Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing
Jonathan Liu, Vanessa Tran, Venkata N. P. Vemuri, Ashley Byrne, Michael Borja, Yang Joon Kim, Snigdha Agarwal, Ruofan Wang, Kyle Awayan, Abhishek Murti, Aris Taychameekiatchai, Bruce Wang, George Emanuel, Jiang He, John Haliburton, Angela Oliveira Pisco, Norma Neff
Abstract
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.