Codon Bias -Natural Selections last stand

-


"Several criteria can discriminate between the natural selection and biased gene conversion. We argue that these regions, far from contributing to..natural selection,..they represent the Achilles’ heel of our genome." -Nicolas Galtier

The mutation-selection-drift (MSD) model of codon bias (1990) was proposed to explain the observation that synonymous codons (codons that code for the same amino acid) are not used with equal frequency in most organisms. This phenomenon is known as codon bias. It challenged the random mutation axiom of NeoDarwinism. As such the MSD was an ad hoc (created or done for a particular purpose as necessary) explanation to preserve neo darwinism.

The model proposes that codon bias is maintained by a balance between the forces of mutation, selection, and genetic drift. Mutation can randomly change one codon to another, and selection can favor certain codons over others if they are translated more efficiently or accurately. Genetic drift is a random process that can cause changes in the frequency of alleles in a population, even if those alleles are not under selection.

The MSD model proposed that codon bias will be more pronounced in genes that are highly expressed, because these genes are under stronger selection to be translated efficiently. The model also predicts that codon bias will be more pronounced in organisms with smaller effective population sizes, because genetic drift is stronger in smaller populations.

The MSD is a Neo-Darwinian explanation for codon bias, because it proposes that codon bias is maintained by the forces of natural selection and genetic drift. 

In contrast to the MSD model, there are also a number of non-Neo-Darwinian explanations for codon bias. For example, some researchers have proposed that codon bias is caused by epigenetic factors, such as DNA methylation. Epigenetic Cytosine methylation can lead to spontaneous demethylation GC>AT, mutation bias.  Other researchers have proposed that codon bias is caused by the physical structure of the genome, such as the presence of GC-rich regions, GC bias.

The MSD model is the most widely accepted explanation for codon bias for now, but it is important to note that other better explanations have been discovered. 

The MSD has recently been shown to be largely inaccurate due to GC bias causing the majority of codon biases.

The model assumed that all mutations are created equal (NeoDarwinian random mutations) and that natural selection is the only force that can change the frequency of alleles in a population.

However, in reality, mutations are not created equal e.g. GC bias (AT>GC) & mutation bias (GC>AT). This naturally occurring seesaw effect guides the majority of mutations. Some are more likely to occur than others depending on the genome. This can lead to biases in the genetic composition of populations.

GC bias is the tendency of DNA to have a higher proportion of guanine (G) and cytosine (C) nucleotides than adenine (A) and thymine (T) nucleotides. This bias is caused by a number of factors, including the higher mutation rate of AT nucleotides (2 h-bonds) and the greater stability of GC base pairs (3 h-bonds). As such it is a natural cellular variation during DNA repair and replication as the 3 h-bonds stabilize the GC during these processes. This is opposed to random mutations for NeoDarwinism's natural selection which ignores the GC nucleotide h-bond properties and the epigenetically guided spontaneous deamination of cytosine in mutation bias (C>U>T).

GC bias has a significant impact on the genetic composition of populations. This is because GC bias leads to codon bias. Codon bias is the tendency of genes to use certain codons more frequently than others. This is because some codons are more efficiently translated by ribosomes than others.


Note the GC dominance in the redundant codons above.

Codon bias can have a number of effects on the evolution of proteins. For example, codon bias can affect the rate of protein evolution and the stability of proteins. It can also affect the expression of genes. So codon bias is a natural mechanism apart from NeoDarwinian random mutations.

The MSD model does not take into account GC bias and its resulting codon bias. This means that the model is inaccurate in predicting how evolution will occur in populations with these biases.

For example, the MSD model predicts that the frequency of neutral mutations in a population will be determined by the mutation rate and the effective population size. However, in populations with GC bias, neutral mutations that increase the GC content of a gene will be more likely to be fixed in the population. This is because GC-rich genes are more likely to be expressed and because GC-rich genes are more likely to be translated efficiently.

As a result, populations with GC bias will tend to evolve towards a higher GC content. This is known as GC-drift as opposed to the MSDs genetic drift. GC-drift can have a significant impact on the evolution of genomes, including the evolution of human genomes.

The selection mutation drift (SMD) model of molecular evolution is also inaccurate due to newly discovered non-neutral synonymous substitutions.

The SMD model is a basic model of molecular evolution that assumes that mutations are either neutral (i.e., they have no effect on fitness), advantageous (i.e., they increase fitness), or deleterious (i.e., they decrease fitness). The model also assumes that natural selection is the primary force driving changes in allele frequencies over time.

However, we now know that synonymous substitutions are not neutral. Synonymous substitutions are mutations that change the DNA sequence of a gene but do not change the amino acid sequence of the protein that the gene encodes. This is because the genetic code is redundant, meaning that there are multiple codons that can code for the same amino acid.


