Gaining insight into plant gene transcription using smFISH

Duncan, Susan; Rosa, Stefanie

doi:10.1080/21541264.2017.1372043

Cited by 12 publications

(11 citation statements)

References 25 publications

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“…Nuclei isolated from root squashes are also suitable for low-intensity single molecule RNA FISH (smFISH) (Figure 3(a2)). The development of this method has opened many novel possibilities: it allows one to investigate exonic versus intronic RNA [94] and nuclear-localised long non-coding (lnc) RNA [95,96].…”

Section: Nuclear Isolation Methodsmentioning

confidence: 99%

“…These customized image analysis software packages and plugins pave the way for analysing thoroughly the spatial positioning of nuclear domains, as demonstrated for chromocenters [119,121], but also for the spatial positioning of loci and transcribed regions (e.g. in combination with 3D DNA and RNA FISH [88,94,96,123], or of other nuclear factors of interest. In other words, these approaches offer new ways of analysing the 3D organisation of plant nuclei that deserve a more systemic application in the community to gain insight into the yet poorly described spatial and functional principles.…”

Section: Semi-automated Batch Image Processingmentioning

confidence: 99%

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Probing the 3D architecture of the plant nucleus with microscopy approaches: challenges and solutions

Dumur

Duncan

Graumann

et al. 2019

Nucleus

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The eukaryotic cell nucleus is a central organelle whose architecture determines genome function at multiple levels. Deciphering nuclear organizing principles influencing cellular responses and identity is a timely challenge. Despite many similarities between plant and animal nuclei, plant nuclei present intriguing specificities. Complementary to molecular and biochemical approaches, 3D microscopy is indispensable for resolving nuclear architecture. However, novel solutions are required for capturing cell-specific, sub-nuclear and dynamic processes. We provide a pointer for utilising high-to-super-resolution microscopy and image processing to probe plant nuclear architecture in 3D at the best possible spatial and temporal resolution and at quantitative and cell-specific levels. High-end imaging and image-processing solutions allow the community now to transcend conventional practices and benefit from continuously improving approaches. These promise to deliver a comprehensive, 3D view of plant nuclear architecture and to capture spatial dynamics of the nuclear compartment in relation to cellular states and responses. Abbreviations: 3D and 4D: Three and Four dimensional; AI: Artificial Intelligence; ant: antipodal nuclei (ant); CLSM: Confocal Laser Scanning Microscopy; CTs: Chromosome Territories; DL: Deep Learning; DLIm: Dynamic Live Imaging; ecn: egg nucleus; FACS: Fluorescence-Activated Cell Sorting; FISH: Fluorescent In Situ Hybridization; FP: Fluorescent Proteins (GFP, RFP, CFP, YFP, mCherry); FRAP: Fluorescence Recovery After Photobleaching; GPU: Graphics Processing Unit; KEEs: KNOT Engaged Elements; INTACT: Isolation of Nuclei TAgged in specific Cell Types; LADs: Lamin-Associated Domains; ML: Machine Learning; NA: Numerical Aperture; NADs: Nucleolar Associated Domains; PALM: Photo-Activated Localization Microscopy; Pixel: Picture element; pn: polar nuclei; PSF: Point Spread Function; RHF: Relative Heterochromatin Fraction; SIM: Structured Illumination Microscopy; SLIm: Static Live Imaging; SMC: Spore Mother Cell; SNR: Signal to Noise Ratio; SRM: Super-Resolution Microscopy; STED: STimulated Emission Depletion; STORM: STochastic Optical Reconstruction Microscopy; syn: synergid nuclei; TADs: Topologically Associating Domains; Voxel: Volumetric pixel

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Section: Nuclear Isolation Methodsmentioning

confidence: 99%

Section: Semi-automated Batch Image Processingmentioning

confidence: 99%

Probing the 3D architecture of the plant nucleus with microscopy approaches: challenges and solutions

Dumur

Duncan

Graumann

et al. 2019

Nucleus

Self Cite

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“…To better understand the mechanism of intercellular coupling of clocks in plants it will be important to investigate whether one, some, or all of these mobile signals act to couple the clock. The study of this will benefit greatly from the development of ‘omics’ methods at the single cell level (44,45).…”

Section: Discussionmentioning

confidence: 99%

Coordinated circadian timing through the integration of local inputs in Arabidopsis thaliana

