A unifying model for the analysis of phenotypic, genetic, and geographic data

Bayesian model; Markov chain Monte Carlo; Myodes; R package; Arvicolinae; Animals; Genetic Variation; Geography; Models, Genetic; Models, Statistical; Phenotype; Software; Species Specificity; Muridae

Abstract :

[en] Recognition of evolutionary units (species, populations) requires integrating several kinds of data, such as genetic or phenotypic markers or spatial information in order to get a comprehensive view concerning the differentiation of the units. We propose a statistical model with a double original advantage: (i) it incorporates information about the spatial distribution of the samples, with the aim to increase inference power and to relate more explicitly observed patterns to geography and (ii) it allows one to analyze genetic and phenotypic data within a unified model and inference framework, thus opening the way to robust comparisons between markers and possibly combined analyses. We show from simulated data as well as real data that our method estimates parameters accurately and is an improvement over alternative approaches in many situations. The power of this method is exemplified using an intricate case of inter- and intraspecies differentiation based on an original data set of georeferenced genetic and morphometric markers obtained on Myodes voles from Sweden. A computer program is made available as an extension of the R package Geneland. © 2012 The Author(s).

Disciplines :

Zoology

Author, co-author :

Guillot, G.; Informatics Department, Technical University of Denmark, Richard Petersens Plads, 2800 Lyngby, Denmark, Laboratoire de Bioḿetrie et Biologie, Evolutive UMR 5558, CNRS, Universit́e Lyon 1, 69622 Villeurbanne, France

Renaud, S.; Laboratoire de Bioḿetrie et Biologie, Evolutive UMR 5558, CNRS, Universit́e Lyon 1, 69622 Villeurbanne, France

Ledevin, R.; Anthropological Institute and Museum, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland

Michaux, Johan ; Université de Liège - ULiège > Département des sciences de la vie > Génétique et physiologie des microalgues

Claude, J.; Laboratoire de Morphoḿetrie, ISE-M, UMR5554 CNRS/UM2/IRD, Universit́e de Montpellier II, Montpellier 34095, France

Title :

A unifying model for the analysis of phenotypic, genetic, and geographic data

Publication date :

2012

Journal title :

Systematic Biology

ISSN :

1063-5157

eISSN :

1076-836X

Publisher :

Taylor & Francis, United Kingdom

Volume :

Issue :

Pages :

897-911

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 19 November 2014

Statistics

Number of views

71 (2 by ULiège)

Number of downloads

201 (1 by ULiège)

