Chongzhi Zang, Ph.D.

Assistant Professor of Public Health Sciences
Assistant Professor of Biochemistry and Molecular Genetics
Assistant Professor of Biomedical Engineering

Center for Public Health Genomics
University of Virginia School of Medicine
P. O. Box 800717, Charlottesville, VA 22908

Office: West Complex (MSB) 6131C
Phone: 434-243-5397
Email: zang@virginia.edu

CV: download
Lab website: https://zanglab.github.io/


Education and Training

B.S., Physics, Peking University, 2005

Ph.D., Physics, The George Washington University, 2010

Postdoc, Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard University, 2010–2016


Research Interests

Bioinformatics methodology development; Epigenetics and chromatin biology; Transcriptional regulation; Cancer genomics and epigenomics; Statistical methods for biomedical data integration; Theoretical and computational biophysics


Research Description

My research program focuses on two aspects: 1) developing quantitative models and computational methods for analyzing high-throughput data generated from emerging genomics technologies; and 2) using innovative computational and data science approaches to study epigenetics and transcriptional regulation of gene expression in mammalian cell systems and human diseases such as cancer.

How gene expression is regulated in chromatin is a fundamental question in molecular biology. The transcriptional program is a major determinant of cell identity; its dysregulation is involved in many diseases, including cancer. High-throughput genomics technologies enable us to obtain massive data measuring numerous factors and elements in the genome that affect chromatin states and gene regulation. We leverage big data and conduct computational research at the intersection of functional genomics, epigenetics, and cancer biology. Several ongoing research directions include:

1. Bioinformatics methods for emerging omics technologies

Modern development of life sciences has been accelerated by new technologies. Innovative analytics methods are essential for converting high-throughput experimental data into scientific knowledge. We are interested in developing innovative statistical models and algorithms for analyzing data from emerging genomics technologies. As a pioneer in next-generation sequencing (NGS) bioinformatics, we developed SICER (Bioinformatics 2009), one of the most widely used methods for ChIP-seq data analysis. We are currently developing new methods for unbiased analysis of data from epigenomics (ATAC-seq, CUT&RUN, CUT&Tag, etc.), single-cell multi-omics, and spatial omics techniques to study gene regulation.

2. Machine learning methods for regulatory factor prediction and multi-omics integration

Transcriptional regulators (TRs, including transcription factors and chromatin regulators) are key players in transcriptional regulation. Leveraging publicly available ChIP-seq data, we developed a series of machine learning-based computational methods, including MARGE (Genome Res 2016), BART (Bioinformatics 2018), BARTweb (NAR Genom Bioinform 2021), and BART3D (Bioinformatics 2021), for predicting cis-regulatory profiles and functional TRs from various input data types. Integrating public omics data with the Cancer Genome Atlas (TCGA), we curated BART Cancer (NAR Cancer 2021) for modeling transcription factor activities in TCGA cancer types. We are currently developing new methods specifically for single-cell multi-omics data, and will further develop a general framework using advanced machine learning for multi-omics integration and regulatory network prediction.

3. Data-inspired modeling for functional epigenetics and transcriptional condensation

Data-driven discovery has become a new paradigm of biological research. By modeling massive data available in the public domain, we can find new patterns and new relationships in biological entities that are usually unseen from individual datasets. Integrating thousands of public omics datasets, we recently identified a cancer-specific binding pattern of CTCF, an important DNA-binding protein, and characterized its function in facilitating oncogenic transcriptional activation (Genome Biol 2020). Inspired by emerging evidence of phase separation phenomena in gene regulation (e.g., Nature 2021), we will develop computational models to characterize phase-separated transcriptional condensation events from multi-omics data, with the ultimate goal of better understanding molecular mechanisms of transcriptional regulation.


Selected Publications

Selected from 50+ journal articles. A complete publication list can be found at my Google Scholar profile.
* indicates authors with equal contributions. # indicates co-corresponding authors. Underscored indicates lab members.

