EZ-Root-VIS: A Software Pipeline for the Rapid Analysis and Visual Reconstruction of Root System Architecture
Author(s) -
Zaigham Shahzad,
Fabian Kellermeier,
Emily May Armstrong,
Simon Rogers,
Guillaume Lobet,
Anna Amtmann,
Adrian Hills
Publication year - 2018
Publication title -
plant physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.554
H-Index - 312
eISSN - 1532-2548
pISSN - 0032-0889
DOI - 10.1104/pp.18.00217
Subject(s) - root (linguistics) , pipeline (software) , creatures , computer science , software , plant root , artificial intelligence , variance (accounting) , arabidopsis , arabidopsis thaliana , pattern recognition (psychology) , data mining , biology , gene , paleontology , philosophy , linguistics , accounting , natural (archaeology) , horticulture , mutant , business , programming language , biochemistry
If we want to understand how the environment has shaped the appearance and behavior of living creatures, we need to compare groups of individuals that differ in genetic makeup and environment experience. For complex phenotypic features, such as body posture or facial expression in humans, comparison is not straightforward because some of the contributing factors cannot easily be quantified or averaged across individuals. Therefore, computational methods are used to reconstruct representative prototypes using a range of algorithms for filling in missing information and calculating means. The same problem applies to the root system architecture (RSA) of plants. Several computer programs are available for extracting numerical data from root images, but they usually do not offer customized data analysis or visual reconstruction of RSA. We developed Root-VIS, a free software tool that facilitates the determination of means and variance of many different RSA features across user-selected sets of root images. Furthermore, Root-VIS offers several options to generate visual reconstructions of root systems from the averaged data to enable screening and modeling. We confirmed the suitability of Root-VIS, combined with a new version of EZ-Rhizo, for the rapid characterization of genotype-environment interactions and gene discovery through genome-wide association studies in Arabidopsis ( Arabidopsis thaliana ).
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