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1.
Proc Natl Acad Sci U S A ; 120(3): e2210300120, 2023 01 17.
Artículo en Inglés | MEDLINE | ID: mdl-36634142

RESUMEN

Rhizogenic Agrobacterium strains comprise biotrophic pathogens that cause hairy root disease (HRD) on hydroponically grown Solanaceae and Cucurbitaceae crops, besides being widely explored agents for the creation of hairy root cultures for the sustainable production of plant-specialized metabolites. Hairy root formation is mediated through the expression of genes encoded on the T-DNA of the root-inducing (Ri) plasmid, of which several, including root oncogenic locus B (rolB), play a major role in hairy root development. Despite decades of research, the exact molecular function of the proteins encoded by the rol genes remains enigmatic. Here, by means of TurboID-mediated proximity labeling in tomato (Solanum lycopersicum) hairy roots, we identified the repressor proteins TOPLESS (TPL) and Novel Interactor of JAZ (NINJA) as direct interactors of RolB. Although these interactions allow RolB to act as a transcriptional repressor, our data hint at another in planta function of the RolB oncoprotein. Hence, by a series of plant bioassays, transcriptomic and DNA-binding site enrichment analyses, we conclude that RolB can mitigate the TPL functioning so that it leads to a specific and partial reprogramming of phytohormone signaling, immunity, growth, and developmental processes. Our data support a model in which RolB manipulates host transcription, at least in part, through interaction with TPL, to facilitate hairy root development. Thereby, we provide important mechanistic insights into this renowned oncoprotein in HRD.


Asunto(s)
Agrobacterium , Proteínas Represoras , Proteínas Represoras/genética , Proteínas Represoras/metabolismo , Agrobacterium/genética , Agrobacterium/metabolismo , Plásmidos , Productos Agrícolas/genética , Inmunidad de la Planta , Raíces de Plantas/metabolismo
2.
Plant J ; 117(1): 280-301, 2024 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-37788349

RESUMEN

Gene regulatory networks (GRNs) represent the interactions between transcription factors (TF) and their target genes. Plant GRNs control transcriptional programs involved in growth, development, and stress responses, ultimately affecting diverse agricultural traits. While recent developments in accessible chromatin (AC) profiling technologies make it possible to identify context-specific regulatory DNA, learning the underlying GRNs remains a major challenge. We developed MINI-AC (Motif-Informed Network Inference based on Accessible Chromatin), a method that combines AC data from bulk or single-cell experiments with TF binding site (TFBS) information to learn GRNs in plants. We benchmarked MINI-AC using bulk AC datasets from different Arabidopsis thaliana tissues and showed that it outperforms other methods to identify correct TFBS. In maize, a crop with a complex genome and abundant distal AC regions, MINI-AC successfully inferred leaf GRNs with experimentally confirmed, both proximal and distal, TF-target gene interactions. Furthermore, we showed that both AC regions and footprints are valid alternatives to infer AC-based GRNs with MINI-AC. Finally, we combined MINI-AC predictions from bulk and single-cell AC datasets to identify general and cell-type specific maize leaf regulators. Focusing on C4 metabolism, we identified diverse regulatory interactions in specialized cell types for this photosynthetic pathway. MINI-AC represents a powerful tool for inferring accurate AC-derived GRNs in plants and identifying known and novel candidate regulators, improving our understanding of gene regulation in plants.


