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3. Rate of sequence divergence under constant selection

Author

Ivankov Dmitry N, Povolotskaya Inna S, Kondrashov Alexey S, and Kondrashov Fyodor A

Subjects
Biology (General), QH301-705.5
Abstract

Abstract Background Divergence of two independently evolving sequences that originated from a common ancestor can be described by two parameters, the asymptotic level of divergence E and the rate r at which this level of divergence is approached. Constant negative selection impedes allele replacements and, therefore, is routinely assumed to decelerate sequence divergence. However, its impact on E and on r has not been formally investigated. Results Strong selection that favors only one allele can make E arbitrarily small and r arbitrarily large. In contrast, in the case of 4 possible alleles and equal mutation rates, the lowest value of r, attained when two alleles confer equal fitnesses and the other two are strongly deleterious, is only two times lower than its value under selective neutrality. Conclusions Constant selection can strongly constrain the level of sequence divergence, but cannot reduce substantially the rate at which this level is approached. In particular, under any constant selection the divergence of sequences that accumulated one substitution per neutral site since their origin from the common ancestor must already constitute at least one half of the asymptotic divergence at sites under such selection. Reviewers This article was reviewed by Drs. Nicolas Galtier, Sergei Maslov, and Nick Grishin.

Published
2010
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6. Energy Barrier for an Ion Crossing an Intra-Membrane Channel

Author

Finkelstein, Alexei V., Ivankov, Dmitry N., and Dykhne, Alexander M.

Subjects
Physics - Biological Physics
Abstract

We present a simple approximate analytical estimate for self-energy of a charge in the middle of cylindrical channel of a high permittivity epsilon_1 in a media of a low permittivity epsilon_2 (for the cases of infinitely long and comparatively short channels) and show that this estimate is in a good quantitative agreement with exact solution of Poisson equation. Further, using these estimates, we explain the observed a lower conductivity, caused by an increased the self-free-energy for ions, whose diameter is by ~1 angstrom less than that of the channel (as compared to ions, whose diameter is equal to that of the channel)., Comment: 6 pages, 2 figures, 1 table, 6 references

Published
2006

8. In-Frame Deletion of Dystrophin Exons 8–50 Results in DMD Phenotype

Author

Egorova, Tatiana V., primary, Galkin, Ivan I., additional, Velyaev, Oleg A., additional, Vassilieva, Svetlana G., additional, Savchenko, Irina M., additional, Loginov, Vyacheslav A., additional, Dzhenkova, Marina A., additional, Korshunova, Diana S., additional, Kozlova, Olga S., additional, Ivankov, Dmitry N., additional, and Polikarpova, Anna V., additional

Published
2023
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11. Local fitness landscape of the green fluorescent protein

Author

Sarkisyan, Karen S., Bolotin, Dmitry A., Meer, Margarita V., Usmanova, Dinara R., Mishin, Alexander S., Sharonov, George V., Ivankov, Dmitry N., Bozhanova, Nina G., Baranov, Mikhail S., Soylemez, Onuralp, Bogatyreva, Natalya S., Vlasov, Peter K., Egorov, Evgeny S., Logacheva, Maria D., Kondrashov, Alexey S., Chudakov, Dmitry M., Putintseva, Ekaterina V., Mamedov, Ilgar Z., Tawfik, Dan S., Lukyanov, Konstantin A., and Kondrashov, Fyodor A.

Subjects
Protein research, Green fluorescent protein -- Research, Fitness (Genetics) -- Research, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Fitness landscapes (1,2) depict how genotypes manifest at the phenotypic level and form the basis of our understanding of many areas of biology (2-7), yet their properties remain elusive. Previous [...]

Published
2016

14. Inhibition of hyaluronan secretion by novel coumarin compounds and chitin synthesis inhibitors

Author

Tsitrina, Alexandra A, primary, Krasylov, Igor V, additional, Maltsev, Dmitry I, additional, Andreichenko, Irina N, additional, Moskvina, Viktoria S, additional, Ivankov, Dmitry N, additional, Bulgakova, Elena V, additional, Nesterchuk, Mikhail, additional, Shashkovskaya, Vera, additional, Dashenkova, Nataliya O, additional, Khilya, Vladimir P, additional, Mikaelyan, Arsen, additional, and Kotelevtsev, Yuri, additional

Published
2021
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19. An experimental assay of the interactions of amino acids from orthologous sequences shaping a complex fitness landscape

Author

Pokusaeva, Victoria O., primary, Usmanova, Dinara R., additional, Putintseva, Ekaterina V., additional, Espinar, Lorena, additional, Sarkisyan, Karen S., additional, Mishin, Alexander S., additional, Bogatyreva, Natalya S., additional, Ivankov, Dmitry N., additional, Akopyan, Arseniy V., additional, Avvakumov, Sergey Ya., additional, Povolotskaya, Inna S., additional, Filion, Guillaume J., additional, Carey, Lucas B., additional, and Kondrashov, Fyodor A., additional

Published
2019
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21. Self-consistency test reveals systematic bias in programs for prediction change of stability upon mutation

Author

Usmanova, Dinara R, primary, Bogatyreva, Natalya S, additional, Ariño Bernad, Joan, additional, Eremina, Aleksandra A, additional, Gorshkova, Anastasiya A, additional, Kanevskiy, German M, additional, Lonishin, Lyubov R, additional, Meister, Alexander V, additional, Yakupova, Alisa G, additional, Kondrashov, Fyodor A, additional, and Ivankov, Dmitry N, additional

Published
2018
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25. HypercubeME: two hundred million combinatorially complete datasets from a single experiment.

Author

Esteban, Laura A, Lonishin, Lyubov R, Bobrovskiy, Daniil M, Leleytner, Gregory, Bogatyreva, Natalya S, Kondrashov, Fyodor A, and Ivankov, Dmitry N

Subjects
MUTAGENESIS, GENOTYPES, AMINO acids
Abstract

Motivation Epistasis, the context-dependence of the contribution of an amino acid substitution to fitness, is common in evolution. To detect epistasis, fitness must be measured for at least four genotypes: the reference genotype, two different single mutants and a double mutant with both of the single mutations. For higher-order epistasis of the order n , fitness has to be measured for all 2 n genotypes of an n -dimensional hypercube in genotype space forming a 'combinatorially complete dataset'. So far, only a handful of such datasets have been produced by manual curation. Concurrently, random mutagenesis experiments have produced measurements of fitness and other phenotypes in a high-throughput manner, potentially containing a number of combinatorially complete datasets. Results We present an effective recursive algorithm for finding all hypercube structures in random mutagenesis experimental data. To test the algorithm, we applied it to the data from a recent HIS3 protein dataset and found all 199 847 053 unique combinatorially complete genotype combinations of dimensionality ranging from 2 to 12. The algorithm may be useful for researchers looking for higher-order epistasis in their high-throughput experimental data. Availability and implementation https://github.com/ivankovlab/HypercubeME.git. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Published
2020
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27. Unexpected Diversity of Signal Peptides in Prokaryotes

Author

Payne, Samuel H., primary, Bonissone, Stefano, additional, Wu, Si, additional, Brown, Roslyn N., additional, Ivankov, Dmitry N., additional, Frishman, Dmitrij, additional, Paša-Tolić, Ljiljana, additional, Smith, Richard D., additional, and Pevzner, Pavel A., additional

Published
2012
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