Population structure inferred by local spatial autocorrelation

An example from an Amerindian tribal population

Datos Bibliográficos

ID8312798
AutoresRobert R Sokal (Stony Brook University, autor de correspondencia), Barbara A Thomson (University of Toronto)
Año2006
Volumen129
Número1
Páginas121-131
Fecha de publicación2006-01-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaAmerican Journal of Physical Anthropology (JOURNAL)
Identificadores de la revistaISSN: 0002-9483 • E-ISSN: 1096-8644
EditorialWiley (PUBLISHER • GB)
DOI10.1002/ajpa.20250
PMID16261547
OpenAlexW2045911289
IdiomaEN
Citas recibidas3
Referencias citadas30

Spatial autocorrelation (SA) methods were recently extended to detect local spatial autocorrelation (LSA) at individual localities. LSA statistics serve as useful indicators of local genetic population structure. We applied this method to 15 allele frequencies from 43 villages of a South American tribe, the Yanomama. Based on a network of links <or=51 km between neighboring villages, we calculated LSA statistics for Moran, Geary, and Getis-Ord coefficients. We also developed two new, rescaled indices of local SA. Local indicators of positive SA highlight villages surrounded by genetically similar near neighbors. Negative LSA statistics indicate sharp genetic differences from near neighbors. Markedly positive LSA was found for all 11 outlier villages. The most negatively LSA villages are in the central, densely connected cluster. The Getis-Ord coefficients of suitably transformed allele frequencies point to clusters of villages with unusually high or low allelic polymorphisms. The most homozygous villages are all in the four geographically isolated village clusters. The most polymorphic villages are all in the large, densely settled Yanomame dialect group. An ad hoc linguistic isolation index between neighboring villages showed that villages in isolated pairs and triplets have linguistically similar neighbors, whereas nine villages with notably negative LSA are all near dialect and kinship boundaries. The location of a village with respect to the graph structure of its neighborhood affects its LSA and genetic polymorphism. The implications of these findings for the population structure of the Yanomama are compatible with those from an earlier study of global SA in these villages

Allele · Allele frequency · Biology · Gene · Geographical distance · Geography · Kinship · Population · Sociology · Spatial analysis · Anthropology · Demography · Genetic and phenotypic traits in livestock · Genetics · Spatial and Panel Data Analysis · Wildlife Ecology and Conservation