Were sea level changes during the Pleistocene in the South Atlantic Coastal Plain a driver of speciation in Petunia (Solanaceae)?
© Ramos-Fregonezi et al.; licensee BioMed Central. 2015
Received: 7 January 2015
Accepted: 27 April 2015
Published: 20 May 2015
Quaternary climatic changes led to variations in sea level and these variations played a significant role in the generation of marine terrace deposits in the South Atlantic Coastal Plain. The main consequence of the increase in sea level was local extinction or population displacement, such that coastal species would be found around the new coastline. Our main goal was to investigate the effects of sea level changes on the geographical structure and variability of genetic lineages from a Petunia species endemic to the South Atlantic Coastal Plain. We employed a phylogeographic approach based on plastid sequences obtained from individuals collected from the complete geographic distribution of Petunia integrifolia ssp. depauperata and its sister group. We used population genetics tests to evaluate the degree of genetic variation and structure among and within populations, and we used haplotype network analysis and Bayesian phylogenetic methods to estimate divergence times and population growth.
We observed three major genetic lineages whose geographical distribution may be related to different transgression/regression events that occurred in this region during the Pleistocene. The divergence time between the monophyletic group P. integrifolia ssp. depauperata and its sister group (P. integrifolia ssp. integrifolia) was compatible with geological estimates of the availability of the coastal plain. Similarly, the origin of each genetic lineage is congruent with geological estimates of habitat availability.
Diversification of P. integrifolia ssp. depauperata possibly occurred as a consequence of the marine transgression/regression cycles during the Pleistocene. In periods of high sea level, plants were most likely restricted to a refuge area corresponding to fossil dunes and granitic hills, from which they colonized the coast once the sea level came down. The modern pattern of lineage geographical distribution and population variation was established by a range expansion with serial founder effects conditioned on soil availability.
KeywordsGenetic diversity Petunia Phylogeography Plant speciation Pleistocene Refuge South Atlantic Coastal Plain
The severe climatic oscillations that occurred during the Pleistocene produced major changes in species distribution and consequently in their genetic diversity. These changes strongly impacted the vegetation at different latitudes and longitudes [1,2]. Some species became extinct over much of their range, some dispersed to new locations, and others survived in refuges and then expanded again; all of these events could have occurred repeatedly during the period [3,4]. Fragmentation, contraction, and expansion of species’ distribution occurred during the Quaternary climate fluctuations and have been suggested as an explanation for the current patterns of genetic diversity found in different lineages [5-7].
The response of vegetation in the Southern Hemisphere to the glacial-interglacial oscillations has been substantially different from that of the Northern Hemisphere [8,9]. Studies from several taxa have reported deep phylogeographic structures in South America dating to the Neogene, possibly as a consequence of old marine transgressions and the uplift of the Andes (for review see ). Nevertheless, genetic consequences of recolonization after the last glacial maximum (LGM) ca. 20 000 years before the present have also been described in species from South America (e.g., [4,10-12]).
Quaternary climatic changes also led to variations in sea level, which was lower during glacial periods and higher during interglacial periods . Periodical transgressions of 100 m above the present level have been reported for the Quaternary [14,15], and some studies [16,17] have indicated that sea level changes during the Quaternary played a significant role in the generation of marine terrace deposits in the South Atlantic Coastal Plain (SACP). Studies along the east-northeast Atlantic Coast in South America have shown that during high sea level, barrier island lagoon systems were the dominant mode of sedimentation (reviewed by ). In the South Atlantic, these systems resulted in a geological formation known as the SACP, which consists of four barrier lagoon depositional systems (Barrier I, II, III and IV) representing the sedimentary record of a marine transgression: three from the Pleistocene and one from the Holocene, dating to 400 000, 325 000, 125 000, and 7000 years before the present, respectively .
The main consequence of the increase in sea level was local extinction or population displacement, such that coastal species would be found around the new coastline. Thus, for coastal species, estuaries and slopes of the mountains may have acted as refuge areas during interglacial periods. Under the refuge hypothesis, one could expect to find evidence of high genetic diversity in areas of stability and lower diversity and the molecular signatures of recent range expansion in the species in unstable, recently recolonized regions [1,20]. The refuge theory has been widely tested for tropical Neotropical biomes , but its general relevance for non-forested biomes has been less explored [10,12].
