One of the central goals in biology is to understand how and how much of the phenotype of an organism is encoded in its genome. Although many genes that are crucial for organismal processes have been identified, much less is known about the genetic bases underlying quantitative phenotypic differences in natural populations. We discuss the fundamental gap between the large body of knowledge generated over the past decades by experimental genetics in the laboratory and what is needed to understand the genotype-to-phenotype problem on a broader scale. We argue that systems genetics, a combination of systems biology and the study of natural variation using quantitative genetics, will help to address this problem. We present major advances in these two mostly disconnected areas that have increased our understanding of the developmental processes of flowering time control and root growth. We conclude by illustrating and discussing the efforts that have been made toward systems genetics specifically in plants.


Article metrics loading...

Loading full text...

Full text loading...


Literature Cited

  1. Alonso-Blanco C, Andrade J, Becker C, Bemm F, Bergelson J. et al. 2016. 1,135 genomes reveal the global pattern of polymorphism in Arabidopsis thaliana. Cell 166:1–11 [Google Scholar]
  2. Alqudah AM, Sharma R, Pasam RK, Graner A, Kilian B, Schnurbusch T. 2014. Genetic dissection of photoperiod response based on GWAS of pre-anthesis phase duration in spring barley. PLOS ONE 9:e113120 [Google Scholar]
  3. Angel A, Song J, Yang H, Questa JI, Dean C, Howard M. 2015. Vernalizing cold is registered digitally at FLC. PNAS 112:4146–51 [Google Scholar]
  4. Aranzana MJ, Kim S, Zhao KY, Bakker E, Horton M. et al. 2005. Genome-wide association mapping in Arabidopsis identifies previously known flowering time and pathogen resistance genes. PLOS Genet. 1:531–39 [Google Scholar]
  5. Atwell S, Huang YS, Vilhjalmsson BJ, Willems G, Horton M. et al. 2010. Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines. Nature 465:627–31 [Google Scholar]
  6. Ayroles JF, Carbone MA, Stone EA, Jordan KW, Lyman RF. et al. 2009. Systems genetics of complex traits in Drosophila melanogaster. Nat. Genet. 41:299–307 [Google Scholar]
  7. Bac-Molenaar JA, Fradin EF, Becker FFM, Rienstra JA, van der Schoot J. et al. 2015. Genome-wide association mapping of fertility reduction upon heat stress reveals developmental stage-specific QTLs in Arabidopsis thaliana. Plant Cell 27:1857–74 [Google Scholar]
  8. Band LR, Wells DM, Fozard JA, Ghetiu T, French AP. et al. 2014. Systems analysis of auxin transport in the Arabidopsis root apex. Plant Cell 26:862–75 [Google Scholar]
  9. Band LR, Wells DM, Larrieu A, Sun J, Middleton AM. et al. 2012. Root gravitropism is regulated by a transient lateral auxin gradient controlled by a tipping-point mechanism. PNAS 109:4668–73 [Google Scholar]
  10. Basnet RK, Del Carpio DP, Xiao D, Bucher J, Jin M. et al. 2016. A systems genetics approach identifies gene regulatory networks associated with fatty acid composition in Brassica rapa seed. Plant Physiol. 170:568–85 [Google Scholar]
  11. Battle A, Khan Z, Wang SH, Mitrano A, Ford MJ. et al. 2015. Impact of regulatory variation from RNA to protein. Science 347:664–67 [Google Scholar]
  12. Beemster GT, De Vusser K, De Tavernier E, De Bock K, Inze D. 2002. Variation in growth rate between Arabidopsis ecotypes is correlated with cell division and A-type cyclin–dependent kinase activity. Plant Physiol. 129:854–64 [Google Scholar]
  13. Begum H, Spindel JE, Lalusin A, Borromeo T, Gregorio G. et al. 2015. Genome-wide association mapping for yield and other agronomic traits in an elite breeding population of tropical rice (Oryza sativa). PLOS ONE 10:e0119873 [Google Scholar]
  14. Berger GL, Liu SY, Hall MD, Brooks WS, Chao SM. et al. 2013. Marker-trait associations in Virginia Tech winter barley identified using genome-wide mapping. Theor. Appl. Genet. 126:693–710 [Google Scholar]
  15. Birnbaum K, Shasha DE, Wang JY, Jung JW, Lambert GM. et al. 2003. A gene expression map of the Arabidopsis root. Science 302:1956–60 [Google Scholar]
  16. Bouche F, Lobet G, Tocquin P, Perilleux C. 2016. FLOR-ID: an interactive database of flowering-time gene networks in Arabidopsis thaliana. Nucleic Acids Res. 44:D1167–71 [Google Scholar]
  17. Bouchet S, Servin B, Bertin P, Madur D, Combes V. et al. 2013. Adaptation of maize to temperate climates: Mid-density genome-wide association genetics and diversity patterns reveal key genomic regions, with a major contribution of the Vgt2 (ZCN8) locus. PLOS ONE 8:e71377 [Google Scholar]
