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Journal of Undergraduate Research

Keywords

splice sites, cancer, dementia, disorders

College

Life Sciences

Department

Biology

Abstract

With the advent of nextgeneration sequencing, one of the unintended consequences is the sheer number of genomic variations requiring interpretation. Mutations in splice sites have been shown to contribute to the development of cancer [1], and dementia [2] among other potentially deadly disorders. Roughly 14 million people are diagnosed with cancer every year [3], and roughly 7 million with dementia [4]. Since these diseases cause an incredible amount of suffering, scientists in all fields are driven to search for ways to identify and treat them. These have been particularly difficult to interpret and have been largely ignored by the bioinformatics community most programs used for predicting the effects of these variants are out-of-date. The development of this software will give researchers a great advantage in searching for the effects of splice site variants, because they will be able to see which variants are most likely to affect splicing and in what ways. While being able to definitively know how a variant affects splicing requires experimentation, this algorithm will help researchers focus on only the most destructive variants. It will save them both time and money in their research. The code for this project will be available for free to the community to use, which will make it readily available for researchers to identify variants of interest and be able to predict their biological significance. Although I didn’t finish the project, it has been handed over to another lab member to finish it up.

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