This is from the Amino Acid sequences: indicators of evolution lab (you can google the pdf online to see the figure) Question: More than 100 locations were not listed in Figure 1 because. Show more I've been have a lot of difficulty answering this today. I'm an eighth grader in advanced bio classes for the regents.
Subjects
Abstract
The rate and mechanism of protein sequence evolution have been central questions in evolutionary biology since the 1960s. Although the rate of protein sequence evolution depends primarily on the level of functional constraint, exactly what determines functional constraint has remained unclear. The increasing availability of genomic data has enabled much needed empirical examinations on the nature of functional constraint. These studies found that the evolutionary rate of a protein is predominantly influenced by its expression level rather than functional importance. A combination of theoretical and empirical analyses has identified multiple mechanisms behind these observations and demonstrated a prominent role in protein evolution of selection against errors in molecular and cellular processes.
Key points
- Studying the rate of protein sequence evolution led to the foundation of the field of molecular evolution and continues to offer insights into the mechanism of evolution.
- The evolutionary rate of a protein is only weakly influenced by the functional importance of the protein.
- The expression level of a protein is a major determinant of its evolutionary rate.
- Natural selection against molecular and cellular errors such as mistranslation, protein misfolding and protein misinteraction is a primary explanation of why highly expressed proteins evolve slowly.
- The functional constraints on a protein include not only a constraint to maintain its physiological function but also a constraint to avoid toxicity, and both factors influence the evolutionary rate of the protein.
Access optionsAccess options
Subscribe to Journal
Get full journal access for 1 year
All prices include VAT for Germany.
Rent or Buy article
Get time limited or full article access on ReadCube.
from$8.99
All prices are NET prices.
References
- 1.Zuckerkandl, E. & Pauling, L. in Horizons in Biochemistry (eds Kasha, M. & Pullman, B.) 189–225 (Academic Press, 1962).
- 2.Zuckerkandl, E. & Pauling, L. in Evolving Genes and Proteins (eds Bryson, V. & Vogel, H. J.) 97–166 (Academic Press, 1965).
- 3.Kimura, M.Evolutionary rate at the molecular level. Nature217, 624–626 (1968).
- 4.Kumar, S.Molecular clocks: four decades of evolution. Nat. Rev. Genet.6, 654–662 (2005).
- 5.Takahata, N.Molecular clock: an anti-neo-Darwinian legacy. Genetics176, 1–6 (2007).
- 6.Kimura, M.The Neutral Theory of Molecular Evolution (Cambridge Univ. Press, 1983).
- 7.Li, W.Molecular Evolution (Sinauer, 1997).
- 8.Wang, Z. & Zhang, J.Why is the correlation between gene importance and gene evolutionary rate so weak?PLoS Genet.5, e1000329 (2009).
- 9.Pal, C., Papp, B. & Hurst, L. D.Highly expressed genes in yeast evolve slowly. Genetics158, 927–931 (2001).This is the first report of the E–R anticorrelation.
- 10.Drummond, D. A., Bloom, J. D., Adami, C., Wilke, C. O. & Arnold, F. H.Why highly expressed proteins evolve slowly. Proc. Natl Acad. Sci. USA102, 14338–14343 (2005).This paper proposes the translational robustness hypothesis of the E–R anticorrelation.
- 11.Yang, J. R., Liao, B. Y., Zhuang, S. M. & Zhang, J.Protein misinteraction avoidance causes highly expressed proteins to evolve slowly. Proc. Natl Acad. Sci. USA109, E831–E840 (2012).This paper proposes the protein misinteraction hypothesis of the E–R anticorrelation.
- 12.Park, C., Chen, X., Yang, J. R. & Zhang, J.Differential requirements for mRNA folding partially explain why highly expressed proteins evolve slowly. Proc. Natl Acad. Sci. USA110, E678–E686 (2013).This paper proposes the mRNA folding requirement hypothesis of the E–R anticorrelation.
- 13.Yang, J. R., Zhuang, S. M. & Zhang, J.Impact of translational error-induced and error-free misfolding on the rate of protein evolution. Mol. Syst. Biol.6, 421 (2010).
- 14.Drummond, D. A. & Wilke, C. O.Mistranslation-induced protein misfolding as a dominant constraint on coding-sequence evolution. Cell134, 341–352 (2008).
