Size matters: the impact of nucleus size on results from spatial transcriptomics.
IF: 8.440


Visium Spatial Gene Expression (ST) is a method combining histological spatial information with transcriptomics profiles directly from tissue sections. The use of spatial information has made it possible to discover new modes of gene expression regulations. However, in the ST experiment, the nucleus size of cells may exceed the thickness of a tissue slice. This may, in turn, negatively affect comprehensive capturing the transcriptomics profile in a single slice, especially for tissues having large differences in the size of nuclei. Here, we defined the effect of Consecutive Slices Data Integration (CSDI) on unveiling accurate spot clustering and deconvolution of spatial transcriptomic spots in human postmortem brains. By considering the histological information as reference, we assessed the improvement of unsupervised clustering and single nuclei RNA-seq and ST data integration before and after CSDI. Apart from the escalated number of defined clusters representing neuronal layers, the pattern of clusters in consecutive sections was concordant only after CSDI. Besides, the assigned cell labels to spots matches the histological pattern of tissue sections after CSDI. CSDI can be applied to investigate consecutive sections studied with ST in the human cerebral cortex, avoiding misinterpretation of spot clustering and annotation, increasing accuracy of cell recognition as well as improvement in uncovering the layers of grey matter in the human brain.


Spatial Transcriptomics
Cerebral cortex
Consecutive tissue sections
Data integration
Neuronal nuclei
Spatial transcriptomics

MeSH terms

Gene Expression Profiling
Cell Communication


Mohammadi, Elyas
Chojnowska, Katarzyna
Bieńkowski, Michał
Kostecka, Anna
Koczkowska, Magdalena
Żmijewski, Michał A
Jąkalski, Marcin
Ingelsson, Martin
Filipowicz, Natalia
Olszewski, Paweł
Davies, Hanna
Wierzbicka, Justyna M
Hyman, Bradley T
Dumanski, Jan P
Piotrowski, Arkadiusz
Mieczkowski, Jakub