To an Old White Pine, Op. 62, No. 7
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We first examined the composition and geographic distribution of chloroplast haplotypes to infer genetic lineages and post-glacial northward migration of eastern white pine. The geographic distribution of the haplotype data was visualized using PhyloGeoViz [ 46 ]. The hypotheses were constructed primarily to test the order from south to north and time of divergence of the population groups, as well as the possibility of population admixture after divergence.
For the ABC simulations, we analyzed the nuclear and chloroplast marker data separately. First, we compared the competing scenarios of population divergence without admixture and then with population admixture Additional file 2 : Figure S1. The information on the parameters and their prior distributions used in the analysis are provided in Additional file 1 : Table S1.
Then we compared the best scenarios taken from each of the without and with admixture analyses. The population divergence scenarios differed in the order of population divergence and in the number and time of demographic expansion events. The population admixture scenarios were developed based on both the chloroplast haplotype distribution and the best scenario from with and without admixture comparison. We performed a logistic regression to estimate posterior probability of each scenario, taking the simulated data sets closest to our real data set between 0. Once the most likely scenarios were identified, we used a linear regression analysis to estimate the posterior distributions of parameters under this scenario.
In order to evaluate the goodness-of-fit of the estimation procedure, we performed a model checking computation [ 47 ] by generating 10, pseudo-observed data sets with parameters values drawn from the posterior distribution given the most likely scenario. A total of alleles were observed at 12 nuclear microsatellite loci in eastern white pine individuals. Twenty alleles were observed at three chloroplast microsatellites in the subset of individuals. A total of 60 chloroplast haplotypes were observed Additional file 3 : Table S2.
Generally, the Asheville population from North Carolina showed the highest and the Saint Margarets Bay population from Nova Scotia the lowest nuclear microsatellite genetic diversity. The Newfoundland population GL showed somewhat higher levels of genetic diversity than the Nova Scotia and New Brunswick eastern white pine populations. Western populations western Ontario and Minnesota had, on average, slightly higher levels of heterozygosity at nuclear microsatellites. The overall mean F ST among the populations was 0. The two Bayesian analyses of population genetic structure revealed significant levels of genetic structure of eastern white pine populations across its range, and the results were consistent between the two approaches with only slight differences.
After performing Evanno et al. Each of the rest of the 27 population formed its own individual group Fig. BAPS, with the addition of geographic coordinates, identified 26 genetic groups among 33 populations Additional file 5 : Figure S3. In all cases, populations that were clustered together were in close geographical proximity. Each individual is represented by a single vertical line while each colour represents one of the 30 clusters. The fourth group consisted of the two southern populations from Virginia and North Carolina.
Each individual is represented by a single vertical line. We identified two barriers among the 33 sample populations from both the nuclear and chloroplast microsatellite markers that separated the populations into three groups Additional file 5 : Figure S3. The second barrier separated a central and southern 10 populations from an eastern group 20 populations and was supported by 10 nuclear and 3 chloroplast microsatellite loci.
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The geographic distribution of the most common chloroplast haplotypes across the sampled range is presented in Fig. The southernmost population NCAV from North Carolina had all five most common chloroplast microsatellite haplotypes, whereas the eastern populations had two or three of these chloroplast microsatellite haplotypes.
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From the haplotypes constitution and haplotypes sharing among populations, three phylogenetic lineages were apparent: western, central and eastern Fig. The Green AG haplotype was shared between the western and some central populations, indicating some sort of admixture between these apparent lineages. Geographic distribution of the most abundant chloroplast haplotypes in eastern white pine populations.
Colours correspond to individual haplotype. This placed the first event 1-t 3 of population divergence between the southern group ST and the western group WS , the second split 1-t 2 between the ST and the ancestral population of the central CNT and eastern EST groups, and the final split 1-t 1 between the central and eastern groups Fig.
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Highest probable ancestral connectivity observed using DIY Approximate Bayesian Computation ABC analysis between four population groups from a nuclear microsatellite, and b chloroplast microsatellite markers. ST: southern group. EST: eastern group. CNT: central group. WS: western group. AD: admixture events. See Additional file 2 : Table S1 for group information. In order to better understand the extant population genetic structure, the historical processes that shaped the current distribution and potential fate of a species in the future, especially under climate change conditions, and conservation of its genetic resources, knowledge of its postglacial phylogeography, evolution and expansion is important.
Here we have examined the range-wide genetic diversity and population structure of widely distributed and heavily exploited keystone species, eastern white pine, using microsatellite markers of the nuclear and chloroplast genomes and inferred its postglacial evolution and migration testing various hypothetical evolutionary scenarios.
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We have demonstrated that the extant eastern white pine populations have relatively high genetic diversity, with south to north trend of reduced genetic diversity, and are significantly genetically structured across the range. The signals of postglacial phylogeography and evolution were disentangled from the effects of resource extraction of over the past century and half.
