Showing papers on "Mutation (genetic algorithm) published in 1993"

A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping. IV. Nested analyses with cladogram uncertainty and recombination.

Abstract: We previously developed an analytical strategy based on cladistic theory to identify subsets of haplotypes that are associated with significant phenotypic deviations. Our initial approach was limited to segments of DNA in which little recombination occurs. In such cases, a cladogram can be constructed from the restriction site data to estimate the evolutionary steps that interrelate the observed haplotypes to one another. The cladogram is then used to define a nested statistical design for identifying mutational steps associated with significant phenotypic deviations. The central assumption behind this strategy is that a mutation responsible for a particular phenotypic effect is embedded within the evolutionary history that is represented by the cladogram. The power of this approach depends on the accuracy of the cladogram in portraying the evolutionary history of the DNA region. This accuracy can be diminished both by recombination and by uncertainty in the estimated cladogram topology. In a previous paper, we presented an algorithm for estimating the set of likely claodgrams and recombination events. In this paper we present an algorithm for defining a nested statistical design under cladogram uncertainty and recombination. Given the nested design, phenotypic associations can be examined using either a nested analysis of variance (for haploids or homozygous strains) or permutation testing (for outcrossed, diploid gene regions). In this paper we also extend this analytical strategy to include categorical phenotypes in addition to quantitative phenotypes. Some worked examples are presented using Drosophila data sets. These examples illustrate that having some recombination may actually enhance the biological inferences that may derived from a cladistic analysis. In particular, recombination can be used to assign a physical localization to a given subregion for mutations responsible for significant phenotypic effects.

A mutation in CFTR produces different phenotypes depending on chromosomal background

Abstract: Cystic fibrosis (CF) is caused by mutations in the CF transmembrane conductance regulator (CFTR) gene but the association between mutation (genotype) and disease presentation (phenotype) is not straightforward. We have been investigating whether variants in the CFTR gene that alter splicing efficiency of exon 9 can affect the phenotype produced by a mutation. A missense mutation, R117H, which has been observed in three phenotypes, was found to occur on two chromosome backgrounds with intron 8 variants that have profoundly different effects upon splicing efficiency. A close association is shown between chromosome background of the R117H mutation and phenotype. These findings demonstrate that the genetic context in which a mutation occurs can play a significant role in determining the type of illness produced.

Genetic Algorithms for Tracking Changing Environments

Abstract: : In this paper, we explore the use of alternative mutation strategies as a means of increasing diversity so that the GA can track the optimum of a changing environment. This paper contrasts three different strategies: the Standard GA using a constant level of mutation, a mechanism called Random Immigrants, that replaces part of the population each generation with randomly generated values, and an adaptive mechanism called Triggered Hypermutation, that increases the mutation rate whenever there is a degradation in the performance of the time-averaged best performance. The study examines each of these strategies in the context of several kinds of environmental change, including linear translation of the optimum, random movement of the optimum, and oscillation between two significantly different landscapes. These first results should lead to the development of a single mechanism that can work well in both stationary and nonstationary environments. (AN)

Optimal Mutation Rates in Genetic Search

Abstract: The optimization of a single bit string by means of iterated mutation and selection of the best a Genetic Algorithm is dis cussed with respect to three simple tness functions The counting ones problem a standard binary encoded integer and a Gray coded integer optimization problem A mu tation rate schedule that is optimal with re spect to the success probability of mutation is presented for each of the objective functions and it turns out that the standard binary code can hamper the search process even in case of unimodal objective functions While normally a mutation rate of l where l de notes the bit string length is recommend able our results indicate that a variation of the mutation rate is useful in cases where the tness function is a multimodal pseudo boolean function where multimodality may be caused by the objective function as well as the encoding mechanism

Muller's ratchet and mutational meltdowns.

