, Volume 129, Issue 2, pp 205–216 | Cite as

Resolving the genetic basis of invasiveness and predicting invasions

  • Cynthia Weinig
  • Marcus T. Brock
  • Jenny A. Dechaine
  • Stephen M. Welch


Considerable effort has been invested in determining traits underlying invasiveness. Yet, identifying a set of traits that commonly confers invasiveness in a range of species has proven elusive, and almost nothing is known about genetic loci affecting invasive success. Incorporating genetic model organisms into ecologically relevant studies is one promising avenue to begin dissecting the genetic underpinnings of invasiveness. Molecular biologists are rapidly characterizing genes mediating developmental responses to diverse environmental cues, i.e., genes for plasticity, as well as to environmental factors likely to impose strong selection on invading species, e.g., resistance to herbivores and competitors, coordination of life-history events with seasonal changes, and physiological tolerance of heat, drought, or cold. Here, we give an overview of molecular genetic tools increasingly used to characterize the genetic basis of adaptation and that may be used to begin identifying genetic mechanisms of invasiveness. Given the divergent traits that affect invasiveness, “invasiveness genes” common to many clades are unlikely, but the combination of developmental genetic advances with further evolutionary studies and modeling may provide a framework for identifying genes that account for invasiveness in related species.


Adaptive strategies Arabidopsis thaliana Competitive ability Invasive species Phenotypic plasticity Quantitative trait loci 



Earlier versions of this paper benefited from the comments of C.E. Lee, and three anonymous reviewers. The paper was invited for the 2004 Society for the Study of Evolution Symposium “All Stressed Out and Nowhere to Go: Does Evolvability Limit Adaptation in Invasive Species?” The research on Arabidopsis thaliana described here has been supported by NSF grant DBI-0227103 and USDA-AES grant MIN-71–048 to CW and, in part, by NSF grant 0425759 to SW.


  1. Alonso-Blanco A, Peeters AJM, Koornneef M, Lister C, Dean C, van den Bosch N, Pot J, Kuiper MT (1998) Development of an AFLP based linkage map of Ler, Col and Cvi Arabidopsis thaliana ecotypes and construction of a Ler/Cvi recombinant inbred line population. Plant J 14:259–271PubMedCrossRefGoogle Scholar
  2. Ardlie KG, Kruglyak L, Seielstad M (2002) Patterns of linkage disequilibrium in the human genome. Nat Rev Genet 3:299–309PubMedCrossRefGoogle Scholar
  3. Ausín I, Alonso-Blanco C, Martínez-Zapater J (2005) Environmental regulation of flowering. Int J Dev Biol 49:689–705PubMedCrossRefGoogle Scholar
  4. Benz J (2006) An on-line Registry of Ecological Models containing many entries for economic plants is located at Scholar
  5. Borevitz JO, Nordborg M (2003) The impact of genomics on the study of natural variation in Arabidopsis. Plant Physiol 132:718–725PubMedCrossRefGoogle Scholar
  6. Botto JF, Smith H (2002) Differential genetic variation in adaptive strategies to a common environmental signal in Arabidopsis accessions: phytochrome-mediated shade avoidance. Plant Cell Environ 25:57–67CrossRefGoogle Scholar
  7. Bouman BAM, van Keulen H, van Laar HH, Rabbinge R (1996) The ‘School of de Wit’ crop growth simulation models: a pedigree and historical overview. Agric Syst 52:171–198CrossRefGoogle Scholar
