Estimating the effects of population size and type on the accuracy of genetic maps

Based on simulation studies, it was shown that the type and size of experimental populations can exert an influence on the accuracy of genetic maps. A hypothetical genome map (one chromosome with nine equidistant molecular markers) was generated for the following population types: F2 with dominant a...

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Bibliographic Details
Main Authors: Adésio Ferreira, Marcia Flores da Silva, Luciano da Costa e Silva, Cosme Damião Cruz
Format: Article
Language:English
Published: Sociedade Brasileira de Genética 2006-01-01
Series:Genetics and Molecular Biology
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572006000100033
Description
Summary:Based on simulation studies, it was shown that the type and size of experimental populations can exert an influence on the accuracy of genetic maps. A hypothetical genome map (one chromosome with nine equidistant molecular markers) was generated for the following population types: F2 with dominant and co-dominant markers, backcrossing, recombinant inbred lines (RIL) and double-haploid. The population sizes were 50, 100, 150, 200, 500 and 1000 individuals and 100 simulations were made for each population. The inaccuracies of the populations with the lowest number of individuals were shown by inversions in the order of the markers and the establishment of more than one linkage group in up to 38% of the simulations, depending on the population type. Stress and variance values of the distances between adjacent markers were significantly reduced with the increased size of the population. More accurate maps were obtained for the co-dominant F2 and RIL whereas the maps for the dominant F2 population were less accurate. The higher the number of individuals, the more precise was the map. In all populations, a total of 200 individuals were considered as being sufficient for the construction of reasonably accurate genetic maps. Although this paper deals with plant populations this approach is equally applicable to other organisms.
ISSN:1415-4757
1678-4685