  18. Brachi B, Faure N, Bergelson J, Cuguen J, Roux F. 2013a. Genome-wide association mapping of flowering time in Arabidopsis thaliana in nature: genetics for underlying components and reaction norms across two successive years. Acta Bot. Gallica 160:205–18 [Google Scholar]
  19. Brachi B, Faure N, Horton M, Flahauw E, Vazquez A. et al. 2010. Linkage and association mapping of Arabidopsis thaliana flowering time in nature. PLOS Genet. 6:e1000940 [Google Scholar]
  20. Brachi B, Morris GP, Borevitz JO. 2011. Genome-wide association studies in plants: The missing heritability is in the field. Genome Biol. 12:232 [Google Scholar]
  21. Brachi B, Villoutreix R, Faure N, Hautekeete N, Piquot Y. et al. 2013b. Investigation of the geographical scale of adaptive phenological variation and its underlying genetics in Arabidopsis thaliana. Mol. Ecol. 22:4222–40 [Google Scholar]
  22. Brady SM, Orlando DA, Lee JY, Wang JY, Koch J. et al. 2007. A high-resolution root spatiotemporal map reveals dominant expression patterns. Science 318:801–6 [Google Scholar]
  23. Brady SM, Zhang L, Megraw M, Martinez NJ, Jiang E. et al. 2011. A stele-enriched gene regulatory network in the Arabidopsis root. Mol. Syst. Biol. 7:459 [Google Scholar]
  24. Breakfield NW, Corcoran DL, Petricka JJ, Shen J, Sae-Seaw J. et al. 2012. High-resolution experimental and computational profiling of tissue-specific known and novel miRNAs in Arabidopsis. Genome Res. 22:163–76 [Google Scholar]
  25. Bruex A, Kainkaryam RM, Wieckowski Y, Kang YH, Bernhardt C. et al. 2012. A gene regulatory network for root epidermis cell differentiation in Arabidopsis. PLOS Genet. 8:e1002446 [Google Scholar]
  26. Chan EK, Rowe HC, Corwin JA, Joseph B, Kliebenstein DJ. 2011. Combining genome-wide association mapping and transcriptional networks to identify novel genes controlling glucosinolates in Arabidopsis thaliana. PLOS Biol. 9:e1001125 [Google Scholar]
  27. Chen X, Guo W, Liu B, Zhang Y, Song X. et al. 2012. Molecular mechanisms of fiber differential development between G. barbadense and G. hirsutum revealed by genetical genomics. PLOS ONE 7:e30056 [Google Scholar]
  28. Civelek M, Lusis AJ. 2014. Systems genetics approaches to understand complex traits. Nat. Rev. Genet. 15:34–48 [Google Scholar]
  29. Cockram J, White J, Zuluaga DL, Smith D, Comadran J. et al. 2010. Genome-wide association mapping to candidate polymorphism resolution in the unsequenced barley genome. PNAS 107:21611–16 [Google Scholar]
  30. Costanzo M, Baryshnikova A, Bellay J, Kim Y, Spear ED. et al. 2010. The genetic landscape of a cell. Science 327:425–31 [Google Scholar]
  31. Cruz-Ramirez A, Diaz-Trivino S, Blilou I, Grieneisen VA, Sozzani R. et al. 2012. A bistable circuit involving SCARECROW-RETINOBLASTOMA integrates cues to inform asymmetric stem cell division. Cell 150:1002–15 [Google Scholar]
  32. Cubillos FA, Yansouni J, Khalili H, Balzergue S, Elftieh S. et al. 2012. Expression variation in connected recombinant populations of Arabidopsis thaliana highlights distinct transcriptome architectures. BMC Genom. 13:117 [Google Scholar]
  33. de Leeuw CA, Neale BM, Heskes T, Posthuma D. 2016. The statistical properties of gene-set analysis. Nat. Rev. Genet. 17:353–64 [Google Scholar]
  34. De Rybel B, Adibi M, Breda AS, Wendrich JR, Smit ME. et al. 2014. Plant development. Integration of growth and patterning during vascular tissue formation in Arabidopsis. Science 345:1255215 [Google Scholar]
  35. De Rybel B, Vassileva V, Parizot B, Demeulenaere M, Grunewald W. et al. 2010. A novel aux/IAA28 signaling cascade activates GATA23-dependent specification of lateral root founder cell identity. Curr. Biol. 20:1697–706 [Google Scholar]
  36. De Smet I, Vassileva V, De Rybel B, Levesque MP, Grunewald W. et al. 2008. Receptor-like kinase ACR4 restricts formative cell divisions in the Arabidopsis root. Science 322:594–97 [Google Scholar]
  37. DeCook R, Lall S, Nettleton D, Howell SH. 2006. Genetic regulation of gene expression during shoot development in Arabidopsis. Genetics 172:1155–64 [Google Scholar]
  38. Deng W, Ying H, Helliwell CA, Taylor JM, Peacock WJ, Dennis ES. 2011. FLOWERING LOCUS C (FLC) regulates development pathways throughout the life cycle of Arabidopsis. PNAS 108:6680–85 [Google Scholar]
  39. Ding J, Nilsson O. 2015. Molecular regulation of phenology in trees—because the seasons they are a-changin'. Curr. Opin. Plant Biol. 29:73–79 [Google Scholar]
