Biomedical subjects

Alan R Lemmon

Publications and source records attributed to Alan R Lemmon.

3 recordsLinked to original sources

PubMed2006

Reinforcement and the genetics of hybrid incompatibilities.

Recent empirical studies suggest that genes involved in speciation are often sex-linked. We derive a general analytic model of reinforcement to study the effects of sex linkage on reinforcement under three forms of selection against hybrids: one-locus, two-locus, and ecological incompatibilities. We show that the pattern of sex linkage can have a large effect on the amount of reinforcement due to hybrid incompatibility. Sex linkage of genes involved in postzygotic isolation generally increases the strength of reinforcement, but only if genes involved in prezygotic isolation are also sex linked. We use exact simulations to test the accuracy of the approximation and find that qualitative predictions made assuming weak selection can hold when selection is strong. Our simulations also show that incompatibilities that evolve in allopatry by drift or weak selection are likely to be lost by swamping during secondary contact, even when selection against hybrids is strong.

Alleles↗

PubMed2004

The importance of proper model assumption in bayesian phylogenetics.

We studied the importance of proper model assumption in the context of Bayesian phylogenetics by examining >5,000 Bayesian analyses and six nested models of nucleotide substitution. Model misspecification can strongly bias bipartition posterior probability estimates. These biases were most pronounced when rate heterogeneity was ignored. The type of bias seen at a particular bipartition appeared to be strongly influenced by the lengths of the branches surrounding that bipartition. In the Felsenstein zone, posterior probability estimates of bipartitions were biased when the assumed model was underparameterized but were unbiased when the assumed model was overparameterized. For the inverse Felsenstein zone, however, both underparameterization and overparameterization led to biased bipartition posterior probabilities, although the bias caused by overparameterization was less pronounced and disappeared with increased sequence length. Model parameter estimates were also affected by model misspecification. Underparameterization caused a bias in some parameter estimates, such as branch lengths and the gamma shape parameter, whereas overparameterization caused a decrease in the precision of some parameter estimates. We caution researchers to assure that the most appropriate model is assumed by employing both a priori model choice methods and a posteriori model adequacy tests.

Bayes Theorem↗

PubMed2002

The metapopulation genetic algorithm: An efficient solution for the problem of large phylogeny estimation.

Large phylogeny estimation is a combinatorial optimization problem that no future computer will ever be able to solve exactly in practical computing time. The difficulty of the problem is amplified by the need to use complex evolutionary models and large taxon samplings. Hence, many heuristic approaches have been developed, with varying degrees of success. Here, we report on a heuristic approach, the metapopulation genetic algorithm, involving several populations of trees that are forced to cooperate in the search for the optimal tree. Within each population, trees are subjected to evaluation, selection, and mutation events, which are directed by using inter-population consensus information. The method proves to be both very accurate and vastly faster than existing heuristics, such that data sets comprised of hundreds of taxa can be analyzed in practical computing times under complex models of maximum-likelihood evolution. Branch support values produced by the metapopulation genetic algorithm might closely approximate the posterior probabilities of the corresponding branches.

Algorithms↗