Quantification of Variation in Expression Networks

  • Daniel J. Kliebenstein
Part of the Methods in Molecular Biology™ book series (MIMB, volume 553)


Gene expression microarrays allow rapid and easy quantification of transcript accumulation for almost transcripts present in a genome. This technology has been utilized for diverse investigations from studying gene regulation in response to genetic or environmental fluctuation to global expression QTL (eQTL) analyses of natural variation. Typical analysis techniques focus on responses of individual genes in isolation of other genes. However, emerging evidence indicates that genes are organized into regulons, i.e., they respond as groups due to individual transcription factors binding multiple promoters, creating what is commonly called a network. We have developed a set of statistical approaches that allow researchers to test specific network hypothesis using a priori-defined gene networks. When applied to Arabidopsis thaliana this approach has been able to identify natural genetic variation that controls networks. In this chapter we describe approaches to develop and test specific network hypothesis utilizing natural genetic variation. This approach can be expanded to facilitate direct tests of the relationship between phenotypic trait and transcript genetic architecture. Finally, the use of a priori network definitions can be applied to any microarray experiment to directly conduct hypothesis testing at a genomics level.

Key words

Microarray network quantitative systems biology hypothesis test 



Funding for this methods development was obtained by a National Science Foundation grants DBI 0642481 to DJK.


  1. 1.
    Zeng, Z.-B., Kao, C.-H., and Basten, C.J. (1999) Estimating the genetic architecture of quantitative traits. Genetic Research 75, 345–355.Google Scholar
  2. 2.
    Mackay, T.F.C. (2001) The genetic architecture of quantitative traits. Annual Review of Genetics 35, 303–339.PubMedCrossRefGoogle Scholar
  3. 3.
    Lander, E.S. and Botstein, D. (1989) Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121, 185–199.PubMedGoogle Scholar
  4. 4.
    Schadt, E.E., Monks, S.A., Drake, T.A., Lusis, A.J., Che, N., Colinayo, V., Ruff, T.G., Milligan, S.B., Lamb, J.R., Cavet, G., Linsley, P.S., Mao, M., Stoughton, R.B., and Friend, S.H. (2003) Genetics of gene expression surveyed in maize, mouse and man. Nature 422, 297–302.PubMedCrossRefGoogle Scholar
  5. 5.
    Craig, B.A., Black, M.A., and Doerge, R.W. (2003) Gene expression data: the technology and statistical analysis. Journal of Agricultural Biological and Environmental Statistics 8, 1–28.CrossRefGoogle Scholar
  6. 6.
    Brem, R.B., Yvert, G., Clinton, R., and Kruglyak, L. (2002) Genetic dissection of transcriptional regulation in budding yeast. Science 296, 752–755.PubMedCrossRefGoogle Scholar
  7. 7.
    Jansen, R.C. and Nap, J.P. (2001) Genetical genomics: the added value from segregation. Trends in Genetics 17, 388–391.PubMedCrossRefGoogle Scholar
  8. 8.
    Kirst, M., Basten, C.J., Myburg, A.A., Zeng, Z.B., and Sederoff, R.R. (2005) Genetic architecture of transcript-level variation in differentiating xylem of a eucalyptus hybrid. Genetics 169, 2295–2303.PubMedCrossRefGoogle Scholar
  9. 9.
    Potokina, E., Druka, A., Luo, Z., Wise, R., Waugh, R., and Kearsey, M. (2007) Gene expression quantitative trait locus analysis of 16 000 barley genes reveals a complex pattern of genome-wide transcriptional regulation. Plant Journal doi: 10.1111/j.1365-313X.2007.03315.x.Google Scholar
  10. 10.
    West, M.A.L., Kim, K., Kliebenstein, D.J., van Leeuwen, H., Michelmore, R.W., Doerge, R.W., and St. Clair, D.A. (2007) Global eQTL mapping reveals the complex genetic architecture of transcript level variation in Arabidopsis. Genetics 175, 1441–1450.Google Scholar
  11. 11.
