Genetic diversity of microsatellite loci in hierarchically structured populations

Shorebirds' Longer Migratory Distances Are Associated With Larger ADCYAP1 Microsatellites and Greater Morphological Complexity of Hippocampal Astrocytes

For the epic journey of autumn migration, long-distance migratory birds use innate and learned information and follow strict schedules imposed by genetic and epigenetic mechanisms, the details of which remain largely unknown. In addition, bird migration requires integrated action of different multisensory systems for learning and memory, and the hippocampus appears to be the integration center for this task. In previous studies we found that contrasting long-distance migratory flights differentially affected the morphological complexity of two types of hippocampus astrocytes. Recently, a significant association was found between the latitude of the reproductive site and the size of the ADCYAP1 allele in long distance migratory birds. We tested for correlations between astrocyte morphological complexity, migratory distances, and size of the ADCYAP1 allele in three long-distance migrant species of shorebird and one non-migrant. Significant differences among species were found in the number and morphological complexity of the astrocytes, as well as in the size of the microsatellites of the ADCYAP1 gene. We found significant associations between the size of the ADCYAP1 microsatellites, the migratory distances, and the degree of morphological complexity of the astrocytes. We suggest that associations between astrocyte number and morphological complexity, ADCYAP1 microsatellite size, and migratory behavior may be part of the adaptive response to the migratory process of shorebirds.

Challenges in analysis and interpretation of microsatellite data for population genetic studies

Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (F ST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.