Characterization of network hierarchy reflects cell state specificity in genome organization.
Jingyao WangYue XueYueying HeHui QuanJun ZhangYi Qin GaoPublished in: Genome research (2023)
Dynamic chromatin structure acts as the regulator of transcription program in crucial processes including cancer and cell development, but a unified framework for characterizing chromatin structural evolution remains to be established. Here, we performed graph inferences on Hi-C data sets and derived the chromatin contact networks. We discovered significant decreases in information transmission efficiencies in chromatin of colorectal cancer (CRC) and T-cell acute lymphoblastic leukemia (T-ALL) compared to corresponding normal controls through graph statistics. Using network embedding in the Poincaré disk, the hierarchy depths of chromatin from CRC and T-ALL patients were found to be significantly shallower compared to their normal controls. A reverse trend of change in chromatin structure was observed during early embryo development. We found tissue-specific conservation of hierarchy order in chromatin contact networks. Our findings reveal the top-down hierarchy of chromatin organization, which is significantly attenuated in cancer.
Keyphrases
- transcription factor
- genome wide
- dna damage
- gene expression
- acute lymphoblastic leukemia
- single cell
- dna methylation
- end stage renal disease
- chronic kidney disease
- squamous cell carcinoma
- papillary thyroid
- oxidative stress
- newly diagnosed
- ejection fraction
- stem cells
- machine learning
- mesenchymal stem cells
- acute myeloid leukemia
- social media
- allogeneic hematopoietic stem cell transplantation
- deep learning
- electronic health record
- bone marrow
- quality improvement
- big data
- convolutional neural network