Ph.D., Massachusetts Institute of Technology
Tel: (617) 552-0804
E-mail: chuangj@bc.edu
Dr. Chuang's Lab Website
Fields of Interest
Computational biology and bioinformatics. Comparative genomics, gene regulation, molecular evolution
Academic Profile
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 whole-genome gene expression arrays, 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.
Detecting Functional Sequences in DNA through Comparative Genomics
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. Our current research is focused on two systems. The first 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.
A second system with which our lab has expertise is the malaria parasite Plasmodium falciparum. We have previously identified intergenic sequences likely to be under selective pressure based on sequence conservation (Imamura, Persampieri and Chuang, 2007). 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.
Previously, we have applied comparative techniques to identify functional sites in the promoters of the Saccharomyces genus of yeasts. Such sequence comparisons can yield predictions of not only individual DNA/protein binding sites, but also broader features, such as the complexity of gene regulation and the types of genes likely to be under the strictest regulation (Chin, Chuang, and Li, 2005).
Characterization of Neutral Mutation Rates
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. A related question is what DNA sequence should be considered neutral, and in particular what the effect of codon usage bias is on silent sites in genes.
Evolution of Transcription Factors and Their Binding Sites
Currently, only a small fraction of the binding sites for transcription factors are known, and these are mostly restricted to a few model organisms. As more transcription factor binding sites are discovered and mapped to their counterparts in other species, it will be possible to learn how transcription regulation has evolved. Such knowledge will be extremely valuable for understanding species evolution, as many of the changes leading to speciation have been speculated to occur at the level of transcription regulation. Some questions in which we are interested are: How quickly do binding sites and transcription factors change between different species (Chin, Chuang, and Li, 2005) How much of this change is neutral? How much is due to selection for new regulatory behaviors? In addition to comparative genomics techniques for identifying transcription factor binding sites across species, we also use a variety of other computational methods, including those based on motif overrepresentation and gene expression patterns.
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).
Representative Publications
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, doi: 10.1093/bioinformatics/btn443 (in press).
Fox, A.K., Tuch, B.B., and Chuang, Jeffrey 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, Jeffrey 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 Jeffrey H. Chuang. 2007. Sequences conserved by selection across mouse and human malaria species. BMC: Genomics 8: 372.
Chin, C.S., Chuang, Jeffrey H., and Li, H. 2005. Genome-wide regulatory complexity in yeast promoters: separation of functional and neutral sequence. Genome Research 15: 205.
Chuang, Jeffrey, 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.
Ito, K., Chuang, Jeffrey, Alvarez-Lorenzo, C., Watanabe, T., Ando, N., and Grosberg, A. Yu. 2003. Multiple point adsorption in a heteropolymer gel and the Tanaka approach to imprinting: experiment and theory. Progress in Polymer Science 28: 1489.
Chuang, Jeffrey, Kantor, Y., and Kardar, M. 2001. Anomalous dynamics of translocation. Physical Review E 65: 011802.
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