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Ascertainment of evolutionary processes from the genetic variation associated to each geographic point in a map

Author:
Quevedo Pérez, José RamónUniovi authority; Fernández-Combarro Álvarez, ElíasUniovi authority; Royo, L.J.; Alvarez, I.; Beja-Pereira, A.; Fernandez, I.; Bahamonde Rionda, AntonioUniovi authority; Goyache, F.
Subject:

Gene variation

map projection

Interpolation

Uniqueness

Publication date:
2005-06-05
Editorial:

European Association for Animal Production

Abstract:

Available techniques suited for spatial analysis of genetic variation are scarce, preventing the ascertainment of the source and direction of evolutionary processes. Here we propose a new approach using actual information at population level (size, allelic frequencies) to infer a distribution of the individuals forming said population in an area around a node considered as its center of the distribution. We subsequently define an area around each geographical point on our map to sample the individuals (belonging to any ‘real’ population) contributing to the genetic variation at this given geographical point and compute the genetic variables associated with it. The genetic information associated with each geographical point will be graphically projected onto the map to allow visual inspection of possible patterns of variation. The methodology is demonstrated by its application to published microsatellite data sets for two livestock species and for Eurasian otter (Lutra lutra) in Scotland, using two single parameters (variability and uniqueness) that allow us to take into account both the highly stochastic nature of gene variation and the distribution of rare alleles. The methodology described here has been implemented in the freely downloadable program GeoGen (http://www.aic.uniovi.es/GeoGen/).

Available techniques suited for spatial analysis of genetic variation are scarce, preventing the ascertainment of the source and direction of evolutionary processes. Here we propose a new approach using actual information at population level (size, allelic frequencies) to infer a distribution of the individuals forming said population in an area around a node considered as its center of the distribution. We subsequently define an area around each geographical point on our map to sample the individuals (belonging to any ‘real’ population) contributing to the genetic variation at this given geographical point and compute the genetic variables associated with it. The genetic information associated with each geographical point will be graphically projected onto the map to allow visual inspection of possible patterns of variation. The methodology is demonstrated by its application to published microsatellite data sets for two livestock species and for Eurasian otter (Lutra lutra) in Scotland, using two single parameters (variability and uniqueness) that allow us to take into account both the highly stochastic nature of gene variation and the distribution of rare alleles. The methodology described here has been implemented in the freely downloadable program GeoGen (http://www.aic.uniovi.es/GeoGen/).

Description:

Annual meeting of the European Association for Animal Production (56th. 2005. Uppsala, Sweden)

URI:
https://hdl.handle.net/10651/73074
ISBN:
9076998663
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