- 15.Yang, J. R., Chen, X. & Zhang, J.Codon-by-codon modulation of translational speed and accuracy via mRNA folding. PLoS Biol.12, e1001910 (2014).This paper explains the underlying cause of the mRNA folding requirement that partially accounts for the E–R anticorrelation.
- 16.Gout, J. F., Kahn, D. & Duret, L.The relationship among gene expression, the evolution of gene dosage, and the rate of protein evolution. PLoS Genet.6, e1000944 (2010).
- 17.Cherry, J. L.Expression level, evolutionary rate, and the cost of expression. Genome Biol. Evol.2, 757–769 (2010).References 16 and 17 independently propose the expression cost hypothesis of the E–R anticorrelation.
- 18.Yang, Z.Among-site rate variation and its impact on phylogenetic analyses. Trends Ecol. Evol.11, 367–372 (1996).
- 19.Hedges, S. B., Dudley, J. & Kumar, S.TimeTree: a public knowledge-base of divergence times among organisms. Bioinformatics22, 2971–2972 (2006).
- 20.King, J. L. & Jukes, T. H.Non-Darwinian evolution. Science164, 788–798 (1969).
- 21.Zhang, J. in Evolution Since Darwin: The First 150 Years (eds Bell, M. A. et al.) 87–118 (Sinauer, 2010).
- 22.Karp, G.Cell and Molecular Biology (John Wiley & Sons, 2008).
- 23.Kimura, M. & Ohta, T.On some principles governing molecular evolution. Proc. Natl Acad. Sci. USA71, 2848–2852 (1974).This paper proposes the role of protein functional importance and functional constraint in determining the rate of protein sequence evolution.
- 24.Wilson, A. C., Carlson, S. S. & White, T. J.Biochemical evolution. Annu. Rev. Biochem.46, 573–639 (1977).
- 25.Hurst, L. D. & Smith, N. G.Do essential genes evolve slowly?Curr. Biol.9, 747–750 (1999).This study was the first to test the relationship between protein functional importance and evolutionary rate based on a fairly large genomic data set.
- 26.Winzeler, E. A.et al.Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science285, 901–906 (1999).
- 27.Hirsh, A. E. & Fraser, H. B.Protein dispensability and rate of evolution. Nature411, 1046–1049 (2001).
- 28.Holstege, F. C.et al.Dissecting the regulatory circuitry of a eukaryotic genome. Cell95, 717–728 (1998).
- 29.Pal, C., Papp, B. & Hurst, L. D.Genomic function: rate of evolution and gene dispensability. Nature421, 496–497 (2003).
- 30.Zhang, J. & He, X.Significant impact of protein dispensability on the instantaneous rate of protein evolution. Mol. Biol. Evol.22, 1147–1155 (2005).
- 31.Wall, D. P.et al.Functional genomic analysis of the rates of protein evolution. Proc. Natl Acad. Sci. USA102, 5483–5488 (2005).
- 32.Liao, B. Y., Scott, N. M. & Zhang, J.Impacts of gene essentiality, expression pattern, and gene compactness on the evolutionary rate of mammalian proteins. Mol. Biol. Evol.23, 2072–2080 (2006).
- 33.Jordan, I. K., Rogozin, I. B., Wolf, Y. I. & Koonin, E. V.Essential genes are more evolutionarily conserved than are nonessential genes in bacteria. Genome Res.12, 962–968 (2002).
- 34.Rocha, E. P. & Danchin, A.An analysis of determinants of amino acids substitution rates in bacterial proteins. Mol. Biol. Evol.21, 108–116 (2004).
- 35.Lindblad-Toh, K.et al.A high-resolution map of human evolutionary constraint using 29 mammals. Nature478, 476–482 (2011).
- 36.Pennacchio, L. A.et al.In vivo enhancer analysis of human conserved non-coding sequences. Nature444, 499–502 (2006).
- 37.Krylov, D. M., Wolf, Y. I., Rogozin, I. B. & Koonin, E. V.Gene loss, protein sequence divergence, gene dispensability, expression level, and interactivity are correlated in eukaryotic evolution. Genome Res.13, 2229–2235 (2003).
- 38.Greenbaum, D., Colangelo, C., Williams, K. & Gerstein, M.Comparing protein abundance and mRNA expression levels on a genomic scale. Genome Biol.4, 117 (2003).
- 39.Vogel, C. & Marcotte, E. M.Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat. Rev. Genet.13, 227–232 (2012).
- 40.Drummond, D. A., Raval, A. & Wilke, C. O.A single determinant dominates the rate of yeast protein evolution. Mol. Biol. Evol.23, 327–337 (2006).
