Abstract

Molecular data are now commonly used in taxonomy for delimiting cryptic species. In the case of giraffes, which were treated as a single species (Giraffa camelopardalis) during half of a century, several molecular studies have suggested a splitting into four to seven species, but the criteria applied for taxonomic delimitation were not fully described. In this study, we have analysed all multi-locus DNA sequences available for giraffes using multispecies coalescent (MSC: *BEAST, BPP and STACEY), population genetic (STRUCTURE, allelic networks, haplotype network and bootstrapping, haplowebs and conspecificity matrix) and phylogenetic (MrBayes, PhyML, SuperTRI) methods to identify the number of species. Our results show that depending on the method chosen, different taxonomic hypotheses, recognizing from two to six species, can be considered for the genus Giraffa. Our results confirm that MSC methods can lead to taxonomic over-splitting, as they delimit geographic structure rather than species. The 3-species hypothesis, which recognizes G. camelopardalis sensu strico A, G. giraffa, and G. tippelskirchi, is highly supported by phylogenetic analyses and also corroborated by most population genetic and MSC analyses. The three species show high levels of nucleotide divergence in both nuclear (0.35–0.51%) and mitochondrial sequences (3–4%), and they are characterised by 7 to 12 exclusive synapomorphies (ES) detected in nine of the 21 nuclear introns analysed for this study. By contrast, other putative species, such as G. peralta, G. reticulata, G. thornicrofti or G. tippelskirchi sensu stricto, do not exhibit any ES in the nuclear genes. A robust mito-nuclear conflict was found for the position and monophyly of G. giraffa and G. tippelskirchi, which is interpreted as the result of a mitochondrial introgression from Masai to southeastern giraffe during the Pleistocene and nuclear gene flow mediated by male dispersal between southern populations (subspecies G. g. giraffa and G. g. angolensis).

Highlights

  • Speciation implies reproductive isolation through barriers preventing or limiting gene flow between populations [1]

  • The results of other analyses (ML bootstrap [Bootstrap percentages (BP)] and SuperTRI indices [supertree bootstrap percentages (SBPs)/mean posterior probabilities (MPP)/ NRep]) are indicated only for the nodes supported by posterior probability (PP) values 0.9, as well as for nodes discussed in the text

  • Within Giraffa, 19 nodes are supported by posterior probabilities (PP) 0.9 in the Bayesian tree of the nuDNA supermatrix (Fig 1A; Fig Y in S2 Appendix), but only three of them are associated with BP > 90: (1) the clade here named G. camelopardalis sensu stricto A, which groups together all members of the subspecies camelopardalis, antiquorum, peralta, reticulata, and rothschildi (PP = 1; BP = 100); (2) G. giraffa, including all members of the subspecies angolensis and giraffa (PP = 1; BP = 100); and (3) G. tippelskirchi, comprising all members of the subspecies thornicrofti and tippelskirchi (PP = 1; BP = 100)

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Summary

Introduction

Speciation implies reproductive isolation through barriers preventing or limiting gene flow between populations [1]. The maternal inheritance of the mtDNA genome can be misleading for species delimitation in mammals, because females and males have usually different dispersal behaviours (female philopatry versus male dispersal) [5, 6], and because interspecific hybrid females are generally fertile, whereas hybrid males are often sterile (Haldane’s rule), facilitating mitochondrial introgression between closely related species [7,8,9] To overcome these limitations, most recent taxonomic studies dealing with the delimitation between cryptic mammal species have focused on multi-locus datasets [10,11,12], as the use of multiple independent DNA markers has been shown to provide a strong and reliable signal for deciphering relationships among closely related taxa [13, 14]. Allele-sharing methods, such as haplowebs [30] and conspecificity matrix (CM) [31], can be used to detect reproductively isolated populations

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