Aspects of Molecular Evolution

Fitch, Walter M.

doi:10.1146/annurev.ge.07.120173.002015

Cited by 102 publications

(36 citation statements)

References 73 publications

(100 reference statements)

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“…The repeated sequences are homologous with each other. In the terminology introduced by Fitch (27) they are orthologous because they occupy different genetic loci (Fig. 4).…”

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Origins of metabolic diversity: Evolutionary divergence by sequence repetition

Ornston

Yeh

1979

Proc. Natl. Acad. Sci. U.S.A.

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Recurring patterns of primary structure have been observed in enzymes that mediate sequential metabolic reactions in bacteria. The enzymes, muconolactone A-isomerase (+)-4-hydroxy4-carboxymethylisocrotonolactone A2-AK3-isomerase, EC 5.3.3.4] and f3-ketoadipate enol-lactone hydrolase [4-carboxymethylbut-3-enolide(1,4)enol-lactone-hydrolase, EC 3.1.1.24], have been coselected in bacterial populations because the isomerase can confer no nutritional advantage in the absence of the hydrolase. Similar amino acid sequences recur within the structure of the isomerase, and the amino-terminal amino acid sequence of the isomerase from Pseudomonas putida appears to be evolutionarily homologous with the corresponding sequence of a fl-ketoadipate enol-lactone hydrolase from Acinetobacter calcoaceticus. One interpretation of the sequence repetitions is that they reflect tandem duplication mutations that took place early in the evolution of the proteins. According to this view, the mutations caused elongation of structural genes and the creation of duplicated genes as the metabolic pathways evolved. A review of the sequence data calls attention to a different hypothesis: repeated amino acid sequences were introduced in the course of the proteins' evolution by substitution of copies of DNA sequences into structural genes. Our observations are interpreted on the basis of a model proposing genetic exchange between misaligned DNA sequences. The model predicts that misalignments in one chromosomal region can influence the nature of mutations in another region. Thus, as often has been observed, the mutability of a base pair will be determined by its location in a DNA sequence. Furthermore, the intrachromosomal recombination of DNA sequences may account for compler genetic modifications that occur as new pathways evolve. The model provides an interpretation of an apparent paradox, the rapid creation of new metabolic traits bybacterial genomes that are remarkably resistant to genetic drift.

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“…The repeated sequences are homologous with each other. In the terminology introduced by Fitch (27) they are orthologous because they occupy different genetic loci (Fig. 4).…”

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confidence: 99%

“…4). In contrast, parologous sequences (27) are homologous sequences encoded at the same genetic locus in separate genomes (Fig. 4) 28 identical residues in matching positions in the 50-residue sequences (22).…”

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confidence: 99%

Origins of metabolic diversity: Evolutionary divergence by sequence repetition

Ornston

Yeh

1979

Proc. Natl. Acad. Sci. U.S.A.

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“…Both of the subphylogenies we have described are in normal form. Observe that Pe(v) = {{s 7 , s 8 }, {s 9 , s 10 }} and Im(v) = {{s 6 …”

Section: An Edge Subfamily Q At V Is Perfect If No State Is Shared Bementioning

confidence: 99%

“…A fundamental problem in biology and linguistics is that of inferring the evolutionary history of a set of taxa, each of which is specified by the set of traits or characters that it exhibits [4,6,15]. Formally, let C be a set of characters, and for every c ∈ C let A c be the set of allowable states for character c. where, for any two species u, v, dist(u, v) denotes the number of character states in which u and v differ (that is, dist(u, v) is the Hamming distance between u and v).…”

Section: Introductionmentioning

confidence: 99%

A Polynomial-Time Algorithm for Near-Perfect Phylogeny

Fernández-Baca¹,

Lagergren²

2003

SIAM J. Comput.

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“…Character based methods: A species is specified by the set of traits or characters that it exhibits [31,36,46,47] and each character can occur in a species in one of a fixed number of states. Most of these methods use the •parsimony criterion and look for a phylogeny in which species evolve with the least number of character changes.…”

Section: Paleontologymentioning

confidence: 99%

Algorithms for weighted multidimensional search and perfect phylogeny

Agarwala

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Aspects of Molecular Evolution

Cited by 102 publications

References 73 publications

Origins of metabolic diversity: Evolutionary divergence by sequence repetition

Origins of metabolic diversity: Evolutionary divergence by sequence repetition

A Polynomial-Time Algorithm for Near-Perfect Phylogeny

Algorithms for weighted multidimensional search and perfect phylogeny

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