Research area: genomics

Multi-dimensional structure function relationships in human β-cardiac myosin from population scale genetic variation.

Created on 9th February 2016

Julian R Homburger; Eric M Green; Colleen Caleshu; Margaret Sunitha; Rebecca Taylor; Kathleen M Ruppel; Raghu Metpally; SHaRe Investigators; Steven D Colan; Michelle Michels; Sharlene Day; Iacopo Olivotto; Carlos D Bustamante; Frederick Dewey; Carolyn Ho; James A Spudich; Euan A Ashley;

Myosin motors are the fundamental force-generating element of muscle contraction. Variation in the human β-cardiac myosin gene (MYH7) can lead to hypertrophic cardiomyopathy (HCM), a heritable disease characterized by cardiac hypertrophy, heart failure, and sudden cardiac death. How specific myosin variants alter motor function or clinical expression of disease remains incompletely understood. Here, we combine structural models of myosin from multiple stages of its chemomechanical cycle, exome sequencing data from population cohorts of 60,706 and 42,930 individuals, and genetic and phenotypic data from 2,913 HCM patients to elucidate novel structure-function relationships within β-cardiac myosin. We first developed computational models of the human β-cardiac myosin protein before and after the myosin power stroke. Then, using a spatial scan statistic modified to analyze genetic variation in protein three-dimensional space, we found significant enrichment of disease-associated variants in the converter, a kinetic domain that transduces force from the catalytic domain to the lever arm to accomplish the power stroke. Focusing our analysis on surface-exposed residues, we identified another region enriched for disease-associated variants that contains both the converter domain and residues on a single flat surface on the myosin head described as a myosin mesa. This surface is prominent in the pre-stroke model, but substantially reduced in size following the power stroke. Notably, HCM patients with variants in the enriched regions have earlier presentation and worse outcome than those with variants in other regions. In summary, this study provides a model for the combination of protein structure, large-scale genetic sequencing and detailed phenotypic data to reveal insight into time-shifted protein structures and genetic disease.

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