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On the mapping of quantitative trait loci at marker and non-marker locations

Published online by Cambridge University Press:  02 April 2002

GRANT A. WALLING
Affiliation:
Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS, UK
CHRIS S. HALEY
Affiliation:
Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS, UK
MIGUEL PEREZ-ENCISO
Affiliation:
IRTA, Ctr UdL, Rovira Roure 177, Lleida 25198, Spain Current Address: Institut National de la Recherche Agronomique, Station d'amélioration Génétique des Animaux, BP 27, 31326, Castanet-Toloson Cedex, France.
ROBIN THOMPSON
Affiliation:
Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS, UK IACR-Rothamsted, Harpenden, Hertfordshire AL5 2JQ, UK
PETER M. VISSCHER
Affiliation:
Institute of Cell, Animal and Population Biology, University of Edinburgh West Mains Road, Edinburgh EH9 3JG, UK

Abstract

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Previous studies have noted that the estimated positions of a large proportion of mapped quantitative trait loci (QTLs) coincide with marker locations and have suggested that this indicates a bias in the mapping methodology. In this study we predict the expected proportion of QTLs with positions estimated to be at the location of a marker and further examine the problem using simulated data. The results show that the higher proportion of putative QTLs estimated to be at marker positions compared with non-marker positions is an expected consequence of the estimation methods. The study initially focused on a single interval with no QTLs and was extended to include multiple intervals and QTLs of large effect. Further, the study demonstrated that the larger proportion of estimated QTL positions at the location of markers was not unique to linear regression mapping. Maximum likelihood produced similar results, although the accumulation of positional estimates at outermost markers was reduced when regions outside the linkage group were also considered. The bias towards marker positions is greatest under the null hypothesis of no QTLs or when QTL effects are small. This study discusses the impact the findings could have on the calculation of thresholds and confidence intervals produced by bootstrap methods.

Type
Research Article
Copyright
© 2002 Cambridge University Press