Gene optimization

Visual Gene Developer provides several algorithms to optimize gene constructs and find the best candidates.

Module name	Module category	Description
Monte-Carlo Codon Optimization	Sequence optimization	Predefined probability (defined in w-table file) based random mutation (=Monte-Carlo simulation). Target codons will be replaced by new codons that have a different probability. It checks following functions to screen out candidate gene constructs (Check CAI, Check restriction enzyme site, Check repeated sequence, Check excluded sequence)
Local mRNA Optimization	mRNA structure optimization	Adjust mRNA Gibbs energy to be in the specified range given by lowest Gibbs Energy (AvgBaseGibbs_Low) and highest Gibbs Energy (AvgBaseGibbs_High). It modified sequence performing Codon optimization or synonymous substitution. A user can set the target range given by Start and End locations in a sequence.
mRNA Profile Optimization	mRNA structure optimization	Improved from Do_mRNAOpt_ProbabilityRandom. It optimizes an mRNA Gibbs energy profile along a long sequence. A moving window method was adopted.
Local mRNA Profile Optimization	mRNA structure optimization	Modification of Do_mRNAProfileOpt. A user can set the target range given by Start and End locations in a sequence.
Silent removal v1	Gene manipulation	Remove undesired sequences. It can specify up to 10 sequences.
Silent removal v2	Gene manipulation	Remove undesired sequences. Can process multiple query sequences.
Silent removal of potential polyadenylation sites	Gene manipulation	Remove predefined sequences of potential polyadenylation signal sequences
Silent removal of potential intron cryptic splice sites	Gene manipulation	Remove predefined sequences of potential intron cryptic donor and receptor signal sequences
Check CAI	Constraint	Return 'Not pass' if CAI value is lower than setpoint
Check restriction enzyme site	Constraint	Return 'Not pass' if the sequence contains a certain restriction enzyme sequence
Check repeated sequence	Constraint	Return 'Not pass' if the sequence contains a certain number of repeated sequence
Check excluded sequence	Constraint	Return 'Not pass' if the sequence contains a certain excluded sequence
Check stable mRNA structure	Constraint	Return 'Not pass' if the sequence contains stable mRNA secondary structures The module retrieves sequence information and then generates lots of sequence segments specified by 'Window size'. The moving window scans along the sequence with a given 'Step size'. The Visual Gene Developer predicts mRNA secondary structure and calculates Gibbs free energy for each segment. If Gibbs energy is lower than a specified value ('Threshold value'), it returns 'Not pass' which means the gene includes stable mRNA secondary structure. If all sequence segments of the target gene are more unstable than the expected value ('Threshold value'), the module returns 'Pass'.

For more details about the 'Module category', check the 'Module development' section on the left menu. At the same time, all predefined modules were summarized in the 'Class & module' section on the left menu.

Method 1 (Working on 'Workspace'): Paste sequence to 'Workspace' window and then click on the 'Function > Codon optimization'. You will see the 'Codon optimization' window. Adjust parameters and then click on the 'Perform' button. For mRNA structure optimization, click on the 'Function > mRNA optimization'. You will see the 'mRNA optimization' window. Adjust parameters and then click on the 'Analyze' button and then 'Optimize' button

Method 2 (Working on Gene construct): Firstly, configure optimization condition in the 'Configuration of gene optimization' window and then do optimize a gene construct in the 'Gene optimization' window.

7. Adjust parameters. For example, when you click on the 'On' checkbox, it will deactivate a selected module and an optimization algorithm will neglect inactivated items.

There are 4 different categories of optimization conditions such as 'Sequence optimization', 'mRNA structure', 'Manipulation', and 'Constraint'.

It's up to you to classify the module to one of them. However, internal algorithms orderly proceed from 'Sequence optimization' to 'Constraint'. Therefore, 'Sequence optimization' has the highest priority than other conditions and 'Constraint' is the lowest priority. For more details, check the 'Module development' section on the left menu.

2. A window titled 'Configuration of gene optimization' will be shown. Choose an algorithm and click on the 'Run' button. If you want to stop the optimization, click on the 'Stop' button.

As shown in the figure, the 'Automated conditional search' algorithm produces a lot of candidates that fit for the condition defined in 'Constraint' in the 'Gene optimization condition' window.

3. Because the optimization algorithm initially starts from a selected gene construct (=there are a parent gene construct and lots of child gene constructs), simply choose a gene construct clicking in the table and then start a new optimization cycle.

4. If you want to re-define the table, click on the 'Viewer setting' button in the 'Gene optimization' window.

The software supports developing user-defined new algorithms for gene optimization. The module development section on the left menu will be much helpful. Basically, users can access the gene construct memory array using a class (class name: GeneConstruct) to modify sequence.