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One silent mutation causes the dopamine receptor D2 gene to be less stable and degrade faster, underexpressing the gene. A silent mutation in the multidrug resistance gene 1 , which codes for a cellular membrane pump that expels drugs from the cell, can slow down translation in a specific location to allow the peptide chain to bend into an ...
It is a measure of the "population mutation rate" (the product of the effective population size and the neutral mutation rate) from the observed nucleotide diversity of a population. θ = 4 N e μ {\displaystyle \theta =4N_{e}\mu } , [ 3 ] where N e {\displaystyle N_{e}} is the effective population size and μ {\displaystyle \mu } is the per ...
Point substitution mutations of a codon, classified by their impact on protein sequence. A synonymous substitution (often called a silent substitution though they are not always silent) is the evolutionary substitution of one base for another in an exon of a gene coding for a protein, such that the produced amino acid sequence is not modified.
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For example, for an amino acid sequence (there are 20 "standard" amino acids that make up proteins), one would find there are 209 parameters. However, when studying coding regions of the genome, it is more common to work with a codon substitution model (a codon is three bases and codes for one amino acid in a protein).
An example would be a seemingly silent mutation in the multidrug resistance gene 1 , which codes for a cellular membrane pump that expels drugs from the cell, can slow down translation and allow the peptide chain to fold into an unusual conformation, causing the mutant pump to be less functional (in MDR1 protein e.g. C1236T polymorphism changes ...
Where k is the length of a DNA sequence and is the probability a mutation will occur at a site. [5] Watterson developed an estimator for mutation rate that incorporates the number of segregating sites (Watterson's estimator). [6] One way to think of the ISM is in how it applies to genome evolution.
Tajima's D is a population genetic test statistic created by and named after the Japanese researcher Fumio Tajima. [1] Tajima's D is computed as the difference between two measures of genetic diversity: the mean number of pairwise differences and the number of segregating sites, each scaled so that they are expected to be the same in a neutrally evolving population of constant size.