BMC Evolutionary Biology

BMC Evol Biol. 11: 66-66

Population dynamics and genetic changes of Picea abies in the South Carpathians revealed by pollen and ancient DNA analyses

Enikő K Magyari¹, Ágnes Major², Miklós Bálint³⁷, Judit Nédli⁴, Mihály Braun⁵, István Rácz², Laura Parducci⁶

1. MTA-MTM Research Group for Paleontology, 1476 Budapest, P. O. Box 222, Hungary

2. Hungarian Natural History Museum, 1431 Budapest, P. O. Box 137, Hungary

3. Molecular Biology Center, Babeş -Bolyai University, Str. Treboniu Laurian 42, 400271 Cluj, Romania

4. Balaton Limnological Research Institute, 8237 Tihany, P.O. Box 35, Hungary

5. University of Debrecen, Department of Inorganic and Analytical Chemistry, 4010 Debrecen, P.O. Box 21, Hungary

6. Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, 75236, Uppsala, Sweden

7. Biodiversität und Klima Forschungszentrum (BiK-F), Senckenberganlage 25, D-60325 Frankfurt am Main, Germany

Copyright ©2011 Magyari et al; licensee BioMed Central Ltd.

DOI: 10.1186/1471-2148-11-66

Published online: 10 March 2011

Abstract

Background

Studies on allele length polymorphism designate several glacial refugia for Norway spruce (Picea abies) in the South Carpathian Mountains, but infer only limited expansion from these refugia after the last glaciation. To better understand the genetic dynamics of a South Carpathian spruce lineage, we compared ancient DNA from 10,700 and 11,000-year-old spruce pollen and macrofossils retrieved from Holocene lake sediment in the Retezat Mountains with DNA extracted from extant material from the same site. We used eight primer pairs that amplified short and variable regions of the spruce cpDNA. In addition, from the same lake sediment we obtained a 15,000-years-long pollen accumulation rate (PAR) record for spruce that helped us to infer changes in population size at this site.

Results

We obtained successful amplifications for Norway spruce from 17 out of 462 pollen grains tested, while the macrofossil material provided 22 DNA sequences. Two fossil sequences were found to be unique to the ancient material. Population genetic statistics showed higher genetic diversity in the ancient individuals compared to the extant ones. Similarly, statistically significant Ks and Kst values showed a considerable level of differentiation between extant and ancient populations at the same loci.

Lateglacial and Holocene PAR values suggested that population size of the ancient population was small, in the range of 1/10 or 1/5 of the extant population. PAR analysis also detected two periods of rapid population growths (from ca. 11,100 and 3900 calibrated years before present (cal yr BP)) and three bottlenecks (around 9180, 7200 and 2200 cal yr BP), likely triggered by climatic change and human impact.

Conclusion

Our results suggest that the paternal lineages observed today in the Retezat Mountains persisted at this site at least since the early Holocene. Combination of the results from the genetic and the PAR analyses furthermore suggests that the higher level of genetic variation found in the ancient populations and the loss of ancient allele types detected in the extant individuals were likely due to the repeated bottlenecks during the Holocene; however our limited sample size did not allow us to exclude sampling effect.

This study demonstrates how past population size changes inferred from PAR records can be efficiently used in combination with ancient DNA studies. The joint application of palaeoecological and population genetics analyses proved to be a powerful tool to understand the influence of past population demographic changes on the haplotype diversity and genetic composition of forest tree species.

Background

In the last two decades ancient DNA (aDNA) has been successfully extracted from fossil plant material, and the results from the specimens of late Quaternary remains (up to 100 ka yrs) have provided insights into many evolutionary processes [1-9]. These studies represented the first attempts in linking extant and fossil plant populations and provided important information on genetic changes through time. Parducci et al. [7] did a promising attempt to analyze short chloroplast DNA (cpDNA) regions in fossil pollen extracted from a Holocene lake sediment in Sweden. Fossil pollen grains are abundant in lake sediments. Under ideal preservation conditions (neutral pH, low temperature, no oxygen) the study of pollen DNA allows studying past demographic events by analyzing neutrally evolving regions of the organelle genome, such as microsatellites and introns [10,11]. During the Quaternary (last 2.6 million years) climatic oscillations have dramatically influenced the distribution of plant species [12]. Repeated range expansions and contractions in response to warming and cooling resulted in large-scale demographic changes with consequent impact on their genetic composition [11].

Progress in aDNA-based phylogenetic and population genetic studies have been very rapid in animal species and lately several specific primers have been designed to study population-level changes (reviewed in Leonard [13] and Hofreiter [14]). Rohland et al. [15] have for example detected divergence events between mammoth and the two extant elephant species. Barnes et al. [16] and Valdiosera et al. [17] successfully reconstructed population movements during the last glaciation in brown bears and detected frequent events of extinctions and recolonizations. Unfortunately, similar studies on woody plants are still in their infancy with few attempts done on fossil pollen and wood [7,18,19]. This is despite the many questions that plant aDNA analyses are amenable to answer [20].

In this study we focus on Picea abies (Norway spruce), one of the ecologically and economically most important forest tree species in Europe. Pollen and macrofossil evidence combined with genetic surveys of the current European populations of this species showed that its wide-ranging distribution in central and south-eastern Europe originated from several glacial refugia [21-26]. One such refugium was identified in the South Carpathians, where several unique cpDNA and mitochondrial DNA (mtDNA) haplotypes suggested long-lasting isolation [22,25]. Populations from these regions showed lower level of genetic variation compared to other refugial populations in central Europe, and north- and westward postglacial expansion from this area showed to be limited, as these haplotypes do not appear in the central and northwest European populations today. In addition, the genetic diversity increased north of the Carpathians, probably as a result of admixture of expanding populations from two separate refugia. Tollefsrud et al. [25] suggested that the dry plains of central and south-eastern Europe, including the Hungarian Plain, formed an ecological barrier to any expansion, whereas humid mountain ranges elsewhere in central Europe facilitated the northward spread of other spruce lineages. The lateglacial and early Holocene warming also brought major altitudinal displacements of the species range in the South Carpathians [27,28]. In addition, fossil pollen records indicate that a large proportion of glacial lowland coniferous woodlands went destroyed by fire in the early Holocene as summer temperatures rose [29]. An ongoing pollen and plant macrofossil study of a sediment sequence retrieved from a lake located in the Retezat Mountains (Tăul dintre Brazi) in the South Carpathian Range demonstrates that at the onset of the early Holocene warming (around 11,000 cal yr BP) a rapid population expansion of Norway spruce took place around this lake [30].

Based on all this knowledge, we hypothesized two possible population demographic scenarios during the Holocene in the South Carpathian refugium. (1) The spruce populations of the Retezat Mountains remained constrained to this region with a relatively constant population size. In this case we expect to find the same haplotypes and similar levels of diversity in extant and ancient samples. (2) The population of the Retezat Mts underwent significant demographic changes, most probably due to climatic shifts and anthropogenic influences. In this case we expect altered haplotype frequencies in the extant population relative to the ancient population, and different levels of genetic diversity.

To asses the consistency of the two scenarios, we analyzed fossil spruce pollen and other macrofossils (seeds and cone scales) from the early Holocene section of a sediment core extracted at lake Tăul dintre Brazi (TDB) in the Retezat Mountains (Figure 1). We analyzed cpDNA from material retrieved from two radiocarbon dated sediment layers (11,000 and 10,700 cal yr BP levels) (Figure 2) and compared results with genetic data obtained from the extant spruce population of the Retezat Mountains. Population genetic inferences from the past were then linked to a 15,000-year record of spruce pollen accumulation rates (PAR) obtained from the same sediment core and used to infer past population size changes. PAR values represent the number of pollen grains accumulated at the sediment surface (cm²) in a year and they can be directly related to the population size of the studied taxon in the effective pollen source area of the examined lake [31]. The importance of this relationship has been long recognized by palaeoecologists [32] and used to reconstruct past population growth rates [33,34]. Recently, the collection of forestry data allowed direct comparison of surface sediment PAR values with actual biomass and population sizes in modern forests and thus the projection of PAR-based population size estimates back in time [35].