  40. Dinneny JR, Long TA, Wang JY, Jung JW, Mace D. et al. 2008. Cell identity mediates the response of Arabidopsis roots to abiotic stress. Science 320:942–45 [Google Scholar]
  41. Dong Z, Danilevskaya O, Abadie T, Messina C, Coles N, Cooper M. 2012. A gene regulatory network model for floral transition of the shoot apex in maize and its dynamic modeling. PLOS ONE 7:e43450 [Google Scholar]
  42. Drost DR, Benedict CI, Berg A, Novaes E, Novaes CR. et al. 2010. Diversification in the genetic architecture of gene expression and transcriptional networks in organ differentiation of Populus. PNAS 107:8492–97 [Google Scholar]
  43. Drost DR, Puranik S, Novaes E, Novaes CR, Dervinis C. et al. 2015. Genetical genomics of Populus leaf shape variation. BMC Plant Biol. 15:166 [Google Scholar]
  44. El-Soda M, Kruijer W, Malosetti M, Koornneef M, Aarts MGM. 2015. Quantitative trait loci and candidate genes underlying genotype by environment interaction in the response of Arabidopsis thaliana to drought. Plant Cell Environ. 38:585–99 [Google Scholar]
  45. Fuller DQ. 2007. Contrasting patterns in crop domestication and domestication rates: recent archaeobotanical insights from the Old World. Ann. Bot. 100:903–24 [Google Scholar]
  46. Fusi N, Stegle O, Lawrence ND. 2012. Joint modelling of confounding factors and prominent genetic regulators provides increased accuracy in genetical genomics studies. PLOS Comput. Biol. 8:e1002330 [Google Scholar]
  47. Gawenda I, Thorwarth P, Gunther T, Ordon F, Schmid KJ. 2015. Genome-wide association studies in elite varieties of German winter barley using single-marker and haplotype-based methods. Plant Breed. 134:28–39 [Google Scholar]
  48. Giaever G, Chu AM, Ni L, Connelly C, Riles L. et al. 2002. Functional profiling of the Saccharomyces cerevisiae genome. Nature 418:387–91 [Google Scholar]
  49. Gifford ML, Banta JA, Katari MS, Hulsmans J, Chen L. et al. 2013. Plasticity regulators modulate specific root traits in discrete nitrogen environments. PLOS Genet. 9:e1003760 [Google Scholar]
  50. Graham NS, Hammond JP, Lysenko A, Mayes S, Lochlainn O. et al. 2014. Genetical and comparative genomics of Brassica under altered Ca supply identifies Arabidopsis Ca-transporter orthologs. Plant Cell 26:2818–30 [Google Scholar]
  51. Gregis V, Andres F, Sessa A, Guerra RF, Simonini S. et al. 2013. Identification of pathways directly regulated by SHORT VEGETATIVE PHASE during vegetative and reproductive development in Arabidopsis. Genome Biol. 14:R56 [Google Scholar]
  52. Grieneisen VA, Xu J, Maree AF, Hogeweg P, Scheres B. 2007. Auxin transport is sufficient to generate a maximum and gradient guiding root growth. Nature 449:1008–13 [Google Scholar]
  53. Gudmundsson J, Sulem P, Gudbjartsson DF, Masson G, Agnarsson BA. et al. 2012. A study based on whole-genome sequencing yields a rare variant at 8q24 associated with prostate cancer. Nat. Genet. 44:1326–29 [Google Scholar]
  54. Hancock AM, Brachi B, Faure N, Horton MW, Jarymowycz LB. et al. 2011. Adaptation to climate across the Arabidopsis thaliana genome. Science 334:83–86 [Google Scholar]
  55. Hao ZF, Li XH, Xie CX, Weng JF, Li MS. et al. 2011. Identification of functional genetic variations underlying drought tolerance in maize using SNP markers. J. Integr. Plant Biol. 53:641–52 [Google Scholar]
  56. Higgins RH, Thurber CS, Assaranurak I, Brown PJ. 2014. Multiparental mapping of plant height and flowering time QTL in partially isogenic sorghum families. G3 Genes Genom. Genet. 4:1593–602 [Google Scholar]
  57. Himanen K, Vuylsteke M, Vanneste S, Vercruysse S, Boucheron E. et al. 2004. Transcript profiling of early lateral root initiation. PNAS 101:5146–51 [Google Scholar]
  58. Hirsch CN, Foerster JM, Johnson JM, Sekhon RS, Muttoni G. et al. 2014. Insights into the maize pan-genome and pan-transcriptome. Plant Cell 26:121–35 [Google Scholar]
  59. Holloway B, Luck S, Beatty M, Rafalski JA, Li B. 2011. Genome-wide expression quantitative trait loci (eQTL) analysis in maize. BMC Genom. 12:336 [Google Scholar]
  60. Horton MW, Hancock AM, Huang YS, Toomajian C, Atwell S. et al. 2012. Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel. Nat. Genet. 44:212–16 [Google Scholar]
  61. Huang W, Perez-Garcia P, Pokhilko A, Millar AJ, Antoshechkin I. et al. 2012a. Mapping the core of the Arabidopsis circadian clock defines the network structure of the oscillator. Science 336:75–79 [Google Scholar]