    Keurentjes, J.J.B., Fu, J.Y., Terpstra, I.R., Garcia, J.M., van den Ackerveken, G., Snoek, L.B., Peeters, A.J.M., Vreugdenhil, D., Koornneef, M., and Jansen, R.C. (2007) Regulatory network construction in Arabidopsis by using genome-wide gene expression quantitative trait loci. Proceedings of the National Academy of Sciences of the United States of America 104, 1708–1713.PubMedCrossRefGoogle Scholar
  12. 12.
    Van Leeuwen, H., Kliebenstein, D.J., West, M.A.L., Kim, K.D., van Poecke, R., Katagiri, F., Michelmore, R.W., Doerge, R.W., and St. Clair, D.A. (2007) Natural variation among Arabidopsis thaliana accessions for transcriptome response to exogenous salicylic acid. Plant Cell 19, 2099–2110.Google Scholar
  13. 13.
    Van Poecke, R.M.P., Sato, M., Lenarz-Wyatt, L., Weisberg, S., and Katagiri, F. (2008) Natural variation in RPS2-mediated resistance among Arabidopsis accessions: correlation between gene expression profiles and phenotypic responses. Plant Cell 19, 4046–4060.CrossRefGoogle Scholar
  14. 14.
    Kliebenstein, D.J., West, M.A.L., Van Leeuwen, H., Kyunga, K., Doerge, R.W., Michelmore, R.W., and St. Clair, D.A. (2006) Genomic survey of gene expression diversity in Arabidopsis thaliana. Genetics 172, 1179–1189.Google Scholar
  15. 15.
    Flint, J., Valdar, W., Shifman, S., and Mott, R. (2005) Strategies for mapping and cloning quantitative trait genes in rodents. Nature Reviews Genetics 6, 271–286.PubMedCrossRefGoogle Scholar
  16. 16.
    Wentzell, A.M., Rowe, H.C., Hansen, B.G., Ticconi, C., Halkier, B.A., and Kliebenstein, D.J. (2007) Linking metabolic QTL with network and cis-eQTL controlling biosynthetic pathways. PLoS Genetics 3, e162.CrossRefGoogle Scholar
  17. 17.
    Sønderby, I.E., Hansen, B.G., Bjarnholt, N., Ticconi, C., Halkier, B.A., and Kliebenstein, D.J. (2007) A systems biology approach identifies a R2R3 MYB gene subfamily with distinct and overlapping functions in regulation of aliphatic glucosinolates. PLoS ONE 2, e1322.PubMedCrossRefGoogle Scholar
  18. 18.
    Hansen, B.G., Kliebenstein, D.J., and Halkier, B.A. (2007) Identification of a flavin-monooxygenase as the S-oxygenating enzyme in aliphatic glucosinolate biosynthesis in Arabidopsis. Plant Journal 50, 902–910.PubMedCrossRefGoogle Scholar
  19. 19.
    Zhang, Z.-Y., Ober, J.A., and Kliebenstein, D.J. (2006) The gene controlling the quantitative trait locus EPITHIOSPECIFIER MODIFIER1 alters glucosinolate hydrolysis and insect resistance in Arabidopsis. Plant Cell 18, 1524–1536.PubMedCrossRefGoogle Scholar
  20. 20.
    Yvert, G., Brem, R.B., Whittle, J., Akey, J.M., Foss, E., Smith, E.N., Mackelprang, R., and Kruglyak, L. (2003) Trans-acting regulatory variation in Saccharomyces cerevisiae and the role of transcription factors. Nature Genetics 35, 57–64.PubMedCrossRefGoogle Scholar
  21. 21.
    Bystrykh, L., Weersing, E., Dontje, B., Sutton, S., Pletcher, M.T., Wiltshire, T., Su, A.I., Vellenga, E., Wang, J.T., Manly, K.F., Lu, L., Chesler, E.J., Alberts, R., Jansen, R.C., Williams, R.W., Cooke, M.P., and de Haan, G. (2005) Uncovering regulatory pathways that affect hematopoietic stem cell function using ‘genetical genomics’ Nature Genetics 37, 225–232.PubMedCrossRefGoogle Scholar
  22. 22.
