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3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture.

Publication ,  Journal Article
Topp, CN; Iyer-Pascuzzi, AS; Anderson, JT; Lee, C-R; Zurek, PR; Symonova, O; Zheng, Y; Bucksch, A; Mileyko, Y; Galkovskyi, T; Moore, BT ...
Published in: Proceedings of the National Academy of Sciences of the United States of America
April 2013

Identification of genes that control root system architecture in crop plants requires innovations that enable high-throughput and accurate measurements of root system architecture through time. We demonstrate the ability of a semiautomated 3D in vivo imaging and digital phenotyping pipeline to interrogate the quantitative genetic basis of root system growth in a rice biparental mapping population, Bala × Azucena. We phenotyped >1,400 3D root models and >57,000 2D images for a suite of 25 traits that quantified the distribution, shape, extent of exploration, and the intrinsic size of root networks at days 12, 14, and 16 of growth in a gellan gum medium. From these data we identified 89 quantitative trait loci, some of which correspond to those found previously in soil-grown plants, and provide evidence for genetic tradeoffs in root growth allocations, such as between the extent and thoroughness of exploration. We also developed a multivariate method for generating and mapping central root architecture phenotypes and used it to identify five major quantitative trait loci (r(2) = 24-37%), two of which were not identified by our univariate analysis. Our imaging and analytical platform provides a means to identify genes with high potential for improving root traits and agronomic qualities of crops.

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Published In

Proceedings of the National Academy of Sciences of the United States of America

DOI

EISSN

1091-6490

ISSN

0027-8424

Publication Date

April 2013

Volume

110

Issue

18

Start / End Page

E1695 / E1704

Related Subject Headings

  • Reproducibility of Results
  • Recombination, Genetic
  • Quantitative Trait, Heritable
  • Quantitative Trait Loci
  • Principal Component Analysis
  • Plant Roots
  • Phenotype
  • Oryza
  • Multivariate Analysis
  • Models, Biological
 

Citation

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Topp, C. N., Iyer-Pascuzzi, A. S., Anderson, J. T., Lee, C.-R., Zurek, P. R., Symonova, O., … Benfey, P. N. (2013). 3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture. Proceedings of the National Academy of Sciences of the United States of America, 110(18), E1695–E1704. https://doi.org/10.1073/pnas.1304354110
Topp, Christopher N., Anjali S. Iyer-Pascuzzi, Jill T. Anderson, Cheng-Ruei Lee, Paul R. Zurek, Olga Symonova, Ying Zheng, et al. “3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture.Proceedings of the National Academy of Sciences of the United States of America 110, no. 18 (April 2013): E1695–1704. https://doi.org/10.1073/pnas.1304354110.
Topp CN, Iyer-Pascuzzi AS, Anderson JT, Lee C-R, Zurek PR, Symonova O, et al. 3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture. Proceedings of the National Academy of Sciences of the United States of America. 2013 Apr;110(18):E1695–704.
Topp, Christopher N., et al. “3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture.Proceedings of the National Academy of Sciences of the United States of America, vol. 110, no. 18, Apr. 2013, pp. E1695–704. Epmc, doi:10.1073/pnas.1304354110.
Topp CN, Iyer-Pascuzzi AS, Anderson JT, Lee C-R, Zurek PR, Symonova O, Zheng Y, Bucksch A, Mileyko Y, Galkovskyi T, Moore BT, Harer J, Edelsbrunner H, Mitchell-Olds T, Weitz JS, Benfey PN. 3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture. Proceedings of the National Academy of Sciences of the United States of America. 2013 Apr;110(18):E1695–E1704.
Journal cover image

Published In

Proceedings of the National Academy of Sciences of the United States of America

DOI

EISSN

1091-6490

ISSN

0027-8424

Publication Date

April 2013

Volume

110

Issue

18

Start / End Page

E1695 / E1704

Related Subject Headings

  • Reproducibility of Results
  • Recombination, Genetic
  • Quantitative Trait, Heritable
  • Quantitative Trait Loci
  • Principal Component Analysis
  • Plant Roots
  • Phenotype
  • Oryza
  • Multivariate Analysis
  • Models, Biological