Genome-scale analysis of demographic history and adaptive selection

One of the main topics in population genetics is identification of adaptive selection among populations. For this purpose, population history should be correctly inferred to evaluate the effect of random drift and exclude it in selection identification. With the rapid progress in genomics in the past decade, vast genome-scale variations are available for population genetic analysis, which however requires more sophisticated models to infer species' demographic history and robust methods to detect local adaptation. Here we aim to review what have been achieved in the fields of demographic modeling and selection detection. We summarize their rationales, implementations, and some classical applications. We also propose that some widely-used methods can be improved in both theoretical and practical aspects in near future.

Influence of day length, ambient temperature, and seasonality on daily travel distance in the Yunnan snub-nosed monkey at Jinsichang, Yunnan, China.

This article examines the effect of ambient temperature, day length, weather conditions, and seasonality on daily path length (DPL) of a free-ranging group of Yunnan snub-nosed monkeys (Rhinopithecus bieti) using an auto-released GPS collar. Data were collected from December 17, 2003 to October 22, 2004 at Laojunshan in northwestern Yunnan province, China. The average DPL of the monkey group was 909+/-472 m (n=291), with the shortest distance being 180 m and the longest distance 3,626 m. Ambient temperature and day length were found to affect DPL. Both factors were positively correlated with DPL, which means that the monkey group traveled greater distances on longer and warmer days. At the study site, three distinct seasons were identified, and DPL did not vary significantly across these periods. The time of sunrise was not correlated with DPL. Nevertheless, we sometimes observed the group starting its daily trip later on cloudy days than on sunny days. Furthermore, weather conditions (e.g. rainy, cloudy, and sunny) did not influence the average DPL of the study group. Overall we found that the primary factors affecting DPL in R. bieti were day length and ambient temperature, especially daily highest temperature.