The Potential of Genomics and Genetics to Understand Plant Response to Elevated Atmospheric [CO2]

  • G. Taylor
  • P. J. Tricker
  • L. E. Graham
  • M. J. Tallis
  • A. M. Rae
  • H. Trewin
  • N. R. Street
Part of the Ecological Studies book series (ECOLSTUD, volume 187)


Quantitative Trait Locus Single Nucleotide Polymorphism Natural Genetic Variation Elevated Carbon Dioxide Face Experiment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Agrawal GK, Rakwal R, Yonekura M, Kubo A, Saji H (2002) Proteome analysis of differentially displayed proteins as a tool for investigating ozone stress in rice (Oryza sativa L.) seedlings. Proteomics 2:947–959PubMedCrossRefGoogle Scholar
  2. Ainsworth EA, Long SP (2005) What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. New Phytol 165:351–371PubMedCrossRefGoogle Scholar
  3. Alba R, Fei ZJ, Payton P, Liu Y, Moore SL, Debbie P, Cohn J, D’Ascenzo M, Gordon JS, Rose JKC, Martin G, Tanksley SD, Bouzayen M, Jahn MM, Giovannoni J (2004) ESTs, cDNA microarrays, and gene expression profiling: tools for dissecting plant physiology and development. Plant J 39: 697–714PubMedCrossRefGoogle Scholar
  4. Alonso-Blanco C, El-Assal SE, Coupland G, Koornneef M (1998) Analysis of natural allelic variation at flowering time loci in the landsberg erecta and Cape Verde Islands ecotypes of Arabidopsis thaliana. Genetics 149:749–764PubMedGoogle Scholar
  5. Andersson A, Keskitalo J, Sjodin A, Bhalerao R, Sterky F, Wissel K, Tandre K, Aspeborg H, Moyle R, Ohmiya Y, Bhalerao R, Brunner A, Gustafsson P, Karlsson J, Lundeberg J, Nilsson O, Sandberg G, Strauss S, Sundberg B, Uhlen M, Jansson S, Nilsson (2004) A transcriptional timetable of autumn senescence. Genome Biol 5:R24PubMedCrossRefGoogle Scholar
  6. Bae H, Sicher R (2004) Changes in soluble protein expression and leaf metabolite levels in Arabidopsis thaliana grown in elevated carbon dioxide. Field Crop Res 90:61–73CrossRefGoogle Scholar
  7. Bertrand C, Benhamed M, Li YF, Ayadi M, Lemonnier G, Renou JP, Delarue M, Zhou DX (2005) Arabidopsis HAF2 gene encoding TATA-binding protein (TBP)-associated factor TAF1, is required to integrate light signals to regulate gene expression and growth. J Biol Chem 280:1465–1473PubMedCrossRefGoogle Scholar
  8. Bhalerao R, Keskitalo J, Sterky F, Erlandsson R, Bjorkbacka H, Jonsson Birve S, Karlsson J, Gardestrom P, Gustafsson P, Lundeberg J, Jansson S (2003) Gene expression in autumn leaves. Plant Physiol 131:1–13CrossRefGoogle Scholar
  9. Bino RJ, Hall RD, Fiehn O, Kopka J, Saito K, Draper J, Nikolau BJ, Mendes P, Roessner-Tunali U, Beale MH, Trethewey RN, Lange BM, Wurtele ES, Sumner LW (2004) Potential of metabolomics as a functional genomics tool. Trends Plant Sci 9:418–425PubMedCrossRefGoogle Scholar
  10. Blanchard JL (2004) Bioinformatics and systems biology, rapidly evolving tools for interpreting plant response to global change. Field Crops Res 90:117–131CrossRefGoogle Scholar
  11. Bradshaw HD, Villar M, Watson BD, Otto KG, Stewart S, Stettler RF (1994) Molecular genetics of growth and development in Populus. III.A genetic linkage map of a hybrid poplar composed of RFLP, STS, and RAPD markers. Theor Appl Genet 89:167–178Google Scholar
  12. Cardon LR, Fulker DW (1994) The power of interval mapping of quantitative trait loci using selected sib pairs. Am J Hum Genet 55:825–833PubMedGoogle Scholar
  13. Chivasa S, Ndimba BK, Simon WJ, Robertson D, Yu XL, Knox JP, Bolwell P, Slabas AR (2002) Proteomic analysis of the Arabidopsis thaliana cell wall. Electrophoresis 23:1754–1765PubMedCrossRefGoogle Scholar
