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J Mol Evol. 2009 May;68(5):433-47. doi: 10.1007/s00239-009-9237-2. Epub 2009 May 8.

Emergence of complex haplotypes from microevolutionary variation in sequence and structure of Colias phosphoglucose isomerase.

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1
Department of Biology, Stanford University, 371 Serra Mall, Stanford, CA 94305-5020, USA.

Abstract

A molecular evolutionary explanation of natural genetic variation requires analysis of specific variants' evolutionary dynamics. To pursue this for phosphoglucose isomerase (PGI) of Colias butterflies, whose polymorphism is maintained by strong natural selection, we assembled a large data set of wild haplotypes, highly variable at the amino acid and DNA levels. The most common electrophoretic, i.e., charge macrostate, allele class, 3, is conserved in its pattern of charged amino acid residues. The next most common macrostate, 4, has multiple patterns of charge, i.e., microstates, while less common (1, 2, 5, 6) macrostates are very diverse. Macrostate 4 shows significant linkage disequilibrium (LD) among its variants, especially for two groups of five haplotypes each. We find extensive intragenic recombination among all haplotypes except the two high-LD groups of macrostate 4, which display none. Phyletic relations among haplotypes are largely reticulate, again except for the high-LD groups of macrostate 4, which form clades with strong bootstrap support. Charge-changing and linked charge-neutral amino acid variants occur in diverse parts of PGI's sequence. Homology-based modeling of PGI's structure shows that these regions are related spatially in ways suggesting functional interaction. The high-LD groups of macrostate 4 display parallel amino acid variation in these regions. This pattern of haplotype clades with high LD among multiple varying sites, emerging from chaotically recombining variation, may be a "signature" of refinement of complex adaptive sequences by recombination and selection. It should be tested further in this study system and others as a possibly general feature of the evolution of living complexity.

PMID:
19424742
DOI:
10.1007/s00239-009-9237-2
[Indexed for MEDLINE]
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