Faculty Opinions recommendation of High-resolution whole-mount imaging of three-dimensional tissue organization and gene expression enables the study of Phloem development and structure in Arabidopsis.

AbstractQuantifying RNAs in their spatial context is crucial to understanding gene expression and regulation in complex tissues. In situ transcriptomic methods generate spatially resolved RNA profiles in intact tissues. However, there is a lack of a unified computational framework for integrative analysis of in situ transcriptomic data. Here, we present an unsupervised and annotation-free framework, termed ClusterMap, which incorporates physical proximity and gene identity of RNAs, formulates the task as a point pattern analysis problem, and thus defines biologically meaningful structures and groups. Specifically, ClusterMap precisely clusters RNAs into subcellular structures, cell bodies, and tissue regions in both two- and three-dimensional space, and consistently performs on diverse tissue types, including mouse brain, placenta, gut, and human cardiac organoids. We demonstrate ClusterMap to be broadly applicable to various in situ transcriptomic measurements to uncover gene expression patterns, cell-cell interactions, and tissue organization principles from high-dimensional transcriptomic images.

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High Resolution Whole Mount In Situ Hybridization within Zebrafish Embryos to Study Gene Expression and Function

Journal of Visualized Experiments ◽

10.3791/50644 ◽

2013 ◽

Cited By ~ 3

Author(s):

Babykumari P. Chitramuthu ◽

Hugh P. J. Bennett

Keyword(s):

Gene Expression ◽

High Resolution ◽

Zebrafish Embryos ◽

Study Gene Expression ◽

Whole Mount ◽

And Function

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X-ray 3D imaging of gene expression in whole-mount murine brain by microCT, implication for functional analysis of tRNA endonuclease 54 gene mutated in pontocerebellar hypoplasia

10.1101/2019.12.19.882688 ◽

2019 ◽

Author(s):

Olga Ermakova ◽

Tiziana Orsini ◽

Paolo Fruscoloni ◽

Francesco Chiani ◽

Alessia Gambadoro ◽

...

Keyword(s):

Gene Expression ◽

Expression Pattern ◽

Reporter Gene ◽

Three Dimensional ◽

Gene Expression Pattern ◽

Lacz Gene ◽

Pontocerebellar Hypoplasia ◽

X Ray ◽

Whole Mount ◽

Murine Brain

AbstractAcquisition of detailed structural and molecular information from intact biological samples, while preserving cellular three-dimensional structures, still represents a challenge for biological studies aiming to unravel system functions. Here we describe a novel X-ray-based methodology for analysis of gene expression pattern in intact murine brain ex vivo by microCT. The method relays on detection of bromine molecules in the products of enzymatic reaction generated by the β-galactosidase (lacZ) gene reporter. To demonstrate the feasibility of the method, the analysis of the expression pattern of tRNA endonuclease 54 (Tsen54)-lacZ reporter gene in the whole-mount murine brain in semi-quantitative manner is performed. Mutations in Tsen54 gene causes pontocerebellar hypoplasia (PCH), severe neurodegenerative disorder with both mental and motor deficits. Comparing relative levels of Tsen54 gene expression, we have demonstrated that highest Tsen54 expression observed in anatomical brain substructures important for the normal motor and memory functions in mice. In the forebrain strong expression in perirhinal, retrosplenial and secondary motor areas was observed. In olfactory area Tsen54 is highly expressed in the nucleus of the lateral olfactory tract, anterior olfactory and bed nuclei, while in hypothalamus in lateral mammillary nucleus and preoptic area. In hindbrain Tsen54 is expressed in the reticular, cuneate and trigeminal nuclei of medulla, and in pontine gray of pons and in cerebellum, in the molecular and Purkinje cell layers. Delineating anatomical brain regions in which Tsen54 is strongly expressed will allow functionally address the role Tsen54 gene in normal physiology and in PCH disease.Significance StatementCharacterization of gene expression pattern in the brain of model organisms is critical for unravelling the gene function in normal physiology and disease. It is performed by optical imaging of the two-dimensional brain sections which then assembled in volume images. Here we applied microCT platform, which allows three-dimensional imaging of non transparent samples, for analysis of gene expression. This method based on detection by X-ray the bromine molecules presented in the products generated by enzymatic activity of b-galactosidase reporter gene. With this method we identify anatomical brain substructures in which Tsen54 gene, mutated in pontocerebellar hypoplasia disease, is expressed.

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ClusterMap: multi-scale clustering analysis of spatial gene expression

10.21203/rs.3.rs-249361/v1 ◽

2021 ◽

Author(s):

Yichun He ◽

Xin Tang ◽

Jiahao Huang ◽

Haowen Zhou ◽

Kevin Chen ◽

...

Keyword(s):

Gene Expression ◽

Dimensional Space ◽

Expression Patterns ◽

Three Dimensional ◽

Point Pattern Analysis ◽

Point Pattern ◽

Computational Framework ◽

Spatially Resolved ◽

Tissue Organization

Abstract Quantifying RNAs in their spatial context is crucial to understanding gene expression and regulation in complex tissues. In situ transcriptomic methods generate spatially resolved RNA profiles in intact tissues. However, there is a lack of a unified computational framework for integrative analysis of in situ transcriptomic data. Here, we present an unsupervised and annotation-free framework, termed ClusterMap, which incorporates physical proximity and gene identity of RNAs, formulates the task as a point pattern analysis problem, and thus defines biologically meaningful structures and groups. Specifically, ClusterMap precisely clusters RNAs into subcellular structures, cell bodies, and tissue regions in both two- and three-dimensional space, and consistently performs on diverse tissue types, including mouse brain, placenta, gut, and human cardiac organoids. We demonstrate ClusterMap to be broadly applicable to various in situ transcriptomic measurements to uncover gene expression patterns, cell-cell interactions, and tissue organization principles from high-dimensional transcriptomic images.

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