Back

Cross-species single-cell annotation with orthologous marker gene groups

Chau, T.; Timilsena, P. R.; Bathala, S. P.; Bargmann, B.; Li, S.

2023-06-20 bioinformatics
10.1101/2023.06.18.545471 bioRxiv
Show abstract

Single-cell RNA sequencing (scRNA-seq) technology has been widely used in characterizing various cell types from in plant growth and development1-6. Applications of this technology in Arabidopsis have benefited from the extensive knowledge of cell-type identity markers7,8. Contrastingly, accurate labeling of cell types in other plant species remains a challenge due to the scarcity of known marker genes9. Various approaches have been explored to address this issue; however, studies have found many closest orthologs of cell-type identity marker genes in Arabidopsis do not exhibit the same cell-type identity across diverse plant species10,11. To address this challenge, we have developed a novel computational strategy called Orthologous Marker Gene Groups (OMGs). We demonstrated that using OMGs as a unit to determine cell type identity enables assignment of cell types by comparing 15 distantly related species. Our analysis revealed 14 dominant clusters with substantial conservation in shared cell-type markers across monocots and dicots.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.