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Genome-wide association study of grain shape variation among Oryza sativa L. germplasms based on elliptic Fourier analysis

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Abstract

Although grain shape is an important cereal breeding target, it has only been evaluated using simple measurements, e.g., the length:width ratio. We used elliptic Fourier analysis to evaluate grain shape variation and conducted whole genome association mapping of grain shape using a germplasm collection of Asian cultivated rice. The first principal component of elliptic Fourier descriptors, accounting for over 90% of the total variation, was associated with the length:width ratio of brown rice. That component was the most significant among the first ten components: the length:width ratio is the major genetic variation of rice grain shape. Bayesian multilocus association mapping detected five significant markers for this component; three might be linked to previously reported quantitative trait loci. Allelic effects of significant markers were visualized using inverse Fourier transformation, showing that the allele of a Japonica variety “Nipponbare” produced plumper grains in four of five significant markers. For the second to tenth principal components, varietal effects were significant (P < 0.001), although most accounted for less than 1% of the total variation in elliptic Fourier descriptors. Association mapping detected at least one quantitative trait locus in six of these nine components: breeding programs can improve the heritable shape characteristics associated with these components. For association mapping, elliptic Fourier analysis’ accuracy and high throughput are suitable; it is readily applicable to cereal crops because it is not based on rice-specific morphological characteristics but rather on universal shape descriptors that can delineate any closed contour.

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Abbreviations

QTL:

Quantitative trait locus

EFD:

Elliptic Fourier descriptors

PC:

Principal component

PCA:

Principal component analysis

RFLP:

Restricted fragment length polymorphism

ANOVA:

Analysis of variance

MCMC:

Markov chain Monte Carlo

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Acknowledgments

The authors thank Yosuke Yoshioka and Akifumi Imada for assistance in digital photography and image processing. This work was supported by a grant from the Green Technology Project (QT1001) of the Ministry of Agriculture, Forestry and Fisheries of Japan, and also by a grant from the Grant-in-Aid for Young Scientists B (no. 15780007) of the Ministry of Education, Culture, Sports, Science and Technology of Japan.

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Authors and Affiliations

  1. Data Mining and Grid Research Team, National Agricultural Research Center, National Agriculture and Food Research Organization, Tsukuba, Ibaraki, 305-8666, Japan

    Hiroyoshi Iwata

  2. QTL Genomics Research Center, National Institute of Agrobiological Sciences, Tsukuba, Ibaraki, 305-8602, Japan

    Kaworu Ebana & Yusaku Uga

  3. Laboratory of Animal Genome, National Institute of Agrobiological Sciences, Ikenodai, Tsukuba, Ibaraki, 305-0901, Japan

    Takeshi Hayashi

  4. Plant, Soil and Nutrition Research Unit, Robert W. Holly Center for Agriculture and Health, USDA-ARS, Ithaca, NY, 14853, USA

    Jean-Luc Jannink

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  1. Hiroyoshi Iwata
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  2. Kaworu Ebana
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  3. Yusaku Uga
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  4. Takeshi Hayashi
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Correspondence to Hiroyoshi Iwata.

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Iwata, H., Ebana, K., Uga, Y. et al. Genome-wide association study of grain shape variation among Oryza sativa L. germplasms based on elliptic Fourier analysis. Mol Breeding 25, 203–215 (2010). https://doi.org/10.1007/s11032-009-9319-2

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