Mutation (genetic algorithm)

About: Mutation (genetic algorithm) is a research topic. Over the lifetime, 31223 publications have been published within this topic receiving 720553 citations.

Microsatellites, from molecules to populations and back

Abstract: Population genetics studies using microsatellites, and data on their molecular dynamics, are on the increase. But, so far, no consensus has emerged on which mutation model should be used, though this is of paramount importance for analysis of population genetic structure. However, this is not surprising given the variety of microsatellite molecular motifs. Null alleles may be disturbing for population studies, even though their presence can be detected through careful population analyses, while homoplasy seems of little concern, at least over short evolutionary scales. Interspecific studies show that microsatellites are poor markers for phylogenetic inference. However, these studies are fuelling discussions on directional mutation and the role of selection and recombination in their evolution. Nonetheless, it remains true that microsatellites may be considered as good, neutral mendelian markers.

A second common mutation in the methylenetetrahydrofolate reductase gene: an additional risk factor for neural-tube defects?

Abstract: Summary Recently, we showed that homozygosity for the common 677(C→T) mutation in the methylenetetrahydrofolate reductase (MTHFR) gene, causing thermolability of the enzyme, is a risk factor for neural-tube defects (NTDs). We now report on another mutation in the same gene, the 1298(A→C) mutation, which changes a glutamate into an alanine residue. This mutation destroys an Mbo II recognition site and has an allele frequency of .33. This 1298(A→C) mutation results in decreased MTHFR activity (one-way analysis of variance [ANOVA] P P P n = 86) of the NTD patients compared with 20% ( n = 403) among controls, resulting in an odds ratio of 2.04 (95% confidence interval: .9–4.7). These data suggest that the combined heterozygosity for the two MTHFR common mutations accounts for a proportion of folate-related NTDs, which is not explained by homozygosity for the 677(C→T) mutation, and can be an additional genetic risk factor for NTDs.

Impact of mutant p53 functional properties on TP53 mutation patterns and tumor phenotype: lessons from recent developments in the IARC TP53 database.

Abstract: The tumor suppressor gene TP53 is frequently mutated in human cancers More than 75% of all mutations are missense substitutions that have been extensively analyzed in various yeast and human cell assays The International Agency for Research on Cancer (IARC) TP53 database (www-p53iarcfr) compiles all genetic variations that have been reported in TP53 Here, we present recent database developments that include new annotations on the functional properties of mutant proteins, and we perform a systematic analysis of the database to determine the functional properties that contribute to the occurrence of mutational "hotspots" in different cancer types and to the phenotype of tumors This analysis showed that loss of transactivation capacity is a key factor for the selection of missense mutations, and that difference in mutation frequencies is closely related to nucleotide substitution rates along TP53 coding sequence An interesting new finding is that in patients with an inherited missense mutation, the age at onset of tumors was related to the functional severity of the mutation, mutations with total loss of transactivation activity being associated with earlier cancer onset compared to mutations that retain partial transactivation capacity Furthermore, 80% of the most common mutants show a capacity to exert dominant-negative effect (DNE) over wild-type p53, compared to only 45% of the less frequent mutants studied, suggesting that DNE may play a role in shaping mutation patterns These results provide new insights into the factors that shape mutation patterns and influence mutation phenotype, which may have clinical interest

Analysis of protein-coding genetic variation in 60,706 humans

Abstract: Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities. The resulting catalogue of human genetic diversity has unprecedented resolution, with an average of one variant every eight bases of coding sequence and the presence of widespread mutational recurrence. The deep catalogue of variation provided by the Exome Aggregation Consortium (ExAC) can be used to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; we identify 3,230 genes with near-complete depletion of truncating variants, 79% of which have no currently established human disease phenotype. Finally, we show that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human knockout variants in protein-coding genes.

What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity.

Abstract: We review commonly used population definitions under both the ecological paradigm (which emphasizes demographic cohesion) and the evolutionary paradigm (which emphasizes reproductive cohesion) and find that none are truly operational. We suggest several quantitative criteria that might be used to determine when groups of individuals are different enough to be considered ‘populations’. Units for these criteria are migration rate ( m ) for the ecological paradigm and migrants per generation ( Nm ) for the evolutionary paradigm. These criteria are then evaluated by applying analytical methods to simulated genetic data for a finite island model. Under the standard parameter set that includes L = 20 High mutation (microsatellitelike) loci and samples of S = 50 individuals from each of n = 4 subpopulations, power to detect departures from panmixia was very high (∼ 100%; P < 0.001) even with high gene flow ( Nm = 25). A new method, comparing the number of correct population assignments with the random expectation, performed as well as a multilocus contingency test and warrants further consideration. Use of Low mutation (allozyme-like) markers reduced power more than did halving S or L . Under the standard parameter set, power to detect restricted gene flow below a certain level X (H 0 : Nm < X ) can also be high, provided that true Nm ≤ 0.5 X . Developing the appropriate test criterion, however, requires assumptions about several key parameters that are difficult to estimate in most natural populations. Methods that cluster individuals without using a priori sampling information detected the true number of populations only under conditions of moderate or low gene flow ( Nm ≤ ≤ ≤ 5), and power dropped sharply with smaller samples of loci and individuals. A simple algorithm based on a multilocus contingency test of allele frequencies in pairs of samples has high power to detect the true number of populations even with Nm = 25 but requires more rigorous statistical evaluation. The ecological paradigm remains challenging for evaluations using genetic markers, because the transition from demographic dependence to independence occurs in a region of high migration where genetic methods have relatively little power. Some recent theoretical developments and continued advances in computational power provide hope that this situation may change in the future.