Research

The research focus of our lab is on developing and applying computational and experimental multi-omic methods to understand the gene regulation of non-coding genetic variants. Specifically, we would like to utilize multi-dimensional epigenomics signals within the same single cells and that from circulating cell-free DNA (outside cells) to dissect the functional roles of non-coding regulatory elements and therefore bridge the gaps between genetic variations and phenotypic variations at different physiological and pathological conditions.

Current Projects

Non-invasive monitor the in vivo epigenomes by circulating cell-free DNA

Circulating cell-free DNA (cfDNA) is released into the peripheral blood after cellular death and recycled every few mins up to 12 hours. The collection of cfDNA fragments represents a real-time in vivo snapshot of the genome from cells that contribute to cfDNA. CfDNA is not randomly fragmented into small pieces and recently associated with the cellular epigenomes, suggesting the possibility of computationally inferring the cellular epigenomes from cfDNA fragmentation. However, the computational tools are still not available to comprehensively infer the cellular epigenomes from cfDNA whole-genome sequencing (WGS). Millions of low-coverage and high-coverage cfDNA WGS are generated every year. Given the potential to leverage these cfDNA WGS datasets to advance the understanding of the epigenomes and thus the function of non-coding regulatory elements, we are developing a set of computational methods to reconstruct the multi-dimensional epigenomes from a single cfDNA WGS.

Develop methods to jointly profile multi-omics in the same single cells

Epigenetic modifications, including DNA methylation, histone modifications, and three-dimensional (3D) genome topology, combine with genetic content to determine the mammalian transcriptional factor (TF) binding and, thus, gene regulation. Gene activation or repression potential, however, cannot be entirely predicted by looking at a single molecular measurement. Accurate predictive models require multiple molecular measurements simultaneously. At present, we are limited by the number of simultaneous measurements that we can perform in a single cell. In addition, the interactions between different epigenetic marks and their effects on gene expression are currently studied either in homogenous cultured cells or bulk tissues that average the readout. The study of interactions between different cell-type-specific epigenetic marks and gene expression in heterogeneous tissues at the single cell level is still in its infancy. We and others developed several technologies to simultaneously capture multiple molecular measurements in the same assay or single-cells. We continue to develope more high-throughput mutli-omic technologies to comprehensively dissect the regulatory roles of the non-coding regulatory elements in the genome.

Epigenomics in liquid biopsy for the early diagnosis and prognosis of diseases

Routine screening in the average-risk population provides the opportunity to detect cancer early and significantly reduce morbidity and mortality in cancer. Early identification of lethal cancer versus non-lethal diseases will minimize overdiagnosis. Both medical needs require non-invasive biomarkers with ultra-high specificity (>99%) and high sensitivity at the same time, which, however, are still not available in the clinic. Recent advances in circulating cell-free DNA (cfDNA) suggested a promising non-invasive approach for cancer diagnosis and prognosis by using the tumor-specific genetic and epigenetic alterations. However, there is still a huge gap to limit its clinical application for cancer screening. We are utilizing the epigenomic signals from circulating cfDNA for the early diagnosis and prognosis of cancers. Moreover, we are expanding the studies in cancer to many other complex diseases.

Funding

Our work is currently (and was previously) supported by NIH (R35GM147283, R56HG012360, R01HG011411), NSF (XSEDE Resource Allocation Service), Bill & Melinda Gates Foundation (MOMI Ideas Award), The Center for Clinical and Translational Science and Training (Mentored Pilot Translational Award), and Cincinnati Children’s Research Foundation (Innovation Fund, Trustee Award, Center for Pediatric Genomics Award, and Yaping Liu’s start-up).