SEE: A Method for Predicting the Dynamics of Chromatin Conformation Based on Single‐Cell Gene Expression - Minghong Li; Yurong Yang; Rucheng Wu; Haiyan Gong; Zan Yuan; Jixin Wang; Erping Long; Xiaotong Zhang; Yang Chen (Advanced Science)
Abstract The dynamics of chromatin conformation involve continuous and reversible changes within the nucleus of a cell, which participate in regulating processes such as gene expression, DNA replication, and damage repair. Here, SEE is introduced, an artificial intelligence (AI) method that utilizes autoencoder and transformer techniques to analyze chromatin dynamics using single‐cell RNA sequencing data and a limited number of single‐cell Hi‐C maps. SEE is employed to investigate chromatin dynamics across different scales, enabling the detection of (i) rearrangements in topologically associating domains (TADs), and (ii) oscillations in chromatin interactions at gene loci. Additionally, SEE facilitates the interpretation of disease‐associated single‐nucleotide polymorphisms (SNPs) by leveraging the dynamic features of chromatin conformation. Overall, SEE offers a single‐cell, high‐resolution approach to analyzing chromatin dynamics in both developmental and disease contexts.