  1. Single-cell chromatin profiling of the primitive gut tube reveals regulatory dynamics underlying lineage fate decisions
    Ryan J. Smith*, Hongpan Zhang*, Shengen Shawn Hu*, Theodora Yung, Roshane Francis, Lilian Lee, Mark W. Onaitis, Peter B. Dirks, Chongzhi Zang#, Tae-Hee Kim#
    Nature Communications 13, 2965 (2022)

  2. Single-nucleus chromatin accessibility profiling highlights regulatory mechanisms of coronary artery disease risk
    Adam W. Turner*, Shengen Shawn Hu*, Jose Verdezoto Mosquera, Wei Feng Ma, Chani J. Hodonsky, Doris Wong, Gaëlle Auguste, Yipei Song, Katia Sol-Church, Emily Farber, Soumya Kundu, Anshul Kundaje, Nicolas G. Lopez, Lijiang Ma, Saikat Kumar B. Ghosh, Suna Onengut-Gumuscu, Euan A. Ashley, Thomas Quertermous, Aloke V. Finn, Nicholas J. Leeper, Jason C. Kovacic, Johan L.M. Björkgren, Chongzhi Zang#, Clint L. Miller#
    Nature Genetics, doi: 10.1038/s41588-022-01069-0 (2022)

  3. Tcf1 preprograms the mobilization of glycolysis in central memory CD8+ T cells during recall responses
    Qiang Shan*, Shengen Shawn Hu*, Shaoqi Zhu, Xia Chen, Vladimir P. Badovinac, Weiqun Peng, Chongzhi Zang#, Hai-Hui Xue#
    Nature Immunology 23, 386–398 (2022)

  4. UTX condensation underlies its tumour-suppressive activity
    Bi Shi*, Wei Li*, Yansu Song*, Zhenjia Wang*, Rui Ju, Aleksandra Ulman, Jing Hu, Francesco Palomba, Yanfang Zhao, John Philip Le, William Jarrard, David Dimoff, Michelle A. Digman, Enrico Gratton, Chongzhi Zang, Hao Jiang
    Nature 597, 726–731 (2021)

  5. BARTweb: a web server for transcriptional regulator association analysis
    Wenjing Ma*, Zhenjia Wang*, Yifan Zhang, Neal E Magee, Yayi Feng, Ruoyao Shi, Yang Chen, Chongzhi Zang
    NAR Genomics and Bioinformatics 3(2), lqab022 (2021)

  6. BART3D: Inferring transcriptional regulators associated with differential chromatin interactions from Hi-C data
    Zhenjia Wang, Yifan Zhang, Chongzhi Zang
    Bioinformatics, btab173 (2021)

  7. BART Cancer: a web resource for transcriptional regulators in cancer genomes
    Zachary V. Thomas, Zhenjia Wang, Chongzhi Zang
    NAR Cancer 3, zcab011 (2021)

  8. Cancer-specific CTCF binding facilitates oncogenic transcriptional dysregulation
    Celestia Fang*, Zhenjia Wang*, Cuijuan Han, Stephanie L. Safgren, Kathryn A. Helmin, Emmalee R. Adelman, Valentina Serafin, Giuseppe Basso, Kyle P. Eagen, Alexandre Gaspar-Maia, Maria E. Figueroa, Benjamin D. Singer, Aakrosh Ratan, Panagiotis Ntziachristos#, Chongzhi Zang#
    Genome Biology 21, 247 (2020)

  9. RECOGNICER: A coarse-graining approach for identifying broad domains from ChIP-seq data
    Chongzhi Zang#, Yiren Wang, Weiqun Peng#
    Quantitative Biology, doi:10.1007/s40484-020-0225-2 (2020)

  10. Polyadenylation of histone H3.1 mRNA promotes cell transformation by displacing H3.3 from gene regulatory elements
    Danqi Chen*, Qiao Yi Chen*, Zhenjia Wang*, Yusha Zhu, Thomas Kluz, Wuwei Tan, Jinquan Li, Feng Wu, Lei Fang, Xiaoru Zhang, Rongquan He, Steven Shen, Hong Sun, Chongzhi Zang#, Chunyuan Jin#, Max Costa#
    iScience 23, 101518 (2020)