  62. Huang W, Richards S, Carbone MA, Zhu D, Anholt RRH. et al. 2012b. Epistasis dominates the genetic architecture of Drosophila quantitative traits. PNAS 109:15553–59 [Google Scholar]
  63. Huang XH, Zhao Y, Wei XH, Li CY, Wang A. et al. 2012. Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm. Nat. Genet. 44:32–39 [Google Scholar]
  64. Hung HY, Shannon LM, Tian F, Bradbury PJ, Chen C. et al. 2012. ZmCCT and the genetic basis of day-length adaptation underlying the postdomestication spread of maize. PNAS 109:E1913–21 [Google Scholar]
  65. Immink RG, Pose D, Ferrario S, Ott F, Kaufmann K. et al. 2012. Characterization of SOC1's central role in flowering by the identification of its upstream and downstream regulators. Plant Physiol. 160:433–49 [Google Scholar]
  66. Iyer-Pascuzzi AS, Jackson T, Cui H, Petricka JJ, Busch W. et al. 2011. Cell identity regulators link development and stress responses in the Arabidopsis root. Dev. Cell 21:770–82 [Google Scholar]
  67. Jaeger KE, Pullen N, Lamzin S, Morris RJ, Wigge PA. 2013. Interlocking feedback loops govern the dynamic behavior of the floral transition in Arabidopsis. Plant Cell 25:820–33 [Google Scholar]
  68. Jansen RC, Nap JP. 2001. Genetical genomics: the added value from segregation. Trends Genet. 17:388–91 [Google Scholar]
  69. Jimenez-Gomez JM, Corwin JA, Joseph B, Maloof JN, Kliebenstein DJ. 2011. Genomic analysis of QTLs and genes altering natural variation in stochastic noise. PLOS Genet. 7:e1002295 [Google Scholar]
  70. Jimenez-Gomez JM, Wallace AD, Maloof JN. 2010. Network analysis identifies ELF3 as a QTL for the shade avoidance response in Arabidopsis. PLOS Genet. 6:e1001100 [Google Scholar]
  71. 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 290:344–47 [Google Scholar]
  72. Kabelitz T, Kappel C, Henneberger K, Benke E, Noh C, Baurle I. 2014. eQTL mapping of transposon silencing reveals a position-dependent stable escape from epigenetic silencing and transposition of AtMu1 in the Arabidopsis lineage. Plant Cell 26:3261–71 [Google Scholar]
  73. Keurentjes JJ, Fu J, de Vos CH, Lommen A, Hall RD. et al. 2006. The genetics of plant metabolism. Nat. Genet. 38:842–49 [Google Scholar]
  74. Keurentjes JJ, Fu J, Terpstra IR, Garcia JM, van den Ackerveken G. et al. 2007. Regulatory network construction in Arabidopsis by using genome-wide gene expression quantitative trait loci. PNAS 104:1708–13 [Google Scholar]
  75. Keurentjes JJ, Sulpice R, Gibon Y, Steinhauser MC, Fu J. et al. 2008. Integrative analyses of genetic variation in enzyme activities of primary carbohydrate metabolism reveal distinct modes of regulation in Arabidopsis thaliana. Genome Biol. 9:R129 [Google Scholar]
  76. Kirst M, Myburg AA, De Leon JP, Kirst ME, Scott J, Sederoff R. 2004. Coordinated genetic regulation of growth and lignin revealed by quantitative trait locus analysis of cDNA microarray data in an interspecific backcross of eucalyptus. Plant Physiol. 135:2368–78 [Google Scholar]
  77. Kliebenstein DJ, West MA, van Leeuwen H, Loudet O, Doerge RW, St. Clair DA. 2006. Identification of QTLs controlling gene expression networks defined a priori. BMC Bioinform. 7:308 [Google Scholar]
  78. Kloosterman B, Anithakumari AM, Chibon PY, Oortwijn M, van der Linden GC. et al. 2012. Organ specificity and transcriptional control of metabolic routes revealed by expression QTL profiling of source–sink tissues in a segregating potato population. BMC Plant Biol. 12:17 [Google Scholar]
  79. Krouk G, Mirowski P, LeCun Y, Shasha DE, Coruzzi GM. 2010. Predictive network modeling of the high-resolution dynamic plant transcriptome in response to nitrate. Genome Biol. 11:R123 [Google Scholar]
  80. Lachowiec J, Shen X, Queitsch C, Carlborg O. 2015. A genome-wide association analysis reveals epistatic cancellation of additive genetic variance for root length in Arabidopsis thaliana. PLOS Genet 11:e1005541 [Google Scholar]
  81. Laibach F. 1951. Über sommer- und winterannuelle Rassen von Arabidopsis thaliana (L.) Heynh. Ein Beitrag zur Ätiologie der Blütenbildung. Beiträge Biol. Pflanz. 28:173–210 [Google Scholar]
  82. Laskowski M, Grieneisen VA, Hofhuis H, Hove CA, Hogeweg P. et al. 2008. Root system architecture from coupling cell shape to auxin transport. PLOS Biol. 6:e307 [Google Scholar]
  83. Lavenus J, Goh T, Guyomarc'h S, Hill K, Lucas M. et al. 2015. Inference of the Arabidopsis lateral root gene regulatory network suggests a bifurcation mechanism that defines primordia flanking and central zones. Plant Cell 27:1368–88 [Google Scholar]
