Long-term live-cell imaging approaches to study lateral root formation in Arabidopsis thaliana

Mining key genes related to root morphogenesis through genome-wide identification and expression analysis of RR gene family in citrus

Morphogenesis of root is a vital factor to determine the root system architecture. Cytokinin response regulators (RRs) are the key transcription factors in cytokinin signaling, which play important roles in regulating the root morphogenesis. In this study, 29 RR proteins, including 21 RRs and 8 pseudo RRs, were identified from the genome of citrus, and termed as CcRR1-21 and CcPRR1-8, respectively. Phylogenetic analysis revealed that the 29 CcRRs could be classified into four types according to their representative domains. Analysis of cis-elements of CcRRs indicated that they were possibly involved in the regulation of growth and abiotic stress resistance in citrus. Within the type A and type B CcRRs, CcRR4, CcRR5, CcRR6 and CcRR16 highly expressed in roots and leaves, and dramatically responded to the treatments of hormones and abiotic stresses. CcRR2, CcRR10, CcRR14 and CcRR19 also highly expressed in roots under different treatments. Characteristic analysis revealed that the above 8 CcRRs significantly and differentially expressed in the three zones of root, suggesting their functional differences in regulating root growth and development. Further investigation of the 3 highly and differentially expressed CcRRs, CcRR5, CcRR10 and CcRR14, in 9 citrus rootstocks showed that the expression of CcRR5, CcRR10 and CcRR14 was significantly correlated to the length of primary root, the number of lateral roots, and both primary root and the number of lateral roots, respectively. Results of this study indicated that CcRRs were involved in regulating the growth and development of the root in citrus with different functions among the members.

ACORBA: Automated workflow to measure Arabidopsis thaliana root tip angle dynamics

The ability of plants to sense and orient their root growth towards gravity is studied in many laboratories. It is known that manual analysis of image data is subjected to human bias. Several semi-automated tools are available for analysing images from flatbed scanners, but there is no solution to automatically measure root bending angle over time for vertical-stage microscopy images. To address these problems, we developed ACORBA, which is an automated software that can measure root bending angle over time from vertical-stage microscope and flatbed scanner images. ACORBA also has a semi-automated mode for camera or stereomicroscope images. It represents a flexible approach based on both traditional image processing and deep machine learning segmentation to measure root angle progression over time. As the software is automated, it limits human interactions and is reproducible. ACORBA will support the plant biologist community by reducing labour and increasing reproducibility of image analysis of root gravitropism.

A Sight on Single-Cell Transcriptomics in Plants Through the Prism of Cell-Based Computational Modeling Approaches: Benefits and Challenges for Data Analysis

Single-cell technology is a relatively new and promising way to obtain high-resolution transcriptomic data mostly used for animals during the last decade. However, several scientific groups developed and applied the protocols for some plant tissues. Together with deeply-developed cell-resolution imaging techniques, this achievement opens up new horizons for studying the complex mechanisms of plant tissue architecture formation. While the opportunities for integrating data from transcriptomic to morphogenetic levels in a unified system still present several difficulties, plant tissues have some additional peculiarities. One of the plants' features is that cell-to-cell communication topology through plasmodesmata forms during tissue growth and morphogenesis and results in mutual regulation of expression between neighboring cells affecting internal processes and cell domain development. Undoubtedly, we must take this fact into account when analyzing single-cell transcriptomic data. Cell-based computational modeling approaches successfully used in plant morphogenesis studies promise to be an efficient way to summarize such novel multiscale data. The inverse problem's solutions for these models computed on the real tissue templates can shed light on the restoration of individual cells' spatial localization in the initial plant organ-one of the most ambiguous and challenging stages in single-cell transcriptomic data analysis. This review summarizes new opportunities for advanced plant morphogenesis models, which become possible thanks to single-cell transcriptome data. Besides, we show the prospects of microscopy and cell-resolution imaging techniques to solve several spatial problems in single-cell transcriptomic data analysis and enhance the hybrid modeling framework opportunities.

Lateral Root Formation in Arabidopsis: A Well-Ordered LRexit

Lateral roots (LRs) are crucial for increasing the surface area of root systems to explore heterogeneous soil environments. Major advances have recently been made in the model plant arabidopsis (Arabidopsis thaliana) to elucidate the cellular basis of LR development and the underlying gene regulatory networks (GRNs) that control the morphogenesis of the new root organ. This has provided a foundation for understanding the sophisticated adaptive mechanisms that regulate how plants pattern their root branching to match the spatial availability of resources such as water and nutrients in their external environment. We review new insights into the molecular, cellular, and environmental regulation of LR development in arabidopsis.