RT Journal Article
SR Electronic
T1 Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing
JF Life Science Alliance
JO Life Sci. Alliance
FD Life Science Alliance LLC
SP e202201701
DO 10.26508/lsa.202201701
VO 6
IS 1
A1 Jonathan Liu
A1 Vanessa Tran
A1 Venkata Naga Pranathi Vemuri
A1 Ashley Byrne
A1 Michael Borja
A1 Yang Joon Kim
A1 Snigdha Agarwal
A1 Ruofan Wang
A1 Kyle Awayan
A1 Abhishek Murti
A1 Aris Taychameekiatchai
A1 Bruce Wang
A1 George Emanuel
A1 Jiang He
A1 John Haliburton
A1 Angela Oliveira Pisco
A1 Norma F Neff
YR 2023
UL https://www.life-science-alliance.org/content/6/1/e202201701.abstract
AB 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.