  14. Clauser, K.R., Baker, P., and Burlingame, A.L. (1999) Role of accurate mass measurement (±10 ppm) in protein identification strategies employing MS or MS/MS and database searching. Anal Chem 71:2871–2882PubMedCrossRefGoogle Scholar
  15. Cronk QCB (2005) Plant eco-devo: the potential of poplar as a model organism. New Phytol 166:39–48PubMedCrossRefGoogle Scholar
  16. Deyholos MK, Galbraith DW (2001) High-density microarrays for gene expression analysis. Cytometry 43:229–238PubMedCrossRefGoogle Scholar
  17. Eisen MB, Spellman PT, Brown PO, Botstein D (1998) Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 95:14863–14868PubMedCrossRefGoogle Scholar
  18. Feder ME, Mitchell-Olds T (2003) Evolutionary and ecological functional genomics. Nature 4:649–655Google Scholar
  19. Fernandes J, Brendel V, Gai XW, Lal S, Chandler VL, Elumalai P, Galbraith DW, Pierson EA, Walbot V (2002) Comparison of RNA expression profiles based on maize expressed sequence tag frequency analysis and micro-array hybridization. Plant Physiol 128:896–910PubMedCrossRefGoogle Scholar
  20. Ferris R, Sabatti M, Miglietta F, Mills RF, Taylor G (2001) Leaf area is stimulated in Populus by free air CO2 enrichment (POPFACE), through cell expansion and production. Plant Cell Environ 24:305–315CrossRefGoogle Scholar
  21. Ferris R, Long L, Bunn SM, Robinson KM, Bradshaw HD, Rae AM, Taylor G (2002) Leaf stomatal and epidermal cell development: identification of putative quantitative trait loci in relation to elevated carbon dioxide concentration in poplar. Tree Physiol 22:633–640PubMedGoogle Scholar
  22. Fiehn O, Kopka J, Dormann P, Altmann T, Trethewey RN, Willmitzer L (2000) Metabolite profiling for plant functional genomics. Nat Biotechnol 18:1157–1161PubMedCrossRefGoogle Scholar
  23. Fullerton J, Cubin M, Bhomra A, Davidson S, Miller S, Turn M, Dolby C, Mott R, Wang C, Tiwari H, Allison D, Neale M, Fairburn C, Goodwin G, Flint J (2002) Linkage analysis of extremely discordant and concordant sibling pairs identifies QTL that influence variation in a human personality trait. Am J Hum Genet 71[Suppl]:263Google Scholar
  24. Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA, Bloomfield CD, Lander ES (1999) Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286:531–537PubMedCrossRefGoogle Scholar
  25. Gupta P, Duplessis S, white H, Karnosky DF, Martin F, Podila GK (2005a) Gene expression patterns of trembling aspen trees following long-term exposure to interacting elevated CO2 and tropospheric O3. New Phytol (in press)Google Scholar
  26. Gupta PK, Rustgi S, Kulwal PL (2005b) Linkage disequilibrium and association studies in higher plants: present status and future prospects. Plant Mol Biol 57:461–485PubMedCrossRefGoogle Scholar
  27. Hall R, Beale M, Fiehn O, Hardy N, Sumner L, Bino R (2002) Plant metabolomics: the missing link in functional genomics strategies. Plant Cell 14:1437–1440PubMedCrossRefGoogle Scholar
  28. Hetherington AM, Woodward FI (2003) The role of stomata in sensing and driving environmental change. Nature 424:901–908PubMedCrossRefGoogle Scholar
  29. Ideker T, Galitski T, Hood L (2005) A new approach to decoding life: Systems biology. Annu Rev Genomics Hum Genet 2:343–372CrossRefGoogle Scholar
  30. Kearsey MJ, Farquhar AGL (1998) QTL analysis in plants; where are we now? Heredity 80:137–142PubMedCrossRefGoogle Scholar
  31. Kirkpatrick M, Jarne P (2000) The effects of a bottleneck on inbreeding depression and the genetic load. Am Nat 155:154–167PubMedCrossRefGoogle Scholar
  32. Lister C, Dean C (1993) Recombinant inbred lines for mapping RFLP and phenotypic markers in Arabidopsis thaliana. Plant J 4:745–750CrossRefGoogle Scholar
  33. Luscombe NM, Greenbaum D, Gerstein M (2001) What is bioinformatics? A proposed definition and overview of the field. Methods Inform Med 40:346–358Google Scholar