  8. Brandman O, Ferrell JE Jr, Li R, Meyer T (2005) Interlinked fast and slow positive feedback loops drive reliable cell decisions. Science 310:496–498PubMedCrossRefGoogle Scholar
  9. Bray EA (1997) Plant responses to water deficit. Trends Plant Sci 2:48–54CrossRefGoogle Scholar
  10. Callahan HS, Pigliucci M (2002) Shade-induced plasticity and its ecological significance in wild populations of Arabidopsis thaliana. Ecology 83:1965–1980Google Scholar
  11. Carlson AM, Gorchov DL (2004) Effects of herbicide on the invasive biennial Alliaria petiolata (garlic mustard) and initial responses of native plants in a southwestern Ohio forest. Restor Ecol 12:559–567CrossRefGoogle Scholar
  12. Chhandak B, Halfhill MD, Mueller TC, Stewart CNJ (2004) Weed genomics: new tools to understand weed biology. Trends Plant Sci 9:1360–1385Google Scholar
  13. Cooper M, Hammer GL (eds) (2005) Complex traits and plant breeding—can we understand the complexities of gene-to-phenotype relationships and use such knowledge to enhance plant breeding outcomes. Aust J Agric Res 56(special issue):869–960CrossRefGoogle Scholar
  14. David JR, Gibert P, Moreteau B (2004) Evolution of reaction norms. In: Dewitt TJ, Scheiner SM (eds) Phenotypic plasticity. Oxford University Press, New York, pp. 50–63Google Scholar
  15. Dodd AN, Salathia N, Hall A, Kevei E, Toth R, Nagy F, Hibberd JM, Millar AJ, Webb AAR (2005) Plant circadian clocks increase photosynthesis, growth, survival, and competitive advantage. Science 309:630–633PubMedCrossRefGoogle Scholar
  16. Donatelli M, Bindi M, Porter JR, van Ittersum MK (eds) (2002) Process simulation and application of cropping systems models. Eur J Agron 18(special issue):1–185Google Scholar
  17. Donohue K, Polisetty CR, Wender NJ (2005) Genetic basis and consequences of niche construction: plasticity-induced genetic constraints on the evolution of seed dispersal in Arabidopsis thaliana. Am Nat 165:537–550PubMedCrossRefGoogle Scholar
  18. Dorn LA, Pyle EH, Schmitt J (2000) Plasticity to light cues and resources in Arabidopsis thaliana: testing for adaptive value and costs. Evolution 54:1982–1994PubMedGoogle Scholar
  19. Dudley SA, Schmitt J (1996) Testing the adaptive plasticity hypothesis: density-dependent selection on manipulated stem length in Impatiens capensis. Am Nat 147:445–465CrossRefGoogle Scholar
  20. Ellstrand NC, Schierenbeck KA (2000) Hybridization as a stimulus for the evolution of invasiveness in plants? Proc Natl Acad Sci USA 97:7043–7050PubMedCrossRefGoogle Scholar
  21. Endler JA (1986) Natural selection in the wild. Princeton University Press, PrincetonGoogle Scholar
  22. Falconer DS, Mackay TFC (1997) Introduction to quantitative genetics. Addison Wesley Longman Ltd, EssexGoogle Scholar
  23. Fankhauser C, Chory J (1997) Light control of plant development. Annu Rev Cell Dev Biol 13:203–229PubMedCrossRefGoogle Scholar
  24. Fisher RA (1930) The genetical theory of natural selection. Oxford University Press, OxfordGoogle Scholar
  25. Forger D, Drapeau M, Collins B, Blau J (2005) A new model for circadian clock research? Mol Syst Biol. DOI 10.1038/msb4100019Google Scholar
  26. Fowler S, Lee K, Onouchi H, Samach A, Richardson K, Morris B, Coupland G, Putterill J (1999) GIGANTEA: a circadian clock-controlled gene that regulates photoperiodic flowering in Arabidopsis and encodes a protein with several possible membrane-spanning domains. EMBO J 18:4679–4688PubMedCrossRefGoogle Scholar
