Testing Hierarchical Levels of Population Sub-Structuring: The Azores Islands (Portugal) as a Case Study

Abstract

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.

A weighted difference barrier method in landscape genetics

“…WDB incorporates both within group and between group genetic information, and delineates the barriers as a more complex pattern. Besides the WDB, there are other techniques being explored for boundary delineation that make use of simulated annealing algorithm (Dupanloup et al 2002), Bayesian criteria or specific distance-decay behaviors (Guillot et al 2005;Santos et al 2008;Culley et al 2002;Guiller et al 2006;Hull et al 2008;Manel et al 2003;Sambridge 1998). We argue the method introduced here is an alternative approach, and a beginning in initiating and integrating more spatial modeling and methods into the problem solving process.…”

Biodemographic and Genetic Structure of Zamora Province (Spain): Insights from Surname Analysis

“…It has been well-recognized for a long time that surname distributions can be informative about the genetic relationships in subdivided populations (for an extensive review see Colantonio et al 2003, and more recent works, such as Boattini et al 2007, andSantos et al 2008). Moreover, the isonymic method has also been extensively used to estimate inbreeding in human populations (Crow and Mange 1965).…”

“…However, inbreeding may also be influenced, among other factors, by cultural patterns of mate choice, by demographic variation, and by geographical dispersion of populations. Although surnames are an inexpensive marker to study the structure of human populations, it is important to acknowledge that surnames provide only a rough view of the genetic scenario of populations, since polyphyletism and incorrect transmission of surnames can occur in variable frequencies Relethford 1988;Roman et al 2007;Santos et al 2005;Santos et al 2008;Santos et al 2004). In Europe, the establishment of surnames dates to the Middle Ages; the first family surnames were used in the seventh century, but it was only in the sixteenth century that the use of surnames was established as the norm (Junyent 1996).…”