TY - JOUR
T1 - Mapping genome-genome epistasis
T2 - A high-dimensional model
AU - Cui, Yuehua
AU - Wu, Rongling
N1 - Funding Information:
We thank the two anonymous referees for their constructive comments on this manuscript. This work is supported by an Outstanding Young Investigator Award of the National Natural Science Foundation of China (30128017), a University of Florida Research Opportunity Fund (02050259) and a University of South Florida Biodefense grant (7222061-12) to R.W. We thank Drs Jianguo Wu and Chunhai Shi at Zhejiang University for providing molecular marker and phenotypic data. The publication of this manuscript was approved as Journal Series No. R-10584 by the Florida Agricultural Experiment Station.
PY - 2005/5/15
Y1 - 2005/5/15
N2 - Motivation: The proper development of any organ or tissue requires the coordinated expression of its underlying genes that can be located on different genomes present in an organism. For instance, each step in the development of seed for a higher plant is the consequence of gene interactions from the maternal, embryo and endosperm genomes. Results: We present a multivariate statistical model for mapping quantitative trait loci (QTL) by incorporating two important aspects of seed development in plants - QTL interactions derived from different genomes, the maternal, embryo and endosperm, and genetic correlations among phenotypic traits expressed in different genome-specific tissues. This model, which has a high dimensionality, is constructed within the maximum-likelihood context based on a finite mixture model. The implementation of the expectation-maximization algorithm allows for the efficient estimation of QTL positions, their action and interaction effects and pleiotropic effects. The application of this high-dimensional model to a real rice dataset has validated its usefulness. Conclusions: Our model was derived for self-pollinated plants, but it can be extended to cross-pollinated plants and to animals. With the burgeoning of genetic and genomic data, this high-dimensional model will have many implications for agricultural and evolutionary genetic research.
AB - Motivation: The proper development of any organ or tissue requires the coordinated expression of its underlying genes that can be located on different genomes present in an organism. For instance, each step in the development of seed for a higher plant is the consequence of gene interactions from the maternal, embryo and endosperm genomes. Results: We present a multivariate statistical model for mapping quantitative trait loci (QTL) by incorporating two important aspects of seed development in plants - QTL interactions derived from different genomes, the maternal, embryo and endosperm, and genetic correlations among phenotypic traits expressed in different genome-specific tissues. This model, which has a high dimensionality, is constructed within the maximum-likelihood context based on a finite mixture model. The implementation of the expectation-maximization algorithm allows for the efficient estimation of QTL positions, their action and interaction effects and pleiotropic effects. The application of this high-dimensional model to a real rice dataset has validated its usefulness. Conclusions: Our model was derived for self-pollinated plants, but it can be extended to cross-pollinated plants and to animals. With the burgeoning of genetic and genomic data, this high-dimensional model will have many implications for agricultural and evolutionary genetic research.
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U2 - 10.1093/bioinformatics/bti342
DO - 10.1093/bioinformatics/bti342
M3 - Article
C2 - 15728111
AN - SCOPUS:19544388128
SN - 1367-4803
VL - 21
SP - 2447
EP - 2455
JO - Bioinformatics
JF - Bioinformatics
IS - 10
ER -