A model for estimating joint maternal-offspring effects on seed development in autogamous plants

Li Zhang; Mark C.K. Yang; Xuelu Wang; Brian A. Larkins; Maria Gallo-Meagher; Rongling Wu

doi:10.1152/physiolgenomics.00052.2004

A model for estimating joint maternal-offspring effects on seed development in autogamous plants

Li Zhang, Mark C.K. Yang, Xuelu Wang, Brian A. Larkins, Maria Gallo-Meagher, Rongling Wu

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

We present a statistical model for testing and estimating the effects of maternal-offspring genome interaction on the embryo and endosperm traits during seed development in autogamous plants. Our model is constructed within the context of maximum likelihood implemented with the EM algorithm. Extensive simulations were performed to investigate the statistical properties of our approach. We have successfully identified a quantitative trait locus that exerts a significant maternal-offspring interaction effect on amino acid contents of the endosperm in maize, demonstrating the power of our approach. This approach will be broadly useful in mapping endosperm traits for many agriculturally important crop plants and also make it possible to study the genetic significance of double fertilization in the evolution of higher plants.

Original language	English (US)
Pages (from-to)	262-269
Number of pages	8
Journal	Physiological genomics
Volume	19
DOIs	https://doi.org/10.1152/physiolgenomics.00052.2004
State	Published - Jan 2005

All Science Journal Classification (ASJC) codes

Physiology
Genetics

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10.1152/physiolgenomics.00052.2004

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abstract = "We present a statistical model for testing and estimating the effects of maternal-offspring genome interaction on the embryo and endosperm traits during seed development in autogamous plants. Our model is constructed within the context of maximum likelihood implemented with the EM algorithm. Extensive simulations were performed to investigate the statistical properties of our approach. We have successfully identified a quantitative trait locus that exerts a significant maternal-offspring interaction effect on amino acid contents of the endosperm in maize, demonstrating the power of our approach. This approach will be broadly useful in mapping endosperm traits for many agriculturally important crop plants and also make it possible to study the genetic significance of double fertilization in the evolution of higher plants.",

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AU - Zhang, Li

AU - Yang, Mark C.K.

AU - Wang, Xuelu

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AU - Gallo-Meagher, Maria

AU - Wu, Rongling

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AB - We present a statistical model for testing and estimating the effects of maternal-offspring genome interaction on the embryo and endosperm traits during seed development in autogamous plants. Our model is constructed within the context of maximum likelihood implemented with the EM algorithm. Extensive simulations were performed to investigate the statistical properties of our approach. We have successfully identified a quantitative trait locus that exerts a significant maternal-offspring interaction effect on amino acid contents of the endosperm in maize, demonstrating the power of our approach. This approach will be broadly useful in mapping endosperm traits for many agriculturally important crop plants and also make it possible to study the genetic significance of double fertilization in the evolution of higher plants.

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A model for estimating joint maternal-offspring effects on seed development in autogamous plants

Abstract

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