  11. Expanded encyclopaedias of DNA elements in the human and mouse genomes
    The ENCODE Project Consortium (including Chongzhi Zang), Jill E. Moore*, Michael J. Purcaro*, Henry E. Pratt*, Charles B. Epstein*, Noam Shoresh*, Jessika Adrian*, Trupti Kawli*, Carrie A. Davis*, Alexander Dobin*, Rajinder Kaul*, Jessica Halow*, Eric L. Van Nostrand*, Peter Freese*, David U. Gorkin*, Yin Shen*, Yupeng He*, Mark Mackiewicz*, Florencia Pauli-Behn*, Brian A. Williams, Ali Mortazavi, Cheryl A. Keller, Xiao-Ou Zhang, Shaimae I. Elhajjajy, Jack Huey, Diane E. Dickel, Valentina Snetkova, Xintao Wei, Xiaofeng Wang, Juan Carlos Rivera-Mulia, Joel Rozowsky, Jing Zhang, Surya B. Chhetri, Jialing Zhang, Alec Victorsen, Kevin P. White, Axel Visel, Gene W. Yeo, Christopher B. Burge, Eric Lécuyer, David M. Gilbert, Job Dekker, John Rinn, Eric M. Mendenhall, Joseph R. Ecker, Manolis Kellis, Robert J. Klein, William S. Noble, Anshul Kundaje, Roderic Guigó, Peggy J. Farnham, J. Michael Cherry#, Richard M. Myers#, Bing Ren#, Brenton R. Graveley#, Mark B. Gerstein#, Len A. Pennacchio#, Michael P. Snyder#, Bradley E. Bernstein#, Barbara Wold#, Ross C. Hardison#, Thomas R. Gingeras#, John A. Stamatoyannopoulos#, Zhiping Weng#
    Nature 583, 699–710 (2020)

  12. An integrative ENCODE resource for cancer genomics
    Jing Zhang*, Donghoon Lee*, Vineet Dhiman*, Peng Jiang*, Jie Xu*, Patrick McGillivray*, Hongbo Yang*, Jason Liu, William Meyerson, Declan Clarke, Mengting Gu, Shantao Li, Shaoke Lou, Jinrui Xu, Lucas Lochovsky, Matthew Ung, Lijia Ma, Shan Yu, Qin Cao, Arif Harmanci, Koon-Kiu Yan, Anurag Sethi, Gamze Gürsoy, Michael Rutenberg Schoenberg, Joel Rozowsky, Jonathan Warrell, Prashant Emani, Yucheng T. Yang, Timur Galeev, Xiangmeng Kong, Shuang Liu, Xiaotong Li, Jayanth Krishnan, Yanlin Feng, Juan Carlos Rivera-Mulia, Jessica Adrian, James R Broach, Michael Bolt, Jennifer Moran, Dominic Fitzgerald, Vishnu Dileep, Tingting Liu, Shenglin Mei, Takayo Sasaki, Claudia Trevilla-Garcia, Su Wang, Yanli Wang, Chongzhi Zang, Daifeng Wang, Robert J. Klein, Michael Snyder, David M. Gilbert, Kevin Yip, Chao Cheng, Feng Yue#, X. Shirley Liu#, Kevin P. White#, Mark Gerstein#
    Nature Communications 11, 3696 (2020)

  13. Ectopic Tcf1 expression instills a stem-like program in exhausted CD8+ T cells to enhance viral and tumor immunity
    Qiang Shan*, Sheng’en Hu*, Xia Chen, Derek B. Danahy, Vladimir P. Badovinac, Chongzhi Zang#, Hai-Hui Xue#
    Cellular & Molecular Immunology, doi:10.1038/s41423-020-0436-5 (2020)

