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This model is helpful in determining whether a certain gene mutation will cause the changes of the structures and functions of protein molecules.
Corresponding to the underlying mechanism of gene expression, it assumes that any single mutation will cause complete loss of protein function, which probably only occurs for non-sense mutations.
CYBA's mutation will cause the failure of phagocytosis and immune defects [ 50].
Additionally, Yeast 6 improves the accuracy of predicting the likelihood that a mutation will cause auxotrophy.
The probability that a mutation will cause disease tends to be higher when the missense mutation was within a functionally important region.
In absence of gene flow between two populations that were genetically identical at separation, mutation will cause allelic polymorphism to arise over time.
Similar(51)
This is appropriate biologically because it will typically not be possible to predict in advance, for example, whether loss of function mutations will cause an increase or decrease in trait values.
Thus, in tissues such as the proximal renal tubules, thyroid, gonads, and pituitary, where the maternal allele is the predominant source of Gs-alpha, maternally inherited mutations will cause a marked reduction of Gs-alpha levels, leading to hormone resistance.
Systematically predicting which mutations will cause nonfunctional or deleterious protein folds is not feasible, but nonetheless, mistranslation remains a strong force of selection on codon usage over evolutionary timescales (Drummond and Wilke, 2008, 2009).
The HSP proteins are involved in many different cellular functions, which underlie the pathogenic mechanisms by which mutations will cause HSP, including disrupted axonal pathfinding and axonal transport, disrupted ER morphology, myelin abnormality, mitochondrial dysfunction, disturbed endosomal dynamics and disturbed lipid metabolism (Blackstone, 2012).
The case K = 0 represents fitness landscapes possessing only main/additive effects; i.e., there is no epistasis and as such we can envision a Mount Fuji-like fitness landscape, where mutations will cause the population to ultimately climb to the maximum fitness, as there is only one local optimum that is also the global optimum.
Related(20)
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