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Abundant Mitochondrial Genome Diversity, Population Differentiation and Convergent Evolution in Pines
Junyuan Wua, Konstantin V. Krutovskii1,a, and Steven H. Straussaa Department of Forest Science, Oregon State University, Corvallis, Oregon 97331-7501
Corresponding author: Steven H. Strauss, Department of Forest Science, Oregon State University, Corvallis, OR 97331-7501., strauss{at}fsl.orst.edu (E-mail).
Communicating editor: A. H. D. BROWN
| ABSTRACT |
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We examined mitochondrial DNA polymorphisms via the analysis of restriction fragment length polymorphisms in three closely related species of pines from western North America: knobcone (Pinus attenuata Lemm.), Monterey (P. radiata D. Don), and bishop (P. muricata D. Don). A total of 343 trees derived from 13 populations were analyzed using 13 homologous mitochondrial gene probes amplified from three species by polymerase chain reaction. Twenty-eight distinct mitochondrial DNA haplotypes were detected and no common haplotypes were found among the species. All three species showed limited variability within populations, but strong differentiation among populations. Based on haplotype frequencies, genetic diversity within populations (HS) averaged 0.22, and population differentiation (GST and
) exceeded 0.78. Analysis of molecular variance also revealed that >90% of the variation resided among populations. For the purposes of genetic conservation and breeding programs, species and populations could be readily distinguished by unique haplotypes, often using the combination of only a few probes. Neighbor-joining phenograms, however, strongly disagreed with those based on allozymes, chloroplast DNA, and morphological traits. Thus, despite its diagnostic haplotypes, the genome appears to evolve via the rearrangement of multiple, convergent subgenomic domains.
PLANT organelle genomes have been increasingly applied to study population genetic structure and phylogenetic relationships in plants (see reviews in ![]()
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The aim of this study was to intensively assess the level and distribution of mtDNA genetic diversity in the CCCP via sampling of a number of regions of the genome. The CCCP contains three closely related species and includes several disjunct populations and distinctive taxonomic varieties, thus providing samples of several early stages of speciation. It is comprised of one interior species, Pinus attenuata (knobcone pine), and two maritime species, P. muricata (bishop pine) and P. radiata (Monterey pine). Knobcone pine grows on interior sites of southern Oregon and California as disjunct populations. The two other species are distributed discontinuously along the California coast and on four islands (Figure 1; ![]()
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| MATERIALS AND METHODS |
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Plant materials:
Trees were sampled from natural populations or from gene conservation and genetic test plantations, as described in ![]()
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Probe preparation and universal mtDNA primers:
A total of 13 different probes were used in the restriction fragment length polymorphism (RFLP) analysis. Ten probes were specific for different single mtDNA genes: atp1, atp6, cob, cox1, cox2 (exon 1), cox3, nad1 (exon 1), nad3, nad4 (exons 1 and 2 including intron 1), and rps14. Two probes were specific to different parts of nad5: one probe (nad5a) hybridized to exons 1 and 2, including intron 1, and the other (nad5d) hybridized to exons 4 and 5, including intron 4. One probe hybridized to the intergenic region between nad3 and rps12.
Probes were amplified using universal mtDNA-specific primers (Table 1) via the polymerase chain reaction (PCR). To design universal mtDNA-specific primers, we retrived and aligned as many genes of fungal, algal, and higher plant mtDNA sequences as were available from international DNA sequence databases, including GenBank, EMBL, DDBJ, and others. Among plant species, we used monocots, dicots, and gymnosperms when available. GeneRunner (version 3.04; Hastings Software, Inc.) was used for multiple alignment, oligonucleotide analysis, and primer design. Our primary criteria for choosing primer sites and sequences were as follows: (1) high conservation of amino acid sequences across all available organisms; (2) exact or nearly exact matches of DNA sequences across seed plants; (3) avoidance of sites of likely C-to-T editing when possible; (4) nearly perfect matches for the last seven to eight nucleotides and no mismatches for the last four to five nucleotides in the primers' 3' ends; (5) avoidance of amino acids with highly degenerate codons, and preference of those encoding unique and low-degeneracy codons; (6) avoidance of internal repeats, hairpins, internal loops, and dimers; (7) selection of primers with a relatively high melting temperature, usually not less than 55°, and a high G:C ratio; and (8) no significant homologies to cpDNA sequences based on database searches. For these cpDNA homology searches, we used all published cpDNA genome sequences, including liverwort Marchantia polymorpha, maize Zea mays, rice Oryza sativa, tobacco Nicotiana tabacum, and black pine Pinus thunbergii, using the Organelle Genome Database (GOBASE: http://megasun.bch.umontreal.ca/gobase/content.html/).