Figure 1View larger versionFigure 1. Sampling sites in the Retezat Mountains. (a) Map showing the location of the Retezat Mountains in Europe and (b) in the Carpathians; H: herbarium sample; AF: Austrian Alps. (c) Relief map of the Retezat Mts showing the position of Tăul dintre Brazi lake with location of the extant samples analysed in this study. The location of herbarium specimens is shown in map (b). On map (c) labels mark valleys and tracks in the Retezat Mountains; CP: Carnic-Pietrele; St: Valea Stanisoarei; P: Valea Pietrele; R: Vale Rea; Gt(k): Valea Gales; Buk: Valea Bucura; KR: Rtezatul Mic; B: Buta; M. Valea Marii; Z: Vale Zanoaga.

Figure 2View larger versionFigure 2. Sample location and schematics of the core TDB-1 (Tăul dintre Brazi) with a digital photo of the sediment where the ancient spruce samples were collected. On the left, depth and calibrated BP timescales are shown.

Results

We analyzed eight different cpDNA regions in extant and fossil material from Norway spruce and six of them showed polymorphism (Table 1). The alignment of the extant sequences revealed 13 point mutations and five length polymorphisms that yielded nine haplotypes (Table 1 and Additional File 1). Two haplotypes were the most common (Ht2 and Ht8) found in 15 and 22 out of 58 individuals, respectively. Out of 462 fossil pollen grains analyzed we obtained totally 28 positive amplifications (three amplifications for fragment B, four for fragment D, ten for fragment TL, seven for fragment LF, two for the non-variable fragment CK, and finally two for the non-variable fragment MD). The higher amplification success (16.5%) obtained with pollen compared to Parducci et al. [7] was likely due to the choice of using more (usually five) pollen grains instead of one during amplification trials, or it may simply indicates favorable condition for DNA survival in the lake sediment at the Retezat. After sequencing, four of the 28 amplicons (two obtained with primers B and two with primers D) showed to be of Pinus origin, while seven amplicons obtained with primers LF were of Abies origin. Pollen grains of these two taxa were present in the examined sediment layer [30] and they were likely selected by mistake during the analyses. The rest of the amplicons were assigned to P. abies. Another possible explanation for the findings of Pinus and Abies sequences is DNA contamination from molecules of the surrounding sediment that may permeate or adhere to macrofossils in the sediments [36]. Nevertheless, these sequences still provide authentic early Holocene DNA information from Pinus and Abies individuals.

See full tableTable 1. Base substitutions detected in extant and ancient cpDNA sequences of Norway spruce (Picea abies)

Out of the investigated six Norway spruce seeds, DNA was successfully amplified from five seeds. Altogether, we obtained 15 positive amplifications (one for fragment B, three for fragment D, three for fragment TL, two for region Li, one for region LF, two for fragment K2i, one for the non-variable CK fragment, and two for the non-variable fragment M) (Table 1). When sequences were concatenated, the total length of the haplotypes varied between 124 and 1016 bp in the five seeds, and between 136 and 251 bp in pollen. Concatenation of the four regions amplified from the 4 cone scales gave a haplotype with a total length of 901 bp. Because cpDNA is paternally inherited in Norway spruce, sequence difference between cone and seed haplotypes (mother-tree versus offspring) were not unexpected. We found three transversion substitutions at position 77 in fragment D (C > A), position 197 in fragment TL (C > A) and position 157 in fragment Li (A > C). Finally, replication of the analyses done at Uppsala University using four new seeds retrieved at 502, 513, 525 and 545 cm depths in the same sediment, gave two positive amplifications (from sample 502 and 545 cm) using primers B. Both sequences were of Norway spruce origin and showed the 12A + 5G block, the most common variant present in the extant population.

Comparison of ancient and extant sequences

After manually editing for base call errors, we performed an alignment between homologous regions obtained in extant and ancient individuals. The alignment revealed mismatches at several positions. Transition substitutions (G > A and C > T) were interpreted as incorrect nucleotide PCR incorporations due to post-mortem lesions in the ancient DNA molecules, a common problem when amplifications are performed from degraded DNA molecules [5]. We therefore neglected two G > A substitutions detected in sample P13 (fragment TL, positions 168 & 206 in Table 1). The rest of the substitutions were considered authentic, i.e. due to true polymorphism. Two variants were unique to the ancient population: a 10A + 7G repetition found in sample S9 (fragment B), and a GA dinucleotide substitution present in sample P13 (fragment TL). As expected, variants that were common to the extant population were also found in the ancient material (e.g. the common A, A, and C nucleotides at positions 77, 78 and 82 in fragment D was found in seeds S3 and S10). However, also rare variants found in extant individuals were detected among the ancient samples. For example, the 10A + 6G repetition in fragment B, and the C > A substitution at position 157 in fragment Li, both with a frequency 0.017 in the extant population, were found in sample P1 and S4, respectively. Similarly, a C > A substitution at position 197 in fragment TL was detected in samples P12 and S10.

Population genetic analyses

Estimates of nucleotide diversity, haplotype diversity and average number of nucleotide differences calculated at the six polymorphic cpDNA loci are presented in Table 2. Observed values for fragment D, TL and Li suggest that the ancient spruce population harbored higher levels of genetic variation compared to the extant population. Fst values at these loci were also statistically significant, an unusual result considering the low level of differentiation usually observed among populations of conifer species. Nucleotide-based genetic differentiation (Ks and Kst,) was also statistically significant at these three loci. On the whole, our results suggest differentiation between extant and ancient spruce populations that inhabited the areas surrounding Tăul dintre Brazi at 10,700-11,000 cal yr BP.

See full tableTable 2. Genetic diversity and population differentiation estimates in ancient and extant Norway spruce (Picea abies) populations based on six cpDNA loci

Phylogenetic relationships of ancient and extant specimens

Results of the phylogenetic analyses conducted on separate loci based on all sequences available (data set c in the Methods) for fragments D, TL, Li and LF are presented in Figure 3. A small group of sequences is formed by nine extant and four ancient sequences in the case of fragment D, while the other two ancient sequences are grouped with the rest of the extant material. In the case of LF fragment, the ancient sequences obtained from the cone and seed S8 are clustering together with the majority of the extant samples, while a smaller group of extant sequences that included samples collected on the northern slopes of the Retezat, form a well-supported cluster. The phylogenetic analysis conducted on fragment Li grouped together the majority of extant samples with one ancient sequence obtained from seed S10, while the other two ancient sequences form a well-defined clade with one extant sequence collected on the shores of Tăul dintre Brazi. For fragment TL we obtained the largest number of sequences from the ancient material and the majority of them grouped together with the extant specimens. Only three ancient and one herbarium specimen form a well-separated group.

Figure 3View larger versionFigure 3. Phylogenetic tree based on B/MCMC analysis of D, LF, Li and TL chloroplast fragments with ancient sequences indicated in boxes. Posterior probabilities are shown along the branches.

Finally, the a median-joining network created using microsatellite B sequences (Figure 4) grouped the two previously identified 100-year-old spruce pollen from Sweden [7] together with the common haplotype detected in this study in extant and herbarium specimens. Our ancient sequences were also similar to this common extant haplotype with a single mutation step away from it, thus suggesting genetic continuity between Norway spruce populations.

Figure 4View larger versionFigure 4. Median-joining haplotype network of the chloroplast fragment B. Numbers denote haplotypes found for fragment B only. Haplotype 1 corresponds to Ht9 (Table 1); haplotype 2 includes Ht2, Ht3; haplotype 3 includes Ht1, Ht6, Ht8; haplotype 4 includes Ht 4, Ht7 and P1; haplotype 5 corresponds to Ht5; haplotype 6 corresponds to S9; haplotype 7 corresponds to haplotype R in Parducci et al. (2005). For information on the ancient and extant haplotypes see Table 1 and Additional File 1.

