Positional conservation and amino acids shape the correct diagnosis and population frequencies of benign and damaging personal amino acid mutations

Abstract

As the cost of DNA sequencing drops, we are moving beyond one genome per species to one genome per individual to improve prevention, diagnosis, and treatment of disease by using personal genotypes. Computational methods are frequently applied to predict impairment of gene function by nonsynonymous mutations in individual genomes and single nucleotide polymorphisms (nSNPs) in populations. These computational tools are, however, known to fail 15%-40% of the time. We find that accurate discrimination between benign and deleterious mutations is strongly influenced by the long-term (among species) history of positions that harbor those mutations. Successful prediction of known diseaseassociated mutations (DAMs) is much higher for evolutionarily conserved positions and for original-mutant amino acid pairs that are rarely seen among species. Prediction accuracies for nSNPs show opposite patterns, forecasting impediments to building diagnostic tools aiming to simultaneously reduce both false-positive and false-negative errors. The relative allele frequencies of mutations diagnosed as benign and damaging are predicted by positional evolutionary rates. These allele frequencies are modulated by the relative preponderance of the mutant allele in the set of amino acids found at homologous sites in other species (evolutionarily permissible alleles [EPAs]). The nSNPs found in EPAs are biochemically less severe than those missing from EPAs across all allele frequency categories. Therefore, it is important to consider position evolutionary rates and EPAs when interpreting the consequences and population frequencies of human mutations. The impending sequencing of thousands of human and many more vertebrate genomes will lead to more accurate classifiers needed in real-world applications.

Human genomic disease variants: A neutral evolutionary explanation

“…3; Subramanian and Kumar 2006;Kumar et al 2009). Similarly, 10-fold more synonymous substitutions (per base pair) have occurred between human and chimpanzee proteins than nonsynonymous substitutions, a trend that is universally observed among closely and distantly related species (Clark et al 2003;Subramanian and Kumar 2006).…”

Genes, mutations, and human inherited disease at the dawn of the age of personalized genomics

“…The question of the proportion of possible mutations within human disease genes that are likely to be of pathological significance is very difficult to address because it is dependent not only upon the type and location of the mutation but also upon the functionality of the nucleotides involved (itself dependent in part upon the amino acid residues that they encode) which is often hard to assess [Arbiza et al, 2006;Capriotti et al, 2008;Ferrer-Costa et al, 2002;Kumar et al, 2009;Li et al, 2009a;Miller and Kumar, 2001]. In addition, some types of mutation are likely to be much more comprehensively ascertained than others, making observational comparisons between mutation types an inherently hazardous undertaking.…”

Inferring causality and functional significance of human coding DNA variants

“…In general, the prediction techniques based on protein spatial structure can be applied only if the structure has been resolved for the query protein or its close homolog, which is only true for a minor fraction of human proteins. However, even for the proteins with known spatial structure, structure-based methods work best only in addition to phylogeny-based approach and provide only a slight increase in the accuracy of the methods (67,68).…”