If refuge areas were important in the SACP during the Pleistocene, it should be possible to find a correlation between genetic diversity and putative ancient refuge areas (see [9,20]). More specifically, one would expect to find areas of high genetic diversity and no signal of recent population growth in refuge areas, whereas recently colonized habitats would have lower genetic diversity and signals of population expansion. Moreover, the age of genetic lineages should be congruent with geographical distribution, and population expansion must postdate SACP origin.
In this work, we used a phylogeographic approach to characterize the genetic diversity of a comprehensive sample of P. integrifolia ssp. depauperata, looking for geographical patterns of genetic variation and lineage distribution that could have emerged during the Pleistocene. Our main aim was to investigate the effects of sea level changes and the putative role of refuge areas for P. integrifolia ssp. depauperata using sequences from two plastid intergenic spacers. We chose these genetic markers because they have been successfully used in phylogeographic studies in Petunia [24,26-30] and in a closely related genus, Calibrachoa Cerv. .
Results and discussion
Characterization of plastid markers used in this work
P. integrifolia ssp. depauperata
P. integrifolia spp. integrifolia
Summary statistics obtained for the three haplogroups and for the whole sampled sequences of Petunia integrifolia ssp. depauperata
Haplotype diversity (sd)
Nucleotide diversity % (sd)
Fu’s F S
Phylogenetic relationships and molecular dating
The three haplogroups of P. integrifolia ssp. depauperata had a striking geographical structure (Figure 2), with one haplogroup distributed in the central part of the species distribution (Center Group), one in the northern part (Northern Group), and the last distributed in the southern part (Southern Group). Haplotypes from the Center Group were observed in individuals from a region of a fossil dune environment and granitic hills that were not affected by changes in the sea level during the Pleistocene [31,32] and were reminiscent of the oldest sea level transgression/regression cycle (Barrier I; ). Haplotypes from the Northern Group were distributed in populations localized in regions associated with Barrier II , which is younger than Barrier I. Finally, haplotypes from the Southern Group occurred in a region corresponding to the more recent Barriers III and IV . Notably, the Northern Group was separated by one mutational step from the central haplogroup, while the southern haplogroup was separated from the northern haplogroup by one mutational step. The northern and southern haplogroups exhibited a marked star-like shape, which might indicate a population expansion.
Different populations shared the four most frequent haplotypes (H1, H4, H5, and H10). Only six populations were monomorphic, and 18 haplotypes were exclusives (Additional file 2). In general, neighbor populations shared haplotypes. Sharing ancestral polymorphisms is common in Petunia species populations [24,28,29] and Calibrachoa [30,33], independent of the geographic distance between the populations. However, neighbor populations may also share haplotypes due to gene flow mediated by pollen and seeds between these populations because the plastid is maternally inherited (through seeds) in Petunia species . The nearly continuous geographical distribution of P. integrifolia ssp. depauperata along the coast may facilitate gene flow either due to higher pollinator displacement or due to seed dispersal caused by the strong winds in the SACP [35,36].
The Bayesian phylogenetic tree displayed two main clades with maximum support values corresponding to P. integrifolia subspecies and a divergence time of approximately 635 thousand years ago (Kya; Figure 2 top). The P. integrifolia ssp. depauperata clade showed the same three haplogroups previously identified in the evolutionary network (Figure 2 bottom). The Center Group was sister to the group formed by individuals from the Northern and Southern Groups. The Northern and Southern Groups diverged from one another ca. 361 Kya, whereas both diverged from the Center Group ca. 488 Kya. These ages are broadly compatible with the estimates of ages for SACP origin and the associated depositional systems , which suggest that the diversification of these haplogroups was possible as soon as new habitat was available for plant colonization in 400 kya (Barrier I), 325 kya (Barrier II), 125 kya (Barrier III), and 7 kya (Barrier IV), respectively.
Posterior probabilities for the most recent common ancestor in phylogeographic reconstruction
P. integrifolia ssp. integrifolia
P. integrifolia ssp. depauperata
The phylogeographic model assumes constant migration rates throughout evolutionary history. While this is clearly not the case for our analyses because some of the regions were submerged and thus unavailable for plant migration, the results highlight our hypothesis of a refuge in the center of distribution and posterior migration to the north and to the south. Even without informing the model that the southern and northern portions of the SAPC were not available habitats early in their evolutionary history, we infer the origin of these populations of P. integrifolia ssp. depauperata to be in the western regions, from P. integrifolia ssp. integrifolia individuals, and migration to the coastal regions to only happen in more recent times (Figure 2).