  34. Martin GB (1998) Gene discovery for crop improvement. Curr Opin Biotechnol 9:220–226PubMedCrossRefGoogle Scholar
  35. Matsuyama T, Tamaoki M, Nakajima N, Aono M, Kubo A, Moriya S, Ichihara T, Suzuki O, Saji H (2002) cDNA microarray assessment for ozone-stressed Arabidopsis thaliana. Environ Pollut 117:191–194PubMedCrossRefGoogle Scholar
  36. Michael TP, McClung CR (2003) Enhancer trapping reveals widespread circadian clock transcriptional control in Arabidopsis. Plant J 31:279–292Google Scholar
  37. Miyazaki S, Fredricksen M, Hollis KC, Poroyko V, Shepley D, Galbraith DW, Long SP, Bohnert HJ (2004) Transcript expression profiles of Arabidopsis thaliana grown under controlled conditions and open-air elevated concentrations of CO2 and O3. Field Crop Res 90:47–59CrossRefGoogle Scholar
  38. Moore BD, Cheng SH, Rice J, Seemann JR (1998) Sucrose cycling, Rubisco expression, and prediction of photosynthetic acclimation to elevated atmospheric CO2. Plant Cell Environ 21:905–915CrossRefGoogle Scholar
  39. Norby RJ, Wullschleger SD, Gunderson CA, Johnson DW, Ceulemans R (1999) Tree responses to rising CO2 in field experiments: implications for the future forst. Plant, Cell Environ 22:683–714CrossRefGoogle Scholar
  40. Nordborg M (2000) Linkage disequilibrium, gene trees and selfing: an ancestral recombination graph with partial self-fertilization. Genetics 154:923–929PubMedGoogle Scholar
  41. Palaisa K, Morgante M, Tingey S, Rafalski A (2004) Long-range patterns of diversity and linkage disequilibrium surrounding the maize Y1 gene are indicative of an asymmetric selective sweep. Proc Natl Acad Sci USA 101:9885–9890PubMedCrossRefGoogle Scholar
  42. Perkins DN, Pappin DJC, Creasy DM, Cottrell JS (1999) Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20:3551–3567PubMedCrossRefGoogle Scholar
  43. Pichersky E, Gang DR (2000) Genetics and biochemistry of secondary metabolites in plants: an evolutionary perspective. Trends Plant Sci 5:439–445PubMedCrossRefGoogle Scholar
  44. Quadroni M, James P (1999) Proteomics and automation. Electrophoresis 20:664–677PubMedCrossRefGoogle Scholar
  45. Qin J, Fenyo D, Zhao YM, Hall WW, Chao DM, Wilson CJ, Young RA, Chait BT (1997) A strategy for rapid, high confidence protein identification. Anal Chem 69:3995–4001PubMedCrossRefGoogle Scholar
  46. Rae AM, Graham LE, Street NR, Hughes J, Hanley ME, Tucker J, Taylor G (2005) QTL for growth and development in elevated carbon dioxide in two model plant genera: a novel approach for understanding adaptation to climate change? Global Change Biol (in press)Google Scholar
  47. Rafalski A, Morgante M (2004) Corn and humans: recombination and linkage disequilibrium in two genomes of similar size. Trends Genet 20:103–111PubMedCrossRefGoogle Scholar
  48. Ranasinghe S, Taylor G (1996) Mechanism for increased leaf growth in elevated CO2. J Exp Bot 47:349–358Google Scholar
  49. Ranish JA, Yi EC, Leslie DM, Purvine SO, Goodlett DR, Eng J, Aebersold R (2003) The study of macromolecular complexes by quantitative proteomics. Nat Genet 33:349–355PubMedCrossRefGoogle Scholar
  50. Schaffer R, Landgraf J, Perez-Amador M, Wisman E (2000) Monitoring genome-wide expression in plants. Curr Opin Biotechnol 11:162–167PubMedCrossRefGoogle Scholar
  51. Schena M, Shalon D, Davis RW, Brown PO (1995) Quantitative monitoring of gene-expression patterns with a complementary-DNA microarray. Science 270:467–470PubMedGoogle Scholar
  52. Schrader J, Nilsson J, Mellerowicz E, Berglund A, Nilsson P, Hertzberg M, Sandberg G (2004) A high-resolution transcript profile across the wood-forming meristem of poplar identifies potential regulators of cambial stem cell identity. Plant Cell 16:2278–2292PubMedCrossRefGoogle Scholar
