Rhoné, Bénédicte (2008) Genetic mechanisms involved in climatic adaptation of experimentally evolving populations of bread wheat. PhD thesis Science de la vie, UMR INRA/Univ. Paris-Sud/CNRS/AgroParisTech, AgroParistech 2008AGPT0018 p.230.
Full text available as:
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Abstract
Local adaptation resulting from selection pressure acts on heritable characters and is a major
force shaping the phenotypic diversity of natural populations. Currently, numerous questions
exist surrounding the impact of selection on the evolution of genes involved in the structure of
adaptive traits, which are often complex characters involving many interacting genes.
The objective of this thesis is to identify certain genetic mechanisms which are activated
during the adaptation of experimental wheat populations to different climactic contexts. The
adaptive trait studied was flowering time, which permits the plant to synchronize reproduction
with favorable seasonal conditions. The experimental populations considered had a common
genetic origin and have evolved independently since 1984 in different sites in France, without
conscious human selection or migration, but subject to the influence of natural selection and
genetic drift. Using a base of knowledge on genes implicated in flowering in Arabidopsis
thaliana and rice, and recent publications on wheat, the evolution of nucleotide
polymorphisms in candidate genes was followed during 12 generations (2, 7 and 12) in three
experimental populations (Vervins in the north of France, Le Moulon in the Parisian region
and Tolouse in the South). These populations were also characterized for precocity of
flowering time measured under different day length and vernalization regimes (duration of
exposure to low temperatures) and for diversity of microsatellite loci sampled from
throughout the genome. The comparison of levels of genetic differentiation among
populations for these three measures of genetic diversity showed that precocity was subject to
divergent selection from the first generations. However, it appears that this selection was not
directly for flowering time, but instead achieved through indirect selection on correlated traits
in the different environments, such as plant height or grain weight. Selection for precocity
can be related to climactic characteristics of the experimental locations, with the northern
populations flowering later than the southern population. This rapid evolution of the trait
accompanied significant changes in allele frequencies for major genes involved in flowering
time, and the development of specific multi-locus allelic combinations in the different
climatic contexts considered. This evolution did not diminish the existing within-population
genetic diversity because multiple combinations were favored in the different populations.
The work presented in this thesis is an important contribution to our understanding of the
maintenance of evolutionary potential in cultivated species.
| Item Type: | PhD Thesis (PhD) |
|---|---|
| PhD Supervisor: | Bonnin, Isabelle |
| Date: | 13 March 2008 |
| Board of examiners: | Cuguen, Joël and Goudet, Jérôme and Gallais, André and Le Corre, Valérie and Machon, Nathalie and Bonnin, Isbaelle |
| Ecole Doctorale: | ED 435 AGRICULTURE, ALIMENTATION, BIOLOGIE, ENVIRONNEMENTS ET SANTE |
| Discipline: | Science de la vie |
| Collection (Fonds): | AgroParistech |
| Institution: | AgroParistech |
| Department: | UMR INRA/Univ. Paris-Sud/CNRS/AgroParisTech |
| Subjects: | 8. Earth Sciences and Environmental Engineering 7. Life Sciences and Engineering |
| Uncontrolled Keywords: | Population Genetics, Génétique des populations, Adaptation, Experimental populations, Population expérimentale, Flowering time, Précocité de floraison, Sélection, Différenciation, Triticum aestivum |
| ID Code: | 3822 |
| Deposited By: | Bénédicte Rhoné |
| Deposited On: | 01 December 2008 |
References
Alonso-Blanco C, Mendez-Vigo B, Koornneef M (2005) From phenotypic to molecular polymorphisms involved in naturally occuring variation of plant development. International Journal of Developmental Biology, 49, 717-732.
Ardlie KG, Kruglyak L, Seielstad L (2002) Patterns of linkage disequilibrium in the human genome. Nature Review Genetics, 3, 299-309.
Barrett RDH Schluter D (2008) Adaptation from standing genetic variation. Trends in Ecology and Evolution. 23, 38-44.
Beales J, Turner A, Griffiths S, Snape JW, Laurie DA (2007) A Pseudo-Response Regulator is misexpressed in the photoperiod insensitive Ppd-D1a mutant of wheat (Triticum aestivum L.). Theoretical and Applied Genetics, 115, 1432-2242.
Beaumont MA, Nichols RA (1996) Evaluating loci for use in the genetic analysis of population structure.
Beaumont MA, Balding DJ (2004) Identifying adaptative genetic divergence among populations from genome scans. Molecular Ecology, 13, 969-980.
Belkhir K, Borsa P, Chikhi L, Raufaste N, Bonhomme F (2004) GENETIX 4.05, logiciel sous Windows TM pour la génétique des populations. Laboratoire Génome, Populations, Interactions, CNRS UMR 5000, Université de Montpellier II, Montpellier (France), http://www.genetix.univ-montp2.fr/genetix/genetix.htm.
