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Development of a single-cell RNA structure sequencing approach to study human neurogenesis

Time:Wednesday, September, at 16:00 SGT

Event Overview:

Transcription and translation are the major steps in controlling gene expression. However, RNA expression abundance only has around 40% explanatory power of protein abundance, suggesting post-transcription regulation such as RNA structure-based regulation.

To date, great interest is growing in the relationship between gene function and RNA structure. For example, RNA structure has been linked to neurological disease. However, unlike DNA and protein structure, RNA is inherently flexible and hence more difficult to study due to technical limitations. One of the bottlenecks of RNA structure study is that it requires millions of cells as starting materials, causing the lagging behind RNA structure studies. To overcome this problem, we recently developed a single-cell RNA structure sequencing approach to obtain both RNA secondary structure and RNA expression information simultaneously, at the single-cell level.

Key learning objective:

● Learn more about developing a single-cell RNA structure sequencing approach and applied it to human neurogenesis.

● Learn how to identify cell stage-specific RNA structures with no gene expression difference.

● Know how RNA structure could help to better cluster cell types.

Presenters Biography:

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Jiaxu Wang

PI, Genome Institute of Singapore

Jiaxu Wang has a Ph.D. degree from the University of Science and Technology of China (USTC). By the end of 2013, he joined Stanton LW’s lab as a post-doctoral fellow at the Genome Institute of Singapore and was soon promoted to junior PI. Thanks to his rich experience, he is now developing a single-cell RNA structure sequencing approach, then applying it to human neurogenesis and neurological disease to identify RNA-structure-based biomarkers and drug targets. 

 

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Shuyun Ding

Technical Support Engineer, Vazyme

Shuyun Ding is a Technical Support Engineer with Vazyme, where she assists and resolves technical problems and operational issues in next-generation sequencing.

 

 

 
 

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