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Gene representation bias in spatial transcriptomics.

Authors :
Li X
Qiu P
Source :
Journal of bioinformatics and computational biology [J Bioinform Comput Biol] 2024 Jun; Vol. 22 (3), pp. 2450007. Date of Electronic Publication: 2024 Jul 20.
Publication Year :
2024

Abstract

For sequencing-based spatial transcriptomics data, the gene-spot count matrix is highly sparse. This feature is similar to scRNA-seq. The goal of this paper is to identify whether there exist genes that are frequently under-detected in Visium compared to bulk RNA-seq, and the underlying potential mechanism of under-detection in Visium. We collected paired Visium and bulk RNA-seq data for 28 human samples and 19 mouse samples, which covered diverse tissue sources. We compared the two data types and observed that there indeed exists a collection of genes frequently under-detected in Visium compared to bulk RNA-seq. We performed a motif search to examine the last 350 bp of the frequently under-detected genes, and we observed that the poly (T) motif was significantly enriched in genes identified from both human and mouse data, which matches with our previous finding about frequently under-detected genes in scRNA-seq. We hypothesized that the poly (T) motif may be able to form a hairpin structure with the poly (A) tails of their mRNA transcripts, making it difficult for their mRNA transcripts to be captured during Visium library preparation.

Details

Language :
English
ISSN :
1757-6334
Volume :
22
Issue :
3
Database :
MEDLINE
Journal :
Journal of bioinformatics and computational biology
Publication Type :
Academic Journal
Accession number :
39036848
Full Text :
https://doi.org/10.1142/S0219720024500070