Validation of outlier loci through replication in independent data sets: a test on Arabis alpina.

Outlier detection and environmental association analysis are common methods to search for loci or genomic regions exhibiting signals of adaptation to environmental factors. However, a validation of outlier loci and corresponding allele distribution models through functional molecular biology or transplant/common garden experiments is rarely carried out. Here, we employ another method for validation, namely testing outlier loci in specifically designed, independent data sets.

Pleiotropy of segregating genetic variants that affect honey bee worker life expectancy.

In contrast to many other complex traits, the natural genetic architecture of life expectancy has not been intensely studied, particularly in non-model organisms, such as the honey bee (Apis mellifera L.). Multiple factors that determine honey bee worker lifespan have been identified and genetic analyses have been performed on some of those traits.

Using the 454 pyrosequencing-based technique in the development of nuclear microsatellite loci in the alpine plant Arabis alpina (Brassicaceae).

Premise Of The Study: Polymorphic microsatellite markers were developed for the inbred alpine perennial plant Arabis alpine to infer life-history parameters and measure patterns of contemporary gene fl ow within populations.

Methods And Results: Using the 454 pyrosequencing technique, 19 microsatellite primer sets were developed for A. alpina .

Landscape genetics of plants.

Landscape genetics is the amalgamation of landscape ecology and population genetics to help with understanding microevolutionary processes such as gene flow and adaptation. In this review, we examine why landscape genetics of plants lags behind that of animals, both in number of studies and consideration of landscape elements. The classical landscape distance/resistance approach to study gene flow is challenging in plants, whereas boundary detection and the assessment of contemporary gene flow are more feasible.