Copyright 0 1995 by the Genetics Society of America Separating Population Structure from Population History A Cladistic Analysis of the Geographical Distribution of Mitochondrial DNA Haplotypes in the Tiger Salamander Ambystoma tigrinurn Alan R Templeton Eric Routman and Christopher A Phillips Department of Biology Washington University St Louis Missouri 63130 4899 Manuscript received October 17 1994 Accepted for publication February 16 1995 ABSTRACT Nonrandom associations of alleles or haplotypes with geographical location can arise from restricted gene flow historical events fragmentation range expansion colonization or any mixture of these factors In this paper we show how a nested cladistic analysis of geographical distances can be used to test the null hypothesis of no geographical association of haplotypes test the hypothesis that significant associations are due torestricted gene flow and identify patterns of significant association that are due to historical events In this last case criteria are given to discriminate among contiguous range expansion long distance colonization and population fragmentation The ability to make these discriminations depends critically upon an adequate geographical sampling design These points are illustrated with a worked example mitochondrial DNA haplotypes in the salamanderAmbystoma tign num For this example prior information exists about restricted gene flow and likely historical events and the nested cladistic analyses were completely concordant with this prior information This concordance establishes the plausibility of this nested cladistic approach but much future work will be necessary to demonstrate robustness and to explore the power and accuracy of this procedure 0 NEof the principal aims of population genetics is the measurement of the amount and patterns of genetic variation found within and among subpopulations of interbreeding organisms to study gene flow genetic drift system of mating mutation and natural selection Traditionally inferences about microevolutionary forces have been based upon the number of alleles or haplotypes their frequencies and their geographical distribution For example WRIGHT 1969 developed hierarchical Fstatistics as a tool to study gene flow genetic drift and system of mating from data on allele and genotype frequencies and geography After estimating these F statistics microevolutionary parameters could be estimated by relating the Fstatistics to an underlying model For example in the island model of gene flow in whichthe population is subdivided into many islands of inbreeding effective size N with a rate of exchange of m per generation at random over all islands Wright s should be equal to 1 4N m p 13 where p is themutation rate Hence if and p are estimated it is possible to estimate Nm the effective number of migrating individuals per generation One serious limitation ofthis approach is that the Corresponding authm Alan R Templeton Department of Biology Washington University St Louis MO 63130 4899 E mail templeton wustlb wustl edu Present address Department of Biology San Francisco State University San Francisco CA 94132 Present address Illinois Natural History Survey Center forBiodiversity 607 E Peabody Drive Champaign IL 61820 Genetics 140 767 782 June 1995 relation of 4 to underlying microevolutionary parameters changes with different models of population structure For example if the populations are in a onedimensional habitat such as in or along a river and all dispersal is limited to exchanges between adjacent populations at a rate of m 2 per generation then F 1 4N 2mp 13 KIMURA and WEISS1964 Many other models exist each with its own relationship between and underlying inbreeding effective size mutation and gene flow parameters Consequently one major limitation of the use of F and related statistics e 8 LYNCHand CREASE1990 HUDSON et al 1992a is that the data used to estimate the F statistics often do not indicate which model of gene flow is appropriate for the populations being studied This is further complicated by the fact that the various models of gene flow are not necessarily alternatives one part of a species range may be restricted to onedimensional stepping stone gene flow whereas another part may fit the two dimensional continuous isolation by distance model Even worse the geographical genetic variation measured by and related statistics may have nothing to do with current patterns of gene flow at all For example LAFSON 1984 pointed out that when a population expands into or colonizes a new geographic area genetic homogeneity could be created within the recently colonized area that does not reflect current patterns of gene flow Similarly two populations may have been fragmented in the past and currently have no gene flow whatsoever yet their shared ancestry can create F values less than one that 768 R A Templeton E Routman and would erroneously imply gene flow Hence the g e e graphical pattern of genetic variation is influenced by population structure by population history and by combinations of these structural and historical factors This paper is concerned with separating population structure from population history as sources of geographical associations with genetic variants The effects of population history and structure have been studied by spatial autocorrelation SOKALet al 1989a b SLATKIN and ARTER 1991 EPPERSON1993 principal component analyses e g AMMERMAN and CAVALLI SFORZA 1984 and multidimensional scaling LESSA1990 These approaches can be thought of as the analogue of phenetic approaches in systematics as they are based upon some sort ofgenetic distance or identity measure In contrast we will outline a cladistic approach in this paper that uses a character state based haplotype evolutionary tree This paper will be limited to genetic surveys using DNA sequence or restriction site data with samples derived from a finite number of distinct sampling locations With such genetic surveys it is possible not only to estimate the number of alleles their frequencies and their geographical distribution but also their genealogical structure With the rapid development of coalescent theory over the last decade KINGMAN 1982a b EWENS1990 HUDSON1990 an increasingly rich theoretical framework within population genetics is arising for dealing with gene genealogies and allele frequency distributions in an integrated fashion This gene genealogy approach has already proven to be a powerful tool
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