Estimation of spontaneous mutation rates

Spontaneous or randomly occurring mutations play a key role in cancer progression. Estimation of the mutation rate of cancer cells can provide useful information about the disease. To ascertain these mutation rates, we need mathematical models that describe the distribution of mutant cells. In this investigation, we develop a discrete time stochastic model for a mutational birth process. We assume that mutations occur concurrently with mitosis so that when a nonmutant parent cell splits into two progeny, one of these daughter cells could carry a mutation. We propose an estimator for the mutation rate and investigate its statistical properties via theory and simulations. A salient feature of this estimator is the ease with which it can be computed. The methods developed herein are applied to a human colorectal cancer cell line and compared to existing continuous time models.     

Estimation of mutation rates in cultured mammalian cells

The factors that affect reliable estimations of mutation rates (μ) in cultured mammalian somatic cell populations by fluctuation analysis are studied experimentally and statistically. We analyze the differential effect of the final cell population size in each culture (N_t) and the number of parallel cultures (C) on the variation in the rate estimates ($\text{μ}$) inferred from the P₀ method. The analysis can be made after the derivation of the variance of $\text{μ}$, which is a measure of variation of $\text{μ}$ for a given combination of N_t and C in a number of repeat experiments. The variance of $\text{μ}$ is inversely proportional to C and to the square of N_t. N_t determines the probability of occurrence of mutation in a cell culture. By influencing the size of P₀, N_t also determines whether a rate estimate is obtainable from the experiment. Since P_o is estimated from the fraction of cultures containing no mutation in a set of C cultures, C becomes a determining factor for the accuracy of $\text{μ}$. The rate estimated from $\text{P}\text{?}{}_0$ is biased, but the bias is in general 2 orders of magnitude smaller than $\text{μ}$. By the selection of an appropriate combination of N_t and C for the experiment, this bias can be reduced even further.Based on the notion of comparing two proportions, we propose a test statistic and have applied it to experimental results for a test of equality of mutation rates in different cell lines. This development places the comparison of mutation rates on a statistical basis.     

Estimation of microsatellite mutation rates in Drosophila melanogaster

Microsatellite mutations were studied in a set of 175 mutation accumulation lines, all of them independently derived from a completely homozygous population of Drosophila melanogaster and maintained under strong inbreeding during 80 generations. We assayed 28 microsatellites and detected two mutations. One mutation consisted of a single addition of a dinucleotide repeat and the other was a deletion of five trinucleotide repeats. The average mutation rate was 5.1 x 10(-6), in full agreement with previous estimates from two different sets of mutation accumulation lines.     

Estimation of the male and female mutation rates in Duchenne muscular dystrophy (DMD)

Summary We present the results of an international collaborative study aimed at estimating the ratio of male to female mutation rates in Duchenne muscular dystrophy based on the method of C. Müller and T. Grimm. With a sample size of 295, this ratio is found to be very close to 1, thus giving evidence for equal mutation rates in males and females in Duchenne muscular dystrophy.     

Estimation of nucleotide diversity, disequilibrium coefficients, and mutation rates from high-coverage genome-sequencing projects

Recent advances in sequencing strategies have made it feasible to rapidly obtain high-coverage genomic profiles of single individuals, and soon it will be economically feasible to do so with hundreds to thousands of individuals per population. While offering unprecedented power for the acquisition of population-genetic parameters, these new methods also introduce a number of challenges, most notably the need to account for the binomial sampling of parental alleles at individual nucleotide sites and to eliminate bias from various sources of sequence errors. To minimize the effects of both problems, methods are developed for generating nearly unbiased and minimum-sampling-variance estimates of a number of key parameters, including the average nucleotide heterozygosity and its variance among sites, the pattern of decomposition of linkage disequilibrium with physical distance, and the rate and molecular spectrum of spontaneously arising mutations. These methods provide a general platform for the efficient utilization of data from population-genomic surveys, while also providing guidance for the optimal design of such studies.     

Environmental tuning of mutation rates

Through their life cycles, bacteria experience many different environments in which the relationship between available energy resources and the frequency and the nature of various stresses is highly variable. In order to survive in such changeable environments, bacteria must balance the need for nutritional competence with stress resistance. In Escherichia coli natural populations, this is most frequently achieved by changing the regulation of the RpoS sigma factor-dependent general stress response. One important secondary consequence of altered regulation of the RpoS regulon is the modification of mutation rates. For example, under nutrient limitation during stationary phase, the high intracellular concentration of RpoS diminishes nutritional competence, increases stress resistance, and, by downregulating the mismatch repair system and upregulating [corrected] the expression of the dinB gene (coding for PolIV translesion synthesis polymerase) increases mutation rates. The reduction of the intracellular concentration of RpoS has exactly opposite effects on nutritional competence, stress resistance and mutation rates. Therefore, the natural selection that favours variants having the highest fitness under different environmental conditions results in high variability of stress-associated mutation rates in those variants.     