Population structure and spatial genetic analysis
Analysis of molecular variance (AMOVA) for the Petunia integrifolia ssp . depauperata estimated using two hierarchical models: two-level model includes only populations and three-level model includes all populations distributed in the three haplogroups observed
Source of variation
Sum of squares
Φ ST = 0.656*
Φ CT = 0.642*
Among populations within groups
Φ SC = 0.246*
Φ ST = 0.730*
Fu’s F S value was negative and significant (-16.5, P < 0.02), whereas Tajima’s D was also negative but marginally non-significant (-1.31, P = 0.05) for P. integrifolia ssp. depauperata. Tajima’s D and Fu’s F s are classical neutrality tests used to assess population demographic history. Both assume that populations have been in mutation–drift balance for a long period of time . Negative values in both tests are indicative of a demographic expansion. Together with the star-like shape observed in the networks, particularly for the Northern and Southern Groups, this may suggest a population expansion associated with SACP colonization.
The Northern group presented the lower haplotype diversity (h = 0.27) and a significant Fu’s F S (-4.09, P < 0.02), while the Southern group displayed the lower nucleotide diversity (π = 0.03) and significant and negative values for both neutrality tests (Tajima’s D = -1.92, P < 0.05; Fu’s F S = -11.30, P < 0.02) (Table 2).
The higher genetic diversity and lack of indication of population growth are perfectly compatible with Center group representing a refuge for P. integrifolia ssp. depauperata. However, the smaller genetic diversity and signals of population expansion suggest that Southern and Northern groups represent distinct events of range expansion from the refuge as long as SACP became available for this taxon.
There are several species endemic to the SACP, but few studies have used a phylogeographic perspective to put in evolutionary context the genetic variation in this region. Mäder et al. , studying C. heterophylla, found that this species migrated from the west to colonize the SACP, with paleo river channels associated with the main genealogical lineages differentiation at SACP. Lopes et al.  studied a subterranean rodent in the same geographic area and identified (modern) rivers acting as effective barriers to gene flow in this species. Strikingly, P. integrifolia ssp. depauperata seems to be less sensitive to rivers in the SACP, as its genetic groups occurred along a wide area. This may be related to a different seed dispersal efficiency compared with C. heterophylla, for which rivers were more efficient barriers .
Single-locus studies may be problematic because single markers may tell a different evolutionary history compared to the rest of the genome [39-41]. However, it has also been recently suggested that one or a few small fragments presenting highly informative content could be better in solving the evolutionary relationships among lineages than a large genome survey with incongruent results . In this sense, cpDNA markers applied to Petunia and in the closely related genus Calibrachoa [33,43] have been able to clarify the evolutionary relationships among species and among lineages within species [24,27,29,44-46].
Considering the results presented here and the absence of many studies in the South Atlantic Coastal Region, especially in regards to plant species and the influence of changes in the sea level on genetic variability distribution, this is an important contribution to the understanding of the processes that drove evolution.
Climate changes that occurred during the Pleistocene influenced the sea level in the South Atlantic Coastal Plain and promoted genetic differentiation and speciation in the herbaceous annual plant Petunia integrifolia ssp. depauperata. During this period, plants were restricted to a refuge area, represented by the central part of its current distribution, corresponding to fossil dunes and granitic hills, from which plants colonized the coast as soon as marine regressions exposed suitable lands. This inference is supported by genetic diversity and population expansion statistics. This is the first time that a refuge is proposed on the south edge of the Atlantic Coast.
Plant material, DNA extraction, PCR amplification and sequencing
A total of 291 individuals of P. integrifolia ssp. depauperata were identified and sampled from 30 locations, with regular distance intervals, covering all of the known distribution of this taxon, including the adjacent northern and southern areas (Figure 1, locations numbered from 1 to 30, hereafter named as populations). In addition, 85 individuals of P. integrifolia ssp. integrifolia were used in comparative approaches and in dating estimates. We obtained the geographic coordinates by Global Positioning System (GPS), and vouchers were deposited in the BHCB herbarium, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil. Total DNA was extracted from young leaves carefully collected for genetic analysis. Silica gel dried leaves were frozen in liquid nitrogen and ground to a fine powder, and DNA was extracted with cetyltrimethyl ammonium bromide (CTAB) protocol as described by Roy et al. . This work was conducted under permit MP 2.186/16 of the Brazilian Federal Government to access plant genetic information to develop evolutionary or taxonomic studies. No specific collection permits were required because neither taxa are endangered or protected and because no population occurs on protected areas.
