Submitted to: Journal of Theoretical and Applied Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 28, 1995
Publication Date: N/A
Interpretive Summary: Individual genes with the largest effects on traits of economic importance can be isolated with the aid of linked genetic markers. Most studies have analyzed each marker or pair of linked markers separately for each trait included in the analysis. Thus, the number of contrasts to be tested can be quite large, which causes computational difficulties. The original set of traits was mathematically transformed to a new set of uncorrelated traits. Statistical tests were then applied to these new traits to determine the effects of genetic markers. An example is presented for milk production traits of Israeli dairy cattle. The gene investigated had significant effects on milk and protein production but not on fat. After analysis using mathematical transformation, the gene had a significant effect on only one of the new uncorrelated traits, thus reducing the number of traits that need to be analyzed and making each of the tests independent of the others. Effects on the original traits are then derived by backtransformation. This method will aid scientists currently involved in detection of individual genes.
Effects of individual quantitative trait loci can be isolated with the aid of linked genetic markers. Most studies have analyzed each marker or pair of linked markers separately for each trait included in the analysis. Thus, the number of contrasts tested can be quite large. The overall experiment type I error can be readily derived from the nominal type I error if all contrasts are statistically independent, but different traits are generally correlated. A new set of uncorrelated traits can be derived by application of a canonical transformation. The total number of effective traits will generally be less than the original set. An example is presented for a DNA microsatellite with effects on milk production traits of Israel dairy cattle. This locus had significant effects on milk and protein production but not on fat. The locus had a significant effect on only one of the canonical variables, and this variable explained 82% of the total variance. The effects on the original traits could be derived by a backtransformation of the effects on the canonical variable.