Literature DB >> 19917767

Mating-system variation, demographic history and patterns of nucleotide diversity in the Tristylous plant Eichhornia paniculata.

Rob W Ness1, Stephen I Wright, Spencer C H Barrett.   

Abstract

Inbreeding in highly selfing populations reduces effective size and, combined with demographic conditions associated with selfing, this can erode genetic diversity and increase population differentiation. Here we investigate the role that variation in mating patterns and demographic history play in shaping the distribution of nucleotide variation within and among populations of the annual neotropical colonizing plant Eichhornia paniculata, a species with wide variation in selfing rates. We sequenced 10 EST-derived nuclear loci in 225 individuals from 25 populations sampled from much of the geographic range and used coalescent simulations to investigate demographic history. Highly selfing populations exhibited moderate reductions in diversity but there was no significant difference in variation between outcrossing and mixed mating populations. Population size interacted strongly with mating system and explained more of the variation in diversity within populations. Bayesian structure analysis revealed strong regional clustering and selfing populations were highly differentiated on the basis of an analysis of F(st). There was no evidence for a significant loss of within-locus linkage disequilibrium within populations, but regional samples revealed greater breakdown in Brazil than in selfing populations from the Caribbean. Coalescent simulations indicate a moderate bottleneck associated with colonization of the Caribbean from Brazil approximately 125,000 years before the present. Our results suggest that the recent multiple origins of selfing in E. paniculata from diverse outcrossing populations result in higher diversity than expected under long-term equilibrium.

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Year:  2009        PMID: 19917767      PMCID: PMC2828719          DOI: 10.1534/genetics.109.110130

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


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