Skip to main content

Advertisement

SpringerLink
Log in

Influences of environmental and spatial factors on genetic and epigenetic variations in Rhododendron oldhamii (Ericaceae)

  • Original Paper
  • Published:
Tree Genetics & Genomes Aims and scope Submit manuscript

Abstract

Test of the relationship of genetic and particularly epigenetic variation with geographic isolation and environment is important to reveal potential environmental drivers for selection. Rhododendron oldhamii is widespread but inhabits fragmented subtropical forest landscapes, and populations across its range may exhibit different levels of genetic and epigenetic structuring correlated to their environmental conditions. Here, we investigated the genetic and epigenetic variations and their ecological correlates in R. oldhamii. Genetic and epigenetic variations were surveyed using amplified fragment length polymorphism (AFLP) and methylation-sensitive amplification polymorphism (MSAP), respectively. Using variation partitioning by redundant analysis (RDA), we examined the pure and spatially structured environmental effects and pure spatial factors on genetic and epigenetic variations among individuals collected from 18 localities across R. oldhamii distribution range in Taiwan. We found that environments compared to geographic isolation among sites explained more genetic and epigenetic variations. Patchy distribution of the contemporary R. oldhamii populations was revealed by correlograms with patch size of approximately around 20–30 km based on the total genetic and epigenetic data. Spatial variables derived from the method of principal coordinates of neighbor matrices (PCNM), including PCNM3, PCNM5, PCNM7, and PCNM8 representing biotic processes, such as individual dispersal, were found to be important influencing potentially adaptive genetic and epigenetic variations. Annual mean temperature, annual precipitation, precipitation of the warmest quarter, aspect, slope, and soil moisture were the most important environmental variables influencing potentially adaptive genetic and epigenetic variations and could be particularly important for the evolution of local adaptation in R. oldhamii.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Batke SP, Jocque M, Kelly DL (2014) Modelling hurricane exposure and wind speed on a mesoclimate scale: a case study from Cusuco NP, Honduras. PLoS One 9:e91306

    Article  PubMed Central  PubMed  Google Scholar 

  • Bartoń K (2013) MuMIn: multi-model inference. R package version 1(9):13, Available at: http://CRAN.R-project.org/package=MuMin. Accessed 29 October 2013

    Google Scholar 

  • Beaumont MA, Balding DJ (2004) Identifying adaptive genetic divergence among populations from genome scans. Mol Ecol 13:969–980

    Article  CAS  PubMed  Google Scholar 

  • Blanchet FG, Legendre P, Borcard D (2008) Forward selection of explanatory variables. Ecology 89:2623–2632

    Article  PubMed  Google Scholar 

  • Borcard D, Legendre P (2002) All-scale spatial analysis of ecological data by means of principal coordinates of neighbor matrices. Ecol Model 153:51–68

    Article  Google Scholar 

  • Borcard D, Legendre P, Drapeau P (1992) Partialling out the spatial component of ecological variation. Ecology 73:1045–1055

    Article  Google Scholar 

  • Borcard D, Gillet F, Legnedre P (2011) Numerical ecology with R. Springer, New York

    Book  Google Scholar 

  • Bossdorf O, Richards CL, Pigliucci M (2008) Epigenetics for ecologists. Ecol Lett 11:106–115

    PubMed  Google Scholar 

  • Bothwell H, Bisbing S, Therkildsen NO, Crawford L, Alvarez N, Holderegger R, Manel S (2013) Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach. Conserv Genet 14:467–481

    Article  Google Scholar 

  • Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach. Springer, New York

    Google Scholar 

  • Caccamo G, Chisholm LA, Bradstock RA, Puotinen ML (2011) Assessing the sensitivity of MODIS to monitor drought in high biomass ecosystems. Rem Sens Environ 115:2626–2639

    Article  Google Scholar 

  • Carrera-Hernández JJ, Gaskin SJ (2007) Spatio temporal analysis of daily precipitation and temperature in the basin of Mexico. J Hydrol 336:231–249

