Evolution just got Crispr

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The vast majority of evolution studies measure the ratio of nonsynonymous to synonymous substitutions (e.g. Ka/Ks) as a proxy for the strength of natural selection. Nonsynonymous substitutions are changes in the DNA sequence that result in a change in the amino acid sequence of a protein. Synonymous substitutions are changes in the DNA sequence that do not result in a change in the amino acid sequence of a protein.

Here are some formulas that measure nonsynonymous to synonymous substitution:

  • Ka/Ks ratio: This is the most common formula used to measure nonsynonymous versus synonymous substitution. It is calculated by dividing the number of nonsynonymous substitutions per site by the number of synonymous substitutions per site. A Ka/Ks ratio of 1 indicates that nonsynonymous and synonymous substitutions are occurring at the same rate, while a Ka/Ks ratio greater than 1 indicates that nonsynonymous substitutions are occurring more frequently.

  • dN/dS ratio: This ratio is also known as the omega (ω) ratio. It is calculated in the same way as the Ka/Ks ratio, but it is normalized for the mutation rate. This makes it more useful for comparing different genes or species.

  • Synonymous substitution rate (Ks): This is the number of synonymous substitutions per site. It is calculated by counting the number of synonymous substitutions in a sequence and dividing by the total number of synonymous sites.

  • Nonsynonymous substitution rate (Ka): This is the number of nonsynonymous substitutions per site. It is calculated in the same way as the synonymous substitution rate, but it counts nonsynonymous substitutions instead.

  • Ka/Ks: This is a synonym for dN/dS.

  • McDonald-Kreitman test: This test compares the ratio of nonsynonymous to synonymous substitutions in a pair of homologous genes to the ratio of nonsynonymous to synonymous substitutions in a pair of paralogous genes. It can be used to identify genes that are under positive selection.

Formulas that include McDonald:

  • McDonald-Kreitman statistic: This statistic is used to test whether a gene is under positive selection. It is calculated by comparing the ratio of nonsynonymous to synonymous substitutions in a pair of homologous genes to the ratio of nonsynonymous to synonymous substitutions in a pair of paralogous genes.

  • McDonald-Kreitman test: This test is a synonym for the McDonald-Kreitman statistic.

It is important to note that these formulas are only estimates of the true rates of nonsynonymous and synonymous substitution. This is because it is difficult to accurately measure the number of substitutions that have occurred in a gene or genome. Until now…

CRISPR/Cas9 technology has been used to discover that non-neutral synonymous substitutions are relatively common. Synonymous substitutions are mutations in protein-coding genes that do not change the amino acid sequence of the encoded protein. They were previously thought to be neutral, meaning that they had no effect on the fitness of the organism. However, recent studies using CRISPR/Cas9 have shown that many synonymous substitutions can have a significant impact on fitness.

One way that CRISPR/Cas9 has been used to study the effects of synonymous substitutions is by generating libraries of mutants in which each gene has been randomly mutated at a single site. These libraries can then be screened to identify mutants that have a reduced fitness. In one study, researchers used CRISPR/Cas9 to create a library of over 8,000 mutants in the yeast Saccharomyces cerevisiae. They found that 75% of the synonymous mutations in this library had a significant negative impact on fitness.

Another way to use CRISPR/Cas9 to study synonymous substitutions is to target specific mutations that are known to be associated with disease. For example, researchers have used CRISPR/Cas9 to create transgenic mice that carry synonymous mutations in genes that are associated with cystic fibrosis and muscular dystrophy. These mice have been shown to develop the same symptoms as human patients with these diseases, suggesting that synonymous mutations can play a role in disease development.

The discovery that synonymous substitutions can be non-neutral has important implications for our understanding of evolution and disease. It suggests that the genetic code is more complex than previously thought, and that even seemingly minor changes in DNA sequence can have a significant impact on the organism.

Here is a specific example of how CRISPR/Cas9 was used to discover non-neutral synonymous substitutions in the yeast S. cerevisiae:

  1. The researchers created a library of over 8,000 mutants in S. cerevisiae by using CRISPR/Cas9 to randomly introduce single point mutations into each gene.

