We are working on a number of research projects that all are related to applying bioinformatics approaches to the study of gene regulation and signaling pathways, with particular but not exclusive attention to the regulation of retinal gene regulation.
Transcriptional regulation. We are interested in the molecular basis of tissue specificity. One area we have been working on is combinatorial gene regulation that contributes to the tissue specificity. We have performed large-scale computational analysis of transcription factor (TF) interactions specific to human tissues [Yu et al, 2006, NAR]. The identified TF interactions can help to determine cis-regulatory modules in the promoters of tissue specific genes [Yu et al 2007, BMC Bioinformatics]. A database (TiGER) was built for tissue-specific gene expression and regulation [Liu et al, 2008, BMC Bioinformatics]. In another project, we identified a set of unconventional DNA binding proteins, including kinases, that can potentially play a role in gene regulation [Hu et al 2009, Cell].
Post-transcriptional gene regulation. We are also interested in developing an integrative model of gene regulation, in which different types of gene regulations cooperate to carry out biological functions. To understand the crosstalk between TFs and microRNAs, we investigated the interaction patterns (i.e. network motifs) in an integrative regulatory network. From this global survey, we find that a regulated feedback loop, in which two TFs regulate each other and one microRNA regulates both of the factors, is the most significantly overrepresented network motif. We also demonstrate the existence of two classes of microRNAs with distinct network topological properties. Our analysis suggests that the interaction patterns between TFs and microRNAs can influence the biological functions of microRNAs [Yu et al, 2008, NAR]. Furthermore, we found that network motif usage at early and late developmental stages is distinct. For example, network motifs containing reciprocal feedback regulatory relationships between two regulators are overrepresented in early developmental stages, while the motifs with one-way regulations, such as single input modules and feed-forward loops, are more frequently used in the late developmental stages [Hwang et al, 2012, PLoS One].
Epigenetic gene regulation. We took advantage of available genome wide DNA methylation datasets to derive the rules that determine epigenetic regulation, and their effects on biological functions.
Retinal regulatory networks. We are interested in elucidating molecular events underlying retinal gene regulation. We have been working on several projects relevant to retina-specific gene regulation. For example, we predicted the regulatory target genes of retina-specific TFs by integrating the information of promoter sequence and tissue-specific gene expression [Qian et al, 2005, NAR]. We also studied the alternative splicing in developing retina [Wan et al, 2011, NAR]. In another project, we identified a set of retina specific microRNAs and their expression patterns during retina development [Hackler et al, 2010, IOVS]. In addition, we constructed retinal functional networks using a data integration approach. The resulted networks can be used to identify novel retinal disease genes and predict biological function of retinal genes [Hu et al, 2010, Bioinformatics].