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Adjusting for Spatial Effects in Genomic Prediction

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Abstract

This paper investigates the problem of adjusting for spatial effects in genomic prediction. Despite being seldomly considered in genomic prediction, spatial effects often affect phenotypic measurements of plants. We consider a Gaussian random field model with an additive covariance structure that incorporates genotype effects, spatial effects and subpopulation effects. An empirical study shows the existence of spatial effects and heterogeneity across different subpopulation families, while simulations illustrate the improvement in selecting genotypically superior plants by adjusting for spatial effects in genomic prediction.

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Acknowledgements

The authors thank the Joint Editor and the two reviewers whose constructive comments and suggestions led to a considerably improved version of the manuscript. The authors acknowledge the Iowa State University Plant Sciences Institute Scholars Program for financial support and the lab of Patrick S. Schnable and former graduate research assistant Sarah Hill–Skinner for collecting and sharing the maize data. This article is a product of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa. Project No. IOW03617 is supported by USDA/NIFA and State of Iowa funds. Xiaojun Mao’s research is partially supported by Shanghai Sailing Program 19YF1402800. Any opinions, findings, conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the U.S. Department of Agriculture or the Science and Technology Commission of Shanghai Municipality.

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Authors and Affiliations

  1. School of Data Science, Fudan University, Shanghai, 200433, China

    Xiaojun Mao

  2. Department of Statistics, Iowa State University, Ames, IA, 50011, USA

    Somak Dutta & Dan Nettleton

  3. Department of Statistics, Texas A&M University, College Station, TX, 77843, USA

    Raymond K. W. Wong

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  1. Xiaojun Mao
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Correspondence to Somak Dutta.

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Mao, X., Dutta, S., Wong, R.K.W. et al. Adjusting for Spatial Effects in Genomic Prediction. JABES 25, 699–718 (2020). https://doi.org/10.1007/s13253-020-00396-1

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