GiA Roots: Software for the high throughput analysis of plant root system architecture

T. Galkovskyi, Y. Mileyko, A. Bucksch, B. Moore, O. Symonova, C. Price, C. Topp, A. Iyer Pascuzzi, P. Zurek, S. Fang, J. Harer, P. Benfey, J. Weitz, BMC Plant Biology 12 (2012).

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Journal Article | Published | English

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Author
Galkovskyi, Taras; Mileyko, Yuriy; Bucksch, Alexander; Moore, Brad; Symonova, OlgaIST Austria; Price, Charles; Topp, Chrostopher; Iyer Pascuzzi, Anjali; Zurek, Paul; Fang, Suqin; Harer, John; Benfey, Philip
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Abstract
Background: Characterizing root system architecture (RSA) is essential to understanding the development and function of vascular plants. Identifying RSA-associated genes also represents an underexplored opportunity for crop improvement. Software tools are needed to accelerate the pace at which quantitative traits of RSA are estimated from images of root networks.Results: We have developed GiA Roots (General Image Analysis of Roots), a semi-automated software tool designed specifically for the high-throughput analysis of root system images. GiA Roots includes user-assisted algorithms to distinguish root from background and a fully automated pipeline that extracts dozens of root system phenotypes. Quantitative information on each phenotype, along with intermediate steps for full reproducibility, is returned to the end-user for downstream analysis. GiA Roots has a GUI front end and a command-line interface for interweaving the software into large-scale workflows. GiA Roots can also be extended to estimate novel phenotypes specified by the end-user.Conclusions: We demonstrate the use of GiA Roots on a set of 2393 images of rice roots representing 12 genotypes from the species Oryza sativa. We validate trait measurements against prior analyses of this image set that demonstrated that RSA traits are likely heritable and associated with genotypic differences. Moreover, we demonstrate that GiA Roots is extensible and an end-user can add functionality so that GiA Roots can estimate novel RSA traits. In summary, we show that the software can function as an efficient tool as part of a workflow to move from large numbers of root images to downstream analysis.
Publishing Year
Date Published
2012-07-26
Journal Title
BMC Plant Biology
Volume
12
Article Number
116
IST-REx-ID
492

Cite this

Galkovskyi T, Mileyko Y, Bucksch A, et al. GiA Roots: Software for the high throughput analysis of plant root system architecture. BMC Plant Biology. 2012;12. doi:10.1186/1471-2229-12-116
Galkovskyi, T., Mileyko, Y., Bucksch, A., Moore, B., Symonova, O., Price, C., … Weitz, J. (2012). GiA Roots: Software for the high throughput analysis of plant root system architecture. BMC Plant Biology, 12. https://doi.org/10.1186/1471-2229-12-116
Galkovskyi, Taras, Yuriy Mileyko, Alexander Bucksch, Brad Moore, Olga Symonova, Charles Price, Chrostopher Topp, et al. “GiA Roots: Software for the High Throughput Analysis of Plant Root System Architecture.” BMC Plant Biology 12 (2012). https://doi.org/10.1186/1471-2229-12-116.
T. Galkovskyi et al., “GiA Roots: Software for the high throughput analysis of plant root system architecture,” BMC Plant Biology, vol. 12, 2012.
Galkovskyi T, Mileyko Y, Bucksch A, Moore B, Symonova O, Price C, Topp C, Iyer Pascuzzi A, Zurek P, Fang S, Harer J, Benfey P, Weitz J. 2012. GiA Roots: Software for the high throughput analysis of plant root system architecture. BMC Plant Biology. 12.
Galkovskyi, Taras, et al. “GiA Roots: Software for the High Throughput Analysis of Plant Root System Architecture.” BMC Plant Biology, vol. 12, 116, BioMed Central, 2012, doi:10.1186/1471-2229-12-116.
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2018-12-12
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