Title: Searching for Meaningful Signals in the 3D Genome Universe and in the 

          Blood of Cancer Patients

Speaker: Prof. Xianghong Zhou

               Department of Pathology & Laboratory Medicine

               University of California at Los Angeles

Time: 3:30PM, Aug. 18th

Location: Rm. 302, Integrated Science Research Center

Host: Prof. Fan Bai

Contact: Ms. He

Office: 62767408, hejiao@pku.edu.cn

 

Searching for meaningful signals from massive amount of data is a common task in computational biology. In this talk, I will discuss two such examples from our recent research. Firstly, I will describe our method to perform structure-function mapping of 3D genomes. Unlike protein structures, genome structures are highly plastic, posing a significant challenge for structure-function mapping. Here we report an approach to comprehensively identify 3D chromatin clusters that each occurs frequently across a population of genome structures, either deconvoluted from ensemble-averaged Hi-C data or from a collection of single-cell Hi-C data. Applying our method to a population of genome structures of lymphoblastoid cells, we identify an atlas of chromatin clusters. A large number of these clusters are enriched in binding of specific regulatory factors and are therefore defined as “Regulatory Communities.” We reveal two major factors, centromere clustering and transcription factor binding, which significantly stabilize such communities. Secondly, I will report a probabilistic method, CancerLocator, to detect and locate tumor from cell-free DNA of patient blood. Liquid biopsy, unlike traditional tissue biopsy, has the potential to diagnose tumors from many organs. Our method exploits the diagnosis potential of cell-free DNA by determining not only the presence but also the location of tumors.