Cell cycle gene regulation dynamics revealed by RNA velocity and deep-learning.
Ontology highlight
ABSTRACT: Despite the fact that the cell cycle is a fundamental process of life, a detailed quantitative understanding of gene regulation dynamics throughout the cell cycle is far from complete. Single-cell RNA-sequencing (scRNA-seq) technology gives access to these dynamics without externally perturbing the cell. Here, by generating scRNA-seq libraries in different cell systems, we observe cycling patterns in the unspliced-spliced RNA space of cell cycle-related genes. Since existing methods to analyze scRNA-seq are not efficient to measure cycling gene dynamics, we propose a deep learning approach (DeepCycle) to fit these patterns and build a high-resolution map of the entire cell cycle transcriptome. Characterizing the cell cycle in embryonic and somatic cells, we identify major waves of transcri
SUBMITTER: Riba A
PROVIDER: S-EPMC9126911 | biostudies-literature | 2022 May
REPOSITORIES: biostudies-literature
ACCESS DATA