  27. Galen C, Huddle J, Liscum E (2004) An experimental test of the adaptive evolution of phototropins: blue-light photoreceptors controlling phototropism in Arabidopsis thaliana. Evolution 58:515–523PubMedGoogle Scholar
  28. Geiger-Thornsberry GL, Mackay TFC (2002) Association of single-nucleotide polymorphisms at the Delta locus with genotype by environment interaction for sensory bristle number in D. melanogaster. Genet Res 79:211–218PubMedCrossRefGoogle Scholar
  29. Goodnight CJ (1995) Epistasis and the increase in additive genetic variance: implications for phase I of Wright’s shifting balance process. Evolution 49:502–511CrossRefGoogle Scholar
  30. Griffith C, Kim E, Donohue K (2004) Life-history variation and adaptation in the historically mobile plant Arabidopsis thaliana in North America. Am J Bot 91:837–849Google Scholar
  31. Grimm SS, Jones JW, Boote KJ, Hesketh JD (1993) Parameter estimation for predicting flowering date of soybean cultivars. Crop Sci 33:137–144CrossRefGoogle Scholar
  32. Hanks J, Ritchie JT (1991) Modeling plant and soil systems. ASA, CSSA, SSSA, MadisonGoogle Scholar
  33. Hardin PE (2004) Transcription regulation within the circadian clock: the E-box and beyond. J Biol Rhythms 19:348–360PubMedCrossRefGoogle Scholar
  34. Holm L, Doll J, Holm E, Pancho J, Herberger J (1997) World weeds: natural histories and distribution. Wiley, New YorkGoogle Scholar
  35. Hoogenboom G (2006) Readers wishing to simulate a selection of crops can do so on-line using daily weather data for locations in the state of Georgia (USA) at i-bin/ = AAAA&report = dsGoogle Scholar
  36. Hoogenboom G, Jones JW, Boote KJ (1992) Modeling the growth development, and yield of grain legumes using SOYGRO, PNUTGRO, and BEANGRO: a review. Trans ASAE 35:2043–2056Google Scholar
  37. Huq E, Quail PH (2002) PIF4, a phytochrome-interacting BHLH factor, functions as a negative regulator of phytochrome B signaling in Arabidopsis. EMBO J 21:2441–2450PubMedCrossRefGoogle Scholar
  38. Huq E, Tepperman JM, Quail PH (2000) GIGANTEA is a nuclear protein involved in phytochrome signaling in Arabidopsis. Proc Natl Acad Sci USA 97:9789–9794PubMedCrossRefGoogle Scholar
  39. Irmak A, Jones JW, Mavromatis T, Welch SM, Boote KJ, Wilkerson GG (2000) Evaluating methods for simulating soybean cultivar responses using cross validation. Agron J 92:1140–1149CrossRefGoogle Scholar
  40. Jamieson PD, Brooking IR, Semenov MA, Porter JR (1998) Making sense of wheat development: a critique of methodology. Field Crops Res 55:117–127CrossRefGoogle Scholar
  41. Johanson U, West J, Lister C, Michaels S, Amasino R, Dean C (2000) Molecular analysis of FRIGIDA, a major determinant of natural variation in Arabidopsis flowering time. Science 290:344–347PubMedCrossRefGoogle Scholar
  42. Kingsolver JG, Hoekstra HE, Hoekstra JM, Berrigan D, Vignieri SN, Hill CE, Hoang A, Gibert P, Beerli P (2001) The strength of phenotypic selection in natural populations. Am Nat 157:245–261CrossRefPubMedGoogle Scholar
  43. Kiniry JR, Williams JR, Gassman PW, Debaeke P (1992) A general, process-oriented model for two competing plant species. Trans ASAE 35:801–810Google Scholar
  44. Kliebenstein DJ, Gershenzon J, Mitchell-Olds T (2001) Comparative quantitative trait loci mapping of aliphatic, indolic and benzylic glucosinolate production in Arabidopsis thaliana leaves and seeds. Genetics 159(1):359–370PubMedGoogle Scholar
