Literature DB >> 29542254

Placing RNA in context and space - methods for spatially resolved transcriptomics.

Carina Strell1, Markus M Hilscher1, Navya Laxman1, Jessica Svedlund1, Chenglin Wu1, Chika Yokota1, Mats Nilsson1.   

Abstract

Single-cell transcriptomics provides us with completely new insights into the molecular diversity of different cell types and the different states they can adopt. The technique generates inventories of cells that constitute the building blocks of multicellular organisms. However, since the method requires isolation of discrete cells, information about the original location within tissue is lost. Therefore, it is not possible to draw detailed cellular maps of tissue architecture and their positioning in relation to other cells. In order to better understand the cellular and tissue function of multicellular organisms, we need to map the cells within their physiological, morphological, and anatomical context and space. In this review, we will summarize and compare the different methods of in situ RNA analysis and the most recent developments leading to more comprehensive and highly multiplexed spatially resolved transcriptomic approaches. We will discuss their highlights and advantages as well as their limitations and challenges and give an outlook on promising future applications and directions both within basic research as well as clinical integration.
© 2018 Federation of European Biochemical Societies.

Keywords:  cell profiling; gene expression maps; in situ sequencing; spatial transcriptomics; spatially resolved transcriptomics; tissue heterogeneity; tissue maps

Year:  2018        PMID: 29542254     DOI: 10.1111/febs.14435

Source DB:  PubMed          Journal:  FEBS J        ISSN: 1742-464X            Impact factor:   5.542


  30 in total

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2.  An in situ sequencing approach maps PLASTOCHRON1 at the boundary between indeterminate and determinate cells.

Authors:  Reinout Laureyns; Jessica Joossens; Denia Herwegh; Julie Pevernagie; Benjamin Pavie; Kirin Demuynck; Kevin Debray; Griet Coussens; Laurens Pauwels; Tom Van Hautegem; Michiel Bontinck; Josh Strable; Hilde Nelissen
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Review 3.  The Human Islet: Mini-Organ With Mega-Impact.

Authors:  John T Walker; Diane C Saunders; Marcela Brissova; Alvin C Powers
Journal:  Endocr Rev       Date:  2021-09-28       Impact factor: 25.261

4.  Interrogating RNA and protein spatial subcellular distribution in smFISH data with DypFISH.

Authors:  Anca F Savulescu; Robyn Brackin; Emmanuel Bouilhol; Benjamin Dartigues; Jonathan H Warrell; Mafalda R Pimentel; Nicolas Beaume; Isabela C Fortunato; Stephane Dallongeville; Mikaël Boulle; Hayssam Soueidan; Fabrice Agou; Jan Schmoranzer; Jean-Christophe Olivo-Marin; Claudio A Franco; Edgar R Gomes; Macha Nikolski; Musa M Mhlanga
Journal:  Cell Rep Methods       Date:  2021-09-13

Review 5.  Spatial-omics: Novel approaches to probe cell heterogeneity and extracellular matrix biology.

Authors:  Grace C Bingham; Fred Lee; Alexandra Naba; Thomas H Barker
Journal:  Matrix Biol       Date:  2020-05-19       Impact factor: 10.447

6.  RollFISH achieves robust quantification of single-molecule RNA biomarkers in paraffin-embedded tumor tissue samples.

Authors:  Chenglin Wu; Michele Simonetti; Carla Rossell; Marco Mignardi; Reza Mirzazadeh; Laura Annaratone; Caterina Marchiò; Anna Sapino; Magda Bienko; Nicola Crosetto; Mats Nilsson
Journal:  Commun Biol       Date:  2018-11-28

7.  Molecular profiling of resident and infiltrating mononuclear phagocytes during rapid adult retinal degeneration using single-cell RNA sequencing.

Authors:  Kaitryn E Ronning; Sarah J Karlen; Eric B Miller; Marie E Burns
Journal:  Sci Rep       Date:  2019-03-19       Impact factor: 4.379

Review 8.  Spatial omics and multiplexed imaging to explore cancer biology.

Authors:  Verena C Wimmer; Delphine Merino; Kelly L Rogers; Shalin H Naik; Sabrina M Lewis; Marie-Liesse Asselin-Labat; Quan Nguyen; Jean Berthelet; Xiao Tan
Journal:  Nat Methods       Date:  2021-08-02       Impact factor: 28.547

9.  Discovery of molecular features underlying the morphological landscape by integrating spatial transcriptomic data with deep features of tissue images.

Authors:  Sungwoo Bae; Hongyoon Choi; Dong Soo Lee
Journal:  Nucleic Acids Res       Date:  2021-06-04       Impact factor: 16.971

Review 10.  The Unmixing Problem: A Guide to Applying Single-Cell RNA Sequencing to Bone.

Authors:  Matthew B Greenblatt; Noriaki Ono; Ugur M Ayturk; Shawon Debnath; Sarfaraz Lalani
Journal:  J Bone Miner Res       Date:  2019-07       Impact factor: 6.741

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