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Journal ArticleDOI

An integrated view of protein evolution

01 May 2006-Nature Reviews Genetics (Nature Publishing Group)-Vol. 7, Iss: 5, pp 337-348
TL;DR: The status of a much-needed coherent view that integrates studies on protein evolution with biochemistry and functional and structural genomics is discussed.
Abstract: Why do proteins evolve at different rates? Advances in systems biology and genomics have facilitated a move from studying individual proteins to characterizing global cellular factors. Systematic surveys indicate that protein evolution is not determined exclusively by selection on protein structure and function, but is also affected by the genomic position of the encoding genes, their expression patterns, their position in biological networks and possibly their robustness to mistranslation. Recent work has allowed insights into the relative importance of these factors. We discuss the status of a much-needed coherent view that integrates studies on protein evolution with biochemistry and functional and structural genomics.
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Journal ArticleDOI
Andrew G. Clark1, Michael B. Eisen2, Michael B. Eisen3, Douglas Smith  +426 moreInstitutions (70)
08 Nov 2007-Nature
TL;DR: These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution.
Abstract: Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.

2,057 citations

Journal ArticleDOI
25 Jul 2008-Cell
TL;DR: In this article, the authors demonstrate conserved patterns of simple covariation between sequence evolution, codon usage, and mRNA level in E. coli, yeast, worm, fly, mouse, and human that suggest that all observed trends stem largely from a unified underlying selective pressure.

1,020 citations

Journal ArticleDOI
TL;DR: Way of predicting and analyzing stability effects of mutations, and mechanisms that buffer or compensate for these destabilizing effects and thereby promote protein evolvabilty, in nature and in the laboratory are described.

874 citations


Cites background from "An integrated view of protein evolu..."

  • ...Thus, although the initial stability of a protein can buffer some of the destabilizing effects of mutations (Figure 1a), stability appears to comprise the main factor (although clearly not the only one [6]) that dictates the rate of protein evolution [1 ,4 ], and possibly of whole organisms [14 ,15,16], in particular, but not only, in relation to the acquisition of new functions....

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  • ...Indeed, understanding and predicting the effects of mutations on the organismal level is a major challenge of evolutionary biology [1 ,6,7]....

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Journal ArticleDOI
TL;DR: Current understanding of the extent to which synonymous mutations influence disease, the various molecular mechanisms that underlie these effects and the implications for future research and biomedical applications are reviewed.
Abstract: Synonymous mutations — sometimes called 'silent' mutations — are now widely acknowledged to be able to cause changes in protein expression, conformation and function. The recent increase in knowledge about the association of genetic variants with disease, particularly through genome-wide association studies, has revealed a substantial contribution of synonymous SNPs to human disease risk and other complex traits. Here we review current understanding of the extent to which synonymous mutations influence disease, the various molecular mechanisms that underlie these effects and the implications for future research and biomedical applications.

853 citations

Journal ArticleDOI
TL;DR: The understanding of viruses as quasispecies has led to new antiviral designs, such as lethal mutagenesis, whose aim is to drive viruses toward low fitness values with limited chances of fitness recovery.
Abstract: Summary: Evolution of RNA viruses occurs through disequilibria of collections of closely related mutant spectra or mutant clouds termed viral quasispecies. Here we review the origin of the quasispecies concept and some biological implications of quasispecies dynamics. Two main aspects are addressed: (i) mutant clouds as reservoirs of phenotypic variants for virus adaptability and (ii) the internal interactions that are established within mutant spectra that render a virus ensemble the unit of selection. The understanding of viruses as quasispecies has led to new antiviral designs, such as lethal mutagenesis, whose aim is to drive viruses toward low fitness values with limited chances of fitness recovery. The impact of quasispecies for three salient human pathogens, human immunodeficiency virus and the hepatitis B and C viruses, is reviewed, with emphasis on antiviral treatment strategies. Finally, extensions of quasispecies to nonviral systems are briefly mentioned to emphasize the broad applicability of quasispecies theory.

852 citations

References
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Journal ArticleDOI
TL;DR: The program MODELTEST uses log likelihood scores to establish the model of DNA evolution that best fits the data.
Abstract: Summary: The program MODELTEST uses log likelihood scores to establish the model of DNA evolution that best fits the data. Availability: The MODELTEST package, including the source code and some documentation is available at http://bioag.byu.edu/zoology/crandall―lab/modeltest.html. Contact: dp47@email.byu.edu.

20,105 citations

Book
01 Jan 1930

14,612 citations

Book
15 Aug 2000
TL;DR: This chapter discusses the molecular basis of evolution, the evolution of organisms based on the fossil record, and the implications of these events for phylogenetic inference.
Abstract: 1. Molecular basis of evolution 2. Evolutionary changes of amino acid sequences 3. Evolutionary changes of DNA sequences 4. Synonymous and nonsynonymous nucleotide substitutions 5. Phylogenetic trees 6. Phylogenetic inference: Distance methods 7. Phylogenetic inference: Maximum parsimony methods 8. Phylogenetic inference: Maximum likelihood methods 9. Accuracies and statistical tests of phylogenetic trees 10. Molecular clocks and linearized trees 11. Ancestral nucleotide and amino acid sequences 12. Genetic polymorphism and evolution 13. Population trees from genetic markers 14. Perspectives Appendices A. Mathematical sumbols and notations B. Geological timescale C. Geological events in the Cenozoic and Meszoic eras D. Evolution of organisms based on the fossil record

5,629 citations

Journal ArticleDOI
TL;DR: SIFT is a program that predicts whether an amino acid substitution affects protein function so that users can prioritize substitutions for further study and can distinguish between functionally neutral and deleterious amino acid changes in mutagenesis studies and on human polymorphisms.
Abstract: Single nucleotide polymorphism (SNP) studies and random mutagenesis projects identify amino acid substitutions in protein-coding regions. Each substitution has the potential to affect protein function. SIFT (Sorting Intolerant From Tolerant) is a program that predicts whether an amino acid substitution affects protein function so that users can prioritize substitutions for further study. We have shown that SIFT can distinguish between functionally neutral and deleterious amino acid changes in mutagenesis studies and on human polymorphisms. SIFT is available at http://blocks.fhcrc.org/sift/SIFT.html.

5,318 citations