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September 2010 A general statistical framework for dissecting parent-of-origin effects underlying endosperm traits in flowering plants
Gengxin Li, Yuehua Cui
Ann. Appl. Stat. 4(3): 1214-1233 (September 2010). DOI: 10.1214/09-AOAS323

Abstract

Genomic imprinting has been thought to play an important role in seed development in flowering plants. Seed in a flowering plant normally contains diploid embryo and triploid endosperm. Empirical studies have shown that some economically important endosperm traits are genetically controlled by imprinted genes. However, the exact number and location of the imprinted genes are largely unknown due to the lack of efficient statistical mapping methods. Here we propose a general statistical variance components framework by utilizing the natural information of sex-specific allelic sharing among sibpairs in line crosses, to map imprinted quantitative trait loci (iQTL) underlying endosperm traits. We propose a new variance components partition method considering the unique characteristic of the triploid endosperm genome, and develop a restricted maximum likelihood estimation method in an interval scan for estimating and testing genome-wide iQTL effects. Cytoplasmic maternal effect which is thought to have primary influences on yield and grain quality is also considered when testing for genomic imprinting. Extension to multiple iQTL analysis is proposed. Asymptotic distribution of the likelihood ratio test for testing the variance components under irregular conditions are studied. Both simulation study and real data analysis indicate good performance and powerfulness of the developed approach.

Citation

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Gengxin Li. Yuehua Cui. "A general statistical framework for dissecting parent-of-origin effects underlying endosperm traits in flowering plants." Ann. Appl. Stat. 4 (3) 1214 - 1233, September 2010. https://doi.org/10.1214/09-AOAS323

Information

Published: September 2010
First available in Project Euclid: 18 October 2010

zbMATH: 1202.62158
MathSciNet: MR2751339
Digital Object Identifier: 10.1214/09-AOAS323

Keywords: Experimental cross , genomic imprinting , likelihood ratio test , quantitative trait loci , variance components model

Rights: Copyright © 2010 Institute of Mathematical Statistics

Vol.4 • No. 3 • September 2010
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