    Potokina, E., Druka, A., Luo, Z., Wise, R., Waugh, R., and Kearsey, M. (2008) Gene expression quantitative trait locus analysis of 16 000 barley genes reveals a complex pattern of genome-wide transcriptional regulation. Plant Journal 53, 90–101.PubMedCrossRefGoogle Scholar
  23. 23.
    Subramanian, A., Tamayo, P., Mootha, V.K., Mukherjee, S., Ebert, B.L., Gillette, M.A., Paulovich, A., Pomeroy, S.L., Golub, T.R., Lander, E.S., and Mesirov, J.P. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America 102, 15545–15550.PubMedCrossRefGoogle Scholar
  24. 24.
    Mootha, V.K., Lindgren, C.M., Eriksson, K.F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstrale, M., Laurila, E., Houstis, N., Daly, M.J., Patterson, N., Mesirov, J.P., Golub, T.R., Tamayo, P., Spiegelman, B., Lander, E.S., Hirschhorn, J.N., Altshuler, D., and Groop, L.C. (2003) PGC-1 a-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nature Genetics 34, 267–273.PubMedCrossRefGoogle Scholar
  25. 25.
    Kliebenstein, D., West, M., van Leeuwen, H., Loudet, O., Doerge, R., and St. Clair, D. (2006) Identification of QTLs controlling gene expression networks defined a priori. BMC Bioinformatics 7, 308.Google Scholar
  26. 26.
    Zhao, K.Y., Aranzana, M.J., Kim, S., Lister, C., Shindo, C., Tang, C.L., Toomajian, C., Zheng, H.G., Dean, C., Marjoram, P., and Nordborg, M. (2007) An Arabidopsis example of association mapping in structured samples. PLoS Genetics 3, e4.PubMedCrossRefGoogle Scholar
  27. 27.
    Weigel, D. and Nordborg, M. (2005) Natural variation in arabidopsis. How do we find the causal genes? Plant Physiology 138, 567–568.PubMedCrossRefGoogle Scholar
  28. 28.
    Nordborg, M., Borevitz, J.O., Bergelson, J., Berry, C.C., Chory, J., Hagenblad, J., Kreitman, M., Maloof, J.N., Noyes, T., Oefner, P.J., Stahl, E.A., and Weigel, D. (2002) The extent of linkage disequilibrium in Arabidopsis thaliana. Nature Genetics 30, 190–193.PubMedCrossRefGoogle Scholar
  29. 29.
    Loudet, O., Chaillou, S., Camilleri, C., Bouchez, D., and Daniel-Vedele, F. (2002) Bay-0 x Shahdara recombinant inbred line population: a powerful tool for the genetic dissection of complex traits in Arabidopsis. Theoretical and Applied Genetics 104, 1173–1184.PubMedCrossRefGoogle Scholar
  30. 30.
    El-Assal, S.E.D., Alonso-Blanco, C., Peeters, A.J.M., Raz, V., and Koornneef, M. (2001) A QTL for flowering time in Arabidopsis reveals a novel allele of CRY2. Nature Genetics 29, 435–440.CrossRefGoogle Scholar
  31. 31.
    Koornneef, M., Alonso-Blanco, C., and Vreugdenhil, D. (2004) Naturally occurring genetic variation in Arabidopsis thaliana. Annual Review of Plant Biology 55, 141–172.PubMedCrossRefGoogle Scholar
  32. 32.
    Clarke, J., Mithen, R., Brown, J., and Dean, C. (1995) QTL analysis of flowering time in Arabidopsis thaliana. Molecular and General Genetics 248, 278–286.PubMedCrossRefGoogle Scholar
  33. 33.
    Lister, C. and Dean, D. (1993) Recombinant inbred lines for mapping RFLP and phenotypic markers in Arabidopsis thaliana. Plant Journal 4, 745–750.CrossRefGoogle Scholar
  34. 34.