  2. They then screened the library to identify mutants that had a reduced fitness. They did this by growing the mutants in competition with the wild-type yeast strain.

  3. They found that 75% of the synonymous mutations in the library had a significant negative impact on fitness. This means that these mutations made the yeast cells less likely to survive and reproduce.

The researchers then investigated the mechanisms by which synonymous mutations can reduce fitness. They found that many synonymous mutations can affect the level of expression of the mutated gene. This can happen because synonymous mutations can change the way that the mRNA is transcribed or processed.

The discovery that synonymous mutations can be non-neutral has important implications for our understanding of evolution and disease. It suggests that the genetic code is more complex than previously thought, and that even seemingly minor changes in DNA sequence can have a significant impact on the organism.

Here are 10 ways in which "fitness" measurements by CRISPR/Cas9 DMS are different from natural selection measurements:

  1. CRISPR/Cas9 DMS can be used to measure fitness directly. Natural selection measures fitness indirectly, by observing which individuals survive and reproduce more successfully. CRISPR/Cas9 DMS can be used to measure fitness directly, by measuring the growth rate or survival of individual cells or organisms with specific genetic changes.

  2. CRISPR/Cas9 DMS can be used to measure fitness in controlled environments. Natural selection occurs in the wild, where it is difficult to control all of the factors that can affect fitness. CRISPR/Cas9 DMS can be used to measure fitness in controlled laboratory environments, where all of the factors except for the specific genetic change being tested can be held constant.

  3. CRISPR/Cas9 DMS can be used to measure fitness in short time periods. Natural selection can take generations or even millions of years to produce measurable changes in fitness. CRISPR/Cas9 DMS can be used to measure fitness in short time periods, such as days or weeks.

  4. CRISPR/Cas9 DMS can be used to measure fitness in a wide range of organisms. Natural selection can only measure fitness in organisms that can reproduce in the wild. CRISPR/Cas9 DMS can be used to measure fitness in a wide range of organisms, including bacteria, yeast, plants, animals, and humans.

  5. CRISPR/Cas9 DMS can be used to measure fitness for specific traits. Natural selection measures overall fitness, which is a combination of all of the traits that affect survival and reproduction. CRISPR/Cas9 DMS can be used to measure fitness for specific traits, such as resistance to disease or tolerance to stress.

  6. CRISPR/Cas9 DMS can be used to measure fitness in combination with other factors. Natural selection measures fitness in the context of all of the other factors that are present in the environment. CRISPR/Cas9 DMS can be used to measure fitness in combination with other factors, such as different environmental conditions or different genetic backgrounds.

  7. CRISPR/Cas9 DMS can be used to measure fitness for future environments. Natural selection can only measure fitness for the current environment. CRISPR/Cas9 DMS can be used to measure fitness for future environments, by simulating different environmental conditions in the laboratory.

  8. CRISPR/Cas9 DMS can be used to measure fitness at the molecular level. Natural selection measures fitness at the level of the individual organism. CRISPR/Cas9 DMS can be used to measure fitness at the molecular level, by measuring the expression of specific genes or the activity of specific proteins.

  9. CRISPR/Cas9 DMS can be used to identify new targets for genetic engineering. By measuring the fitness effects of different genetic changes, CRISPR/Cas9 DMS can be used to identify new targets for genetic engineering. For example, CRISPR/Cas9 DMS could be used to identify genes that could be edited to make crops more resistant to pests or diseases.

  10. CRISPR/Cas9 DMS can be used to develop new therapies for human diseases. By measuring the fitness effects of different genetic changes in human cells, CRISPR/Cas9 DMS could be used to develop new therapies for human diseases. For example, CRISPR/Cas9 DMS could be used to identify genes that could be edited to cure cancer or other genetic disorders.

Overall, CRISPR/Cas9 DMS is a powerful new tool that can be used to measure fitness in a wide range of organisms and under a variety of conditions. It has the potential to revolutionize our understanding of fitness and to accelerate the development of new genetic engineering and therapeutic strategies.

It stands to overthrow the 170 year old hypothesis of a Victorian age naturalist. Finally!!!


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