PAR-based population size estimates

Figure 5 shows pollen accumulation rates (PAR) of Norway spruce calculated at Tăul dintre Brazi for the last ca. 15,700 cal yr BP. PAR values are very low until 11,100 cal yr BP (0-270 grains cm⁻²yr⁻¹) with an average of 120 grains cm⁻²yr-1 that indicate very small population size in the Retezat Mts (ca. 1.2 - 6.4 trees per hectare according to the equation of Seppä et al. [35] for the Finnish woodlands). The Lateglacial interstadial, between 14,450 and 12,900 cal yr BP (zone 2 in Figure 5) show moderately higher PAR values (av. 155 grains cm⁻²yr⁻¹). These values, together with the concurrent findings of spruce stomata (Figure 6), suggest the presence of a small lakeshore population during the Lateglacial interstadial at the study site. It is likely that spruce was absent from the lakeshore prior to this period and for a short period during the successive Younger Dryas climatic reversal (zone 3), between ca. 12,600-12,400 cal yr BP. From ca. 11,100 cal yr BP (period 4 and 5) a massive increase in spruce PAR, stomata concentration and pollen frequencies commenced with PAR values increasing from 200 to nearly 7000 grains cm⁻²yr-1 in about 1000 years. Such values are equivalent to an approximate population size increase from 9 to 101 trees per hectare [35]. It should be noticed however, that due to approximation in the PAR-based population size extrapolations only the magnitude of this change is certain. Subsequently, the highest overall Holocene PAR values and hence inferred population size was detected between ca. 10,100 and 9180 cal yr BP (av. 4886 grains cm⁻²yr⁻¹) followed by a modest decline, with still high PAR values until 7200 cal yr BP (zone 6). At this time, a significant decrease suggests also a decrease in population size (from ca. 252 to 120 trees per hectare on the basis of Seppä et al. [35]). These values were maintained until ca. 3900 cal yr BP and were followed by a second significant increase between 3900 and 2200 cal yr BP (zone 8). Finally, the PAR curve suggests a third decrease in population size after 2200 cal yr BP. This period coincides with the late Iron Age increase in livestock and the development of high altitude seasonal pasturing in the Romanian Carpathians [37] suggesting intensive timber exploitation by humans in the region. Overall, the PAR record suggests that following an early Holocene massive population increase on the northern slopes of the Retezat, the spruce population size did not remain constant, but showed marked fluctuation with three clear population bottlenecks dated to ca. 9180, 7200 and 2200 cal yr BP.

Figure 5View larger versionFigure 5. Lateglacial and Holocene pollen accumulation rates (PAR) of Norway spruce (Picea abies) from Tăul dintre Brazi in the Retezat Mountains. The dashed line on top of the PAR curve displays a three-term running mean.

Figure 6View larger versionFigure 6. Pollen and stomata record of Tăul dintre Brazi plotted against depth and calibrated BP timescales. Norway spruce (Picea abies) fossils are highlighted in red. LPAZ: local pollen assemblage zones as in Table 3; ➊ first occurrence of spruce stomata at 13,900 cal yr BP; ➋ -➌ early Holocene population expansion of spruce between 11,750 - 10,780 cal yr BP inferred by pollen and stomata increases. Black rectangles along the timescale bar indicate the position of the radiocarbon dated samples.

Discussion

Patterns of plant genetic diversity in Europe show that levels of diversity usually decrease during postglacial colonization from the refugia [25,38-41]. There can be however large differences between colonization routes followed by different plant species due to climatic and environmental factors, altitudinal range expansion and contraction, proximity to the ice sheets, and topography. Results from our study suggest that these factors were crucial in determining the distribution and demography that shaped the genetic structure of the populations of the South Carpathians in the Retezat. In Central Europe, high levels of diversity are usually found in the oldest spruce regions ( i.e. where spruce pollen is present since at least the Early Holocene), in the south-eastern Alps, southern Bohemian Massif, West Carpathians and northern Dinaric Alps [25]. The only exception is the South Carpathian refugium, where scientists have found unique haplotypes and relatively low diversity levels in extant populations [25]. Indeed, in our study we found a decreased genetic variation in the extant populations in the Retezat compared to the ancient population, and such lower diversity could be easily associated with the several population bottlenecks identified by the PAR data. Nevertheless, we cannot exclude that the limited number of fossil sequences affected the interpretation of the aDNA data.

It is reasonable to assume that the fluctuations observed in population size after an early Holocene rapid expansion at Tăul dintre Brazi had a substantial impact on the genetic structure of the spruce population. The pollen record shows that a small population was already established in the lateglacial period around 13,900 cal yr BP at high altitudes formerly covered by glacier ice (Figure 5 and 6) supporting the presence of a refugium in this area. Such a refugium has been also detected by genetic analysis conducted on living populations by Bucci & Vendramin [22] and Tollefsrud et al. [25]. Assuming therefore that spruce was present and probably abundant throughout the last glacial cycle at lower elevations in the Retezat, it is likely that our sampled ancient population is similar in genetic composition to this refugial population. The pollen and the stomata record (Figure 6) show that the lateglacial expansion came to a halt during the Younger Dryas climatic reversal (between ca. 12,900 and 11,500 cal yr BP), and the spruce population was greatly reduced and/or eradicated from the lakeshore [30]. The species expanded again during the early Holocene and our ancient material was sampled at the beginning of this second population expansion that started around 11,100 cal yr BP. Such increase in population size started from a population that was very small, according to the PAR record about 1/10 or 1/5 of the extant one, and that successively increased between ca. 11,100 and 10,100 cal yr BP. A significant increase in population size, however, only began around 10,000 cal yr BP, when the largest overall Holocene distribution was reached. Fossil pollen data from this site (Figure 5) indicates that between 10,100 and 9180 cal yr BP Norway spruce replaced European larch (Larix decidua) on the lakeshore and probably also in other areas at the same altitudinal belt [30]. By this time, the population increased to a number that likely exceeded the extant population size.

According to the PAR record, the maximum extension of Norway spruce in the Retezat was followed by three distinct population bottlenecks. The first reduction occurred at 9180 cal yr BP and was likely caused by a local population decline due to the expanding lake surface area [42]. A second reduction in size occurred at 7200 cal yr BP and it was attributable to the climate-induced spread of European hornbeam (Carpinus betulus) that partially replaced former mixed Norway spruce - hazel forests at mid elevations [27,42]. The third bottleneck started 2200 years ago and was of anthropogenic origin as suggested by the accompanying decrease in many other arboreal elements and the spread of human-indicator herbs [42].

Typically, population bottlenecks are characterized by loss in allelic richness and a more limited decrease of genetic diversity at neutral loci [43]. This theory however is not strictly applicable to the events that seem to have occurred during postglacial recolonization in the Retezat. In our case, a combination of factors may have acted to limit the initial loss in allelic richness (original large population sizes in the early Holocene), and later to increase it (population bottlenecks and range fragmentation due to forest management). Several pollen studies and historical documents show indeed that forest management was intense from 2200 cal years BP and destroyed the large continuous distribution of Norway spruce in this region [27,44,45].

Results from the genetic and PAR analyses seem therefore to support the hypothesis that the higher ancient genetic variability and the absence of some ancient haplotypes in the extant spruce populations was due to repeated bottlenecks experienced during the Holocene in the Retezat. In addition, as suggested by Tollefsrud et al. [25], the dry plains of central and south-eastern Europe, may also have acted as an ecological barrier to the expansion of the early Holocene populations from this site, whereas humid mountain ranges elsewhere in central Europe facilitated the northward spread of new spruce lineages in the successive periods. As a result, despite the proximity to the South Carpathian refugium, the genetic diversity of this site declined during the Holocene.

Conclusions

This study demonstrates how past population size changes inferred from PAR records can be efficiently used in combination with aDNA data. The joint application of palaeoecological and population genetic analyses proved to be a powerful tool to understand the influence of past population demographic changes on the haplotype diversity and genetic composition of an important forest tree species. We used a pollen and plant macrofossil-based aDNA approach and traced population size changes of Norway spruce in a refugial area in the South Carpathian Mountains. Results clearly show that the paternal lineage observed at the beginning of the Holocene in the Retezat Mts persisted at the site until today. Problems associated with low sample size in our aDNA data could be overcome by the information obtained from the PAR data that clearly showed significant population size fluctuations in the Retezat Mts during the Holocene. This combined information support the hypothesis that the spruce population of the Retezat Mts underwent significant demographic changes, most probably due to climatic shifts and anthropogenic influences, and that likely these changes significantly altered the haplotype frequencies and the level of genetic diversity.

This study thus laid down the first basis for further aDNA analyses. By examining additional levels of this sediment profile we can provide further insight to support the hypotheses presented in this study.

