It is well known that the genetic code translates DNA genes into proteins. But the process is immensely complex and new research is revealing some fascinating and challenging details. This process of protein synthesis begins with the unwinding of the DNA double helix. The two strands are separated and an incredible protein machine makes a copy of one of the strands. The copy contains the appropriate gene and, after some editing, the copy is sent to the ribosome where it provides the needed instructions.
The copy of the DNA strand is simply a sequence of nucleotides glued together. At the ribosome the nucleotides are read three at a time. Each triplet of nucleotides is called a codon because it codes for one of the 20 amino acids, according to the genetic code. There are four different nucleotides, so a codon has 64 different possible sequences of the three nucleotides. Since there are only 20 amino acids, several codons code for the same amino acid. In other words, the genetic code is degenerate.
At the ribosome there is a small army of molecular machines, called tRNAs, that read the codons and supply the appropriate amino acid, as per the genetic code. These tRNAs have a codon reader on one end and the corresponding amino acid glued to the other end. (The amino acids are glued onto the tRNAs by an army of proteins--the masters of the genetic code).
The tRNA machines are not always restricted to reading a particular codon, and in general there is not a one-to-one relationship between the codons and the tRNAs. For instance, a particular type of tRNA may read two of the six different codons that code for the serine amino acid. Also, the different tRNA machines are not in equal abundance. Instead, some are common and others are more rare.
One consequence of all this is that a given amino acid sequence (to be used in a protein) can be coded for by many different sequences of codons, which in turn could be read by different tRNAs. Therefore, a given amino acid sequence can use very different tRNAs, depending on the codon sequence used.
It has long been known that the different possible codons, which code for an amino acid, are not merely used at random in gene sequences. Instead, there are patterns though they vary across different genes and different organisms.
For instance, some codons appear more often than others, and genes that are used frequently tend to show a marked preference for the more common codons. And of course this means that certain tRNAs tend to be in greater demand.
The new research has now found another pattern: correlations in the sequence of codons used for a given amino acid along the protein sequence. For instance, consider all the serine amino acids in a protein sequence. What codons are used to code for those different serines?
The research found that the particular codon used for one of the serines, to stay with our example, influences the codon used at the next serine in the sequence. And what is this influence? The two codons tend to be either identical or, if not identical, they tend to be two codons that are read by a common tRNA machine. In other words, gene sequences tend to use the same tRNA machine for successive occurrences of an amino acid--tRNAs tend to be conserved.
This influence tends to wane as the distance between the two codons grows, in the protein sequence. And, as usual, the correlation is by no means consistent across genes or organisms. But the correlation is statistically significant, and the researchers showed that is is not merely a consequence of the well known codon bias.
Indeed, the correlation seems to be stronger in genes that need to be expressed quickly, such as those contributing to rapid growth or to acute stress responses. And finally, the researchers found this pattern of tRNA conservation is strongest for rare tRNAs, particularly in highly expressed genes.
Though many questions remain, all of this makes sense for enhancing the speed and fidelity of protein synthesis. What doesn't make a great deal of sense, as usual, is evolution. With evolution we must imagine a micro world of profound complexity--which we still do not fully understand--just happened to emerge.