- 41.Shen, Y.et al.Testing hypotheses on the rate of molecular evolution in relation to gene expression using microRNAs. Proc. Natl Acad. Sci. USA108, 15942–15947 (2011).
- 42.Managadze, D., Rogozin, I. B., Chernikova, D., Shabalina, S. A. & Koonin, E. V.Negative correlation between expression level and evolutionary rate of long intergenic noncoding RNAs. Genome Biol. Evol.3, 1390–1404 (2011).
- 43.Geiler-Samerotte, K. A.et al.Misfolded proteins impose a dosage-dependent fitness cost and trigger a cytosolic unfolded protein response in yeast. Proc. Natl Acad. Sci. USA108, 680–685 (2011).
- 44.Drummond, D. A. & Wilke, C. O.The evolutionary consequences of erroneous protein synthesis. Nat. Rev. Genet.10, 715–724 (2009).
- 45.Akashi, H.Synonymous codon usage in Drosophila melanogaster: natural selection and translational accuracy. Genetics136, 927–935 (1994).
- 46.Cherry, J. L.Highly expressed and slowly evolving proteins share compositional properties with thermophilic proteins. Mol. Biol. Evol.27, 735–741 (2010).
- 47.Chakravarty, S. & Varadarajan, R.Residue depth: a novel parameter for the analysis of protein structure and stability. Structure7, 723–732 (1999).
- 48.Stambolsky, P.et al.Modulation of the vitamin D3 response by cancer-associated mutant p53. Cancer Cell17, 273–285 (2010).
- 49.Vavouri, T., Semple, J. I., Garcia-Verdugo, R. & Lehner, B.Intrinsic protein disorder and interaction promiscuity are widely associated with dosage sensitivity. Cell138, 198–208 (2009).
- 50.Zhang, J., Maslov, S. & Shakhnovich, E. I.Constraints imposed by non-functional protein–protein interactions on gene expression and proteome size. Mol. Syst. Biol.4, 210 (2008).
- 51.Levy, E. D., De, S. & Teichmann, S. A.Cellular crowding imposes global constraints on the chemistry and evolution of proteomes. Proc. Natl Acad. Sci. USA109, 20461–20466 (2012).
- 52.Zur, H. & Tuller, T.Strong association between mRNA folding strength and protein abundance in S. cerevisiae. EMBO Rep.13, 272–277 (2012).
- 53.Akashi, H. & Gojobori, T.Metabolic efficiency and amino acid composition in the proteomes of Escherichia coli and Bacillus subtilis. Proc. Natl Acad. Sci. USA99, 3695–3700 (2002).
- 54.Wolf, M. Y., Wolf, Y. I. & Koonin, E. V.Comparable contributions of structural-functional constraints and expression level to the rate of protein sequence evolution. Biol. Direct3, 40 (2008).
- 55.Chen, S. C., Chuang, T. J. & Li, W. H.The relationships among microRNA regulation, intrinsically disordered regions, and other indicators of protein evolutionary rate. Mol. Biol. Evol.28, 2513–2520 (2011).
- 56.Cheng, C., Bhardwaj, N. & Gerstein, M.The relationship between the evolution of microRNA targets and the length of their UTRs. BMC Genomics10, 431 (2009).
- 57.He, X. & Zhang, J.Toward a molecular understanding of pleiotropy. Genetics173, 1885–1891 (2006).
- 58.Fraser, H. B., Hirsh, A. E., Steinmetz, L. M., Scharfe, C. & Feldman, M. W.Evolutionary rate in the protein interaction network. Science296, 750–752 (2002).
- 59.Bloom, J. D. & Adami, C.Apparent dependence of protein evolutionary rate on number of interactions is linked to biases in protein–protein interactions data sets. BMC Evol. Biol.3, 21 (2003).
- 60.Hughes, A. L. & Nei, M.Pattern of nucleotide substitution at major histocompatibility complex class I loci reveals overdominant selection. Nature335, 167–170 (1988).
- 61.Lee, Y. H., Ota, T. & Vacquier, V. D.Positive selection is a general phenomenon in the evolution of abalone sperm lysin. Mol. Biol. Evol.12, 231–238 (1995).
- 62.Dunn, J. G., Foo, C. K., Belletier, N. G., Gavis, E. R. & Weissman, J. S.Ribosome profiling reveals pervasive and regulated stop codon readthrough in Drosophila melanogaster. eLife2, e01179 (2013).