Black CW, Krafsur ES (1985) A FORTRAN program for the calculation and analysis of two-locus linkage disequilibrium coefficients. Theoretical Applied Genetics, 70:491-496.
Bonin A, Bellemain E, Bronkein Eidesen P, Pompanon F, Brchmann C, Taberlet P (2004) How to track and assess genotyping errors in population genetics studies. Molecular Ecology, 13, 3261-3273.
Bonin A, Taberlet P, Miaud C, Pompanon F (2006) Explorative genome scan to detect candidate loci for adaptation along a gradient of altitude in the common frog (Rana temporaria). Molecular Biology Evolution, 23, 773-783.
Bonin A, Ehrich D, Manel S (2007) Statistical analysis of amplified fragment length polymorphism data: a toolbox for molecular ecologists and evolutionists. Molecular Ecology 16, 3737–3758.
Bonnin I, Rousset M, Madur D, Sourdille P, Dupuits C, Brunel D, Goldringer I (2008) FT genome A and D polymorphisms are associated with the variation of earliness components in hexaploid wheat. Theoretical and Applied Genetics, 116, 383-394
Börner A, Worland AJ, Plashke J, Shuman E, Law CN (1993) Pleiotropic effects of genes for reduced height (Rht) and day-length insensitivity (Ppd) on yield and its components for wheat growth in Middle Europe. Plant Breeding, 11, 204-216.
Boudry P, McCombie H, van Dijk H (2002). Vernalization requirement of wild beet Beta vulgaris ssp. maritima: among population variation and its adaptative significance. Journal of Ecology, 90, 693-703.
Boutin-Ganache I, Raposo M, Raymond M, Deschepper CF (2001) M13-tailed primers improve the readability and usability of microsatellite analyses performed with two different allele-sizing methods. Biotechniques, 24-28.
Chao S, Zhang W, Dubcovsky J, Sorrells M (2007) Evaluation of genetic diversity and genome-wide linkage disequilibrium among U.S. wheat (Triticum aestivum L.) germplasm representing different market classes. Crop Science, 47, 1018-1030.
Charlesworth B, Nordborg M, Charlesworth D (1997) The effects of local selection, balanced polymorphism and background selection on equilibrium patterns of genetic diversity in subdivided populations. Genetical Research, 70, 155-174.
Charlesworth D (2003) Effects of inbreeding on the genetic diversity of populations. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 358, 1051–1070.
Cockram J, Jones H, Leigh FJ, O’Sullivan D, Powell W, Laurie DA, Greenland AJ (2007) Control of flowering time in temperate cereals: genes, domestication, and sustainable productivity. Journal of Experimental Botany, 58, 1231-1244.
Comai L (2005) The advantages and disavantages of being polyploid. Nature Reviews Genetics, 6, 836-846.
David J (1992) Approche méthodologique d’une gestion dynamique des ressources génétiques chez le Blé tendre (Triticum aestivum L.). Thèse, Institut National Agronomique Paris Grignon.
David JL, Savy Y, Trottet M, Pichon M (1992) Méthode de gestion dynamique de la variabilité génétique. Exemple d’un réseau expérimental de populations composites de blé tendre. In : Complexes d’espèces, Flux de gènes et ressources génétiques (Ed. BRG) 337-350, Lavoisier, Cachan, France.
David JL, Savy Y, Brabant P (1993) Outcrossing and selfing evolution in populations under directional selection. Heredity, 71, 642-651.
David P, Pujol B, Viard F, Castella V, Goudet J (2007) Reliable selfing rate estimates from imperfect population genetic data. Molecular Ecology, 16, 2474-2487.
Demotes-Mainard S, Doussinault G, Meynard JM (1995) Effects of low radiation and low temperature at meiosis on pollen viability and grain set in wheat. Agronomie, 15, 357-365.
Demuth JP, Wade MJ (2006) Experimental methods for measuring gene interactions. Annual Review of Ecology, Evolution, and Systematics, 37, 289-316.
Ehrenreich IM, Purugganan MD (2006) The molecular genetic basis of plant adaptation. American Journal of Botany, 97, 953-962.
Endler JA (1986) Natural selection in the wild. Princeton University Press, Princeton.
Enjalbert J, Goldringer I, David J, Brabant P (1998) The relevance of outcrossing for the dynamic management of genetic resources in predominantly selfing Triticum aestivum L. (bread wheat). Génétique, Sélection, Evolution, 30: S197-S211.
Enjalbert J, Goldringer I, Paillard S, Brabant P (1999) Molecular markers to study genetic drift and selection in wheat populations. Journal of experimental botany, 50, 283-290.
Enjalbert J (1999) Diversité et régime de reproduction de populations de blé tendre (Triticum aestivum L.) menées en gestion dynamique. Thèse, Institut National Agronomique Paris Grignon.
Erickson DL, Fenster CB, Stenoien HK, Price D (2004) Quantitative trait analyses and the study of evolutionary process. Molecular Ecology, 13, 2505-2522.