  84. Leal Valentim F, Mourik S, Pose D, Kim MC, Schmid M. et al. 2015. A quantitative and dynamic model of the Arabidopsis flowering time gene regulatory network. PLOS ONE 10:e0116973 [Google Scholar]
  85. Lee I, Ambaru B, Thakkar P, Marcotte EM, Rhee SY. 2010. Rational association of genes with traits using a genome-scale gene network for Arabidopsis thaliana. Nat. Biotechnol. 28:149–56 [Google Scholar]
  86. Lee J-Y, Colinas J, Wang JY, Mace D, Ohler U, Benfey PN. 2006. Transcriptional and posttranscriptional regulation of transcription factor expression in Arabidopsis roots. PNAS 103:6055–60 [Google Scholar]
  87. Lex J, Ahlemeyer J, Friedt W, Ordon F. 2014. Genome-wide association studies of agronomic and quality traits in a set of German winter barley (Hordeum vulgare L.) cultivars using Diversity Arrays Technology (DArT). J. Appl. Genet. 55:295–305 [Google Scholar]
  88. Li Y, Cheng RY, Spokas KA, Palmer AA, Borevitz JO. 2014. Genetic variation for life history sensitivity to seasonal warming in Arabidopsis thaliana. Genetics 196:569–77 [Google Scholar]
  89. Li Y, Huang Y, Bergelson J, Nordborg M, Borevitz JO. 2010. Association mapping of local climate-sensitive quantitative trait loci in Arabidopsis thaliana. PNAS 107:21199–204 [Google Scholar]
  90. Lin D-Y, Zeng D, Tang Z-Z. 2013. Quantitative trait analysis in sequencing studies under trait-dependent sampling. PNAS 110:12247–52 [Google Scholar]
  91. Liu J, Mehdi S, Topping J, Tarkowski P, Lindsey K. 2010. Modelling and experimental analysis of hormonal crosstalk in Arabidopsis. Mol. Syst. Biol. 6:373 [Google Scholar]
  92. Long TA, Tsukagoshi H, Busch W, Lahner B, Salt DE, Benfey PN. 2010. The bHLH transcription factor POPEYE regulates response to iron deficiency in Arabidopsis roots. Plant Cell 22:72219–36 [Google Scholar]
  93. Lorenz AJ, Hamblin MT, Jannink JL. 2010. Performance of single nucleotide polymorphisms versus haplotypes for genome-wide association analysis in barley. PLOS ONE 5:e14079 [Google Scholar]
  94. Lowry DB, Logan TL, Santuari L, Hardtke CS, Richards JH. et al. 2013. Expression quantitative trait locus mapping across water availability environments reveals contrasting associations with genomic features in Arabidopsis. Plant Cell 25:3266–79 [Google Scholar]
  95. Mackay TF, Stone EA, Ayroles JF. 2009. The genetics of quantitative traits: challenges and prospects. Nat. Rev. Genet. 10:565–77 [Google Scholar]
  96. Madsen BE, Browning SR. 2009. A groupwise association test for rare mutations using a weighted sum statistic. PLOS Genet. 5:e1000384 [Google Scholar]
  97. Mähönen AP, ten Tusscher K, Siligato R, Smetana O, Diaz-Trivino S. et al. 2014. PLETHORA gradient formation mechanism separates auxin responses. Nature 515:125–29 [Google Scholar]
  98. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA. et al. 2009. Finding the missing heritability of complex diseases. Nature 461:747–53 [Google Scholar]
  99. Manzano C, Pallero-Baena M, Casimiro I, De Rybel B, Orman-Ligeza B. et al. 2014. The emerging role of reactive oxygen species signaling during lateral root development. Plant Physiol. 165:1105–19 [Google Scholar]
  100. Markowetz F, Boutros M. 2015. Systems Genetics: Linking Genotypes and Phenotypes Cambridge, UK: Cambridge Univ. Press
  101. Mateos JL, Madrigal P, Tsuda K, Rawat V, Richter R. et al. 2015. Combinatorial activities of SHORT VEGETATIVE PHASE and FLOWERING LOCUS C define distinct modes of flowering regulation in Arabidopsis. Genome Biol. 16:31 [Google Scholar]
  102. Mathieu J, Yant LJ, Murdter F, Kuttner F, Schmid M. 2009. Repression of flowering by the miR172 target SMZ. PLOS Biol. 7:e1000148 [Google Scholar]
  103. Maurer A, Draba V, Jiang Y, Schnaithmann F, Sharma R. et al. 2015. Modelling the genetic architecture of flowering time control in barley through nested association mapping. BMC Genom. 16:290 [Google Scholar]
  104. Meijon M, Satbhai SB, Tsuchimatsu T, Busch W. 2014. Genome-wide association study using cellular traits identifies a new regulator of root development in Arabidopsis. Nat. Genet. 46:77–81 [Google Scholar]
  105. Mendel G. 1865. Versuche über Pflanzenhybriden. Verh. Nat. Ver. Brünn 4:3–47 [Google Scholar]
  106. Moreno-Risueno MA, Sozzani R, Yardimci GG, Petricka JJ, Vernoux T. et al. 2015. Transcriptional control of tissue formation throughout root development. Science 350:426–30 [Google Scholar]
