Highly accurate isoform identification for the human transcriptome
Sommer, M. J.; Cha, S.; Varabyou, A.; Rincon, N.; Park, S.; Minkin, I.; Pertea, M.; Steinegger, M.; Salzberg, S.
Show abstract
We explore a new hypothesis in genome annotation, namely whether computationally predicted protein structures can help to identify which of multiple possible gene isoforms represents a functional protein product. Guided by structure predictions, we evaluated over 140,000 isoforms of human protein-coding genes assembled from over 10,000 RNA sequencing experiments across many human tissues. We illustrate our new method with examples where structure provides a guide to function in combination with expression and evolutionary evidence. Additionally, we provide the complete set of structures as a resource to better understand the function of human genes and their isoforms. These results demonstrate the promise of protein structure prediction as a genome annotation tool, allowing us to refine even the most highly-curated catalog of human proteins. One-Sentence SummaryWe describe the use of 3D protein structures on a genome-wide scale to evaluate human protein isoforms for biological functionality.
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