  14. Nickel induced transcriptional changes persist post exposure through epigenetic reprograming
    Cynthia C Jose*, Zhenjia Wang*, Vinay Singh Tanwar, Xiaoru Zhang, Chongzhi Zang#, Suresh Cuddapah#
    Epigenetics & Chromatin 12, 75 (2019)

  15. YY1 is a cis-regulator in the organoid models of high mammographic density
    Qingsu Cheng, Mina Khoshdeli, Bradley S. Ferguson, Kosar Jabbari, Chongzhi Zang#, Bahram Parvin#
    Bioinformatics 36, 1663–1667 (2019)

  16. BART: a transcription factor prediction tool with query gene sets or epigenomic profiles
    Zhenjia Wang, Mete Civelek, Clint L. Miller, Nathan C. Sheffield, Michael J. Guertin, Chongzhi Zang
    Bioinformatics 34, 2867–2869 (2018)

  17. Cistrome Cancer: a web resource for integrative gene regulation modeling in cancer
    Shenglin Mei, Clifford A. Meyer, Rongbin Zheng, Qian Qin, Qiu Wu, Peng Jiang, Bo Li, Xiaohui Shi, Binbin Wang, Jingyu Fan, Celina Shih, Myles Brown, Chongzhi Zang#, X. Shirley Liu#
    Cancer Research 77, e19–e22 (2017)

  18. Modeling cis-regulation with a compendium of genome-wide histone H3K27ac profiles
    Su Wang*, Chongzhi Zang*, Tengfei Xiao, Jingyu Fan, Shenglin Mei, Qian Qin, Qiu Wu, Xujuan Li, Kexin Xu, Housheng Hansen He, Myles Brown, Clifford A. Meyer#, X. Shirley Liu#
    Genome Research 26, 1417–1429 (2016)

  19. NF-E2, FLI1 and RUNX1 collaborate at areas of dynamic chromatin to activate transcription in mature mouse megakaryocytes
    Chongzhi Zang*, Annouck Luyten*, Christina Chen, X. Shirley Liu, Ramesh A. Shivdasani
    Scientific Reports 6, 30255 (2016)

  20. High-dimensional genomic data bias correction and data integration using MANCIE
    Chongzhi Zang*, Tao Wang*, Ke Deng, Bo Li, Sheng’en Hu, Qian Qin, Tengfei Xiao, Shihua Zhang, Clifford A. Meyer, Housheng Hansen He, Myles Brown, Jun S. Liu, Yang Xie#, X. Shirley Liu#
    Nature Communications 7, 11305 (2016)

  21. Partitioning heritability by functional annotation using genome-wide association summary statistics
    Hilary K. Finucane*#, Brendan Bulik-Sullivan*#, Alexander Gusev, Gosia Trynka, Yakir Reshef, Po-Ru Loh, Verneri Anttila, Han Xu, Chongzhi Zang, Kyle Farh, Stephan Ripke, Felix R. Day, ReproGen Consortium, Schizophrenia Working Group of the Psychiatric Genomics Consortium, The RACI Consortium, Shaun Purcell, Eli Stahl, Sara Lindstrom, John R. B. Perry, Yukinori Okada, Soumya Raychaudhuri, Mark J. Daly, Nick Patterson, Benjamin M. Neale#, Alkes L. Price#
    Nature Genetics 47, 1228–1235 (2015)

  22. Active enhancers are delineated de novo during hematopoiesis with limited lineage fidelity among specified primary blood cells
    Annouck Luyten*, Chongzhi Zang*, X. Shirley Liu#, Ramesh A. Shivdasani#
    Genes and Development 28, 1827–1839 (2014)

  23. NOTCH1-RBPJ complexes drive target gene expression through dynamic interactions with superenhancers
    Hongfang Wang*, Chongzhi Zang*, Len Taing, Kelly Arnett, Yinling Joey Wong, Warren S. Pear, Stephen C. Blacklow, X. Shirley Liu#, Jon C. Aster#
    Proceedings of the National Academy of Sciences USA 111, 715–710 (2014)

