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Molecular Markers Allow to Remove Introgressed Genetic Background: A Simulation Study

Overview of attention for article published in PLOS ONE, November 2012
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Title
Molecular Markers Allow to Remove Introgressed Genetic Background: A Simulation Study
Published in
PLOS ONE, November 2012
DOI 10.1371/journal.pone.0049409
Pubmed ID
Authors

Carmen Amador, Miguel Ángel Toro, Jesús Fernández

Abstract

The maintenance of genetically differentiated populations can be important for several reasons (whether for wild species or domestic breeds of economic interest). When those populations are introgressed by foreign individuals, methods to eliminate the exogenous alleles can be implemented to recover the native genetic background. This study used computer simulations to explore the usefulness of several molecular based diagnostic approaches to recover of a native population after suffering an introgression event where some exogenous alleles were admixed for a few generations. To remove the exogenous alleles, different types of molecular markers were used in order to decide which of the available individuals contributed descendants to next generation and their number of offspring. Recovery was most efficient using diagnostic markers (i.e., with private alleles) and least efficient when using alleles present in both native and exogenous populations at different frequencies. The increased inbreeding was a side-effect of the management strategy. Both values (% of native alleles and inbreeding) were largely dependent on the amount of exogenous individuals entering the population and the number of generations of admixture that occurred prior to management.

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Geographical breakdown

Country Count As %
Finland 1 3%
Spain 1 3%
Portugal 1 3%
Unknown 27 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 27%
Student > Master 5 17%
Student > Ph. D. Student 4 13%
Other 2 7%
Student > Postgraduate 2 7%
Other 3 10%
Unknown 6 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 63%
Environmental Science 3 10%
Biochemistry, Genetics and Molecular Biology 2 7%
Unknown 6 20%