Abstract: We extend our earlier work on the role of deleterious mutations in the extinction of obligately asexual populations. First, we develop analytical models for mutation accumulation that obviate the need for time-consuming computer simulations in certain ranges of the parameter space. When the number of mutations entering the population each generation is fairly high, the number of mutations per individual and the mean time to extinction can be predicted using classical approaches in quantitative genetics. However, when the mutation rate is very low, a fixation-probability approach is quite effective. Second, we show that an intermediate selection coefficient (s) minimizes the time to extinction. The critical value of s can be quite low, and we discuss the evolutionary implications of this, showing that increased sensitivity to mutation and loss of capacity for DNA repair can be selectively advantageous in asexual organisms. Finally, we consider the consequences of the mutational meltdown for the extinction of mitochondrial lineages in sexual species.

A mutation in the human ryanodine receptor gene associated with central core disease.

Abstract: Central core disease (CCD) is a morphologically distinct, autosomal dominant myopathy with variable clinical features A close association with malignant hyperthermia (MH) has been identified Since MH and CCD genes have been linked to the skeletal muscle ryanodine receptor (RYR1) gene, cDNA sequence analysis was used to search for a causal RYR1 mutation in a CCD individual The only amino acid substitution found was an Arg2434His mutation, resulting from the substitution of A for G7301 This mutation was linked to CCD with a lod score of 48 at a recombinant fraction of 00 in 16 informative meioses in a 130 member family, suggesting a causal relationship to CCD

An experimental evaluation of selective mutation

Abstract: Mutation testing is a technique for unit-testing software that, although powerful, is computationally expensive. The principal expense of mutation is that many variants of the test program, called mutants, must be repeatedly executed. Selective mutation is a way to approximate mutation testing that saves execution by reducing the number of mutants that must be executed. The authors report experimental results that compare selective mutation testing to standard, or nonselective, mutation testing. The results support the hypothesis that selective mutation is almost as strong as nonselective mutation. In experimental trials, selective mutations provide almost the same coverage as nonselective mutation, with significant reductions in cost. >

Crossover or Mutation

Abstract: Genetic algorithms rely on two genetic operators - crossover and mutation. Although there exists a large body of conventional wisdom concerning the roles of crossover and mutation, these roles have not been captured in a theoretical fashion. For example, it has never been theoretically shown that mutation is in some sense “less powerful” than crossover or vice versa. This paper provides some answers to these questions by theoretically demonstrating that there are some important characteristics of each operator that are not captured by the other.

Adaptive Mutation: The Uses of Adversity

Abstract: When populations of microorganisms are subjected to certain nonlethal selections, useful mutants arise among the nongrowing cells whereas useless mutants do not. This phenomenon, known as adaptive, directed, or selection-induced mutation, challenges the long-held belief that mutations only arise at random and without regard for utility. In recent years a growing number of studies have examined adaptive mutation in both bacteria and yeast. Although conflicts and controversies remain, the weight of the evidence indicates that adaptive mutation cannot be explained by trivial artifacts and that nondividing cells accumulate mutations in the absence of genomic replication. Because this process tends to produce only useful mutations, the cells appear to have a mech- anism for preventing useless genetic changes from occurring or for eliminating them after they occur. The model that most readily explains the evidence is that cells under stress produce genetic variants continuously and at random, but these variants are immortalized as mutations only if they allow the cell to grow.

The full mutation in the FMR–1 gene of male fragile X patients is absent in their sperm

Abstract: Fragile X syndrome is characterized at the molecular level by amplification of a (CGG)n repeat and hypermethylation of a CpG island preceeding the open reading frame of the fragile X gene (FMR-1) located in Xq27.3. Anticipation in this syndrome is associated with progressive amplification of the (CGG)n repeat from a premutation to a full mutation through consecutive generations. Remarkably, expansion of the premutation to the full mutation is strictly maternal. To clarify this parental influence we studied FMR-1 in sperm of four male fragile X patients. This showed that only the premutation was present in their sperm, although they had a full mutation in peripheral lymphocytes. This might suggest that expansion of the premutation to the full mutation in FMR-1 does not occur in meiosis but in a postzygotic stage.

