ArticleBMC plant biology2014
Regulatory network rewiring for secondary metabolism in Arabidopsis thaliana under various conditions.
Article in BMC plant biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Article
- Plant-microbe interactions in the rhizosphere via a circular metabolic economy.The Plant cell · 2022Review
- Both Binding Strength and Evolutionary Accessibility Affect the Population Frequency of Transcription Factor Binding Sequences in Arabidopsis thaliana.Genome biology and evolution · 2021Article
- Identification of biological pathway and process regulators using sparse partial least squares and triple-gene mutual interaction.Scientific reports · 2021Article
- Characterizing the Role of the miR156-SPL Network in Plant Development and Stress Response.Plants (Basel, Switzerland) · 2020Review
- Gene Regulatory Network Inference: Connecting Plant Biology and Mathematical Modeling.Frontiers in genetics · 2020Review
- TGMI: an efficient algorithm for identifying pathway regulators through evaluation of triple-gene mutual interaction.Nucleic acids research · 2018Article
- Targeted and Untargeted Metabolic Profiling of Wild Grassland Plants identifies Antibiotic and Anthelmintic Compounds Targeting Pathogen Physiology, Metabolism and Reproduction.Scientific reports · 2018Article
- Metabolite profiling and associated gene expression reveal two metabolic shifts during the seed-to-seedling transition in Arabidopsis thaliana.Plant molecular biology · 2017Article
- Large-scale transcriptome analysis reveals arabidopsis metabolic pathways are frequently influenced by different pathogens.Plant molecular biology · 2017Article
- De novo transcriptome analysis of rose-scented geranium provides insights into the metabolic specificity of terpene and tartaric acid biosynthesis.BMC genomics · 2017Article
- Article
- Molecular and physiological responses to titanium dioxide and cerium oxide nanoparticles in Arabidopsis.Environmental toxicology and chemistry · 2017Article
- Article
- Differential Coexpression Analysis Reveals Extensive Rewiring of Arabidopsis Gene Coexpression in Response to Pseudomonas syringae Infection.Scientific reports · 2016Article
- Transcriptome exploration for further understanding of the tropane alkaloids biosynthesis in Anisodus acutangulus.Molecular genetics and genomics : MGG · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPlant secondary metabolites are critical to various biological processes. However, the regulations of these metabolites are complex because of regulatory rewiring or crosstalk. To unveil how regulatory behaviors on secondary metabolism reshape biological processes, we constructed and analyzed a dynamic regulatory network of secondary metabolic pathways in Arabidopsis.
resultsThe dynamic regulatory network was constructed through integrating co-expressed gene pairs and regulatory interactions. Regulatory interactions were either predicted by conserved transcription factor binding sites (TFBSs) or proved by experiments. We found that integrating two data (co-expression and predicted regulatory interactions) enhanced the number of highly confident regulatory interactions by over 10% compared with using single data. The dynamic changes of regulatory network systematically manifested regulatory rewiring to explain the mechanism of regulation, such as in terpenoids metabolism, the regulatory crosstalk of RAV1 (AT1G13260) and ATHB1 (AT3G01470) on HMG1 (hydroxymethylglutaryl-CoA reductase, AT1G76490); and regulation of RAV1 on epoxysqualene biosynthesis and sterol biosynthesis. Besides, we investigated regulatory rewiring with expression, network topology and upstream signaling pathways. Regulatory rewiring was revealed by the variability of genes' expression: pathway genes and transcription factors (TFs) were significantly differentially expressed under different conditions (such as terpenoids biosynthetic genes in tissue experiments and E2F/DP family members in genotype experiments). Both network topology and signaling pathways supported regulatory rewiring. For example, we discovered correlation among the numbers of pathway genes, TFs and network topology: one-gene pathways (such as δ-carotene biosynthesis) were regulated by a fewer TFs, and were not critical to metabolic network because of their low degrees in topology. Upstream signaling pathways of 50 TFs were identified to comprehend the underlying mechanism of TFs' regulatory rewiring.
conclusionOverall, this dynamic regulatory network largely improves the understanding of perplexed regulatory rewiring in secondary metabolism in Arabidopsis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.