  107. Moussaieff A, Rogachev I, Brodsky L, Malitsky S, Toal TW. et al. 2013. High-resolution metabolic mapping of cell types in plant roots. PNAS 110:E1232–41 [Google Scholar]
  108. Moyroud E, Minguet EG, Ott F, Yant L, Pose D. et al. 2011. Prediction of regulatory interactions from genome sequences using a biophysical model for the Arabidopsis LEAFY transcription factor. Plant Cell 23:1293–306 [Google Scholar]
  109. Munoz-Amatriain M, Cuesta-Marcos A, Endelman JB, Comadran J, Bonman JM. et al. 2014. The USDA Barley Core Collection: genetic diversity, population structure, and potential for genome-wide association studies. PLOS ONE 9:e94688 [Google Scholar]
  110. Myles S, Peiffer J, Brown PJ, Ersoz ES, Zhang ZW. et al. 2009. Association mapping: Critical considerations shift from genotyping to experimental design. Plant Cell 21:2194–202 [Google Scholar]
  111. Nadeau JH, Dudley AM. 2011. Systems genetics. Science 331:1015–16 [Google Scholar]
  112. O'Malley RC, Huang S-SC, Song L, Lewsey MG, Bartlett A. et al. 2016. Cistrome and epicistrome features shape the regulatory DNA landscape. Cell 165:1280–92 [Google Scholar]
  113. Obayashi T, Hayashi S, Saeki M, Ohta H, Kinoshita K. 2009. ATTED-II provides coexpressed gene networks for Arabidopsis. Nucleic Acids Res. 37:D987–91 [Google Scholar]
  114. Ogura T, Busch W. 2015. From phenotypes to causal sequences: using genome wide association studies to dissect the sequence basis for variation of plant development. Curr. Opin. Plant Biol. 23:98–108 [Google Scholar]
  115. Para A, Li Y, Marshall-Colon A, Varala K, Francoeur NJ. et al. 2014. Hit-and-run transcriptional control by bZIP1 mediates rapid nutrient signaling in Arabidopsis. PNAS 111:10371–76 [Google Scholar]
  116. Pasam RK, Sharma R, Malosetti M, van Eeuwijk FA, Haseneyer G. et al. 2012. Genome-wide association studies for agronomical traits in a world wide spring barley collection. BMC Plant Biol. 12:16 [Google Scholar]
  117. Péret B, Li G, Zhao J, Band LR, Voss U. et al. 2012. Auxin regulates aquaporin function to facilitate lateral root emergence. Nat. Cell Biol. 14:991–98 [Google Scholar]
  118. Péret B, Middleton AM, French AP, Larrieu A, Bishopp A. et al. 2013. Sequential induction of auxin efflux and influx carriers regulates lateral root emergence. Mol. Syst. Biol. 9:699 [Google Scholar]
  119. Perez-Perez JM, Serrano-Cartagena J, Micol JL. 2002. Genetic analysis of natural variations in the architecture of Arabidopsis thaliana vegetative leaves. Genetics 162:893–915 [Google Scholar]
  120. Petricka JJ, Schauer MA, Megraw M, Breakfield NW, Thompson JW. et al. 2012. The protein expression landscape of the Arabidopsis root. PNAS 109:6811–18 [Google Scholar]
  121. Phung NTP, Mai CD, Mournet P, Frouin J, Droc G. et al. 2014. Characterization of a panel of Vietnamese rice varieties using DArT and SNP markers for association mapping purposes. BMC Plant Biol. 14:371 [Google Scholar]
  122. Pino Del Carpio D, Basnet RK, Arends D, Lin K, De Vos RC. et al. 2014. Regulatory network of secondary metabolism in Brassica rapa: insight into the glucosinolate pathway. PLOS ONE 9:e107123 [Google Scholar]
  123. Porth I, White R, Jaquish B, Alfaro R, Ritland C, Ritland K. 2012. Genetical genomics identifies the genetic architecture for growth and weevil resistance in spruce. PLOS ONE 7:e44397 [Google Scholar]
  124. Pose D, Verhage L, Ott F, Yant L, Mathieu J. et al. 2013. Temperature-dependent regulation of flowering by antagonistic FLM variants. Nature 503:414–17 [Google Scholar]
  125. Potokina E, Druka A, Luo Z, Wise R, Waugh R, Kearsey M. 2008. Gene expression quantitative trait locus analysis of 16,000 barley genes reveals a complex pattern of genome-wide transcriptional regulation. Plant J. 53:90–101 [Google Scholar]
  126. Putterill J, Robson F, Lee K, Simon R, Coupland G. 1995. The CONSTANS gene of Arabidopsis promotes flowering and encodes a protein showing similarities to zinc-finger transcription factors. Cell 80:847–57 [Google Scholar]
  127. Raman H, Raman R, Coombes N, Song J, Prangnell R. et al. 2016. Genome-wide association analyses reveal complex genetic architecture underlying natural variation for flowering time in canola. Plant Cell Environ. 391228–39
  128. Rincent R, Nicolas S, Bouchet S, Altmann T, Brunel D. et al. 2014. Dent and Flint maize diversity panels reveal important genetic potential for increasing biomass production. Theor. Appl. Genet. 127:2313–31 [Google Scholar]