Excoffier, L. G. Laval, and S. Schneider (2005) Arlequin ver. 3.0: An integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online 1:47-50.
Fay JC, Wittkopp PJ (2008) Evaluating the role of natural selection in the evolution of gene regulation. Heredity, 100, 191-199.
Fisher RA (1930) The genetical theory of natural selction. Oxford Univisersity Press, Oxford.
Flint J, Mott R (2001) Finding the molecular basis of quantitative traits: successes and pitfalls. Nature Reviews Genetics, 2, 437-445.
Fox CW, Roff DA, Fairbairn DJ (2001) Evolutionary ecology: concepts and case studies. Oxford Univisersity Press, Oxford.
Frankham R (1995) Effective population size/adult population size ratios in wildlife: a review. Genetical Research, 66, 95-107.
Franks SJ, Sim S, Weis AE (2007) Rapid evolution of flowering time by an annual plant in response to a climate fluctuation. Procceding of the National Academy of Sciences, 104, 1278-1282.
Fu DL, Szucs P, Yan LL et al. (2005) Large deletions within the first intron in VRN-1 are associated with spring growth habit in barley and wheat. Molecular Genetics and Genomics, 273, 54-65.
Gardner KM, Latta RG (2007) Shared quantitative trait loci underlying the genetic correlation between continuous traits. Molecular Ecology, 16, 4195-4209.
Garnier-Gere P, Dillmann C (1992) A computer program for testing pairwise linkage disequilibrium in subdivided populations. Journal of Heredity, 83, 239.
Glémin S, Bazin E, Charlesworth D (2006) Impact of mating systems on patterns of sequence polymorphism in flowering plants. Proceeding of the Royal Society B, 273, 3011-3019.
Goldringer I, Enjalbert J, Raquin AL, Brabant P (2001) Strong selection in wheat populations during ten generations of dynamic management, Génétique, Sélection, Evolution, 33, S441-S463.
Goldringer I, Bataillon T (2004) On the distribution of temporal variations in allele frequencies, Consequences for the estimation of effective population size and the detection of loci undergoing selection. Genetics, 168, 563-568.
Goldringer I, Prouin C, Rousset M, Galic N, Bonnin I (2006) Rapid differentiation of Experimental populations of wheat for heading time in response to local climatic conditions. Anals of Botany, 98, 805-817.
Goudet J (2002) FSTAT version 2.9.3.2. A program to estimate and test gene diversities and fixation indices. Institut of Ecology, Lausanne, Switzerland, Available from http://www.unil.ch/izea/softwares/fstat.html. Updated from Goudet (1995).
Goudet J, Büchi L (2006) The effect of dominance, regular inbreeding and sampling design on Qst, an estimator of population differenciation for quantitative traits. Genetics, 172, 1337-1347.
Goudet J, Martin G (2007) Under neutrality, Qst ≤ Fst when there is dominance in an island model. Genetics, 176, 1371-1374.
Griffiths S, Dunford RP, Coupland G, Laurie DA (2003) The Evolution of CONSTANS-Like Gene Families in Barley, Rice, and Arabidopsis. Plant Physiology, 131, 1855–1867.
Guyomarc'h H, Sourdille P, Charmet G, Edwards KJ, Bernard M (2002) Characterisation of polymorphic microsatellite markers from Aegilops tauschii and transferability to the D-genome of bread wheat. Theorical Applied Genetics, 104, 1164-1172.
Hanocq E, Laperche A, Jaminon O, Lainé AL, Legouis J (2007) Most significant genome regions involved in the control of earliness traits in bread wheat, as revealed by QTL meta-analysis. Theoretical and Applied Genetics, 114, 569-584.
Hansen TF (2006) The evolution of genetic architecture. Annual Review of Ecology, Evolution, and Systematics, 37, 123-57.
Haudry A, Cenci A, Ravel C, Bataillon T, Brunel D, Poncet C, Hochu I, Poirier S, Santoni S, Glémin S, David J (2007) Grinding up wheat: a massive loss of nucleotide diversity since domestication. Molecular Biology and Evolution, 24, 1506-1517.
Hedrick PW (2005) Genetics of populations. 3ème édition. Jones and Batlett Publishers, Sudbury.
Hendry AP, Kinnison MT (2001) An introduction to microevolution: rate, pattern, process. Genetica, 112-113, 1-8.
Henry JP, Pontis C, David JL Gouon PH (1991). An experiment on dynamic conservation of genetic ressources with metapopulations, In : Seitz A. and Loeschcke V. (eds), Species Conservation : a Population Biological Approach, Basel, 185-198.
Hoekstra HE, Coyne JA (2007) The locus of evolution: evo devo and the genetics of adaptation. Evolution, 61, 995-1016.