    Article  Google Scholar 

  • Chang L-W, Zelený D, Li C-F, Chiu S-T, Hsieh C-F (2013) Better environmental data may reverse conclusions about niche- and dispersal-based processes in community assembly. Ecology 94:2145–2151

    Article  PubMed  Google Scholar 

  • Chen C-Y, Liang B-K, Chung J-D, Chang C-T, Hsieh Y-C, Lin T-C, Hwang S-Y (2014) Demography of the upward-shifting temperate woody species of the Rhododendron pseudochrysanthum complex and ecologically relevant adaptive divergence in its trailing edge populations. Tree Genet Gen 10:111–126

    Article  CAS  Google Scholar 

  • Chiou C-R, Song G-Z M, Chien J-H, Hsieh C-F, Wang J-C, Chen M-Y, Liu H-Y, Yeh C-L, Hsia Y-J, Chen T-Y (2010) Altitudinal distribution patterns of plant species in Taiwan are mainly determined by the northeast monsoon rather than the heat retention mechanism of Massenerhebung. Bot Stud 51:89–97

    Google Scholar 

  • Cottenie K (2005) Integrating environmental and spatial processes in ecological community dynamics. Ecol Lett 8:1175–1182

    Article  PubMed  Google Scholar 

  • Dray S (2013) Packfor: forward selection with permutation (Canoco p.46), R package version 0.0-8. Available at: http://r-forge.r-project.org/R/?group_id=195. Accessed 25 October 2013

  • Dray S, Legendre P, Peres-Neto PR (2006) Spatial-modelling: a comprehensive framework for principal coordinate analysis of neighbor matrices (PCNM). Ecol Model 196:483–493

    Article  Google Scholar 

  • Dray S, Pélissier R, Couteron P, Fortin M-J, Legendre P, Peres-Neto PR, Bellier E, Bivand R, Blanchet FG, De Cáceres M, Dufour A-B, Heegaard E, Jombart T, Nunoz F, Oksanen J, Thioulouse J, Wagner HH (2012) Community ecology in the age of multivariate multiscale spatial analysis. Ecol Monogr 82:257–275

    Article  Google Scholar 

  • Eckert CG, Samis KE, Lougheed SC (2008) Genetic variation across species’ geographical ranges: the central-marginal hypothesis and beyond. Mol Ecol 17:1170–1188

    Article  CAS  PubMed  Google Scholar 

  • Epperson BK (1990) Spatial autocorrelation of genotypes under directional selection. Genetics 124:757–771

    PubMed Central  CAS  PubMed  Google Scholar 

  • Epperson BK (1993) Spatial and space-time correlations in systems of subpopulations with genetic drift and migration. Genetics 133:711–727

    PubMed Central  CAS  PubMed  Google Scholar 

  • Escaravage N, Wagner J (2004) Pollination effectiveness and pollen dispersal in a Rhododendron ferrugineum (Ericaceae) population. Pl Biol 6:606–615

    Article  CAS  Google Scholar 

  • Escudero A, Iriondo JM, Torres ME (2003) Spatial analysis of genetic diversity as a tool for plant conservation. Biol Conserv 113:351–365

    Article  Google Scholar 

  • Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620

    Article  CAS  PubMed  Google Scholar 

  • Excoffier L, Lischer HEL (2010) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Res 10:564–567

    Article  Google Scholar 

  • Falush D, Stephens M, Pritchard JK (2007) Inference of population structure using multilocus genotype data: dominant markers and null alleles. Mol Ecol Notes 7:574–578

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Fang J-Y, Chung J-D, Chiang Y-C, Chang C-T, Chen C-Y, Hwang S-Y (2013) Divergent selection and local adaptation in disjunct populations of an endangered conifer, Keteleeria davidiana var. formosana (Pinaceae). PLoS One 8:e70162

