QTL linkage analysis of connected populations using ancestral marker and pedigree information.
The common assumption in quantitative trait locus (QTL) linkage mapping studies that parents of multiple connected populations are unrelated is unrealistic for many plant breeding programs. We remove this assumption and propose a Bayesian approach that clusters the alleles of the parents of the current mapping populations from locus-specific identity by descent (IBD) matrices that capture ancestral marker and pedigree information. Moreover, we demonstrate how the parental IBD data can be incorporated into a QTL linkage analysis framework by using two approaches: a Threshold IBD model (TIBD) and a Latent Ancestral Allele Model (LAAM). The TIBD and LAAM models are empirically tested via numerical simulation based on the structure of a commercial maize breeding program. The simulations included a pilot dataset with closely linked QTL on a single linkage group and 100 replicated datasets with five linkage groups harboring four unlinked QTL. The simulation results show that including parental IBD data (similarly for TIBD and LAAM) significantly improves the power and particularly accuracy of QTL mapping, e.g., position, effect size and individuals' genotype probability without significantly increasing computational demand.
Department of Biometris, Wageningen University and Research Centre, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands. marco.bink@wur.nl
Marco C A M
MC
Bink
L Radu
LR
Totir
Cajo J F
CJ
ter Braak
Christopher R
CR
Winkler
Martin P
MP
Boer
Oscar S
OS
Smith
D000483:Alleles; D001499:Bayes Theorem; D001947:Breeding; D002874:Chromosome Mapping / Q000379:methods; D003433:Crosses, Genetic; D017343:Genes, Plant; D005819:Genetic Markers; D005828:Genetics, Population; D005838:Genotype; D006239:Haplotypes; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D040641:Quantitative Trait Loci; D003313:Zea mays / Q000235:genetics
D005819:Genetic Markers