The INDEPTH (Impact of Nuclear Domains on Gene Expression and Plant Traits) Academy: a community resource for plant science

Tatout, Christophe; Mougeot, G; Parry, Geraint; Baroux, Célia; Pradillo, Mónica; Evans, David

doi:10.1093/jxb/erac005

Cited by 4 publications

(3 citation statements)

References 28 publications

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“…In plant biology, increasing efforts are devoted to develop DL-based tools for species identification [ 21 ], phenotypic analysis of aerial parts [ 27 ], roots [ 28 ], cells [ 29 ] and analysis of organellar morphology [ 30 ]. As the field of plant epigenetics and 3D genomics develops, interest in automated detection of nuclei and of prominent subnuclear structures such as chromocenters in microscopy images is rapidly growing [ 7 , 31 ]. In interphase nuclei of most Arabidopsis organs, chromocenters are formed by the coalescence between centromeres and other “heterochromatic” repeat-rich chromosomal domains such as transposable elements (TEs) and pericentromeric and sub-telomeric nucleolar organizing regions (NORs) into highly condensed 8-to-10 conspicuous foci [ 10 , 32 ].…”

Section: Introductionmentioning

confidence: 99%

Advanced Image Analysis Methods for Automated Segmentation of Subnuclear Chromatin Domains

et al. 2022

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The combination of ever-increasing microscopy resolution with cytogenetical tools allows for detailed analyses of nuclear functional partitioning. However, the need for reliable qualitative and quantitative methodologies to detect and interpret chromatin sub-nuclear organization dynamics is crucial to decipher the underlying molecular processes. Having access to properly automated tools for accurate and fast recognition of complex nuclear structures remains an important issue. Cognitive biases associated with human-based curation or decisions for object segmentation tend to introduce variability and noise into image analysis. Here, we report the development of two complementary segmentation methods, one semi-automated (iCRAQ) and one based on deep learning (Nucl.Eye.D), and their evaluation using a collection of A. thaliana nuclei with contrasted or poorly defined chromatin compartmentalization. Both methods allow for fast, robust and sensitive detection as well as for quantification of subtle nucleus features. Based on these developments, we highlight advantages of semi-automated and deep learning-based analyses applied to plant cytogenetics.

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Section: Introductionmentioning

confidence: 99%

Advanced Image Analysis Methods for Automated Segmentation of Subnuclear Chromatin Domains

et al. 2022

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“…Efforts are undertaken to promote education and support in image analysis for scientists dealing with biological images [ 13 ]. This resource paper contributes to these efforts by providing a compendium of image analysis workflows for nucleus, chromatin and chromosome studies, taking seven case-studies as examples developed by participants of the training school of the INDEPTH COST action [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

“…Each workflow is associated with a Supplemental File folder that includes a step-by-step guideline (text); a table summarizing the main step functions and parameters used on the training image; one or two training images per workflow; and, for workflow 1, a video tutorial. Training image datasets are available on the INDEPTH-OMERO repository [ 13 , 14 ]. 1…”

Section: Introductionmentioning

confidence: 99%

Image analysis workflows to reveal the spatial organization of cell nuclei and chromosomes

Randall

Jourdain

Nowicka

et al. 2022

Nucleus

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Nucleus, chromatin, and chromosome organization studies heavily rely on fluorescence microscopy imaging to elucidate the distribution and abundance of structural and regulatory components. Three-dimensional (3D) image stacks are a source of quantitative data on signal intensity level and distribution and on the type and shape of distribution patterns in space. Their analysis can lead to novel insights that are otherwise missed in qualitative-only analyses. Quantitative image analysis requires specific software and workflows for image rendering, processing, segmentation, setting measurement points and reference frames and exporting target data before further numerical processing and plotting. These tasks often call for the development of customized computational scripts and require an expertise that is not broadly available to the community of experimental biologists. Yet, the increasing accessibility of high- and super-resolution imaging methods fuels the demand for user-friendly image analysis workflows. Here, we provide a compendium of strategies developed by participants of a training school from the COST action INDEPTH to analyze the spatial distribution of nuclear and chromosomal signals from 3D image stacks, acquired by diffraction-limited confocal microscopy and super-resolution microscopy methods (SIM and STED). While the examples make use of one specific commercial software package, the workflows can easily be adapted to concurrent commercial and open-source software. The aim is to encourage biologists lacking custom-script-based expertise to venture into quantitative image analysis and to better exploit the discovery potential of their images. Abbreviations: 3D FISH: three-dimensional fluorescence in situ hybridization; 3D: three-dimensional; ASY1: ASYNAPTIC 1; CC: chromocenters; CO: Crossover; DAPI: 4',6-diamidino-2-phenylindole; DMC1: DNA MEIOTIC RECOMBINASE 1; DSB: Double-Strand Break; FISH: fluorescence in situ hybridization; GFP: GREEN FLUORESCENT PROTEIN; HEI10: HUMAN ENHANCER OF INVASION 10; NCO: Non-Crossover; NE: Nuclear Envelope; Oligo-FISH: oligonucleotide fluorescence in situ hybridization; RNPII: RNA Polymerase II; SC: Synaptonemal Complex; SIM: structured illumination microscopy; ZMM (ZIP: MSH4: MSH5 and MER3 proteins); ZYP1: ZIPPER-LIKE PROTEIN 1.

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Connecting high-resolution 3D chromatin maps with cell division and cell differentiation at the root apical meristem

Caballero,

Pasternak,

Riyazuddin

et al. 2024

Plant Cell Rep

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Key message We used marker-free technologies to study chromatin at cellular resolution. Our results show asymmetric chromatin distribution, explore chromatin dynamics during mitosis, and reveal structural differences between trichoblast and atrichoblast cell. Abstract The shapes, sizes, and structural organizations of plant nuclei vary considerably among cell types, tissues, and species. This diversity is dependent on various factors, including cellular function, developmental stage, and environmental or physiological conditions. The differences in nuclear structure reflect the state of chromatin, which, in turn, controls gene expression and regulates cell fate. To examine the interrelationship between nuclear structure, cell morphology, and tissue-specific cell proliferation and differentiation processes, we conducted multiple visualizations of H3K4me1, H3K9me2, 4′,6-diamidino-2-phenylindole, 5-ethynyl 2′-deoxyuridine, and SCRI Renaissance 2200, followed by subsequent quantitative analysis of individual cells and nuclei. By assigning cylindrical coordinates to the nuclei in the iRoCS toolbox, we were able to construct in situ digital three-dimensional chromatin maps for all the tissue layers of individual roots. A detailed analysis of the nuclei features of H3K4me1 and H3K9me2 in the mitotic and the elongation zones in trichoblast and atrichoblast cells at the root apical meristem revealed cell type-specific chromatin dynamics with asymmetric distribution of euchromatin and heterochromatin marks that may be associated with cell cycle and cell differentiation characteristics of specific cells. Furthermore, the spatial distribution of nuclei stained with 5-ethynyl 2′-deoxyuridine in the epidermis and cortex tissues suggests short-range coordination of cell division and nuclear migration in a linear sequence through an unknown regulatory mechanism.

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The INDEPTH (Impact of Nuclear Domains on Gene Expression and Plant Traits) Academy: a community resource for plant science

Cited by 4 publications

References 28 publications

Advanced Image Analysis Methods for Automated Segmentation of Subnuclear Chromatin Domains

Advanced Image Analysis Methods for Automated Segmentation of Subnuclear Chromatin Domains

Image analysis workflows to reveal the spatial organization of cell nuclei and chromosomes

Connecting high-resolution 3D chromatin maps with cell division and cell differentiation at the root apical meristem

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