Christopher Lee

Laboratory Address:
Paul Boyer Hall 609

Work Address:
Paul Boyer Hall 601A

Professor, Chemistry and Biochemistry, Biochemistry, Molecular Biology
Member, Bioinformatics GPB Home Area, Graduate Program in Biochemistry, Molecular and Structural Biology, Molecular Biology Institute
Researcher, Biochemistry, Biophysics and Structural Biology, Proteomics and Bioinformatics
Research Interests
My lab works in several areas of bioinformatics: 1. alternative splicing and genome evolution: alternative splicing is the process by which a single gene can produce multiple gene products with different specific functions (by controlling which exons are spliced into the final product). My lab has done both a lot of genome-wide analysis of the types and functions of alternative splicing, and its apparent role in evolution of mammalian genomes. Alternative splicing appears to have greatly accelerated major evolutionary events such as exon creation, and now is an exciting new area of research in genome evolution. 2. protein evolutionary pathways. Using a massive dataset of clinical HIV sequences, we have developed new methods to decode the evolutionary pathways by which HIV evolves drug resistance -- a major clinical problem for the treatment of AIDS. We have just shown that our methods can measure the detailed "fitness landscape" describing how HIV proteins can evolve, as a kinetic network showing the actual rate of evolution along every possible evolutionary pathway. This work is aimed at both a new level of understanding of pathogen evolution, and the ability to predict the detailed evolutionary pathways that lead to drug resistance. 3. graph databases for bioinformatics and genomics. Graph structures are becoming increasingly important and universal in bioinformatics, as a flexible way of describing and querying genomic data. We have developed a general framework for working with genomic data as an abstract graph database, with very high performance for fundamental problems such as multiple genome alignment query and protein interaction network analysis. These problems also pose interesting computer science questions. For more information see Focus on Alternative splicing: Annotation of the human genome by gene prediction methods has turned out to be very error-prone; fortunately, there is abundant experimental data that we can use instead. In particular, high-throughput shotgun sequencing of mRNA fragments (Expressed Sequence Tags, or ESTs) provides a massive dataset for seeing exactly what?s expressed, discovering gene structures, and identifying alternative splice forms. Whereas alternative splicing was previously considered to be a relatively rare form of functional regulation (perhaps present in 5 - 15% of genes), EST analyses have indicated that it is ubiquitous, observable in 40-60% of human genes. Using this combination of experimental data and bioinformatics methods, our lab has identified over 30,000 alternative splicing events in the human genome (effectively doubling the number of transcript forms relative to the consensus estimate of approximately 32,000 human genes). These data are used by researchers around the world via our online ASAP database ( These data provide many fascinating windows into the regulation of biological function, when careful statistics are employed to assess the significance of apparent patterns and shifts in alternative splicing within the data. For example, we have identified a large subset of alternative splice forms that display strong tissue-specificity, indicating functional regulation of the transcript and protein product in an individual tissue or developmental stage. Similarly, we have identified a large set of genes whose splicing is altered dramatically in tumors relative to normal tissue, suggesting that alternative splicing may play a significant role in cancer, for example, by contributing to maintenance of the transformed state. We have also obtained very interesting results from analysis of how alternative splicing changes protein domain architecture and function. Recently, we analyzed the comparative genomics of alternative splicing by comparing alternative splicing patterns in orthologous genes from a number of vertebrate genomes. Surprisingly, whereas 98% of exons from the human genome are also found in the orthologous mouse and rat genes, alternatively spliced exons showed a 30-fold increase in newly created exons (that is, exons that were found in the human genome but not mouse, indicating that they were created subsequent to the split of these two genomes from their common ancestor). These data suggest that alternative splicing may play an important role in accelerating gene evolution by enabling much more rapid exon creation than is possible without alternative splicing. Our lab is looking at many aspects of the comparative genomics of alternative splicing and its role in genome evolution.

Prof. Lee has been a Faculty member in the Department of Chemistry and Biochemistry since 1998. His training provided an unusual combination of experimental cell biology, biophysics, and algorithm development, which he has has applied at UCLA to bioinformatics analysis of genome evolution. He has led efforts to establish a bioinformatics Ph.D. program at UCLA. He has served on the Board of Scientific Counselors, NIH National Center for Biotechnology Information, and serves on the editorial board of Biology Direct. His current research focuses on alternative splicing and its role in genome evolution.

Lee Christopher Open peer review by a selected-papers network. Frontiers in computational neuroscience. 2012; 6(12): 1.
Lu Hongchao, Lin Lan, Sato Seiko, Xing Yi, Lee Christopher J Predicting functional alternative splicing by measuring RNA selection pressure from multigenome alignments. PLoS computational biology. 2009; 5(12): e1000608.
Wang Qi, Barr Ian, Guo Feng, Lee Christopher Evidence of a novel RNA secondary structure in the coding region of HIV-1 pol gene. RNA (New York, N.Y.). 2008; 14(12): 2478-88.
Roy Meenakshi, Kim Namshin, Xing Yi, Lee Christopher The effect of intron length on exon creation ratios during the evolution of mammalian genomes. RNA (New York, N.Y.). 2008; 14(11): 2261-73.
Parker Douglass Stott, Hsiao Ruey-Lung, Xing Yi, Resch Alissa M, Lee Christopher J Solving the problem of Trans-Genomic Query with alignment tables. IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM. 2008; 5(3): 432-47.
Kim Namshin, Lee Christopher Bioinformatics detection of alternative splicing. Methods Mol. Biol. 2008; 452(1): 179-97.
Wang Qi, Lee Christopher Distinguishing functional amino acid covariation from background linkage disequilibrium in HIV protease and reverse transcriptase. PLoS ONE. 2007; 2(8): e814.
Kim Namshin, Lee Christopher QPRIMER: a quick web-based application for designing conserved PCR primers from multigenome alignments. Bioinformatics. 2007; 23(17): 2331-3.
Kim Namshin, Lee Christopher Three-Dimensional Phylogeny Explorer: distinguishing paralogs, lateral transfer, and violation of . BMC Bioinformatics. 2007; 8(3): 213.
Alekseyenko Alexander V, Lee Christopher J Nested Containment List (NCList): a new algorithm for accelerating interval query of genome alignment and interval databases. Bioinformatics. 2007; 23(11): 1386-93.
Alekseyenko Alexander V, Kim Namshin, Lee Christopher J Global analysis of exon creation versus loss and the role of alternative splicing in 17 vertebrate genomes. RNA. 2007; 13(5): 661-70.
Xing Yi, Lee Christopher Relating alternative splicing to proteome complexity and genome evolution. Adv. Exp. Med. Biol. 2007; 623(2): 36-49.
Kim Namshin, Alekseyenko Alexander V, Roy Meenakshi, Lee Christopher The ASAP II database: analysis and comparative genomics of alternative splicing in 15 animal species. Nucleic Acids Res. 2007; 35(Database issue): D93-8.
Pan Calvin, Kim Joseph, Chen Lamei, Wang Qi, Lee Christopher The HIV positive selection mutation database. Nucleic Acids Res. 2007; 35(Database issue): D371-5.
Xing Yi, Lee Christopher Alternative splicing and RNA selection pressure--evolutionary consequences for eukaryotic genomes. Nat. Rev. Genet. 2006; 7(7): 499-509.
Xing Yi, Yu Tianwei, Wu Ying Nian, Roy Meenakshi, Kim Joseph, Lee Christopher An expectation-maximization algorithm for probabilistic reconstructions of full-length isoforms from splice graphs. Nucleic Acids Res. 2006; 34(10): 3150-60.