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Root system architecture: opportunities and constraints for genetic improvement of crops

de Dorlodot, Sophie, Forster, Brian, Pagès, Loïc, Price, Adam, Tuberosa, Roberto, Draye, Xavier·2007·Trends in Plant Science

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  1. Lynch, 1995, Root architecture and plant productivity, Plant Physiol., 109, 7, 10.1104/pp.109.1.7 · DOI · Paper page
  2. Chloupek, 2006, The effect of semi-dwarf genes on root system size in field-grown barley, Theor. Appl. Genet., 112, 779, 10.1007/s00122-005-0147-4 · DOI
  3. Beebe, 2006, Quantitative trait loci for root architecture traits correlated with phosphorus acquisition in common bean, Crop Sci., 46, 413, 10.2135/cropsci2005.0226 · DOI
  4. Yue, 2006, Genetic basis of drought resistance at reproductive stage in rice: Separation of drought tolerance from drought avoidance, Genetics, 172, 1213, 10.1534/genetics.105.045062 · DOI · Paper page
  5. Kato, 2006, Genotypic variation in root growth angle in rice (Oryza sativa L.) and its association with deep root development in upland fields with different water regimes, Plant Soil, 287, 117, 10.1007/s11104-006-9008-4 · DOI
  6. Sanguineti, 2006, Effects of long-term selection on seedling traits and ABA accumulation in commercial maize hybrids, Maydica, 51, 329
  7. Tuberosa, 2002, Identification of QTLs for root characteristics in maize grown in hydroponics and analysis of their overlap with QTLs for grain yield in the field at two water regimes, Plant Mol. Biol., 48, 697, 10.1023/A:1014897607670 · DOI · Paper page
  8. Steele, 2007, Field evaluation of upland rice lines selected for QTLs controlling root traits, Field Crops Res., 101, 180, 10.1016/j.fcr.2006.11.002 · DOI
  9. Johnson, 2000, Lettuce, a shallow-rooted crop, and Lactuca serriola, its wild progenitor, differ at QTL determining root architecture and deep soil water exploitation, Theor. Appl. Genet., 101, 1066, 10.1007/s001220051581 · DOI
  10. Price, 1997, Genetic dissection of root growth in rice (Oryza sativa L). 2. mapping quantitative trait loci using molecular markers, Theor. Appl. Genet., 95, 143, 10.1007/s001220050542 · DOI
  11. Price, 2002, Linking drought-resistance mechanisms to drought avoidance in upland rice using a QTL approach: progress and new opportunities to integrate stomatal and mesophyll responses, J. Exp. Bot., 53, 989, 10.1093/jexbot/53.371.989 · DOI · Paper page
  12. Giuliani, 2005, Root-ABA1, a major constitutive QTL, affects maize root architecture and leaf ABA concentration at different water regimes, J. Exp. Bot., 56, 3061, 10.1093/jxb/eri303 · DOI · Paper page
  13. Rauh, 2002, Quantitative trait loci analysis of growth response to varying nitrogen sources in Arabidopsis thaliana, Theor. Appl. Genet., 104, 743, 10.1007/s00122-001-0815-y · DOI
  14. Magalhaes, 2004, Comparative mapping of a major aluminum tolerance gene in sorghum and other species in the Poaceae, Genetics, 167, 1905, 10.1534/genetics.103.023580 · doi:10.1534/genetics.103.023580
  15. Dasgupta, 2004, An arsenate tolerance gene on chromosome 6 of rice, New Phytol., 163, 45, 10.1111/j.1469-8137.2004.01109.x · doi:10.1111/j.1469-8137.2004.01109.x
  16. Wissuwa, 2002, Substitution mapping of Pup1: a major QTL increasing phosphorus uptake of rice from a phosphorus-deficient soil, Theor. Appl. Genet., 105, 890, 10.1007/s00122-002-1051-9 · DOI · Paper page
  17. Ochoa, 2006, QTL analysis of adventitious root formation in common bean under contrasting phosphorus availability, Crop Sci., 46, 1609, 10.2135/cropsci2005.12-0446 · DOI
  18. Reymond, 2006, Identification of QTL controlling root growth response to phosphate starvation in Arabidopsis thaliana, Plant Cell Environ., 29, 115, 10.1111/j.1365-3040.2005.01405.x · DOI
  19. Macmillan, 2006, Assessing the importance of genotype×environment interaction for root traits in rice using a mapping population II: conventional QTL analysis, Theor. Appl. Genet., 113, 953, 10.1007/s00122-006-0357-4 · DOI
  20. Kamoshita, 2002, Effects of phenotyping environment on identification of quantitative trait loci for rice root morphology under anaerobic conditions, Crop Sci., 42, 255, 10.2135/cropsci2002.0255 · doi:10.2135/cropsci2002.0255
  21. Horii, 2005, Quantitative trait loci for adventitious and lateral roots in rice, Plant Breed., 125, 198, 10.1111/j.1439-0523.2006.01124.x · DOI
