Testing hierarchical levels of population sub-structuring: the Azores islands (Portugal) as a case study.
The Azores archipelago (Portugal) is formed by nine islands whose relative positions define them as three geographical groups: Eastern (S. Miguel and Sta. Maria), Central (Terceira, Faial, Pico, Graciosa and S. Jorge) and Western (Flores and Corvo). Using the father's surname of 187,398 individuals living on the nine Azorean Islands, a population analysis based on inter-island relationship and hierarchical organization was conducted. The relation between islands was investigated using summary statistics, analysis of molecular variance (AMOVA) as well as graphical methods. When the values of heteronymy were contrasted with values of gene diversity based on haplogroup frequencies of the Y chromosome, it was possible to verify that Graciosa and Sta. Maria appeared to have the least diverse populations, and that Flores, despite its smaller population size and geographical isolation, has considerably higher levels of diversity. As for inter-island relationships, the difficulty of directly interpreting summary statistics values was evidenced. The AMOVA revealed that only 0.77% of the variation in surnames can be attributed to among-island variation, a value that, although small, can be considered significant. Application of Malécot's model revealed that geographic distance has an important impact in the genetic structure of the archipelago. Monmonier's maximum-difference algorithm demonstrated that the most isolated island of the archipelago appears to be Graciosa, followed by the islands of the Western group and by Sta. Maria. After integrating values of summary statistics with results from AMOVA and graphical methods, a more accurate genetic profile of the Azores, highly supported by genetic data, has emerged.
Santos
Cristina
C
Center of Research in Natural Resources (CIRN) and Department of Biology, University of the Azores, Ponta Delgada, Azores, Portugal.
Abade
Augusto
A
Lima
Manuela
M
D001394:Azores; D014644:Genetic Variation; D005828:Genetics, Population / Q000706:statistics & numerical data*; D005843:Geography; D006801:Humans; D009275:Names; D010865:Pilot Projects; D011174:Portugal