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The estimation of genotypic probabilities in an adult population by the analysis of descendants

Published online by Cambridge University Press:  14 April 2009

Antonio Barbadilla ,
Horacio Naveira ,
Alfredo Ruiz  and
Mauro Santos
Antonio Barbadilla*
Affiliation:
Departament de Genèlica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra (Barcelona), Spain
Horacio Naveira
Affiliation:
Departament de Genèlica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra (Barcelona), Spain
Alfredo Ruiz
Affiliation:
Departament de Genèlica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra (Barcelona), Spain
Mauro Santos
Affiliation:
Departament de Genèlica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra (Barcelona), Spain
*
* Corresponding author.
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There are instances, the most typical being inversion polymorphism in Drosophila, where the genotype is not directly accessible in the adult organism, but can be observed in young life-stages. In these cases, if we want to estimate genotypic probabilities in adult populations, we must examine an offspring sample from adults. In this paper we derive the maximum likelihood estimators, and their errors, for genotypic probabilities in an adult population, according to a standard protocol in which collected parents of a random sample are individually crossed with individuals of a laboratory stock with known homozygous genotype, and a fixed number of their offspring is genetically examined in young life-stages. Arnold's probabilistic model for one locus with two alleles is developed for our estimates. An optimum design which generates a minimum variance is proposed, consisting of examining a moderate offspring number (3–4) per parent. Finally, we propose maximum likelihood estimates when several samples with different numbers of parents per sample, and/or examined progeny per parent are obtained.

Type
Research Article
Information
Genetics Research , Volume 59 , Issue 2 , April 1992 , pp. 131 - 137
Copyright
Copyright © Cambridge University Press 1992

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