Estimation of male to female ratio of mutation rates from carrier-detection tests in X-linked disorders.

A method is presented for the estimation of the ratio of male to female mutation rates from female carrier-detection test data from pedigrees containing an isolated male manifesting an X-linked necessive disorder. Pedigrees of any size and complexity (barring consanguinity) and containing any number of tested females can be utilized. The relative fitness of affected males and carrier females, and the segregation probability of the abnormal gamete in females, can be estimated simultaneously with the ratio of mutation rates in order to test specific hypotheses against given bodies of data. Here this method is applied to families containing isolated individuals affected with Lesch-Nyhan syndrome.     

Estimation of in-vivo miscoding rates

The replication of premutagenic DNA lesions generates mutant progeny in patterns that distinguish lesions that rarely produce a mutation per DNA replication from those that frequently do so. The quantitative aspects of this distinction were tested in studies of heat-mutagenized bacteriophage T4. Previous T4 studies had demonstrated that transition mutations produced at G.C base-pairs depended upon heat-induced DNA lesions distinct from those responsible for transversions at G.C pairs. In this study the transversion mutations are shown to arise in patterns predicted for mutations produced from lesions that miscode rarely (fewer than 10% per replication). In contrast, the transition mutations arise in patterns predicted for mutations produced from lesions that miscode at about 20 to 60% per replication. The fact that the two classes of DNA lesions are distinguishable as predicted by the quantitative model suggests that such studies may in general be useful in quantifying the behavior of mutation-generating DNA lesions. The method employed also estimates the frequency of premutagenic lesions in DNA.     

Statistical inference of sequence-dependent mutation rates

Several lines of research are now converging towards an integrated understanding of mutational mechanisms and their evolutionary implications. Experimentally, crystal structures reveal the effect of sequence context on polymerase fidelity; large-scale sequencing projects generate vast amounts of sequence polymorphism data; and locus-specific databases are being constructed. Computationally, software and analytical tools have been developed to analyze mutational data, to identify mutational hot spots, and to compare the signatures of mutagenic agents.     

Evolution of mutation rates in bacteria

Evolutionary success of bacteria relies on the constant fine-tuning of their mutation rates, which optimizes their adaptability to constantly changing environmental conditions. When adaptation is limited by the mutation supply rate, under some conditions, natural selection favours increased mutation rates by acting on allelic variation of the genetic systems that control fidelity of DNA replication and repair. Mutator alleles are carried to high frequency through hitchhiking with the adaptive mutations they generate. However, when fitness gain no longer counterbalances the fitness loss due to continuous generation of deleterious mutations, natural selection favours reduction of mutation rates. Selection and counter-selection of high mutation rates depends on many factors: the number of mutations required for adaptation, the strength of mutator alleles, bacterial population size, competition with other strains, migration, and spatial and temporal environmental heterogeneity. Such modulations of mutation rates may also play a role in the evolution of antibiotic resistance.     

Likelihood-based estimation of microsatellite mutation rates

Microsatellites are widely used in genetic analyses, many of which require reliable estimates of microsatellite mutation rates, yet the factors determining mutation rates are uncertain. The most straightforward and conclusive method by which to study mutation is direct observation of allele transmissions in parent-child pairs, and studies of this type suggest a positive, possibly exponential, relationship between mutation rate and allele size, together with a bias toward length increase. Except for microsatellites on the Y chromosome, however, previous analyses have not made full use of available data and may have introduced bias: mutations have been identified only where child genotypes could not be generated by transmission from parents' genotypes, so that the probability that a mutation is detected depends on the distribution of allele lengths and varies with allele length. We introduce a likelihood-based approach that has two key advantages over existing methods. First, we can make formal comparisons between competing models of microsatellite evolution; second, we obtain asymptotically unbiased and efficient parameter estimates. Application to data composed of 118,866 parent-offspring transmissions of AC microsatellites supports the hypothesis that mutation rate increases exponentially with microsatellite length, with a suggestion that contractions become more likely than expansions as length increases. This would lead to a stationary distribution for allele length maintained by mutational balance. There is no evidence that contractions and expansions differ in their step size distributions.