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Am J Bot. 2011 Apr;98(4):669-79. doi: 10.3732/ajb.1000378. Epub 2011 Mar 24.

Low levels of population genetic structure in Pinus contorta (Pinaceae) across a geographic mosaic of co-evolution.

Author information

  • 1Department of Botany, Dept. 3165, 1000 E. University Ave., University of Wyoming, Laramie, Wyoming 82071, USA. tparchma@uwyo.edu

Abstract

PREMISE OF THE STUDY:

Population genetic analyses provide information on the population context in which evolutionary processes operate and are important for understanding the evolution of geographically variable traits. Earlier studies showed that cone structure of lodgepole pine in the Rocky Mountains diverged among populations because of geographic variation in coevolutionary interactions involving mammalian and avian seed predators. Analyses of population genetic variation are needed to determine whether this divergence has arisen despite extensive gene flow and whether populations to the east and west of the Rocky Mountains have evolved convergent phenotypes independently.

METHODS:

We investigated genetic structuring across 22 stands of lodgepole pine in the central Rocky Mountains and in isolated peripheral populations that experience different seed predators and exhibit parallel divergence in cone traits using a set of nine simple sequence repeats and 235 AFLP loci.

KEY RESULTS:

Our analyses reveal high levels of genetic diversity within and low genetic differentiation among populations. Nonetheless, geographic and genetic distances were correlated, and isolated populations to the east and west of the Rocky Mountains had higher levels of differentiation than did populations in the central part of the range.

CONCLUSIONS:

These data indicate not only that adaptive divergence of cone traits across a geographic mosaic of coevolution has occurred despite minimal genetic differentiation, but also that isolated populations to the east and west of the Rocky Mountains have evolved distinctive cones independently and in parallel. The population structure quantified here will inform future research aimed at detecting genetic variants associated with divergent adaptive traits.

PMID:
21613166
[PubMed - indexed for MEDLINE]
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