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Systematics of the Southeast Asian mongooses (Herpestidae,Carnivora): solving the mystery of the elusive collared mongoose and Palawan mongoose 下载免费PDF全文
Géraldine Veron Marie‐Lilith Patou Regis Debruyne Arnaud Couloux Desamarie Antonette P. Fernandez Siew Te Wong Jérome Fuchs Andrew P. Jennings 《Zoological Journal of the Linnean Society》2015,173(1):236-248
Although recent molecular studies have clarified the phylogeny of mongooses, the systematics of the Southeast Asian species was incomplete as the collared mongoose Urva semitorquata and some debatable taxa (Hose's mongoose, Palawan mongoose) were missing in the analyses. We sequenced three mitochondrial (cytochrome b, ND2, control region) and one nuclear (beta‐fibrinogen intron 7) fragments of the Southeast Asian mongooses to clarify the systematic position of the different species and populations occurring in this region. Our results showed that the collared mongoose is closely related to the crab‐eating mongoose Urva urva, these two species forming a sister‐group to the short‐tailed mongoose Urva brachyura. Despite Sumatran collared mongooses having a peculiar orange phenotype, we showed that they exhibited very little genetic divergence to individuals from Borneo. In contrast, the populations of the short‐tailed mongoose from Borneo were strongly divergent to those from Peninsular Malaysia and Sumatra, and these might represent separate species. Within the crab‐eating mongoose, we observed little geographical genetic structure. Our study suggests that Hose's mongoose is not a valid species. The Palawan mongooses did not cluster with the other populations of the short‐tailed mongoose; they were closer to the collared mongoose and should be included in this species. © 2014 The Linnean Society of London 相似文献
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Distance-based methods are popular for reconstructing evolutionary trees thanks to their speed and generality. A number of methods exist for estimating distances from sequence alignments, which often involves some sort of correction for multiple substitutions. The problem is to accurately estimate the number of true substitutions given an observed alignment. So far, the most accurate protein distance estimators have looked for the optimal matrix in a series of transition probability matrices, e.g. the Dayhoff series. The evolutionary distance between two aligned sequences is here estimated as the evolutionary distance of the optimal matrix. The optimal matrix can be found either by an iterative search for the Maximum Likelihood matrix, or by integration to find the Expected Distance. As a consequence, these methods are more complex to implement and computationally heavier than correction-based methods. Another problem is that the result may vary substantially depending on the evolutionary model used for the matrices. An ideal distance estimator should produce consistent and accurate distances independent of the evolutionary model used. 相似文献7.
Background
Profile hidden Markov model (HMM) techniques are among the most powerful methods for protein homology detection. Yet, the critical features for successful modelling are not fully known. In the present work we approached this by using two of the most popular HMM packages: SAM and HMMER. The programs' abilities to build models and score sequences were compared on a SCOP/Pfam based test set. The comparison was done separately for local and global HMM scoring. 相似文献8.
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