  129. Rode J, Ahlemeyer J, Friedt W, Ordon F. 2012. Identification of marker-trait associations in the German winter barley breeding gene pool (Hordeum vulgare L.). Mol. Breed. 30:831–43 [Google Scholar]
  130. Romay MC, Millard MJ, Glaubitz JC, Peiffer JA, Swarts KL. et al. 2013. Comprehensive genotyping of the USA national maize inbred seed bank. Genome Biol. 14:R55 [Google Scholar]
  131. Rosas U, Cibrian-Jaramillo A, Ristova D, Banta JA, Gifford ML. et al. 2013. Integration of responses within and across Arabidopsis natural accessions uncovers loci controlling root systems architecture. PNAS 110:15133–38 [Google Scholar]
  132. Rowan BA, Weigel D, Koenig D. 2011. Developmental genetics and new sequencing technologies: the rise of nonmodel organisms. Dev. Cell 21:65–76 [Google Scholar]
  133. Salazar JD, Saithong T, Brown PE, Foreman J, Locke JC. et al. 2009. Prediction of photoperiodic regulators from quantitative gene circuit models. Cell 139:1170–79 [Google Scholar]
  134. Sasaki E, Zhang P, Atwell S, Meng D, Nordborg M. 2015. “Missing” G×E variation controls flowering time in Arabidopsis thaliana. PLOS Genet. 11:e1005597 [Google Scholar]
  135. Schauer N, Semel Y, Roessner U, Gur A, Balbo I. et al. 2006. Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement. Nat. Biotechnol. 24:447–54 [Google Scholar]
  136. Schiessl S, Iniguez-Luy F, Qian W, Snowdon RJ. 2015. Diverse regulatory factors associate with flowering time and yield responses in winter-type Brassica napus. BMC Genom. 16:737 [Google Scholar]
  137. Schiml S, Puchta H. 2016. Revolutionizing plant biology: multiple ways of genome engineering by CRISPR/Cas. Plant Methods 12:1–9 [Google Scholar]
  138. Schmid M, Uhlenhaut NH, Godard F, Demar M, Bressan R. et al. 2003. Dissection of floral induction pathways using global expression analysis. Development 130:6001–12 [Google Scholar]
  139. Slovak R, Göschl C, Su X, Shimotani K, Shiina T, Busch W. 2014. A scalable open-source pipeline for large-scale root phenotyping of Arabidopsis. Plant Cell 262390–403
  140. Snoek LB, Terpstra IR, Dekter R, Van den Ackerveken G, Peeters AJ. 2012. Genetical genomics reveals large scale genotype-by-environment interactions in Arabidopsis thaliana. Front. Genet. 3:317 [Google Scholar]
  141. Sozzani R, Busch W, Spalding EP, Benfey PN. 2014. Advanced imaging techniques for the study of plant growth and development. Trends Plant Sci. 19:304–10 [Google Scholar]
  142. Sozzani R, Cui H, Moreno-Risueno MA, Busch W, Van Norman JM. et al. 2010. Spatiotemporal regulation of cell-cycle genes by SHORTROOT links patterning and growth. Nature 466:128–32 [Google Scholar]
  143. Sprink T, Metje J, Hartung F. 2015. Plant genome editing by novel tools: TALEN and other sequence specific nucleases. Curr. Opin. Biotechnol. 32:47–53 [Google Scholar]
  144. Stetter MG, Schmid K, Ludewig U. 2015. Uncovering genes and ploidy involved in the high diversity in root hair density, length and response to local scarce phosphate in Arabidopsis thaliana. PLOS ONE 10:e0120604 [Google Scholar]
  145. Sullivan AM, Arsovski AA, Lempe J, Bubb KL, Weirauch MT. et al. 2014. Mapping and dynamics of regulatory DNA and transcription factor networks in A. thaliana. Cell Rep. 8:2015–30 [Google Scholar]
  146. Tao Z, Shen L, Liu C, Liu L, Yan Y, Yu H. 2012. Genome-wide identification of SOC1 and SVP targets during the floral transition in Arabidopsis. Plant J. 70:549–61 [Google Scholar]
  147. Taylor-Teeples M, Lin L, de Lucas M, Turco G, Toal TW. et al. 2015. An Arabidopsis gene regulatory network for secondary cell wall synthesis. Nature 517:571–75 [Google Scholar]
  148. Terpstra IR, Snoek LB, Keurentjes JJ, Peeters AJ, van den Ackerveken G. 2010. Regulatory network identification by genetical genomics: signaling downstream of the Arabidopsis receptor-like kinase ERECTA. Plant Physiol. 154:1067–78 [Google Scholar]
  149. Thirunavukkarasu N, Hossain F, Arora K, Sharma R, Shiriga K. et al. 2014. Functional mechanisms of drought tolerance in subtropical maize (Zea mays L.) identified using genome-wide association mapping. BMC Genom. 15:1182 [Google Scholar]
  150. Torti S, Fornara F, Vincent C, Andres F, Nordstrom K. et al. 2012. Analysis of the Arabidopsis shoot meristem transcriptome during floral transition identifies distinct regulatory patterns and a leucine-rich repeat protein that promotes flowering. Plant Cell 24:444–62 [Google Scholar]
  151. Tsukagoshi H, Busch W, Benfey PN. 2010. Transcriptional regulation of ROS controls transition from proliferation to differentiation in the root. Cell 143:606–16 [Google Scholar]
