The amino-acid mutational spectrum of human genetic disease

By Dennis Vitkup, Christopher Sander, George M. Church. 2003

211 citations recorded by the source corpus.

BackgroundNonsynonymous mutations in the coding regions of human genes are responsible for phenotypic differences between humans and for susceptibility to genetic disease. Computational methods were recently used to predict deleterious effects of nonsynonymous human mutations and polymorphisms. Here we focus on understanding the amino-acid mutation spectrum of human genetic disease. We compare the disease spectrum to the spectra of mutual amino-acid mutation frequencies, non-disease polymorphisms in human genes, and substitutions fixed between species.ResultsWe find that the disease spectrum correlates well with the amino-acid mutation frequencies based on the genetic code. Normalized by the mutation frequencies, the spectrum can be rationalized in terms of chemical similarities between amino acids. The disease spectrum is almost identical for membrane and non-membrane proteins. Mutations at arginine and glycine residues are together responsible for about 30% of genetic diseases, whereas random mutations at tryptophan and cysteine have the highest probability of causing disease.ConclusionsThe overall disease spectrum mainly reflects the mutability of the genetic code. We corroborate earlier results that the probability of a nonsynonymous mutation causing a genetic disease increases monotonically with an increase in the degree of evolutionary conservation of the mutation site and a decrease in the solvent-accessibility of the site; opposite trends are observed for non-disease polymorphisms. We estimate that the rate of nonsynonymous mutations with a negative impact on human health is less than one per diploid genome per generation.

Subfields: Genetics, Molecular Biology

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Citations in the corpus

Mutation severity spectrum of rare alleles in the human genome is predictive of disease type (2019, background): “In protein-coding regions, non-synonymous variations (missense mutations) result in the change of a single amino acid in the protein product [21].”
Advanced sequencing technologies: methods and goals (2004, unknown): “cgi?id=248310">malaria ) but would miss most of the genetic diseases that have been documented so fa”
The Personal Genome Project (2005, unknown): “…Molecular Systems Biology 2005 1 Molecular Systems Biology (2005) doi:10.1038/msb4100040 & 2005 EMBO and Nature Publishing Group All rights reserved 1744-4292/05 www.molecularsystemsbiology.com Article number: 2005.0030 2002; Vitkup, 2003), and/or (c) create homozygous or (co)dominant alleles.”
Computational approaches for predicting the biological effect of p53 missense mutations: a comparison of three sequence analysis based methods (2006, background): “The majority of mutations associated with disease show larger biochemical differences between mutant and wild-type amino acids than between amino acids observed in the MSA for a given position (17).”
Assessment of computational methods for predicting the effects of missense mutations in human cancers (2013, unknown): “This is consistent with the stronger conservation of functionally important residues and the higher probability of damaging mutations to occur in the protein interior [12].”
Variation Interpretation Predictors: Principles, Types, Performance, and Choice (2016, background): “These positions are usually essential for the structure or function of the protein [Miller and Kumar, 2001; Vitkup et al., 2003; Shen and Vihinen, 2004].”
SDM: a server for predicting effects of mutations on protein stability (2017, background): “Previously, it has been predicted that the damaging mutations have a higher probability of occurring at the protein interior (52).”