Journal Article

Distribution of the strength of selection against amino acid replacements in human proteins

Lev Y. Yampolsky, Fyodor A. Kondrashov and Alexey S. Kondrashov

in Human Molecular Genetics

Volume 14, issue 21, pages 3191-3201
Published in print November 2005 | ISSN: 0964-6906
Published online September 2005 | e-ISSN: 1460-2083 | DOI: http://dx.doi.org/10.1093/hmg/ddi350
Distribution of the strength of selection against amino acid replacements in human proteins

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The impact of an amino acid replacement on the organism's fitness can vary from lethal to selectively neutral and even, in rare cases, beneficial. Substantial data are available on either pathogenic or acceptable replacements. However, the whole distribution of coefficients of selection against individual replacements is not known for any organism. To ascertain this distribution for human proteins, we combined data on pathogenic missense mutations, on human non-synonymous SNPs and on human–chimpanzee divergence of orthologous proteins. Fractions of amino acid replacements which reduce fitness by >10−2, 10−2–10−4, 10−4–10−5 and <10−5 are 25, 49, 14 and 12%, respectively. On average, the strength of selection against a replacement is substantially higher when chemically dissimilar amino acids are involved, and the Grantham's index of a replacement explains 35% of variance in the average logarithm of selection coefficients associated with different replacements. Still, the impact of a replacement depends on its context within the protein more than on its own nature. Reciprocal replacements are often associated with rather different selection coefficients, in particular, replacements of non-polar amino acids with polar ones are typically much more deleterious than replacements in the opposite direction. However, differences between evolutionary fluxes of reciprocal replacements are only weakly correlated with the differences between the corresponding selection coefficients.

Journal Article.  8008 words.  Illustrated.

Subjects: Genetics and Genomics

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