  53. Seki M, Narusaka M, Ishida J, Nanjo T, Fujita M, Oono Y, Kamiya A, Nakajima M, Enju A, Sakurai T, Satou M, Akiyama K, Taji T, Yamaguchi-Shinozaki K, Carninci P, Kawai J, Hayashizaki Y, Shinozaki K (2002) Monitoring the expression profiles of 7000 Arabidopsis genes under drought, cold and high-salinity stresses using a full-length cDNA microarray. Plant J 31:279–292PubMedCrossRefGoogle Scholar
  54. Sumner LW, Mendes P, Dixon RA (2003) Plant metabolomics: large-scale phytochemistry in the functional genomics era. Phytochemistry 62:817–836PubMedCrossRefGoogle Scholar
  55. Tao WA, Aebersold R (2003) Advances in quantitative proteomics via stable isotope tagging and mass spectrometry. Curr Opin Biotechnol 14:110–118PubMedCrossRefGoogle Scholar
  56. Taylor G, Tricker PJ, Zhang FZ, Alston VJ, Miglietta F, Kuzminsky E (2003) Spatial and temporal effects of free-air CO2 enrichment (POPFACE) on leaf growth, cell expansion, and cell production in a closed canopy of poplar. Plant Physiol 131:177–185PubMedCrossRefGoogle Scholar
  57. Taylor G, Street NR, Tricker PJ, Sjödin A, Graham L, Skogström O, Calfapietra C, Scarascia-Mugnozza, Janssen S (2005) The transciptome of Populus in elevated CO2. New Phytol 167:143–154PubMedCrossRefGoogle Scholar
  58. Thimm O, Blasing O, Gibon Y, Nagel A, Meyer S, Kruger P, Selbig J, Muller LA, Rhee SY, Stitt M (2004) MAPMAN: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. Plant J 37:914–939PubMedCrossRefGoogle Scholar
  59. Vodkin LO, Khanna A, Shealy R, Clough SJ, Gonzalez DO, Philip R, Zabala G, Thibaud-Nissen F, Sidarous M, Stromvik MV, Shoop E, Schmidt C, Retzel E, Erpelding J, Shoemaker RC, Rodriguez-Huete AM, Polacco JC, Coryell V, Keim P, Gong G, Liu L, Pardinas J, Schweitzer P (2004) Microarrays for global expression constructed with a low redundancy set of 27,500 sequenced cDNAs representing an array of developmental stages and physiological conditions of the soybean plant. Genomics 5:73PubMedCrossRefGoogle Scholar
  60. Wagner C, Sefkow M, Kopka J (2003) Construction and application of a mass spectral and retention time index database generated from plant GC/EI-TOF-MS metabolite profiles. Phytochemistry 62:887–900PubMedCrossRefGoogle Scholar
  61. Ward JK, Kelly JK (2004) Scaling up evolutionary responses to elevated CO2: lessons from Arabidopsis. Ecol Lett 7:427–440CrossRefGoogle Scholar
  62. Wasaki J, Yonetani R, Shinano T, Kai M, Osaki M (2003) Expression of the OsPI1 gene, cloned from rice roots using cDNA microarray, rapidly responds to phosphorus status. New Phytol 158:239–248CrossRefGoogle Scholar
  63. Watson BS, Lei ZT, Dixon RA, Sumner LW (2004) Proteomics of Medicago sativa cell walls. Phytochemistry 65:1709–1720PubMedCrossRefGoogle Scholar
  64. Weir BS, Basten CJ (1990) Sampling strategies for distances between DNA-sequences. Biometrics 46:551–572PubMedCrossRefGoogle Scholar
  65. Wu R, Ma CX, Casella G (2002) Joint linakge and linkage disequilibrium mapping of quantitative trait loci in natural populations. Genetics 160:779–792PubMedGoogle Scholar
  66. Wu TD (2001) Analysing gene expression data from DNA microarrays to identify candidate genes. J Pathol 195:53–65PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • G. Taylor
    • 1
  • P. J. Tricker
    • 1
  • L. E. Graham
    • 1
  • M. J. Tallis
    • 1
  • A. M. Rae
    • 1
  • H. Trewin
    • 1
  • N. R. Street
    • 1
  1. 1.School of Biological Sciences, Bassett Crescent EastUniversity of SouthamptonSouthamptonUK

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