title: Hierarchical analysis of nucleotide diversity in geographically structured populations.
abstract: Existing methods for analyzing nucleotide diversity require investigators to identify relevant hierarchical levels before beginning the analysis. We describe a method that partitions diversity into hierarchical components while allowing any structure present in the data to emerge naturally. We present an unbiased version of NEI's nucleotide diversity statistics and show that our modification has the same properties as WRIGHT's FST. We compare its statistical properties with several other FST estimators, and we describe how to use these statistics to produce a rooted tree of relationships among the sampled populations in which the mean time to coalescence of haplotypes drawn from populations belonging to the same node is smaller than the mean time to coalescence of haplotypes drawn from populations belonging to different nodes. We illustrate the method by applying it to data from a recent survey of restriction site variation in the chloroplast genome of Coreopsis grandiflora.
authors.affiliation: Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs 06269-3043, USA. kent@darwin.eeb.uconn.edu
authors.forename: K E
authors.initials: KE
authors.lastname: Holsinger
authors.forename: R J
authors.initials: RJ
authors.lastname: Mason-Gamer
mesh_terms: D002736:Chloroplasts; D018744:DNA, Plant; D014644:Genetic Variation; D005843:Geography; D008432:Mathematical Computing; D008957:Models, Genetic; D009711:Nucleotides; D010802:Phylogeny; D010944:Plants / Q000235:genetics*; D015183:Restriction Mapping
chemical_list: D018744:DNA, Plant; D009711:Nucleotides