Biology subjects

Cortijo, S.

Publications and source records attributed to Cortijo, S..

10 recordsLinked to original sources

bioRxiv2026

Regulatory architecture tunes gene expression noise in the plant heat shock response

Cells within the same tissue can respond differently to the same stress, yet how gene regulatory networks generate and control this variability remains unclear. Here, we show that cell-to-cell variation in the Arabidopsis heat shock response is coordinated across the heat shock regulon and that the distribution of responses is tuned by the underlying regulatory network. Imaging of an HSP70 promoter reporter revealed basal activity in a subset of root cells and heterogeneous induction after heat shock, with some cells remaining near pre-stress expression levels. Dual reporters showed strong coordination between independently integrated HSP70 reporter loci, consistent with substantial shared upstream regulatory variation. Single-nucleus RNA sequencing confirmed heterogeneous but coordinated activation of heat shock genes across root cell types. Stronger heat shock states at both ambient and heat stress temperatures were associated with a recurrent thermoprotective programme across root cell populations, whereas weak responders after heat shock were associated with distinct cell-type specific transcriptional programmes, including defence- and jasmonate-associated states in some root cell types. Stochastic modelling suggested that HSFA2-dependent amplification could broaden the distribution of HSP70 expression across cells. Consistent with this prediction, experiments showed that loss of HSFA2 reduced HSP70 induction and lowered cell-to-cell variability after controlling for differences in mean expression. Together, these results show that the plant heat shock network controls both the magnitude and distribution of stress-responsive gene expression across cells.

plant biology↗

bioRxiv2025

Establishment, maintenance and consequences of inter-individual transcriptional variability for a gene involved in nitrate nutrition in plants

Differences in phenotypes and gene expression are observed between genetically identical plants grown in the same environment. While we now have a good knowledge of the source and consequences of transcriptional differences observed between cells, in particular in unicellular organisms, it is still very scarce when it comes to variability between multicellular organisms. Using NRT2.1, a high affinity nitrate transporter gene, as a model for high inter-individual transcriptional variability, we showed that differences in expression between plants for that gene are established in young seedlings, maintained over time but not transmitted to the next generation. Our results also indicate that these differences in expression could have phenotypic consequences. Indeed, they can explain phenotypic variability for the root growth as well as the amount of nitrate imported by the NRT2.1 protein in the plant. Finally, we found an enrichment for genes involved in photosynthesis among the ones with an expression correlated with NRT2.1 in single seedlings. All in all, our study suggests that a global coordination of the genes involved in the carbon/nitrate balance in plants is established in young seedlings, with differences in this state between plants, and then maintained over time.

plant biology↗

bioRxiv2020

Tunable phenotypic variability through an autoregulatory alternative sigma factor circuit

Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σV circuit in B. subtilis generates functional phenotypic variability that can be tuned by stress level, environmental history, and genetic perturbations. Using single-cell time-lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σV under lysozyme stress depends on stress level and on a memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the sigV operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma-anti-sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗

bioRxiv2020

Co-expression networks from gene expression variability between genetically identical seedlings can reveal novel regulatory relationships

Co-expression networks are a powerful tool to understand gene regulation. They have been used to identify new regulation and function of genes involved in plant development and their response to the environment. Up to now, co-expression networks have been inferred using transcriptomes generated on plants experiencing genetic or environmental perturbation, or from expression time series. We propose a new approach by showing that co-expression networks can be constructed in the absence of genetic and environmental perturbation, for plants at the same developmental stage. For this we used transcriptomes that were generated from genetically identical individual plants that were grown in the same conditions and for the same amount of time. Twelve time points were used to cover the 24h light/dark cycle. We used variability in gene expression between individual plants of the same time point to infer a co-expression network. We show that this network is biologically relevant and use it to suggest new gene functions and to identify new targets for the transcription factors GI, PIF4 and PRR5. Moreover, we find different co-regulation in this network based on changes in expression between individual plants, compared to the usual approach requiring environmental perturbation. Our work shows that gene co-expression networks can be identified using variability in gene expression between individual plants, without the need for genetic or environmental perturbations. It will allow further exploration of gene regulation in contexts with subtle differences between plants, which could be closer to what individual plants in a population might face in the wild. Author summaryPlant development and response to changes in the environment are strongly regulated at the level of gene expression. That is why understanding how gene expression is regulated is key, and transcriptome approaches have allowed the analysis of transcription for all genes of the genome. Extracting useful information from the high amount of data generated by transcriptomes is a challenge, and gene co-expression networks are a powerful tool to do this. The principle is to find genes that co-vary in expression in different conditions and to pair them together. Communities of genes that are more closely linked are then identified and this is the starting point to look for their implication in the same pathway. Co-expression networks have been used to identify new regulation and function of genes involved in plant development and their response to the environment. They were constructed using transcriptomes generated on plants experiencing genetic or environmental perturbation. We show that co-expression networks can in fact be constructed in the absence of genetic and environmental perturbation. Our work will allow further exploration of gene co-regulation in contexts with subtle differences between plants, which could be closer to what individual plants in a population might face in the wild.

