Email

chenghang.zong@bcm.edu

Positions

Assistant Professor

Molecular and Human Genetics
Baylor College of Medicine
Houston, Texas United States

McNair Scholar

Baylor College of Medicine
Houston, Texas United States

Member

Dan L Duncan Comprehensive Cancer Center
Baylor College of Medicine
Houston, Texas United States

Education

BA from University of Science and Technology of China

01/2000 - Hefei, Anhui China

Physical Chemistry

PhD from University of California

01/2007 - San Diego, California United States

Chemistry

Post-Doctoral Fellowship at University of Illinois

01/2009 - Urbana-Champaign, Illinois United States

Post-Doctoral Fellowship at Harvard University

01/2013 - Cambridge, Massachusetts United States

Professional Interests

• Single-cell whole genome sequencing, single-cell RNA-seq, single-cell ATAC-seq, single cell DNA damagenome, tumorigenesis.

Professional Statement

The research of our laboratory focuses on the development of novel single-cell technologies and their applications in biology studies. With the rapid development of next-generation sequencing technology, high-throughput sequencing has become a powerful tool for biological research. In our lab, we are interested in examining the genome at single-cell resolution, in contrast to the genome averaged from an ensemble of cells. As a demonstration of the principle, we are able to detect genomic variations including DNA lesions existing in individual cancer cells. We are particularly interested in detecting early mutations that drive tumorigenesis as well as the early stage of heterogeneity that will influence later tumor development. The lab specifically focuses on pancreatic cancer.

In addition to the genome, we are also interested in developing novel methods for single-cell transcriptional and epigenetic profiling. The goal is to capture the development in action, particularly adult stem cell differentiation. Much finer temporal and spatial resolution will allow us to unveil the early signature transcriptome and epigenome changes, which are often buried among downstream responses by late stage and ensemble profiling. The modeling of complex cellular decision-making processes at multiple layers of pathways and regulatory networks will also be pursued in the lab with the enriched heterogeneous and dynamic information extracted from single cells. For translational research, we will actively pursue clinical applications of single-cell techniques, including prenatal genetic testing as well as early cancer diagnosis.

Over the recent years, we have developed the following single-cell methods: the linear whole-genome implication (LCS-WGA), single-cell total-RNA-seq method (MATQ-seq) and the droplet-based single-cell total-RNA-seq (MATQ-drop). These methods have been applied to various research fronts including cancer biology, aging, and neuronal science.

Websites

Selected Publications

• "Effective detection of variation in single-cell transcriptomes using MATQ-seq." Nature Methods. 2017 January ; 14 : 267-270.
• Zong C, Lu S, Chapman AR, Xie XS "Genome-wide detection of single-nucleotide and copy-number variations of a single human cell.." Science. 2012 338 (6114): 1622-6. Pubmed PMID: 23258894

Funding

New Innovator Award

NIH Director's program