Biomedical subjects

J P Reeve

Publications and source records attributed to J P Reeve.

4 recordsLinked to original sources

PubMed2003

Joint Bayesian estimation of mutation location and age using linkage disequilibrium.

Associations between disease and marker alleles on chromosomes in populations can arise as a consequence of historical forces such as mutation, selection and genetic drift, and is referred to as "linkage disequilibrium" (LD). LD can be used to estimate the map position of a disease mutation relative to a set of linked markers, as well as to estimate other parameters of interest, such as mutation age. Parametric methods for estimating the location of a disease mutation using marker linkage disequilibrium in a sample of normal and affected individuals require a detailed knowledge of population demography, and in particular require users to specify the postulated age of a mutation and past population growth rates. A new Bayesian method is presented for jointly estimating the position of a disease mutation and its age. The method is illustrated using haplotype data for the cystic fibrosis deltaF508 mutation in Europe and the DTD mutation in Finland. It is shown that, for these datasets, the posterior probability distribution of disease mutation location is insensitive to the population growth rate when the model is averaged over possible mutation ages using a prior probability distribution for the mutation age based on the population frequency of the disease mutation. Fewer assumptions are therefore needed for parametric LD mapping.

Bayes Theorem↗

PubMed2001

High-resolution multipoint linkage-disequilibrium mapping in the context of a human genome sequence.

A new method is presented for fine-scale linkage disequilibrium (LD) mapping of a disease mutation; it uses multiple linked single-nucleotide polymorphisms, restriction-fragment-length polymorphisms, or microsatellite markers and incorporates information from an annotated human genome sequence (HGS) and from a human mutation database. The method takes account of population demographic effects, using Markov chain Monte Carlo methods to integrate over the unknown gene genealogy and gene coalescence times. Information about the relative frequency of disease mutations in exons, introns, and other regions, from mutational databases, as well as assumptions about the completeness of the gene annotation, are used with an annotated HGS, to generate a prior probability that a mutation lies at any particular position in a specified region of the genome. This information is updated with information about mutation location, from LD at a set of linked markers in the region, to generate the posterior probability density of the mutation location. The performance of the method is evaluated by simulation and by analysis of a data set for diastrophic dysplasia (DTD) in Finland. The DTD disease gene has been positionally cloned, so the actual location of the mutation is known and can be compared with the position predicted by our method. For the DTD data, the addition of information from an HGS results in disease-gene localization at a resolution that is much higher than that which would be possible by LD mapping alone. In this case, the gene would be found by sequencing a region < or =7 kb in size.

Algorithms↗

PubMed2000

Predicting long-term response to selection.

Lande's equation for predicting the response of trait means to a shift in optimal trait values is tested using a stochastic simulation model. The simulated population is finite, and each individual has a finite number of loci. Therefore, selection may cause allele frequencies and distributions to change over time. Since the equation assumes constant genetic parameters, the degree to which such allelic changes affect predictions can be examined. Predictions are based only on information available at generation zero of directional selection. The quality of the predictions depends on the nature of allelic distributions in the original population. If allelic effects are approximately normally distributed, as assumed in Lande's Gaussian approximation to the continuum-of-alleles model, the predictions are very accurate, despite small changes in the G matrix. If allelic effects have a leptokurtic distribution, as is likely in Turelli's 'house-of-cards' approximation, the equation underestimates the rate of response and correlated response, and overestimates the time required for the trait means to reach their equilibrium values. Models with biallelic loci have limits as to the amount of trait divergence possible, since only two allelic values are available at each of a finite set of loci. If the new optimal trait values lie within these limits, predictions are good, if not, singularity in the G matrix results in suboptimal equilibria, despite the presence of genetic variance for each individual trait.

Gene Frequency↗

PubMed1999

Change in sexual size dimorphism as a correlated response to selection on fecundity.

Fecundity selection is often suggested as the main causal factor underlying the prevalence of female-biased sexual size dimorphism (SSD), but this assumption has not been empirically tested. We selected female Drosophila melanogaster for increased or decreased fecundity (eggs laid over a single 18-h period, between days 5 and 7 posteclosion) for 20 generations, to see what effect this would have on SSD in three morphological traits (thorax width, abdomen width and thorax length). A direct response to fecundity selection was found in the downward direction (16.6%), whereas the response to upward selection (5.7%) was not statistically significant. Significant sex by selection interaction terms in the ANOVAs for thorax width and abdomen width indicate that the two sexes responded differently. Females usually showed a greater correlated response than males. In lines selected for increased fecundity, the correlated response in females for thorax and abdomen width was greater than the direct response in standard deviation units. SSD generally increased with selection for increased fecundity, but showed no consistent trend with selection for decreased fecundity. These results support the general hypothesis that SSD can evolve rapidly in response to fecundity selection. Selection on fecundity also produced correlated responses in life history traits. Downward selection resulted in flies that had lower viability and longevity, and both directions of selection were associated with an increase in development time.

Animals↗