assistant professor of biology
Fields of Interest
Computational biology. Gene regulation, molecular evolution, and high-throughput lipidomics.
Large scale DNA sequencing has ushered in a new era in biology. There are now hundreds of organisms in which nearly all the genomic sequence is known, making it possible to comprehensively analyze and compare species at their most atomistic genetic level. At the same time, massive phenotypic datasets, such as gene expression and lipidomic data, have become increasingly available. My lab is interested in computational and mathematical approaches to analyzing such large data sources, to understand how genomes function and evolve.
Functions of Highly Conserved Enhancer Sequences
In a given phylogeny, comparative sequence data can be used to infer the functional sequences within genomes. Just as morphological features shared among species (e.g. all vertebrates have a spine) are likely to be important to those species, DNA sequences shared among species are likely to be functional. One of the organisms we focus on is the model vertebrate Danio rerio, i.e. the zebrafish. Our lab collaborates with the Guo lab at UCSF to study conserved noncoding elements, sequences with conservation far beyond what would be expected by neutral mutation in vertebrate intergenic regions. For example, at a threshold of at least 50 bp and at least 50% sequence identity, there are 73187 strand-specific CNEs conserved between zebrafish and human. A major challenge in understanding these CNEs is to organize them in a meaningful way, analogous to the organization of genes provided by the Gene Ontology. We have recently developed a tool for organizing CNEs based on the expression of nearby genes (cneviewer.zebrafishcne.org, Persampieri et al., 2008), as this may provide a key to understanding the tissue-specific enhancer behavior of CNEs. We are also exploring the relative importance of cis- and trans- regulatory effects on the functional behavior of enhancers (Ritter et al., 2010).
Functions Contained in Coding Sequences
We are also actively exploring the functions and neutral evolutionary behavior of synonymous sites in coding sequences, as these sequences appear to contain a substantial amount of selection in a variety of phylogenies (Kural et al., 2009).
We have shown, for example, that coding sequences are replete with binding sites for microRNAs, as well as other types of functional sequences such as exonic splicing enhancers. Such sites exhibit a strong selective pressure on the synonymous sites of coding regions.
Tools for High Throughput Lipidomics
A recent lab interest has been the analysis of high-throughput lipidomic data. Our lab collaborates with the Seyfried Lab (Boston College) and the Han Lab (Washington University in St. Louis) to analyze lipid content in cancerous vs. non-cancerous tissues. Our group is developing tools to analyze which aspects of lipid content are important to cancer phenotypes (Kiebish et al., 2008). This work is closely tied to evaluating the Warburg theory of cancer, as described in this report. Another recent interest has been the analysis of the dynamics of lipid remodeling (Kiebish et al., 2010).
Other Topics in Comparative Genomics and Molecular Evolution
Other model organisms with which we have expertise are the malaria parasite Plasmodium falciparum and the yeast S. cerevisiae. A central mystery of the malaria genome is how transcription is regulated. We have observed that there is far less intergenic sequence apparently under purifying selection in malaria than in yeast genomes, suggesting that transcription regulation is simpler in malaria (Imamura, Persampieri and Chuang, 2007). We have also applied comparative techniques to identify functional sites in the promoters of the Saccharomyces genus of yeasts, to estimate the complexity of gene regulation and the types of genes likely to be under the strictest regulation (Chin, Chuang, and Li, 2005).
Our lab is also interested in a variety of issues in molecular evolution related to the balance of functional and neutral signatures in genomes. Evaluating the functional significance of sequences that are conserved is still a major challenge. One reason for this is that neutral mutation rates, which describe the evolution of non-functional DNA, are not always known. Another direction of the lab is therefore to characterize neutral mutation rates, which can vary both within and between species. For example, one puzzle is why mutation rates are uniform in some species, such as the sensu stricto yeasts, while rates vary by location in other species, such as mouse and human. We have found that all mammalian species have regional mutation rates, with regional behavior having a typical scale of several megabases. In contrast, all yeasts have uniform mutation rates, with the exception of the Candida clade. The reason the Candida clade differs is a mystery in which we are greatly interested (Fox et al., 2008; Chuang and Li, 2004; Chuang and Li, 2007; Chin, Chuang, and Li, 2005). In species where the mutation rate is non-uniform, we are interested in questions such as what structural or sequence features affect mutation rates, and whether gene locations have evolved to make use of mutational heterogeneity.
Ritter, D.I., Li, Q., Kostka, D., Pollard, K.S., Guo, S., and Chuang, J.H. 2010. The importance of being cis: Evolution of orthologous fish and mammalian enhancer activity. Molecular Biology and Evolution: May 2010 [Epub ahead of print].
Kiebish, M.A., Bell, R., Yang, K., Phan, T., Zhao, Z., Ames, W., Seyfried, T.N., Gross, R.W., Chuang, J.H., and Han, X. 2010. Dynamic simulation of cardiolipin remodeling: Greasing the wheels for an interpretative approach to lipidomics. Journal of Lipid Research: April 2010 [Epub ahead of print].
Kural, D., Ding, Y., Wu, J., Korpi, A.M., and Chuang, J. H. 2009. COMIT: Identification of noncoding motifs under selection in coding sequences. Genome Biology 10: R133.
Li, Q., Ritter, D., Yang, N., Dong, Z., Li, H., Chuang, J.H., and Guo, S. 2009. A systematic approach to identify functional motifs within vertebrate developmental enhancers. Developmental Biology 337: 484–95.
Imamura, H., Karro, J.E., and Chuang, J.H. 2009. Weak preservation of local neutral mutation rates across mammalian genomes. BMC: Evolutionary Biology 9: 89.
Kiebish, M.A., Han, X., Cheng, H., Chuang, J. H., and Seyfried, T. N. 2008. Cardiolipin and electron transport chain abnormalities in mouse brain tumor mitochondria: lipidomic evidence supporting the Warburg theory of cancer. Journal of Lipid Research 49: 2545–56.
Persampieri, J., Ritter, D. I., Lees, D., Lehoczky, J., Li, Q., Guo, S., and Chuang, Jeffrey H. 2008. cneViewer: A database of conserved noncoding elements for studies of tissue-specific gene regulation. Bioinformatics 24(20): 2418–2419.
Fox, A.K., Tuch, B.B., and Chuang, J. H. 2008. Measuring the prevalence of regional mutation rates: an analysis of silent substitutions in mammals, fungi, and insects. BMC: Evolutionary Biology 8: 186.
Kiebish, M.A., Han, X., Cheng, H., Lunford, A., Clarke, C. F., Moon, H., Chuang, J.H., and Seyfried, T.N. 2008. Lipidomic analysis and electron transport chain activities in C57BL/6J mouse brain mitochondria. Journal of Neurochemistry 106: 299–312.
Imamura, H., Persampieri, J., and Chuang, J.H. 2007. Sequences conserved by selection across mouse and human malaria species. BMC: Genomics 8: 372.
Chin, C.S., Chuang, J.H., and Li, H. 2005. Genome-wide regulatory complexity in yeast promoters: separation of functional and neutral sequence. Genome Research 15: 205.
Chuang, J., and Li, H. 2004. Functional bias and spatial organization of genes in mutational hot and cold regions in the human genome. PLoS Biology 2: 0253.