To understand protein expression, we need to revisit the “central dogma” of molecular biology: DNA is transcribed into mRNA, that is translated into protein. During the discovery of the genetic code, Francis Crick hypothesized that protein translation required a mediator to convert the mRNA ribonucleotide code into amino acids. Crick postulated that a triplet, a group of three bases, codes for one amino acid. He also proposed a “degenerate code,” where one amino acid may be coded for by one of several base triplets.
Crick was right. A tRNA mediator, reads complementary mRNA sequences via a triplet anticodon. But tRNA recognition is ambiguous, 31 different anticodons translate the 61 sense codons of the standard genetic code found in transcribed mRNA.
The promiscuity in anticodon recognition is partially explained by the tRNA-specific RNA residue, inosine. Inosine recognizes the nucleotides U, C and A, and more specifically recognizes the third base of codons, the “wobble position.” Inosine ambiguity is what facilitates the degenerate genetic code.
Codons mutated in the wobble position are still recognized by the same tRNA anticodon. While these “synonymous mutations” do not change the amino acid sequence, they are still able to affect protein expression levels. This is why optimizing the design of transgenic protein expression is important in molecular biology.
When expressing proteins, synonymous mutations may not be neutral, because certain codons are translated more efficiently than others—creating codon bias. A synonymous mutation in a codon with a limited availability of corresponding tRNA anticodons could result in significantly lower protein expression due to ribosome stalling. Many organisms display biased codon usage, and it is generally accepted that codon biases reflect a balance between mutational biases and natural selection for translational optimization.
The most common measurement for codon usage is the Codon Adaptation Index (CAI). This index examines the codon usage (resulting from codon bias) in highly expressed genes from a species and assesses the codons that are preferentially used in that reference set.
Nowadays, a variety of programs, known as codon optimization tools, exist to help you optimize your sequence in your species of interest. But codon optimization tools can differ greatly, newer design algorithms analyze much more than just codon usage. Additional properties to consider are:
Transcriptional Efficiency
Translational Efficiency & Stability
GenScript's proprietary OptimumGene™ codon optimization tool is the most cited technology for gene design. Our algorithms take the entire mRNA structure, various cis-elements, and codon adaptability into consideration.
OptimumGene™ is able to
GenScript OptimumGene™ increases the yield of expression (8/10 genes) and the degree of solubility (6/10 genes) in comparison to wild-type sequences.
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