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Abstract
While functional profiling is widely used to characterize the functional relevance of gene expression at genome-wide level, similar tools at isoform resolution are missing. In contrast to short-reads, single molecular sequencing technologies allow for direct sequencing of full-length transcripts, and novel tools are needed to leverage the information potential of these platforms to study the functional consequences of alternative transcript processing. We present a novel computational framework for Functional Iso-Transcriptomics analysis (FIT), specially designed to study isoform (differential) expression from a functional perspective. Our analysis showed that alternative transcript processing increased the availability of functional features in differentiated neural cells, and is a mechanism for altering gene function by changing cellular localization and binding properties of proteins. A number of these findings were experimentally validated.
Bio
My research focuses on the understanding of the functional aspects of gene expression at the genome-wide level and across different organisms. We integrate multi-omics platforms to understand the progression of complex diseases and study how transcriptional complexity is shaped by annotating the functional consequences of alternative splicing. The lab develops statistical methods and user-friendly software to answer all these questions. Examples of our tools are Blast2GO, maSigPro, Paintomics, NOISeq, SQANTI and tappAS. More info at conesalab.org and @conesagroup.
To accommodate a disability, please contact Ben Coffey at the UC Santa Cruz Genomics Institute (becoffey@ucsc.edu, 831-459-1477).
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