Asunto(s)
Arabidopsis , Redes Reguladoras de Genes , Redes Reguladoras de Genes/genética , Cromatina/genética , Cromatina/metabolismo , Regulación de la Expresión Génica de las Plantas/genética , Factores de Transcripción/genética , Factores de Transcripción/metabolismo , Arabidopsis/genética , Arabidopsis/metabolismo , Plantas/metabolismo
3.
Plant Physiol ; 193(3): 1933-1953, 2023 Oct 26.
Artículo en Inglés | MEDLINE | ID: mdl-37345955

RESUMEN

Thousands of long intergenic noncoding RNAs (lincRNAs) have been identified in plant genomes. While some lincRNAs have been characterized as important regulators in different biological processes, little is known about the transcriptional regulation for most plant lincRNAs. Through the integration of 8 annotation resources, we defined 6,599 high-confidence lincRNA loci in Arabidopsis (Arabidopsis thaliana). For lincRNAs belonging to different evolutionary age categories, we identified major differences in sequence and chromatin features, as well as in the level of conservation and purifying selection acting during evolution. Spatiotemporal gene expression profiles combined with transcription factor (TF) chromatin immunoprecipitation (ChIP) data were used to construct a TF-lincRNA regulatory network containing 2,659 lincRNAs and 15,686 interactions. We found that properties characterizing lincRNA expression, conservation, and regulation differ between plants and animals. Experimental validation confirmed the role of 3 TFs, KANADI 1, MYB DOMAIN PROTEIN 44, and PHYTOCHROME INTERACTING FACTOR 4, as key regulators controlling root-specific lincRNA expression, demonstrating the predictive power of our network. Furthermore, we identified 58 lincRNAs, regulated by these TFs, showing strong root cell type-specific expression or chromatin accessibility, which are linked with genome-wide association studies genetic associations related to root system development and growth. The multilevel genome-wide characterization covering chromatin state information, promoter conservation, and chromatin immunoprecipitation-based TF binding, for all detectable lincRNAs across 769 expression samples, permits rapidly defining the biological context and relevance of Arabidopsis lincRNAs through regulatory networks.


Asunto(s)
Proteínas de Arabidopsis , Arabidopsis , Fitocromo , ARN Largo no Codificante , Animales , Arabidopsis/genética , Arabidopsis/metabolismo , Proteínas de Arabidopsis/genética , Cromatina/genética , Estudio de Asociación del Genoma Completo , Fitocromo/genética , ARN Largo no Codificante/genética , ARN Largo no Codificante/metabolismo , Factores de Transcripción/genética
4.
Nucleic Acids Res ; 50(D1): D165-D173, 2022 01 07.
Artículo en Inglés | MEDLINE | ID: mdl-34850907

RESUMEN

JASPAR (http://jaspar.genereg.net/) is an open-access database containing manually curated, non-redundant transcription factor (TF) binding profiles for TFs across six taxonomic groups. In this 9th release, we expanded the CORE collection with 341 new profiles (148 for plants, 101 for vertebrates, 85 for urochordates, and 7 for insects), which corresponds to a 19% expansion over the previous release. We added 298 new profiles to the Unvalidated collection when no orthogonal evidence was found in the literature. All the profiles were clustered to provide familial binding profiles for each taxonomic group. Moreover, we revised the structural classification of DNA binding domains to consider plant-specific TFs. This release introduces word clouds to represent the scientific knowledge associated with each TF. We updated the genome tracks of TFBSs predicted with JASPAR profiles in eight organisms; the human and mouse TFBS predictions can be visualized as native tracks in the UCSC Genome Browser. Finally, we provide a new tool to perform JASPAR TFBS enrichment analysis in user-provided genomic regions. All the data is accessible through the JASPAR website, its associated RESTful API, the R/Bioconductor data package, and a new Python package, pyJASPAR, that facilitates serverless access to the data.


Asunto(s)
Bases de Datos Genéticas , Genómica/clasificación , Programas Informáticos , Factores de Transcripción/genética , Animales , Sitios de Unión/genética , Biología Computacional , Genoma/genética , Humanos , Ratones , Plantas/genética , Unión Proteica/genética , Factores de Transcripción/clasificación , Vertebrados/genética
5.
J Exp Bot ; 72(22): 7927-7941, 2021 12 04.
Artículo en Inglés | MEDLINE | ID: mdl-34387350