  22. Shen, 2001, Evaluation of near-isogenic lines of rice introgressed with QTLs for root depth through marker-aided selection, Theor. Appl. Genet., 103, 75, 10.1007/s001220100538 · DOI · Paper page
  23. Landi, 2005, Validation and characterization of a major QTL affecting leaf ABA concentration in maize, Mol. Breed., 15, 291, 10.1007/s11032-004-7604-7 · DOI
  24. Darvasi, 1997, A simple method to calculate resolving power and confidence interval of QTL map location, Behav. Genet., 27, 125, 10.1023/A:1025685324830 · doi:10.1023/a:1025685324830
  25. Goffinet, 2000, Quantitative trait loci: A meta-analysis, Genetics, 155, 463, 10.1093/genetics/155.1.463 · DOI · Paper page
  26. Veyrieras, 2007, MetaQTL: a package of new computational methods for the meta-analysis of QTL mapping experiments, BMC Bioinformatics, 8, 49, 10.1186/1471-2105-8-49 · DOI · Paper page
  27. Tuberosa, 2003, Searching for quantitative trait loci controlling root traits in maize: a critical appraisal, Plant Soil, 255, 35, 10.1023/A:1026146615248 · DOI
  28. Price, 2006, Believe it or not, QTLs are accurate!, Trends Plant Sci., 11, 213, 10.1016/j.tplants.2006.03.006 · DOI · Paper page
  29. Yano, 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, 10.1105/tpc.12.12.2473 · DOI · Paper page
  30. Salvi, 2005, To clone or not to clone plant QTLs: present and future challenges, Trends Plant Sci., 10, 297, 10.1016/j.tplants.2005.04.008 · DOI · Paper page
  31. Sergeeva, 2006, Vacuolar invertase regulates elongation of Arabidopsis thaliana roots as revealed by QTL and mutant analysis, Proc. Natl. Acad. Sci. U. S. A., 103, 2994, 10.1073/pnas.0511015103 · DOI · Paper page
  32. Tuberosa, 1998, RFLP mapping of quantitative trait loci controlling abscisic acid concentration in leaves of drought-stressed maize (Zea mays L.), Theor. Appl. Genet., 97, 744, 10.1007/s001220050951 · DOI
  33. Landi, 2007, Root-ABA1 QTL affects root lodging, grain yield and other agronomic traits in maize grown under well-watered and water-stressed conditions, J. Exp. Bot., 58, 319, 10.1093/jxb/erl161 · DOI
  34. Osterberg, 2002, Naturally occurring indel variation in the Brassica nigra COL1 gene is associated with variation in flowering time, Genetics, 161, 299, 10.1093/genetics/161.1.299 · DOI
  35. Chardon, 2004, Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome, Genetics, 168, 2169, 10.1534/genetics.104.032375 · DOI · Paper page
  36. Harhay, 2003, Positional candidate gene selection from livestock EST databases using Gene Ontology, Bioinformatics, 19, 249, 10.1093/bioinformatics/19.2.249 · doi:10.1093/bioinformatics/19.2.249
  37. Casson, 2003, Genes and signalling in root development, New Phytol., 158, 11, 10.1046/j.1469-8137.2003.00705.x · DOI · Paper page
  38. Salvi, 2007, Conserved noncoding genomic sequences associated with a flowering-time quantitative trait locus in maize, Proc. Natl. Acad. Sci. U. S. A., 104, 11376, 10.1073/pnas.0704145104 · DOI · Paper page
  39. Willemsen, 2004, Mechanisms of pattern formation in plant embryogenesis, Annu. Rev. Genet., 38, 587, 10.1146/annurev.genet.38.072902.092231 · DOI
  40. Swarup, 2005, Root gravitropism requires lateral root cap and epidermal cells for transport and response to a mobile auxin signal, Nat. Cell Biol., 7, 1057, 10.1038/ncb1316 · DOI · Paper page
  41. Casimiro, 2003, Dissecting Arabidopsis lateral root development, Trends Plant Sci., 8, 165, 10.1016/S1360-1385(03)00051-7 · DOI · Paper page
  42. Zhang, 1998, An Arabidopsis MADS box gene that controls nutrient-induced changes in root architecture, Science, 279, 407, 10.1126/science.279.5349.407 · DOI · Paper page
  43. Lynch, 1997, SimRoot: Modelling and visualization of root systems, Plant Soil, 188, 139, 10.1023/A:1004276724310 · DOI · Paper page
  44. Dunbabin, 2002, Modelling the interactions between water and nutrient uptake and root growth, Plant Soil, 239, 19, 10.1023/A:1014939512104 · DOI
  45. Somma, 1998, Transient three-dimensional modeling of soil water and solute transport with simultaneous root growth, root water and nutrient uptake, Plant Soil, 202, 281, 10.1023/A:1004378602378 · DOI · Paper page
  46. Pages, 2004, Root Typ: a generic model to depict and analyse the root system architecture, Plant Soil, 258, 103, 10.1023/B:PLSO.0000016540.47134.03 · doi:10.1023/b:plso.0000016540.47134.03
  47. Hochholdinger, 2004, From weeds to crops: genetic analysis of root development in cereals, Trends Plant Sci., 9, 42, 10.1016/j.tplants.2003.11.003 · DOI · Paper page