Hoffman JI, Amos W (2005). Microsatellite genotyping errors: detection approaches, common sources and consequences for paternal exclusion. Molecular Ecology 14, 599–612
Houle D (1992) Comparing evolvability and variability of quantitative traits. Genetics, 130, 195-204.
Kauer M, Zangerl B, Dieringer D, Schlötterer C (2002) Chromosomal patterns of microsatellite variabilllity contrast sharply in African and non-African populations of Drosophila melanogaster. Genetics, 160, 247-256.
Kingsolver JG, Hoekstra HE, Berrigan D, Vignieri SN, Hoang A, Gibert P, Beerli P (2001) The strength of phenotypic selection in natural populations. The American Naturalist, 157, 245-261.
Kingsolver JG, Pfennig DW (2007) Patterns and Power of Phenotypic Selection in Nature, BioScience, 57, 561-572.
Kingslover JG, Massie KR, Shlichta JG, Smith MH, Ragland GJ, Gomulkiewicz R (2007) Relating environmental variation to selection on reaction norms: an experimental test. The American Naturalist, 169, 163-174.
Kuchel H, Hollamby G, Landridge P, Williams K, Jefferies SP (2006) Identification of genetic loci associated with ear-emergence in bread wheat. Theoretical and Applied Genetics 113:1103-1112
Kraakman A, Niks R, Van den Berg P, Stam P, Van Eeuwijk P (2004) Linkage disequilibrium mapping of yield and yield stability in modern spring barley cultivars. Genetics, 168, 435-446.
Lande R (1979) Quantitative genetics analysis of multivariate evolution, applied to brain: body size allometry. Evolution, 33, 402-416.
Lande R, Arnold SJ (1983) The measurement of selection on correlated characters. Evolution, 37, 1210-1226.
Latta RG (1998) Differenciation of allelic frequencies at quantitative trait loci affecting locally adaptative traits. The American Naturalist, 151, 283-292.
Le Boulc’h V., David J., Brabant P., de Vallavieille-Pope C., 1994. Dynamic conservation of variability : responses of wheat populations in different selective forces including powdery mildew, Genetics Selection Evolution, 26, S221-S240.
Le Corre V, Kremer A (2003) Genetic variability at neutral markers, quantitative trait loci and trait in subdivided population under selection. Genetics, 164, 1205-1219.
Le Corre V (2005) Variation at two flowering time genes within and among populations of Arabidopsis thaliana: comparison with markers and traits. Molecular Ecology, 14, 4181–4192
Leinonen T, O’Hara RB, Cano JM, Merilä J (2008) Comparative studies of quantitative trait and neutral marker divergence: a meta-analysis. Journal of Evolutionary Biology, 21, 1-17.
Lewontin RC, Krakauer J (1973) Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms. Genetics, 74, 175-195.
López-Fanjul C, Fernández A, Toro MA (2003) The effect of neutral nonadditive gene action on the quantitative index of population divergence. Genetics, 164, 1627-1633.
López-Fanjul C, Fernández A, Toro MA (2007) The effect of dominance on the use of the Qst-Fst contrast to detect natural selection on quantitative traits. Genetics, 176, 725-727.
Loskutov IG (2001) Influence of vernalization and photoperiod to the vegetation period of wild species of oats (Avena spp.). Euphytica, 117, 125–131.
Lynch M, Walsh B (1998) Genetics and Analysis of Quantitative Traits. Sinauer, Sunderland, Massachusetts.
Mackay TFC (2001) The genetic architecture of quantitative traits. Annual review of genetics, 35, 303-339.
Maynard Smith J, Haigh J (1974) The hitch-hiking effect of a favorable gene. Genetical Research, 23, 23–35
McKay JK, Latta RG (2002) Adaptative population divergence: markers, QTL and traits. Trends in Ecology and Evolution, 17, 285-291.
Merilä J, Crnokrak P (2001) Comparison of genetic differentiation at marker loci and quantitative traits. Journal of Evolutionary Biology, 14, 892-903.
Mitchell-Olds T, Willis JH, Goldstein DB (2007) Which evolutionary processes influence natural genetic variation for phenotypic traits ? Nature Reviews Genetics, 8, 845-856.
Moore RC, Purugganan MD (2005) The evolutionary dynamics of plant duplicate genes. Current Opinion in Plant Biology, 8, 122-128
Mouradov A, Cremer F, Coupland G (2002) Control of flowering time, Interacting pathways as a basis for diversity. Plant Cell, 14, s111-s130.
Nei M, Tajima F (1981) Genetic drift and estimation of effective population size. Genetics, 98, 625-640.
Nei M (1987) Molecular Evolutionary Genetics. Columbia University Press, New York.
Nordborg M, Borevitz JO, Bergelson J, Berry C, Chory J et al. (13 co-auteurs) (2002) The extent of linkage disequilibrium in Arabidopsis thaliana. Nature Genetics, 30, 190-193.
O’Hara RB, Merilä J (2005) Bias and precision in Qst estimates: problems and some solutions. Genetics, 171, 1331-1339.
