Codon usage
Counts every codon in a coding sequence and plots how often each one is used.
Counts every codon in a coding sequence and plots how often each one is used.
The genetic code is redundant: 61 codons encode 20 amino acids, so most amino acids have two, four or six synonymous codons. Genes do not use them evenly. A codon usage table counts how often each of the 64 codons appears in a coding sequence and reports three numbers for each:
The per thousand column is the one published host tables use, and all 64 values add up to 1,000. The fraction column is the one that shows bias, because it divides out how common the amino acid itself is. The chart draws the per thousand value of every codon in codon table order, four bars per group, so a gene that leans on one codon of a family is visible at a glance.
Third positions are where synonymous codons differ, so GC3 measures codon choice rather than the protein. Values near 50 % mean little third-position bias. High GC3 is typical of genes written for mammalian cells and of GC-rich genomes such as Streptomyces; low GC3 is typical of Plasmodium and of many yeast genes.
"Try an example" loads the 720 nt coding sequence of EGFP, which is 240 codons. Only31 of the 64 codons occur in it, and GC3 is 96.7 %: this gene was written for mammalian cells, and almost every third base is G or C. The most frequent codons are AAG (Lys) and GGC (Gly) with 19 each, which is 79.2 per thousand; the tool names AAG, the first of the two in codon table order. CTG carries 18 of the 21 leucine codons, a fraction of 0.86, while CTA, CTT and TTA never appear. Choose E. coli under "Compare with" and the reference line sits far below the bars for GGC, CTG and GAC and far above them for AAA and GAA, which is why this gene is a poor fit for E. coli and the reasoncodon optimisation exists.
The reference frequencies are those of the Codon Usage Database at the Kazusa DNA Research Institute (Nakamura, Gojobori and Ikemura, Nucleic Acids Res 2000), compiled from GenBank coding sequences: Escherichia coli W3110 (1,372,057 codons),Saccharomyces cerevisiae (6,534,504 codons) and Homo sapiens (40,662,582 codons). The same tables are used by the rare codon analysis and the codon optimizer.
The genetic code option changes only which amino acid a codon is assigned to, and so which codons count as synonyms. The standard code covers nuclear genes of every organism; the three mitochondrial codes differ in a handful of codons, for example TGA is tryptophan rather than a stop.
To translate the frame and check it, use theDNA to protein translator; to find the frame, the ORF finder. For the standard code itself see thecodon table, and for GC content along the sequence theGC content calculator.
Read the coding sequence in frame from its first base, three bases at a time, and count how often each of the 64 codons occurs. The count is then expressed per 1,000 codons, so tables from genes of different lengths can be compared, and as a fraction of the synonymous codons for the same amino acid, which is what shows the bias.
Frequency per thousand mixes two things: how common the amino acid is and which of its codons is preferred. All 64 values add up to 1,000. The fraction of synonyms removes the first effect by dividing by the total for that amino acid, so the six leucine codons add up to 1. Use the fraction to judge codon bias and the per thousand value to compare with a published host table.
GC3 is the share of codons whose third base is G or C. The third base is the one that is usually free to change without changing the amino acid, so GC3 tracks codon bias rather than protein composition. It is high in genes optimised for mammalian expression and in GC-rich genomes, and it correlates with expression level in many species.
Yes. Every FASTA record is read in frame from its own first base and the counts are pooled into one table, which is how a codon usage table for a genome or a gene set is normally built. Records that are not a multiple of three lose their last one or two bases and are reported under the input.
Because it counts one gene, not a genome. A single gene of 300 codons gives each codon an average of fewer than 5 counts, so the sampling noise is large. Choose a host under "Compare with" to see the reference frequencies drawn over the bars, and read the fraction of synonyms rather than single counts.