  45. Kliebenstein DJ, Figuth A, Mitchell-Olds T (2002a) Genetic architecture of plastic methyl jasmonate responses in Arabidopsis thaliana. Genetics 161(4):1685–1696Google Scholar
  46. Kliebenstein D, Pedersen D, Barker B, Mitchell-Olds T (2002b) Comparative analysis of quantitative trait loci controlling glucosinolates, myrosinase and insect resistance in Arabidopsis thaliana. Genetics 161:325–332Google Scholar
  47. Leblanc ML, Cloutier DC, Stewart KA, Hamel C (2004) Calibration and validation of a common lambsquarters (Chenopodium album) seedling emergence model. Weed Sci 52:61–66CrossRefGoogle Scholar
  48. Lee CE (2002) Evolutionary genetics of invasive species. Trends Ecol Evol 17:386–391CrossRefGoogle Scholar
  49. Leips J, Mackay TFC (2000) Quantitative trait loci for life span in Drosophila melanogaster: interactions with genetic background and larval density. Genetics 155:1773–1788PubMedGoogle Scholar
  50. Lexer C, Welch ME, Durphy JL, Rieseberg LH (2003) Natural selection for salt tolerance quantitative trait loci (QTLs) in wild sunflower hybrids: implications for the origin of Helianthus paradoxus, a diploid hybrid species. Mol Ecol 12:1225–1235PubMedCrossRefGoogle Scholar
  51. Lister C, Dean C (1993) Recombinant inbred lines for mapping RFLP and phenotypic markers in Arabidopsis thaliana. Plant J 4:745–750 CrossRefGoogle Scholar
  52. Locke JCW, Southern MM, Kozma-Bognar L, Hibberd V, Brown PE, Turner MS, Millar AJ (2005) Extension of a genetic network model by iterative experimentation and mathematical analysis. Mol Syst Biol. DOI 10.1038/msb4100018Google Scholar
  53. Long AD, Lyman RF, Langley CH, Mackay TFC (1998) Two sites in the Delta gene region contribute to naturally occurring variation in bristle number in Drosophila melanogaster. Genetics 149:999–1017PubMedGoogle Scholar
  54. Ma CX, Casella G, Wu RL (2002) Functional mapping of quantitative trait loci underlying the character process: a theoretical framework. Genetics 161:1751–1762PubMedGoogle Scholar
  55. Mackay TFC (2001) Quantitative trait loci in Drosophila. Nat Genet 2:11–20Google Scholar
  56. Malmberg RL, Held S, Waits A, Mauricio R (2005) Epistasis for fitness-related quantitative traits in Arabidopsis thaliana grown in the field and in the greenhouse. Genetics 171(4): 2013–2027 PubMedCrossRefGoogle Scholar
  57. Maloof JN, Borevitz JO, Dabi T, Lutes J, Nehring RB, Redfern JL, Trainer GT, Wilson JM, Asami T, Berry CC, Weigel D, Chory J (2001) Natural variation in light sensitivity of Arabidopsis. Nat Genet 29(4):441–446 PubMedCrossRefGoogle Scholar
  58. Mauricio R (1998) Costs of resistance to natural enemies in field populations of the annual plant Arabidopsis thaliana. Am Nat 151:20–28CrossRefPubMedGoogle Scholar
  59. Mauricio R (2001) Mapping quantitative trait loci in plants: uses and caveats for evolutionary biology. Nat Rev Genet 2:370–381PubMedCrossRefGoogle Scholar
  60. McKay JK, Richards JH, Mitchell-Olds T (2003) Genetics of drought adaptation in Arabidopsis thaliana: I. Pleiotropy contributes to genetic correlations among ecological traits. Mol Ecol 12:1137–1151PubMedCrossRefGoogle Scholar
  61. Meekins JF, McCarthy BC (1999) Competitive ability of Alliaria petiolata (garlic mustard, Brassicaceae), an invasive, nonindigenous forest herb. Int J Plant Sci 160:743–752CrossRefGoogle Scholar
