Biomedical subjects

Philip M Service

Publications and source records attributed to Philip M Service.

5 recordsLinked to original sources

PubMed2004

How good are quantitative complementation tests?

Several recent studies have used quantitative complementation tests to identify relatively short chromosome regions that contain genes that influence life span and to screen for candidate life-span genes in flies. The methodology and logic of quantitative complementation tests are described. Arguments are presented that suggest that these tests may be misleading because there is a substantial, but unknown, likelihood of false positive results. The arguments are supported by the published results of quantitative complementation tests.

Animals↗

PubMed2004

Demographic heterogeneity explains age-specific patterns of genetic variance in mortality rates.

The genetic variance of mortality rates in Drosophila melanogaster increases with age early in life, but declines at intermediate ages. A simulation study was done in order to evaluate two competing explanations for this age-specific pattern: (1) demographic heterogeneity, and (2) binomial sampling effects. The pattern can be explained by demographic heterogeneity among and within genotypes. In contrast, binomial sampling variance is not sufficient to explain this age-specific pattern of genetic variance in mortality rates. A previous publication that rejected the 'heterogeneity explanation' in favor of binomial sampling is shown to be mistaken.

Aging↗

PubMed2004

Quantitative trait loci affecting life span in replicated populations of Drosophila melanogaster. I. Composite interval mapping.

Composite interval mapping was used to identify life-span QTL in F2 progeny of three crosses between different pairs of inbred lines. Each inbred line was derived from a different outbred population that had undergone long-term selection for either long or short life span. Microsatellite loci were used as genetic markers, and confidence intervals for QTL location were estimated by bootstrapping. A minimum of 10 QTL were detected, nine of which were located on the two major autosomes. Five QTL were present in at least two crosses and five were present in both sexes. Observation of the same QTL in more than one cross was consistent with the hypothesis that genetic variation for life span is maintained by balancing selection. For all QTL except one, allelic effects were in the direction predicted on the basis of outbred source population. Alleles that conferred longer life were always at least partially dominant.

Analysis of Variance↗

PubMed2004

Quantitative trait loci affecting life span in replicated populations of Drosophila melanogaster. II. Response to selection.

Three selection experiments were used to identify chromosome regions that contain QTL affecting late-life and early-life fitness in Drosophila melanogaster. The selection experiments were initiated by crossing pairs of inbred lines that had been derived from outbred laboratory populations that had different mean life spans. QTL regions were located by association with microsatellite markers that showed significant selection responses. Regions between recombination map positions 54 and 81 on chromosome 2, between 0 and 30 on chromosome 3, and near locations 49 and 81 on chromosome 3 had the strongest support as locations of life-span QTL. There was good general agreement between the life-span QTL regions that were identified by selection and those that were identified in a companion recombination mapping experiment that used the same fly stocks. Many marker loci responded in opposite directions to selection for late- and early-life fitness, indicating negative genetic correlations or trade-offs between those traits. Indirect evidence suggested that some negative genetic correlations were due to antagonistic pleiotropy.

Animals↗

PubMed2000

Heterogeneity in Individual Mortality Risk and Its Importance for Evolutionary Studies of Senescence.

Mortality was simulated under the assumption of heterogeneity in individual age-specific mortality risk. Heterogeneity was modeled by assigning each individual its own Gompertz mortality function. Means and variances of the Gompertz intercept and slope parameters were based on published data for Drosophila melanogaster. Simulations of large cohorts reproduced mortality plateaus similar to those observed for actual cohorts of flies. Catastrophic late-age mortality was not observed except when heterogeneity was very low and rates of senescence were very high. A second set of simulations was designed to mimic experiments that have investigated age-specific patterns of genetic variance in mortality rates. Within-genotype heterogeneity in mortality risk resulted in a decline in genetic variance of mortality rates at old ages. That result suggests that the decline in genetic variance at old ages that has been observed in some experiments is an artifact of heterogeneity. Mortality rate plateaus, decrease in genetic variance of mortality rates at old ages, and absence of catastrophic late-age mortality all appear to contradict predictions of the evolutionary theory of senescence. Heterogeneity in mortality risk may explain those contradictions.

Gompertz function↗