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Foll M, Gaggiotti O (2008) A genome scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesain perspective. Genetics 180:977–993

    Article  PubMed Central  PubMed  Google Scholar 

  • Herrera CM, Bazaga P (2010) Epigenetic differentiation and relationship to adaptive genetic divergence in discrete populations of the violet Viola cazorlensis. New Phytol 187:867–876

    Article  CAS  PubMed  Google Scholar 

  • Herrera CM, Bazaga P (2011) Untangling individual variation in natural populations: ecological, genetic and epigenetic correlates of long-term inequality in herbivory. Mol Ecol 20:1675–1688

    Article  CAS  PubMed  Google Scholar 

  • Herrera CM, Medrano M, Bazaga P (2014) Variation in DNA methylation transmissibility, genetic heterogeneity and fecundity-related traits in natural populations of the perennial herb Helleborus foetidus. Mol Ecol 23:10851095

    Article  Google Scholar 

  • Heywood JS (1991) Spatial analysis of genetic variation in plant populations. Ann Rev Ecol System 22:335–355

    Article  Google Scholar 

  • Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Internal J Climat 25:1965–1978

    Article  Google Scholar 

  • Hirao AS (2010) Kinship between parents reduces offspring fitness in a natural population of Rhododendron brachycarpum. Ann Bot 105:637–646

    Article  PubMed Central  PubMed  Google Scholar 

  • Hsieh Y-C, Chung J-D, Wang C-N, Chang C-T, Chen C-Y, Hwang S-Y (2013) Historical connectivity, contemporary isolation and local adaptation in a widespread but discontinuously distributed species endemic to Taiwan, Rhododendron oldhamii (Ericaceae). Heredity 111:147–156

    Article  PubMed Central  PubMed  Google Scholar 

  • Huete AR, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira LG (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Rem Sens Environ 83:195–213

    Article  Google Scholar 

  • Hufford KM, Mazer SJ (2003) Plant ecotypes: genetic differentiation in the age of ecological restoration. Trends Ecol Evol 18:147–155

    Article  Google Scholar 

  • Jeffreys H (1961) Theory of probability, 3rd edn. Oxford University Press, Oxford

    Google Scholar 

  • Jombart T (2008) adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24:1403–1405

    Article  CAS  PubMed  Google Scholar 

  • Jombart T, Devillard S, Balloux F (2010) Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet 11:94

    Article  PubMed Central  PubMed  Google Scholar 

  • Johnson LJ, Tricker PJ (2010) Epigenomic plasticity within populations: its evolutionary significance and potential. Heredity 105:113–121

    Article  CAS  PubMed  Google Scholar 

  • Kameyama Y, Isagi Y, Nakagoshi N (2000) Microsatellite analysis of pollen flow in Rhododendron metternichii var. hondoense. Ecol Res 15:263–269

    Article  Google Scholar 

  • Kozak KH, Wiens JJ (2006) Does niche conservatism promote speciation: a case study in North American salamanders. Evolution 60:2604–2621

    Article  PubMed  Google Scholar 

  • Latzel V, Allan E, Silveira AB, Colot V, Fischer M, Bossdorf O (2013) Epigenetic diversity increases the productivity and stability of plant populations. Nat Commu 4:2875

    Google Scholar 

  • Legendre P, Fortin M-J (1989) Spatial pattern and ecological analysis. Vegetatio 80:107–138

    Article  Google Scholar 

  • Legendre P, Mi XC, Ren HB, Ma KP, Yu MJ, Sun I-F, He FL (2009) Partitioning beta diversity in a subtropical broad-leaved forest of China. Ecology 90:663–674

    Article  PubMed  Google Scholar 

  • Liew P-M, Chung N-J (2001) Vertical migration of forests during the last glacial period in subtropical Taiwan. West Pac Earth Sci 1:405–414

    Google Scholar 

  • Lira-Medeiros CF, Parisod C, Fernandes RA, Mata CS, Cardoso MA, Ferreira PCG (2010) Epigenetic variation in mangrove plants occurring in contrasting natural environments. PLoS One 5:e10326

