Combination of the targeted amplification of nuclear introns and the analysis of single-stranded conformational polymorphisms has the potential to provide an inexpensive, rapid, versatile and sensitive genetic assay for evolutionary studies and conservation. We are developing primers and protocols to analyse nuclear introns in vertebrates, and are testing them in a population genetic study of marbled murrelets Brachyramphus marmoratus. Here we present protocols and results for introns for aldolase B, alpha-enolase, glyceraldehyde-3-phosphate dehydrogenase and lamin A. Results suggest that this approach presents a potentially powerful method for detecting genetic variation within and among local populations and species of animals: (i) a variety of genes can be surveyed, including genes of special interest such as those involved in disease resistance; (ii) assays are rapid and relatively inexpensive; (iii) large numbers of genes can be assayed, enabling accurate estimation of variation in the total genome; (iv) almost any mutation can be detected in the genes amplified; (v) the exact nature of variation can be investigated by sequence analysis if desired; (vi) statistical methods previously developed for proteins and/or sequence data can be used; (vii) protocols can be easily transferred to other species and other laboratories; and (viii) assays can be performed on old or degraded samples, blood or museum skins, so that animals need not be killed. Results of analyses for murrelets support earlier evidence that North American and Asiatic subspecies represent reproductively isolated species, and that genetic differences exist among murrelets from different sites within North America.
Although phylogenetic hypotheses can provide insights into mechanisms of evolution, their utility is limited by our inability to differentiate simultaneous speciation events (hard polytomies) from rapid cladogenesis (soft polytomies). In the present paper, we tested the potential for statistical power analysis to differentiate between hard and soft polytomies in molecular phytogenies. Classical power analysis typically is used a priori to determine the sample size required to detect a particular effect size at a particular level of significance (a) with a certain power (1 - β). A posteriori, power analysis is used to infer whether failure to reject a null hypothesis results from lack of an effect or from insufficient data (i.e., low power). We adapted this approach to molecular data to infer whether polytomies result from simultaneous branching events or from insufficient sequence information. We then used this approach to determine the amount of sequence data (sample size) required to detect a positive branch length (effect size). A worked example is provided based on the auklets (Charadriiformes: Alcidae), a group of seabirds among which relationships are represented by a polytomy, despite analyses of over 3000 bp of sequence data. We demonstrate the calculation of effect sizes and sample sizes from sequence data using a normal curve test for difference of a proportion from an expected value and a t-test for a difference of a mean from an expected value. Power analyses indicated that the data for the auklets should be sufficient to differentiate speciation events that occurred at least 100,000 yr apart (the duration of the shortest glacial and interglacial events of the Pleistocene), 2.6 million years ago.
Abstract.-Although phylogenetic hypotheses can provide insights into mechanisms of evolution, their utility is limited by our inability to differentiate simultaneous speciation events (hard polytomies) from rapid cladogenesis (soft polytomies). In the present paper, we tested the potential for statistical power analysis to differentiate between hard and soft polytomies in molecular phylogenies. Classical power analysis typically is used a priori to determine the sample size required to detect a particular effect size at a particular level of significance («) with a certain power (1 -~). A posteriori, power analysis is used to infer whether failure to reject a null hypothesis results from lack of an effect or from insufficient data (i.e., low power). We adapted this approach to molecular data to infer whether polytomies result from simultaneous branching events or from insufficient sequence information. We then used this approach to determine the amount of sequence data (sample size) required to detect a positive branch length (effect size). A worked example is provided based on the auklets (Charadriiformes: Alcidae), a group of seabirds among which relationships are represented by a polytomy, despite analyses of over 3000 bp of sequence data. We demonstrate the calculation of effect sizes and sample sizes from sequence data using a normal curve test for difference of a proportion from an expected value and a t-test for a difference of a mean from an expected value. Power analyses indicated that the data for the auklets should be sufficient to differentiate speciation events that occurred at least 100,000 yr apart (the duration of the shortest glacial and interglacial events of the Pleistocene), 2.6 million years ago.
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