Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-26T08:43:28.447Z Has data issue: false hasContentIssue false

An application of Bayesian QTL mapping to early development in double haploid lines of rainbow trout including environmental effects

Published online by Cambridge University Press:  02 February 2006

VICTOR MARTINEZ
Affiliation:
Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santa Rosa 11735, La Pintana, Santiago, Chile Institute of Cell, Animal and Population Biology, University of Edinburgh Ashworth Laboratories. King's Buildings, Edinburgh, UK
GARY THORGAARD
Affiliation:
School of Biological Sciences, Washington State University, USA
BARRIE ROBISON
Affiliation:
School of Biological Sciences, Washington State University, USA Present address: Department of Biological Sciences and Center for Reproductive Biology University of Idaho, USA.
MIKKO J. SILLANPÄÄ
Affiliation:
Rolf Nevanlinna Institute, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

A Bayesian model and variable dimensional parameter estimation based on Markov chain Monte Carlo was applied to map quantitative trait loci (QTLs) in a doubled haploid mapping population of rainbow trout. To increase power, the analysis was performed using the multiple-QTL model, which simultaneously accounted for all the environmental and genetic main effects that influence the expression of early development life history traits. By doing so we obtained the posterior estimated effects for the environmental factors as well as the number, positions, and the effects for the QTLs. The analyses revealed QTLs for time at hatching, embryonic length and weight at swim-up stage. The posterior expectation of the number of QTLs in different linkage groups shows that at least four QTLs are needed to explain the observed differences in early development between the clonal lines. The Bayesian method effectively combined all the information available to accurately position these QTLs in the rainbow trout genome.

Type
Research Article
Copyright
© 2005 Cambridge University Press