We have shown also that longer sequences, and more robust phylogenetic inferences can be obtained from plant macrofossils like seeds and cone scales when aliquots of the DNA extracts are used in multiple PCR reactions providing sequences from different cpDNA regions. Similar attempts performed with fossil pollen grains were not as successful limiting at the moment population genetic inferences to single loci. On the other hand, multiple PCR products (obtained by applying multiple primer sets in one reaction) and thus longer sequences might be obtained from pollen using the new generation sequencing platforms, like the 454 GS FLX [14,46] or multiple-loci PCR analyses. With this type of analyses, the use of DNA extracted from plant macrofossils allows the study of longer DNA sequences or, in the case of the 454 platform, even complete genomes from ancient plant specimens providing good resolution data sets for population genetic analyses, as recently done with an extinct cave bear species [47]. The main obstacle to the use of plant macrofossils for detecting population level changes is the limited number of individuals that can be obtained from a sediment sample. In cases, however, where macrofossils are well preserved and retrieved in large quantities from multiple time horizons [48], they can easily provide multiple genotypes suitable for population genetic studies similarly to our recovery of an intact 11,000-year-old Norway spruce cone from Tăul dintre Brazi. In such cases, the opportunity offered by new data analytical methods in population genetics that work with multi-locus data, enables an efficient use of a relatively small number of individuals in the reconstruction of past population demographic changes [49]. Indeed, there are several fossil sites in Europe where Upper Weichselian (ca. 11,500 - 45,000 cal yr BP) plant macrofossils from single or multiple chronological horizons have been recovered in large numbers [24]. In the Carpathians, for example, numerous Picea sp., Pinus cembra and Larix sp. cones have been reported from several last glacial (15,000-45,000 cal yr BP) and Holocene peat sediments [50,51]. Such material seems ideal for aDNA analysis, as both organellar and nuclear DNA in the seeds of these cones hold many alleles. Its study have the potential of revealing ancient genetic diversity in cryptic northern refugia and adding valuable information on the role of this area in the postglacial recolonization of northern and western Europe [11].

Our analyses in particular proved that the use of aDNA in combination with PAR data obtained from the same site can be very efficient in discovering demographic changes that occurred in the past in Norway spruce, and will hopefully be used in other wind-pollinated tree species. Finally, PAR-inferred demographic scenarios offer the opportunity of being incorporated in coalescence-based Bayesian mutation rate estimations, and this way more accurate substitution rates can be obtained [52].

Methods

Ancient material

Our ancient material came from the early Holocene part of a 5-m long sediment sequence extracted at Tăul dintre Brazi (0.5 ha, 1740 m a.s.l.). The lake is situated in a north-facing slope of the Retezat Mts, South Carpathians (Figure 1) and was formed in a glacial basin approximately 15,700 years ago, directly after the retreat of the Lolaia glacier from this valley [42,53]. Today, the forest around the lake consists of P. abies, Pinus cembra (Stone pine), Pinus mugo (Mountain pine) and Rhododendron myrtifolium. The core was analysed for fossil pollen, plant macrofossils, and an age-depth model was constructed based on eleven radiocarbon determinations of terrestrial plant macro remains (Additional File 2) [42]. Pollen preservation was excellent throughout the entire core. The sediment sample from which the spruce pollen grains were retrieved for DNA analysis was organic-rich gyttja showing the first major concentration increase of spruce pollen (533 cm; Figure 2). The age of the studied layer was 10,700 cal yr BP.

An intact Norway spruce cone at 545 cm sediment depth and dated 11,000 cal yr BP [42], was used for aDNA analysis (Figure 2). Half of this cone was sent to the Poznań Radiocarbon Laboratory for dating, while the other half including 6 seeds and 4 cone scales was used for aDNA analysis. The fossil spruce pollen and cone were analyzed in the arche DNA laboratory of the Hungarian Natural History Museum (NHMUS).

Replication of the aDNA analyses was performed at Uppsala University, where DNA from four additional seeds were analyzed. These seeds were retrieved from the same sediment at 502, 513, 525 and 545 cm depths corresponding to 9972, 10,145, 10,331 and 11,000 cal yr BP, respectively.

Pre-PCR preparation of the fossil samples - Molecular Taxonomy Laboratory at the Natural History Museum of Budapest, Hungary (NHMUS)

In a clean-air, DNA-free room (room 1) at the archeDNA laboratory of NHMUS, one cm3 sediment was removed from the inner section of the core at 533 cm using sterile scalpels (Figure 2). The sample was sieved through 120 μm mesh and stored in sterile distilled water at 2°C until further treatment. Aliquots of the filtrate were examined under a light microscope at magnification x100 (Olympus CX 42). Spruce pollen grains were isolated and serially moved between water drops on microscope slides using sterile Hamilton syringes. Totally, we selected 462 fossil pollen grains from sediments dated 10,700 cal BP and stored them at -80°C until aDNA analysis. For PCR set up we followed the methods described in Parducci et al. [7], but we increased the number of pollen grains up to five in each aliquots prepared for amplification and used a finer mesh (120 μm instead of 180 μm) to obtain more efficient concentration of the grains.

Seeds and cone scales were separated from the 11,000-year-old fossil cone under a sterile hood irradiated by high intensity UV light (1 J/cm², 1 hour, several times, turning around the particles at each step to decontaminate the whole surface). All lab ware used for manipulations (forceps, tubes, pestles and mortars, etc.) was nightly UV-irradiated.

In a second room in the arche DNA lab (room 2) we transferred the pollen grains on sterilized microscope slides using a sterile Hamilton syringe and washed them separately ten times with UV-irradiated sterile water. After washing, we moved five to six grains to separate UV-irradiated sterile PCR microtube with 5 μL UV-irradiated sterile water. Along with each tube, we prepared also a negative control including 5 μL of the last drop of water used for washing the five grains. The tubes were stored at -20°C and before PCR they were transferred to the third room in the arche DNA lab (room 3) where the frozen pollen grains were crushed on ice with a sterile pestle in 12 μL sterile distilled water. Five μL aliquots were immediately used as template for PCR. Each pollen sample was amplified with one primer pair. A reagent blank and a negative control including 5 μL of the last washing water were prepared for each amplification.

DNA from seeds and cone scales was extracted in room 3. We manually powdered the material using a NucleoSpin Plant II Kit (Macherey-Nagel) and following the CTAB protocol provided by the manufacturer in 100 μL elution volume. Aliquots of each seed DNA extract was amplified with all primers used in this study.

DNA amplification and sequencing

We selected eight primer pairs (six specifically designed for this study) that amplified short and variable and neutral regions from the spruce cpDNA (pseudogenes, microsatellites, intergenic spacers and introns). In addition, we used two cpDNA microsatellite primer pairs previously used by Parducci et al. [7]. The name of the amplified regions, the sequence of the primers and the expected length in Norway spruce of the eight fragments are listed in Table 3. The primers developed for this study were designed using Clone Manager Suite 7 (SciEd) using Pinus thunbergii and P. sitchensis reference sequences and P. abies chloroplast cpDNA sequences retrieved from GeneBank.

See full tableTable 3. Targeted regions, primer sequences and approximate product length (bp) of PCR for primer pairs used to amplify six cpDNA regions of Norway spruce

DNA amplifications were performed on all DNA extracts (from pollen, seeds and cone) using single primers pairs. We used 20 μL that included 5 μL of template solution (regardless of the source), 1x reaction buffer, 1.5 mM MgCl₂, 0.1 mM dNTP (each), 0.25 mM forward and reverse primers, and 0.4 U of AmpliTaq Gold polymerase (Applied Biosystems). The PCR profile was 10 min at 94°C, 45 cycles of 20 sec at 94°C, 30 sec at 55°C, 1 min at 72°C and final elongation 7 min at 72°C. Five μL of the PCR reactions were tested for amplicons on 2% agarose by gel-electrophoresis in 0.5x TBE and stained with ethidium bromide. In case of successful amplification, 2-3 μL of the first PCR product was reamplified and purified using High Pure PCR Product Purification Kit (Roche) in a PCR room in the modern DNA lab at NHMUS where spruce had never been processed before (room 4). Finally, DNA sequencing reactions were prepared in a fifth room at NHMUS (room 5) using 10 ng of purified PCR products using forward and reverse primers and BigDye Terminator v1.1 Cycle Sequencing Kit (Applied Biosystems). After purification the products were run on a 3130 Genetic Analyzer (Applied Biosystems).