Orr HA (1998) The population genetics of adaptation: the distribution of factors fixed during adaptive evolution. Evolution, 52, 935-949.
Orr HA (2005) The genetic theory of adaptation. Nature Reviews Genetics, 6, 119-127.
Otto SP (2007) The evolutionary consequences of polyploidy. Cell, 131, 452-462.
Paillard S (1999) Evolution des résistances à différentes maladies dans des populations de blé tendre (Triticum aestivum L.) menée en gestion dynamique. Thèse, Institut National Agronomique Paris-Grignon.
Paillard S, Goldringer I, Enjalbert J, Doussinault G., de Vallavieille-Pope C, Brabant P (2000) Evolution of resistance against powdery mildew in winter wheat populations conducted under dynamic management. I- Is specific seedling resistance selected ? Theoretical Applied Genetics, 101,449-456.
Paillard S, Goldringer I, Enjalbert J, Trottet M, David J, De Vallaveille-Pope C, Brabant P (2000b) Evolution of resistance against powdery mildew in winter wheat populations conducted under dynamic management. II- Adult plant resistance. Theoretical and Applied Genetics, 101, 457-462.
Palo JU, O’Hara RB, Laugen AT, Laurila A, Primmer CR, Merilä J (2003) Latitudinal divergence of common frog (Rana temporaria) life history traits by natural selection: evidence from a comparison of molecular and quantitative genetic data. Molecular Ecology, 12, 1963-1978.
Petit C, Thompson JD (1998) Phenotypic selection and population differentiation in relation to habitat heterogeneity in Arrhenatherum elatius (Poaceae). Journal of Ecology, 86, 829-840.
Picard E., 1984. Contribution à l’étude de l’hérédité et de l’utilisation en sélection de l’haplodiploïdisation par androgénèse in vitro chez une céréale autogame Triticum aestivum L., Thèse d’Etat, Université Paris Sud.
Pompanon F, Bonin A, Bellemain E, Taberlet P(2005) Genotyping errors: causes, consequences and solutions. Nature Review Genetics, 6, 847-859.
Porcher E, Giraud T, Lavigne C (2006) Genetic differentiation of neutral markers and quantitative traits in predominantly selfing metapopulations: confronting theory and experiments with Arabidobsis thaliana. Genetical Research, 87, 1-12.
Price AH (2006) Believe it or not, QTLs are accurate ! Trends in Plant Science, 11, 213-216.
Pritchard JK, Stephens M, Donnely P (2000) Inference of population structure using multilocus genotype data. Genetics, 155, 945-959.
Przeworski M, Coop G, Wall JD (2005) The signature of positive selection on standing genetic variation. Evolution, 59, 2312-2323.
Putterill J, Laurie R, Macknight R (2004) It’s time to flower: the genetic control of flowering time. BioEssays, 26, 363-373.
Rafalski A (2002) Applications of single nucleotide polymorphisms in crop genetics. Current Opinion in Plant Biology, 5, 94-100.
Raquin AL (2005) Evolution de la diversité microsatellite dans une population de blé tendre conduite en gestion dynamique : effets de la mutation, de la dérive et de la sélection. Thèse, Université Paris XI, Orsay.
Raquin AL, Depaulis F, Lambert A, Galic N, Brabant P, Goldringer I (in prep) Experimental estimation of mutation rates in a wheat population with coalescent-related methods.
Raymond M, Rousset F (1995) GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. Journal of Heredity, 86, 248-249.
Rebourg C, Chastanet M, Gouesnard B, Welcker C, Dubreuil P, Charcosset A (2003) Maize introduction into Europe: the history reviewed in the light of molecular data. Theoretical and Applied Genetics, 106, 895-902.
Remington DL, Purugganan MD (2003) Candidate genes, Quantitative trait loci, and functional trait evolution in plants. International Journal of plant science, 164, s7-s20.
Reynolds MP, Ortiz-Monasterio JI, and McNab A (2001) Application of Physiology in Wheat Breeding. Mexico, D.F.: CIMMYT.
Rhoné B, Raquin, AL, Goldringer I (2007) Strong linkage disequilibrium near the selected Yr17 resistance gene in a wheat experimental population. Theoretical and Applied Genetics, 114, 787-802.
Rhoné B, Remoué C, Galic N, Goldringer I, Bonnin I (2008). Insight into the genetic bases of climatic adaptation in experimentally evolving wheat populations. Molecular Ecology, 17, 930-943.
Robert D, Gate P, Couvreur F (1993) Les satdes du blé. Institut technique des céréales et des fourrages, La Primaube.
Röder M, Korzun V, Wendehake K, Plaschke J, Tixier MH, Leroy P, Ganal M (1998) A microsatellite map of wheat. Genetics, 149, 2007-2023
Rogers SM, Bernatchez L (2005) Integrating QTL mapping and genome scans towards the characterization of candidate loci under parallel selection in the lake whitefish (Coregonus clupeaformis). Molecular Ecology, 14, 351-361.