    Article  PubMed Central  PubMed  Google Scholar 

  • Manel S, Schwartz MK, Luikart G, Taberlet P (2003) Landscape genetics: combining landscape ecology and population genetics. Trends Ecol Evol 18:189–197

    Article  Google Scholar 

  • Manel S, Poncet BN, Legendre P, Gugerli F, Holderegger R (2010) Common factors drive adaptive genetic variation at different spatial scales in Arabis alpina. Mol Ecol 19:3824–3835

    Article  PubMed  Google Scholar 

  • Manel S, Gugerli F, Thuiller W, Alvarez N, Legendre P, Holderegger R, Gielly L, Taberlet P, IntraBioDiv Consortium (2012) Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation. Mol Ecol 21:3729–2738

    Article  PubMed Central  PubMed  Google Scholar 

  • Mikita T, Klimánek M (2010) Topographic exposure and its practical applications. J Landscape Ecol 3:42–51

    Google Scholar 

  • Nei M (1973) Analysis of gene diversity in subdivided populations. Proc Natl Acad Sci U S A 70:3321–3323

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Nei M, Li W-H (1979) Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc Natl Acad Sci U S A 76:5269–5273

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Nybom H (2004) Comparison of different nuclear DNA markers for estimating intraspecific genetic diversity in plants. Mol Ecol 13:1143–1155

    Article  CAS  PubMed  Google Scholar 

  • Oden N, Sokal RR (1986) Directional autocorrelation: an extension of spatial correlograms to two dimensions. Syst Zool 35:608–617

    Article  Google Scholar 

  • Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens HH, Wagner H (2011) vegan: community ecology package. R package version 2.0-1. Available at: http://CRAN.R-project.org/package=vegan. Accessed 31 December 2013.

  • Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in excel. Population genetic software for teaching and research—an update. Bioinformatics 28:2537–2539

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Poncet BN, Herrmann D, Gugerli F, Taberlet P, Holderegger R, Gielly L, Rious D, Thuiller W, Aubert S, Manel S (2010) Tracking genes of ecological relevance using a genome scan in two independent regional population samples of Arabis alpina. Mol Ecol 19:2896–2907

    Article  CAS  PubMed  Google Scholar 

  • Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959

    PubMed Central  CAS  PubMed  Google Scholar 

  • R Development Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, http://www.R-project.org/

  • Radeloff VC, Miller TF, He HS, Mladenoff DJ (2000) Periodicity in spatial data and geostatistical models: autocorrelation between patches. Ecography 23:81–92

    Article  Google Scholar 

  • Rapp RA, Wendel JF (2005) Epigenetics and plant evolution. New Phytol 168:81–91

    Article  CAS  PubMed  Google Scholar 

  • Richards EJ (2006) Inherited epigenetic variation—revisiting soft inheritance. Nat Rev Genet 7:395–401

    Article  CAS  PubMed  Google Scholar 

  • Richards EJ (2011) Natural epigenetic variation in plant species: a view from the field. Curr Opin Pl Biol 14:204–209

    Article  CAS  Google Scholar 

  • Sokal RR, Oden NL (1978) Spatial autocorrelation in biology. 2. Some biological implications and four applications of evolutionary and ecological interest. Biol J Linn Soc 10:229–249

    Article  Google Scholar 

  • Sokal RR, Jacquez GM, Wooten MC (1989) Spatial autocorrelation analysis of migration and selection. Genetics 121:845–855

    PubMed Central  CAS  PubMed  Google Scholar 

  • Storfer A, Murphy MA, Evans JS, Goldberg CS, Robinson S, Spear SF, Dezzani R, Delmelle E, Vierling L, Waits LP (2007) Putting the “landscape” in landscape genetics. Heredity 98:128–142

    Article  CAS  PubMed  Google Scholar 

  • Su H-J (1985) Studies on the climate and vegetation types of the natural forests in Taiwan (III): a scheme of geographic regions. Quar J Chin For 18:33–44

    Google Scholar 

  • Taiwan Forestry Bureau (1995) The third survey of forest resources and land use in Taiwan. Taiwan Forestry Bureau, Department of Agriculture, Taipei, Taiwan.