Polymerase chain reaction (PCR) was employed to amplify the non-coding plastid trnH-psbA and trnS-trnG intergenic spacers, using the universal primers previously described ([48,49], respectively), and following amplification conditions described in Lorenz-Lemke et al. . The PCR products were purified according to Dunn and Blatnner  and sequenced in a MegaBACE1000 (GE Healthcare Bio Sciences Corp., Piscataway, NY, USA) automatic sequencer according to the manufacturer’s instructions and the DYEnamicET Terminator Sequencing Premix Kit (GE Healthcare). Tables S1 and S2 in Additional information provide voucher information, GenBank accession numbers, and the general geographic information for each sample.
Sequence analysis and molecular diversity
For each marker, both forward and reverse strands were checked using Chromas (available at website: http://technelysium.com.au/) and aligned manually in GeneDoc . Because the plastid segments are naturally linked and this genome is usually non-recombining, a common situation in plant phylogenies, the two markers were combined in a single concatenated set. All insertion/deletion events (indels) that involved poly A/T were eliminated from the analyses because their homologies cannot be adequately accessed . Contiguous indels of more than one base pair (bp) were treated as one mutational event . Descriptive statistics of genetic variability, such as haplotype (h) and nucleotide (π) diversities , were estimated in Arlequin 3.5 .
The evolutionary relationships between haplotypes were estimated using the median-joining network method (e = 0; ) as implemented in the Network 4.6 software (available at website: http://www.fluxus-engineering.com/sharenet.htm).
The dated Bayesian phylogenetic tree of haplotypes was inferred using Beast 1.8.0  with a Yule tree prior and the HKY substitution model with four gamma-distributed rate categories based on results from the Akaike Information Criterion in jModelTest 2 . We also used a lognormal relaxed clock and went to the literature for an informed prior for the nucleotide substitution rate. We compiled rates calculated for plastid markers for shrubs or herbaceous plants with generation time of up to three years, features that are similar to Petunia. We found eight published rates that fit these criteria, varying between 1 x 10-9 and 8.24 x 10-9 substitutions per site per year (s/s/y) [59-63]. To take into account this rate heterogeneity, we used a gamma distribution prior with a shape parameter 1.6 and scale parameter 1.6 x 10-9 as prior. We assumed an offset value of 1 x 10-9 s/s/y, such that the median of the prior was 3.05 x 10-9 s/s/y, allowing rate values of 8.24 x 10-9 s/s/y to be reached with low probability (distribution graphical result is available in Additional file 3).
Discrete phylogeographical analysis
For the phylogeographic reconstruction, we modeled geography through the discrete phylogeographic diffusion model of  and used the Bayesian stochastic search variable selection (BSSVS) procedure in Beast. We classified sampling locations in four discrete states: southern coastal plain (Southern), northern coastal plain (Northern), Center, and “integrifolia” (corresponding to inland individuals of P. integrifolia ssp. integrifolia). We then estimated a reconstruction of the phylogeographic history of the clade. We also explored different choices of prior distributions for migration rates in this model, including a uniform prior and a distance-informed prior, and we found that additional information on geographic distances between locations had little impact on the estimated rates.
For each of the above analyses, two independent runs consisting of 1 x 108 Markov chain Monte Carlo (MCMC) iterations were performed, sampling every 1000 generations; 10% of iterations were removed as burn-in. Convergence was checked by visual inspection of the independent runs in Tracer 1.6  so that all parameters had effective sample sizes (ESS) > 200. We obtained the maximum clade credibility (MCC) tree and the posterior probabilities (PP) for each node  using the TreeAnnotator from Beast package, and finally, we used Figtree 1.4.0  to draw and edit the resulting phylogenetic trees.
We also used Arlequin to perform an analysis of molecular variance (AMOVA; ) to quantify the degree of genetic structure among groups of populations, which was performed using Φ-statistics and 1000 permutations to test significance. The Mantel test was used to evaluate the correlation between genetic and geographic distances, using 1000 permutations in the program Alleles in Space 1.0 . We used Samova 1.0  to estimate the number of genetic homogeneous groups (K) for P. integrifolia ssp. depauperata through a spatial analysis of molecular variance. Following this, we used Arlequin to estimate AMOVA and genetic variability statistics for the groups defined by Samova, as described previously.
