Multigeneration maximum-likelihood analysis applied to mutation-accumulation experiments in Caenorhabditis elegans

We develop a maximum-likelihood (ML) approach to estimate genomic mutation rates (U) and average homozygous mutation effects: (s) from mutation-accumu lation (MX) experiments in which phenotypic assays are carried out in sever al generations. We use simulations to compare the procedure's performance w ith the method of moments traditionally used to analyze MA data. Similar pr ecision is obtained if mutation effects are small relative to the environme ntal standard deviation, bur. ML can give estimates of mutation parameters that have lower sampling variances than those obtained by the method of mom ents if mutations with large effects have accumulated. The inclusion of dat a from intermediate generations may improve the precision. We analyze life- history trait data from two Caenorhabditis elegans MA experiments. Under a model with equal mutation effects, thr two experiments provide similar esti mates for U of similar to 0.005 per haploid, averaged over traits. Estimate s of s ar-e more divergent and average at -0.51 and -0.13 in the two studie s. Detailed analysis shows that changes of mean and variance of genetic val ues of MA lines in both C. elegans experiments are dominated by mutations w ith lar-ge effects, but the analysis does not rule out the presence of a la rge class of deleterious mutations with very small effects.