plant biology↗

bioRxiv2019

DEK influences the trade-off between growth and arrest via H2A.Z-nucleosomes in Arabidopsis

The decision of whether to grow and proliferate or to restrict growth and develop resilience to stress is a key biological trade-off. In plants, constitutive growth results in increased sensitivity to environmental stress1,2. The underlying mechanisms controlling this decision are however not well understood. We used temperature as a cue to discover regulators of this process in plants, as it both enhances growth and development rates within a specific range and is also a stress at extremes. We found that the conserved chromatin-associated protein DEK plays a central role in balancing the response between growth and arrest in Arabidopsis, and it does this via H2A.Z-nucleosomes. DEK target genes show two distinct categories of chromatin architecture based on the distribution of H2A.Z in +1 nucleosome and gene body, and these predict induction or repression by DEK. We show that these chromatin signatures of DEK target genes are conserved in human cells, suggesting that DEK may act through an evolutionarily conserved mechanism to control the balance between growth and arrest in plants and animals.

plant biology↗

bioRxiv2019

From bud formation to flowering: transcriptomic state defines the cherry developmental phases of sweet cherry bud dormancy

BackgroundBud dormancy is a crucial stage in perennial trees and allows survival over winter to ensure optimal flowering and fruit production. Recent work highlighted physiological and molecular events occurring during bud dormancy in trees. However, they usually examined bud development or bud dormancy in isolation. In this work, we aimed to further explore the global transcriptional changes happening throughout bud development and dormancy onset, progression and release.\n\nResultsUsing next-generation sequencing and modelling, we conducted an in-depth transcriptomic analysis for all stages of flower buds in several sweet cherry (Prunus avium L.) cultivars that are characterized for their contrasted dates of dormancy release. We find that buds in organogenesis, paradormancy, endodormancy and ecodormancy stages are defined by the expression of genes involved in specific pathways, and these are conserved between different sweet cherry cultivars. In particular, we found that DORMANCY ASSOCIATED MADS-box (DAM), floral identity and organogenesis genes are up-regulated during the pre-dormancy stages while endodormancy is characterized by a complex array of signalling pathways, including cold response genes, ABA and oxidation-reduction processes. After dormancy release, genes associated with global cell activity, division and differentiation are activated during ecodormancy and growth resumption. We then went a step beyond the global transcriptomic analysis and we developed a model based on the transcriptional profiles of just seven genes to accurately predict the main bud dormancy stages.\n\nConclusionsOverall, this study has allowed us to better understand the transcriptional changes occurring throughout the different phases of flower bud development, from bud formation in the summer to flowering in the following spring. Our work sets the stage for the development of fast and cost effective diagnostic tools to molecularly define the dormancy stages. Such integrative approaches will therefore be extremely useful for a better comprehension of complex phenological processes in many species.