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Primers were synthesized in the Central Service Laboratory of the OSU Center for Gene Research and Biotechnology using the ABI 380B or 394 DNA synthesizers (Perkin Elmer Applied Biosystems Division, Foster City, CA). To test synthesized primers, we used DNA samples from a large variety of plant species and from enriched cpDNA and mtDNA samples provided by V. Hipkins and J. Aagaard (![]()
RFLP procedures:
Total genomic DNA was extracted from needles using a CTAB-based DNA extraction protocol (![]()
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Preliminary detection of polymorphisms:
For a preliminary survey, two trees were randomly chosen from each of the 13 study populations. Thirteen mtDNA probes and two restriction enzymes (BamHI and XbaI) previously identified as showing high polymorphism (![]()
Data analysis:
Haplotype analysis:
Haplotypes were determined based on having unique restriction fragment patterns over the various combinations of restriction enzymes and probes. Haplotype frequency (where haplotypes are treated as alleles at a single genetic locus) in each population was used to estimate genetic diversity and population differentiation. Genetic diversity and NEI's (1986) population differentiation (GST) adjusted for sample size and population number were calculated using the GeneStat-PC 3.3 program (![]()
value for population subdivision and the standard deviation derived by jackknifing over populations were calculated from individual haplotypes using the Genetic Data Analysis (GDA) program (![]()
Probe-enzyme-based multilocus analysis: To better understand diversity in different parts of the mtDNA genome, we analyzed the data where each probe-enzyme combination was considered as a genetic locus and each restriction fragment profile variant was considered as an allele. Allele frequencies at each locus in each population were then used to estimate the genetic diversity parameters and NEI's (1986) GST using the GeneStat-PC 3.3 program. To give a more accurate estimate of gene diversity than the inflated value that would be obtained if only polymorphic combinations were used (see DISCUSSION), probe-enzyme combinations monomorphic in the preliminary sample were assumed to be monomorphic in all trees.
Analysis of molecular variance (AMOVA):
AMOVA was used to partition molecular variance into different hierarchical levels. Each tree was scored by a vector of ones (presence of a band) and zeros (absence of a band) representing the components of their multibanded RFLP phenotypes. The proportion of shared fragments was calculated for each possible pairwise comparison according to ![]()
, where NAB is the number of bands shared by individuals A and B; NA and NB are the number of bands in individuals A and B, respectively. The distance index was D = 1 - S. All similarity and distance indices were obtained using the RAPDPLOT program (![]()
-statistics, which are analogous to F-statistics. The significance of the variance component was computed using a nonparametric permutation test (![]()
Phylogenetic analysis:
To test the usefulness of mtDNA as a phylogenetic marker, pairwise Manhattan distances (Prevosti distance in ![]()
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| RESULTS |
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Diversity:
Of the 13 probes tested, three probes (atp1, cob, and cox3) failed to reveal any polymorphism, regardless of the restriction enzymes used. Four probes (nad3, nad3-rps12, nad4, and nad5a) detected polymorphism with only XbaI, whereas another 3 probes (atp6, nad1, and rps14) exhibited polymorphism with only BamHI. The other 3 probes (cox1, cox2, and nad5d) showed polymorphism with both enzymes (e.g., Figure 2). However, 2 pairs of probes (nad3 and nad3-rps12; nad1 and rps14) detected identical mtDNA RFLP patterns for the screened individuals. Thus, only one gene from each pair (e.g., nad3 and rps14) was used in the full analysis. In sum, 22 probe-enzyme combinations were used to generate our data.
