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Zhipeng Lu, PhD - USC School of Pharmacy. Los Angeles, CA, US

Zhipeng Lu, PhD Zhipeng Lu, PhD

Assistant Professor of Pharmacology and Pharmaceutical Sciences | USC School of Pharmacy

Los Angeles, CA, UNITED STATES

An expert in RNA structures and interactions, chemical tools for RNA, RNA in genetic and infectious diseases, and
computational biology.

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Get an Eye-full (Eiffel)/Cell, May 12, 2016 (Vol. 165, Issue 5)

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Biography

Dr. Lu received his B.S. in Biology from Fudan University in 2008. He earned his Ph.D. in Biology with Professor Greg Matera at UNC Chapel Hill in 2014. During his PhD work, Dr. Lu discovered novel RNA-protein interactions and new forms of circular RNAs. Dr. Lu conducted postdoctoral training with Professor Howard Y. Chang at Stanford University from 2014 to 2018. His postdoctoral work established a general strategy to determine RNA secondary structures and interactions in living cells.

Dr. Lu’s work on noncoding RNA structures led to the discovery of drug target that has been employed to develop drugs to treat X-linked genetic diseases. His work was featured on the cover of Cell, on the cover of Best of Cell 2016.

Dr. Lu joined the faculty in the Department of Pharmacology and Pharmaceutical Sciences at USC School of Pharmacy as an Assistant Professor in 2018. Dr. Lu’s research contributions have been recognized by several awards, including the Damon Runyon-Sohn Pediatric Cancer Award (Layton Family Fellow), Stanford’s Jump Start Award for Excellence in Research, RNA Society Scaringe Award, and NIH Pathway to Independence Award (K99 /R00, NHGRI)

Areas of Expertise (4)

Computational Biology

Chemical tools for RNA

RNA structures and interactions

RNA in genetic and infectious diseases

Accomplishments (2)

Damon Runyon-Sohn Pediatric Cancer Award

Layton Family Fellow

Stanford’s Jump Start Award

Excellence in Research

Education (3)

Stanford University: Postdoctoral Studies, Biology 2018

UNC Chapel Hill: Ph.D., Biology 2014

Fudan University: B.S., Biology 2008

Research Grants (3)

Decoding the RNA Structurome: Method Development and Function Analysis

NIH/NHGRI R00HG009662 

Dec 17, 2018 - Nov 30, 2021
Role: Principal Investigator

Keck Genomics Partnership Award

USC 

Aug 1, 2019 - July 31, 2020
Role: Principal Investigator

Decoding the RNA Structurome: Method Development and Function Analysis

NIH/NHGRI K99HG009662 

Aug 15, 2017 - May 31, 2019
Role: Principal Investigator

Selected Articles (5)

Modeling microcephaly with cerebral organoids reveals a WDR62–CEP170–KIF2A pathway promoting cilium disassembly in neural progenitors Nature Communications

Wei Zhang, Si-Lu Yang, Mei Yang, Stephanie Herrlinger, Qiang Shao, John L Collar, Edgar Fierro, Yanhong Shi, Aimin Liu, Hui Lu, Bruce E Herring, Ming-Lei Guo, Shilpa Buch, Zhen Zhao, Jian Xu, Zhipeng Lu, Jian-Fu Chen

2019

Primary microcephaly is caused by mutations in genes encoding centrosomal proteins including WDR62 and KIF2A. However, mechanisms underlying human microcephaly remain elusive. By creating mutant mice and human cerebral organoids, here we found that WDR62 deletion resulted in a reduction in the size of mouse brains and organoids due to the disruption of neural progenitor cells (NPCs), including outer radial glia (oRG). WDR62 ablation led to retarded cilium disassembly, long cilium, and delayed cell cycle progression leading to decreased proliferation and premature differentiation of NPCs. Mechanistically, WDR62 interacts with and promotes CEP170’s localization to the basal body of primary cilium, where CEP170 recruits microtubule-depolymerizing factor KIF2A to disassemble cilium. WDR62 depletion reduced KIF2A’s basal body localization, and enhanced KIF2A expression partially rescued deficits in cilium length and NPC proliferation. Thus, modeling microcephaly with cerebral organoids and mice reveals a WDR62-CEP170-KIF2A pathway promoting cilium disassembly, disruption of which contributes to microcephaly.

