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• W1978791818 abstract "In a recent review (Zink & Barrowclough 2008, hereafter ZB08), we pointed out that elementary population genetics reveals that mitochondrial DNA (mtDNA) is a leading indicator, vis-à-vis nuclear loci, of population divergence. Our review was prompted by the appearance of a number of phylogeography studies reporting mitochondrial and nuclear (usually microsatellite) results in which there was less nuclear than mitochondrial structure. Some authors were ascribing the divergent results to natural history differences, sex-biased dispersal behaviour and other post-hoc explanations, or to pathological problems with mitochondrial variation. However, we felt that a proper null hypothesis was that such heterogeneous mtDNA vs. nuclear DNA (nuDNA) behaviour was to be expected and that there was an onus on researchers to first establish that the difference in coalescent times between mitochondrial and nuclear loci was not responsible for the divergent results. It appeared that some researchers thought microsatellites evolved faster than mtDNA and consequently should show more structure, but this represents a confusion of substitution rate with coalescent time. In ZB08, we developed an analogy between coalescent times and leading and lagging economic indicators, provided a table describing when congruence and conflict were to be anticipated between loci, listed potential sources of false positive and false negative signals and provided simple equations describing the relative dynamics of nuDNA and mtDNA differentiation. We surveyed the literature of avian phylogeographic publications and, based on this meta-analysis, concluded that, in a search for vicariant geographical signal, ‘mtDNA is the molecule of choice’. Given neutral DNA variation (traits under positive selection are a leading indicator, compared with neutral ones: ZB08), we believe that mtDNA sequences are sufficient for the discovery of differentiated taxa. In this issue of Molecular Ecology, Edwards & Bensch (2009, hereafter EB09) comment on ZB08 and rise to the defence of nuDNA sequences in phylogeography. Although they agree with us about the analytical difficulties associated with microsatellites, they emphasize the advantages of sequence data from multiple nuclear loci over mitochondrial sequence. In doing so, EB09 are reframing the argument from one of the efficacy of tools for taxic discovery to a pejorative statement about old-fashioned mitochondria vs. the au courant nucleus. They state that mtDNA is ‘a tool that has proven extremely useful, but is ultimately limited, and that can now be supplemented relatively easily by the enormous signal available in the many loci of the nuclear genome’. For the present, ZB08’s literature survey indicated that mtDNA’s limitations were, at best, underwhelming. Unless we acquiesce to EB09’s resetting of the agenda of phylogeography to be equivalent to that of population genetics, we are not sure how often their ‘supplement’ is required. That is, we maintain that there is a distinction between the endeavours of phylogeography and population genetics. The major theme of ZB08 flows from the well-established observation that differences in Ne result in an approximate fourfold reduction in expected coalescent time of mtDNA over nuDNA, rendering the latter a relatively lagging indicator of phylogeographic divergence, and opening a temporal window during which mtDNA variation would capture vicariant signal that nuDNA data would miss. EB09 counter that observation with a claim that what is lost in coalescent time ‘one gains back by many orders of magnitude from adding additional nuclear genes to this signal’. This is a bold conjecture, but its empirical truth is as yet unknown. Also, the ‘gain’ is not very clear to us, because one’s measure of ‘gain’ will depend on the timescale of the divergence events, and particularly on the nature of the questions that motivate the research in the first place; with ‘orders of magnitude’ being a hyperbole. In the case of taxon discovery, the actual usefulness of nuDNA depends on the compromise between the numbers of independent nuclear loci required to overcome the ‘coalescent lag’ and their cost of production. When many such studies are published, the nature of the tradeoff and the truth of their prediction will become apparent. Currently there are few studies, at least in birds, of multiple nuclear sequences that approach the geographical comprehensiveness of even a routine mitochondrial phylogeographic study. The most extensive nuDNA plus mtDNA sequencing study of a bird to date is Lee & Edwards (2008) study of the red-backed fairy wren (Malurus melanocephalus). This Australian bird is distributed across northeastern Queensland and the Northern Territory; it is generally considered to comprise two subspecies that intergrade southeast of Cape York (Higgins et al. 2001). Related species were used as outgroups. Lee & Edwards (2008) sequenced 35 nuclear loci (29 anonymous: 12.8 kb and six introns: 2.2 kb) and around half of a mitochondrial gene (467 bp of ND2) for a total of 29 individuals (an average of <3 birds/locality). Although EB09 view the topology of individual gene trees as a ‘nuisance parameter’, they showed the mtDNA and three nuclear gene trees. The sequenced fraction of the mitochondrial gene resulted in a tree with a monophyletic red-backed fairy wren, which was divided into three major clades with bootstrap values of 75–99%, and a monophyletic sister-species, the white-winged fairy wren (Malurus leucopterus; Fig. 1). The three clades of the red-backed fairy wren corresponded to regions termed ‘Top End’ (TE), ‘Cape York’ (CY) and ‘Eastern Forest’ (EF), but with some haplotypes shared between regions. Shared identical haplotypes might be due to recent hybridization and gene flow, shared ancestral polymorphism (incomplete lineage sorting) or homoplasy. In this case, it seems clear that the sharing is due to gene flow because the high bootstrap values on the three clades make either incomplete lineage sorting or homoplasy vanishingly unlikely (i.e. it would require one-for-one parallelism across the clades without any reversals or autapomorphies). The bootstrap values, plus the shared terminal haplotypes, strongly suggest separate evolutionary histories (divergence) of these three areas, coupled with modest introgression. Although ZB08 did