Why are phenotypic mutation rates much higher than genotypic mutation rates?

The evolution of genotypic mutation rates has been investigated in numerous theoretical and experimental studies. Mutations, however, occur not only when copying DNA, but also when building the phenotype, especially when translating and transcribing DNA to RNA and protein. Here we study the effect of such phenotypic mutations. We find a maximum phenotypic mutation rate, umax, that is compatible with maintaining a certain function of the organism. This may be called a phenotypic error threshold. In particular, we find a minimum phenotypic mutation rate, umin, with the property that there is (nearly) no selection pressure to reduce the rate of phenotypic mutations below this value. If there is a cost for lowering the phenotypic mutation rate, then umin is close to the optimum phenotypic mutation rate that maximizes the fitness of the organism. In our model, there is selective pressure to decrease the rate of genotypic mutations to zero, but to decrease the rate of phenotypic mutations only to a positive value. Despite its simplicity, our model can explain part of the huge difference between genotypic and phenotypic mutation rates that is observed in nature. The relevant data are summarized.     

ND4 mutation in transitional cell carcinoma: Does mitochondrial mutation occur before tumorigenesis?

To investigate how mitochondrial mutation occurs in cancers, we analyzed ND4 mutation in 53 transitional cell carcinomas (TCCs) of the upper urinary tract and the normal counterpart (perirenal soft tissue). Three methods, i.e., DNA sequencing, restriction fragment length polymorphism (RFLP), and denaturing high-performance liquid chromatography (DHPLC), were employed because of their different sensitive of detecting mutation. The results of sequencing and RFLP showed that ND4 mutations were only found in 24.5% (13/53) of tumor. However, 11 of these mutations could also be identified in the normal tissue by DHPLC, indicating that most mitochondrial mutations identified in tumors preexist as minor components, which are too low in quantity to be detected by less sensitive methods such as DNA sequencing. The result suggests that mtDNA mutation occurs before tumorigenesis and become apparent in cancer cells.     

Exploring the common molecular basis for the universal DNA mutation bias: revival of Löwdin mutation model

Recently, numerous genome analyses revealed the existence of a universal G:C→A:T mutation bias in bacteria, fungi, plants and animals. To explore the molecular basis for this mutation bias, we examined the three well-known DNA mutation models, i.e., oxidative damage model, UV-radiation damage model and CpG hypermutation model. It was revealed that these models cannot provide a sufficient explanation to the universal mutation bias. Therefore, we resorted to a DNA mutation model proposed by L?wdin 40 years ago, which was based on inter-base double proton transfers (DPT). Since DPT is a fundamental and spontaneous chemical process and occurs much more frequently within GC pairs than AT pairs, L?wdin model offers a common explanation for the observed universal mutation bias and thus has broad biological implications.     

Hereditary retinoblastoma: delayed mutation or host resistance?

Evidence is presented from the literature that there is little need to postulate delayed mutation for the retinoblastoma locus. Both penetrance and expressivity in the gene carrier can be defined as a variable determined by genetic and environmental factors, not by a Poisson distribution of tumors formed. Of individuals who received a new mutation from a healthy parent, approximately 13% do not manifest retinoblastoma, and the heritability of the host resistance is estimated at about 90%. The nonhereditary form of retinoblastoma may occur in the most susceptible group of the population.     

Evolutionary genetics: what is driving male mutation?

In mammals, most new mutations occur in males. But a study of the evolution of a human X to Y chromosomal translocation has revealed a sex bias much lower than previous estimates. Patterns of substitution suggest that differential methylation between male and female germ lines is a key determinant of the mutation rate.     

Estimating mutation rate: how to count mutations?

Mutation rate is an essential parameter in genetic research. Counting the number of mutant individuals provides information for a direct estimate of mutation rate. However, mutant individuals in the same family can share the same mutations due to premeiotic mutation events, so that the number of mutant individuals can be significantly larger than the number of mutation events observed. Since mutation rate is more closely related to the number of mutation events, whether one should count only independent mutation events or the number of mutants remains controversial. We show in this article that counting mutant individuals is a correct approach for estimating mutation rate, while counting only mutation events will result in underestimation. We also derived the variance of the mutation-rate estimate, which allows us to examine a number of important issues about the design of such experiments. The general strategy of such an experiment should be to sample as many families as possible and not to sample much more offspring per family than the reciprocal of the pairwise correlation coefficient within each family. To obtain a reasonably accurate estimate of mutation rate, the number of sampled families needs to be in the same or higher order of magnitude as the reciprocal of the mutation rate.     

How does mutation affect the distribution of phenotypes?

The potential for mutational processes to influence patterns of neutral or adaptive phenotypic evolution is not well understood. If mutations are directionally biased, shifting trait means in a particular direction, or if mutation generates more variance in some directions of multivariate trait space than others, mutation itself might be a source of bias in phenotypic evolution. Here, we use mutagenesis to investigate the affect of mutation on trait mean and (co)variances in zebrafish, Danio rerio. Mutation altered the relationship between age and both prolonged swimming speed and body shape. These observations suggest that mutational effects on ontogeny or aging have the potential to generate variance across the phenome. Mutations had a far greater effect in males than females, although whether this is a reflection of sex‐specific ontogeny or aging remains to be determined. In males, mutations generated positive covariance between swimming speed, size, and body shape suggesting the potential for mutation to affect the evolutionary covariation of these traits. Overall, our observations suggest that mutation does not generate equal variance in all directions of phenotypic space or in each sex, and that pervasive variation in ontogeny or aging within a cohort could affect the variation available to evolution.     