- 63.Raj, A. & van Oudenaarden, A.Nature, nurture, or chance: stochastic gene expression and its consequences. Cell135, 216–226 (2008).
- 64.Marinov, G. K.et al.From single-cell to cell-pool transcriptomes: stochasticity in gene expression and RNA splicing. Genome Res.24, 496–510 (2014).
- 65.Zhang, Z., Qian, W. & Zhang, J.Positive selection for elevated gene expression noise in yeast. Mol. Syst. Biol.5, 299 (2009).
- 66.Wang, Z. & Zhang, J.Impact of gene expression noise on organismal fitness and the efficacy of natural selection. Proc. Natl Acad. Sci. USA108, E67–E76 (2011).
- 67.Warnecke, T. & Hurst, L. D.Error prevention and mitigation as forces in the evolution of genes and genomes. Nat. Rev. Genet.12, 875–881 (2011).
- 68.Eldar, A. & Elowitz, M. B.Functional roles for noise in genetic circuits. Nature467, 167–173 (2010).
- 69.Xu, G. & Zhang, J.Human coding RNA editing is generally nonadaptive. Proc. Natl Acad. Sci. USA111, 3769–3774 (2014).
- 70.Gregersen, N., Bross, P., Vang, S. & Christensen, J. H.Protein misfolding and human disease. Annu. Rev. Genom. Hum. Genet.7, 103–124 (2006).
- 71.Wang, Z. & Moult, J.SNPs, protein structure, and disease. Hum. Mutat.17, 263–270 (2001).
- 72.Oren, M. & Rotter, V.Mutant p53 gain-of-function in cancer. Cold Spring Harb. Perspect Biol2, a001107 (2010).
- 73.Wu, J., Li, Y. & Jiang, R.Integrating multiple genomic data to predict disease-causing nonsynonymous single nucleotide variants in exome sequencing studies. PLoS Genet.10, e1004237 (2014).
- 74.Cooper, G. M. & Shendure, J.Needles in stacks of needles: finding disease-causal variants in a wealth of genomic data. Nat. Rev. Genet.12, 628–640 (2011).
- 75.Orgel, L. E.The maintenance of the accuracy of protein synthesis and its relevance to ageing. Proc. Natl Acad. Sci. USA49, 517–521 (1963).
- 76.Silva, R. M.et al.The yeast PNC1 longevity gene is up-regulated by mRNA mistranslation. PLoS ONE4, e5212 (2009).
- 77.Pandolfi, P. P.Aberrant mRNA translation in cancer pathogenesis: an old concept revisited comes finally of age. Oncogene23, 3134–3137 (2004).
- 78.Frank, S. A.Somatic mosaicism and disease. Curr. Biol.24, R577–R581 (2014).
- 79.Stiffler, M. A., Hekstra, D. R. & Ranganathan, R.Evolvability as a function of purifying selection in TEM-1 β-lactamase. Cell160, 882–892 (2015).
- 80.Podgornaia, A. I. & Laub, M. T.Pervasive degeneracy and epistasis in a protein–protein interface. Science347, 673–677 (2015).
- 81.Whitehead, D. J., Wilke, C. O., Vernazobres, D. & Bornberg-Bauer, E.The look-ahead effect of phenotypic mutations. Biol. Direct3, 18 (2008).
- 82.Pal, C., Papp, B. & Lercher, M. J.An integrated view of protein evolution. Nat. Rev. Genet.7, 337–348 (2006).
- 83.Wolf, Y. I., Carmel, L. & Koonin, E. V.Unifying measures of gene function and evolution. Proc. Biol. Sci.273, 1507–1515 (2006).
- 84.Xia, Y., Franzosa, E. A. & Gerstein, M. B.Integrated assessment of genomic correlates of protein evolutionary rate. PLoS Comput. Biol.5, e1000413 (2009).
- 85.Du, X., Lipman, D. J. & Cherry, J. L.Why does a protein's evolutionary rate vary over time?Genome Biol. Evol.5, 494–503 (2013).
- 86.Franzosa, E. A. & Xia, Y.Structural determinants of protein evolution are context-sensitive at the residue level. Mol. Biol. Evol.26, 2387–2395 (2009).
- 87.Yeh, S. W.et al.Site-specific structural constraints on protein sequence evolutionary divergence: local packing density versus solvent exposure. Mol. Biol. Evol.31, 135–139 (2014).
