How does the possible impact of a chromosomal mutation

Many organisms have powerful control genes that determine how the body is laid out. For example, Hox genes are found in many animals including flies and humans and designate where the head goes and which regions of the body grow appendages. So evolving a major change in basic body layout may not be so unlikely; it may simply require a change in a Hox gene and the favor of natural selection. Weird Fact: Mutations to control genes can transform one body part into another.

Scientists have studied flies carrying Hox mutations that sprout legs on their foreheads instead of antennae! The causes of mutations. A case study of the effects of mutation: Sickle cell anemia. Subscribe to our newsletter. Email Facebook Twitter. Detrimental effect. Fruit fly image courtesy of the Syndicat National des Ophtalmologistes de France. Lynch, M.

Perspective: Spontaneous deleterious mutation. Evolution 53 , — Orr, H. The genetic theory of adaptation: A brief history. Nature Review Genetics 6 , — doi Sandelin, A.

Arrays of ultraconserved non-coding regions span the loci of key developmental genes in vertebrate genomes. BMC Genomics 5 , 99 Restriction Enzymes. Genetic Mutation. Functions and Utility of Alu Jumping Genes. Transposons: The Jumping Genes. DNA Transcription. What is a Gene? Colinearity and Transcription Units. Copy Number Variation. Copy Number Variation and Genetic Disease.

Copy Number Variation and Human Disease. Tandem Repeats and Morphological Variation. Chemical Structure of RNA.

Eukaryotic Genome Complexity. RNA Functions. Genetic Mutation By: Dr. Citation: Loewe, L. Nature Education 1 1 Is it possible to have "too many" mutations? What about "too few"? While mutations are necessary for evolution, they can damage existing adaptations as well.

Aa Aa Aa. What is a mutation? Are Mutations Random? Types of Mutations. Effects of Mutations. Estimating Rates of Mutation. References and Recommended Reading Drake, J. Genetics , — Eyre-Walker, A. Biology Letters 2 , — Lynch, M. Evolution 53 , — Orr, H.

Article History Close. Share Cancel. Revoke Cancel. Keywords Keywords for this Article. Save Cancel. Flag Inappropriate The Content is: Objectionable. Flag Content Cancel. Email your Friend. Submit Cancel. This content is currently under construction. Explore This Subject. Applications in Biotechnology. DNA Replication. Jumping Genes. Discovery of Genetic Material. Gene Copies. No topic rooms are there. Following the single-fitness-peak approximation that is commonly used as a starting point in quasispecies and population genetics models, we assume that for each homologous group there is a wild-type chromosome for which that chromosome is functional.

Any mutation to the wild-type is assumed to render the chromosome non-functional. If the chromosomes are taken to be sufficiently long, then we may make an approximation known as the neglect of backmutations , which states that a template strand that differs from the wild-type will produce a daughter that differs from the wild-type with probability. The basis for this assumption is that, for a sufficiently long chromosome, any new mutations will likely occur in a previously unmutated portion of the genome, so that the wild-type cannot be restored.

Finally, we assume that the first-order growth rate constant, or fitness, of a genome is determined by the number of functional chromosomes in each homologous group, as well as by the number of non-functional chromosomes in each homologous group. Thus, if denotes the number of functional chromosomes in homologous group , and denotes the number of non-functional chromosomes, then the fitness is given by , where.

When a given parent cell reproduces, it produces two daughters. Given a left daughter cell with genome characterized by , we define parameters , where , for and for , as follows:. Now, for , let , where , and , where. If , denote the number of functional and non-functional chromosomes in homologous group , respectively, then we have, 1 For the left daughter cell, we also have, 2 These two equations imply that , and so we have that.

We then have that , , , , ,. Taking into account the transition probabilities listed above, as well as degeneracies in the ways we can choose the segregation patterns of the chromosomes consistent with given values of , we obtain, 3 where is the fraction of the population whose genome is characterized by , and is the mean fitness of the population, or the average of all the first-order growth-rate constants weighted over the population distribution.

We assume that the fitness is either or. The fitness is taken to be if each homologous group contains at least one functional chromosome, and if the total number of chromosomes does not exceed some value.

Otherwise, the fitness is taken to be. If , then the fitness only depends on the number of functional chromosomes in each homologous group, so that we may write.

If we define to be the total fraction of the population with functional chromosomes in homologous group , where , then by summing over all possible values of , we obtain, after some manipulation, 4. We may analytically solve for the mutation-selection balance of Eq. To do so, we define the quantity via, 5 Using Eq. Interestingly, this suggests that the mean fitness at steady-state does not depend on the value of.

In Figure 1 we show a plot of the steady-state mean fitness, or , obtained from a stochastic simulation of reproducing organisms. Instead of plotting the mean fitness versus , we plotted it versus. Note the good agreement between our theory and the simulation results. We took , , and. The stochastic simulation was run with a population size of , out to a time of in time steps of , and with an initially clonal, wild-type population of haploids.

Although we do not show plots for smaller values of , we do indeed find that, as is decreased, the mean fitness drops, and may drop significantly below the values. Our result for the mean fitness hinges on the assumption that converges to a finite value.

However, for , if this is the case, then it follows that. This implies, however, that at mutation-selection balance for. To see this, note that since cells with some finite have a positive probability of producing a daughter without any chromosomes in homologous group , it follows that if with some finite, then the subsequent dynamics will lead to the production of genomes with zero fitness, resulting in , contradicting the fact that the population is at steady-state.

The way this issue is resolved is if for , so that, by continuity, for. Also, is finite for , but infinite for. As a result, the convergence of as a function of is not uniform, but rather must be increased as. While we do not show plots of , our stochastic simulation results suggest that the analysis above is indeed correct. We developed a simpe mathematical model describing the evolutionary dynamics of a population exhibiting CIN.