    Perchepied, L., Kroj, T., Tronchet, M., Loudet, O., and Roby, D. (2006) Natural variation in partial resistance to Pseudomonas syringae is controlled by two major QTLs in Arabidopsis thaliana. PLoS ONE 1, e123.PubMedCrossRefGoogle Scholar
  35. 35.
    Symonds, V.V., Godoy, A.V., Alconada, T., Botto, J.F., Juenger, T.E., Casal, J.J., and Lloyd, A.M. (2005) Mapping quantitative trait loci in multiple populations of Arabidopsis thaliana identifies natural allelic variation for trichome density. Genetics 169, 1649–1658.PubMedCrossRefGoogle Scholar
  36. 36.
    El-Lithy, M.E., Bentsink, L., Hanhart, C.J., Ruys, G.J., Rovito, D.I., Broekhof, J.L.M., van der Poel, H.J.A., van Eijk, M.J.T., Vreugdenhil, D., and Koornneef, M. (2006) New Arabidopsis recombinant inbred line populations genotyped using SNPWave and their use for mapping flowering-time quantitative trait loci. Genetics 172, 1867–1876.PubMedCrossRefGoogle Scholar
  37. 37.
    Nordborg, M., Hu, T.T., Ishino, Y., Jhaveri, J., Toomajian, C., Zheng, H., Bakker, E., Calabrese, P., Gladstone, J., Goyal, R., Jakobsson, M., Kim, S., Morozov, Y., Padhukasahasram, B., Plagnol, V., Rosenberg, N.A., Shah, C., Wall, J.D., Wang, J., Zhao, K., Kalbfleisch, T., Schulz, V., Kreitman, M., and Bergelson, J. (2005) The pattern of polymorphism in Arabidopsis thaliana. PLoS Biology 3, e196.PubMedCrossRefGoogle Scholar
  38. 38.
    Borevitz, J.O., Hazen, S.P., Michael, T.P., Morris, G.P., Baxter, I.R., Hu, T.T., Chen, H., Werner, J.D., Nordborg, M., Salt, D.E., Kay, S.A., Chory, J., Weigel, D., Jones, J.D.G., and Ecker, J.R. (2007) Genome-wide patterns of single-feature polymorphism in Arabidopsis thaliana. Proceedings of the National Academy of Sciences of the United States of America 104, 12057–12062.PubMedCrossRefGoogle Scholar
  39. 39.
    Clark, R.M., Schweikert, G., Toomajian, C., Ossowski, S., Zeller, G., Shinn, P., Warthmann, N., Hu, T.T., Fu, G., Hinds, D.A., Chen, H.M., Frazer, K.A., Huson, D.H., Schoelkopf, B., Nordborg, M., Raetsch, G., Ecker, J.R., and Weigel, D. (2007) Common sequence polymorphisms shaping genetic diversity in Arabidopsis thaliana. Science 317, 338–342.PubMedCrossRefGoogle Scholar
  40. 40.
    Lempe, J., Balasubramanian, S., Sureshkumar, S., Singh, A., Schmid, M., and Weigel, D. (2005) Diversity of flowering responses in wild Arabidopsis thaliana strains. PLoS Genetics 1, 109–118.PubMedCrossRefGoogle Scholar
  41. 41.
    Manfield, I.W., Jen, C.H., Pinney, J.W., Michalopoulos, I., Bradford, J.R., Gilmartin, P.M., and Westhead, D.R. (2006) Arabidopsis co-expression tool (ACT): web server tools for microarray-based gene expression analysis. Nucleic Acids Research 34, W504–W509.PubMedCrossRefGoogle Scholar
  42. 42.
    Obayashi, T., Kinoshita, K., Nakai, K., Shibaoka, M., Hayashi, S., Saeki, M., Shibata, D., Saito, K., and Ohta, H. (2007) ATTED-II: a database of co-expressed genes and cis elements for identifying co-regulated gene groups in Arabidopsis. Nucleic Acids Research 35, D863–D869.PubMedCrossRefGoogle Scholar
  43. 43.