  62. Michaels SD, Amasino RM (1999) FLOWERING LOCUS C encodes a novel MADS domain protein that acts as a repressor of flowering. Plant Cell 11:949–956PubMedCrossRefGoogle Scholar
  63. Michaels SD, Amasino RM (2000) Memories of winter: vernalization and the competence to flower. Plant Cell Environ 23:1145–1153CrossRefGoogle Scholar
  64. Millar AJ (1999) Tansley review no. 103—biological clocks in Arabidopsis thaliana. New Phytol 141:175–197CrossRefGoogle Scholar
  65. Mitchell-Olds T (1996) Genetic constraints on life-history evolution: Quantitative-trait loci influencing growth and flowering in Arabidopsis thaliana. Evolution 50:140–145CrossRefGoogle Scholar
  66. Mitchell-Olds T (2001) Arabidopsis thaliana and its wild relatives: a model system for ecology and evolution. Trends Ecol Evol 16:693–700CrossRefGoogle Scholar
  67. Napp-Zinn K (1976) Population genetical and geographical aspects of germination and flowering in Arabidopsis thaliana. Arab Inf Serv 13Google Scholar
  68. Neff MM, Fankhauser C, Chory J (2000) Light: an indicator of time and place. Genes Dev 14:257–271PubMedGoogle Scholar
  69. Ni M, Tepperman JM, Quail PH (1998) PIF3, a phytochrome-interacting factor necessary for normal photoinduced signal transduction, is a novel basic helix-loop-helix protein. Cell 95:657–667PubMedCrossRefGoogle Scholar
  70. Ni M, Tepperman JM, Quail PH (1999) Binding of phytochrome B to its nuclear signalling partner PIF3 is reversibly induced by light. Nature 400:781–784PubMedCrossRefGoogle Scholar
  71. Nordborg M, Bergelson J (1999) The effect of seed and rosette cold treatment on germination and flowering time in some Arabidopsis thaliana (Brassicaceae) ecotypes. Am J Bot 86:470PubMedCrossRefGoogle Scholar
  72. Nordborg M, Hu TT, Ishino Y, Jhaveri J, Toomajian C, Zheng HG, Bakker E, Calabrese P, Gladstone J, Goyal R, Jakobsson M, Kim S, Morozov Y, Padhukasahasram B, Plagnol V, Rosenberg NA, Shah C, Wall JD, Wang J, Zhao KY, Kalbfleisch T, Schulz V, Kreitman M, Bergelson J (2005) The pattern of polymorphism in Arabidopsis thaliana. PLoS Biol 3(7): 1289–1299CrossRefGoogle Scholar
  73. Nuzhdin SV, Pasyukova EG, Dilda CL, Zeng Z-B, Mackay TFC (1997) Sex-specific quantitative trait loci affecting longevity in Drosophila melanogaster. Proc Natl Acad Sci USA 94:9734–9739PubMedCrossRefGoogle Scholar
  74. Oliver LR (1979) Influence of soybean (Glycine max) planting date on velvetleaf (Abutilon theophrasti). Weed Sci 27:183–188Google Scholar
  75. Olsen KM, Halldorsdottir SS, Stinchcombe JR, Weinig C, Schmitt J, Purugganan MD (2004) Linkage disequilibrium mapping of Arabidopsis CRY2 flowering time alleles. Genetics 167:1361–1369PubMedCrossRefGoogle Scholar
  76. Palsson A, Gibson G (2004) Association between nucleotide variation in Egfr and wing shape in Drosophila melanogaster. Genetics 167:1187–1198PubMedCrossRefGoogle Scholar
  77. Paz JO, Batchelor WD, Tylka GL, Hartzler RG (2001) A modeling approach to quantify the effects of spatial soybean yield limiting factors. Trans ASAE 44:1329–1334Google Scholar
  78. Penrose LDJ, Rawson HM, Zajac M (2003) Prediction of vernalisation in three Australian vrn responsive wheats. Aust J Agric Res 54:283–292CrossRefGoogle Scholar
  79. Pritchard JK, Donnelly P (2001) Case–control studies of association in structured or admixed populations. Theor Popul Biol 60:227–237PubMedCrossRefGoogle Scholar
