A genome-wide view of the spectrum of spontaneous mutations in yeast

Abstract

The mutation process ultimately defines the genetic features of all populations and, hence, has a bearing on a wide range of issues involving evolutionary genetics, inheritance, and genetic disorders, including the predisposition to cancer. Nevertheless, formidable technical barriers have constrained our understanding of the rate at which mutations arise and the molecular spectrum of their effects. Here, we report on the use of complete-genome sequencing in the characterization of spontaneously arising mutations in the yeast Saccharomyces cerevisiae. Our results confirm some findings previously obtained by indirect methods but also yield numerous unexpected findings, in particular a very high rate of point mutation and skewed distribution of base-substitution types in the mitochondrion, a very high rate of segmental duplication and deletion in the nuclear genome, and substantial deviations in the mutational profile among various model organisms.

Fig. 1.

Microsatellites (triangles, solid lines). The three rightmost filled triangles denote direct estimates of the mutation rates for classes of microsatellites containing large numbers of repeats (n = 10, 8, and 3, respectively); the bottom filled triangle is a rough estimate of the mutation rate for the smallest class, taken to be the midpoint between the upper statistical bound (base of the arrow) and zero; fitted regression to all four points: (1.75 × 10⁻¹⁰) × L^3.60 (r² = 0.88), where L is the number of repeats. Open triangles denote estimates from two earlier studies with reporter constructs (19, 31); fitted regression: (3.24 × 10⁻¹¹) × L^3.42 (r² = 0.87). Circles, squares, and dotted lines indicate homopolymeric runs. Maximum-likelihood estimates (circles) of the mutation rate of HPR loci as a function of the run length are fitted to the regression line, with each data point representing the average result over all four MA lines, with separate points for A/T and G/C runs. The regression equation is (3.73 × 10⁻⁹) × L^3.78 (r² = 0.94). The filled squares denote direct estimates derived from sequence analysis of PCR products in this study, whereas the open squares denote results from other studies (28, 29, 32); the joint regression for these latter two sets of points is (1.50 × 10⁻¹²) × L^5.47 (r² = 0.88).

Fig. 2.

Inferred ploidy levels for each chromosome within the four surveyed lines. Each chromosome-wide measure is an average over all surveyed nonredundant sequences, scaled by the genome-wide average, so 0.5, 1.0, 1.5, and 2.0 imply monosomy, disomy, trisomy, and tetrasomy, respectively.