Roux F, Touzet P, Cuguen J, Le Corre V (2006) How to be early flowering: an evolutionary perspective. Trends in Plant Science, 11, 375-381.
Rubinsztein DC, Amos W, Leggo J, Goodburn S, Jain S et al. (1995) Microsatellite evolution – Evidence for directionality and variation in rate between species. Nature Genetics, 10, 337-343.
Sandring S, Riihimäki MA, Savolainen O, Ågren J (2007). Selection on flowering time and floral display in an alpine and a lowland population of Arabidopsis lyrata. Journal of Evolutionary Biology, 20, 558-567
SAS. 2002. SAS version 8 for Windows. SAS Institute, Cary, North Carolina, USA.
Sherman JD, Yan L, Talbert L, Dubcovsky J (2004) A PCR marker for growth habit in common wheat based on allelic variation at the VRN-A1 gene. Crop Science, 44, 1832–1838.
Schlötterer C (2002) A microsatellite-based multilocus screen for the identification of local selective sweeps. Genetics, 160, 753-763.
Siol M, Bonnin I, Olivieri I, Prosperi JM, Ronfort J (2007) Effective populations size associated with self-fertilization: lessons from temporal changes in allele frequencies in the selfing annual Medicago truncatula. Journal of Evolutionary Biology, 20, 2349-2360.
Slate J (2005) Quantitative trait locus mapping in natural populations: progress, caveats and future directions. Molecular Ecology, 14, 363-379.
Somers DJ, Isaac P, Edwards K (2004) A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theorical Applied Genetics, 109, 1105-1114.
Song QJ, Shi JR, Singh S, Fickus EW, Costa JM et al. (2005) Development and mapping of microsatellite (SSR) markers in wheat. Theorical Applied Genetics, 110, 550-560.
Sourdille P, Snape JW, Cadalen T, Charmet G, Nakata N, Bernard S, Bernard M (2000) Detection of QTLs for heading time and photperiod response in wheat using a doubled-haploid population. Genome 43:487-494
Spitze K (1993) Population structure in Daphnia obtusa: quantitative genetic and allozymic variation. Genetics, 135, 367-374.
Stinchcombe JR, Hoekstra HE (2008) Combining population genomics and quantitative genetics: finding the genes underlying ecologically important traits. Heredity, 100, 158-170.
Stockwell CA, Hendry AP, Kinnison MT (2003) Contemporary evolution meets conservation biology. Trends in Ecology and Evolution, 18, 94-101.
Storz JF (2005) Using genome scans of DNA polymorphsim to infer adaptive population divergence. Molecular Ecology, 14, 671-688.
Strasburg JL, Gross BL (2008) Adapting to winter in wheat: a long-term study follows parallel phenotypic and genetic changes in three experimental wheat populations. Molecular Ecology, 17, 216-218.
Tenaillon MI, Sawkins MC, Long AD, Gaut RL, Doebley JF, Gaut BS (2001) Patterns of DNA sequence polymorphism along chromosome 1 of maize (Zea mays ssp. mays L.). Procceding of the National Academy of Sciences, 16, 9161-9166.
Teshima KM, Coop G, Przeworski M (2006) How reliable are empirical genomic scans for selective sweeps ? Genome research, 16, 702-712.
Thomas G, Rousset M, Pichon M, Trottet M, Doussinault G, Picard E (1991) Méthodologie de l’amélioration de blé tender (Triticum aestivum L.) I. Création par croisements et analyse d’une population artificielle à 16 parents, base de cette étude méthodologique. Agronomie, 11, 359-368.
Thuillet AC, Bru D, David JL, Roumet P, Santoni S et al (2002) Direct estimation of mutation rate for 10 microsatellite loci in durum wheat, Triticum turgidum (L.) Thell. Ssp durum desf. Molecular Biology and Evolution, 19 ,122-125.
Tishkoff SA, Reed FA, Ranciaro A, Voight BF, Babbitt CC et al. (19 co-auteurs) (2006) Convergent adaptation of human lactase persistence in Africa and Europe. Nature Genetics, 39, 31-40.
Trottet M., 1988. Use of genic male sterility for breeding wheat lines resistant to Leptosphaeria nodorum Müller : results of a first selection cycle and prospects, In : Seventh International Wheat Genetics Symposium, Cambridge, UK,13-19 july 1988, Institut of plant Science Research, 1199-1202.
Vasemägi A, Primmer CR (2005) Challenges for identifying functionally important genetic variation: the promise of combining complementary research strategies. Molecular Ecology, 14, 3623–3642.
Veyriéras JB (2006) Etude du déterminisme génétique de caractères quantitatifs chez les végétaux : méta-analyses de QTL et etude d’association. Thèse, Institut National Agronomique, Paris-Grignon.