Analysis on extant material

Fresh needles were collected from 52 adult trees of extant spruce populations located in the Retezat Mts. In addition, we sampled needles from 6 herbarium specimens (5 from the Carpathians, 1 from the Austrian Alps) (Figure 1; Additional File 3). Needles were stored at 4°C until use, and total genomic DNA was extracted with DNeasy Plant Mini Kit (QIAGEN). PCR amplifications and DNA sequencing were performed after all fossil DNA analyses had been completed in room 6 that was physically separated from rooms 1-3 at the archeDNA laboratory, and also from room 4 in the modern DNA laboratory, using the same procedures as for the fossil material.

Altogether 833 sample and 322 control PCR reactions were done on the modern and extant material at NHMUS (without re-amplification and sequencing PCRs).

DNA amplification, cloning and sequencing - Molecular Genetic Laboratory (EBC, Uppsala University, Sweden)

Replication of the aDNA analyses was performed on four seeds using the Quiagen Multiplex PCR kit and increasing the number of amplification cycles to 38. This kit contains a built-in hot start polymerase enzyme and a unique PCR buffer that makes it appropriate for the amplification of difficult templates like in the case of fragmented aDNA. We run single reactions with single primer pairs at a time in 20 μL volume, including 3 μL of extracted DNA solution, 1X Multiplex PCR Master Mix (QIAGEN), 0.2 μM of each primer, and water for adjusting the final volume. After amplification 5 uL of PCR products visible as bands of the expected size on 2% agarose gel were purified using ExoSAP-IT (Affymetrix, Inc.). Two μL of purified product was used directly for cloning using the CloneJet PCR Cloning Kit (Fermentas). Two μL of the purified products were ligated into pJET1.2/blunt Cloning Vector in the presence of T4 DNA ligase at room temperature for 30'. Fifty μL of competent DH5 cells were transformed using 5 μl of the ligation and grown in SOC solution for 90' at 37°C. The cells were plated on LB-ampicillin plates. Colonies were screened in 10 uL PCRs using pJET universal primers and following manufacture's instructions. All clones with inserts of expected sizes were sequenced using Macrogen DNA Sequencing service in Korea.

Precautions against contamination and criteria used for sequence authentication

We extracted DNA in environments specifically dedicated to aDNA studies (see methods). At NHMUS in Hungary and at EBC in Sweden all analyses on ancient material were performed in separate DNA-free rooms, in laboratories specifically dedicated to aDNA work and physically separated from laboratories where the modern DNA analyses were performed. Analyses on extant material were performed after aDNA analyses had been completed. No amplifications were obtained in extraction and reagent controls and amplifications from aDNA extracts always produced PCR products visible on agarose gel as single and clear bands.

Cloning is generally performed in the case of aDNA studies to detect mosaic sequences as a result of jumping PCR between sequences, to identify amplification errors due to post-mortem DNA damage in the template and to detect PCR-slippage in the case of microsatellites [20,54]. Initially we planned to sequence PCR products using forward and reverse primers to detect sequence variants after cloning. Because we found no sequence variation in our products after three independent cycle-sequencing assays, we disregarded the cloning step at NHMUS. The multiple cycle-sequencing method also allowed us to exclude the presence of artifacts resulting from PCR-slippage in the microsatellite B region. Importantly, generation of mosaic sequences was excluded in our case due to the uniparental inheritance of the chloroplast genome in spruce.

Data analysis

Ancient and extant DNA sequences were manually aligned in MEGA v4 [55] and identity was verified using BLASTN [56]. The 10,700-year-old DNA sequences obtained from pollen were analyzed together with the sequences derived from fossil seeds and cone scales at NHMUS and EBC.

To compare genetic diversity in ancient and extant spruce populations, we estimated haplotype (Hd) and nucleotide diversities (π, [57]), average number of nucleotide differences (k, [58]), weighted average of the number of differences between sequences from two populations (KS, averaged with a weight of w = n₁/(n₁+n₂), where n1 and n2 represent population sizes [59]), and an estimate of genetic differentiation between two populations (KST, calculated from KS and the average number of differences between two sequences in the total sample [59]). We calculated the statistical support of KS and KST values with permutation tests through 1000 randomizations [59]. Gene flow between extant and ancient populations was estimated using FST [59]. KST and FST statistics are identical except for a different weighting with population sizes [59]. Alignment gaps were considered as fifth-state characters when calculating Hd, k, KS, KST and FST values. We performed the calculations in DnaSP v 4 [60].

Phylogenetic relationships between ancient and extant sequences were analyzed using B/MCMC inference as implemented in MrBayes [61]. Only point mutations in the form of transversion were taken into consideration, disregarding also allele length polymorphisms of microsatellite B. In the phylogenetic analysis we also included two previously obtained 100-year-old spruce sequences obtained by Parducci et al. [7] using primer pair B. The nucleotide substitution model was selected using the Akaike Information Criterion in ModelTest 3.7 [62]. The analyses were run (a) on concatenated fragments using all ancient and extant sequences; (b) on concatenated fragments of all extant sequences and of the longest ancient sequences (obtained from cone scales and seeds S8, S9 and S10); (c) on single fragments on all sequences. Two parallel tests were run for 20 million generations in the case of dataset (a) and dataset (b) to achieve convergence. The determined substitution model was K81uf+I [63] in both cases, with a proportion I = 0.9667 of invariable sites for dataset (a) and I = 0.9606 for dataset (b). One cold and eleven heated chains were used in both analyses, sampling for every 10,000 generations. After discarding 25% of the samples as burnin, all identified compatible groups were added to consensus trees. The trees were visualized in FigTree [64].

Substitution model for dataset (c) were TrN for fragment B [55], F81 [65] for fragments D, LF, Li and TL and HKY for K2i [66], all without Γ-distributed or invariable loci. The parallel tests were run until achieving convergence (i.e. 5 million generations for fragment K2i, 16 million generations for Li, and 20 million for B, D, LF and TL). Sampling was performed in every 10,000 generations. Twenty-five percent of the samples were discarded as burnin and 50% majority rule consensus trees were constructed. The trees were visualized in FigTree.

To map haplotype relationships for fragment B, we also calculated a median-joining network [67] using the software Network v4.510 (http://www.fluxus-engineering.com/ accessed on September 25 2009). Two 100-year old Norway spruce pollen sequences from Parducci et al. [7] were included in this analysis, and the entire sequence set was truncated to the common length of 112 bp.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

ÁM, JN and EM designed the experiment. EM, MB and MB collected and sampled the extant material. EM provided the fossil samples and the palynological data information. IR conducted the taxonomic identification of the macrofossils. ÁM, JN, EM and LP conducted PCR and sequencing analyses. ÁM and MB performed sequence alignment and data analysis. EM, LP, MB and ÁM wrote the manuscript. All authors read and approved the final manuscript.

Supplementary Material

Open In Web Browser

Acknowledgements

This research was funded by the European Commission through a Marie Curie Reintegration Grant (MERG-CT-2006-041088: Combining Palaeoecology and Palaeogenetics), the Bólyai Scholarship (BO/00518/07) and the OTKA Research Funds (F026036, PD73234) to EKM. This is MTA-MTM Paleo Contribution No. 121. The Hungarian Scholarship Board provided postdoctoral grant to MB at the Hungarian Natural History Museum. Additional funding to MB was provided by the research funding program "LOEWE - Landes-Offensive zur Entwicklung Wissenschaftlich-ökonomischer Exzellenz" of Hesse's Ministry of Higher Education, Research, and the Arts. LP research was supported by The Swedish National Council of Research and The Carl Trygger's Foundation in Sweden. We thank Mária Tuschek and Anikó Gál for her help during laboratory analyses.

Articles from BMC Evolutionary Biology are provided here courtesy of BioMed Central

PMC Copyright Notice

The articles available from the PMC site are protected by copyright, even though access is free. Copyright is held by the respective authors or publishers who provide these articles to PMC. Users of PMC are responsible for complying with the terms and conditions defined by the copyright holder.

Users should assume that standard copyright protection applies to articles in PMC, unless an article contains an explicit license statement that gives a user additional reuse or redistribution rights. PMC does not allow automated/bulk downloading of articles that have standard copyright protection.

See the copyright notice on the PMC site, https://www.ncbi.nlm.nih.gov/pmc/about/copyright/, for further details and specific exceptions.