  80. Pritchard JK, Stephens M, Rosenberg NA, Donnelly P (2000) Association mapping in structured populations. J Hum Genet 67:170–181CrossRefGoogle Scholar
  81. Rand DA, Shulgin BV, Salazar JD, Millar AJ (2006) Uncovering the design principles of circadian clocks: mathematical analysis of flexibility and evolutionary goals. J Theor Biol 238:616–635PubMedCrossRefGoogle Scholar
  82. Ratcliffe D (1965) Germination characteristics and their inter- and intra-population variability in Arabidopsis. Arab Inf Serv 13Google Scholar
  83. Rejmanek M (2000) Invasive plants: approaches and predictions. Aust J Ecol 25:497–506CrossRefGoogle Scholar
  84. Remington DL, Ungerer MC, Purugganan MD (2001) Map-based cloning of quantitative trait loci: progress and prospects. Genet Res 78:213–218PubMedCrossRefGoogle Scholar
  85. Reymond M, Muller B, Leonardi A, Charcosset A, Tardieu F (2003) Combining quantitative trait loci analysis and an ecophysiological model to analyze the genetic variability of the responses of maize leaf growth to temperature and water deficit. Plant Physiol 131:664–675PubMedCrossRefGoogle Scholar
  86. Richards RA (1996) Defining selection criteria to improve yield under drought. Plant Growth Regul 20:157–166CrossRefGoogle Scholar
  87. Richardson DM, Pysek P, Rejmanek M, Barbour MG, Panetta FD, West CJ (2000) Naturalization and invasion of alien plants: concepts and definitions. Divers Distrib 6:93–107CrossRefGoogle Scholar
  88. Ritchie JT, Singh U, Goodwin DC, Bowen WT (1998) Cereal growth, development, and yield. In: Tsuji GY, Hoogenboom G, Thornton PK (eds) Understanding options for agricultural production. Kluwer Academic, Dordrecht, pp. 79–97Google Scholar
  89. Schmitt J, McCormac AC, Smith H (1995) A test of the adaptive plasticity hypothesis using transgenic and mutant plants disabled in phytochrome-mediated elongation responses to neighbors. Am Nat 146:937–953CrossRefGoogle Scholar
  90. Schranz ME, Quijada P, Sung SB, Lukens L, Amasino R, Osborn TC (2002) Characterization and effects of the replicated flowering time gene FLC in Brassica rapa. Genetics 162:1457–1468PubMedGoogle Scholar
  91. Sharrock RA, Quail PH (1989) Novel phytochrome sequences in Arabidopsis thaliana: structure, evolution, and differential expression of a plant regulatory photoreceptor family. Genes Dev 3:1745–1757PubMedCrossRefGoogle Scholar
  92. Shimizu KK, Purugganan MD (2005) Evolutionary and ecological genomics of Arabidopsis thaliana. Plant Physiol 138:578–584PubMedCrossRefGoogle Scholar
  93. Smith H (2000) Phytochromes and light signal perception by plants—an emerging synthesis. Nature 407:585–591PubMedCrossRefGoogle Scholar
  94. Soh MS, Song P-S, Choi G (1999) Phytochrome signalling is mediated through nucleoside diphosphate kinase 2. Nature 401:610–613PubMedCrossRefGoogle Scholar
  95. Spencer NR (1984) Velvetleaf, Abutilon theophrasti (Malvaceae), history and economic impact in the United States. Econ Bot 38:407–416Google Scholar
  96. Stinchcombe JR, Weinig C, Ungerer M, Olsen KM, Mays C, Halldorsdottir SS, Purugganan MD, Schmitt J (2004) A latitudinal cline in flowering time in Arabidopsis thaliana modulated by the flowering time gene FRIGIDA. Proc Natl Acad Sci USA 101:4712–4717PubMedCrossRefGoogle Scholar
  97. Tan DKY, Birch CJ, Wearing AH, Rickert KG (2000) Predicting broccoli development. II. Comparison and validation of thermal time models. Sci Hortic 86:89–101CrossRefGoogle Scholar