Our results suggest a single southern refugium, two recolonization routes and three genetically distinguishable lineages in eastern white pine that we suggest be treated as separate Evolutionarily Significant Units. Eastern white pine has relatively high nuclear microsatellite DNA genetic diversity over its range.
These observations of higher genetic diversity observed in our study is consistent with much larger range of eastern white pine studied in ours than previous studies. Also, our study included southern populations from Virginia and North Carolina that were found to be the most genetically diverse. The genetic diversity of the chloroplast microsatellites was in all cases lower than that for the nuclear markers. This is consistent with the lower mutation rate in chloroplast than nuclear microsatellites in Pinus [ 50 ] and other plants.
Chloroplast microsatellites cpSSR have been previously used to test the somatic stability of the cloned material [ 51 ] and spatial genetic structure [ 52 ] in eastern white pine. This is the first report of chloroplast microsatellite genetic diversity across the range in eastern white pine. The differences are likely due to the differences in the sample size and the number of cpSSRs used between the two studies. We used 20 individuals per population and three cpSSRs, whereas the average sample size in the Myers et al. Our study clearly demonstrates the existence of south—north patterns in the genetic diversity levels, with the populations in Virginia and North Carolina having higher levels of genetic diversity than the northern populations.
This is consistent with the possible repeated founder effects during post-glacial migration northward of eastern white pine from a southern Pleistocene refugium. The lower genetic diversity in the northern eastern white pine populations may also be due to divergent selection in response to south to north gradient in climate factors, such as temperature and moisture regimes, and range marginalization [ 27 ]. However, none of the microsatellite loci showed any signatures of divergent selection when we tested for outliers with respect to the magnitude of F ST using BayeScan ver.
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On the other hand, the New Brunswick and Nova Scotia eastern white populations have been heavily exploited. The number of private alleles did not show any geographical patterns in our study. Private alleles may arise from population-specific new mutations and severely curtailed inter-population gene flow.
Geographic patterns for private alleles will be expected if the mutation and gene flow rates were geographically structured among populations within a region: southern, northern, eastern central, and western. Apparently, this is not the case with the eastern white pine populations studied.
However, a separate study is required to validate this assumption. We observed These results clearly suggest that significant population genetic structure and differentiation exist across the range of eastern white pine.
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The observed levels of genetic differentiation could be considered as low when compared to the plant kingdom as a whole but for the conifer trees, the levels are higher than the average of 0. Mortality caused by invasive white pine blister rust Cronartium ribicola may have also reduced the population size and number of eastern white pine. Encroaching agriculture, grasslands and deciduous forests, and changing precipitation and wind patterns may negatively impact the distances over which seeds and pollen are dispersed between populations.
All of the above factors may have reduced the levels of inter-population gene flow and increased inbreeding. However, eastern white pine has strong inbreeding depression [ 55 ], and selection against inbreds can occur at a very early stage in conifers [ 56 ]. Although eastern white pine is long-lived and has highly dispersed pollen [ 52 ]; these factors may not be enough to counterbalance the effects of anthropogenic and natural disturbances to sustain a homogenized genetic structure over its range.
The inter-population genetic differentiation of This may be the result of the large area covered by our study that, for the first time, included populations from the western and southern edges of the range. Within the smaller range, in particular the western populations, we observed similar levels of differentiation F ST : 0. Chloroplast microsatellite genetic differentiation was lower than that for the nuclear markers.
This is likely due to pollen-mediated paternal inheritance of the chloroplast genome in Pinus [ 15 ] and long-distance gene dispersal via pollen as compared to that via seeds in conifers. The phylogeographic patterns emerged from the nuclear and chloroplast genetic markers were consistent between themselves and broadly consistent with the findings from previous fossil pollen studies [ 12 ].
The most parsimonious hypothesis and scenario from our genetic data and ABC model testing would be to suggest that eastern white pine likely expanded northward along two routes of post-glacial recolonization from a single southern refugium Fig. The highest probability scenario from the ABC analysis and earlier fossil pollen evaluation [ 12 ] suggest that this refugium likely existed on the mid-Atlantic plain from coastal Virginia to the southern cost of South Carolina. The Ashville population from North Carolina is the only sampled location from an area that contained eastern white pine pollen from the LGM.
This is typical for populations of glacial refugia. Thus, it is highly likely that the North Carolina sample location is a remnant of the eastern white pine LGM refugia. From the ABC analysis Fig. Probable eastern white pine post-glacial recolonization routes arrows from the glacial refuge shaded grey area based on the highest probable Approximate Bayesian Computation ABC scenarios observed from nuclear and chloroplast microsatellite data and available fossil pollen information.