A free website for discovering non-coding lupus-associated variant function

Despite incredible advances in sequencing and genotyping, we lack effective tools for leveraging the resulting data to identify causal non-coding lupus-associated genetic variants and their mechanistic modes of action. The vast majority of lupus-associated variants are non-coding, and we currently lack a comprehensive system for effectively predicting their functional impact. The goal of this proposal is to create a computational system that will combine lupus-relevant data in a single framework for identifying and prioritizing lupus-associated variants, based on their likelihood of impacting the binding of specific regulatory molecules such as transcription factors, RNA binding proteins, and micro RNAs. We will populate this system with publically available lupus-relevant datasets, and enhance it with data from ChIP-seq experiments for transcription factors likely to play key roles in lupus, which we will perform in lupus patient-derived cell lines. We will create a freely-available, user-friendly web server that will provide these sophisticated analysis capabilities to the entire lupus research community. The proposed work is significant because it will enable any lupus researcher to form testable hypotheses for understanding the function of non-coding lupus-associated variants. This resource will produce knowledge that will form a foundation for lupus diagnosis and the development of therapies.