We are recruiting audacious postdocs to rejuvenate the aging brain. We aim to transform the diagnoses and develop cures for Alzheimer’s disease. Our approach is to iteratively improve interpretable artificial intelligence (AI), technology, big data generation, and experimental and clinical validations. We are recruiting bioinformatics postdocs to develop interpretable AI and neuroscience postdocs to evaluate AI-identified candidate routes.
We welcome bold minds who will innovate in genomic technologies, including spatial, single-cell, and extracellular transcriptomics. We are interested in revealing novel RNA types and functions. Our favorite application areas include blood vasculature in diverse tissues and diseases, liquid biopsy-based diagnoses, and mechanisms of neurodegeneration and aging. Ph.D.s in genomics, bioinformatics, molecular biology, and neuroscience are most welcome.
Sheng Zhong is a Professor of Bioengineering at UC San Diego. He received an NIH Director's Pioneer Award, an NIH Catalyst Award in Diabetes, Endocrinology and Metabolic Diseases, an NIH Director's New Innovator Award, an NSF CAREER Award, and an Alfred Sloan Fellowship. He serves as the director for UCSD Center for Liquid Biopsy Research and the organizational hub of the NIH funded 4D Nucleome (4DN) Network. He leads a Human Cell Atlas (HCA) seed network and a Transformative Technology Development team for the Human BioMolecular Atlas Program (HuBMAP). Eight of his previous trainees are contributing to science on tenure-track faculty positions.
Our lab invented PROPER-seq (Protein-protein interaction by sequencing) to massively reveal protein-protein interactions (Molecular Cell, 2021). We also invented the MARIO (Mapping RNA interactome in vivo) technology to massively reveal RNA-RNA interactions from human tissue (Nat Comm, 2016) and the MARGI (Mapping RNA-Genome Interactions) technology for revealing thousands of chromatin-associated RNAs (caRNA) and their respective genomic interaction sites (Current Biology, 2017; Nature Protocols, 2019). Leveraging MARGI, we and our collaborators characterized caRNA’s roles in 3D organization of the nucleus (bioRxiv, 2021), modulation of gene expression during progression of diabetes mellitus in blood vessel endothelium (Nat Comm, 2020), and the biogenesis of fusion RNAs (PNAS 2019a). These results inspired the idea that caRNA is a layer of the epigenome (Trends Genetics, 2018).
We developed SILVER-seq for extracellular RNA (exRNA) sequencing from ultra-small volumes of liquid biopsy, solidifying a basis for future in vitro diagnostic trials using finger-prick blood for monitoring cancer recurrence (PNAS, 2019b). We identified and validated an exRNA biomarker that can predict the symptoms of late-onset Alzheimer's disease (Current Biology, 2020; Cell Metabolism, 2022).
We contributed to discovering the nuclear-encoded RNAs that are stably attached to the cell surface and exposed to the extracellular space, called membrane-associated extracellular RNAs (maxRNAs). maxRNAs are functional components of the cell surface and mediate cell-cell interactions (Genome Biology, 2020).
We contributed to discovering that the earliest cell fate decision in mouse is made sooner than the commonly thought 8-cell stage (Genome Res, 2014). Our Rainbow-seq technology combined tracing of cell division history and single-cell RNA sequencing into one experiment (iScience 2018b).
We contributed to revealing that transposons are indispensable regulatory sequences in the mammalian genomes. Species-specific transposons are required for preimplantation embryonic development in humans and other mammals (Genome Res, 2010). Nature highlighted this discovery as "Hidden Differences," reporting that "transposons or 'jumping genes' had hopped in front of the genes, changing their regulation" (Nature, 2010). We contributed to establishing the proof-of-principle that cis-regulatory sequences can be annotated by cross-species epigenomic comparison (Cell, 2012).
Our projects contribute to the Human Cell Atlas (HCA), the Human BioMolecular Altas (HuBMAP), the 4D Nucleome (4DN) program, diabetes research, and Alzheimer's research.
Spatial transcriptomics methods allow for sequencing RNA from human tissue while registering the spatial locations of every sequenced RNA in the original tissue. This project will develop next generation spatial transcriptomics tools that will significantly improve the spatial resolution and the size of the tissue that can be analyzed. We will develop extremely high-resolution, high-density, high-fidelity and reproducible spatial mapping slides (HiFi slides) for spatial transcriptome analysis.
This project will develop a genomic technology that can reveal all drug-protein interactions between a small molecule library and a protein library. This technology is expected to transform the current practices of identification of drug screening by 1000-fold increase of efficiency.
Develop interpretable AI for AD diagnosis based on big data of aging brain and blood plasma, including brain (single-nucleus) transcriptomes, epigenomics, imaging, blood extracellular RNA, cfDNA sequencing.
Powell-Focht Bioengineering Hall 371, University of California San Diego, 9500 Gilman Drive, MC 0412, La Jolla, CA 92093-0412
Lab Phone: (858) 822-5649