The mutation at nt 8993 of mitochondrial DNA is a common cause of Leigh's syndrome

Abstract: Twelve patients with Leigh's syndrome from 10 families harbored a T > G point mutation at nt 8993 of mtDNA. This mutation, initially associated with neurogenic weakness, ataxia, and retinitis pigmentosa, was later found to result in the Leigh phenotype when present in a high percentage. In our patients, the mutation was heteroplasmic, maternally inherited, and appeared to segregate rapidly within the pedigrees. Quantitative analysis revealed a good correlation between percentage of mutant mitochondrial genomes and severity of the clinical phenotype. The mutation was not found in > 200 patients with other mitochondrial encephalomyopathies or in controls. Mitochondrial enzyme activities were normal in all but 1 patient, and there were no ragged-red fibers in the muscle biopsy. Lactic acidosis was present in 92% of patients. Our findings suggest that the mtDNA nt 8993 mutation is a relatively common cause of Leigh's syndrome.

The science of breeding and its application to the breeder genetic algorithm (bga)

Abstract: The breeder genetic algorithm (BGA) models artificial selection as performed by human breeders. The science of breeding is based on advanced statistical methods. In this paper a connection between genetic algorithm theory and the science of breeding is made. We show how the response to selection equation and the concept of heritability can be applied to predict the behavior of the BGA. Selection, recombination, and mutation are analyzed within this framework. It is shown that recombination and mutation are complementary search operators. The theoretical results are obtained under the assumption of additive gene effects. For general fitness landscapes, regression techniques for estimating the heritability are used to analyze and control the BGA. The method of decomposing the genetic variance into an additive and a nonadditive part connects the case of additive fitness functions with the general case.

Sensor placement for on-orbit modal identification via a genetic algorithm

Abstract: The selection and reproduction schemes of the genetic algorithm are modified, and a new operator called forced mutation is introduced. These changes are shown to improve the convergence of the algorithm and to lead to near-optimal sensor locations. Two practical examples are investigated: sensor placement for an early version of the space station and an individual space station photovoltaic array

Origin of the expansion mutation in myotonic dystrophy.

Abstract: Myotonic dystrophy (DM) is caused by the expansion of a CTG trinucleotide repeat. The mutation is in complete linkage disequilibrium with a nearby two–allele insertion/deletion polymorphism, suggesting a single origin for the mutation or predisposing mutation. To trace this ancestral event, we have studied the association of CTG repeat alleles in a normal population to alleles of the insertion/deletion polymorphism and of a (CA)n repeat marker 90 kilobases from the DM mutation. The results strongly suggest that the initial predisposing event(s) consisted of a transition from a (CTG)5 allele to anallele with 19 to 30 repeats. The heterogeneous class of (CTG)19–30 alleles which has an overall frequency of about 10%, may constitute a reservoir for recurrent DM mutations.

Clinical features associated with the A-->G transition at nucleotide 8344 of mtDNA ("MERRF mutation").

Abstract: We looked for the A-->G transition at position 8344 of mtDNA in 150 patients, most of them with diagnosed or suspected mitochondrial disease, to assess the specificity of this mutation for the MERRF phenotype, to define the clinical spectrum associated with the mutation, and to study the relationship between percentage of mutation in muscle and clinical severity. Our results confirm the high correlation between the A-->G transition at position 8344 and the MERRF syndrome, but they also show that this mutation can be associated with other phenotypes, including Leigh's syndrome, myoclonus or myopathy with truncal lipomas, and proximal myopathy. The absence of the mutation in four typical MERRF patients suggests that other mutations in the tRNA(Lys) gene, or elsewhere in the mitochondrial DNA, can produce the same phenotype.

