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Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing
Spatial transcriptomics extends single-cell RNA sequencing (scRNA-seq) by providing spatial context for cell type identification and analysis. Imaging-based spatial technologies such as multiplexed error-robust fluorescence in situ hybridization (MERFISH) can achieve single-cell resolution, directly...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Life Science Alliance LLC
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9760489/ https://www.ncbi.nlm.nih.gov/pubmed/36526371 http://dx.doi.org/10.26508/lsa.202201701 |
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author | Liu, Jonathan Tran, Vanessa Vemuri, Venkata Naga Pranathi Byrne, Ashley Borja, Michael Kim, Yang Joon Agarwal, Snigdha Wang, Ruofan Awayan, Kyle Murti, Abhishek Taychameekiatchai, Aris Wang, Bruce Emanuel, George He, Jiang Haliburton, John Oliveira Pisco, Angela Neff, Norma F |
author_facet | Liu, Jonathan Tran, Vanessa Vemuri, Venkata Naga Pranathi Byrne, Ashley Borja, Michael Kim, Yang Joon Agarwal, Snigdha Wang, Ruofan Awayan, Kyle Murti, Abhishek Taychameekiatchai, Aris Wang, Bruce Emanuel, George He, Jiang Haliburton, John Oliveira Pisco, Angela Neff, Norma F |
author_sort | Liu, Jonathan |
collection | PubMed |
description | Spatial transcriptomics extends single-cell RNA sequencing (scRNA-seq) by providing spatial context for cell type identification and analysis. Imaging-based spatial technologies such as multiplexed error-robust fluorescence in situ hybridization (MERFISH) can achieve single-cell resolution, directly mapping single-cell identities to spatial positions. MERFISH produces a different data type than scRNA-seq, and a technical comparison between the two modalities is necessary to ascertain how to best integrate them. We performed MERFISH on the mouse liver and kidney and compared the resulting bulk and single-cell RNA statistics with those from the Tabula Muris Senis cell atlas and from two Visium datasets. MERFISH quantitatively reproduced the bulk RNA-seq and scRNA-seq results with improvements in overall dropout rates and sensitivity. Finally, we found that MERFISH independently resolved distinct cell types and spatial structure in both the liver and kidney. Computational integration with the Tabula Muris Senis atlas did not enhance these results. We conclude that MERFISH provides a quantitatively comparable method for single-cell gene expression and can identify cell types without the need for computational integration with scRNA-seq atlases. |
format | Online Article Text |
id | pubmed-9760489 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Life Science Alliance LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-97604892022-12-20 Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing Liu, Jonathan Tran, Vanessa Vemuri, Venkata Naga Pranathi Byrne, Ashley Borja, Michael Kim, Yang Joon Agarwal, Snigdha Wang, Ruofan Awayan, Kyle Murti, Abhishek Taychameekiatchai, Aris Wang, Bruce Emanuel, George He, Jiang Haliburton, John Oliveira Pisco, Angela Neff, Norma F Life Sci Alliance Resources Spatial transcriptomics extends single-cell RNA sequencing (scRNA-seq) by providing spatial context for cell type identification and analysis. Imaging-based spatial technologies such as multiplexed error-robust fluorescence in situ hybridization (MERFISH) can achieve single-cell resolution, directly mapping single-cell identities to spatial positions. MERFISH produces a different data type than scRNA-seq, and a technical comparison between the two modalities is necessary to ascertain how to best integrate them. We performed MERFISH on the mouse liver and kidney and compared the resulting bulk and single-cell RNA statistics with those from the Tabula Muris Senis cell atlas and from two Visium datasets. MERFISH quantitatively reproduced the bulk RNA-seq and scRNA-seq results with improvements in overall dropout rates and sensitivity. Finally, we found that MERFISH independently resolved distinct cell types and spatial structure in both the liver and kidney. Computational integration with the Tabula Muris Senis atlas did not enhance these results. We conclude that MERFISH provides a quantitatively comparable method for single-cell gene expression and can identify cell types without the need for computational integration with scRNA-seq atlases. Life Science Alliance LLC 2022-12-16 /pmc/articles/PMC9760489/ /pubmed/36526371 http://dx.doi.org/10.26508/lsa.202201701 Text en © 2022 Liu et al. https://creativecommons.org/licenses/by/4.0/This article is available under a Creative Commons License (Attribution 4.0 International, as described at https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Resources Liu, Jonathan Tran, Vanessa Vemuri, Venkata Naga Pranathi Byrne, Ashley Borja, Michael Kim, Yang Joon Agarwal, Snigdha Wang, Ruofan Awayan, Kyle Murti, Abhishek Taychameekiatchai, Aris Wang, Bruce Emanuel, George He, Jiang Haliburton, John Oliveira Pisco, Angela Neff, Norma F Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing |
title | Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing |
title_full | Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing |
title_fullStr | Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing |
title_full_unstemmed | Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing |
title_short | Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing |
title_sort | concordance of merfish spatial transcriptomics with bulk and single-cell rna sequencing |
topic | Resources |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9760489/ https://www.ncbi.nlm.nih.gov/pubmed/36526371 http://dx.doi.org/10.26508/lsa.202201701 |
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