  • Vekemans X, Beauwens T, Lemaire M, Roldan-Ruiz I (2002) Data from amplified fragment length polymorphism (AFLP) markers show indication of size homoplasy and of a relationship between degree of homoplasy and fragment size. Mol Ecol 11:139–151

    Article  CAS  PubMed  Google Scholar 

  • Vos P, Hogers R, Bleeker M, Reijans M, van der Lee T, Hornes M, Frijters A, Pot J, Peleman J, Kuiper M, Zabeau M (1995) AFLP: a new technique for DNA fingerprinting. Nucl Acid Res 23:4407–4414

    Article  CAS  Google Scholar 

  • Wagner HH, Fortin M-J (2005) Spatial analysis of landscapes: concepts and statistics. Ecology 86:1975–1987

    Article  Google Scholar 

  • Wang IJ, Glor RE, Losos JB (2013) Quantifying the roles of ecology and geography in spatial genetic divergence. Ecol Lett 16:175–182

    Article  PubMed  Google Scholar 

  • Xiong LZ, Xu CG, Maroof MAS, Zhang Q (1999) Patterns of cytosine methylation in an elite rice hybrid and its parental lines, detected by a methylation-sensitive amplification polymorphism technique. Mol Gen Genet 261:439–446

    Article  CAS  PubMed  Google Scholar 

  • Yilmaz MT, Hunt ER, Jackson TJ (2008) Remote sensing of vegetation water content from equivalent water thickness using satellite imagery. Rem Sens Environ 112:2514–2522

    Article  Google Scholar 

  • Zhivotovsky LA (1999) Estimating population structure in diploids with multilocus dominant DNA markers. Mol Ecol 8:907–913

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

We thank Ji-Sheng Wu for the assistance with field collections. This research was supported by the National Science Council of Taiwan (grant numbers NSC100-2621-B-003-001 and NSC101-2313-B-003-001-MY3 to SYH). We thank Yen-Heng Lin for his laboratory work. Postdoctoral fellowships awarded to JHC and to CTC from the National Science Council of Taiwan are also acknowledged.

Data archiving statement

AFLP and MSAP fingerprinting datasets used in this study deposited at Dryad: http://dx.doi.org/10.5061/dryad.fm278

Author information

Authors and Affiliations

  1. Laboratory of Molecular Phylogenetics, Department of Biology, National Museum of Natural Science, 1 Guanchien Rd, Taichung, 40453, Taiwan

    Chun-Lin Huang

  2. Department of Life Science, National Taiwan Normal University, 88 Tingchow Rd, Section 4, Taipei, 11677, Taiwan

    Jui-Hung Chen, Ming-Hsuan Tsang & Shih-Ying Hwang

  3. Division of Silviculture, Taiwan Forestry Research Institute, Taipei, 10066, Taiwan

    Jeng-Der Chung

  4. Department of Geography, National Taiwan University, 1 Roosevelt Rd, Section 4, Taipei, 10617, Taiwan

    Chung-Te Chang

Authors
  1. Chun-Lin Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jui-Hung Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ming-Hsuan Tsang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jeng-Der Chung
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Chung-Te Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Shih-Ying Hwang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shih-Ying Hwang.

Additional information

Communicated by Y. Tsumura

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(DOCX 3195 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Huang, CL., Chen, JH., Tsang, MH. et al. Influences of environmental and spatial factors on genetic and epigenetic variations in Rhododendron oldhamii (Ericaceae). Tree Genetics & Genomes 11, 823 (2015). https://doi.org/10.1007/s11295-014-0823-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11295-014-0823-0

Keyword

Search

Navigation