  24. Refined DNase-seq protocol and data analysis reveals intrinsic bias in transcription factor footprint identification
    Housheng Hansen He*, Clifford A. Meyer*, Sheng’en Shawn Hu*, Mei-Wei Chen, Chongzhi Zang, Yin Liu, Prakash K. Rao, Teng Fei, Han Xu, Henry Long#, X. Shirley Liu#, Myles Brown#
    Nature Methods 11, 73–78 (2014)

  25. PTIP promotes chromatin changes critical for immunoglobulin switch recombination
    Jeremy A. Daniel, Margarida A. Santos*, Zhibin Wang*, Chongzhi Zang*, Mila Jankovic, Anna Gazumyan, Kristopher R. Schwab, Arito Yamane, Darius Filsuf, Young-Wook Cho, Kai Ge, Weiqun Peng, Michel C. Nussenzweig, Rafael Casellas, Gregory R. Dressler, Keji Zhao, André Nussenzweig
    Science 329, 917–923 (2010)

  26. Genome-wide mapping of HATs and HDACs reveals distinct functions in active and inactive genes
    Zhibin Wang*, Chongzhi Zang*, Kairong Cui*, Dustin E. Schones, Artem Barski, Weiqun Peng, Keji Zhao
    Cell 138, 1019–1031 (2009)

  27. A clustering approach for identification of enriched domains from histone modification ChIP-Seq data
    Chongzhi Zang, Dustin E. Schones, Chen Zeng, Kairong Cui, Keji Zhao, Weiqun Peng
    Bioinformatics 25, 1952–1958 (2009)

  28. H3.3/H2A.Z double variant-containing nucleosomes mark ‘nucleosome-free regions’ of active promoters and other regulatory regions
    Chunyuan Jin*, Chongzhi Zang*, Gang Wei, Kairong Cui, Weiqun Peng, Keji Zhao#, Gary Felsenfeld#
    Nature Genetics 41, 941–945 (2009)

  29. Global mapping of H3K4me3 and H3K27me3 reveals specificity and plasticity in lineage fate determination of differentiating CD4+ T cells
    Gang Wei*, Lai Wei*, Jinfang Zhu, Chongzhi Zang, Jane Hu-Li, Zhengju Yao, Kairong Cui, Yuka Kanno, Tae-Young Roh, Wendy Watford, Dustin E. Schones, Weiqun Peng, Hong-wei Sun, William E. Paul, John J. O’Shea#, Keji Zhao#
    Immunity 30, 155–167 (2009)

  30. Chromatin signatures in multipotent hematopoietic stem cells indicate the fate of bivalent genes during differentiation
    Kairong Cui*, Chongzhi Zang*, Tae-Young Roh, Dustin E. Schones, Richard W. Childs, Weiqun Peng, Keji Zhao
    Cell Stem Cell 4, 80–93 (2009)

  31. Combinatorial patterns of histone acetylations and methylations in the human genome
    Zhibin Wang*, Chongzhi Zang*, Jeffrey A. Rosenfeld*, Dustin E. Schones, Artem Barski, Suresh Cuddapah, Kairong Cui, Tae-Young Roh, Weiqun Peng, Michael Q. Zhang, Keji Zhao
    Nature Genetics 40, 897–903 (2008)

  32. Fluorescence measurement and acoustic diagnostics of plasma channels in air
    Zuo-Qiang Hao, Jie Zhang#, Jin Yu, Zhe Zhang, Jia-Yong Zhong, Chong-Zhi Zang, Zhan Jin, Zhao-Hua Wang, Zhi-Yi Wei
    Acta Physica Sinica 55, 299–303 (2006)


Software


Honors and Awards


Recruiting

My lab is recruiting motivated young students and scholars to work on a variety of topics in computational biology in a collaborative research team. Postdocs, graduate students, and undergraduate students are all welcome. Please contact me for any questions.

Prospective postdocs can find the job details and submit applications here.



"While the art of printing is left to us science can never be retrograde; what is once acquired of real knowledge can never be lost."

—Thomas Jefferson, 1799



Last modified: May 31, 2022