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      Multigene phylogeny of the Mustelidae: Resolving relationships, tempo and biogeographic history of a mammalian adaptive radiation

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          Abstract

          Background

          Adaptive radiation, the evolution of ecological and phenotypic diversity from a common ancestor, is a central concept in evolutionary biology and characterizes the evolutionary histories of many groups of organisms. One such group is the Mustelidae, the most species-rich family within the mammalian order Carnivora, encompassing 59 species classified into 22 genera. Extant mustelids display extensive ecomorphological diversity, with different lineages having evolved into an array of adaptive zones, from fossorial badgers to semi-aquatic otters. Mustelids are also widely distributed, with multiple genera found on different continents. As with other groups that have undergone adaptive radiation, resolving the phylogenetic history of mustelids presents a number of challenges because ecomorphological convergence may potentially confound morphologically based phylogenetic inferences, and because adaptive radiations often include one or more periods of rapid cladogenesis that require a large amount of data to resolve.

          Results

          We constructed a nearly complete generic-level phylogeny of the Mustelidae using a data matrix comprising 22 gene segments (~12,000 base pairs) analyzed with maximum parsimony, maximum likelihood and Bayesian inference methods. We show that mustelids are consistently resolved with high nodal support into four major clades and three monotypic lineages. Using Bayesian dating techniques, we provide evidence that mustelids underwent two bursts of diversification that coincide with major paleoenvironmental and biotic changes that occurred during the Neogene and correspond with similar bursts of cladogenesis in other vertebrate groups. Biogeographical analyses indicate that most of the extant diversity of mustelids originated in Eurasia and mustelids have colonized Africa, North America and South America on multiple occasions.

          Conclusion

          Combined with information from the fossil record, our phylogenetic and dating analyses suggest that mustelid diversification may have been spurred by a combination of faunal turnover events and diversification at lower trophic levels, ultimately caused by climatically driven environmental changes. Our biogeographic analyses show Eurasia as the center of origin of mustelid diversity and that mustelids in Africa, North America and South America have been assembled over time largely via dispersal, which has important implications for understanding the ecology of mustelid communities.

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          Most cited references206

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          Molecular Cloning : A Laboratory Manual

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            Trends, rhythms, and aberrations in global climate 65 Ma to present.

            Since 65 million years ago (Ma), Earth's climate has undergone a significant and complex evolution, the finer details of which are now coming to light through investigations of deep-sea sediment cores. This evolution includes gradual trends of warming and cooling driven by tectonic processes on time scales of 10(5) to 10(7) years, rhythmic or periodic cycles driven by orbital processes with 10(4)- to 10(6)-year cyclicity, and rare rapid aberrant shifts and extreme climate transients with durations of 10(3) to 10(5) years. Here, recent progress in defining the evolution of global climate over the Cenozoic Era is reviewed. We focus primarily on the periodic and anomalous components of variability over the early portion of this era, as constrained by the latest generation of deep-sea isotope records. We also consider how this improved perspective has led to the recognition of previously unforeseen mechanisms for altering climate.
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              MrBayes 3: Bayesian phylogenetic inference under mixed models.

              MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models. This allows the user to analyze heterogeneous data sets consisting of different data types-e.g. morphological, nucleotide, and protein-and to explore a wide variety of structured models mixing partition-unique and shared parameters. The program employs MPI to parallelize Metropolis coupling on Macintosh or UNIX clusters.
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                Author and article information

                Journal
                BMC Biol
                BMC Biology
                BioMed Central
                1741-7007
                2008
                14 February 2008
                : 6
                : 10
                Affiliations
                [1 ]Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, 90095-1606, USA
                [2 ]Postnet Suite 230, Private Bag X18, Rondebosch, 7701, Republic of South Africa
                [3 ]Caesar Kleberg Wildlife Research Institute, MSC 218, 700 University Boulevard, Texas A and M University-Kingsville, Kingsville, TX 78363, USA
                [4 ]Grupo de Ecología Comportamental de Mammiferos (GECM), Cátedra Fisiología Animal, Departamento de Biología, Bioquímica y Farmacia, Universidad Nacional del Sur – CONICET, San Juan 670, 8000 Bahía Blanca, Argentina
                [5 ]Muséum National d'Histoire Naturelle, Département Systématique et Evolution, CP 51 USM 601-UMR 5202, Origine, Structure et Evolution de la Biodiversité, 57 Rue Cuvier, 75231 Paris Cedex 05, France
                Article
                1741-7007-6-10
                10.1186/1741-7007-6-10
                2276185
                18275614
                63192504-076a-48f2-9850-80d1bb621836
                Copyright © 2008 Koepfli et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 29 January 2008
                : 14 February 2008
                Categories
                Research Article

                Life sciences
                Life sciences

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