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Cross-linked RNA Secondary Structure Analysis using Network Techniques bioRxiv

Irena Fischer-Hwang, Zhipeng Lu, James Zou, Tsachy Weissman

2019

Next generation sequencing and biochemical cross-linking methods have been combined into powerful tools to probe RNA secondary structure. One such method, known as PARIS, has been used to produce near base-pair maps of long-range and alternative RNA structures in living cells. However, the procedure for generating these maps typically relies on laborious manual analysis. We developed an automated method for producing RNA secondary structure maps using network analysis techniques. We produced an analysis pipeline, dubbed cross-linked RNA secondary structure analysis using network techniques (CRSSANT), which automates the grouping of gapped RNA sequencing reads produced using the PARIS assay, and tests the validity of secondary structures implied by the groups. We validated the clusters and secondary structures produced by CRSSANT using manually-produced grouping maps and known secondary structures. We implemented CRSSANT in Python using the network analysis package NetworkX and RNA folding software package ViennaRNA. CRSSANT is fast and efficient, and is available as Python source code at https://github.com/ihwang/CRSSANT.

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RISE: a database of RNA interactome from sequencing experiments Nucleic acids research

Jing Gong, Di Shao, Kui Xu, Zhipeng Lu, Zhi John Lu, Yucheng T Yang, Qiangfeng Cliff Zhang

2017

We present RISE (http://rise.zhanglab.net), a database of RNA Interactome from Sequencing Experiments. RNA-RNA interactions (RRIs) are essential for RNA regulation and function. RISE provides a comprehensive collection of RRIs that mainly come from recent transcriptome-wide sequencing-based experiments like PARIS, SPLASH, LIGR-seq, and MARIO, as well as targeted studies like RIA-seq, RAP-RNA and CLASH. It also includes interactions aggregated from other primary databases and publications. The RISE database currently contains 328,811 RNA-RNA interactions mainly in human, mouse and yeast. While most existing RNA databases mainly contain interactions of miRNA targeting, notably, more than half of the RRIs in RISE are among mRNA and long non-coding RNAs. We compared different RRI datasets in RISE and found limited overlaps in interactions resolved by different techniques and in different cell lines. It may suggest technology preference and also dynamic natures of RRIs. We also analyzed the basic features of the human and mouse RRI networks and found that they tend to be scale-free, small-world, hierarchical and modular. The analysis may nominate important RNAs or RRIs for further investigation. Finally, RISE provides a Circos plot and several table views for integrative visualization, with extensive molecular and functional annotations to facilitate exploration of biological functions for any RRI of interest.

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Mechanistic insights in X-chromosome inactivation Philosophical Transactions of the Royal Society B: Biological Sciences

Zhipeng Lu, Ava C Carter, Howard Y Chang

2017

X-chromosome inactivation (XCI) is a critical epigenetic mechanism for balancing gene dosage between XY males and XX females in eutherian mammals. A long non-coding RNA (lncRNA), XIST, and its associated proteins orchestrate this multi-step process, resulting in the inheritable silencing of one of the two X-chromosomes in females. The XIST RNA is large and complex, exemplifying the unique challenges associated with the structural and functional analysis of lncRNAs. Recent technological advances in the analysis of macromolecular structure and interactions have enabled us to systematically dissect the XIST ribonucleoprotein complex, which is larger than the ribosome, and its place of action, the inactive X-chromosome. These studies shed light on key mechanisms of XCI, such as XIST coating of the X-chromosome, recruitment of DNA, RNA and histone modification enzymes, and compaction and compartmentalization of the inactive X. Here, we summarize recent studies on XCI, highlight the critical contributions of new technologies and propose a unifying model for XIST function in XCI where modular domains serve as the structural and functional units in both lncRNA–protein complexes and DNA–protein complexes in chromatin.

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RNA Duplex Map in Living Cells Reveals Higher-Order Transcriptome Structure Cell

Zhipeng Lu, Qiangfeng Cliff Zhang, Byron Lee, Ryan A Flynn, Martin A Smith, James T Robinson, Chen Davidovich, Anne R Gooding, Karen J Goodrich, John S Mattick, Jill P Mesirov, Thomas R Cech, Howard Y Chang

2016

RNA has the intrinsic property to base pair, forming complex structures fundamental to its diverse functions. Here, we develop PARIS, a method based on reversible psoralen crosslinking for global mapping of RNA duplexes with near base-pair resolution in living cells. PARIS analysis in three human and mouse cell types reveals frequent long-range structures, higher-order architectures, and RNA-RNA interactions in trans across the transcriptome. PARIS determines base-pairing interactions on an individual-molecule level, revealing pervasive alternative conformations. We used PARIS-determined helices to guide phylogenetic analysis of RNA structures and discovered conserved long-range and alternative structures. XIST, a long noncoding RNA (lncRNA) essential for X chromosome inactivation, folds into evolutionarily conserved RNA structural domains that span many kilobases. XIST A-repeat forms complex inter-repeat duplexes that nucleate higher-order assembly of the key epigenetic silencing protein SPEN. PARIS is a generally applicable and versatile method that provides novel insights into the RNA structurome and interactome.

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