Abstract

Hyracoids have been allied with either perissodactyls or tethytheres (i.e., Proboscidea + Sirenia) based on morphological data. The latter hypothesis, termed Paenungulata, is corroborated by numerous molecular studies. However, molecular studies have failed to support Tethytheria, a group that is supported by morphological data. We examined relationships among living paenungulate orders using a multigene data set that included sequences from four mitochondrial genes (12S rRNA, tRNA valine, 16S rRNA, cytochrome b) and four nuclear genes (aquaporin, A2AB, IRBP, vWF). Nineteen maximum-likelihood models were employed, including models with process partitions for base composition and substitution parameterizations. With the inclusion of partitions with a heterogeneous base composition, 18 of 19 models favored Hyracoidea + Sirenia. All 19 models favored Hyracoidea + Sirenia after excluding heterogeneous base composition partitions. Most of the support for Hyracoidea + Sirenia derived from the mitochondrial genes (bootstrap support ranged from 51 to 99%); Tethytheria, in turn, received 0 to 19% support in different analyses. Bootstrap support deriving from the nuclear genes was more evenly split among the competing hypotheses (3 to 45% for Tethytheria; 17.5 to 62% for Hyracoidea + Sirenia). Lineage-specific rate variation among both mitochondrial and nuclear genes may contribute to the different results that were obtained with mitochondrial versus nuclear data. Whether Tethytheria or a competing hypothesis is correct, short internodes on the molecular phylogenies suggest that paenungulate orders diverged from each other over a 5- to 8-million-year time window extending from the late Paleocene into the early Eocene. We also used likelihood-ratio tests to compare different models of sequence evolution. A gamma distribution of rates results in a greater improvement in likelihood scores than does an allowance for invariant sites. Twenty-one rate partitions corresponding to stems, loops, and codon positions of different genes result in higher likelihood scores than a gamma distribution of rates and/or an allowance for invariant sites. Process partitions of the data that incorporate base composition and substitution parameterizations result in significant improvements in likelihood scores in comparison to models that allow only for relative rate differences among partitions.

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