More statistics

Scopus citations^®

126

Scopus citations^®
without self-citations

124

OpenCitations

117

OpenAlex citations

170

Bibliography

Adams D.C., Berns C.M., Kozak K.H., Wiens JJ. 2009. Are rates of species diversifcation correlated with rates of morphological evo-lution? Proc. R. Soc. Lond. Biol. Sci. Ser. B 276:2729-2738.
Anderson E. 1935. The irises of the Gaspe peninsula. Bull. Am. Iris Soc. 59:2-5.
Anderson T. 1984. An introduction to multivariate statistical analysis. Probability and mathematical statistics. 2nd ed. New York: Wiley.
Balding D., Nichols R. 1995. A method for quantifying differentiation between populations at multi-allelic loci and its implications for in-vestigating identity and paternity. Genetica. 96:3-12.
Balding D., Nichols R. 1997. Signifcant genetic correlation among Caucasians at forensic DNA loci. Heredity. 78:583-589.
Banfeld J.D., Raftery A.E. 1993. Model-based Gaussian and non-Gaussian clustering. Biometrics. 49:803-821.
Beadell J.S., Hyseni C., Abila P.P., Azabo R., Enyaru J.C.K., Ouma J.O., Mohammed Y.O., Okedi L.M., Aksoy S., Caccone A. 2010. Phylo-geography and population structure of Glossinafuscipesfuscipes in Uganda: implications for control of tsetse. PLoS Neglected Trop. Dis. 4.
Biernacki C., Celeux G., Govaert G., Langrognet F. 2006. Model-based cluster and discriminant analysis with the MIXMOD software. Comput. Stat. Data Anal. 51:587-600.
Bocquet-Appel J., Bacro J. 1994. Generalized wombling. Syst. Biol. 43:442-448.
Burnaby T.P. 1966. Growth-invariant discriminant functions and gen-eralized distances. Biometrics. 22:96-110.
Claude J. 2008. Morphometrics with R. New York: Springer.
Corander J., Waldmann P., Martinen P., Sillanpää M. 2004. Baps2: enhanced possibilities for the analysis of genetic population structure. Bioinformatics. 20:2363-2369.
Corander J., Waldmann P., Sillanpää M. 2003. Bayesian analysis of genetic differentiationbetweenpopulations. Genetics. 163:367-374.
Coulon A., Guillot G., Cosson J., Angibault J., Aulagnier S., Cargnelutti B., Galan M., Hewison A. 2006. Genetics structure is infuenced by landscape features. Empirical evidence from a roe deer population. Mol. Ecol. 15:1669-1679.
Deffontaine V., Ledevin R., Fontaine M.C., Quéré J.-P, Renaud S., Libois R., Michaux J.R. 2009. A relict bank vole lineage highlights the biogeographic history of the Pyrenean region in Europe. Mol. Ecol. 18:2489-2502.
Doyle J. 1995. The irrelevance of allele tree topologies for species delimitation and a non-topological alternative. Syst. Biol. 20:574-588.
Evanno G., Regnault S., Goudet J. 2005. Detecting the number of clusters of individuals using the software structure: a simulation study. Mol. Ecol. 14:2611-2620.
Excoffer L. Heckel G. 2006. Computer programs for population genetics data analysis: a survival guide. Nat. Rev. Genet. 7:745-758.
Falush D., Stephens M., Pritchard J. 2003. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics. 164:1567-1587.
Fisher R.A. 1936. The use of multiple measurements in taxonomic problems. Ann. Eugenics. 7:179-188.
Fontaine M., Baird S., Piry S., Ray N., Tolley K., Duke S., Birkun A., Ferreira M., Jauniaux T, Llavona A., Ostürk B., Ostürk A., Ridoux V., Rogan E., Sequeira M., Siebert U., Vikingson G., Bouquegneau J., Michaux J. 2007. Rise of oceanographic barriers in continuous populations of a cetacean: the genetic structure of harbour porpoises in Old World waters. BMC Biol. 5.
Fraley C. 1999. Mclust: software for model-based cluster analysis. J. Classifcation. 12:297-306.
Frühwirth-Schnatter S. 2006. Finite mixture and Markov switching model. Series in Statistics. New York: Springer.
Galarza J., Carreras-Carbonell J., Macpherson E., Pascual M., Roques S., Turner G., Ricod C. 2009. The infuence of oceanographic fronts and early-life-history traits on connectivity among littoral fsh species. Proc. Natl. Acad. Sci. U.S.A. 106:1473-1478.
Gay L., Crochet P, Bell D., Lenormand T 2008. Comparing genetic and phenotypic clines in hybrid zones: a window on tension zone models. Evolution. 62:2789-2806.
Gelman A., Carlin J., Stern H., Rubin D. 2004. Bayesian data analysis. New York: Chapman and Hall.