- 88.Zhang, J. & Gu, X.Correlation between the substitution rate and rate variation among sites in protein evolution. Genetics149, 1615–1625 (1998).
- 89.Chen, F. C., Liao, B. Y., Pan, C. L., Lin, H. Y. & Chang, A. Y.Assessing determinants of exonic evolutionary rates in mammals. Mol. Biol. Evol.29, 3121–3129 (2012).
- 90.Nei, M. & Kumar, S.Molecular Evolution and Phylogenetics (Oxford Univ. Press, 2000).
- 91.Kim, N. & Jinks-Robertson, S.Transcription as a source of genome instability. Nat. Rev. Genet.13, 204–214 (2012).
- 92.Hanawalt, P. C. & Spivak, G.Transcription-coupled DNA repair: two decades of progress and surprises. Nat. Rev. Mol. Cell Biol.9, 958–970 (2008).
- 93.Park, C., Qian, W. & Zhang, J.Genomic evidence for elevated mutation rates in highly expressed genes. EMBO Rep.13, 1123–1129 (2012).
- 94.Chen, X. & Zhang, J.No gene-specific optimization of mutation rate in Escherichia coli. Mol. Biol. Evol.30, 1559–1562 (2013).
- 95.Chen, X. & Zhang, J.Yeast mutation accumulation experiment supports elevated mutation rates at highly transcribed sites. Proc. Natl Acad. Sci. USA111, E4062 (2014).
- 96.Lind, P. A. & Andersson, D. I.Whole-genome mutational biases in bacteria. Proc. Natl Acad. Sci. USA105, 17878–17883 (2008).
- 97.Gottipati, P. & Helleday, T.Transcription-associated recombination in eukaryotes: link between transcription, replication and recombination. Mutagenesis24, 203–210 (2009).
- 98.Liao, B. Y. & Zhang, J.Low rates of expression profile divergence in highly expressed genes and tissue-specific genes during mammalian evolution. Mol. Biol. Evol.23, 1119–1128 (2006).
- 99.Park, C. & Zhang, J.High expression hampers horizontal gene transfer. Genome Biol. Evol.4, 523–532 (2012).
- 100.Zhang, L. & Li, W. H.Mammalian housekeeping genes evolve more slowly than tissue-specific genes. Mol. Biol. Evol.21, 236–239 (2004).
- 101.Piasecka, B., Lichocki, P., Moretti, S., Bergmann, S. & Robinson-Rechavi, M.The hourglass and the early conservation models — co-existing patterns of developmental constraints in vertebrates. PLoS Genet.9, e1003476 (2013).
- 102.Chuang, T. J. & Chiang, T. W.Impacts of pretranscriptional DNA methylation, transcriptional transcription factor, and posttranscriptional microRNA regulations on protein evolutionary rate. Genome Biol. Evol.6, 1530–1541 (2014).
- 103.Taipale, M.et al.Quantitative analysis of HSP90-client interactions reveals principles of substrate recognition. Cell150, 987–1001 (2012).
- 104.Bogumil, D. & Dagan, T.Chaperonin-dependent accelerated substitution rates in prokaryotes. Genome Biol. Evol.2, 602–608 (2010).
- 105.Liao, B. Y., Weng, M. P. & Zhang, J.Impact of extracellularity on the evolutionary rate of mammalian proteins. Genome Biol. Evol.2, 39–43 (2010).
- 106.Ran, W., Kristensen, D. M. & Koonin, E. V.Couping between protein level selection and codon usage optimization in the evolution of bacteria and archaea. mBio5, e00956-14 (2014).
- 107.Sharp, P. M., Shields, D. C., Wolfe, K. H. & Li, W. H.Chromosomal location and evolutionary rate variation in enterobacterial genes. Science246, 808–810 (1989).
- 108.Flynn, K. M., Vohr, S. H., Hatcher, P. J. & Cooper, V. S.Evolutionary rates and gene dispensability associate with replication timing in the archaeon Sulfolobus islandicus. Genome Biol. Evol.2, 859–869 (2010).
- 109.Hahn, M. W. & Kern, A. D.Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. Mol. Biol. Evol.22, 803–806 (2005).
- 110.Kim, P. M., Lu, L. J., Xia, Y. & Gerstein, M. B.Relating three-dimensional structures to protein networks provides evolutionary insights. Science314, 1938–1941 (2006).
- 111.Vitkup, D., Kharchenko, P. & Wagner, A.Influence of metabolic network structure and function on enzyme evolution. Genome Biol.7, R39 (2006).
