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In contrast to Co, Tpi yields an almost reverse maximum likelihood genealogy in which H. melpomene forms a monophyletic group within a paraphyletic Heliconius cydno.
Our search for the maximum likelihood genealogy, in which 121 terminals had mtCR and mtATP (842 bp) concatenated, resulted in a tree with LnL −9497.713.
The maximum likelihood genealogy suggests that many identical or nearly identical sequences are shared between the two species in Panama, both of which populations are strongly differentiated from H. melpomene from French Guiana (Fig. 3).
Trees based on only intron or only exon sequences show the same deep divergence between the two clades (Additional File 2: ExonIntronTree.pdf), as do regional trees based on 5', middle and 3' regions of the desaturase gene (Additional File 3: RegionalTrees.pdf) and the maximum likelihood genealogy (Additional File 4: MaximumLiklihoodTree.pdf).pdf
As expected if allelic coalescence has occurred more recently than the split between the two species, the maximum likelihood genealogy for Co is consistent with reciprocal monophyly for H. melpomene and H. cydno, with 2.5 3.0% net divergence between species compared to < 1.3% uncorrected divergence within populations, and 0.4% net divergence between H. melpomene races (Table 2).
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Maximum likelihood genealogies of these loci were found with an LnL of −1196.07 and −1337.985 for Mitf and Xsrc respectively.
For the nuclear sequence loci, models of evolution and maximum likelihood genealogies were estimated for each locus using Treefinder as above (Mitf: HKY; Xsrc: HKY + Γ).
However, although mutual monophyly is not ruled out using the Co and Tpi fragments studied here, maximum likelihood genealogies of both genes suggest that species paraphyly is as, or more, likely.
We downloaded the sequence data from the HCV sequence database [ 33] and inferred the corresponding maximum-likelihood genealogy using the TREEFINDER program [ 34].
Unfortunately, the sequence of the closest species, D. moschata, is too distant to be used as an adequate outgroup in an unrooted analysis such as the maximum-likelihood genealogy of Figure 1B.
Bayesian inference may be more accurate and efficient at sampling genealogy space than maximum likelihood approaches for many datasets [47].
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