Tag Archives: Synonymous mutation

The death of the synonymous codon – IV

The coding capacity of our genome continues to amaze. The redundancy of the genetic code has been put to yet another use. Depending on how much you know, skip the following three links and read on. Otherwise all the background to understand the following is in them.

https://luysii.wordpress.com/2011/05/03/the-death-of-the-synonymous-codon/

https://luysii.wordpress.com/2011/05/09/the-death-of-the-synonymous-codon-ii/

https://luysii.wordpress.com/2014/01/05/the-death-of-the-synonymous-codon-iii/

There really was no way around it. If you want to code for 20 different amino acids with only four choices at each position, two positions (4^2) won’t do. You need three positions, which gives you 64 possibilities (61 after the three stop codons are taken into account) and the redundancy that comes with it. The previous links show how the redundant codons for some amino acids aren’t redundant at all but used to code for the speed of translation, or for exonic splicing enhancers and inhibitors. Different codons for the same amino acid can produce wildly different effects leaving the amino acid sequence of a given protein alone.

If anything will figure out a way to use synonymous codons for its own ends, it’s cancer. [ Cell vol. 156 pp. 1129 – 1131, 1324 – 1335 ’14 ] analyzed protein coding genes in cancer. Not just a few cases, but the parts of the genome coding for the exons of a mere 3,851 cases of cancer. In addition they did whole genome sequencing in 400 cases of 19 different tumor types.

There are genes which suppress cancer (which cancer often knocks out — such as the retinoblastoma or the ubiquitous p53), and genes which when mutated promote it (oncogenes like ras). They found a 1.3 fold enrichment of synonymous mutations in oncogenes (which would tend to activate them) than in the tumor suppressors. The synonymous mutations accounted for 20 – 40 % of somatic mutations found in cancer exomes.

Unfortunately, synonymous mutations have been used to estimate the background mutation frequency for evolutionary analysis, on the theory that they are neutral (e.g. because they don’t change protein structure, they are assumed not to change how the gene for the protein functions). Wrong. Wrong. They can change how much, or where, or what exons of a protein are included in the final product.