Vigouroux Y, Jaqueth JS, Matsuoka Y, Smith OS, Beavis WD (2002) Rate and pattern of mutation at microsatellite loci in maize. Molecular Biology and Evolution, 19, 1251-1260.
Vitalis R, Dawson K, Boursot P (2001) Interpretation of variation across marker loci as evidence of selection. Genetics, 158, 1811-1823.
Waldmann P, Garcia-Gil MR, Sillanpää MJ (2005). Comparing Bayesian estimates of genetic differentiation of molecular markers and quantitative traits: an application to Pinus sylvestris. Heredity, 94, 623-629.
Waples RS (1989) A generalized approach for estimating effective population size from temporal changes in allele frequency. Genetics, 121, 379-391.
Wattier R, Engel CR, Saumitou-Laprade P, Valero M (1998) Short allele dominance as a source of heterozygote deficiency at microsatellite loci: experimental evidence at the dinucleotide locus Gv1CT in Gracillaria gracilis (Rhodophyta). Molecular Ecology, 7, 1569-1573.
Weir BS (1979) Inferences about linkage disequilibrium. Biometrics, 35, 235-254.
Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution, 38, 1358-1370.
Whitlock MC 1(999). Neutral additive genetic variance in a metapopulation. Genetical Research, 74, 215-221.
Worland AJ (1996) The influence of flowering time genes on environmental adaptability on European wheats. Euphytica, 89, 49-57.
Wray GA (2007) The evolutionary significance of cis-regulatory mutations. Nature Reviews Genetics, 8, 206-216.
Wright S (1931) Evolution in Mendellian Populations. Genetics, 16, 97-151.
Wright S (1952) The theoretical variance within and among subdivisions of a population that is in a steady state. Genetics, 37, 312-21.
Yan L, Loukoianov A, Tranquilli G, Helguera M, Fahima T,Dubcovsky J (2003) Positional cloning of the wheat vernalization gene VRN1. Proceedings of the National Academy of Sciences, 100, 6263-6268.
Yan L, Helguera M, Kato K, Fukuyama S, Sherman J, Dubcovsky J (2004) Allelic variation at the VRN-1 promoter region in polyploid wheat. Theoretical and Applied Genetics, 109, 1677-1686.
Table of content
CHAPITRE I : INTRODUCTION 4
I-1 L'adaptation comme moteur de l'évolution 4
I-1.1 Définitions et exemples 4
I-1.2 Intérêt d'étudier l'adaptation 5
I-2 Comprendre les mécanismes génétiques de l'adaptation 6
I-2.1 Dissection des bases génétiques de l'adaptation 6
I-2.1.1 Architecture des caractères quantitatifs adaptatifs 7
I-2.1.2 Détection de la sélection 9
I-2.1.3 Combinaisons de plusieurs informations 11
I-2.2 Des avancées, mais encore de nombreuses questions 11
I-2.2.1 Nombre et effets des gènes impliqués dans l’adaptation 12
I-2.2.2 « Standing genetic variation » ou nouvelles mutations ? 13
I-2.2.3 Rôle de la pléiotropie 15
I-2.2.4 Rôle de l’épistasie 15
I-2.2.5 Type des mutations préférentiellement sélectionnées 16
I-2.2.6 Conclusions 16
I-3 Etude de l'adaptation locale dans des populations expérimentales de blé héxaploïde : exemple de la précocité de floraison 17
I-3.1 Présentation des populations expérimentales de gestion dynamique 17
I-3.1.1 Principe des populations 17
I-3.1.2 Principaux résultats 18
I-3.3 Pourquoi s’intéresser à la précocité de floraison en particulier ? 20
I-3.3.1 La précocité de floraison, un caractère adaptatif majeur. 20
I-3.3.2 L’architecture du caractère chez le blé 21
I-3.3.3 Déterminisme bien connu pour des espèces modèles tels le riz ou Arabidopsis thaliana 21
I-4 Objectifs et plan de la thèse 24
CHAPITRE II : MATERIEL ET METHODES 26
II-1. Matériel végétal 26
II-1.1 Conduite des populations de gestion dynamique 26
II-1.2 Echantillonnage 27
II-1.3 Constitution du matériel d'étude 27
II-2. Dispositif expérimental pour la caractérisation phénotypique des populations 28
II-2.1 Estimation de la précocité de floraison au champ et sous différentes conditions de vernalisation en pépinière 28
II-2.2 Estimation des composantes de la précocité à partir des différents traitements 32
II-2.3 Estimation des composantes de la valeur sélective 33
II-3. Marquage microsatellite des populations de GD 34
II-3.1 Extraction 34
II-3.2 Choix des marqueurs 34
II-3.3 Génotypage et acquisition des résultats 36
II-4 Génotypage des gènes candidats 36
II-4.1 Révélation du polymorphisme de VRN-1 36