Gilks W., Richardson S., Spiegelhalter D. editors. 1996. Markov chain Monte Carlo in practice. Interdisciplinary Statistics. New York: Chapman and Hall.
Girard C., Renaud S. 2011. The species concept in a long-extinct fossil group, the conodonts. Comptes Rendus Palevol. 10:107-115.
Godsill S. 2001. On the relationship between Markov chain Monte Carlo methods for model uncertainty. J. Comput. Graph. Stat. 10:230-248.
Goldman D.H., Jansen R.K., Van Den Berg C., Leitch I.J., Fay M.F., Chase M.W. 2004. Molecular and cytological examination of calopogon (Orchidaceae, Epidendroideae): circumscription, phylogeny polyploidy, and possible hybrid speciation. Am. J. Bot. 91:707-723.
Guérécheau A., Ledevin R., Henttonen H., Deffontaine V, Michaux J.R., Chevret P, Renaud S. 2010. Seasonal variation in molar outline ofbank voles: an effect of wear? Mammalian Biol. 75:311-319.
Guillot G. 2008. Inference of structure in subdivided populations at low levels of genetic differentiation. The correlated allele frequencies model revisited. Bioinformatics. 24:2222-2228.
Guillot G., Carpentier-Skandalis A. 2011. On the informativeness of dominant and co-dominant genetic markers for Bayesian supervised clustering. Open Stat. Probab. J. 3:7-12.
Guillot G., Estoup A., Mortier F., Cosson J. 2005. A spatial statistical model for landscape genetics. Genetics. 170:1261-1280.
Guillot G., Leblois R., Coulon A., Frantz A. 2009. Statistical methods in spatial genetics. Mol. Ecol. 18:4734-4756.
Guillot G., Santos F. 2010. Using AFLP markers and the Geneland program for the inference of population genetic structure. Mol. Ecol. Resour. 10:1082-1084.
Guillot G., Santos F., Estoup A. 2008. Analysing georeferenced population genetics data with Geneland: a new algorithm to deal with null alleles and a friendly graphical user interface. Bioinformatics. 24:1406-1407.
Hannelius U., Salmela E., Lappalainen T, Guillot G., Lindgren C., von Döbeln U., Lahermo P, Kere J. 2008. Population substructure in Finland and Sweden revealed by a small number of unlinked autosomal SNPs. BMC Genet.
Hausdorf B., Hennig C. 2003. Biotic element analysis inbiogeography Syst. Biol. 52:717-723.
Hausdorf B., Hennig C. 2010. Species delimitation using dominant and codominant multilocus markers. Syst. Biol. 59:491-503.
Hubisz M., Falush D., Stephens M., Pritchard J.K. 2009. Inferring weak population structure with the assistance of sample group information. Mol. Ecol. Resour. 9:1322-1332.
Jaarola M., Tegelström H., Fredga K. 1999. Colonization history in Fennoscandianrodents. Biol. J. Linn. Soc. 68:113-127.
Joseph L., Dolman G., Donnellan S., Saint K., Berg M., Bennett A. 2008. Where and when does a ring start and end? Testing the ring-species hypothesis in a species complex of Australian parrots. Proc. R. Soc. Lond. Ser. B. 275:2431-2440.
Kaufman L., Rousseeuw PJ. 1990. Finding groups in data: an introduction to cluster analysis. New York: Wiley.
Klingenberg C.P, Leamy LJ., Routman E.J., Cheverud J.M. 2001. Genetic architecture of mandible shape in mice: effects of quantitative trait loci analyzed by geometric morphometrics. Genetics. 157: 785-802.
Kuhl FP, Giardina C.R. 1982. Elliptic Fourier features of a closed contour. Comput. Graph. Image Process. 18:236-258.
Ledevin R. 2010. La dynamique évolutive du campagnol roussâtre (Myodes glareolus): structure spatiale des variations morphométriques. [dissertation]. Lyon (France): Université Lyon 1.
Ledevin R., Michaux J.R., Deffontaine V, Henttonen H., Renaud S. 2010. Evolutionary history of the bank vole Myodes glareolus: a morphometric perspective. Biol. J. Linn. Soc. 100:681-694.
Ledevin R., Quéré J.-P, Renaud S. 2010. Morphometrics as an insight into processes beyond tooth shape variation in a bank vole population. PLoS One. 5:e15470.
Lehanse B. 2010. Etude génétique d'une zone de contact en Suède entre deux lignées de campagnols roussâtres Myodes glareolus [Master's thesis]. Liège (Belgium): Université de Liège.
Luo A., Zhang A., Ho S.Y, Xu W, Shi W, C.S.L., Zhu C. 2011. Potential effcacy of mitochondrial genes for animal DNA barcoding: a case study using eutherian mammals. BMC Genomics. 12.
