Synthetic Biology
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Benefits of codon optimization

Why rebalance codon usage

The genetic code is composed of 64 codons with only 21 amino acid and “stop” assignments. Therefore, degeneracy is inherently designed into translation. Preferential usage of particular codons varies by organism. For example, leucine is specified by 6 distinct codons, some of which are rarely used. By rebalancing codon usage within a reading frame, preferred leucine codons are selected over rarely used codons. This is thought to increase the yield of heterologous expression [1]. The free, online IDT Codon Optimization Tool can help you rebalance codon usage for a sequence from one species to that for the organism chosen for expression.

How the Codon Optimization Tool works

The Codon Optimization Tool was written using a codon sampling strategy [2] in which the reading frame is recoded based on the frequencies of each codon’s usage in the new organism.

As an example, codon optimizations of sequences that will be expressed in human cell lines assign the phenylalanine codon UUU 46% and UUC 54% of the time (see Table 1, amino acid F). In addition, codons with <10% frequency are eliminated, with remaining codons renormalized to 100%. For example, codons CUA and UUA designate leucine (amino acid L), but are rarely used. Thus, they would not be assigned, and the remaining codons for leucine (UUG, CUU, CUC, and CUG) would be renormalized to 100%.

  Codon Amino Acid (AA) Use for that AA  Frequency (per 1000)   Codon Amino Acid (AA) Use for that AA  Frequency (per 1000)  
  UUU F 46% 17.6   UAU  Y  44% 12.2  
  UUC  F  54% 20.3   UAC  Y  56% 15.3  
  UUA L   8%   7.7   UAA  *  30%   1.0  
  UUG   L  13% 12.9   UAG *  24%   0.8  
  UCU  S  19% 15.2   UGU  C  46% 12.9  
  UCC  S  22% 17.7   UGC  C  54%   4.4  
  UCA  S  15% 12.2   UGA  *  47%   0.8  
  UCG  S    5%  4.4   UGG  W  100% 13.2  
  CUU  L  13% 13.2   CAU H  42% 10.9  
  CUC  L  20% 19.6   CAC  H  58% 15.1  
  CUA  L    7%   7.2   CAA  Q  27% 12.3  
  CUG  L  40% 39.6   CAG  Q  73% 34.2  
  CCU P  29% 17.5   CGU  R    8%   4.5  
  CCC  P  32% 19.8   CGC  R  18% 10.4  
  CCA P  28% 16.9   CGA  R  11%   6.2  
  CCG P  11%   6.9   CGG  R  20% 11.4  
  AUU  I  36% 16.0   AAU  N  47% 17.0  
  AUC  I  47% 20.8   AAC  N  53% 19.1  
  AUA  I  17%   7.5   AAA  K  43% 24.4  
  AUG M  100% 22.0   AAG  K  57% 31.9  
  ACU  T  25% 13.1   AGU  S  15% 12.1  
  ACC  T  36% 18.9   AGC  S  24% 19.5  
  ACA  T  28% 15.1   AGA  R  21% 12.2  
  ACG  T  11%   6.1   AGG  R  21% 12.0  
  GUU  V  18% 11.0   GAU  D  46% 21.8  
  GUC V  24% 14.5   GAC  D  54% 25.1  
  GUA  V  12%   7.1   GAA  E  42% 29.0  
  GUG  V  46% 28.1   GAG  E  58% 39.6  
  GCU  A  27% 18.4   GGU  G
16% 10.8  
  GCC  A  40% 27.7   GGC  G
34% 22.2  
  GCA  A  23% 15.8   GGA   G  25% 16.5  
  GCG  A  11%   7.4   GGG  G
25% 16.5  

Table 1. Human codon table. Stars (*) denote stop codons. Data taken from, accessed 4/15/2016.

Will codon optimization affect protein expression?

There is currently no known method that is predictive of protein expression, although the concept of the codon adaptation index has proven most predictive for expression by E. coli [3,4]. While codon optimization can improve expression, it does not provide a guarantee. The amount of increase in protein expression through codon optimization will vary, depending on the particular protein and organism. Additionally, expression levels can be influenced by many other factors, including tRNA copies [5], mRNA stability [6], protein folding kinetics [7], protein stability, protein transport, toxicity of the protein within the expression cell environment, and a host of other factors that vary for each protein and organism. As a result, any particular optimization demands experimental verification.

Get Started

Access IDT’s free, online Codon Optimization Tool and get started.

We also provide a step-by-step tutorial for using the Codon Optimization Tool. View it here or at:

If you are working with an organism not listed in the tool’s extensive Organism list, or do not see the information you need, contact our Genes Support group at:


  1. Plotkin JB, Kudla G. (2011) Synonymous but not the same: the causes and consequences of codon bias. Nat Rev Genet, 12:32–42.
  2. Robison K. (2009) Omics! Omics! Available at
  3. Sharp PM, Li WH. (1987) The codon Adaptation Index—a measure of directional synonymous codon usage bias, and its potential applications. Nucl Acids Res, 15(3):1281–1295.
  4. Khalili M, Soleyman MR, et al. (2015) High-level expression and purification of soluble bioactive recombinant human heparin-binding epidermal growth factor in Escherichia coli. Cell Biol Int, 39(7):858–864.
  5. Cannarozzi G, Schraudolph NN, et al. (2010) A role for codon order in translation dynamics. Cell, 141:355–367.
  6. Wang Y, Liu CL, et al. (2002) Precision and functional specificity in mRNA decay. Proc Natl Acad Sci USA, 99:5860–5865.
  7. Zhang G, Ignatova Z. (2011) Folding at the birth of the nascent chain: coordinating translation with co-translational folding. Curr Opin Struct Biol, 21:25–31.

Additional resources

DECODED Online newsletter articles—Written by scientists, these articles provide tips for conducting more effective experiments, and give overviews of the latest techniques and applications used in the field. They also include in-depth research profiles and citation summaries that describe successful research done by your colleagues who already use IDT products.

Codon optimization tool makes synthetic gene design easy—Product spotlight: Use the free, IDT Codon Optimization Tool to simplify designing synthetic genes and gBlocks® Gene Fragments for expression in a variety of organisms. The tool allows for manual changes, and takes into account natural codon bias and synthesis complexity.

Synthetic biology—Support and educational content—View additional articles about synthetic biology applications, protocols, and products.

The OligoAnalyzer® Program—Get quick instructions on how to use this free IDT web tool that allows you to determine the physical characteristics of your oligonucleotides.

See all DECODED Online articles.

Author: Sam Shen, PhD, is a product applications specialist at IDT.

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