Gene Regulatory Networks controlling Arabidopsis Root Stem Cells

Conferencia sobre aproximaciones sistémicas al conocimiento biológicoGene Regulatory Networks controlling Arabidopsis Root Stem Cells Identifying the transcription factors (TFs) and associated regulatory processes involved in stem cell regulation is key for understanding the initiation and growth of tissues and organs. Although many TFs have been described in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. We used a systems biology approach to predict interactions among the genes involved in stem cell identity and maintenance. We first transcriptionally profiled four stem cell populations and developed a gene regulatory network (GRN) inference algorithm, GENIST, which combines spatial and temporal transcriptomic datasets to identify important TFs and infer gene-to-gene interactions. Our approach resulted in a map of gene interactions that orchestrates the transcriptional regulation of stem cells. In addition to linking known stem cell factors, our resulting GRNs predicted additional TFs involved in stem cell identity and maintenance. We mathematically modeled and experimentally validated some of our predicted transcription factors, which confirmed the robustness of our algorithm and our resulting networks. Our approach resulted in the finding of a factor, PERIANTHIA (PAN), which may play an important role in stem cell maintenance and QC function. We then developed an imaging system to perform in vivo, long-term imaging experiments that will be used to understand the dynamics of the regulatory interactions between PAN and its downstream TFs in a cell-specific manner. For this, we designed and 3-D printed a Multi-sample Arabidopsis Growth and Imaging Chamber (MAGIC) that provides near-physiological imaging conditions and allows high-throughput time-course imaging experiments in the ZEISS Lightsheet Z.1. We showed MAGIC’s imaging capabilities by following cell divisions, as an indicator of plant growth and development, over prolonged time periods, and demonstrated that plants imaged with our chamber undergo cell divisions for >16 times longer than those with the glass capillary system supplied by the ZEISS Z1. Future in vivo observations of the expression of PAN and its predicted downstream factors will be key to refine our model predictions and obtain information about the dynamics of the regulatory processes. Our systems biology approach illustrates the strength of integrating computational and technological tools into the experimental approaches to solve key biological questions. We anticipate that our algorithm and our approach can be applied to solve similar problems in a diverse number of systems, which can result in unsupervised predictions of gene functions and gene candidates.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Machine learning can guide experimental approaches for protein digestibility estimations

Food protein digestibility and bioavailability are critical aspects in addressing human nutritional demands, particularly when seeking sustainable alternatives to animal-based proteins. In this study, we propose a machine learning approach to predict the true ileal digestibility coefficient of food items. The model makes use of a unique curated dataset that combines nutritional information from different foods with FASTA sequences of some of their protein families. We extracted the biochemical properties of the proteins and combined these properties with embeddings from a Transformer-based protein Language Model (pLM). In addition, we used SHAP to identify features that contribute most to the model prediction and provide interpretability. This first AI-based model for predicting food protein digestibility has an accuracy of 90% compared to existing experimental techniques. With this accuracy, our model can eliminate the need for lengthy in-vivo or in-vitro experiments, making the process of creating new foods faster, cheaper, and more ethical.Comment: 50 pages, submitted to Nature Foo

Deciphering Strawberry Ripening by Tissue Specific Gene Regulatory Networks

During ripening, fruits undergo a number of metabolic and physiological changes leading to softening and improvement of characters such as flavor and palatability. Insights into transcriptome changes during strawberry fruit ripening have been reported, but always using either complete fruits in the analysis or separating achenes and the fleshy part (receptacle). However, the receptacle is composed of heterogeneous cell types, each of them with different characteristics and functions. Hence, transcriptomic studies performed so far may have lost important regulatory elements which expression is low but important in a specific cell-type specific. In our study, we use Laser Capture Microdissection (LCM) technique for the isolation of cells from specific tissue types such as the epidermis, vascular bundles, cortex, and pith. Transcriptome profiling of these tissue types was performed by RNAseq. A gene co-expression analysis was performed by Weighted Correlation Network Analysis (WGCNA). Ontology analysis of each module showed wax biosynthesis as the main biological pathway enriched at the red epidermis specific module. In order to elucidate the putative regulatory elements that control the synthesis of waxes in this tissue, a Gene Regulatory Network (GRN) was generated using GENIST (de Luis Balaguer, 2017). As a result, we have identified a set of transcription factors that might regulate the expression of eceriferum genes and a fatty acid elongase necessary for wax biosynthesis in ripe epidermis. Ultimately, our results open the possibility of implementing novel targeted breeding approaches. Moreover, this work shows that LCM followed by RNAseq is a powerful tool that can be used to clarify the regulatory scenario of tissue-specific biological processes during strawberry ripening.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Transcriptional regulatory network controlling strawberry fruit ripening and quality

Ripening is a critical step for the development of flavor quality in fruits. This character has significantly declined in many fleshy fruits over recent decades. This is particularly significant in strawberry (Fragaria × ananassa), where current cultivars are derived from a narrow germplasm collection. Improving fruit quality requires two important breakthroughs: 1) a precise understanding of the fruit ripening process that will allow the targeting of relevant genes, and 2) the identification of novel alleles responsible for fruit quality traits. In our project, we aim at the identification and characterization of key transcription factors involved in fruit ripening regulation and their target genes, in order to infer the Gene Regulatory Network controlling this process. On the other hand, we are carrying out a Genome-Wide Association Study using a germplasm collection of the woodland strawberry (Fragaria vesca) in order to identify loci involved in important traits such as aroma, fruit size or resistance to pathogens. Finally, we have implemented the use of the genome-editing tool CRISPR/Cas9 in the cultivated strawberry, which we expect it might open opportunities for engineering this species to improve traits of economic importance.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Study of Transcriptional Regulatory Network Controlling Strawberry Fruit Ripening and Quality

