Xiangmeng (Shawn) Cai

All Publications

• Rewriting regulatory DNA to dissect and reprogram gene expression. Cell Martyn, G. E., Montgomery, M. T., Jones, H., Guo, K., Doughty, B. R., Linder, J., Bisht, D., Xia, F., Cai, X. S., Chen, Z., Cochran, K., Lawrence, K. A., Munson, G., Pampari, A., Fulco, C. P., Sahni, N., Kelley, D. R., Lander, E. S., Kundaje, A., Engreitz, J. M. 2025

  Abstract

  Regulatory DNA provides a platform for transcription factor binding to encode cell-type-specific patterns of gene expression. However, the effects and programmability of regulatory DNA sequences remain difficult to map or predict. Here, we develop variant effects from flow-sorting experiments with CRISPR targeting screens (Variant-EFFECTS) to introduce hundreds of designed edits to endogenous regulatory DNA and quantify their effects on gene expression. We systematically dissect and reprogram 3 regulatory elements for 2 genes in 2 cell types. These data reveal endogenous binding sites with effects specific to genomic context, transcription factor motifs with cell-type-specific activities, and limitations of computational models for predicting the effect sizes of variants. We identify small edits that can tune gene expression over a large dynamic range, suggesting new possibilities for prime-editing-based therapeutics targeting regulatory DNA. Variant-EFFECTS provides a generalizable tool to dissect regulatory DNA and to identify genome editing reagents that tune gene expression in an endogenous context.

  View details for DOI 10.1016/j.cell.2025.03.034

  View details for PubMedID 40245860

• Deciphering the impact of genomic variation on function. Nature 2024; 633 (8028): 47-57

  Abstract

  Our genomes influence nearly every aspect of human biology-from molecular and cellular functions to phenotypes in health and disease. Studying the differences in DNA sequence between individuals (genomic variation) could reveal previously unknown mechanisms of human biology, uncover the basis of genetic predispositions to diseases, and guide the development of new diagnostic tools and therapeutic agents. Yet, understanding how genomic variation alters genome function to influence phenotype has proved challenging. To unlock these insights, we need a systematic and comprehensive catalogue of genome function and the molecular and cellular effects of genomic variants. Towards this goal, the Impact of Genomic Variation on Function (IGVF) Consortium will combine approaches in single-cell mapping, genomic perturbations and predictive modelling to investigate the relationships among genomic variation, genome function and phenotypes. IGVF will create maps across hundreds of cell types and states describing how coding variants alter protein activity, how noncoding variants change the regulation of gene expression, and how such effects connect through gene-regulatory and protein-interaction networks. These experimental data, computational predictions and accompanying standards and pipelines will be integrated into an open resource that will catalyse community efforts to explore how our genomes influence biology and disease across populations.

  View details for DOI 10.1038/s41586-024-07510-0

  View details for PubMedID 39232149

  View details for PubMedCentralID 7405896

• High-throughput discovery of regulatory effector domains in human RNA-binding proteins. bioRxiv : the preprint server for biology Thurm, A. R., Finkel, Y., Andrews, C., Cai, X. S., Benko, C., Bintu, L. 2024

  Abstract

  RNA regulation plays an integral role in tuning gene expression and is controlled by thousands of RNA-binding proteins (RBPs). We develop and use a high-throughput recruitment assay (HT-RNA-Recruit) to identify regulatory domains within human RBPs by recruiting over 30,000 protein tiles from 367 RBPs to a reporter mRNA. We discover over 100 unique RNA-regulatory effectors in 86 distinct RBPs, presenting evidence that RBPs contain functionally separable domains that dictate their post-transcriptional control of gene expression, and identify some with unique activity at 5' or 3'UTRs. We identify some domains that downregulate gene expression both when recruited to DNA and RNA, and dissect their mechanisms of regulation. Finally, we build a synthetic RNA regulator that can stably maintain gene expression at desired levels that are predictable by a mathematical model. This work serves as a resource for human RNA-regulatory effectors and expands the synthetic repertoire of RNA-based genetic control tools.Highlights: HT-RNA-Recruit identifies hundreds of RNA-regulatory effectors in human proteins.Recruitment to 5' and 3' UTRs identifies regulatory domains unique to each position.Some protein domains have both transcriptional and post-transcriptional regulatory activity.We develop a synthetic RNA regulator and a mathematical model to describe its behavior.

  View details for DOI 10.1101/2024.07.19.604317

  View details for PubMedID 39071298

• Computation empowers CRISPR discovery and technology. Nature computational science Shang, S., Cai, X. S., Qi, L. S. 2022; 2 (9): 533-535

  View details for DOI 10.1038/s43588-022-00321-1

  View details for PubMedID 38177471