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Restriction fragment and haplotype polymorphisms:
The 22 probe-enzyme combinations produced a total of 76 scored fragments (detailed data on restriction fragment phenotypes are available at http://www.fsl.orst.edu/tgerc/: "Protocols/Laboratory Data"). The number of fragments produced per combination varied from 1 to 5 for each haplotype, suggesting that several genes have multiple copies in many of the populations. The multiple fragments usually had identical relative hybridization intensities among individuals, which would result from simple duplications and deletions.
A total of 28 haplotypes were identified on the basis of RFLP patterns of all probe-enzyme combinations. The number of fragments for each haplotype ranged from 25 to 38 out of a total of 76 fragments. Only 13 (22%) of the fragments were present among all haplotypes. Sixteen (27%) of the fragments were unique to a single haplotype, and 60 fragments (73%) were shared by 2 or more haplotypes. There were 6 haplotypes for Monterey pine, 11 for knobcone pine, and 11 for bishop pine. There was no haplotype common among any of the populations from the different species (Table 2).
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Genetic diversity within populations:
Eight population samples had two or more haplotypes, and five samples had only a single haplotype. The frequency of common haplotypes in the polymorphic population samples varied from 52 to 96% (Table 2). The Oakland population of knobcone pine and the Santa Cruz population of bishop pine each contained five different haplotypes, while four haplotypes each were detected for the Cambria population of Monterey pine and the Sierra Nevada population of bishop pine.
On average, the gene diversity within populations based on haplotype frequencies was 0.22 (Table 3), ranging from 0.21 to 0.23 between species. As expected, diversity was substantially lower (0.03; Table 4) when each probe-enzyme combination was considered as a genetic locus and each fragment profile variant was designated as an allele; averaged over populations, the number of effective alleles per locus was only slightly higher than one. The percentage of polymorphic loci ranged from a relatively high value of 22.7% in P. attenuata to a low of 11.4% in P. muricata.
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Levels of diversity differed greatly for some populations, depending on whether multilocus or haplotype analysis was used. For example, the Cambria and Mendocino populations each had two main haplotypes occurring in roughly equal frequencies, but the haplotypes differed because of fragment changes at four loci in the Cambria population and at only one locus in the Mendocino population (Table 2; data on web site). As a result, the haplotype diversity of the Mendocino population was similar to that of the Cambria population (0.41 vs. 0.54), but its multilocus diversity was much lower (0.02 vs. 0.08, data not shown). AMOVA analysis showed very low molecular variance within populations (7% of total variance), comparable with our estimate of multilocus diversity (Table 4; HS = 0.03).
Population differentiation:
Haplotype frequencies differed substantially among populations (Table 2). With the exception of one individual of the Cambria population that showed the same haplotype as the Año Nuevo population, every population of Monterey pine and knobcone pine had a distinctive haplotype. The southern populations of bishop pine, San Vicente and Santa Cruz, each had unique haplotypes. No haplotype was shared among species.
Based on haplotype frequencies, NEI's (1986) GST and WEIR and COCKERHAM's (1984)
values were very similar (Table 3). Differentiation among populations within species was 0.79 for Monterey pine, 0.780.79 for knobcone pine, and 0.750.77 for bishop pine. Differentiation among species (0.210.22) and among northern, intermediate, and southern regions of bishop pine (0.340.35) were substantially lower than differentiation among populations in the total species complex (0.78) and in bishop pine as a whole (0.750.77). Thus, the strong population differentiation observed does not accumulate linearly at higher phyletic levels.
GST was considerably higher when the probe-enzyme multilocus analysis was used. Population differentiation varied from 0.87 to 0.93 for three species. AMOVA analysis also demonstrated that the total mtDNA RFLP polymorphism was mainly attributed to the variance among populations within species (87.3% of total variance; P < 0.01). Variance among species and within populations each accounted for <7% of total variance. The
value (FST analog), like GST and
, can be interpreted as the fraction of among group variance compared to the total amount of variance in the reference group. The
values for populations were all >0.90 within the three species (Table 3). Although the
values among species and among regions of bishop pine appeared to be high (0.22 and 0.66, respectively), they were not statistically significant (P > 0.20).
