Quantification of human mitochondrial DNA in a real time PCR.

Recently, a moderately priced machine for real-time quantitative PCR has become available, the Perkin Elmer 5700. The rapid and quantitative assay of mitochondrial DNA (mtDNA) copy number is potentially useful in a variety of molecular, evolutionary and forensic fields. Using this new tool, we have evaluated the precision and reliability of the real time PCR to quantify undeleted mitochondrial genome copy number, and to determine the frequency of an age-associated deletion of 4977 base pairs in length, in 42 human iliopsoas muscle DNA samples from persons of known age. We have evaluated the accuracy with which age can be predicted, knowing only the frequency of this common 4977 bp deletion, and derived a statistical formula which describes the confidence with which the 4977 bp frequency predicts age. The results indicate that the mutation frequency could be used to distinguish between tissue from young and old individuals. However in this data set, while there was considerable agreement of 4977 bp frequency among replicates from the same individual sample, there was substantial diversity of mean mutation frequency between individuals of the same or similar ages. The simplest interpretation of these results is that there are biological modifiers of 4977 bp frequency that are age-independent, which are potentially interesting but may limit the usefulness of this deletion frequency alone as a "molecular forensic clock."

Confidence intervals for a variance ratio, or for heritability, in an unbalanced mixed linear model.

A procedure is presented for constructing an exact confidence interval for the ratio of the two variance components in a possibly unbalanced mixed linear model that contains a single set of m random effects. This procedure can be used in animal and plant breeding problems to obtain an exact confidence interval for a heritability. The confidence interval can be defined in terms of the output of a least squares analysis. It can be computed by a graphical or iterative technique requiring the diagonalization of an m X m matrix or, alternatively, the inversion of a number of m X m matrices. Confidence intervals that are approximate can be obtained with much less computational burden, using either of two approaches. The various confidence interval procedures can be extended to some problems in which the mixed linear model contains more than one set of random effects. Corresponding to each interval procedure is a significance test and one or more estimators.