The "Survival of the fittest" as measured over the last 120 years

The term "survival of the fittest" was coined by Herbert Spencer in 1864 to describe the process by which nature favors the strong in society. Charles Darwin borrowed the term in his book Origin of the Species seven years later. Spencer took it a step further by arguing that survival of the fittest could also explain social and economic phenomena. This became known as social darwinism. Many leaders in the 20 century applied social darwinism to their citizens with disastrous effect to include justifying wars.

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Darwin's theory of evolution by natural selection was based on his observations of the natural world and his understanding of animal breeding. He did not have access to modern scientific methods, so he was unable to measure the effects of natural selection directly.

Gregory Mendel, the father of genetics, made it possible to study the genes (alleles). Mendel performed  2,500 experiments on plants. This represents the first great application of Francis Bacon's "Scientific Method." 

In the early 1900's scientists rediscovered Mendel's 40 year old work only to realize it contradicted Darwin's ideas. 

Some Neodarwinists, on the other hand, were able to apply Mendel's work in on genetics to Darwin's theory of natural selection. This allowed them to develop mathematical models of evolution, such as the Hardy-Weinberg equation. This equation can be used to predict how the frequency of alleles (different forms of a gene) in a population will change over time due to natural selection.

They reasoned  that the frequency of different alleles (different versions of a gene) in a population can change over time, and that this change might be driven by natural selection.

Scientists used the Hardy-Weinberg equations to predict the allele frequencies in a population if it were in genetic equilibrium. They can then compare these predicted frequencies to the actual frequencies in the population to see if there is a difference. If there is a difference, then this suggests that the population is evolving, and natural selection is one possible explanation.

The concept of survival of the fittest has been modified over time, as scientists have developed new theories and models. One of the most significant changes was the introduction of Kimura's Ka/Ks ratio in the 1960s along with his notable Neutral Theory of Molecular Evolution.

The Ka/Ks ratio is a measure of the ratio of non-synonymous substitutions (which change the amino acid sequence of a protein) to synonymous substitutions (which do not change the amino acid sequence of a protein). Kimura proposed that the Ka/Ks ratio could be used to distinguish between natural selection and genetic drift.

Ka/Ks is more accurate than the Hardy-Weinberg equation for predicting allele frequencies in populations because it takes into account natural selection. The Hardy-Weinberg equation describes the expected allele frequencies in a population under ideal conditions, assuming no selection, migration, or mutation. However, these conditions are rarely met in natural populations

Ka/Ks can be used to infer the strength of natural selection on a gene. If Ka/Ks is equal to 1, then the gene is evolving neutrally, meaning that natural selection is not acting on it. If Ka/Ks is greater than 1, then the gene is under positive selection, meaning that natural selection is favoring certain alleles. If Ka/Ks is less than 1, then the gene is under negative selection, meaning that natural selection is disfavoring certain alleles.

The Hardy-Weinberg equation does not take into account the strength of natural selection. Therefore, it is not as accurate as Ka/Ks for predicting allele frequencies in populations where natural selection is important.

Last year's discovery that synonymous mutation changes are not neutral changed our view on natural selection and how it's measured. For 60 years scientists assumed synonymous mutations were neutral largely due to Kimura.

Nonneutral synonymous mutations are synonymous mutations that have a measurable effect on the fitness of an organism, even though they do not change the amino acid sequence of the protein that is encoded by the gene. 

Nonneutral synonymous mutations have been observed in a wide range of organisms, including bacteria, yeast, plants, and animals. They have also been implicated in a number of human diseases, including cancer, cystic fibrosis, and sickle cell anemia.

A recent study published in Nature Communications in 2022 found that most synonymous mutations in yeast have a significant reduction in fitness. This suggests that synonymous mutations may play a more important role in evolution than previously thought.

The study's authors suggest that synonymous mutations may be nonneutral because they can affect the mRNA structure, codon usage, and gene regulation. They also suggest that synonymous mutations may be more likely to be nonneutral in genes that are highly expressed or that have important functions.

The discovery that synonymous mutations are often nonneutral has important implications for our understanding of evolution and disease. It suggests that we need to be more careful about interpreting the results of genetic studies that rely on the assumption that synonymous mutations are neutral, e.g., Ka/Ka ratios.

Non-neutral synonymous mutations make Ka/Ks equations inaccurate. This is because Ka/Ks equations rely on the assumption that synonymous mutations are neutral, meaning that they do not affect the fitness of the organism. However, non-neutral synonymous mutations can affect the fitness of the organism, which lead to inaccurate results from Ka/Ks equations.

Cas9 CRISPR-DMS is a technique that was used to overcome this problem. Cas9 CRISPR-DMS is a modified version of the Cas9 CRISPR gene editing system that allows for the introduction of specific mutations into DNA. DNA Cas9 CRISPR-DMS was used to show that non-neutral synonymous mutations are more common than previously thought. 

Cas9 CRISPR-DMS is a powerful tool that can be used to improve the accuracy of calculating "fitness". This can lead to a better understanding of the evolution of genes and the role of selection in evolution.

The term "fitness" in biology refers to the ability of an organism or cell to survive and reproduce. Fitness is a complex trait that is influenced by many factors, including genetics, environment, and luck. It is more specific than natural selection. This is because natural selection is derived from the prior assumptions listed above.

CRISPR-Cas9 DSM (dynamic single-molecule) maps are a new tool for measuring fitness in real time. DSM maps track the movement of individual cells through a population as they compete for resources. This allows scientists to measure the fitness of each cell directly, without having to rely on indirect measures such as survival rate or reproductive success.

DSM maps have shown that fitness is not a static trait, but rather a dynamic process that can change in response to environmental changes. For example, DSM maps have shown that cancer cells can evolve to become more resistant to chemotherapy over time.

DSM maps are still under development, but they have the potential to revolutionize our understanding of fitness and evolution and what if any REAL effect natural selection has. By measuring fitness directly, DSM maps can help us to identify the genes and environmental factors that contribute to fitness differences. This information could be used to develop new strategies for treating diseases, improving crop yields, and conserving biodiversity.

Here are some of the benefits of using DSM maps to measure fitness:

• DSM maps can measure fitness in real time, which allows scientists to study how fitness changes in response to environmental changes.

• DSM maps can measure the fitness of individual cells, which allows scientists to identify the genes and environmental factors that contribute to fitness differences.

• DSM maps can be used to study fitness in a variety of organisms, including bacteria, yeast, plants, and animals.

Compared to the term "survival of the fittest," DSM maps provide a more accurate and nuanced measure of fitness. DSM maps show that fitness is not a static trait, but rather a dynamic process that can change in response to environmental changes. Additionally, DSM maps can measure the fitness of individual cells, which allows scientists to identify the genes and environmental factors that contribute to fitness differences.

Overall, DSM maps are a powerful new tool for measuring fitness in real time. DSM maps have the potential to revolutionize our understanding of fitness and evolution, and to lead to new advances in medicine, agriculture, and conservation biology.

We might finally answer the 170 year old question "is natural selection" a real force or just a passive filter.