Marin J., Mengersen K, Robert C. 2005. Bayesian modelling and inference on mixtures of distributions. Handbook of Statistics. Vol. 25. New York: Elsevier Sciences.
Martínez-Ortega M.M., Delgado L., Albach D.C., Elena-Rossello J.A., Rico E. 2004. Species boundaries and phylogeographic patterns in cryptic taxa inferred from AFLP markers: Veronica subgen. Pentasepalae (Scrophulariaceae) in the Western Mediterranean. Syst. Bot. 29:965-986.
McLachlan G.J., Peel D., Basford P, Adams K.E. 1999. The EMMIX software for the ftting of mixtures of normal and t-components. J. Stat. Softw. 4:1-4.
Merilä J., Crnokrak P. 2001. Comparison of genetic differentiation at marker loci and quantitative traits. J. Evol. Biol. 14:892-903.
Møller J., Stoyan D. 2009. Tessellations in the sciences: virtues, techniques and applications of geometric tilings. Stochastic Geometry and Random Tessellations. New York: Springer.
Néraudeau. 2011. The species concept in palaeontology: ontogeny variability, evolution. Comptes Rendus Palevol. 10:71-75.
Nesi N., Nakoumé E., Cruaud C., Hassanin A. 2011. DNA barcoding of African fruit bats (Mammalia, Pteropodidae): the mitochondrial genome does not provide a reliable discrimination between Epomophorus gambianus and Micropteropus pusillus. Comptes Rendus Biologies. 334:544-554.
Pritchard J., Stephens M., Donnelly P. 2000. Inference of population structureusingmultilocus genotype data. Genetics. 155:945-959.
Razzauti M., Plyusnina A., Sironen T., Henttonen H., Plyusnin A. 2009. Analysis of Puumala hantavirus in a bank vole population in northern Finland: evidence for co-circulation of two genetic lineages and frequent reassortment between strain. J. Gen. Virol. 90:1923-1931.
Renaud S., Chevret P, Michaux J. 2007. Morphological vs. molecular evolution: ecology and phylogeny both shape the mandible of rodents. Zool. Script. 36:525-535.
Richardson S., Green P 1997. On Bayesian analysis of mixtures with an unknown number of components. J.R. Stat. Soc. Ser. B. 59:731-792.
Robert C., Casella G. 2004. Monte Carlo statistical methods. 2nd ed. New York: Springer.
Rodríguez F., Pérez T., Hammer S.E., Albornoz J., Domínguez A. 2010. Integrating phylogeographic patterns of microsatellite and mtDNA divergence to infer the evolutionary history of chamois (genus Rupicapra). BMC Evol. Biol. 10:222.
Sacks B., Bannasch D. L., Chomel B. B., Ernst H. 2008. Coyotes demonstrate how habitat specialization by individuals of a generalist species can diversify populations in a heterogeneous ecoregion. Mol. Biol. Evol. 25:1354-1395.
Safner T., Miller M., McRae B., Fortin M., Manel S. 2011. Comparison of Bayesian clustering and edge detection methods for inferring boundaries in landscape genetics. Int. J. Mol. Sci. 12:865-889.
Schwartz M.K., Luikart G., McKelvey K.S., Cushman S.A. 2010. Spatial complexity, informatics, and wildlife conservation chap. In: Cushman S.A., Huettmann F, editors. Landscape genomics: a brief perspective. New York: Springer. p. 165-174.
Sirén J., Marttinen P, Corander J. 2011. Reconstructing population histories from single nucleotide polymorphism data. Mol. Biol. Evol. 28:673-683.
Stephens M. 1997. Discussion of the paper by Richardson and Green "On Bayesian analysis of mixtures with an unknown number of components". J. R. Stat. Soc. Ser. B. 59:768-769.
Tegelström H. 1987. Transfer of mitochondrial DNA from the northern red-backed vole (Clethrionomys rutilus) to the bank vole (C. glareolus). J. Mol. Evol. 24:218-227.
Turmelle A.S., Kunz T.H., Sorenson M.D. 2011. A tale of two genomes: contrasting patterns of phylogeographic structure in a widely distributed bat. Mol. Ecol. 20:357-375.
Waples R., Gaggiotti O.2006. What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity Mol. Ecol. 15:1419-1439.
Wasser S., Mailand C., Booth R., Mutayoba B., Kisamo E., Stephens M. 2007. Using DNA to track the origin of the largest ivory seizure since the 1989 trade ban. Proc. Natl. Acad. Sci. U.S.A. 104: 4228-4233.
Womble W. 1951. Differential systematics. Science. 28:315-322.
Yang Z., Rannala B. 2010. Bayesian species delimitation using multilocus sequence data. Proc. Natl. Acad. Sci. U.S.A. 107:9264-9269.