  98. Tardieu F (2003) Virtual plants: modeling as a tool for the genomics of tolerance to water deficit. Trends Plant Sci 8:9–14PubMedCrossRefGoogle Scholar
  99. Tardieu F, Reymond M, Muller B, Simonneau T, Sadok W, Welcker C (2005) Linking physiological and genetic analyses of the control of leaf growth under fluctuating environmental conditions. Aust J Agric Res 56:937–946CrossRefGoogle Scholar
  100. Thornsberry JM, Goodman MM, Doebley J, Kresovich S, Nielsen D, Buckler ES 4th (2001) Dwarf8 polymorphisms associate with variation in flowering time. Nat Genet 28:286–289PubMedCrossRefGoogle Scholar
  101. Ungerer MC, Halldorsdottir SS, Modliszewski JL, Mackay TFC, Purugganan MD (2002) Quantitative trait loci for inflorescence development in Arabidopsis thaliana. Genetics 160:1133–1151PubMedGoogle Scholar
  102. van Eeuwijk FA, Malosetti M, Yin X, Struik PC, Stam P (2005) Statistical models for genotype by environment data: from conventional ANOVA to eco-physiological QTL models. Aust J Agric Res 56:883–894CrossRefGoogle Scholar
  103. Viczian A, Kircher S, Fejes E, Millar AJ, Schafer E, Kozma-Bognar L, Nagy F (2005) Functional characterization of phytochrome interacting factor 3 for the Arabidopsis thaliana circadian clockwork. Plant Cell Physiol 46:1591–1602PubMedCrossRefGoogle Scholar
  104. Villalobos FJ, Hall AJ, Ritchie JT, Orgaz F (1996) OILCROP-SUN: a development, growth, and yield model of the sunflower crop. Agron J 88:403–415CrossRefGoogle Scholar
  105. Wade MJ, Goodnight CJ (1998) Perspective: the theories of Fisher and Wright in the context of metapopulations: when nature does many small experiments. Evolution 52:1537–1553CrossRefGoogle Scholar
  106. Warwick SI, Black LD (1985) Genecological variation in recently established populations of Abutilon theophrasti. Can J Bot 64:1632–1643CrossRefGoogle Scholar
  107. Weinig C (2000a) Differing selection in alternative competitive environments: shade-avoidance responses and germination timing. Evolution 54:124–136Google Scholar
  108. Weinig C (2000b) Plasticity versus canalization: population differences in the timing of shade-avoidance responses. Evolution 54:441–451Google Scholar
  109. Weinig C (2000c) Limits to adaptive plasticity: Temperature and photoperiod influence shade-avoidance responses. Am J Bot 87(11):1660–1668CrossRefGoogle Scholar
  110. Weinig C, Delph LF (2001) Phenotypic plasticity early in life constrains developmental responses later. Evolution 55(5): 930–936PubMedCrossRefGoogle Scholar
  111. Weinig C, Ungerer MC, Dorn LA, Halldorsdottir SS, Toyonaga Y, Mackay TFC, Purugganan MD, Schmitt J (2002) Novel loci control variation in reproductive timing in Arabidopsis thaliana in natural environments. Genetics 162:1875–1884PubMedGoogle Scholar
  112. Weinig C, Schmitt J (2004) Environmental effects on the expression of quantitative trait loci and implications for phenotypic evolution. BioScience 54:627–635CrossRefGoogle Scholar
  113. Weinig C, Stinchcombe JR, Schmitt J (2003a) Evolutionary genetics of resistance and tolerance to natural herbivory in Arabidopsis thaliana. Evolution 57:1270–1280Google Scholar
  114. Weinig C, Dorn LA, Kane NC, Ungerer MC, Halldorsdottir SS, German ZM, Toyonaga Y, Mackay TFC, Purugganan MD, Schmitt J (2003b) Heterogeneous selection at specific loci in natural environments in Arabidopsis thaliana. Genetics 165:321–329Google Scholar