    Grennan, A.K. (2006) Genevestigator: facilitating web-based gene-expression analysis. Plant Physiology 141, 1164–1166.PubMedCrossRefGoogle Scholar
  44. 44.
    Jen, C.H., Manfield, I.W., Michalopoulos, I., Pinney, J.W., Willats, W.G.T., Gilmartin, P.M., and Westhead, D.R. (2006) The Arabidopsis co-expression tool (ACT): a WWW-based tool and database for microarray-based gene expression analysis. Plant Journal 46, 336–348.PubMedCrossRefGoogle Scholar
  45. 45.
    Zimmermann, P., Hennig, L., and Gruissem, W. (2005) Gene-expression analysis and network discovery using Genevestigator. Trends in Plant Science 10, 407–409.PubMedCrossRefGoogle Scholar
  46. 46.
    Obayashi, T., Okegawa, T., Sasaki-Sekimoto, Y., Shimada, H., Masuda, T., Asamizu, E., Nakamura, Y., Shibata, D., Tabata, S., Takamiya, K.I., and Ohta, H. (2004) Distinctive features of plant organs characterized by global analysis of gene expression in arabidopsis. DNA Research 11, 11–25.PubMedCrossRefGoogle Scholar
  47. 47.
    Gachon, C.M.M., Langlois-Meurinne, M., Henry, Y., and Saindrenan, P. (2005) Transcriptional co-regulation of secondary metabolism enzymes in Arabidopsis: functional and evolutionary implications. Plant Molecular Biology 58, 229–245.PubMedCrossRefGoogle Scholar
  48. 48.
    Wei, H.R., Persson, S., Mehta, T., Srinivasasainagendra, V., Chen, L., Page, G.P., Somerville, C., and Loraine, A. (2006) Transcriptional coordination of the metabolic network in Arabidopsis. Plant Physiology 142, 762–774.PubMedCrossRefGoogle Scholar
  49. 49.
    Zhang, P.F., Foerster, H., Tissier, C.P., Mueller, L., Paley, S., Karp, P.D., and Rhee, S.Y. (2005) MetaCyc and AraCyc. Metabolic pathway databases for plant research. Plant Physiology 138, 27–37.PubMedCrossRefGoogle Scholar
  50. 50.
    Mueller, L.A., Zhang, P.F., and Rhee, S.Y. (2003) AraCyc: a biochemical pathway database for Arabidopsis. Plant Physiology 132, 453–460.PubMedCrossRefGoogle Scholar
  51. 51.
    Luo, Z.W., Potokina, E., Druka, A., Wise, R., Waugh, R., and Kearsey, M. J. (2007) SFP genotyping from Affymetrix arrays is robust but largely detects cis-acting expression regulators. Genetics 176, 789–800.PubMedCrossRefGoogle Scholar
  52. 52.
    Richardson, A., Boscari, A., Schreiber, L., Kerstiens, G., Jarvis, M., Herzyk, P., and Fricke, W. (2007) Cloning and expression analysis of candidate genes involved in wax deposition along the growing barley (Hordeum vulgare) leaf. Planta 226, 1459–1473.PubMedCrossRefGoogle Scholar
  53. 53.
    Shen, L.H., Gong, J., Caldo, R.A., Nettleton, D., Cook, D., Wise, R.P., and Dickerson, J.A. (2005) BarleyBase – an expression profiling database for plant genornics. Nucleic Acids Research 33, D614–D618.PubMedCrossRefGoogle Scholar
  54. 54.
    Saito, K., Hirai, M., and Yonekura-Sakakibara, K. (2008) Decoding genes with coexpression networks and metabolomics – ‘majority report by precogs’. Trends in Plant Science 13, 36–43.Google Scholar
  55. 55.
    Kearsey, M.J. and Farquhar, A.G.L. (1998) QTL analysis in plants; where are we now? Heredity 80, 137–142.PubMedCrossRefGoogle Scholar
  56. 56.