Phylogenetic analysis:
The neighbor-joining phylogenetic tree indicated that mitochondrial genomes representing the species and populations were often polyphyletic (Figure 3). The phenogram topology had three main clusters. One cluster (at bottom) contained four populations from two species and had low bootstrapping support. The four northern populations of bishop pine were grouped into a second paraphyletic cluster with strong bootstrapping support (98%). The third cluster (at the top) included populations from all three species, yet it had very high bootstrapping support (100%).
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| DISCUSSION |
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Diversity:
We used 22 probe-enzyme combinations (11 independent probes and 2 enzymes) to detect mtDNA RFLP polymorphisms in 343 individuals from 13 populations. This appears to be the most intensive genome sample used in plant population genetic studies of mtDNA to date, providing a window on polymorphism and microevolution of the entire genome. By contrast, ![]()
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Based on our preliminary survey, probes nad3 and nad3-rps12, nad1 and rps14 provided identical mtDNA polymorphisms for both enzymes, confirming that the nad3 and rps12 genes and the nad1 and rps14 genes are very closely located in the pine mitochondrial genome, similarly to angiosperms (![]()
The level of mtDNA haplotype diversity is often high in plants. Similar to our results, total gene diversity ranges from 0.68 for lodgepole pine (P. contorta Dougl., ![]()
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Although mtDNA has the lowest sequence mutation rate among the three plant genomes, its presumed high rate of structural rearrangement is likely to be the cause of its high level of diversity. All the polymorphisms that we detected appeared to result from structural rearrangements, particularly large duplications and deletions, rather than point mutations. This is in agreement both with results from previous studies in CCCP (![]()
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Differentiation:
More than three-quarters of mtDNA diversity was distributed among populations in all three species, in contrast to the low population differentiation typical in nuclear genes of long-lived woody species (GST = 0.10; ![]()
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Maternally inherited cytoplasmic polymorphisms in plants are expected to exhibit greater population differentiation at equilibrium than nuclear polymorphisms. This is because of the influence of maternal inheritance on both gene flow and effective population size, and it is a consequence of the lower effective population size of haploid vs. diploid genomes (![]()
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However, cpDNA in conifers shows predominant paternal inheritance (![]()
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Phylogenetic relationships:
Despite high haplotype differentiation, genetic distances between populations were often low. Although nearly every population had unique haplotypes, most of the fragments were shared by other populations, including those of the other species. For example, the Guadalupe population of Monterey pine and the San Vicente population of bishop pine shared no haplotypes, yet they had 24 fragments in common out of 31 total fragments; their genetic distance was only 0.06 (data not shown).
The phylogenetic trees based on our mtDNA analyses roughly agree with those reported in the mtDNA study of ![]()
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The complex nature of mtDNA evolution is probably the cause of its poor performance as a phylogenetic marker. The assumption that the presence or absence of a mtDNA fragment is caused by the same mutational event, and that the phenotypes reflect the underlying mutational events in mtDNA, is likely violated. RFLP polymorphisms of plant mtDNA are mostly length mutations and complex rearrangements rather than site mutations. It is therefore difficult to infer the evolutionary homology among different haplotypes (or fragments) because the complex and overlapping nature of structural changes (![]()
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The high frequency of convergent evolution is likely to be associated with the repetitive nature of mtDNA. mtDNA structural rearrangements are associated with recombination among major repeat elements (![]()
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Although mtDNA rearrangements do not appear to be of value for phylogenetic interpretations in pines, they may be of use in other taxa for grouping closely related genomes (![]()
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| FOOTNOTES |
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1 Permanent address: Laboratory of Population Genetics, N. I. Vavilov Institute of General Genetics, Russian Academy of Sciences, 117809 GSP-1, Moscow B-333, Russia. ![]()
| ACKNOWLEDGMENTS |
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We thank Tony Cario for sampling the San Vicente population of bishop pine, Jan Aagaard and Nathan Strauss for their help in field collections, Bill Libby for his advice and help in accessing the study populations, Steve DiFazio for help with editing the manuscript, and the National Science Foundation (NSF Conservation and Restoration Biology, DEB-9300083) for grant support.
Manuscript received February 27, 1998; Accepted for publication August 19, 1998.
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