- 112.Jovelin, R. & Phillips, P. C.Evolutionary rates and centrality in the yeast gene regulatory network. Genome Biol.10, R35 (2009).
- 113.Kryuchkova, N. & Robinson-Rechavi, M.Determinants of protein evolutionary rates in light of ENCODE functional genomics. BMC Bioinformatics15 (Suppl. 3), A9 (2014).
- 114.Bloom, J. D., Drummond, D. A., Arnold, F. H. & Wilke, C. O.Structural determinants of the rate of protein evolution in yeast. Mol. Biol. Evol.23, 1751–1761 (2006).
- 115.Brown, C. J.et al.Evolutionary rate heterogeneity in proteins with long disordered regions. J. Mol. Evol.55, 104–110 (2002).
- 116.Javier Zea, D., Miguel Monzon, A., Fornasari, M. S., Marino-Buslje, C. & Parisi, G.Protein conformational diversity correlates with evolutionary rate. Mol. Biol. Evol.30, 1500–1503 (2013).
Acknowledgements
The authors thank X. Chen, W.-C. Ho, B. Moyers, J. Xu and three anonymous reviewers for comments. Research in the Zhang Lab on the topic reviewed here has been supported by the US National Institutes of Health.
Author information
Affiliations
Department of Ecology and Evolutionary Biology, University of Michigan, 830 North University Avenue, Ann Arbor, Michigan 48109, USA.
- Jianzhi Zhang
- & Jian-Rong Yang
Authors
- Nature Research journals•
- PubMed•
- Nature Research journals•
- PubMed•
Competing interests
The authors declare no competing financial interests.
Corresponding author
Correspondence to Jianzhi Zhang.
Supplementary information
PDF files
- 1.
Supplementary information S1 (box)
- 2.
Supplementary information S2 (box)
Data sources for Figure 1
Glossary
A theory of molecular evolution asserting that most variations of DNA and protein sequences within and between species are selectively neutral rather than adaptive.
The extent to which random mutations are purged by natural selection owing to their deleterious effects on protein function.
The fitness advantage to an organism conferred by the function of a protein.
The hypothesis that the same protein evolves with an approximately constant rate over time and across different organisms.
The degree to which an organism can survive and reproduce when a given gene is removed.
A gene from a different species that originated by vertical descent from a single gene of the last common ancestor of these species.
(Denoted as Ne). A measure of the strength of random genetic drift in a population. The lower the Ne, the stronger the genetic drift. Ne is influenced by the census population size, breeding system and sex ratio, among other factors.
The process by which a protein structure assumes a non-native shape or conformation, which not only diminishes the physiological function of the protein but may also create cytotoxicity.
A codon that is used more frequently than its synonymous codons in a genome sequence.
Nascent proteins in which incorrect amino acids have been incorporated during synthesis, which may be caused by incorrect charging of tRNAs by aminoacyl tRNA synthetases or incorrect acceptance of tRNAs by ribosomes.
![Amino acid sequences indicators of evolution key Amino acid sequences indicators of evolution key](/uploads/1/2/4/8/124867954/827759595.jpg)
A non-native interaction between protein molecules that not only reduces the concentrations of freely available protein molecules but may also be toxic.
A measure of the reduction in free energy of a folded mRNA molecule compared to its unfolded form.
Pertaining to pleiotropy: the phenomenon whereby one gene or one mutation affects multiple traits.
The number of protein sequences that adopt a protein structure.
The degree of structural variations of various native states of a protein.
Rights and permissions
To obtain permission to re-use content from this article visit RightsLink.
About this article
![Amino Acid Sequences Indicators Of Evolution Amino Acid Sequences Indicators Of Evolution](/uploads/1/2/4/8/124867954/390867271.png)
Publication history
DOI
Further reading
Micro-evolution of three Streptococcus species: selection, antigenic variation, and horizontal gene inflow
BMC Evolutionary Biology (2019)Co-evolution of spliceosomal disassembly interologs: crowning J-protein component with moonlighting RNA-binding activity
Current Genetics (2019)Reduced intrinsic DNA curvature leads to increased mutation rate
Genome Biology (2018)Derivative-free neural network for optimizing the scoring functions associated with dynamic programming of pairwise-profile alignment
Algorithms for Molecular Biology (2018)Correlates of evolutionary rates in the murine sperm proteome
BMC Evolutionary Biology (2018)