References

Suyama Y, Kawamuro K, Kinoshita I, Yoshimura K, Tsumura Y, Takahara H. DNA sequence from a fossil pollen of Abies spp. from Pleistocene peat. Genes Genet Syst. 1996;71(3):145–149. [Cross Ref] [PubMed]

Poinar HN, Hofreiter M, Spaulding WG, Martin PS, Stankiewicz BA, Bland H, Evershed RP, Possnert G, Pääbo S. Molecular coproscopy: Dung and diet of the extinct ground sloth Nothrotheriops shastensis. Science. 1998;281:402–406. [Cross Ref] [PubMed]

Dumolin-Lapègue S, Pemonge MH, Gielly L, Taberlet P, Petit RJ. Amplification of oak DNA from ancient and modern wood. Molecular Ecology. 1999;8:2137–2140. [PubMed]

Küch M, Rohland N, Betancourt JL, Latorre C, Steppan S, Poinar HN. Molecular analysis of a 11700-year-old rodent midden from the Atacama Desert, Chile. Molecular Ecology. 2002;11:913–924. [PubMed]

Höss M, Jaruga P, Zastawny TH, Dizdaroglu M, Pääbo S. DNA damage and DNA sequence retrieval from ancient tissues. Nucleic Acids Research. 1996;24:1304–1307. [PubMed]

Coolen MJL, Boere A, Abbas B, Baas M, Wakeham SG, Sinninghe Damsté JS. Ancient DNA derived from alkenone-biosynthesizing haptophytes and other algae in Holocene sediments from the Black Sea. Paleoceanography. 2006;21:. PA1005. [Cross Ref]

Parducci L, Suyama Y, Lascoux M, Bennett KD. Ancient DNA from pollen: a genetic record of population history in Scots pine. Molecular Ecology. 2005;14:2873–82. [Cross Ref] [PubMed]

Lia VV, Confalonieri VA, Ratto N, Hernández JAC, Alzogaray AMM, Poggio L, Brown TA. Microsatellite typing of ancient maize: insights into the history of agriculture in southern South America. Proceedings of the Royal Society London B. 2007;274:545–554. [Cross Ref]

Brown TA, Jones MK, Powell W, Allaby RG. The complex origins of domesticated crops in the Fertile Crescent. Trends in Ecology & Evolution. 2009;24:103–109

Bennett KD, Parducci L. DNA from pollen: principles and potential. The Holocene. 2006;16:1031–1034. [Cross Ref]

Provan J, Bennett KJ. Phylogeographic insights into cryptic glacial refugia. Trends in Ecology and Evolution. 2008;23:564–571. [Cross Ref] [PubMed]

Davis MB, Shaw RG. Range Shifts and Adaptive Responses to Quaternary Climate Change. Science. 2001;292:673–679. [Cross Ref] [PubMed]

Leonard JA. Ancient DNA applications for wildlife conservation. Molecular Ecology. 2008;17:4186–4196. [Cross Ref] [PubMed]

Hofreiter M. Long DNA sequences and large data sets: investigating the Quaternary via ancient DNA. Quaternary Science Reviews. 2008;27:2586–2592. [Cross Ref]

Rohland N, Malaspinas AS, Pollack JL, Slatkin M, Matheus P, Hofreiter M. Proboscidean mitogenomics: chronology and mode of elephant evolution using Mastodon as outgroup. PLoS Biology. 2007;5:e207 [Cross Ref] [PubMed]

Barnes I, Matheus P, Shapiro B, Jensen D, Cooper A. Dynamics of Pleistocene population extinctions in Beringian brown bears. Science. 2002;295:2267–2270. [Cross Ref] [PubMed]

Valdiosera CE, García-Garitagoitia JL, Garcia N, Doadrio I, Thomas MG, Hänni C, Arsuaga JL, Barnes J, Hofreiter M, Orlando L, Götherström A. Surprising migration and population size dynamics in ancient Iberian brown bears (Ursus arctos). Proceedings of the National Academy of Sciences of the USA. 2008;105:5123–5128. [Cross Ref] [PubMed]

Liepelt S, Bialozyt R, Ziegenhagen B. Wind-dispersed pollen mediates postglacial gene flow among refugia. Proceedings of the National Academy of Sciences of the USA. 2002;99:14590–14594. [Cross Ref] [PubMed]

Paffetti D, Vettori C, Caramelli D, Vernesi C, Lari M, Paganelli A, Paule L, Giannini R. Unexpected presence of Fagus orientalis complex in Italy as inferred from 45,000-year-old DNA pollen samples from Venice lagoon. BMC Evolutionary Biology. 2007;7(Suppl 2):S6 [Cross Ref] [PubMed]

Schlumbaum A, Tensen M, Jaenicke-Després V. Ancient plant DNA in archaeobotany. Vegetation History and Archaeobotany. 2008;17:233–244. [Cross Ref]

Vendramin G, Anzidei M, Madaghiele A, Sperisen C, Bucci G. Chloroplast microsatellite analysis reveals the presence of population subdivision in Norway spruce (Picea abies K.). Genome. 2000;43:68–78. [Cross Ref] [PubMed]

Bucci G, Vendramin GG. Delineation of genetic zones in the European Norway spruce natural range: preliminary evidence. Molecular Ecology. 2000;9:923–934. [Cross Ref] [PubMed]

Sperisen C, Büchler U, Gugerli F, Mátyás G, Geburek T, Vendramin GG. Tandem repeats in plant mitochondrial genomes: application to the analysis of population differentiation in the conifer Norway spruce. Molecular Ecology. 2001;10:257–263. [Cross Ref] [PubMed]

Ravazzi C. Late Quaternary history of spruce in southern Europe. Review of Palaeobotany and Palynology. 2002;120:131–177. [Cross Ref]

Tollefsrud MM, Kissling R, Gugerli F, Johnsen O, Skrøppa T, Cheddadi R, Van der Knaap WO, Latałowa M, Terhürne-Berson R, Litt T, Geburek T, Brochmann C, Sperisen C. Genetic consequences of glacial survival and postglacial colonization in Norway spruce: combined analysis of mitochondrial DNA and fossil pollen. Molecular Ecology. 2008;17:4134–4150. [Cross Ref] [PubMed]

Tollefsrud MM, Sonstebo JH, Brochmann C, Johnsen O, Skroppa T, Vendramin GG. Combined analysis of nuclear and mitochondrial markers provide new insight into the genetic structure of North European Picea abies. Heredity. 2009;102:549–562. [Cross Ref] [PubMed]

Fărcaş S, de Beaulieu J, Reille M, Coldea G, Diaconeasa B, Goeury C, Goslar T, Jull T. First ¹⁴C datings of Late Glacial and Holocene pollen sequences from Romanian Carpathes. Comptes Rendus de l'Académie des Sciences - Series III - Sciences de la Vie. 1999;322:799–807

Feurdean A, Wohlfarth B, Björkman L, Tantau I, Bennike O, Willis KJ, Farcas S, Robertsson AM. The influence of refugial population on Lateglacial and early Holocene vegetational changes in Romania. Review of Palaeobotany and Palynology. 2007;145:305–320. [Cross Ref]

Willis K, Sümegi P, Braun M, Tóth A. Does soil change cause vegetation change or vica versa? A temporal perspective from Hungary. Ecology. 1997;78:740–750. [Cross Ref]

Magyari EK, Jakab G, Braun M, Buczkó K, Bálint M. High-resolution study of Late Glacial and Early Holocene tree line changes in the Southern Carpathian Mountains. Geophysical Research Abstracts. 2009;11:10549

Seppä H, Hicks S. Integration of modern and past pollen accumulation rate (PAR) records across the arctic tree-line: a method for more precise vegetation reconstructions. Quaternary Science Reviews. 2006;25:1501–1516

Davis MB, Deevey E. Pollen accumulation rates: estimates from late-glacial sediment of Rogers Lake. Science. 1964;145:1293–1295. [Cross Ref] [PubMed]

Bennett KD. Postglacial population expansion of forest trees in Norfolk, UK. Nature. 1983;303:164–167. [Cross Ref]

Giesecke T, Fontana S. Revisiting pollen accumulation rates from Swedish lake sediments. The Holocene. 2008;18:293–305. [Cross Ref]

Seppä H, Alenius T, Bradshaw RHW, Giesecke T, Heikkilä M, Muukkonen P. Invasion of Norway spruce (Picea abies) and the rise of the boreal ecosystem in Fennoscandia. Journal of Ecolog. 2009;97:629–640

Anderson-Carpenter LL, McLachlan JS, Jackson ST, Kuch M, Lumibao CY, Poinar HN. Ancient DNA from lake sediments: Bridging the gap between paleoecology and genetics. BMC Evolutionary Biology. 2011;11:30 [Cross Ref] [PubMed]

