Understanding of regulatory elements in the human genome is a key step in our ability to understand complex biological and disease systems. Regulatory elements are much more difficult to identify than genes and likely account for more variation among individuals than actual coding differences in genes. Identifying and studying elements, including promoters, enhancers, silencers, and insulators, will lead to new therapeutic strategies as the complex regulatory networks are revealed. Up to now the characterization and validation of truly functional regulatory elements has been a low throughput endeavor as each regulatory site is cloned into a reporter assay and tested. This proposal produces a novel method that performs one of the most common validation assays, transient transfections, in a high-throughput manner by combining it with an innovative sorting and sequencing system. This system, which has been shown to be practical and feasible, will allow for rapid and thorough identification of the method of action of regulatory elements throughout the human genome. The candidate's background in both computer science and molecular biology ranging from undergraduate to graduate school and post-doctoral work provides a complete background that should allow for implementation and extension of the described experiment in the post-doctoral environment. The nature of the science and the data produced should allow continuation and extension of the work as a new faculty member. Stanford and the Snyder lab provide an outstanding environment for a strong program allowing development of the candidate and preparation for transition to a long-term independent research career. As part of this program, the candidate will combine a mentoring committee with continuing education via available online courses. The end result of both phases of the program will be scientific results that can be extended into useful and important medically and scientifically relevant areas as they relate to regulation of expression in humans. The innovative methods described will allow the candidate to pursue various lines of endeavor well past the end of this funding program. In turn the candidate will be positioned at the end of the program to function as an independent principle investigator and valuable collaborator.
This project seeks to extend current assays demonstrating function of genomic regions into an equivalent genome-wide assay. Identification of the effect of these regions on gene expression will lead to a better understanding of the complex regulatory `code' dictating our cellular processes. In turn, this improved understanding will bring forth new potential targets to approach incorrect regulation leading to disease.
| Diehl, Adam G; Boyle, Alan P (2018) Conserved and species-specific transcription factor co-binding patterns drive divergent gene regulation in human and mouse. Nucleic Acids Res 46:1878-1894 |
| Nishizaki, Sierra S; Boyle, Alan P (2017) Mining the Unknown: Assigning Function to Noncoding Single Nucleotide Polymorphisms. Trends Genet 33:34-45 |
| Spadafore, Maxwell; Najarian, Kayvan; Boyle, Alan P (2017) A proximity-based graph clustering method for the identification and application of transcription factor clusters. BMC Bioinformatics 18:530 |
| Phanstiel, Douglas H; Boyle, Alan P; Heidari, Nastaran et al. (2015) Mango: a bias-correcting ChIA-PET analysis pipeline. Bioinformatics 31:3092-8 |
| Phanstiel, Douglas H; Boyle, Alan P; Araya, Carlos L et al. (2014) Sushi.R: flexible, quantitative and integrative genomic visualizations for publication-quality multi-panel figures. Bioinformatics 30:2808-10 |
