kept at the Paris Zoo (Parc Zoologique de Paris-Vincennes, France). DNA was extracted primarily using kits (Qiagen), or standard phenol-chloroform methods [70]; samples of dung were extracted with DNA using a QIAmp DNA Stool Mini Kit (Qiagen). Microsatellite loci Fifteen microsatellite loci were amplified (Supplementary Table S1). Five loci were from published sources [71,72]; six loci were tetra-nucleotide microsatellites isolated from a savanna elephant using a capture hybridization method as previously described [73], with their sequences deposited in GenBank (accession numbers JF692777–JF692782); four loci with STRs were identified in savanna elephant DNA sequences mined from the NIH Com- parative Vertebrate Sequencing Project (http://www.nisc.nih. gov/open_page.cgi?path = /projects/comp_seq.html). Microsatel- lites were identified using a repeat finder script written in Perl. PCR primers for novel STR loci were designed using Primer3 (http://fokker.wi.mit.edu/primer3/input.htm). PCR primers were tagged for fluorescence detection [74]. PCR amplification used a touchdown protocol as previously described [75]. Samples were genotyped on an ABI 3100 Genetic Analyzer and analyzed with Genescan 3.7 and Genotyper 2.5 programs (Applied Biosystems). Microsatellite data was binned in Allelogram [76] (http://code. google.com/p/allelogram). A total of 15 loci were amplified in 555 African and 9 Asian elephants. The data was analyzed for deviation from Hardy– Weinberg equilibrium or excess of alleles using Cervus 3.0 [77] (http://www.fieldgenetics.com/pages/aboutCervus_Overview. jsp). Two of the novel loci developed for this study from a capture hybridization library (LAF4 and LAF6, also designat- ed p04 and p06) were excluded from some analyses because they exhibited an excess of homozygosity due to alleles. Loci were examined for linkage using GENEPOP [78] (http://genepop.curtin.edu.au). Loci LAF30 and LAF35 (also designated p30 and p35, respectively) were excluded because of potential linkage to the more diverse loci LAF29 (p29) and LAF37 (p37), respectively. Microsatellite analyses We used the program STRUCTURE 2.3.1 to apply a model- based clustering algorithm to identify subgroups of individual elephants that have distinctive allele frequencies [30,79]. Each combination of species or locales was run 5 times using values of K between 1 and 21 genetic clusters, without any prior population information. Each analysis was run for at least 1 million Markov chain Monte Carlo generations following a burn-in of at least 100,000 steps. STRUCTURE was run using four models [30] combining assumptions on the genetic ancestry of individuals (i.e. the genome of a given individual is allowed –or not– to originate from more than one genetic cluster) and the genetic relatedness among populations (i.e. in the case of recent population subdivision allele frequencies in different populations are correlated): admixture–correlated, admixture–independent, no admixture–correlated, and no admixture–independent; with an inferred Dirichlet a parameter for population admixture (low a values suggest that most individuals do not have an admixed genome, while a.1 indicates that most individuals are of admixed genetic ancestry). Results were similar in each case. We estimated the uppermost hierarchical level of clusters using the ad hoc statistic DK based on the rate of change in the log probability of the data between successive values of K [31]. A multivariate representation of the analyzed individuals was carried out by subjecting data from 11 STR loci to Factorial Correspondence Analysis (FCA) in Reconciling African Elephant Phylogenies GENETIX 4.02 [35]. Genetic relationships among sampling locales were estimated using the chord distance [80] calculated in GenoDive [81], and visualized on a neighbor-joining tree [82] calculated in PAUP* 4b10 [83]. Mitochondrial DNA sequencing and analyses PCR amplifications using DNA from Bili Forest (BF) elephants were performed using 0.4 uM final concentration of each primer, 1.5 mM MgCl2, 200 uM of each dNTP (Applied Biosystems Inc. [ABI]) and 1 ug/ul final concentration of bovine serum albumin (BSA; New England BioLabs Inc.) with 0.04 units/ul final concentration of AmpliTaq Gold DNA Polymerase (ABI). PCR consisted of an initial denaturation at 95uC for 9:45 min; cycles of denaturation for 20 sec at 94uC, annealing for 30 sec at 60u (initial 3 cycles), 58uC, 56uC, 54uC, 52uC (5 additional cycles each temperature), or 50uC (last 22 cycles), and 1 min extension at 72uC; with a final extension of 7 min at 72uC. PCR amplicons were examined on a 1% agarose gel and were enzyme-purified and sequenced using the BigDye Terminator v3.1 Cycle Sequencing Kit (ABI). Eight BF samples were successfully amplified and sequenced with amplicon sizes of 726 bp (681 bp excluding primers) or 375 bp (322 bp excluding primers), using the following primers: for the 726 bp amplicon, PCR primers were CBCR-F5 AT- TACAATGGTCTTGTAAGCCATAAA and CBCR-R1d CTC- AGACGGCCATAGCTGA; sequencing used the PCR primers and CBCR-F6 GATAAACCATAGTCTTACATAGCACAT and CBCR-R5 CTTTAATGTGCTATGTAAGACTATGG. For the 375 bp amplicon, PCR and sequencing primers consisted of CBCR- F5 and -R5. Novel mtDNA sequences have been deposited in Genbank (accession numbers: JF827273–JF827275). NCBI Blast (http://www.ncbi.nlm.nih.gov/blast/Blast.cgi) and comparison to previously sequenced elephant mtDNA were used to identify all BF elephant mtDNA sequences as F clade (Supplementary Figure S2). Fisher’s exact test (two-tailed; http://www.graphpad.com/quick- calcs/contingency1.cfm) was used to analyze a 262 contingency table for association between the presence or absence of S clade mtDNA and the type of habitat at a locale (tropical forest vs. non- tropical forest or mixed). Shannon Information Content Shannon Information Content (SIC) measures the amount of information contained in a message [43]. The greater the information in a message, the less random noise it contains, so the information can be referred to as a reduction in uncertainty [45]. Information thus becomes a measure of the improbability of an event. Specifically, Shannon defined information in terms of the base-2 logarithm of the reduction in uncertainty [45]. In terms of genetic markers, a very improbable allele in a locus is therefore assigned very high information content, since the information is comprised of the uncertainty that is eliminated by the appea- rance of the allele. The SIC considers the influence of centrality, whereby alleles that are absent (or nearly so) in one population are more informative than those common in both populations. SIC has been successfully adapted to genetic studies, particu- larly for identifying genetic markers with frequencies highly specific for human populations of different geographic origins; which are used in admixture mapping of the human genome [42], a proven approach for mapping genetic variants that are involved in human disease [84]. In order to quantify the ability of different genetic markers to distinguish between elephants from different species and different regions or locales, we applied a routine described in Smith and O’Brien (2005) [42] to determine the Shannon Information Content. This was implemented in the statistical package SAS 9.1 (SAS Inc., Cary, NC), while Microsoft PLoS ONE | www.plosone.org 14 June 2011 | Volume 6 | Issue 6 | e20642