Feurdean AN, Willis KJ, Astaloş C. Legacy of the past land-use changes and management on the 'natural' upland forest composition in the Apuseni Natural Park, Romania. The Holocene. 2009;19:967–981. [Cross Ref]

Hewitt G. Some genetic consequences of ice ages, and their roles in divergence and speciation. Biological Journal of the Linnean Society. 1996;58:247–276

Hewitt G. The genetic legacy of the Quaternary ice ages. Nature. 2000;405:907–913. [Cross Ref] [PubMed]

Petit RJ, Aguinagalde I, de Beaulieu JL, Bittkau C, Brewer S, Cheddadi R, Ennos R, Fineschi S, Grivet D, Lascoux M, Mohanty A, Müller-Starck G, Demesure-Musch B, Palmé A, Martín JP, Rendell S, Vendramin GG. Glacial Refugia: Hotspots But Not Melting Pots of Genetic Diversity. Science. 2003;300(5625):1563–5156. [Cross Ref] [PubMed]

Magri D, Vendramin GG, Comps B, Dupanloup I, Geburek T, Gömöry D, Latałova M, Litt T, Paule L, Roure JM, Tantau I, van der Knaap WO, Petit RJ, de Beaulieu J-L. A new scenario for the quarternary history of European beech populations: paleobotanical evidence and genetic consequences. New Phytologist. 2006;171:199–221. [Cross Ref] [PubMed]

Magyari EK, Braun M, Buczkó K, Kern Z, László P, Hubay K, Bálint M. Radiocarbon chronology of glacial lake sediments in the Retezat Mts (S Carpathians, Romania): a window to Lateglacial and Holocene climatic and palaeoenvironmental changes. Central European Geology. 2009;52:225–248. [Cross Ref]

Comps B, Gömöry, Letouzey D, Thiébaut B, Petit RJ. Diverging Trends Between Heterozygosity and Allelic Richness During Postglacial Colonization in the European Beech. Genetics. 2001;157:389–397. [PubMed]

Nyárádi G. Flora şi vegetaţia Munţilor Retezat. 1958. Bucuresti, Editura Academiei Republicii Populare Române;

Grodzińska K, Godzik B, Frączek W, Badea O, Oszlányi J, Postelnicu D, Shparyk Y. Vegetation of the selected forest stands and land use in the Carpathian Mountains. Environmental Pollution. 2004;130:17–32. [PubMed]

Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen Z, Dewell SB, Du L, Fierro JM, Gomes XV, Godwin BC, He W, Helgesen S, Ho CH, Irzyk GP, Jando SC, Alenquer ML, Jarvie TP, Jirage KB, Kim JB, Knight JR, Lanza JR, Leamon JH, Lefkowitz SM, Lei M, Li J, Lohman KL, Lu H, Makhijani VB, McDade KE, McKenna MP, Myers EW, Nickerson E, Nobile JR, Plant R, Puc BP, Ronan MT, Roth GT, Sarkis GJ, Simons JF, Simpson JW, Srinivasan M, Tartaro KR, Tomasz A, Vogt KA, Volkmer GA, Wang SH, Wang Y, Weiner MP, Yu P, Begley RF, Rothberg JM. Genome sequencing in microfabricated high-density picolitre reactors. Nature. 2005;437:376–380. [PubMed]

Stiller M, Knapp M, Stenzel U, Hofreiter M, Meyer M. Direct multiplex sequencing (DMPS) - a novel method for targeted high-throughput sequencing of ancient and highly degraded DNA. Genome Research. 2009;19:1843–1848. [Cross Ref] [PubMed]

Tinner W, Kaltenrieder P. Rapid responses of high-mountain vegetation to early Holocene environmental changes in the Swiss Alps. Journal of Ecology. 2005;93:936–947. [Cross Ref]

Heled J, Drummond A. Bayesian inference of population size history from multiple loci. BMC Evolutionary Biology. 2008;8:289 [Cross Ref] [PubMed]

Jankovská V. Late glacial finds of Pinus cembra l. in the Lubovnianská kotlina Basin. Folia Geobotanica & Phytotaxonomica. 1984;19:323–325

Jankovská V. Palaeoecology of Pinus cembra, Larix europaea and Picea excelsa in the Poprad part of Spišská kotlina Basin. Diverzita rastlinatva Slovenska, Zbornik zo VI. zjazdu SBS pri SAV. 1995;6:141–145

Navascués M, Emerson BC. Elevated substitution rate estimates from ancient DNA: model violation and bias of the Bayesian methods. Molecular Ecology. 2009;18:4390–4397. [PubMed]

Reuther AU, Urdea P, Geiger C, Ivy-Ochs S, Niller HP, Kubik PW, Heine K. Late Pleistocene glacial chronology of the Pietrele Valley, Retezat Mountains, Southern Carpathians constrained by 10Be exposure ages and pedological investigations. Quaternary International. 2007;164-165:151–169. [Cross Ref]

Pääbo S, Poinar H, Serre D, Jaenicke-Despres V, Hebler J, Rohland N, Kuch M, Krause J, Vigilant L, Hofreiter M. Genetic analyses from ancient DNA. Annual Review of Genetics. 2004;38:645–679. [PubMed]

Tamura K, Dudley J, Nei M, Kumar S; MEGA4. Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Molecular Biology and Evolution. 2004;24:1596–1599. [Cross Ref]

Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research. 1997;25:3389–3402. [Cross Ref] [PubMed]

Nei M. Molecular Evolutionary Genetics. 1987. New York, Columbia University Press;

Tajima F. Evolutionary relationship of DNA sequences in finite populations. Genetics. 1983;105:437–460. [PubMed]

Hudson RR, Boos D, Kaplan NL. A statistical test for detecting population subdivision. Molecular Biology and Evolution. 1992;9:138–151. [PubMed]

Rozas J, Sánchez-DelBarrio JC, Messeguer X, Rozas R. DnaSP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics. 2003;19:2496–2497. [Cross Ref] [PubMed]

Huelsenbeck JP, Ronquist F. MrBayes: Bayesian inference of phylogenetic trees. Bioinformatics. 2001;17:754–755. [Cross Ref] [PubMed]

Posada D, Crandall KA. Modeltest: testing the model of DNA substitution. Bioinformatics. 1998;14:817–818. [Cross Ref] [PubMed]

Kimura M. Estimation of evolutionary distances between homologous nucleotide sequences. Proceedings of the National Academy of Sciences of the USA. 1981;78:454–458. [Cross Ref] [PubMed]

Rambaut A. Figtree: Tree figure drawing tool version 1.2.1. http://tree.bio.ed.ac.uk/. Computer program, Accessed 21 January 2009.

Felsenstein J. Evolutionary trees from DNA sequences: a maximum likelihood approach. Journal of Molecular Evolution. 1981;17:368–376. [Cross Ref] [PubMed]

Hasegawa M, Kishino K, Yano T. Dating the human-ape splitting by a molecular clock of mitochondrial DNA. Journal of Molecular Evolution. 1985;22:160–174. [Cross Ref] [PubMed]

Bandelt HJ, Forster P, Röhl A. Median-joining networks for inferring intraspecific phylogenies. Molecular Biology and Evolution. 1999;16:37–48. [PubMed]

[Back]

Figure 1.

Sampling sites in the Retezat Mountains. (a) Map showing the location of the Retezat Mountains in Europe and (b) in the Carpathians; H: herbarium sample; AF: Austrian Alps. (c) Relief map of the Retezat Mts showing the position of Tăul dintre Brazi lake with location of the extant samples analysed in this study. The location of herbarium specimens is shown in map (b). On map (c) labels mark valleys and tracks in the Retezat Mountains; CP: Carnic-Pietrele; St: Valea Stanisoarei; P: Valea Pietrele; R: Vale Rea; Gt(k): Valea Gales; Buk: Valea Bucura; KR: Rtezatul Mic; B: Buta; M. Valea Marii; Z: Vale Zanoaga.

[Back]

[Back]

Figure 2.

Sample location and schematics of the core TDB-1 (Tăul dintre Brazi) with a digital photo of the sediment where the ancient spruce samples were collected. On the left, depth and calibrated BP timescales are shown.

[Back]

[Back]

Table 1.