While synonymous substitutions were assumed for 60 years to be neutral, we now know have non-neutral effects on "fitness." For example, synonymous substitutions can affect gene expression levels, mRNA stability, and protein folding. Additionally, synonymous substitutions can interact with other mutations in the genome to produce non-neutral effects even though they code for the same amino acids.

As a result of non-neutral synonymous substitutions, the SMD model is inaccurate in predicting the rate of evolution and the distribution of allele frequencies in a population.

Here are some examples of how non-neutral synonymous substitutions can make the SMD model inaccurate:

  • Synonymous substitutions can affect gene expression levels. Synonymous substitutions can affect how much of the gene is expressed. This can lead to changes in the amount of protein produced, which can have a significant impact on fitness. Same amino acid but different "fitness" by using different synonymous substitutions. 

  • Note: CRISPR-Cas9 is being used to determine "fitness" at the cellular level which is more accurate than natural selection measurement at the population level. It first proved the non neutrality of synonymous mutations just this year. Natural selection calculations can not determine "fitness" at the cellular level as accurately.

  • Synonymous substitutions can affect mRNA stability. Some synonymous substitutions can make mRNA molecules more or less stable. This can affect how long mRNA molecules last in the cell, which can affect the amount of protein produced. This is due to "synonymous" redundant  tRNA having different interactions with the ribosomes and RNA even though they carry the same amino acids.

  • Synonymous substitutions can affect protein folding. Synonymous substitutions can change the way that a protein folds, which can affect its function. This can lead to changes in fitness, especially if the protein is essential for the organism's survival.

  • Synonymous substitutions can interact with other mutations in the genome to produce non-neutral effects. For example, a synonymous substitution in one gene may interact with a non-synonymous substitution in another gene to produce a new protein that has a different function than either of the original proteins. This can have a significant impact on fitness.

  • They can influence the number of tRNAs and how they react to the ribosomes and RNA.

Overall, non-neutral synonymous substitutions makes the SMD model inaccurate in predicting the rate of evolution and the distribution of allele frequencies in a population. It fails to entirely explain codon bias from a NeoDarwinian point of view largely due to the effect of nonrandom GC bias and non neutral synonymous substitutions.  

It is important to take into account the potential non-neutral effects of synonymous substitutions and GC bias when modeling molecular evolution.

Comments

Post a Comment

Popular posts from this blog

No, the EES is not just a add on to Neo-Darwinism aka the Modern Synthesis

-
Image
" The summary of the state of affairs on the 150th anniversary of the Origin is somewhat shocking: in the post-genomic era, all major tenets of the Modern Synthesis fthe theory of evolution) are, if not outright overturned replaced by a new and incomparably more complex vision of the key aspects of evolution (EES). So, not to mince words , the Modern Synthesis is gone" -Eugene Koonin, an evolutionary biologist (Cited by over 270,000 evolutionary scientists.) The Extended Evolutionary Synthesis (EES) represents a significant departure from the traditional neo-Darwinian framework, also known as the Modern Synthesis . While both theories aim to explain evolutionary change, they differ fundamentally in their underlying mechanisms and the roles they assign to various biological processes. A crucial point of divergence lies in the interpretation and application of the term " evolutionary ," particularly concerning the incorporation of epigenetic mechanisms....
Read more

Is the random mutational model of evolution on its way out?

-
Image
While the random mutational model of evolution has long been a cornerstone of evolutionary biology, the Extended Evolutionary Synthesis (EES) and the study of epigenetics are challenging its core assumptions. The Random Mutational Model and Its Limitations The traditional view of evolution, often called the Modern Synthesis or neo-Darwinism , emphasizes random genetic mutations as the primary source of variation. Natural selection then acts upon this variation, favoring individuals with advantageous traits. This model has been successful in explaining some evolutionary phenomena, but it also has limitations: It struggles to explain complex adaptations: The idea that complex features like the eye or the immune system arose solely through random mutations seems statistically improbable. It overlooks the role of the environment: The traditional model treats the environment as a selective force, but it doesn't fully consider how organisms can actively respond to and s...
Read more

ERVs and Common Descent: A Reassessment in Light of Recent Findings

-
Image
Endogenous retroviruses (ERVs) have long been considered strong evidence for the common descent of humans and chimpanzees. These remnants of ancient viral infections, embedded in the genomes of both species, were once thought to be non-functional "junk DNA." The premise was that the shared presence of these seemingly random insertions in corresponding genomic locations could best be explained by a shared evolutionary history. However, recent research, such as the "Switching Sides" article published in May 2021, has challenged this assumption by demonstrating that ERVs play a functional role in the development of the human embryo and immune system. This discovery raises questions about the validity of using ERVs as primary evidence for common descent. The Traditional Argument for Common Descent The traditional argument for common descent based on ERVs rests on the following points: Random Insertion: Retroviral insertions are thought to occur randomly in...
Read more