RESUMEN

Activation of cell-surface and intracellular receptor-mediated immunity results in rapid transcriptional reprogramming that underpins disease resistance. However, the mechanisms by which co-activation of both immune systems lead to transcriptional changes are not clear. Here, we combine RNA-seq and ATAC-seq to define changes in gene expression and chromatin accessibility. Activation of cell-surface or intracellular receptor-mediated immunity, or both, increases chromatin accessibility at induced defence genes. Analysis of ATAC-seq and RNA-seq data combined with publicly available information on transcription factor DNA-binding motifs enabled comparison of individual gene regulatory networks activated by cell-surface or intracellular receptor-mediated immunity, or by both. These results and analyses reveal overlapping and conserved transcriptional regulatory mechanisms between the two immune systems.


Asunto(s)
Cromatina , Redes Reguladoras de Genes , Resistencia a la Enfermedad , Humanos , Factores de Transcripción/genética
6.
Methods Mol Biol ; 2698: 323-349, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-37682483

RESUMEN

Gene regulatory networks (GRNs) represent the regulatory links between transcription factors (TF) and their target genes. In plants, they are essential to understand transcriptional programs that control important agricultural traits such as yield or (a)biotic stress response. Although several high- and low-throughput experimental methods have been developed to map GRNs in plants, these are sometimes expensive, come with laborious protocols, and are not always optimized for tomato, one of the most important horticultural crops worldwide. In this chapter, we present a computational method that covers two protocols: one protocol to map gene identifiers between two different tomato genome assemblies, and another protocol to predict putative regulators and delineate GRNs given a set of functionally related or coregulated genes by exploiting publicly available TF-binding information. As an example, we applied the motif enrichment protocol on tomato using upregulated genes in response to jasmonate, as well as upregulated and downregulated genes in plants with genotypes OENAM1 and nam1, respectively. We found that our protocol accurately infers the expected TFs as top enriched regulators and identifies GRNs functionally enriched in biological processes related with the experimental context under study.


Asunto(s)
Redes Reguladoras de Genes , Solanum lycopersicum , Factores de Transcripción/genética , Solanum lycopersicum/genética , Regulación de la Expresión Génica , Sitios de Unión
7.
Mol Plant ; 15(11): 1807-1824, 2022 11 07.
Artículo en Inglés | MEDLINE | ID: mdl-36307979

RESUMEN

Multicellular organisms, such as plants, are characterized by highly specialized and tightly regulated cell populations, establishing specific morphological structures and executing distinct functions. Gene regulatory networks (GRNs) describe condition-specific interactions of transcription factors (TFs) regulating the expression of target genes, underpinning these specific functions. As efficient and validated methods to identify cell-type-specific GRNs from single-cell data in plants are lacking, limiting our understanding of the organization of specific cell types in both model species and crops, we developed MINI-EX (Motif-Informed Network Inference based on single-cell EXpression data), an integrative approach to infer cell-type-specific networks in plants. MINI-EX uses single-cell transcriptomic data to define expression-based networks and integrates TF motif information to filter the inferred regulons, resulting in networks with increased accuracy. Next, regulons are assigned to different cell types, leveraging cell-specific expression, and candidate regulators are prioritized using network centrality measures, functional annotations, and expression specificity. This embedded prioritization strategy offers a unique and efficient means to unravel signaling cascades in specific cell types controlling a biological process of interest. We demonstrate the stability of MINI-EX toward input data sets with low number of cells and its robustness toward missing data, and show that it infers state-of-the-art networks with a better performance compared with other related single-cell network tools. MINI-EX successfully identifies key regulators controlling root development in Arabidopsis and rice, leaf development in Arabidopsis, and ear development in maize, enhancing our understanding of cell-type-specific regulation and unraveling the roles of different regulators controlling the development of specific cell types in plants.


Asunto(s)
Arabidopsis , Redes Reguladoras de Genes , Redes Reguladoras de Genes/genética , Arabidopsis/genética , Arabidopsis/metabolismo , Factores de Transcripción/genética , Factores de Transcripción/metabolismo , Transcriptoma
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