not consider vicariance as a process per se—we tend to view trees as pattern and phylogeography as the discovery of geographical pattern—we do agree with EB09 that this is the appropriate inference given the mtDNA gene tree. Neighbour-joining tree computed with mega4 (Tamura et al. 2007) using p-distance with pairwise deletion for ND2 sequences deposited in GenBank by Lee & Edwards (2008). Bootstrap values (1000 replicates) are shown on branches. The map is redrawn from Lee & Edwards (2008) and shows the distribution of two subspecies (one spanning the Carpentarian barrier), and the hybrid zone between them (hatched). Dots on the map correspond to sampling localities and are colour coded to match the tree; some localities were represented by multiple individuals. The solid vertical line shows the approximate location of the Carpentarian barrier. No nuclear locus captured this salient mtDNA result. In many (most?) of the nuclear gene trees, neither the red-backed fairy wren nor the clearly distinct white-winged fairy wren was monophyletic because of paraphyly and sharing of many identical alleles. In spite of this, Lee and Edwards assumed the monophyly of the red-backed fairy wren, pooled the individuals into the three populations shown on the mtDNA tree and then estimated population sizes, pairwise divergence times and directional gene flow rates. They convincingly showed that confidence intervals on estimates of these parameters decreased as the number of loci increased. Their estimates of gene flow indicated more gene flow between CY and EF than that between CY and TE, and, between CY and EF, gene flow estimates were greater in the EF to CY direction. We agree that these are interesting results and the gene flow estimates do supplement the suggestion of gene flow inherent in the mtDNA results. The mean estimates of FST for the nuclear loci (0.12) and for the mitochondrial fragment (0.55) lie remarkably close to the theoretical relationship suggested in ZB08 (their fig. 1). So, what about the ‘enormous signal’ in the 35 nuclear genes for discovering taxa? Lee & Edwards (2008) initial pooling of individuals into three populations would be enigmatic, absent the mtDNA tree. For example, Cracraft’s (1986) analysis of the biogeography of Australian birds (shown in their fig. 1) indicates that they actually included five areas of endemism in their sampling, whereas their own Structure analysis of the 35 independent nuclear sequences indicated that they were probably dealing with only two populations. The mtDNA results immediately suggested three divergent taxa that the nuDNA only confirmed given the a priori assumption of their existence. We can only speculate what the nuDNA results would have suggested if one were to have assumed the two Structure populations or the five areas of endemism, that is, without the guidance of the ‘leading’ mitochondrial tree. This is a situation where mtDNA was both necessary and sufficient for the discovery of differentiated taxa in a phylogeographic survey, whereas nuDNA was neither. As technologies advance and become more cost effective, there will be funds enough, and time for everyone to sequence 100 or more nuclear loci for many individuals, and the computational methods will be available to analyse them. Currently, sequencing a single nuclear locus certainly costs at least as much as sequencing a mitochondrial one. With Sanger sequencing, the relationship must be nearly linear; with third generation technologies, expense may be less than linear, but with a high fixed cost. Effective mtDNA primers are easy to design given the chicken mitochondrial genome, the many sequences available in GenBank and a large published literature. However, introns, anonymous loci and single nucleotide polymorphisms are only becoming available, and their use and analysis involves homology, recombination and phasing issues. The latter problem will remain serious until single molecule (e.g. 454 or similar) sequencing drops in price because cloning or polymerase chain reaction-based phasing is expensive and time-consuming, whereas likelihood methods are not effective for rare (particularly singleton) substitutions. With some software, inferring recombination involves heroic assumptions about having homoplasy-free (e.g. infinite alleles) data. Taken together, the 35 nuclear loci used by Lee & Edwards (2008), along with some a priori help, did recover the pattern found with only 470 bp of mtDNA, so it is probably not fair to pass them off as 35 false negatives. Nevertheless, the supplement gained ‘by the enormous signal available in the many loci of the nuclear genome’ was in obtaining tighter confidence intervals on population genetic parameters, not in identifying differentiated taxa. We agree with EB09 that nuclear loci can and will make essential contributions to the quantification of population genetic processes. However, these loci may not be very efficient at recognizing recent qualitative geographical pattern and may almost always require mitochondrial or morphological assistance to do so. For such discovery, having a marker with resolution over the appropriate timescale may be more important than having multiple nuclear loci with less-suitable coalescence times. If one’s goal is to detect recently isolated groups of individuals or populations, i.e. discover taxa, the first step in a study ought to be the construction of a mtDNA gene tree. One can then sequence many nuclear genes to get satisfactory confidence intervals on evolutionary parameters of interest, as ZB08 explicitly pointed out. This may be the only way to answer some questions, but, currently, it will take considerable time and expense. Indeed, it has not escaped our notice that both Bensch (e.g. Hansson et al. 2008) and Edwards (e.g. Kearns et al. 2009) continue to publish phylogeographic surveys invoking process based strictly on mtDNA data. Consequently, we could not agree more with the sentiment of Lee & Edwards (2008:3118): ‘…mtDNA will surely continue to be a mainstay of phylogeography…’. Precisely: that was our (ZB08) original point. We thank B. Barber, J. Cracraft, S. Drovetski, A. Jones, B. McKay, H. Vazquez-Miranda and G. Voelker for discussion." @default.
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• W1978791818 title "Funds enough, and time: mtDNA, nuDNA and the discovery of divergence" @default.
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