We also used Arlequin to perform the neutrality tests Tajima’s D  and Fu’s Fs . Historical changes in the effective size of P. integrifolia ssp. depauperata were also inferred through the Bayesian Skyline Plot (BSP; ) method implemented in Beast, using the same prior and conditions described previously except that all individual sequences were included and the Bayesian Skyline tree prior was used. The BSP reconstruction was done using Tracer 1.6.
Availability of supporting data
Sequences are deposited in GenBank (accession numbers available in Additional file 1).
The authors thank A.P. Lorenz-Lemke, G. Mäder, and P.D. Togni for help with fieldwork and J.R. Stehmann for taxonomic assistance. This project was supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), and the programa de Pós-Graduação em Genética e Biologia Molecular da Universidade Federal do Rio Grande do Sul (PPGBM-UFRGS).
- Bennett KD, Provan J. What do we mean by ‘refugia’? Quat Sci Rev. 2008;27:2449–55.View ArticleGoogle Scholar
- Stewart JR, Lister AM, Barnes I, Dalén L. Refugia revisited: individualistic responses of species in space and time. Proc Roy Soc Lond B. 2010;277:661–71.View ArticleGoogle Scholar
- Hewitt GM. Genetic consequences of climatic oscillations in the Quaternary. Phil Trans Roy Soc B. 2004;359:183–95.View ArticleGoogle Scholar
- Hewitt GM. Quaternary phylogeography: the roots of hybrid zones. Genetica. 2011;139:617–38.View ArticlePubMedGoogle Scholar
- Hewitt GM. Some genetic consequences of ice ages, and their role in divergence and speciation. Biol J Linn Soc. 1996;58:247–76.View ArticleGoogle Scholar
- Hewitt GM. Post glacial recolonization of European biota. Biol J Linn Soc. 1999;68:87–112.View ArticleGoogle Scholar
- Taberlet P, Fumagalli L, Wust-Saucy AG, Cosson JF. Comparative phylogeography and postglacial colonization routes in Europe. Mol Ecol. 1998;7:453–64.View ArticlePubMedGoogle Scholar
- Markgraf V, McGlone M, Hope G. Neogene paleoenvironmental and paleoclimatic change in southern temperate ecosystems a southern perspective. Trends Ecol Evol. 1995;10:143–7.View ArticlePubMedGoogle Scholar
- Keppel G, van Niel KP, Wardell-Johnson GW, Yates CJ, Byrne M, Mucina L, et al. Refugia: identifying and understanding safe havens for biodiversity under climate change. Gl Ecol Biogeogr. 2012;21:393–404.View ArticleGoogle Scholar
- Turchetto-Zolet AC, Pinheiro F, Salgueiro F, Palma-Silva C. Phylogeographical patterns shed light on evolutionary process in South America. Mol Ecol. 2013;22:1193–213.View ArticlePubMedGoogle Scholar
- Hewitt GM. The genetic legacy of the Quaternary ice ages. Nature. 2000;405:907–13.View ArticlePubMedGoogle Scholar
- Beheregaray LB. Twenty years of phylogeography: the state of the field and the challenges for the Southern Hemisphere. Mol Ecol. 2008;17:3754–74.PubMedGoogle Scholar
- Lambeck K, Esat TM, Potter EK. Links between climate and sea levels for the past three million years. Nature. 2002;419:199–206.View ArticlePubMedGoogle Scholar
- Yokoyama Y, Lambeck K, Johnston P, Deckker P, Fifield K. Timing of the last glacial maximum from observed sea level minima. Nature. 2000;406:713–6.View ArticlePubMedGoogle Scholar
- Ponce JF, Rabassa J, Coronato A, Borromei AM. Paleogeographical evolution of the Atlantic coast of Pampa and Patagonia from the last glacial maximum to the Middle Holocene. Biol J Linn Soc. 2011;103:363–79.View ArticleGoogle Scholar
- Bigarella JJ, Andrade GO. Contributions to the study of the Brazilian Quaternary. Geol Soc Spec Publ. 1965;84:433–51.Google Scholar