Base substitutions detected in extant and ancient cpDNA sequences of Norway spruce (Picea abies)

cpDNA region
CK
MD
B
D
TL
Li
LF
K2i

Variable position

88
107-126
77
78
82
168
196
197
206
154
157
115
133
114

Position total

424
443 - 462
629
630
634
834
872
873
882
1081
1084
1279
1297
1464
Seq. length
Rel. freq.

Extant haplotypes

Ht1.
√
√
C
12A + 5G
A
A
C
G
T
C
G
T
C
T
T
C
1551
0.103

Ht2.
√
√
C
11A + 6G
A
A
C
G
T
C
G
T
C
A
T
C
1551
0.259

Ht3.
√
√
C
11A + 6G
C
A
C
G
T
C
G
T
C
A
T
C
1551
0.103

Ht4.
√
√
C
10A + 6G
A
A
C
G
T
C
G
T
A
A
T
T
1550
0.017

Ht5.
√
√
C
13A + 5G
A
A
C
G
T
C
G
T
C
A
T
C
1552
0.034

Ht6.
√
√
C
12A + 5G
C
A
C
G
T
C
G
T
C
A
T
C
1551
0.034

Ht7.
√
√
C
10A + 6G
A
A
C
G
T
C
G
T
C
A
T
C
1550
0.017

Ht8.
√
√
C
12A + 5G
A
A
C
G
T
C
G
T
C
A
T
C
1551
0.379

Ht9.
√
√
T
12A + 4G + 3A + G
A
C
T
G
T
A
G
C
C
A
G
C
1554
0.017

Macrofossil haplotypes

Cone
√

C
A
C
G
T
C
G

A
T
C
901

S 3.

A
A
C

124

S 4.

T
A

237

S 8.

√

C
A
C
G
T
C
G

575

S 9.
√

C
10A + 7GA + 7G

G
T
C
G

A
T
C
990

S 10.

√

A
A
C
G
T
A
G
T
C

C
1016

S 502-S 545

C
12A + 5G

211

Fossil pollen haplotypes

P1.

C
10A + 6G

212

P2-P3.

C
A
C

124

P4-P11.

G
T
C
G

251

P12.

G
T
A
G

251

P13.

G
G
A
G

251

P14-P15.
√

136

P16-P17.

√

200

(√) successful amplification of the fragment with no variation in the sequence; length of concatenated sequences is shown on the right; rows below the name of the fragments indicate the nucleotide position in the single fragments and in the concatenated sequence, respectively; base substitutions in bold were found only in the fossil material; Ht: haplotype; S: seed; P: pollen

[Back]

[Back]

Table 2.

Genetic diversity and population differentiation estimates in ancient and extant Norway spruce (Picea abies) populations based on six cpDNA loci

No. haplo-types
Haplotype diversity (Hd)
Nucleotide diversity (π)
Average no. differences (k)
Fst
Ks
Kst

B
Ancient
3
0.8333
0.0038
2.6667
0.0000
0.9208
0.0000
ns

Extant
5
0.5777
0.0005
0.8004

D
Ancient
2
0.5333
0.5333
0.5333
0.3266
0.3592
0.0937
**

Extant
3
0.3001
0.3410
0.3409

TL
Ancient
3
0.3846
0.0026
0.7912
0.0580
0.1842
0.4248
*

Extant
2
0.0351
0.0001
0.0351

Li
Ancient
2
0.6667
0.0028
0.6667
0.4569
0.1
0.2304
**

Extant
3
0.0696
0.0003
0.0702

LF
Ancient
1
0.0000
0.0000
0.0000
0.0938
0.2458
0.0036
ns

Extant
3
0.2500
0.0014
0.2544

K2i
Ancient
1
0.0000
0.0000
0.0000
0.0000
0.0333
0.0000
ns

Extant
2
0.0351
0.0002
0.0351

** significant at p < 0.01; * significant at p < 0.05; ns - not significant

[Back]

[Back]

Figure 3.

Phylogenetic tree based on B/MCMC analysis of D, LF, Li and TL chloroplast fragments with ancient sequences indicated in boxes. Posterior probabilities are shown along the branches.

[Back]

[Back]

Figure 4.

Median-joining haplotype network of the chloroplast fragment B. Numbers denote haplotypes found for fragment B only. Haplotype 1 corresponds to Ht9 (Table 1); haplotype 2 includes Ht2, Ht3; haplotype 3 includes Ht1, Ht6, Ht8; haplotype 4 includes Ht 4, Ht7 and P1; haplotype 5 corresponds to Ht5; haplotype 6 corresponds to S9; haplotype 7 corresponds to haplotype R in Parducci et al. (2005). For information on the ancient and extant haplotypes see Table 1 and Additional File 1.

[Back]

[Back]

Figure 5.

Lateglacial and Holocene pollen accumulation rates (PAR) of Norway spruce (Picea abies) from Tăul dintre Brazi in the Retezat Mountains. The dashed line on top of the PAR curve displays a three-term running mean.

[Back]

[Back]

Figure 6.

Pollen and stomata record of Tăul dintre Brazi plotted against depth and calibrated BP timescales. Norway spruce (Picea abies) fossils are highlighted in red. LPAZ: local pollen assemblage zones as in Table 3; ➊ first occurrence of spruce stomata at 13,900 cal yr BP; ➋ -➌ early Holocene population expansion of spruce between 11,750 - 10,780 cal yr BP inferred by pollen and stomata increases. Black rectangles along the timescale bar indicate the position of the radiocarbon dated samples.

[Back]

[Back]

Table 3.

Targeted regions, primer sequences and approximate product length (bp) of PCR for primer pairs used to amplify six cpDNA regions of Norway spruce

Region (short name) | cpDNA region | Primer | Sequence (5' - 3') | Position in cpDNA of Pinus thunbergii NC_001631 | Position in cpDNA of Picea sitchensis NC_011152 | Fragment Length in P. abies (bp)
ndhCp-ndhKp (CK) | pseudogene | ndhK-for1 | CACTTCAGTTCTTGTTGTTCC | 66530→66550 | 66774→66794 | 136 bp
|  | ndhC_ndhK-rev | TCGCCACAGAACCAACGATG | 66666→66647 | 66910→66891 |
psbM-trnD (MD) | intergene spacer | psbM_trnD-f1 | GTTCGAGTAACGGAATCTAAC | 28004→28024 | 27925→27945 | 200 bp
|  | psbM_trnD-rev1 | CGAACGTCTTCTGGAGTAGC | 28204→28185 | 28124→28105 |
Pt3024, ORF46b* (B) | microsatellite | B-for | GCTTATGGCATTGTTGATGT | 30166→30185 | 30701→30720 | 212-216 bp
|  | B-rev | TGGGCATTCTAGCTGTATTG | 30387→30368 | 30941→30922 |
Pt15169, ORF84* (D) | microsatellite | D-for | CTTGGATGGAATAGCAGCC | 15169→15187 | 15208→15226 | 124 bp
|  | D-rev | GGAAGCGCATTAAGGTCATTA | 15286→15266 | 15327→15307 |
trnT-trnL (TL) | intergene spacer | trnT_trnL-sp-f1 | CTGAGCTAAGCAGGCTCAATGG | 69189→69168 | 69573→69552 | 251 bp
|  | trnT_trnL-sp-brev | GCATGTTATTATCCTCCCCTAG | 68945→68967 | 69323→69344 |
trnL (Li) | Intron | trnL-intron-f2 | GAACGCTCTATTTACACC | 68497→68480 | 68884→68867 | 237 bp
|  | trnL-intron-rev | ACACGTAGAATTGGACTCTATC | 68261→68282 | 68648→68669 |
trnL-trnF (LF) | Intergene spacer | Aa_trnLF-for | GGTTCAAGTCCCTCTATCCC | 68198→68179 | ? | 186 bp
|  | Aa_trnLF-rev | ACTGATCAACTCAACTTGTCATAAGATGG | 68014→68042 | 68400→68428 |
matK-trnK (K2i) | intron | trnK2i-f1 | GCCCTCGTTCATGAGAATAACC | 3281→3302 | 3368→3389 | 204 bp
|  | trnK2i-r1 | CATGAGTCAGGAGAGCGATTGG | 3477→3456 | 3573→3552 |

* cpDNA region names from Parducci et al. (2005); primers B and D are from Parducci et al. (2005); primers CK, MD, TL, Li, LF and K2i were designed specifically for this study

[Back]