Phylogeography is concerned with the distribution of genealogical lineages, and we know from Chapter 2 that DNA sequences are the markers that are best suited for inferring genealogies. A looser interpretation of phylogeography does allow the use of markers such as microsatellites and AFLPs that provide information about the genetic similarity of populations based on allele frequencies or bandsharing, although strictly speaking such data do not comply with Avise's original definition of phylogeography. Nevertheless, as we saw in Chapter 4, allele frequencies can provide us with information on gene flow and the genetic subdivision of
Molecular Ecology Joanna Freeland © 2005 John Wiley & Sons, Ltd.
populations and therefore often make useful contributions to studies of phylogeo-graphy.
Over the years the markers of choice, at least when studying animals, have been mitochondrial sequences that were obtained through either direct sequencing or RFLP analysis; in fact, prior to 2000, approximately 70 per cent of all phylogeo-graphic studies were based on analyses of animal mitochondrial DNA (Avise, 2000). As we noted in Chapter 2, the popularity of mtDNA is based on several factors, including the ease with which it can be manipulated, its relatively rapid mutation rate, and its presumed lack of recombination, which results in an effectively clonal inheritance. Futhermore, universal animal mitochondrial primers are readily available and this is an important reason why animal phylogeographic studies have historically outnumbered those of plants.
At the same time, mtDNA markers are limited by the fact that the mitochondrion effectively comprises a single locus. Reconstructing population histories from a single locus is less than ideal if that locus has been subjected to selection or some other process that may have given it an unusual history. In addition, mitochondrial data may be misleading if mtDNA has passed recently from one species to another following hybridization. Furthermore, the sensitivity of mtDNA to bottlenecks is not always an advantage, and there is also the possibility that its maternal mode of inheritance will lead to an incomplete reconstruction of population histories if males and females had different patterns of dispersal.
The only way to test whether a mtDNA genealogy accurately reflects population history is to look for concordance with genealogies that are inferred from DNA regions in other genomes. In plants we can compare data from mitochondria, plastids and nuclear regions, but in animals mtDNA data can be supplemented only with data from nuclear loci. However, analysing nuclear data is less straightforward than analysing organelle data because recombination is common in the nuclear genome of sexually reproducing taxa. If the rate of recombination at a particular locus is similar to the rate of nucleotide substitutions, any given allele will, in all likelihood, have more than one recent ancestor, which means that different parts of the same locus will have different evolutionary histories. Although we need to be aware of this complication, a review of several nuclear gene phylogeographies recently suggested that recombination need not be an insurmountable problem (Hare, 2001).
Recombination can be identified with appropriate software (e.g. Holmes, Worobey and Rambaut, 1999; Husmeier and Wright, 2001). Once identified, the easiest way to deal with recombination, provided that it is present at only a low level, is to remove the relevant sequence regions before doing the genealogical analyses. This was the approach used in a study of the plant parasitic ascomycete fungus Sclerotinia sclerotiorum and three closely related species, all of which are parasites of agricultural and wild plants. Researchers sequenced seven nuclear loci and, after aligning the sequences, detected a low level of recombination using a software program that generates compatibility matrices. By removing recombinant haplotypes they were able to control for the effects of recombination in their analyses, and subsequently found some informative patterns regarding the fragmentation of populations in response to ecological conditions and host availability. Their findings were strengthened by their use of data from multiple, independent loci (Carbone and Kohn, 2001).
So far, most phylogeographic studies that have used nuclear data have sequenced specific genes such as bindin, a sperm gamete recognition protein that has been used to compare sea urchin populations (genus Lytechinus; Zigler and Lessios,
2004). There is, however, a growing interest in using single nucleotide polymorphisms (SNPs) from multiple loci for reconstructing population histories because they represent the most prevalent form of genetic variation (Brumfield et al., 2003). At this time SNPs have not been characterized adequately to provide useful markers in most non-model organisms, although a recent study that used 22 SNP loci to genetically characterize Scandinavian wolf populations suggests that the practical constraints associated with SNPs will soon be substantially reduced at which time we are likely to see a rapid increase in SNP-based studies (Seddon et al.,
Regardless of which molecular markers are employed, there are a number of analytical techniques relevant to phylogeography that we have not yet discussed, and we must understand these before we can start to unravel the evolutionary relationships of populations. We will start by looking at some of the more traditional methods, which include molecular clocks and phylogenetic reconstructions. We will then move on to look at some more recently developed methods that are specifically designed to accommodate the sorts of data that we are most likely to encounter in phylogeography.
Was this article helpful?