- Suguio K, Martin L, Bittencourt ACSP, Dominguez JML, Flexor JM, Azevedo AEG. Quaternary emergent and submergent coast: comparison of the Holocene sedimentation in Brazil and Southeastern United States. An Acad Bras Cienc. 1984;56:163–7.Google Scholar
- Dominguez JML, Bittencourt ACSP, Martin L. Controls on Quaternary coastal evolution of the east northeastern coast of Brazil: roles of sea level history, trade winds and climate. Sed Geol. 1992;80:213–32.View ArticleGoogle Scholar
- Martin L, Suguio K, Flexor JM. Hauts niveaux marins pléistocènes du littoral Brésilien. Palaeogeogr Palaeoclim Palaeoecol. 1988;68:231–9.View ArticleGoogle Scholar
- Carnaval AC, Hickerson MJ, Haddad CFB, Rodrigues MT, Moritz C. Stability predicts genetic diversity in the Brazilian Atlantic forest hotspot. Science. 2009;323:785–9.View ArticlePubMedGoogle Scholar
- Gübitz T, Hoballah ME, Dell’Olivo A, Kuhlemeier C. Petunia as a model system for the genetics and evolution of pollination syndromes. In: Gerats T, Strommer J, editors. Petunia evolutionary, developmental and physiological genetics. New York: Springer; 2009. p. 29–49.Google Scholar
- Stehmann JR, Lorenz-Lemke AP, Freitas LB, Semir J. The genus Petunia. In: Gerats T, Strommer J, editors. Petunia evolutionary, developmental and physiological genetics. New York: Springer; 2009. p. 1–28.Google Scholar
- Reck-Kortmann M, Silva-Arias GA, Segatto ALA, Mäder G, Bonatto SL, Freitas LB. Multilocus phylogeny reconstruction: new insights into the evolutionary history of the genus Petunia. Mol Phylogen Evol. 2014;81:19–28.View ArticleGoogle Scholar
- Lorenz-Lemke AP, Togni PD, Mäder G, Kriedt RA, Stehmann JR, Salzano FM, et al. Diversification of plant species in a subtropical region of eastern South American highlands: a phylogeographic perspective on native Petunia (Solanaceae). Mol Ecol. 2010;19:5240–51.View ArticlePubMedGoogle Scholar
- Stehmann JR, Bohs L. Nuevas combinaciones en Solanaceae. Darwiniana. 2007;45:240–1.Google Scholar
- Longo D, Lorenz-Lemke AP, Mäder G, Bonatto SL, Freitas LB. Phylogeography of the Petunia integrifolia complex in southern Brazil. Bot J Linn Soc. 2014;174:199–213.View ArticleGoogle Scholar
- Lorenz-Lemke AP, Mäder G, Muschner VC, Stehmann JR, Bonatto SL, Salzano FM, et al. Diversity and natural hybridization in a highly endemic species of Petunia (Solanaceae): a molecular and ecological analysis. Mol Ecol. 2006;15:4487–97.View ArticlePubMedGoogle Scholar
- Segatto ALA, Cazé ALR, Turchetto C, Klahre U, Kuhlemeier C, Bonatto SL, et al. Nuclear and plastid markers reveal the persistence of genetic identity: A new perspective on the evolutionary history of Petunia exserta. Mol Phylogen Evol. 2014;70:504–12.View ArticleGoogle Scholar
- Turchetto C, Fagundes NJR, Segatto ALA, Kuhlemeier C, Solís-Neffa VG, Speranza PR, et al. Diversification in the South American Pampas: The genetic and morphological variation of the widespread Petunia axillaris complex (Solanaceae). Mol Ecol. 2014;23:374–89.View ArticleGoogle Scholar
- Mäder G, Fregonezi JN, Lorenz-Lemke AP, Bonatto SL, Freitas LB. Geological and climatic changes in quaternary shaped the evolutionary history of Calibrachoa heterophylla, an endemic South Atlantic species of petunia. BMC Evol Biol. 2013;13:178.View ArticlePubMed CentralPubMedGoogle Scholar
- Villwock JA, Tomazelli LJ, Loss EL, Dehnhardt EA, Horn NO, Bachi FA, et al. Geology of the Rio Grande do Sul Coastal Province. Quat South Amer Antarct Penin. 1986;4:79–97.Google Scholar
- Pessenda LCR, Gouveia SEM, Ribeiro AS, Oliveira PE, Aravena R. Late Pleistocene and Holocene vegetation changes in northeastern Brazil determined from carbon isotopes and charcoal records in soils. Palaeogeog Palaeoclim Palaeoecol. 2010;297:597–608.View ArticleGoogle Scholar