    Jordan, M.C., Somers, D.J., and Banks, T.W. (2007) Identifying regions of the wheat genome controlling seed development by mapping expression quantitative trait loci. Plant Biotechnology Journal 5, 442–453.PubMedCrossRefGoogle Scholar
  57. 57.
    DeCook, R., Lall, S., Nettleton, D., and Howell, S.H. (2006) Genetic regulation of gene expression during shoot development in Arabidopsis. Genetics 172, 1155–1164.PubMedCrossRefGoogle Scholar
  58. 58.
    Juenger, T.E., Wayne, T., Boles, S., Symonds, V.V., McKay, J., and Coughlan, S.J. (2006) Natural genetic variation in whole-genome expression in Arabidopsis thaliana: the impact of physiological QTL introgression. Molecular Ecology 15, 1351–1365.PubMedCrossRefGoogle Scholar
  59. 59.
    Street, N.R., Skogstrom, O., Sjodin, A., Tucker, J., Rodriguez-Acosta, M., Nilsson, P., Jansson, S., and Taylor, G. (2006) The genetics and genomics of the drought response in Populus. Plant Journal 48, 321–341.PubMedCrossRefGoogle Scholar
  60. 60.
    An, C.F., Saha, S., Jenkins, J.N., Scheffler, B.E., Wilkins, T.A., and Stelly, D.M. (2007) Transcriptome profiling, sequence characterization, and SNP-based chromosomal assignment of the EXPANSIN genes in cotton. Molecular Genetics and Genomics 278, 539–553.PubMedCrossRefGoogle Scholar
  61. 61.
    Venu, R.C., Jia, Y., Gowda, M., Jia, M.H., Jantasuriyarat, C., Stahlberg, E., Li, H., Rhineheart, A., Boddhireddy, P., Singh, P., Rutger, N., Kudrna, D., Wing, R., Nelson, J.C., and Wang, G.L. (2007) RL-SAGE and microarray analysis of the rice transcriptome after Rhizoctonia solani infection. Molecular Genetics and Genomics 278, 421–431.PubMedCrossRefGoogle Scholar
  62. 62.
    Kiani, S.P., Grieu, P., Maury, P., Hewezi, T., Gentzbittel, L., and Sarrafi, A. (2007) Genetic variability for physiological traits under drought conditions and differential expression of water stress-associated genes in sunflower (Helianthus annuus L.). Theoretical and Applied Genetics 114, 193–207.CrossRefGoogle Scholar
  63. 63.
    Shi, C., Uzarowska, A., Ouzunova, M., Landbeck, M., Wenzel, G., and Lubberstedt, T. (2007) Identification of candidate genes associated with cell wall digestibility and eQTL (expression quantitative trait loci) analysis in a Flint x Flint maize recombinant inbred line population. BMC Genomics 8, 22.PubMedCrossRefGoogle Scholar
  64. 64.
    Aoki, K., Ogata, Y., and Shibata, D. (2007) Approaches for extracting practical information from gene co-expression networks in plant biology. Plant and Cell Physiology 48, 381–390.PubMedCrossRefGoogle Scholar
  65. 65.
    Hirai, M.Y., Klein, M., Fujikawa, Y., Yano, M., Goodenowe, D.B., Yamazaki, Y., Kanaya, S., Nakamura, Y., Kitayama, M., Suzuki, H., Sakurai, N., Shibata, D., Tokuhisa, J., Reichelt, M., Gershenzon, J., Papenbrock, J., and Saito, K. (2005) Elucidation of gene-to-gene and metabolite-to-gene networks in Arabidopsis by integration of metabolomics and transcriptomics. Journal of Biological Chemistry 280, 25590–25595.PubMedCrossRefGoogle Scholar
  66. 66.
    Ma, S.S., Gong, Q.Q., and Bohnert, H.J. (2007) An Arabidopsis gene network based on the graphical Gaussian model. Genome Research 17, 1614–1625.PubMedCrossRefGoogle Scholar
  67. 67.
