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RL: Haplotyping a quantitative trait with a high-density map in experimental crosses. PLoS ONE 2007, 2(8):e732. doi:10.1371/journal.pone.0000732 Publish with BioMed Central and every scientist can read your work free of charge "BioMed Central will be the
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BibTeX
@MISC{Hou_rl:haplotyping,
author = {Wei Hou and John Stephen and F. Yap and Song Wu and Tian Liu and James M. Cheverud and Rongling Wu},
title = {RL: Haplotyping a quantitative trait with a high-density map in experimental crosses. PLoS ONE 2007, 2(8):e732. doi:10.1371/journal.pone.0000732 Publish with BioMed Central and every scientist can read your work free of charge "BioMed Central will be the },
year = {}
}
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Abstract
Background. The ultimate goal of genetic mapping of quantitative trait loci (QTL) is the positional cloning of genes involved in any agriculturally or medically important phenotype. However, only a small portion ( # 1%) of the QTL detected have been characterized at the molecular level, despite the report of hundreds of thousands of QTL for different traits and populations. Methods/Results. We develop a statistical model for detecting and characterizing the nucleotide structure and organization of haplotypes that underlie QTL responsible for a quantitative trait in an F 2 pedigree. The discovery of such haplotypes by the new model will facilitate the molecular cloning of a QTL. Our model is founded on population genetic properties of genes that are segregating in a pedigree, constructed with the mixture-based maximum likelihood context and implemented with the EM algorithm. The closed forms have been derived to estimate the linkage and linkage disequilibria among different molecular markers, such as single nucleotide polymorphisms, and quantitative genetic effects of haplotypes constructed by non-alleles of these markers. Results from the analysis of a real example in mouse have validated the usefulness and utilization of the model proposed. Conclusion. The model is flexible to be extended to model a complex network of genetic regulation that includes the interactions between different haplotypes and between haplotypes and environments.
Keyphrases
quantitative trait charge biomed central high-density map biomed central experimental cross complex network quantitative genetic effect molecular cloning ultimate goal genetic regulation closed form different haplotype mixture-based maximum likelihood context linkage disequilibria important phenotype molecular level real example different molecular marker statistical model genetic mapping method result different trait em algorithm quantitative trait locus nucleotide structure population genetic property small portion new model positional cloning
