Abstract

Computational predictions of the functional impact of genetic variation play a critical role in human genetics research. For nonsynonymous coding variants, most prediction algorithms make use of patterns of amino acid substitutions observed among homologous proteins at a given site. In particular, substitutions observed in orthologous proteins from other species are often assumed to be tolerated in the human protein as well. We examined this assumption by evaluating a panel of nonsynonymous mutants of a prototypical human enzyme, methylenetetrahydrofolate reductase (MTHFR), in a yeast cell-based functional assay. As expected, substitutions in human MTHFR at sites that are well-conserved across distant orthologs result in an impaired enzyme, while substitutions present in recently diverged sequences (including a 9-site mutant that “resurrects” the human-macaque ancestor) result in a functional enzyme. We also interrogated 30 sites with varying degrees of conservation by creating substitutions in the human enzyme that are accepted in at least one ortholog of MTHFR. Quite surprisingly, most of these substitutions were deleterious to the human enzyme. The results suggest that selective constraints vary between phylogenetic lineages such that inclusion of distant orthologs to infer selective pressures on the human enzyme may be misleading. We propose that homologous proteins are best used to reconstruct ancestral sequences and infer amino acid conservation among only direct lineal ancestors of a particular protein. We show that such an “ancestral site preservation” measure outperforms other prediction methods, not only in our selected set for MTHFR, but also in an exhaustive set of E. coli LacI mutants.

Highlights

  • Due to continuing advances in DNA sequencing technologies, our knowledge of human genetic variation is rapidly increasing

  • It is currently impractical to assay the biological effect of most genetic variants empirically, so computational predictions of their functional impact must play an important role in identifying potential genetic causes underlying human disease

  • We describe a novel methodology to predict whether mutations that lead to amino acid substitutions in proteins will impact protein function and, may be more likely to have physiological consequences

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Summary

Introduction

Due to continuing advances in DNA sequencing technologies, our knowledge of human genetic variation is rapidly increasing. It has long been recognized that amino acid substitutions that impair the function of a protein tend to involve substitution with a chemically very different amino acid [3,4]. Chasman and Adams [6] showed that mutation tolerance depends on several properties of the local 3D structure of the site, and this information has been used to make site-specific predictions of the functional effects of substitutions [6,7]. Such approaches are limited to proteins of known three-dimensional structure, or whose structure can be modeled based on a related protein

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