- Fregonezi JN, Turchetto C, Bonatto SL, Freitas LB. Biogeographical history and diversification of Petunia and Calibrachoa (Solanaceae) in the Neotropical Pampas grassland. Bot J Linn Soc. 2013;171:140–53.View ArticleGoogle Scholar
- Derepas A, Dulieu H. Inheritance of the capacity to transfer plastids by pollen parent in Petunia hybrida Hort. J Hered. 1992;83:6–10.Google Scholar
- Garzoli S, Simionato C. Baroclinic instabilities and forced oscillations in the Brazil/Malvinas confluence front. Deep Sea Res. 1990;37:1053–74.View ArticleGoogle Scholar
- Goni GJ, Wainer I. Investigation of the Brazil Current front variability from altimer data. J Geophys Res. 2001;106:31117–28.View ArticleGoogle Scholar
- Nei M, Kumar S. Molecular evolution and phylogenetics. New York: Oxford University Press; 2000.Google Scholar
- Lopes CM, Ximenes SSF, Gava A, Freitas TRO. The role of chromosomal rearrangements and geographical barriers in the divergence of lineages in a South American subterranean rodent (Rodentia: Ctenomyidae: Ctenomys minutus). Heredity. 2013;111:293–305.View ArticlePubMed CentralPubMedGoogle Scholar
- Maddison WP, Knowles LL. Inferring phylogeny despite incomplete lineage sorting. Syst Biol. 2006;55:21–30.View ArticlePubMedGoogle Scholar
- Townsend JP. Profiling phylogenetic informativeness. Syst Biol. 2007;56:222–31.View ArticlePubMedGoogle Scholar
- Townsend JP, Su Z, Tekle YI. Phylogenetic signal and noise: predicting the power to resolve a phylogeny. Syst Biol. 2012;61:835–49.View ArticlePubMedGoogle Scholar
- Horreo JL. ‘Representative Genes’, is it OK to use a small amount of data to obtain a phylogeny that is at least close to the true tree? J Evol Biol. 2012;25:2661–4.View ArticlePubMedGoogle Scholar
- Fregonezi JN, Freitas LB, Bonatto SL, Semir J, Stehmann JR. Infrageneric classification of Calibrachoa (Solanaceae) based on morphological and molecular evidence. Taxon. 2012;61:120–30.Google Scholar
- Ando T, Kokubun H, Watanabe H, Tanaka N, Yukawa T, Hashimoto G, et al. Phylogenetic analysis of Petunia sensu Jussieu (Solanaceae) using chloroplast DNA RFLP. Ann Bot. 2005;96:289–97.View ArticlePubMed CentralPubMedGoogle Scholar
- Kulcheski FR, Muschner VC, Lorenz-Lemke AP, Stehmann JR, Bonatto SL, Salzano FM, et al. Molecular phylogenetic analysis of Petunia Juss. (Solanaceae). Genetica. 2006;126:3–14.View ArticlePubMedGoogle Scholar
- Chen S, Matsubara K, Omori T, Kokubun H, Kodama H, Watanabe H, et al. Phylogenetic analysis of the genus Petunia (Solanaceae) based on the sequence of the HF1 gene. J Plant Res. 2007;120:385–97.View ArticlePubMedGoogle Scholar
- Roy A, Frascaria N, MacKay J, Bousquet J. Segregating random amplified polymorphic DNAs (RAPDs) in Betula alleghaniensis. Theor App Genet. 1992;85:173–80.Google Scholar
- Hamilton MB. Four primers pairs for the amplification of chloroplast intergenic regions with intraspecific variation. Mol Ecol. 1999;8:513–25.View ArticleGoogle Scholar
- Sang T, Crawford DJ, Stuessy TF. Chloroplast DNA phylogeny, reticulate evolution, and biogeography of Paeonia (Paeoniaceae). Am J Bot. 1997;84:1120–36.View ArticlePubMedGoogle Scholar
- Dunn IS, Blattner FR. Charons 36–40: multi enzyme, high capacity, recombination deficient replacement vectors with polylinkers and polystuffers. Nucl Acids Res. 1987;15:2677–98.View ArticlePubMed CentralPubMedGoogle Scholar
- Nicholas KB, Nicholas Jr HB, Deerfield II DW. GeneDoc: analysis and visualization of genetic variation. Embnew News. 1997;4:14.Google Scholar
