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Characterization of genomic imprinting effects and patterns with parametric accelerated failure time model

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Abstract

Genomic imprinting, a genetic phenomenon of non-equivalent allele expression that depends on parental origins, has been ubiquitously observed in nature. It does not only control the traits of growth and development but also may be responsible for survival traits. Based on the accelerated failure time model, we construct a general parametric model for mapping the imprinted QTL (iQTL). Within the framework of interval mapping, maximum likelihood estimation of iQTL parameters is implemented via EM algorithm. The imprinting patterns of the detected iQTL are statistically tested according to a series of null hypotheses. BIC model selection criterion is employed to choose an optimal baseline hazard function with maximum likelihood and parsimonious parameters. Simulations are used to validate the proposed mapping procedure. A published dataset from a mouse model system was used to illustrate the proposed framework. Results show that among the five commonly used survival distributions, Log-logistic distribution is the optimal baseline hazard function for mapping QTL of hyperoxic acute lung injury (HALI) survival; under the log-logistic distribution, four QTLs were identified, in which only one QTL was inherited in Mendelian fashion, whereas others were imprinted in different imprinting patterns.

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Acknowledgments

This work is financially supported by the National Natural Science Foundation of China (30972077).

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Authors and Affiliations

  1. Department of Mathematics, Heilongjiang Bayi Agricultural University, Daqing, 163319, People’s Republic of China

    Xiaojing Zhou

  2. College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Deqing, 163319, People’s Republic of China

    Ming Fang & Runqing Yang

  3. Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, 46556, USA

    Jiahan Li

  4. Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, 45229, USA

    Daniel R. Prows

  5. School of Agriculture and Bilogy, Shanghai Jiaotong University, Shanghai, 200240, People’s Republic of China

    Runqing Yang

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  1. Xiaojing Zhou
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  2. Ming Fang
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  3. Jiahan Li
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  4. Daniel R. Prows
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  5. Runqing Yang
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Corresponding author

Correspondence to Runqing Yang.

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Communicated by S. Hohmann.

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Zhou, X., Fang, M., Li, J. et al. Characterization of genomic imprinting effects and patterns with parametric accelerated failure time model. Mol Genet Genomics 287, 67–75 (2012). https://doi.org/10.1007/s00438-011-0661-9

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  • DOI: https://doi.org/10.1007/s00438-011-0661-9

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