Siyuan (Steven) Wang received a Bachelor of Science degree in Physics from Peking University in 2007, a Ph. D. in Molecular Biology from Princeton University in 2011, and his postdoctoral training at Harvard University. He joined Yale in late 2017 and currently serves as an Associate Professor in the Department of Genetics and the Department of Cell Biology, Yale School of Medicine, Yale University. He is a recipient of the 2011 American Physical Society Award for Outstanding Doctoral Thesis Research in Biological Physics (1-2 recipients per year worldwide), the 2012-2015 Jane Coffin Childs Fellowship, the 2016 International Union of Pure and Applied Physics Young Scientist Prize in Biological Physics (one recipient per year worldwide), the 2017 Harvard Chinese Life Sciences Distinguished Research Award, the 2018 35 Innovators Under 35 of China by MIT Technology Review, the 2019-2024 NIH Director’s New Innovator Award, the 2022 Pershing Square Sohn Prize for Young Investigators in Cancer Research, and the 2023 Biophysical Society Early Career Award in Physical Cell Biology.

Image-based 3D genomics and spatial multi-omics

At Harvard: Wang’s research interest is to understand the spatiotemporal complexity of molecular and cellular systems, and how the complexity affects biological functions. Especially, he aims to understand the spatial organization of mammalian chromatin – the complex of genomic DNA and associated proteins. The spatial organization of chromatin in the nucleus is of critical importance to many essential genomic functions, from the regulation of gene expression to the replication of the genome. Unfortunately, relatively little is known about the three-dimensional (3D) organization of chromatin beyond the length scale of the nucleosomes, in large part due to the lack of tools that allow direct visualization of the 3D folding of chromatin in individual chromosomes. To address this need, his main postdoctoral work (Science 2016) involved the development of a first-in-kind image-based 3D genomics method termed “chromatin tracing“, via multiplexed DNA fluorescence in situ hybridization (multiplexed DNA FISH). This novel method enabled direct spatial tracing of numerous genomic regions in individual chromosomes in single cells, offering a powerful tool to study the 3D folding of chromatin. As the first application of this method, he studied the spatial organization of the recently discovered topologically associating domains (TADs), also termed contact domains, by tracing the 3D positions of TADs in individual chromosomes in interphase human cells, and revealed a series of unexpected structural features. This work opened up many opportunities to study the spatial organization of chromatin at different length scales in a variety of important biological processes and in diseases. He also co-developed a highly-multiplexed RNA FISH technique termed “MERFISH” that enabled localized detection and quantification of 1000 different RNA species in a single cell (Science 2015). In comparison to single-cell RNA sequencing, this multiplexed FISH method easily retains the spatial information of all the probed transcripts, and is highly sensitive for counting low-copy-number transcripts. Additionally, he led the development of a new photoactivatable fluorescent protein (PAFP), named mMaple3 (PNAS 2014), that outperforms previously existing PAFPs in single-molecule-based superresolution imaging (STORM/PALM) and has been adopted by hundreds of research labs around the world, and an RNA-aptamer-based two-color CRISPR labeling system for studying chromatin dynamics (Scientific Reports 2016).

At Yale: Wang’s independent lab at Yale is devoted to understand mammalian genome architectures and spatial transcriptome in health and disease. In the past few years, the lab introduced a new integrative technique, termed Multiplexed Imaging of Nucleome Architectures (MINA) – the first comprehensive 3D nucleomic imaging technique (bioRxiv 2019; Nat Comm 2020; Nat Protoc 2021). This method enabled multi-omic and multiscale visualization of single-cell nucleome architectures and gene expression to functionally define promoter-enhancer interactions, chromatin domains, compartments, territories, and chromatin interactions with nuclear landmarks in the same single cells of complex mammalian tissues, generating true 3D maps of all major chromatin architectures reported by various sequencing methods (P-E loops, TADs, LADs, NADs, A-B compartments, and chromosome territories). In applying the technique to mouse fetal liver, the team discovered cell-type-specific chromatin architectures associated with gene expression, chromatin organization principles independent of cell type, novel cell-cell interaction patterns, and underlying signalling mechanisms (bioRxiv 2019; Nat Comm 2020; Cell Discov 2021). They also applied chromatin tracing to study 3D chromatin changes in early C. elegans embryos (Molecular Cell 2020), and to elucidate novel architectures and their regulation in the folding conformations of the two copies of X chromosomes in female human cells (Genome Biology 2021; Science Advances 2023). Overall, the chromatin tracing and MINA technologies have revolutionized 3D genomics and multi-omics studies (Trends in Cell Biology “Best of 2021”).

Most recently, the team resolved the first single-cell 3D genome atlas of any cancer with genome-wide chromatin tracing, and identified an unexpected 3D genome bottleneck during subclonal lung tumor evolution in the native tissue microenvironment. They further defined key regulator and effector genes upstream and downstream of substantial 3D genome reorganization that drives histologic progression. This work, for the first time, charted a comprehensive blueprint of 3D genome alterations during cancer progression in the native tissue context and systematically revealed functional mechanisms of cancer evolution embedded in the rich information of single-cell 3D chromatin conformations (bioRxiv 2023a). It is expected that applying this approach broadly will have an enormous impact on understanding the epigenetic basis of cancer in situ and will lead to the development of novel diagnostic, prognostic, and therapeutic biomarkers based on the 3D genome. In another recent work, to systematically discover novel regulators of 3D genome, the team developed the first ultra-high-content, high-throughput, 3D genome regulator screening technology (bioRxiv 2023b). This development uniquely integrated real-3D genomics by chromatin tracing, pooled CRISPR screen, and a novel cellular barcoding and in situ decoding technique (BARC-FISH). It enabled efficient discovery of regulators of 3D genome architectures across a wide range of length scales and laid the foundation for a complete mapping of the 3D genomic regulatome, which may lead to a new avenue of therapeutics by halting or reversing the deleterious 3D genome reorganization in aging and diseases.

Earlier research

As a graduate student at Princeton University, Wang studied bacterial cell mechanics, especially how the bacterial cytoskeleton coordinates cell wall synthesis. The first project (PNAS 2010) in his dissertation showed that the bacterial actin homologue MreB contributes nearly as much to the rigidity of an E. coli cell as the peptidoglycan cell wall. This conclusion provided the premise for several theoretical works that assumed MreB applies force to the cell wall during growth, and suggested an evolutionary origin of cytoskeleton-governed cell rigidity. His second project (PNAS 2011) dealt with the discovery of the motion of E. coli MreB linked to cell wall synthesis. This was the first observation of a cell-wall assembly driven molecular motor in bacteria. (Simultaneously with the work, Garner et al and Dominguez-Escobar et al discovered the same phenomenon in B. subtilis.) His third project (PNAS 2012) elucidated that both cell wall synthesis and the peptidoglycan network have a chiral ordering, which is established by MreB. This work linked the molecular structures of the cytoskeleton and of the cell wall with organismal-scale behavior. His fourth project (Biophysical Journal 2013) developed a generic, quantitative model to explain the various spatial patterns adopted by bacterial cytoskeletal proteins. The model set up a new theoretical framework for the study of membrane-polymer interaction, and is useful for the exploration of the physical limits of cytoskeleton organization.