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Titolo:
DETECTING CLINAL AND BALANCED SELECTION USING SPATIAL AUTOCORRELATIONANALYSIS UNDER KIN-STRUCTURED MIGRATION
Autore:
FIX AG;
Indirizzi:
UNIV CALIF RIVERSIDE,DEPT ANTHROPOL RIVERSIDE CA 92521
Titolo Testata:
American journal of physical anthropology
fascicolo: 4, volume: 95, anno: 1994,
pagine: 385 - 397
SICI:
0002-9483(1994)95:4<385:DCABSU>2.0.ZU;2-7
Fonte:
ISI
Lingua:
ENG
Soggetto:
AUTO-CORRELATION ANALYSIS; POPULATION-GENETICS; MODEL; DIFFERENTIATION; FREQUENCIES; PATTERNS; DISTANCE; DRIFT;
Keywords:
SPATIAL AUTOCORRELATION ANALYSIS; STOCHASTIC MIGRATION; COMPUTER SIMULATION; NATURAL SELECTION MODELS;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Physical, Chemical & Earth Sciences
Arts & Humanities Citation Index
CompuMath Citation Index
Science Citation Index Expanded
Citazioni:
25
Recensione:
Indirizzi per estratti:
Citazione:
A.G. Fix, "DETECTING CLINAL AND BALANCED SELECTION USING SPATIAL AUTOCORRELATIONANALYSIS UNDER KIN-STRUCTURED MIGRATION", American journal of physical anthropology, 95(4), 1994, pp. 385-397

Abstract

Recently spatial autocorrelation has been employed to infer microevolutionary processes from patterns of genetic variation. In theory, different processes should show characteristic signature correlograms; e.g., clinal selection should produce correlograms decreasing from positive to negative autocorrelation, whereas uniform balanced selection should lead to no spatial autocorrelation. The ability of a statistical method such as spatial autocorrelation analysis to distinguish between these selective regimes or even to detect departures from neutrality is dependent on the strength of the evolutionary force and the population structure. Weak selection or migration will not be apparent againstthe expected background of stochastic noise. Moreover, the populationstructure may generate sufficient stochastic variation such that evenstrong evolutionary forces may fail to be detected. This study uses computer simulation to examine the effects of kin-structured migration and three different selective regimes on the shape of spatial correlograms to assess the ability of this technique to detect different microevolutionary processes. Genetic variation among 8 loci is simulated ina linear set of 25 artificial populations. Kin-structured stepping-stone migration among adjacent populations is modeled; directional, balanced, and clinal selection, as well as neutral loci are considered. These experiments show that strong selection produces correlograms of the predicted shape. However, with an anthropologically reasonable population structure, considerable stochastic variation among correlograms for different alleles may still exist. This suggests the need for caution in inferring genetic process from spatial patterns. (C) 1994 Wiley-Liss, Inc.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 25/11/20 alle ore 19:00:53