The University of California, Riverside, is given an award to develop unified, automated statistical algorithms to discover newly-developed microarray-based single-feature polymorphism markers (SFPs) and gene expression markers (GEMs) in crops on a genome scale. The PI has successfully developed the algorithm based on robust projection pursuit (RPP) method to identify SFPs between two genotypes, with application in Barley, Rice, Cowpea and Wheat genome. Recently, a new type of microarray-based gene expression markers (GEMs) has been developed that calls for a statistically sound identification method. The project aims to extend the RPP method for more powerful SFPs identification among multiple genotypes (Aim 1); to build a mixture model-based method for GEMs identification (Aim 2); to validate the detected SFPs and GEMs using expressed sequence tags and direct sequencing (Aim 3); to combine SFPs and GEMs for genotyping and construct genetic map by embedding hidden Markov model (HMM) within the framework of the expectation-maximization algorithm (Aim 4); to develop an outreach program that includes training and research experiences for crop research and breeding community (Aim 5). The tools will be demonstrated by using a large publicly available Arabidopsis and Barley expression data. This project will provide the crop community with new resources for producing abundant, high throughput functional-related markers for detailed analysis of the genetic basis of specific traits on a genomic scale, for understanding genomic divergence between genera, and for implementing new approaches toward critically needed cultivar improvement objectives. The project will broaden participation using campus programs that attract female and minority applications at UCR. The inter-disciplinary nature of the project will promote collaborations within and outside our laboratory between biologists, computer scientists and statisticians, and these interactions will strengthen an emerging graduate program in Genetics, Genomics and Bioinformatics (GGB) at UCR.
