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Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States

Single-cell research has provided a breakthrough in biology to understand heterogeneous cell groups, such as tissues and organs, in development and disease. Molecular barcoding and subsequent sequencing technology insert a single-cell barcode into isolated single cells, allowing separation cell by c...

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Autor principal: Kim, Ik Soo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society for Molecular and Cellular Biology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9982054/
https://www.ncbi.nlm.nih.gov/pubmed/36859472
http://dx.doi.org/10.14348/molcells.2023.2168
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author Kim, Ik Soo
author_facet Kim, Ik Soo
author_sort Kim, Ik Soo
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description Single-cell research has provided a breakthrough in biology to understand heterogeneous cell groups, such as tissues and organs, in development and disease. Molecular barcoding and subsequent sequencing technology insert a single-cell barcode into isolated single cells, allowing separation cell by cell. Given that multimodal information from a cell defines precise cellular states, recent technical advances in methods focus on simultaneously extracting multimodal data recorded in different biological materials (DNA, RNA, protein, etc.). This review summarizes recently developed single-cell multiomics approaches regarding genome, epigenome, and protein profiles with the transcriptome. In particular, we focus on how to anchor or tag molecules from a cell, improve throughputs with sample multiplexing, and record lineages, and we further discuss the future developments of the technology.
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spelling pubmed-99820542023-03-04 Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States Kim, Ik Soo Mol Cells Minireview Single-cell research has provided a breakthrough in biology to understand heterogeneous cell groups, such as tissues and organs, in development and disease. Molecular barcoding and subsequent sequencing technology insert a single-cell barcode into isolated single cells, allowing separation cell by cell. Given that multimodal information from a cell defines precise cellular states, recent technical advances in methods focus on simultaneously extracting multimodal data recorded in different biological materials (DNA, RNA, protein, etc.). This review summarizes recently developed single-cell multiomics approaches regarding genome, epigenome, and protein profiles with the transcriptome. In particular, we focus on how to anchor or tag molecules from a cell, improve throughputs with sample multiplexing, and record lineages, and we further discuss the future developments of the technology. Korean Society for Molecular and Cellular Biology 2023-02-28 2023-02-27 /pmc/articles/PMC9982054/ /pubmed/36859472 http://dx.doi.org/10.14348/molcells.2023.2168 Text en © The Korean Society for Molecular and Cellular Biology. All rights reserved. https://creativecommons.org/licenses/by-nc-sa/3.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ (https://creativecommons.org/licenses/by-nc-sa/3.0/)
spellingShingle Minireview
Kim, Ik Soo
Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States
title Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States
title_full Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States
title_fullStr Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States
title_full_unstemmed Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States
title_short Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States
title_sort single-cell molecular barcoding to decode multimodal information defining cell states
topic Minireview
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9982054/
https://www.ncbi.nlm.nih.gov/pubmed/36859472
http://dx.doi.org/10.14348/molcells.2023.2168
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