Ripening is a critical step for the development of flavor quality in fruits. This character has significantly declined in many fleshy fruits over recent decades. This is particularly significant in strawberry (Fragaria × ananassa), where current cultivars are derived from a narrow germplasm collection. Improving fruit quality requires two important breakthroughs: 1) a precise understanding of the fruit ripening process that will allow the targeting of relevant genes, and 2) the identification of novel alleles responsible for fruit quality traits. In our project we aim at the identification and characterization of key transcription factors involved in fruit ripening regulation and their target genes, in order to infer the Gene Regulatory Network controlling this process. On the other hand, we are carrying out a Genome-Wide Association Study using a germplasm collection of the woodland strawberry (Fragaria vesca) in order to identify loci involved in important traits such as aroma, fruit size, and resistance to pathogens. Finally, we have implemented the use of the genome-editing tool CRISPR/Cas9 in the cultivated strawberry, which we expect to open opportunities for engineering this species to improve traits of economic importance.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Identificación y caracterización de genes implicados en la maduración y la calidad de la fresa

Ripening is a critical step for the development of flavor quality in fruits. This character has significantly declined in many fleshy fruits over recent decades. This is particularly significant in strawberry (Fragaria × ananassa), where current cultivars are derived from a narrow germplasm collection. Improving fruit quality requires two important breakthroughs: 1) a precise understanding of the fruit ripening process that will allow the targeting of relevant genes, and 2) the identification of novel alleles responsible for fruit quality traits. In our project (TRANSFR-Q, Starting Grant-ERC), we aim at the identification and characterization of key transcription factors involved in fruit ripening regulation and their target genes, in order to infer the Gene Regulatory Network controlling this process. On the other hand, we are carrying out a Genome-Wide Association Study using a germplasm collection of the woodland strawberry (Fragaria vesca) in order to identify loci involved in important traits such as aroma, fruit size, and resistance to pathogens. Finally, we have implemented the use of the genome-editing tool CRISPR/Cas9 in the cultivated strawberry, which we expect to open opportunities for engineering this species to improve traits of economic importance.ERC Starting Grant ERC-2014-StG 63813

Characterizing the involvement of FaMADS9 in the regulation of strawberry fruit receptacle development

FaMADS9 is the strawberry (Fragaria x ananassa) gene that exhibits the highest homology to the tomato (Solanum lycopersicum) RIN gene. Transgenic lines were obtained in which FaMADS9 was silenced. The fruits of these lines did not show differences in basic parameters, such as fruit firmness or colour, but exhibited lower Brix values in three of the four independent lines. The gene ontology MapMan category that was most enriched among the differentially expressed genes in the receptacles at the white stage corresponded to the regulation of transcription, including a high percentage of transcription factors and regulatory proteins associated with auxin action. In contrast, the most enriched categories at the red stage were transport, lipid metabolism and cell wall. Metabolomic analysis of the receptacles of the transformed fruits identified significant changes in the content of maltose, galactonic acid-1,4-lactone, proanthocyanidins and flavonols at the green/white stage, while isomaltose, anthocyanins and cuticular wax metabolism were the most affected at the red stage. Among the regulatory genes that were differentially expressed in the transgenic receptacles were several genes previously linked to flavonoid metabolism, such as MYB10, DIV, ZFN1, ZFN2, GT2, and GT5, or associated with the action of hormones, such as abscisic acid, SHP, ASR, GTE7 and SnRK2.7. The inference of a gene regulatory network, based on a dynamic Bayesian approach, among the genes differentially expressed in the transgenic receptacles at the white and red stages, identified the genes KAN1, DIV, ZFN2 and GTE7 as putative targets of FaMADS9. A MADS9-specific CArG box was identified in the promoters of these genes

Cell-by-cell dissection of phloem development links a maturation gradient to cell specialization

Publisher Copyright: Copyright © 2021 The Authors, some rights reserved;In the plant meristem, tissue-wide maturation gradients are coordinated with specialized cell networks to establish various developmental phases required for indeterminate growth. Here, we used single-cell transcriptomics to reconstruct the protophloem developmental trajectory from the birth of cell progenitors to terminal differentiation in the Arabidopsis thaliana root. PHLOEM EARLY DNA-BINDING-WITH-ONE-FINGER (PEAR) transcription factors mediate lineage bifurcation by activating guanosine triphosphatase signaling and prime a transcriptional differentiation program. This program is initially repressed by a meristem-wide gradient of PLETHORA transcription factors. Only the dissipation of PLETHORA gradient permits activation of the differentiation program that involves mutual inhibition of early versus late meristem regulators. Thus, for phloem development, broad maturation gradients interface with cell-type-specific transcriptional regulators to stage cellular differentiation.Peer reviewe

Predicting gene regulatory networks by combining spatial and temporal gene expression data in Arabidopsis root stem cells

Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is essential 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. To accomplish this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network inference algorithm that combines clustering with dynamic Bayesian network inference. We leveraged the topology of our networks to infer potential major regulators. Specifically, through mathematical modeling and experimental validation, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center function. The results presented in this work show that our combination of molecular biology, computational biology, and mathematical modeling is an efficient approach to identify candidate factors that function in the stem cells

DOF2.1 Controls Cytokinin-Dependent Vascular Cell Proliferation Downstream of TMO5/LHW

Smet et al. capture the transcriptional responses upon simultaneous TMO5/LHW induction and identify DOF2.1 as part of the cytokinin-dependent downstream responses. Furthermore, they show that DOF2.1 and its closest homologs control periclinal and radial procambium divisions in distinct zones of this tissue.</p