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Phenotype-Genotype Correlation in Hirschsprung Disease Is Illuminated by Comparative Analysis of the RET Protein Sequence

Carl S. Kashuk, Eric A. Stone, Elizabeth A. Grice, Matthew E. Portnoy, Eric D. Green, Arend Sidow, Aravinda Chakravarti, Andrew S. McCallion and Victor A. McKusick
Proceedings of the National Academy of Sciences of the United States of America
Vol. 102, No. 25 (Jun. 21, 2005), pp. 8949-8954
Stable URL: http://www.jstor.org/stable/3375643
Page Count: 6
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Phenotype-Genotype Correlation in Hirschsprung Disease Is Illuminated by Comparative Analysis of the RET Protein Sequence
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Abstract

The ability to discriminate between deleterious and neutral amino acid substitutions in the genes of patients remains a significant challenge in human genetics. The increasing availability of genomic sequence data from multiple vertebrate species allows inclusion of sequence conservation and physicochemical properties of residues to be used for functional prediction. In this study, the RET receptor tyrosine kinase serves as a model disease gene in which a broad spectrum (≥116) of disease-associated mutations has been identified among patients with Hirschsprung disease and multiple endocrine neoplasia type 2. We report the alignment of the human RET protein sequence with the orthologous sequences of 12 non-human vertebrates (eight mammalian, one avian, and three teleost species), their comparative analysis, the evolutionary topology of the RET protein, and predicted tolerance for all published missense mutations. We show that, although evolutionary conservation alone provides significant information to predict the effect of a RET mutation, a model that combines comparative sequence data with analysis of physiochemical properties in a quantitative framework provides far greater accuracy. Although the ability to discern the impact of a mutation is imperfect, our analyses permit substantial discrimination between predicted functional classes of RET mutations and disease severity even for a multigenic disease such as Hirschsprung disease.

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