite the increase in the use of inference methods, existing computational approaches do not integrate RNA-sequencing data analysis, are often not automated, and are restricted to users with bioinformatics and programming backgrounds. To address these limitations, we have developed TuxNet, an integrated user-friendly platform, which, with just a few selections, allows to process raw RNA-sequencing data (using the Tuxedo pipeline) and infer GRNs from these processed data. TuxNet is implemented as a graphical user interface and, using expression data from any organism with an existing reference genome, can mine the regulations among genes either by applying a dynamic Bayesian network inference algorithm, GENIST, or a regression tree-based pipeline that uses spatiotemporal data, RTP-STAR. To illustrate the use of TuxNet while getting insight into the regulatory cascade downstream of the Arabidopsis root stem cell regulator PERIANTHIA (PAN), we obtained time course gene expression data of a PAN inducible line and inferred a GRN using GENIST. Using RTP-STAR, we then inferred the network of a PAN secondary downstream gene, ATHB13, for which we obtained wildtype and mutant expression profiles. Our case studies feature the versatility of TuxNet to infer networks using different types of gene expression data (i.e time course and steady-state data) as well as how inference networks are used to identify important regulators.\n\nSUMMARYTuxNet offers a simple interface for non-computational biologists to infer GRNs from raw RNA-seq data.

plant biology↗

bioRxiv2017

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↗

bioRxiv2017

Genetic Architecture and Molecular Networks Underlying Leaf Thickness in Desert-Adapted Tomato Solanum pennellii

Thicker leaves allow plants to grow in water-limited conditions. However, our understanding of the genetic underpinnings of this highly functional leaf shape trait is poor. We used a custom-built confocal profilometer to directly measure leaf thickness in a set of introgression lines (ILs) derived from the desert tomato species Solanum pennellii, and identified quantitative trait loci (QTL). We report evidence of a complex genetic architecture of this trait and roles for both genetic and environmental factors. Several ILs with thick leaves have dramatically elongated palisade mesophyll cells and, in some cases, increased leaf ploidy. We characterized thick ILs 2-5 and 4-3 in detail and found increased mesophyll cell size and leaf ploidy levels, suggesting that endoreduplication underpins leaf thickness in tomato. Next, we queried the transcriptomes and inferred Dynamic Bayesian Networks of gene expression across early leaf ontogeny in these lines to compare the molecular networks that pattern leaf thickness. We show that thick ILs share S. pennellii-like expression profiles for putative regulators of cell shape and meristem determinacy, as well as a general signature of cell cycle related gene expression. However, our network data suggest that leaf thickness in these two lines is patterned by at least partially distinct mechanisms. Consistent with this hypothesis, double homozygote lines combining introgression segments from these two ILs show additive phenotypes including thick leaves, higher ploidy levels and larger palisade mesophyll cells. Collectively, these data establish a framework of genetic, anatomical, and molecular mechanisms that pattern leaf thickness in desert-adapted tomato.

plant biology↗