Keynote

Keynote speech

Talk title: 3D genomics and diseases

 

Cheng Li, Ph.D.

Principal Investigator

School of Life Sciences, Center for Bioinformatics and Center for Statistical Science

Peking University, China

Email: cheng_li@pku.edu.cn

 

Abstract:

The Hi-C method is widely used to study the functional roles of three-dimensional architecture of genome. Here, we integrate Hi-C, WGS and RNA-seq to study the 3D genome architecture of multiple myeloma (MM) and how it associates with genomic variation and gene expression. Our results show that Hi-C interaction matrices are biased by copy number variations (CNVs) and can be used to detect CNVs. Also, combining Hi-C and WGS data can improve the detection of translocations. We find that CNV breakpoints significantly overlap with topologically associating domain (TAD) boundaries. Compared to normal B cells, the number of TADs increases by 25% in MM and the average size of TADs is smaller, and about 20% of genomic regions switch their chromatin A/B compartment types. In summary, we report a 3D genome interaction map of aneuploid multiple myeloma cells and reveal the relationship among CNVs, translocations, 3D genome reorganization, and gene expression regulation.

 

 

Cheng Li’s biography:

Dr. Cheng Li studied computer science at Beijing Normal University (BS, 1995) and statistics at University of California, Los Angeles (PhD, 2001). He has worked at Harvard School of Public Health and Dana-Farber Cancer Institute as an Assistant Professor since 2002 and Associate Professor since 2008. Dr. Cheng Li’s group has developed many novel gene expression and SNP microarray analysis and visualization methods, and implemented and maintained highly-cited genomics analysis software such as dChip and batch effect adjustment software ComBat (2600 citations). Since 2013, he has worked at Peking University, School of Life Sciences and focuses on 3D genomics experimental techniques, analysis methods and applications to diseases.