| Phylogeny and phylogeography of European Parids: | ||
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The advent of molecular techniques in the mid 1960’s enabled evolutionary researchers to first detect genetic variation in proteins (Margoliash 1963, Kimura 1969) and later directly in DNA. Molecular variation could then be measured quantitatively and empirical results interpreted using population genetics theory (Fisher 1930, Wright 1931, Haldane 1932).
Many studies provided evidence that molecular levels of variation are high in most natural populations (Lewontin & Hubby 1966, Harris 1966, Kimura & Ohta 1971a). The neutral theory proposed by Kimura (1968a, b) asserts that a ‘great majority of evolutionary changes at the molecular level are caused not by Darwinian selection but by random drift of selectively neutral mutants’. The theory, originally applied to protein variation, does not deny the role of natural selection in determining the course of adaptive evolution, but it assumes that only a minute fraction of DNA changes in evolution are adaptive in nature, while the great majority of phenotypically silent molecular substitutions exert no significant influence on survival and reproduction and drift randomly through the species (Kimura 1987). Neutral (or closely so) molecular variation together with population genetics theory offers powerful tools for ecological research. Dynamics of allele frequency change is determined by demographic parameters such as population size, population subdivision, breeding structure and family relations. All these parameters are ecological by definition.
A variety of neutral molecular markers, including mini- and microsatellites, different kinds of restriction fragments, PCR-markers and DNA sequences are available today for studying ecology and evolution (Moritz & Hillis 1996). The markers can be applied to evaluate evolutionary rates, processes and constraints on molecular change through time or to make inferences about population processes, systematics and phylogeny.
Since the idea of the molecular clock was proposed by Zuckerkandl and Pauling (1965), dating of past evolutionary events has been attempted based on the assumption that the molecular evolutionary rate is constant and equal to the mutation rate of neutral markers (Kimura 1987). However, molecular evolutionary rate does not appear to change linearly with time. Different DNA sequences, for example, evolve at different rates. This observation holds true across nucleotide positions, among nonhomologous genes within a lineage, among classes of DNA within a genome, and among genomes within an organismal lineage (Avise 1994). Separate calibrations of the molecular clock are needed for the specific organism and DNA region of interest. One example of the use of a molecular clock was dating the roots of human mitochondrial DNA tree to 200 000 years ago, and suggesting an African origin for the modern humans (Cann et al. 1987).
At least some degree of genetic differentiation of populations is usually found at some geographic scale. This differentiation may be caused by a number of factors, including social structure, mating system, dispersal ability, association of parents with their offspring, and habitat fragmentation, which in turn, lead to certain patterns of gene flow, genetic recombination, natural selection and random drift. When the haplotypes and phylogeny are superimposed over geographical locations the term ‘phylogeography’ has been introduced (Avise 1994).
Studying gene flow (genetically effective dispersal) in relation to the magnitude and spatial scale over which populations differ genetically offers a possibility to establish a link between the ecology and evolution of species. Understanding the microevolutionary forces throughout the history of a species depends on quantification of how gene flow interacts with genetic drift, mutation and natural selection in forming spatial or temporal population structures (Bohonak 1999).
Molecular analyses of population structure and gene flow between subpopulations have been conducted for hundreds of species at a variety of temporal and spatial scales. Currently the most commonly used neutral or nearly neutral markers for studying population structure are microsatellites (e.g., subdivision of South African buffalo populations, Syncerus caffer, caused by habitat fragmentation; O’Ryan et al. 1998, philopatry and genetic differentiation in European harbor seals, Phoca vitulina vitulina; Goodman 1998) and mitochondrial DNA in animals (e.g., male-biased gene flow between rookeries of Australian green turtles, Chelonia mydas; FitzSimmons et al. 1997, lack of phylogeographic structure in Australian red kangaroo, Macropus rufus; Clegg et al. 1998, uniformity of the snapping turtle, Chelydra serpentina, populations; Walker et al. 1998) and chloroplast DNA in plants (e.g., recognition of three refugial sources of European oaks Quercus robur and Quercus petrea; Ferris et al. 1998).
The concept of effective population size (Ne) was first introduced by Wright (1931) referring to the size of an idealised model population that has the same genetic properties as observed for the real population. It is one of the most important parameters in population genetics. Under strict neutral theory, the molecular variability of a population is a function of the effective population size, mutation rate and gene flow (Kimura & Ohta 1971b). Usually the effective population size is much smaller than the census size. The ratio of effective population size to census size average only 0.1 when fluctuations in population size, variance in family size and unequal sex ratios are included (reviewed in Frankham 1995). Several factors affect the prediction of the effective population size, such as sex ratio, mating system, selection, pattern of inheritance, changes of the population size over generations, and population subdivision (Caballero 1994). The estimation of the effective population size has important applications in evolutionary studies, in conservation biology and in breeding programs (Wang & Caballero, 1999). Mitochondrial DNA polymorphism can be used to determine the long-term female effective population size when the mutation rate is known. In Avise et al. (1988) all the three species studied (American eel ,Anguilla rostrata; hardhead catfish, Arius felis; red-winged blackbird Agelaius phoeniceus) had smaller long-term effective population sizes than present-day census sizes.
Change in population size can be detected by examining the patterns of genetic polymorphism. The number of segregating sites (number of polymorphic nucleotides per nucleotide site) is influenced by the current population size more strongly than is the average number of nucleotide differences, while the average number of differences is affected by the historical population size more than the number of segregating sites (Tajima 1989a). The distribution of pairwise genetic differences can also be used for detecting population expansion or decline (Rogers & Harpending 1992, Rogers 1995), though it is possible that this method is insensitive to further changes in population size. Lavery et al. (1996) studied the sequence divergence in coconut crabs (Birgus largo) and noted that the effects of more recent events may not be detectable if the population is not in genetic equilibrium due to past growth events.
In addition to detecting growth or decline of a population, the size and length of a fairly recent population bottleneck can be estimated using the genetic data obtained from natural populations as was done with the endangered elephant seals, Mirounga angustirostrus (Hedrick 1995).
Phylogeny is a stream of gene transmission that flows from generation to generation and continues through conspecific populations, subspecies and species to higher taxonomic levels. Based on this idea, the microevolutionary processes described above can to some extent be applied to explain macroevolutionary differences of higher taxa (Avise et al. 1987).
The coalescent theory is a population genetic model of neutral evolution applied usually to interbreeding populations, instead to different taxa like the phylogenetic methods (Tajima 1983). The coalescent approach is based on modelling mutational processes that occur along lineages. As long as the mutation rate is not zero, more closely related sequences will tend to be more similar. A backward temporal perspective is adopted, thus the name coalescent theory (Harvey & Nee 1996). Coalescence occurs at some point in the past between all pairs of individual lineages and in each generation that a coalescence occurs the number of ancestral stages is reduced by one, generating a bifurcating coalescence tree (Harding 1996).
The phylogenetic approach can be used to help find answers to a variety of evolutionary biology questions. In addition to resolving the taxonomic relationships of species, phylogenetics can be used to study the evolution of gene families (e.g. Zhang & Nei 1996, Johnston et al. 1998), evaluate evolutionary rates in different lineages (e.g. Kocher et al. 1989, Pamilo & O’Neill 1997), date past historical events (e.g. Cann et al. 1987, Klicka & Zink 1997), study the coevolution of host-parasite relationships (Hafner et al. 1994, Page et al. 1998), and clarify the sources of epidemic diseases (e.g. Zhu et al. 1998, Taubenberger et al. 1997).