    Urbanczyk-Wochniak, E. and Sumner, L.W. (2007) MedicCyc: a biochemical pathway database for Medicago truncatula. Bioinformatics 23, 1418–1423.PubMedCrossRefGoogle Scholar
  68. 68.
    Caspi, R., Foerster, H., Fulcher, C.A., Hopkinson, R., Ingraham, J., Kaipa, P., Krummenacker, M., Paley, S., Pick, J., Rhee, S.Y., Tissier, C., Zhang, P.F., and Karp, P.D. (2006) MetaCyc: a multiorganism database of metabolic pathways and enzymes. Nucleic Acids Research 34, D511–D516.PubMedCrossRefGoogle Scholar
  69. 69.
    Li, S.M., Armstrong, C.M., Bertin, N., Ge, H., Milstein, S., Boxem, M., Vidalain, P.O., Han, J.D.J., Chesneau, A., Hao, T., Goldberg, D.S., Li, N., Martinez, M., Rual, J.F., Lamesch, P., Xu, L., Tewari, M., Wong, S.L., Zhang, L.V., Berriz, G.F., Jacotot, L., Vaglio, P., Reboul, J., Hirozane-Kishikawa, T., Li, Q.R., Gabel, H.W., Elewa, A., Baumgartner, B., Rose, D.J., Yu, H.Y., Bosak, S., Sequerra, R., Fraser, A., Mango, S.E., Saxton, W.M., Strome, S., van den Heuvel, S., Piano, F., Vandenhaute, J., Sardet, C., Gerstein, M., Doucette-Stamm, L., Gunsalus, K.C., Harper, J.W., Cusick, M.E., Roth, F.P., Hill, D.E., and Vidal, M. (2004) A map of the interactome network of the metazoan C-elegans. Science 303, 540–543.PubMedCrossRefGoogle Scholar
  70. 70.
    von Mering, C., Krause, R., Snel, B., Cornell, M., Oliver, S.G., Fields, S., and Bork, P. (2002) Comparative assessment of large-scale data sets of protein–protein interactions. Nature 417, 399–403.CrossRefGoogle Scholar
  71. 71.
    Ito, T., Chiba, T., Ozawa, R., Yoshida, M., Hattori, M., and Sakaki, Y. (2001) A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proceedings of the National Academy of Sciences of the United States of America 98, 4569–4574.PubMedCrossRefGoogle Scholar
  72. 72.
    Geisler-Lee, J., O'Toole, N., Ammar, R., Provart, N.J., Millar, A.H., and Geisler, M. (2007) A predicted interactome for Arabidopsis. Plant Physiology 145, 317–329.PubMedCrossRefGoogle Scholar
  73. 73.
    Wei, N., Chamovitz, D.A., and Deng, X.W. (1994) Arabidopsis Cop9 is a component of a novel signaling complex mediating light control of development. Cell 78, 117–124.PubMedCrossRefGoogle Scholar
  74. 74.
    Vision, T.J., Brown, D.G., and Tanksley, S.D. (2000) The origins of genomic duplications in Arabidopsis. Science 290, 2114–2117.PubMedCrossRefGoogle Scholar
  75. 75.
    Blanc, G., Hokamp, K., and Wolfe, K.H. (2003) A recent polyploidy superimposed on older large-scale duplications in the Arabidopsis genome. Genome Research 13, 137–144.PubMedCrossRefGoogle Scholar
  76. 76.
    Wolfe, K.H. and Shields, D.C. (1997) Molecular evidence for an ancient duplication of the entire yeast genome. Nature 387, 708–713.PubMedCrossRefGoogle Scholar
  77. 77.
    Blanc, G. and Wolfe, K.H. (2004) Widespread paleopolyploidy in model plant species inferred from age distributions of duplicate genes. Plant Cell 16, 1667–1678.PubMedCrossRefGoogle Scholar
  78. 78.
    Ober, D. (2005) Seeing double: gene duplication and diversification in plant secondary metabolism. Trends in Plant Science 10, 444–449.PubMedCrossRefGoogle Scholar
  79. 79.
