Journal
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
Volume 20, Issue 2, Pages 1073-1080Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TCBB.2022.3190427
Keywords
Arabidopsis thaliana; digitalization and image capture; image processing and computer vision; image processing software
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This paper reports the development of an informatics tool based on computer vision for processing and analysis of digital images to analyze the expression of the GUS signal in A. thaliana roots. The tool provides quantitative results of image intensity levels, allowing researchers to understand how plants modify their hormonal pathways depending on environmental conditions.
The uidA gene codifies for a glucuronidase (GUS) enzyme which has been used as a biotechnological tool during the last years. When uidA gene is fused to a gene's promotor region, it is possible to evaluate the activity of this one in response to a stimulus. Arabidopsis thaliana has served as the biological platform to elucidate molecular and regulatory signaling responses in plants. Transgenic lines of A. thaliana, tagged with the uidA gene, have allowed explaining how plants modify their hormonal pathways depending on the environmental conditions. Although the information extracted from microscopic images of these transgenic plants is often qualitative and in many publications is not subjected to quantification, in this paper we report the development of an informatics tool focused on computer vision for processing and analysis of digital images in order to analyze the expression of the GUS signal in A. thaliana roots, which is strongly correlated with the intensity of the grayscale images. This means that the presence of the GUS-induced color indicates where the gene has been actively expressed, such as our statistical analysis has demonstrated after treatment of A. thaliana DR5::GUS with naphtalen-acetic acid (0.0001 mM and 1 mM). GUSignal is a free informatics tool that aims to be fast and systematic during the image analysis since it executes specific and ordered instructions, to offer a segmented analysis by areas or regions of interest, providing quantitative results of the image intensity levels.
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