Sang Ming WANG

Sang Ming WANG

University of Nebraska Medical Center

Title: Genome-scale mapping promoter variation through exome sequencing


San Ming Wang finished his Master of Medicine during September, 1983—July, 1986 from Shandong Medical University, Jinan, China. He pursued Doctor of Medicine December, during the year December 1989—June, 1994 at Genetic Unit, Swiss Institute for Experimental Cancer Research (ISREC) / University of Lausanne, Switzerland. He worked as Assistant Professor during January, 2004–October, 2009 at Northwestern University. Later he got appointed as Director for Center for Functional Genomics, ENH Research Institute (Now named NorthShore University HealthSystem Research Institute). From October, 2010 – till date, he is working as an Associate Professor at Department of Genetics, Cell Biology & Anatomy, University of Nebraska Medical Center, Nebraska.


Promoter plays essential roles in regulating gene expression. Alteration in promoter sequences can change gene expression, leading to profound impact in evolution, physiology, and disease. Comprehensive analysis of promoter sequences is critical to understand gene expression regulation under biological and pathological conditions. Here we report the development of a method named EPA (Exome-based Promoter Analysis) for the purpose. The method takes the advantage of the random fragmentation used in exome sequencing to obtain the promoter-exon containing sequences. A unique feature of the method is that it preserves the original contents in promoters for sequencing, therefore, allows de novo detection of the changes in promoters without a priori knowledge. This overcomes the weakness in hybridization-based methods as they rely on the normal promoter sequences to design probes. Our evaluation of the method in an exome data set generated from human CD4+ T helper cells shows that the method provides high sensitivity to detect most of the gene promoters, and high specificity to detect the common, rare and novel variants in the detected promoters, TF binding motifs, and TATA boxes. EPA method provides a simple but effective means for genome-scale promoter study.

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