Modeling X chromosome inactivation using t5iLA naive human pluripotent stem cells
Yudan Shang1, Nannan Wang2,3,4, Haoyi Wang2,3,4,5
1Department of Obstetrics and Gynecology, Guangdong Provincial Key Laboratory for Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, Guangdong-Hong Kong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal Medicine, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
This study presents a new in vitro method using human pluripotent stem cells to model X chromosome inactivation (XCI). The advanced framework tracks XIST RNA and epigenetic changes, aiding research in developmental biology and disease.
Area of Science:
- Epigenetics and Developmental Biology
- Stem Cell Biology
- Genetics
Background:
- X chromosome inactivation (XCI) is essential for gene dosage compensation in female mammals.
- Understanding early embryonic XCI requires a robust in vitro model.
- Human pluripotent stem cells (hPSCs) offer a promising system for studying XCI dynamics.
Purpose of the Study:
- To introduce an advanced framework for in-depth study of XCI using hPSCs.
- To investigate the role of XIST and epigenetic alterations in XCI.
- To model the transition between naive and primed pluripotent states during XCI.
Main Methods:
- Utilized dual fluorescent reporter hESC lines for real-time XCI tracking.
- Developed protocols for inducing X chromosome reactivation and inactivation.
- Employed flow cytometry, RNA FISH, and transcriptome sequencing for X status characterization.
Main Results:
- Successfully distinguished naive and primed hESCs based on XIST expression and reporter activity.
- Demonstrated the utility of hESC lines in modeling human XCI initiation and maintenance.
- Established conditions for random XCI induction and analyzed X chromosome reactivation.
Conclusions:
- Provided a detailed and reproducible methodology for in vitro XCI research using hPSCs.
- The framework advances the study of XCI mechanisms, with applications in developmental biology and disease modeling.
- Facilitates deeper understanding and potential manipulation of XCI dynamics.
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