Another Successful Prediction of Intelligent Design: Cell Paper Reports Functions for Synonymous Codons
In the past we’ve noted papers finding function for synonymous codons (for example, see here and here) — but the functions reported in those papers generally pertained to controlling translation speed. Now a paper in the journal Cell has found a new potential function, namely that synonymous codons can control the rate at which mRNA transcripts degrade and are broken down within cells:
Substitution of optimal codons with synonymous, non-optimal codons results in dramatic mRNA destabilization, whereas the converse substitution significantly increases stability. Further, we demonstrate that codon optimality impacts ribosome translocation, connecting the processes of translation elongation and decay through codon optimality. Finally, we show that optimal codon content accounts for the similar stabilities observed in mRNAs encoding proteins with coordinated physiological function. This work demonstrates that codon optimization exists as a mechanism to finely tune levels of mRNAs and, ultimately, proteins.
(Vladimir Presnyak et al. , “Codon Optimality Is a Major Determinant of mRNA Stability,” Cell, Vol. 160: 1111-1124 (March 12, 2015).)
There are normal cellular pathways that degrade mRNA molecules in living organisms. However, transcriptome studies have found wide variation in decay rates of mRNAs, suggesting that some other factors are regulating mRNA degradation. As the paper puts it, “It seems likely that additional and more general features that act to modulate transcript stability could exist within mRNAs.” Essentially, what they call “optimal codons” prevent decay of mRNA molecules. Here’s how the paper defines “optimal” vs. “non-optimal” codons:
Conceptually, codon optimality is a scale that reflects the balance between the supply of charged tRNA molecules in the cytoplasmic pool and the demand of tRNA usage by translating ribosomes, representing a measure of translation efficiency. Critically, optimal codons are postulated to be decoded faster and more accurately by the ribosome than non-optimal codons, which are hypothesized to slow translation elongation. Therefore, codon optimality is hypothesized to play an important role in modulation of translation elongation rates and the kinetics of protein synthesis.
Or course these “optimal” or “non-optimal” codons really could be designed to allow some mRNAs to be more stable and other mRNAs less stable, for functional reasons. They offer four lines of evidence that codon “optimality” influences mRNA stability, including both theoretical evidence and direct experimental evidence:
[W]e present four lines of evidence in support of the finding that codon optimality has a broad and powerful influence on mRNA stability in yeast cells. First, global analysis of RNA decay rates reveals that mRNA half-life correlates with optimal codon content. Many stable mRNAs demonstrate a strong preference toward the inclusion of optimal codons within their coding regions, whereas many unstable mRNAs harbor non-optimal codons. Second, we demonstrate that substitution of optimal codons with synonymous, nonoptimal codons results in a dramatic destabilization of the mRNA and that the converse replacement leads to a significant increase in mRNA stability. Third, we experimentally demonstrate an impact of codon optimality on ribosome translocation, indicating that the effect on mRNA decay occurs through modulation of mRNA translation elongation. These findings indicate that transcript-specific translation elongation rate, as dictated by codon usage, is an important determinant of mRNA stability. Fourth, we observe tightly coordinated optimal codon content in genes encoding proteins with common physiological function. We hypothesize that this finding explains the previously observed similarity in mRNA decay rates for these gene families.
As part of their experimental evidence, they changed the codons in mRNA transcripts and measured how that affected stability of the mRNA: “To experimentally validate the relationship observed in the computational analysis, we evaluated the effects on stability of altering the percentage of optimal codons within an mRNA.” Usage of optimal vs. non-optimal codons had a major impact on stability and translation:
We find here that codon usage within normal mRNAs also influences translating ribosomes and can have profound effects on mRNA stability. Thus, the ribosome acts as the master sensor, helping to determine the fate of all mRNAs, both normal and aberrant, through modulation of its elongation and/or termination processes. The use of the ribosome as a sensor is ideal for protein- coding genes, whose primary function in the cell is to be translated. We suggest that a component of mRNA stability is built into all mRNAs as a function of codon composition. The elongation rate of translating ribosomes is communicated to the general decay machinery, which affects the rate of deadenylation and decapping. Individually, the identity of codons within an mRNA would be predicted to have a minute influence on overall ribosomal decoding; however, within the framework of an entire mRNA, we show that codon optimality can have profound effects on translation elongation and mRNA turnover. We therefore conclude that codon identity represents a general property of mRNAs and is a critical determinant of their stability.
Why have we focused on functions for synonymous codons? At an astounding pace, molecular biologists are discovering new layers of epigenetic cellular control. We regularly cover many of these discoveries here at ENV because intelligent design predicts we should find new layers of information and control in cells. But why the particular focus on synonymous codons? It’s because evolutionists have long assumed that synonymous codons are functionally equivalent and represent a “junk element” of sorts in the genome. They assumed that one synonymous codon is no better than any other, so which synonymous codon you use doesn’t really matter. Not only does this idea stem directly from the assumption of unguided, blind evolution, but it has become the basis for methodologies that attempt to detect natural selection (or the lack thereof) in the genome.
When synonymous codons (which don’t change amino acid sequence) prevail in frequency over non-synonymous codons (which do change amino acid sequence), that is said to suggest neutral evolution. But when genetic differences that change amino acid sequence (non-synonymous codons) prevail, this has been cited by numerous studies as purportedly showing natural selection acting upon a gene. These are the sorts of studies touted by Darwin advocacy groups like the National Center for Science Education as evidence that we understand how new genes evolve (see here and here).
Now even if these methods worked, they still don’t mean we know how new genes evolve. In fact, these kinds of studies often claim to detect natural selection in a gene when they can’t even say what the gene does! So clearly no stepwise explanation of how a gene evolves is being provided.
But if synonymous codons can have different functions, then that means that these methods are wrong to begin with. Studies that purport to detect natural selection in the genome find no such thing. Instead, these studies reflect how evolutionary assumptions can mistake important functional elements of the genome for the remnant noise of unguided evolutionary processes. It’s another example of how Darwinian thinking leads molecular biology down the wrong path.
ID, on the other hand, predicts that we should find deeper and deeper layers of function in biology. That’s why functions for synonymous codons represent a successful prediction for ID, and a big problem for Darwinian evolution.
Image by Colinadrielgoldberg (Own work) [CC BY-SA 3.0], via Wikimedia Commons.