Research Topics
Broad advances in DNA sequencing have radically transformed the scale and nature of genetics making it possible to analyze genomic changes across species, individuals, cell-types, and as mutations accrue and are subject to natural selection. Diverse phenotypic datasets have also grown rapidly, not only for sequencing-based assays such as gene expression and protein-nucleic acid interactions, but also other types including metabolomic, clinical, and drug-screening data. My lab is interested in computational and mathematical approaches to analyzing such large data sources to understand how genomes function and evolve and to make these findings clinically relevant. We develop and use techniques from a variety of disciplines, including statistical inference, molecular evolution and biophysical modeling. We are currently focused in two major areas: 1) Cancer Evolution and Patient-Derived Xenografts, and 2) RNA-Level Gene Regulation. These projects involve collaborations with experimental and computational colleagues at JAX Genomic Medicine, JAX Mammalian Genetics, and a number of outside groups.
Since joining JAX, our lab has begun projects in patient-derived xenografts, a model system in which human tumors are engrafted and studied in NSG mice. JAX has developed >300 such models from cancer types including breast, lung, bladder, and others, and these are a community wide resource. Our lab is involved in a number of studies using these models to understand the genetic drivers of cancer and drug resistance, with a particular focus on tumor heterogeneity and evolution. Within JAX we work closely with groups studying xenografts, including the Bult (JAX-MG), Liu (JAX-GM), and Lee (JAX-MG) labs, and we also work with a number of other groups in projects on cancer genomics.
Our lab studies gene regulation at both the RNA and DNA levels. For RNA, our projects have included regulation of translation, protein-RNA binding, and splicing. For example, in collaboration with Prof. Susan Ackerman (UCSD) we have identified and characterized a mutation in a tRNA as a driver for neurodegeneration and shown that this phenotype is mediated by specific translational pausing at the codons complementary to the tRNA anticodon (Ishimura et al 2014; Ishimura et al 2016). This was the first tRNA mutation found to have a phenotypic consequence in a mammal. Another current interest is how proteins interact with RNAs to achieve specific binding. In this area, we have developed approaches to identify functional elements in RNA based on functional genomic, structural, algorithmic, and high-throughput sequencing approaches (Dotu et al 2018; Zarringhalam et al 2012). Our lab has been studying the functions and neutral evolutionary behavior of synonymous sites in coding sequences for more than a decade (Chuang and Li 2004; Chin et al 2005). 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 (Kural et al 2009; Ding et al 2012; Ritter et al 2012).
Much of the lab's research has grown out of early interests in molecular evolution and statistical physics. For example, we have characterized the relative importance of cis- and trans- regulatory evolution on enhancers (Ritter et al 2010; Persampieri et al 2008; http://chuanglabapps.jax.org/chuanglab/cneBrowser/ http://chuanglabapps.jax.org/chuanglab/cneViewer/ )