- Aldrich J, Cherney BW, Merlin E, Christopherson L. The role of insertion/deletions in the evolution of the intergenic region between psbA and trnH in the chloroplast genome. Curr Genet. 1988;14:137–46.View ArticlePubMedGoogle Scholar
- Simmons MP, Ochoterena H. Gaps as characters in sequence based phylogenetic analyses. Syst Biol. 2000;49:369–81.View ArticlePubMedGoogle Scholar
- Nei M. Molecular evolutionary genetics. New York: Columbia University Press; 1987.Google Scholar
- Excoffier L, Lischer HEL. Arlequin suite ver. 3.5: A new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Res. 2010;10:564–7.View ArticleGoogle Scholar
- Bandelt HJ, Forster P, Röhl A. Median joining networks for inferring intraspecific phylogenies. Mol Biol Evol. 2005;16:37–48.View ArticleGoogle Scholar
- Drummond AJ, Suchard MA, Xie D, Rambaut A. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol Biol Evol. 2012;29:1969–73.View ArticlePubMed CentralPubMedGoogle Scholar
- Darriba D, Taboada GL, Doallo R, Posada D. jModelTest 2: more models, new heuristics and parallel computing. Nature Meth. 2012;9:772.View ArticleGoogle Scholar
- Zurawski G, Clegg MT, Brown AHD. The nature of nucleotide sequence divergence between barley and maize chloroplast DNA. Genetics. 1984;106:735–49.PubMed CentralPubMedGoogle Scholar
- Wolfe KH, Li WH, Sharp PM. Rates of nucleotide substitution vary greatly among plant mitochondrial, chloroplast, and nuclear DNAs. Proc Natl Acad Sci U S A. 1987;84:9054–8.View ArticlePubMed CentralPubMedGoogle Scholar
- Richardson JE, Pennington RT, Pennington TD, Hollingsworth PM. Rapid diversification of a species rich genus of Neotropical rain forest trees. Science. 2001;293:2242–5.View ArticlePubMedGoogle Scholar
- Mummenhoff K, Linder P, Friesen N, Bowman JL, Lee JY, Franzke A. Molecular evidence for bicontinental hybridogenous genomic constitution in Lepidium sensu stricto (Brassicaceae) species from Australia and New Zealand. Am J Bot. 2004;91:254–61.View ArticlePubMedGoogle Scholar
- Yamane K, Yano K, Kawahara T. Pattern and rate of indel evolution inferred from whole chloroplast intergenic regions in sugarcane, maize and rice. DNA Res. 2006;13:197–204.View ArticlePubMedGoogle Scholar
- Lemey P, Rambaut A, Drummond AJ, Suchard MA. Bayesian phylogeography finds its roots. PLoS Comp Biol. 2009;5, e1000520.View ArticleGoogle Scholar
- Rambaut A, Suchard MA, Xie D, Drummond AJ. Tracer v1.5. http://beast.bio.ed.ac.uk/Tracer.
- Rannala B, Yang ZH. Probability distribution of molecular evolutionary trees: a new method of phylogenetic inference. J Mol Evol. 1996;43:304–11.View ArticlePubMedGoogle Scholar
- Rambaut A. FigTree v1.4: Tree Fig. drawing tool. http://tree.bio.ed.ac.uk/software/figtree/.
- Excoffier L, Smouse PE, Quattro M. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics. 1992;131:479–91.PubMed CentralPubMedGoogle Scholar
- Miller M. Alleles in space: computer software for the joint analysis of interindividual spatial and genetic information. J Hered. 2005;96:722–4.View ArticlePubMedGoogle Scholar
- Dupanloup I, Schneider S, Excoffier L. A simulated annealing approach to define the genetic structure of populations. Mol Ecol. 2002;11:2571–81.View ArticlePubMedGoogle Scholar
- Tajima F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics. 1989;123:585–95.PubMed CentralPubMedGoogle Scholar
- Fu YX. Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics. 1997;147:915–25.PubMed CentralPubMedGoogle Scholar
- Drummond AJ, Suchard MA. Bayesian random local clocks or one rate to rule them all. BMC Biol. 2010;8:114.View ArticlePubMed CentralPubMedGoogle Scholar
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