The same “TATA” box β-thalassemia mutation in Chinese and US blacks: another example of independent origins of mutation

Summary A Chinese ⁺-thalassemia gene in a new haplotype was chosen for cloning and sequencing. The mutation identified was an A-G transition at position-29 in the TATA box of the -globin gene. This mutation has not been seen previously in Chinese but has been documented in American blacks on a different chromosomal background. This observation provides further evidence for independent origins of the same mutation in distinct ethnic groups.     

Frequency of the C34T mutation of the AMPD1 gene in world-class endurance athletes: does this mutation impair performance?

The C34T mutation in the gene encoding for the skeletal muscle-specific isoform of AMP deaminase (AMPD1) is a common mutation among Caucasians (i.e., one of five individuals) that can impair exercise capacity. The purpose of this study was twofold. First, we determined the frequency distribution of the C34T mutation in a group of top-level Caucasian (Spanish) male endurance athletes (cyclists and runners, n = 104). This group was compared with randomly selected Caucasian (Spanish) healthy (asymptomatic) nonathletes (n = 100). The second aim of this study was to compare common laboratory indexes of endurance performance (maximal oxygen uptake or ventilatory thresholds) within the group of athletes depending on their C34T AMPD1 genotype. The frequency of the mutant T allele was lower (P < 0.05) in the group of athletes (4.3%) compared with controls (8.5%). On the other hand, indexes of endurance performance did not differ (P > 0.05) between athlete carriers or noncarriers of the C34T mutation (e.g., maximal oxygen uptake 72.3 +/- 4.6 vs. 73.5 +/- 5.9 ml.kg(-1).min(-1), respectively). In conclusion, although the frequency distribution of the mutant T allele of the AMPD1 genotype is lower in Caucasian elite endurance athletes than in controls, the C34T mutation does not significantly impair endurance performance once the elite-level status has been reached in sports.     

Strand symmetry of mutation rates in theβ-globin region

Summary It has been suggested that there may be inequalities in the types of substitution on the two DNA strands (in particular, in the frequencies of transversions from R to Y and from Y to R) due to a higher error rate on the lagging than the leading strand during replication. Reexamination of 11 kb of the -globin region sequenced in six primates fails to confirm this suggestion. Examination of the 73-kb -globin region sequenced in humans shows that the frequency of pyrimidines in different parts of this region is more variable than expected in a random sequence, but the pattern is more consistent with nonrandomness generated by DNA turnover mechanisms than with strand asymmetry due to a higher error rate on the lagging strand.     

Recombination or mutation rate heterogeneity? Implications for Mitochondrial Eve

The study of mitochondrial DNA (mtDNA) has helped to demonstrate the African origin of our species and the relationship between living humans and the Neanderthals. mtDNA data have also been used to establish the time and route of major events in human history, such as the expansion of Neolithic farmers into Europe, and the settlement of the Pacific and the New World. However, it is becoming apparent that mtDNA evolution is more complex than previously believed. Anomalous mutation patterns perturb phylogenetic assumptions based on mtDNA data. Although they are frequently dismissed as sequencing errors or mutation hotspots, some of the anomalies have no satisfactory explanation. The mechanisms behind apparent mutation rate heterogeneity, or even possible mtDNA recombination, remain unknown. These issues need to be addressed, as they have profound consequences for the interpretation of mtDNA data.     

Dy and Nd induced genetic mutation of bacillus α-amylase

After treatment with DyCl₃ and NdCl₃, two strains of mutated bacilli showing increased α-amylase activity were isolated. The α-amylase genes were amplified, cloned, and sequenced. Sequencing revealed that there were either 11 or 14 bases altered in the two genes. These alterations took the form of base substitutions, and transversion was more common than transition. Based on these results, it was concluded that the rare earth compounds DyCl₃ and NdCl₃ were mutagens.     

On Bartlett's formulation of the Luria-Delbrück mutation model

Current knowledge of microbial mutation rates was accumulated largely by means of fluctuation experiments. A mathematical model describing the cell dynamics in a fluctuation experiment is indispensable to the estimation of mutation rates through fluctuation experiments. In almost six decades the model formulated by Lea and Coulson dominated in research and application, although the model formulated by Bartlett is generally believed to describe the cell dynamics more faithfully. The neglect of the Bartlett formulation was mainly due to mathematical difficulties. The present investigation overcomes some of these difficulties, thereby paving the way for the application of the Bartlett formulation in estimating mutation rates. Specifically, the article offers an algorithm for computing the distribution function of the number of mutants under the Bartlett formulation. The article also provides algorithms for computing point and interval estimates of mutation rates that are based on the maximum-likelihood principle. In addition, the article examines and compares the asymptotic behavior of the distributions of the number of mutants under the two formulations.     

The mutation spectrum of the bestrophin protein – functional implications

Best’s macular dystrophy (BMD), also known as vitelliform macular degeneration type 2 (VMD2; OMIM 153700), is an autosomal dominant form of macular degeneration with mainly juvenile onset. BMD is characterized by the accumulation of lipofuscin within and beneath the retinal pigment epithelium. The gene causing the disease has been localized to 11q13 by recombination breakpoint mapping. Recently, we have identified the causative gene encoding a protein named bestrophin, and mutations have been found mainly to affect residues that are conserved from a family of genes in Caenorhabditis elegans. The function of bestrophin is so far unknown, and no reliable predictions can be made from sequence comparisons. We have investigated the bestrophin gene in 14 unrelated Swedish, Dutch, Danish, and Moroccan families affected with BMD and found eight new mutations. Including the previously published mutations, 15 different missense mutations have now been detected in 19 of the 22 families with BMD investigated by our laboratory. Interestingly, the mutations cluster in certain regions, and no nonsense mutations or mutations causing frame-shifts have been identified. Computer simulations of the structural elements in the bestrophin protein show that this protein is probably membrane bound, with four putative transmembrane regions. Received: 16 November 1998 / Accepted: 17 March 1999