  115. Weinig C, Stinchcombe JR, Schmitt J (2003c) QTL architecture of resistance and tolerance traits in Arabidopsis thaliana in natural environments. Mol Ecol 12:1153–1163CrossRefGoogle Scholar
  116. Weinig C, Johnston J, German ZM, Demink LM (2006) Local and global costs of adaptive plasticity to density in Arabidopsis thaliana. Am Nat 167(6):826–836CrossRefGoogle Scholar
  117. Weinig C, Johnston JA, Willis C, Maloof JN (in review) Antagonistic multilevel selection on size, architecture, and developmental timing in experimental and feral stands of Arabidopsis thaliana. EvolutionGoogle Scholar
  118. Weiss A (ed) (2003) Crop modeling and genomics. Agron J 95(special issue):1–113CrossRefGoogle Scholar
  119. Welch SM, Wilkerson G, Whiting K, Sun N, Vagts T, Buol G, Mavromatis T (2002) Estimating soybean model genetic coefficients from private-sector variety performance trial data. Trans ASAE 45:1163–1175Google Scholar
  120. Welch SM, Dong Z, Roe JL, Das S (2005a) Flowering time control: gene network modelling and the link to quantitative genetics. Aust J Agric Res 56:919–936CrossRefGoogle Scholar
  121. Welch SM, Roe JL, Das S, Dong Z, He R, Kirkham MB (2005b) Merging genomic control networks and soil–plant–atmosphere–continuum models. Agric Syst 86:243–274CrossRefGoogle Scholar
  122. Williamson M (1999) Invasions. Ecography 22:5–12CrossRefGoogle Scholar
  123. Wilson IW, Schiff CL, Hughes DE, Somerville SC (2001) Quantitative trait loci analysis of powdery mildew disease resistance in the Arabidopsis thaliana accession Kashmir-1. Genetics 158:1301–1309PubMedGoogle Scholar
  124. Wright S (1931) Evolution in Mendelian populations. Genetics 16:97–159PubMedGoogle Scholar
  125. Wright S (1977) Evolution and genetics of populations. University of Chicago Press, ChicagoGoogle Scholar
  126. Yano M, Katayose Y, Ashikari M, Yamanouchi U, Monna L, Fuse T, Baba T, Yamamoto K, Umehara Y, Nagamura Y, Sasaki T (2000) Hd1, a major photoperiod sensitivity quantitative trait locus in rice, is closely related to the Arabidopsis flowering time gene CONSTANS. Plant Cell 12:2473–2484PubMedCrossRefGoogle Scholar
  127. Yanovsky M, Kay SA (2002) Molecular basis of seasonal time measurement in Arabidopsis. Nature 419:308–313PubMedCrossRefGoogle Scholar
  128. Yin X, Kropff M, Stam P (1999a) The role of ecophysiological models in QTL analysis: the example of specific leaf area in barley. Heredity 82:415–421CrossRefGoogle Scholar
  129. Yin X, Stam P, Dourleijn C, Kropff M (1999b) AFLP mapping of quantitative trait loci for yield determining physiological characters in spring barley. Theor Appl Genet 99:244–253CrossRefGoogle Scholar
  130. Yin X, Struik PC, van Eeuwijk FA, Stam P, Tang J (2005) QTL analysis and QTL-based prediction of flowering phenology in recombinant inbred lines of barley. J Exp Bot 56:967–976PubMedCrossRefGoogle Scholar
  131. Zhao W, Zhu J, Gallo-Meagher M, Wu R (2004) A unified statistical model for functional mapping of environment-dependent genetic expression and genotype × environment interactions for ontogenetic development. Genetics 168:1751–1762PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2006

Authors and Affiliations

  • Cynthia Weinig
    • 1
  • Marcus T. Brock
    • 1
  • Jenny A. Dechaine
    • 1
  • Stephen M. Welch
    • 2
  1. 1.Department of Plant BiologyUniversity of MinnesotaSt PaulUSA
  2. 2.Department of AgronomyKansas State UniversityManhattenUSA

Personalised recommendations