plant biology↗

bioRxiv2018

Hormonal balance finely tunes dormancy status in sweet cherry flower buds

In temperate trees, optimal timing and quality of flowering directly depend on adequate winter dormancy progression, regulated by a combination of chilling and warm temperatures. Physiological, genetic and functional genomic studies have shown that hormones play a key role in bud dormancy establishment, maintenance and release. We combined physiological, transcriptional analyses, quantification of abscisic acid (ABA) and gibberellins (GAs), and modelling to further investigate how these signaling pathways are associated with dormancy progression in the flower buds of two sweet cherry cultivars. Our results demonstrated that GA-associated pathways have distinct functions and may be differentially related with dormancy. In addition, ABA levels rise at the onset of dormancy, associated with enhanced expression of ABA biosynthesis PavNCED genes, and decreased prior to dormancy release. Following the observations that ABA levels are correlated with dormancy depth, we identified PavUG71B6, a sweet cherry UDP-GLYCOSYLTRANSFERASE gene that up-regulates active catabolism of ABA to ABA-GE and may be associated with low ABA content in the early cultivar. Subsequently, we modelled ABA content and dormancy behavior in three cultivars based on the expression of a small set of genes regulating ABA levels. These results strongly suggest the central role of ABA pathway in the control of dormancy progression and open up new perspectives for the development of molecular-based phenological modelling.

plant biology↗

bioRxiv2018

Widespread inter-individual gene expression variability in Arabidopsis thaliana

A fundamental question in biology is how gene expression is regulated to give rise to a phenotype. However, transcriptional variability is rarely considered and could influence the relationship between genotype and phenotype. It is known in unicellular organisms that gene expression is often noisy rather than uniform and this has been proposed to be beneficial when environmental conditions are unpredictable. However, little is known about transcriptional variability in plants. Using transcriptomic approaches, we analysed gene expression variability between individual Arabidopsis thaliana plants growing in identical conditions over a 24 hour time-course. We identified hundreds of genes that exhibit high inter-individual variability and found that many are involved in environmental responses. We also identified factors that might facilitate gene expression variability, such as gene length, the number of transcription factors regulating the genes and the chromatin environment. These results shed new light on the impact of transcriptional variability in gene expression regulation in plants.

plant biology↗

bioRxiv2018

Chromatin immunoprecipitation-sequencing and RNA-sequencing for complex and low-abundance tree buds

Chromatin immunoprecipitation-sequencing (ChIP-seq) is a robust technique to study interactions between proteins, such as histones or transcription factors, and DNA. This technique in combination with RNA-sequencing (RNA-seq) is a powerful tool to better understand biological processes in eukaryotes. We developed a combined ChIP-seq and RNA-seq protocol for tree buds (Prunus avium L., Prunus persica L Batch, Malus x domestica Borkh.) that has also been successfully tested on Arabidopsis thaliana and Saccharomyces cerevisiae. Tree buds contain phenolic compounds that negatively interfere with ChIP and RNA extraction. In addition to solving this problem, our protocol is optimised to work on small amounts of material. Furthermore, one of the advantages of this protocol is that samples for ChIP-seq are cross-linked after flash freezing, making it possible to work on trees growing in the field and to perform ChIP-seq and RNA-seq on the same starting material. Focusing on dormant buds in sweet cherry, we explored the link between expression level and H3K4me3 enrichment for all genes, including a strong correlation between H3K4me3 enrichment at the DORMANCY-ASSOCIATED MADS-box 5 (PavDAM5) loci and its expression pattern. This protocol will allow analysis of chromatin and transcriptomic dynamics in tree buds, notably during its development and response to the environment.

plant biology↗

bioRxiv2017

The G-box transcriptional regulatory code in Arabidopsis

Plants have significantly more transcription factor (TF) families than animals and fungi, and plant TF families tend to contain more genes--these expansions are linked to adaptation to environmental stressors (1, 2). Many TF family members bind to similar or identical sequence motifs, such as G-boxes (CACGTG), so it is difficult to predict regulatory relationships. We determine that the flanking sequences near G-boxes help determine in vitro specificity, but that this is insufficient to predict the transcription pattern of genes near G-boxes. Therefore, we construct a gene regulatory network that identifies the set of bZIPs and bHLHs that are most predictive of the gene expression of genes downstream of perfect G-boxes. This network accurately predicts transcriptional patterns and reconstructs known regulatory subnetworks. Finally, we present Ara-BOX-cis (araboxcis.org), a website that provides interactive visualisations of the G-box regulatory network, a useful resource for generating predictions for gene regulatory relations.

plant biology↗