Seahorse Hippocampus Hypothesis

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Seahorse Hippocampus Introduction
Seahorses are a prime example of species whose atypical biology and unusual global distribution leads to a series of evolutionary questions. Seahorses (genus Hippocampus) are a marine species that have extensively been studied because of their abnormal behaviors in the marine environment compared to other marine creatures. Many of the seahorse species have large ranges, both longitudinally (over a great horizontal distance across the ocean), and latitudinal (great vertical distance within the ocean), regardless of the fact that they are characterized as weak swimmers and lack any large structural fins for efficient swimming (Lourie et al., 1999a). Although they do have these large range environments, seahorses …show more content…

The first goal was to accumulate the molecular phylogeny data for seahorses using the cytochrome b gene sequence information (S.P. Casey et al, 2004). In this particular study, the cytochrome b gene was used to investigate whether or not the Hippocampus was indeed pre-Tethyan in origin and to illuminate the relationship between Indo-Pacific and Atlantic seahorse species. Molecular markers like the cytochrome b gene were used to survey dispersal of seahorse species and to temporally define the evolutionary processes since much of the seahorse fossil record is deficient (Lourie et al., …show more content…

For the original analysis, the corrected pairwise distance will be calculated using the Jukes–Cantor and the Maximum Composite Likelihood Model. The Jukes–Cantor model assumes that the rate of nucleotide substitution or all nucleotides (C, A, T and G) are equal, that nucleotide frequencies are equal, that there is an equal rate of substitution among sites, and does not correct for the lower rate of transversion substitutes in comparison to transitional substitutions (Jukes and Cantor, 1969). The Maximum Composite Likelihood takes into account the phylogenic relationship between sequences, using the sum of the log likelihoods of the bases as the composite likelihood. Both pair wise distances and substitution parameters are estimated using the Maximum Composite Likelihood (Tamura et al. 2004). Both models should yield different maximum sequence divergence and average divergence that can then be compared to the original paper. With sequence divergence data, the temporal origin of the genus can be identified. The two alternate models to the Kimura-2 parameter will be analyzed to discuss which methods yield results closest to the expected time origin of the genus

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