title: Genomic prediction of biological shape: elliptic Fourier analysis and kernel partial least squares (PLS) regression applied to grain shape prediction in rice (Oryza sativa L.).
abstract: Shape is an important morphological characteristic both in animals and plants. In the present study, we examined a method for predicting biological contour shapes based on genome-wide marker polymorphisms. The method is expected to contribute to the acceleration of genetic improvement of biological shape via genomic selection. Grain shape variation observed in rice (Oryza sativa L.) germplasms was delineated using elliptic Fourier descriptors (EFDs), and was predicted based on genome-wide single nucleotide polymorphism (SNP) genotypes. We applied four methods including kernel PLS (KPLS) regression for building a prediction model of grain shape, and compared the accuracy of the methods via cross-validation. We analyzed multiple datasets that differed in marker density and sample size. Datasets with larger sample size and higher marker density showed higher accuracy. Among the four methods, KPLS showed the highest accuracy. Although KPLS and ridge regression (RR) had equivalent accuracy in a single dataset, the result suggested the potential of KPLS for the prediction of high-dimensional EFDs. Ordinary PLS, however, was less accurate than RR in all datasets, suggesting that the use of a non-linear kernel was necessary for accurate prediction using the PLS method. Rice grain shape can be predicted accurately based on genome-wide SNP genotypes. The proposed method is expected to be useful for genomic selection in biological shape.
authors.affiliation: Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, University of Tokyo, Bunkyo, Tokyo, Japan.
authors.forename: Hiroyoshi
authors.initials: H
authors.lastname: Iwata
authors.affiliation: Genetic Resources Center, National Institute of Agrobiological Sciences, Tsukuba, Ibaraki, Japan.
authors.forename: Kaworu
authors.initials: K
authors.lastname: Ebana
authors.affiliation: Agronomics Research Center, National Institute of Agrobiological Sciences, Tsukuba, Ibaraki, Japan.
authors.forename: Yusaku
authors.initials: Y
authors.lastname: Uga
authors.affiliation: Agroinformatics Division, National Agricultural Research Center, National Agriculture and Food Research Organization, Tsukuba, Ibaraki, Japan.
authors.forename: Takeshi
authors.initials: T
authors.lastname: Hayashi
mesh_terms: D005583:Fourier Analysis; D005838:Genotype; D016018:Least-Squares Analysis; D012275:Oryza / Q000235:genetics*; D012044:Regression Analysis
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