The directed mutation controversy and neo-Darwinism

Abstract: According to neo-Darwinian theory, random mutation produces genetic differences among organisms whereas natural selection tends to increase the frequency of advantageous alleles. However, several recent papers claim that certain mutations in bacteria and yeast occur at much higher rates specifically when the mutant phenotypes are advantageous. Various molecular models have been proposed that might explain these directed mutations, but the models have not been confirmed. Critics contend that studies purporting to demonstrate directed mutation lack certain controls and fail to account adequately for population dynamics. Further experiments that address these criticisms do not support the existence of directed mutations.

Identification of a common mutation in the carnitine palmitoyltransferase II gene in familial recurrent myoglobinuria patients.

Abstract: Carnitine palmitoyltransferase (CPT) II deficiency is the most common inherited disorder of lipid metabolism affecting skeletal muscle. We have identified a missense mutation (Ser113Leu) in one patient with the classical muscular symptomatology. Transfection experiments in COS cells demonstrate that the mutation drastically depresses the catalytic activity of CPT II. The mutation results in normal synthesis but a markedly reduced steady-state level of the protein, indicating decreased stability of mutant CPT II. The Ser113Leu mutation is the most frequent cause of CPT II deficiency. The mutation can be detected easily by restriction analysis enabling molecular diagnosis of most patients and identification of heterozygous carriers.

A markov chain framework for the simple genetic algorithm

Abstract: This paper develops a theoretical framework for the simple genetic algorithm (combinations of the reproduction, mutation, and crossover operators) based on the asymptotic state behavior of a nonstationary Markov chain algorithm model. The methodology borrows heavily from that of simulated annealing. We prove the existence of a unique asymptotic probability distribution (stationary distribution) for the Markov chain when the mutation probability is used with any constant nonzero probability value. We develop a Cramer's Rule representation of the stationary distribution components for all nonzero mutation probability values and then extend the representation to show that the stationary distribution possesses a zero mutation probability limit. Finally, we present a strong ergodicity bound on the mutation probability sequence that ensures that the nonstationary algorithm (which results from varying mutation probability during algorithm execution) achieves the limit distribution asymptotically. Although the focus of this work is on a nonstationary algorithm in which mutation probability is reduced asymptotically to zero via a schedule (in a fashion analogous to simulated annealing), the stationary distribution results (existence, Cramer's Rule representation, and zero mutation probability limit) are directly applicable to conventional, simple genetic algorithm implementations as well.

Training product unit neural networks with genetic algorithms

Abstract: Product unit neural networks are useful because they can handle higher order combinations of inputs When trained using traditional backpropagation, however, they are often susceptible to local minima The use of genetic algorithm exploratory procedures that can often locate near-optimal solutions to complex problems to overcome this, is discussed The genetic algorithm maintains a set of trial solutions and forces them to evolve toward an acceptable solution A representation for possible solutions must first be developed Then, with an initial random population, the algorithm uses survival of the fittest techniques as well as old knowledge in the gene pool to improve each generation's ability to solve the problem This improvement is achieved through a four-step process of evaluation, reproduction, breeding, and mutation An example application is described >

Genetic variation and random drift in autotetraploid populations.

Abstract: The rate of decay of genetic variation is determined for randomly mating autotetraploid populations of finite size, and the equilibrium homozygosity under mutation and random drift is calculated. It is shown that heterozygosity is lost at a slower rate than in diploid populations, and that the equilibrium heterozygosity with mutation and random drift is higher than for diploids. Outcrossing populations as well as populations that randomly self are analyzed. A method of comparing genetic variation between autotetraploid and diploid populations is proposed. Our treatment suggests that the "gametic homozygosity" provides a unified approach for comparing genotypes within a population as well as comparing genetic variation between populations with different levels of ploidy.

Real-time replication garbage collection

Abstract: We have implemented the first copying garbage collector that permits continuous unimpeded mutator access to the original objects during copying. The garbage collector incrementally replicates all accessible objects and uses a mutation log to bring the replicas up-to-date with changes made by the mutator. An experimental implementation demonstrates that the costs of using our algorithm are small and that bounded pause times of 50 milliseconds can be readily achieved.