ArticlePloS one2015
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.).
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed.
- GrainShape: A landmark-annotated image dataset ofData in brief · 2025Article
- Genomic prediction of the performance of tropical doubled haploid maize lines under artificial Striga hermonthica (Del.) Benth. infestation.G3 (Bethesda, Md.) · 2024Article
- GenoDrawing: An Autoencoder Framework for Image Prediction from SNP Markers.Plant phenomics (Washington, D.C.) · 2023Article
- Enhancing genetic gain through the application of genomic selection in developing irrigated rice for the favorable ecosystem in Bangladesh.Frontiers in genetics · 2023Article
- Genome-wide association study and genomic prediction for yield and grain quality traits of hybrid rice.Molecular breeding : new strategies in plant improvement · 2022Article
- Model-based plant phenomics on morphological traits using morphometric descriptors.Breeding science · 2022Article
- Genomic Prediction: Progress and Perspectives for Rice Improvement.Methods in molecular biology (Clifton, N.J.) · 2022Review
- Article
- Identifying Chagas disease vectors using elliptic Fourier descriptors of body contour: a case for the cryptic dimidiata complex.Parasites & vectors · 2020Article
- Improving root characterisation for genomic prediction in cassava.Scientific reports · 2020Article
- Multi-dimensional machine learning approaches for fruit shape phenotyping in strawberry.GigaScience · 2020Article
- Integrating Molecular Markers and Environmental Covariates To Interpret Genotype by Environment Interaction in Rice (G3 (Bethesda, Md.) · 2019Article
- Comparison of shape quantification methods for genomic prediction, and genome-wide association study of sorghum seed morphology.PloS one · 2019Article
- Genomic Prediction for 25 Agronomic and Quality Traits in Alfalfa (Frontiers in plant science · 2018Article
- Description of grain weight distribution leading to genomic selection for grain-filling characteristics in rice.PloS one · 2018Article
- Genomic Prediction in Pea: Effect of Marker Density and Training Population Size and Composition on Prediction Accuracy.Frontiers in plant science · 2015Article
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4 authors.
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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.
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