ArticleFrontiers in plant science2014
Transcript abundance on its own cannot be used to infer fluxes in central metabolism.
Article in Frontiers in plant science, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
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- Sustainable software development in science - insights from 20 years of Vanted.Journal of integrative bioinformatics · 2025Article
- Triacylglycerol stability limits futile cycles and inhibition of carbon capture in oil-accumulating leaves.Plant physiology · 2025Article
- Metabolic modeling reveals distinct roles of sugars and carboxylic acids in stomatal opening as well as unexpected carbon fluxes.The Plant cell · 2024Article
- Mechanisms of metabolic adaptation in the duckweed Lemna gibba: an integrated metabolic, transcriptomic and flux analysis.BMC plant biology · 2023Article
- Transcriptome-based identification and functional characterization of iridoid synthase involved in monotropein biosynthesis in blueberry.Plant direct · 2023Article
- Analysis of companion cell and phloem metabolism using a transcriptome-guided model of Arabidopsis metabolism.Plant physiology · 2023Article
- Causes and consequences of endogenous hypoxia on growth and metabolism of developing maize kernels.Plant physiology · 2023Article
- Polyunsaturated Fatty Acids: Conversion to Lipid Mediators, Roles in Inflammatory Diseases and Dietary Sources.International journal of molecular sciences · 2023Review
- Accurate flux predictions using tissue-specific gene expression in plant metabolic modeling.Bioinformatics (Oxford, England) · 2023Article
- Ectopic expression of theFrontiers in plant science · 2023Article
- Glucose-6-P/phosphate translocator2 mediates the phosphoglucose-isomerase1-independent response to microbial volatiles.Plant physiology · 2022Article
- Assessing the intracellular primary metabolic profile ofFrontiers in fungal biology · 2022Article
- Transcriptome Analysis and Identification of Lipid Genes inInternational journal of molecular sciences · 2021Article
- The Contribution of Metabolomics to Systems Biology: Current Applications Bridging Genotype and Phenotype in Plant Science.Advances in experimental medicine and biology · 2021Article
- Toxicant-Induced Metabolic Alterations in Lipid and Amino Acid Pathways Are Predictive of Acute Liver Toxicity in Rats.International journal of molecular sciences · 2020Article
- Reorganization of Acyl Flux through the Lipid Metabolic Network in Oil-Accumulating Tobacco Leaves.Plant physiology · 2020Article
- Gene Networks Underlying Cannabinoid and Terpenoid Accumulation in Cannabis.Plant physiology · 2019Article
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14 authors.
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No grant is acknowledged in the PubMed record.
Abstract
An attempt has been made to define the extent to which metabolic flux in central plant metabolism is reflected by changes in the transcriptome and metabolome, based on an analysis of in vitro cultured immature embryos of two oilseed rape (Brassica napus) accessions which contrast for seed lipid accumulation. Metabolic flux analysis (MFA) was used to constrain a flux balance metabolic model which included 671 biochemical and transport reactions within the central metabolism. This highly confident flux information was eventually used for comparative analysis of flux vs. transcript (metabolite). Metabolite profiling succeeded in identifying 79 intermediates within the central metabolism, some of which differed quantitatively between the two accessions and displayed a significant shift corresponding to flux. An RNA-Seq based transcriptome analysis revealed a large number of genes which were differentially transcribed in the two accessions, including some enzymes/proteins active in major metabolic pathways. With a few exceptions, differential activity in the major pathways (glycolysis, TCA cycle, amino acid, and fatty acid synthesis) was not reflected in contrasting abundances of the relevant transcripts. The conclusion was that transcript abundance on its own cannot be used to infer metabolic activity/fluxes in central plant metabolism. This limitation needs to be borne in mind in evaluating transcriptome data and designing metabolic engineering experiments.
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