The copy number of genes in chromosomes can be modified by chromosomal integration to construct efficient microbial cell factories but the resulting genetic systems are prone to failure or instability from triggering homologous recombination in repetitive DNA sequences. Finding the optimal copy number of each gene in a pathway is also time and labor intensive. To overcome these challenges, we applied a multiple nonrepetitive coding sequence calculator that generates sets of coding DNA sequence (CDS) variants. A machine learning method was developed to calculate the optimal copy number combination of genes in a pathway. We obtained an engineered Yarrowia lipolytica strain for eicosapentaenoic acid biosynthesis in 6 months, producing the highest titer of 27.5 g l-1 in a 50-liter bioreactor. Moreover, the lycopene production in Escherichia coli was also greatly improved. Importantly, all engineered strains of Y. lipolytica, E. coli and Saccharomyces cerevisiae constructed with nonrepetitive CDSs maintained genetic stability.
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| Evidence ID | Analyze ID | Gene/Complex | Systematic Name/Complex Accession | Qualifier | Gene Ontology Term ID | Gene Ontology Term | Aspect | Annotation Extension | Evidence | Method | Source | Assigned On | Reference |
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| Evidence ID | Analyze ID | Gene | Gene Systematic Name | Phenotype | Experiment Type | Experiment Type Category | Mutant Information | Strain Background | Chemical | Details | Reference |
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| Evidence ID | Analyze ID | Gene | Gene Systematic Name | Disease Ontology Term | Disease Ontology Term ID | Qualifier | Evidence | Method | Source | Assigned On | Reference |
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| Evidence ID | Analyze ID | Regulator | Regulator Systematic Name | Target | Target Systematic Name | Direction | Regulation of | Happens During | Regulator Type | Direction | Regulation Of | Happens During | Method | Evidence | Strain Background | Reference |
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| Site | Modification | Modifier | Source | Reference |
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| Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Allele | Assay | Annotation | Action | Phenotype | SGA score | P-value | Source | Reference | Note |
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Increase the total number of rows showing on this page by using the pull-down located below the table, or use the page scroll at the table's top right to browse through the table's pages; use the arrows to the right of a column header to sort by that column; filter the table using the "Filter" box at the top of the table; click on the small "i" buttons located within a cell for an annotation to view further details about experiment type and any other genes involved in the interaction.
| Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Assay | Annotation | Action | Modification | Source | Reference | Note |
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| Complement ID | Locus ID | Gene | Species | Gene ID | Strain background | Direction | Details | Source | Reference |
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| Evidence ID | Analyze ID | Dataset | Description | Keywords | Number of Conditions | Reference |
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