Greenwood

Domijan

Gould

et al. 2019

Preprint

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29Every plant cell has a genetic circuit, the circadian clock, that times key processes 30 to the day-night cycle. These clocks are aligned to the day-night cycle by multiple 31 environmental signals that vary across the plant. How does the plant integrate 32 clock rhythms, both within and between organs, to ensure coordinated timing? 33To address this question, we examined the clock at the sub-tissue level across 34Arabidopsis thaliana seedlings under multiple environmental conditions and 35 genetic backgrounds. Our results show that the clock runs at different speeds 36 (periods) in each organ, which causes the clock to peak at different times across 37 the plant in both constant environmental conditions and light-dark cycles. Closer 38 examination reveals that spatial waves of clock gene expression propagate both 39 within and between organs. Using a combination of modeling and experiment, 40we reveal that these spatial waves are the result of the period differences 41 between organs and local coupling, rather than long distance signaling. With 42 further experiments we show that the endogenous period differences, and thus 43 the spatial waves, are caused by the organ specificity of inputs into the clock. We 44 demonstrate this by modulating periods using light and metabolic signals, as 45 well as with genetic perturbations. Our results reveal that plant clocks are set 46 locally by organ specific inputs, but coordinated globally via spatial waves of 47 clock gene expression. 48 49

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“…Of particular interest is the transcription factor ELONGATED HYPOCOTYL 5 [60], which moves locally and long distance [61], is activated by stem-piped light [62], and can influence the circadian clock [63][64][65]. As many components can move between cells, with, for example, thousands of mobile mRNA elements [66], single cell "omics" methods [67,68] will become increasingly important tools.…”

Section: Discussionmentioning

confidence: 99%

Coordinated circadian timing through the integration of local inputs in Arabidopsis thaliana

et al. 2019

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Individual plant cells have a genetic circuit, the circadian clock, that times key processes to the day-night cycle. These clocks are aligned to the day-night cycle by multiple environmental signals that vary across the plant. How does the plant integrate clock rhythms, both within and between organs, to ensure coordinated timing? To address this question, we examined the clock at the sub-tissue level across Arabidopsis thaliana seedlings under multiple environmental conditions and genetic backgrounds. Our results show that the clock runs at different speeds (periods) in each organ, which causes the clock to peak at different times across the plant in both constant environmental conditions and light-dark (LD) cycles. Closer examination reveals that spatial waves of clock gene expression propagate both within and between organs. Using a combination of modeling and experiment, we reveal that these spatial waves are the result of the period differences between organs and local coupling, rather than long-distance signaling. With further experiments we show that the endogenous period differences, and thus the spatial waves, can be generated by the organ specificity of inputs into the clock. We demonstrate this by modulating periods using light and metabolic signals, as well as with genetic perturbations. Our results reveal that plant clocks can be set locally by organ-specific inputs but coordinated globally via spatial waves of clock gene expression.PLOS Biology | https://doi.org/10.days at near-cellular resolution (Materials and methods). This reporter line was chosen because of its strong expression level and its similar spatial expression to other clock components [5].In order to observe the endogenous component of the rhythms, we first imaged seedlings under LL, having previously grown them under LD cycles (LD-to-LL; Fig 2A and Materials and methods). Under the LD-to-LL condition we observed phase differences of GI::LUC expression between organs ( Fig 2B and 2C). The cotyledon and hypocotyl peaked before the root, but the tip of the root peaked before the middle region of the root (Fig 2C, S1 Fig, and S1 Video). Furthermore, we observed a decrease in coherence between regions over time, with a range between the earliest and latest peaking region of 4.92 ± 3.79 h (mean ± standard deviation) in the first and 18.36 ± 5.67 h in the final oscillation. This is due to the emergence of period differences between all regions ( Fig 2D). The cotyledon maintained a mean period of 23.82 ± 0.60 h, whereas the hypocotyl and root ran at 25.41 ± 0.91 h and 28.04 ± 0.86 h, respectively. However, the root tip ran slightly faster than the middle of the root, with a mean period of 26.90 ± 0.45 h, demonstrating the presence of endogenous period differences across all regions. We verified that our results were not specific to the GI::LUC reporter, as we observed similar differences in periods and phases across the plant using luciferase reporters for promoter activity of the core clock genes PSEUDO-RESPONSE REGULATOR 9 (PRR9) [31], TI...

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Gaining insight into plant gene transcription using smFISH

Cited by 12 publications

References 25 publications

Probing the 3D architecture of the plant nucleus with microscopy approaches: challenges and solutions

Probing the 3D architecture of the plant nucleus with microscopy approaches: challenges and solutions

Coordinated circadian timing through the integration of local inputs in Arabidopsis thaliana

Coordinated circadian timing through the integration of local inputs in Arabidopsis thaliana

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