ArticleScientific reports2020
Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 36 citations in OpenAlex.
- Mitochondrial glutamine synthetase overexpression in tomato source leaves increases assimilate export and fruit yield.The Plant cell · 2026Article
- Synthetic biology and artificial intelligence in crop improvement.Plant communications · 2025Review
- Same, yet different: towards understanding nutrient use in hemp- and drug-type Cannabis.Journal of experimental botany · 2025Review
- A Comparative Analysis of XGBoost and Neural Network Models for Predicting Some Tomato Fruit Quality Traits from Environmental and Meteorological Data.Plants (Basel, Switzerland) · 2024Article
- Genetic architecture of fresh-market tomato yield.BMC plant biology · 2023Article
- A comparative transcriptomics and eQTL approach identifies SlWD40 as a tomato fruit ripening regulator.Plant physiology · 2022Article
- Development of a facile genetic transformation system for the Spanish elite rice paella genotype Bomba.Transgenic research · 2022Article
- Exploring Genotype-by-Environment Interactions of Chemical Composition of Raspberry by Using a Metabolomics Approach.Metabolites · 2021Article
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Authors and funding
11 authors at 5 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The capacity to assimilate carbon and nitrogen, to transport the resultant sugars and amino acids to sink tissues, and to convert the incoming sugars and amino acids into storage compounds in the sink tissues, are key determinants of crop yield. Given that all of these processes have the potential to co-limit growth, multiple genetic interventions in source and sink tissues, plus transport processes may be necessary to reach the full yield potential of a crop. We used biolistic combinatorial co-transformation (up to 20 transgenes) for increasing C and N flows with the purpose of increasing tomato fruit yield. We observed an increased fruit yield of up to 23%. To better explore the reconfiguration of metabolic networks in these transformants, we generated a dataset encompassing physiological parameters, gene expression and metabolite profiling on plants grown under glasshouse or polytunnel conditions. A Sparse Partial Least Squares regression model was able to explain the combination of genes that contributed to increased fruit yield. This combinatorial study of multiple transgenes targeting primary metabolism thus offers opportunities to probe the genetic basis of metabolic and phenotypic variation, providing insight into the difficulties in choosing the correct combination of targets for engineering increased fruit yield.
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