The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Multi-level engineering facilitates the production of phenylpropanoid compounds in tomato
Open accessAbstract
Phenylpropanoids comprise an important class of plant secondary metabolites. A number of transcription factors have been used to upregulate-specific branches of phenylpropanoid metabolism, but by far the most effective has been the fruit-specific expression of AtMYB12 in tomato, which resulted in as much as 10% of fruit dry weight accumulating as flavonols and hydroxycinnamates. We show that AtMYB12 not only increases the demand of flavonoid biosynthesis but also increases the supply of carbon from primary metabolism, energy and reducing power, which may fuel the shikimate and phenylalanine biosynthetic pathways to supply more aromatic amino acids for secondary metabolism. AtMYB12 directly binds promoters of genes encoding enzymes of primary metabolism. The enhanced supply of precursors, energy and reducing power achieved by AtMYB12 expression can be harnessed to engineer high levels of novel phenylpropanoids in tomato fruit, offering an effective production system for bioactives and other high value ingredients.
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Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp616 · Cited by 41,364
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
Self-citationBioconductor: open software development for computational biology and bioinformatics
Gentleman, R. C., Carey, V. J., Bates, D. M., Bolstad, B., Dettling, M., Dudoit, S., Ellis, B., Gautier, L., Ge, Y., Gentry, J., et al. (2004) · Genome Biology · doi:10.1186/gb-2004-5-10-r80 · Cited by 12,172
Resveratrol improves health and survival of mice on a high-calorie diet
Baur, J. A., Pearson, K. J., Price, N. L., Jamieson, H. A., Lerin, C., Kalra, A., Prabhu, V. V., Allard, J. S., Lopez-Lluch, G., Lewis, K., et al. (2006) · Nature · doi:10.1038/nature05354 · Cited by 4,290
Therapeutic potential of resveratrol: the in vivo evidence
Baur, J. A., & Sinclair, D. A. (2006) · Nature Reviews Drug Discovery · doi:10.1038/nrd2060 · Cited by 3,958
Herrmann, K. M., & Weaver, L. M. (1999) · Annual Review of Plant Physiology and Plant Molecular Biology · doi:10.1146/annurev.arplant.50.1.473 · Cited by 1,320
Butelli, E., Titta, L., Giorgio, M., Mock, H.-P., Matros, A., Peterek, S., Schijlen, E. G. W. M., Hall, R. D., Bovy, A. G., Luo, J., et al. (2008) · Nature Biotechnology · doi:10.1038/nbt.1506 · Cited by 1,238
Self-citationRoessner, U., Luedemann, A., Brust, D., Fiehn, O., Linke, T., Willmitzer, L., & Fernie, A. R. (2001) · The Plant Cell · doi:10.1105/tpc.13.1.11 · Cited by 1,017
Self-citationZhong, S., Fei, Z., Chen, Y.-R., Zheng, Y., Huang, M., Vrebalov, J., McQuinn, R., Gapper, N., Liu, B., Xiang, J., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2462 · Cited by 840
Cited by
Geng, P., Zhang, S., Liu, J., Zhao, C., Wu, J., Cao, Y., Fu, C., Han, X., He, H., & Zhao, Q. (2020) · Plant Physiology · doi:10.1104/pp.19.01070 · Cited by 325
Tyrosine biosynthesis, metabolism, and catabolism in plants
Schenck, C. A., & Maeda, H. A. (2018) · Phytochemistry · doi:10.1016/j.phytochem.2018.02.003 · Cited by 286
Metabolic flux analysis of secondary metabolism in plants
Shih, M.-L., & Morgan, J. A. (2020) · Metabolic Engineering Communications · doi:10.1016/j.mec.2020.e00123 · Cited by 85
Soubeyrand, E., Johnson, T. S., Latimer, S., Block, A., Kim, J., Colquhoun, T. A., Butelli, E., Martin, C., Wilson, M. A., & Basset, G. J. (2018) · The Plant Cell · doi:10.1105/tpc.18.00688 · Cited by 61
Self-citationThe Multiplanetary Future of Plant Synthetic Biology
Llorente, B., Williams, T. C., & Goold, H. D. (2018) · Genes · doi:10.3390/genes9070348 · Cited by 52
Metadata
- Authors
- Zhang, Y., Butelli, E., Alseekh, S., Tohge, T., Rallapalli, G., Luo, J., Kawar, P. G., Hill, L., Santino, A., Fernie, A. R., & Martin, C.
- Venue
- Nature Communications
- Published
- 2015-10-26
- Volume
- 6
- Issue
- 1
- Pages
- 8635-8635
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W2237501542
- Cited by
- 365
- References
- 42
- FWCI
- 10.16
- Type
- journal article
- Language
- en
- Open access
- gold
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