II-4.2 Révélation du polymorphisme de Ppd-1 37
II-4.3 Génotypage de FT 38
II-4.4 Génotypage de LD, CO et GI 38
CHAPITRE III : SUIVI DE L'EVOLUTION DES MARQUEURS NEUTRES DU GENOME DANS LES POPULATIONS DE GESTION DYNAMIQUE 41
III-1 Introduction 41
III-2. Méthodes 45
III-2.1 Diversité 45
III-2.2 Taux d'allo-fécondation 45
III-2.3 Structuration spatiale et temporelle 47
III-2.4 Variations de fréquences alléliques et effectifs efficaces 47
III-2.5 Déséquilibre de liaison 49
III-2.6 Reconstruction d'haplotypes multilocus 50
III-3 Résultats 52
III-3.1 Diversité génétique, apparition de nouveaux allèles 52
III-3.2 Différenciation spatiale 54
III-3.3 Variations temporelles des fréquences alléliques et effectifs efficaces 55
III-3.4 Régime de reproduction 56
III-3.5 Evolution du DL et génotype multilocus 57
III-4. Discussion 65
III-4.1 Régime de reproduction 65
III-4.2 Régime de reproduction et effectif efficace 68
III-4.3 Régime de reproduction et déséquilibre de liaison 69
III-4.4 Nouveaux allèles : mutation ou migration ? 71
III-4.5 Cas particulier de la population de Vervins 73
III-5 Conclusions 75
CHAPITRE IV: EVOLUTION DES CARACTERES QUANTITATIFS: PRECOCITE DE FLORAISON ET COMPOSANTES DE LA VALEUR SELECTIVE 77
IV-1 Introduction 77
IV-2 Méthodes 80
IV-2.1 Estimation des variances environnementales 81
IV-2.2 Evolution des caractères au cours des générations dans chaque population 84
IV-2.2.1 Evolution phénotypique des caractères 84
IV-2.2.2 Caractérisation de la variabilité génétique intra population des caractères 85
IV-2.3 Caractérisation de la variabilité génétique inter populations des caractères : mise en évidence de la sélection. 86
IV-2.4 Estimation de la sélection directionnelle directe et indirecte : approche multivariée 87
IV-2.4.1 Estimation des gradients de sélection directionnelle observés dans les conditions "champ" au Moulon. 87
IV-2.4.2 Estimation des gradients de sélection attendus dans des contextes variant pour les besoins en vernalisation 89
IV-3. Résultats 91
IV-3.1 Evolution phénotypique de la précocité et des composantes de la valeur sélective au champ 91
IV-3.2 Evolution de la variabilité intra population pour les caractères mesurés au champ 93
IV-3.3 Détection de la sélection 95
IV-3.4 Corrélations entre précocité et composantes de la valeur sélective : estimation des gradients de sélection. 96
IV-3.5 Estimation des gradients de sélection attendus en conditions différentes pour la durée de vernalisation. 97
IV-3.6. Evolution des composantes de la précocité de floraison 99
IV-3.6.1 Evolution des composantes de la précocité dans les populations 99
IV-3.6.2 Evolution des corrélations entre mesures de précocité 102
IV-4 Discussion 105
IV-4.1 Evolution de la précocité: mise en évidence de la sélection divergente 105
IV-4.2 Les forces de sélection agissant sur la précocité en relation avec les composantes de la valeur sélective 108
IV-4.3. La précocité évolue en fonction des caractéristiques climatiques de chaque site 110
IV-5 Conclusions 115
CHAPITRE V: EVOLUTION CONJOINTE DES CARACTERES QUANTITATIFS, DES MARQUEURS MICROSATELLITES ET DES GENES CANDIDATS DE PRECOCITE 116
V-1 Introduction 116
V-2 Relations entre l’évolution du gène majeur de la voie de la vernalisation et l’évolution de la sensibilité à la vernalisation 117
V-3 Détection de la sélection des gènes candidats pour la précocité de floraison 135
V-4 Conclusions 178
CHAPITRE VI : CONCLUSIONS ET PERSPECTIVES 179
VI-1 Etude de l’évolution conjointe des marqueurs microsatellites, de la précocité de floraison et des gènes candidats : synthèse des principaux résultats 179
VI-2 Apports et limites de l’étude dans la compréhension des bases génétiques de l’adaptation 181
VI-2.1 Les apports de l’étude 181
VI-2.1.1 Effets des gènes sélectionnés 181
VI-2.1.2 Standing genetic variation vs. mutation 181
VI-2.1.3 Pléiotropie 182
VI-2.1.4 Rôle de l’épistasie 182
VI-2.1.5 Type de mutations 183
VI-2.2 Les limites 184
VI-2.3 Les nouvelles interrogations 185
VI-2.3.1 Allogamie 185
VI-2.3.2 Polyploïdie 186
VI-3 Implications pour la conservation dynamique des ressources génétiques du blé 187
BIBLIOGRAPHIE 188
ANNEXES 199
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