    Meyer, R.C., Steinfath, M., Lisec, J., Becher, M., Witucka-Wall, H., Törjék, O., Fiehn, O., Eckardt, A., Willmitzer, L., Selbig, J., and Altmann, T. (2007) The metabolic signature related to high plant growth rate in Arabidopsis thaliana. Proceedings of the National Academy of Sciences of the United States of America 104, 4759–4764.PubMedCrossRefGoogle Scholar
  80. 80.
    Basten, C.J., Weir, B.S., and Zeng, Z.-B. (1999) QTL Cartographer, Version 1.13, Department of Statistics, North Carolina State University, Raleigh, N.C.Google Scholar
  81. 81.
    Wang, S., Basten, C.J., and Zeng, Z.-B. (2006) Windows QTL Cartographer 2.5. Department of Statistics, North Carolina State University, Raleigh, NC.Google Scholar
  82. 82.
    Irizarry, R.A., Hobbs, B., Collin, F., Beazer-Barclay, Y.D., Antonellis, K.J., Scherf, U., and Speed, T.P. (2003) Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4, 249–264.PubMedCrossRefGoogle Scholar
  83. 83.
    Churchill, G.A. and Doerge, R.W. (1994) Empirical threshold values For quantitative trait mapping. Genetics 138, 963–971.PubMedGoogle Scholar
  84. 84.
    Bogdan, M. and Doerge, R.W. (2005) Biased estimators of quantitative trait locus heritability and location in interval mapping. Heredity 95, 476–484.PubMedCrossRefGoogle Scholar
  85. 85.
    Doerge, R.W. (2002) Mapping and analysis of quantitative trait loci in experimental populations. Nature Reviews Genetics 3, 43–52.PubMedCrossRefGoogle Scholar
  86. 86.
    Doerge, R.W. and Churchill, G.A. (1996) Permutation tests for multiple loci affecting a quantitative character. Genetics 142, 285–294.PubMedGoogle Scholar
  87. 87.
    Gilbert, H. and Le Roy, P. (2003) Comparison of three multitrait methods for QTL detection. Genetics Selection Evolution 35, 281–304.CrossRefGoogle Scholar
  88. 88.
    Knott, S.A. and Haley, C.S. (2000) Multitrait least squares for quantitative trait loci detection. Genetics 156, 899–911.PubMedGoogle Scholar
  89. 89.
    Ronin, Y.I., Kirzhner, V.M., and Korol, A.B. (1995) Linkage between loci of quantitative traits and marker loci – multi-trait analysis with a single marker. Theoretical and Applied Genetics 90, 776–786.CrossRefGoogle Scholar
  90. 90.
    Chen, M. and Kendziorski, C. (2007) A statistical framework for expression quantitative trait loci mapping. Genetics 177, 761–771.PubMedCrossRefGoogle Scholar
  91. 91.
    Ball, R.D. (2007) Quantifying evidence for candidate gene polymorphisms: Bayesian analysis combining sequence-specific and quantitative trait loci colocation information. Genetics 177, 2399–2416.PubMedCrossRefGoogle Scholar
  92. 92.
    Hoti, F. and Sillanpaa, M.J. (2006) Bayesian mapping of genotype x expression interactions in quantitative and qualitative traits. Heredity 97, 4–18.PubMedCrossRefGoogle Scholar
  93. 93.
    Lan, H., Chen, M., Flowers, J.B., Yandell, B.S., Stapleton, D.S., Mata, C.M., Mui, E.T.K., Flowers, M.T., Schueler, K.L., Manly, K.F., Williams, R.W., Kendziorski, C., and Attie, A.D. (2006) Combined expression trait correlations and expression quantitative trait locus mapping. PLoS Genetics 2, 51–61.CrossRefGoogle Scholar

Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Daniel J. Kliebenstein
    • 1
  1. 1.Department of Plant SciencesUniversity of CaliforniaDavisUSA

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