  152. Van Inghelandt D, Melchinger AE, Martinant JP, Stich B. 2012. Genome-wide association mapping of flowering time and northern corn leaf blight (Setosphaeria turcica) resistance in a vast commercial maize germplasm set. BMC Plant Biol. 12:56 [Google Scholar]
  153. Voss U, Wilson MH, Kenobi K, Gould PD, Robertson FC. et al. 2015. The circadian clock rephases during lateral root organ initiation in Arabidopsis thaliana. Nat. Commun. 6:7641 [Google Scholar]
  154. Wang HY, Smith KP, Combs E, Blake T, Horsley RD, Muehlbauer GJ. 2012. Effect of population size and unbalanced data sets on QTL detection using genome-wide association mapping in barley breeding germplasm. Theor. Appl. Genet. 124:111–24 [Google Scholar]
  155. Wang MH, Jiang N, Jia TY, Leach L, Cockram J. et al. 2012. Genome-wide association mapping of agronomic and morphologic traits in highly structured populations of barley cultivars. Theor. Appl. Genet. 124:233–46 [Google Scholar]
  156. Weirauch MT, Yang A, Albu M, Cote AG, Montenegro-Montero A. et al. 2014. Determination and inference of eukaryotic transcription factor sequence specificity. Cell 158:1431–43 [Google Scholar]
  157. Wen Z, Boyse JF, Song Q, Cregan PB, Wang D. 2015. Genomic consequences of selection and genome-wide association mapping in soybean. BMC Genom. 16:671 [Google Scholar]
  158. West MA, Kim K, Kliebenstein DJ, van Leeuwen H, Michelmore RW. et al. 2007. Global eQTL mapping reveals the complex genetic architecture of transcript-level variation in Arabidopsis. Genetics 175:1441–50 [Google Scholar]
  159. Xiao D, Wang H, Basnet RK, Zhao J, Lin K. et al. 2014. Genetic dissection of leaf development in Brassica rapa using a genetical genomics approach. Plant Physiol. 164:1309–25 [Google Scholar]
  160. Xiao D, Zhao JJ, Hou XL, Basnet RK, Carpio DP. et al. 2013. The Brassica rapa FLC homologue FLC2 is a key regulator of flowering time, identified through transcriptional co-expression networks. J. Exp. Bot. 64:4503–16 [Google Scholar]
  161. Xu X, Bai G. 2015. Whole-genome resequencing: changing the paradigms of SNP detection, molecular mapping and gene discovery. Mol. Breed. 35:33 [Google Scholar]
  162. Xue YD, Warburton ML, Sawkins M, Zhang XH, Setter T. et al. 2013. Genome-wide association analysis for nine agronomic traits in maize under well-watered and water-stressed conditions. Theor. Appl. Genet. 126:2587–96 [Google Scholar]
  163. Yang N, Lu Y, Yang X, Huang J, Zhou Y. et al. 2014. Genome wide association studies using a new nonparametric model reveal the genetic architecture of 17 agronomic traits in an enlarged maize association panel. PLOS Genet. 10:e1004573 [Google Scholar]
  164. Yang Q, Li Z, Li WQ, Ku LX, Wang C. et al. 2013. CACTA-like transposable element in ZmCCT attenuated photoperiod sensitivity and accelerated the postdomestication spread of maize. PNAS 110:16969–74 [Google Scholar]
  165. Yant L, Mathieu J, Dinh TT, Ott F, Lanz C. et al. 2010. Orchestration of the floral transition and floral development in Arabidopsis by the bifunctional transcription factor APETALA2. Plant Cell 22:2156–70 [Google Scholar]
  166. Zhang JP, Song QJ, Cregan PB, Nelson RL, Wang XZ. et al. 2015. Genome-wide association study for flowering time, maturity dates and plant height in early maturing soybean (Glycine max) germplasm. BMC Genom. 16:217 [Google Scholar]
  167. Zhang X, Cal AJ, Borevitz JO. 2011. Genetic architecture of regulatory variation in Arabidopsis thaliana. Genome Res. 21:725–33 [Google Scholar]
  168. Zhao K, Tung CW, Eizenga GC, Wright MH, Ali ML. et al. 2011. Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nat. Commun. 2:467 [Google Scholar]
  169. Zhou L, Wang SB, Jian J, Geng QC, Wen J. et al. 2015. Identification of domestication-related loci associated with flowering time and seed size in soybean with the RAD-seq genotyping method. Sci. Rep. 5:9350 [Google Scholar]
  170. Zhu B, Zhang W, Zhang T, Liu B, Jiang J. 2015. Genome-wide prediction and validation of intergenic enhancers in Arabidopsis using open chromatin signatures. Plant Cell 27:2415–26 [Google Scholar]
  171. Zhu C, Gore M, Buckler ES, Yu J. 2008. Status and prospects of association mapping in plants. Plant Genome 1:5–20 [Google Scholar]
  172. Zuk O, Hechter E, Sunyaev SR, Lander ES. 2012. The mystery of missing heritability: Genetic interactions create phantom heritability. PNAS 109:1193–98 [Google Scholar]

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error