  48. Lecompte, 2001, The relationships between static and dynamic variables in the description of root growth. Consequences for field interpretation of rooting variability, Plant Soil, 236, 19, 10.1023/A:1011924529885 · doi:10.1023/a:1011924529885
  49. Tardieu, 2003, Virtual plants: modelling as a tool for the genomics of tolerance to water deficit, Trends Plant Sci., 8, 9, 10.1016/S1360-1385(02)00008-0 · DOI · Paper page
  50. Reymond, 2004, Dealing with the genotype×environment interaction via a modelling approach: a comparison of QTLs of maize leaf length or width with QTLs of model parameters, J. Exp. Bot., 55, 2461, 10.1093/jxb/erh200 · DOI
  51. Quilot, 2005, Analysing the genetic control of peach fruit quality through an ecophysiological model combined with a QTL approach, J. Exp. Bot., 56, 3083, 10.1093/jxb/eri305 · DOI
  52. Doussan, 1998, Modelling of the hydraulic architecture of root systems: An integrated approach to water absorption - model description, Ann. Bot. (Lond.), 81, 213, 10.1006/anbo.1997.0540 · DOI · Paper page
  53. Thaler, 1998, Modelling the influence of assimilate availability on root growth and architecture, Plant Soil, 201, 307, 10.1023/A:1004380021699 · doi:10.1023/a:1004380021699
  54. Bidel, 2000, MassFlowDyn I: a carbon transport and partitioning model for root system architecture, Ann. Bot. (Lond.), 85, 869, 10.1006/anbo.2000.1149 · doi:10.1006/anbo.2000.1149
  55. Ho, 2004, Optimization modeling of plant root architecture for water and phosphorus acquisition, J. Theor. Biol., 226, 331, 10.1016/j.jtbi.2003.09.011 · DOI
  56. Dunbabin, 2003, Is there an optimal root architecture for nitrate capture in leaching environments?, Plant Cell Environ., 26, 835, 10.1046/j.1365-3040.2003.01015.x · DOI · Paper page
  57. Yadav, 1997, Mapping genes controlling root morphology and root distribution in a doubled-haploid population of rice, Theor. Appl. Genet., 94, 619, 10.1007/s001220050459 · DOI · Paper page
  58. Champoux, 1995, Locating genes associated with root morphology and drought avoidance in rice via linkage to molecular markers, Theor. Appl. Genet., 90, 969, 10.1007/BF00222910 · DOI · Paper page
  59. Kamoshita, 2002, Mapping QTLs for root morphology of a rice population adapted to rainfed lowland conditions, Theor. Appl. Genet., 104, 880, 10.1007/s00122-001-0837-5 · DOI · Paper page
  60. Price, 2002, Upland rice grown in soil-filled chambers and exposed to contrasting water-deficit regimes II. Mapping quantitative trait loci for root morphology and distribution, Field Crops Res., 76, 25, 10.1016/S0378-4290(02)00010-2 · DOI · Paper page
  61. Venuprasad, 2002, Tagging quantitative trait loci associated with grain yield and root morphological traits in rice (Oryza sativa L.) under contrasting moisture regimes, Euphytica, 128, 293, 10.1023/A:1021281428957 · DOI
  62. Courtois, 2003, Locating QTLs controlling constitutive root traits in the rice population IAC 165×Co39, Euphytica, 134, 335, 10.1023/B:EUPH.0000004987.88718.d6 · DOI
  63. Zheng, 2003, Mapping QTLs and candidate genes for rice root traits under different water-supply conditions and comparative analysis across three populations, Theor. Appl. Genet., 107, 1505, 10.1007/s00122-003-1390-1 · DOI
  64. Loudet, 2005, Quantitative trait loci controlling root growth and architecture in Arabidopsis thaliana confirmed by heterogeneous inbred family, Theor. Appl. Genet., 110, 742, 10.1007/s00122-004-1900-9 · DOI
  65. Zhu, 2005, Mapping of QTLs for lateral root branching and length in maize (Zea mays L.) under differential phosphorus supply, Theor. Appl. Genet., 111, 688, 10.1007/s00122-005-2051-3 · DOI · Paper page
  66. Fitz Gerald, 2006, Identification of quantitative trait loci that regulate Arabidopsis root system size and plasticity, Genetics, 172, 485, 10.1534/genetics.105.047555 · DOI
  67. Hund, 2004, QTL controlling root and shoot traits of maize seedlings under cold stress, Theor. Appl. Genet., 109, 618, 10.1007/s00122-004-1665-1 · DOI · Paper page
  68. Huang, 2004, QTLs for nitrate induced elongation and initiation of lateral roots in rice (Oryza sativa L.), Plant Soil, 263, 229, 10.1023/B:PLSO.0000047736.66712.c6 · doi:10.1023/b:plso.0000047736.66712.c6
  69. Draye, 2002, Influence of root growth and vascular structure on the distribution of lateral roots, Plant Cell Environ., 25, 1463, 10.1046/j.0016-8025.2002.00924.x · doi:10.1046/j.0016-8025.2002.00924.x
  70. Dubrovsky, 2006, Lateral root initiation in Arabidopsis: Developmental window, spatial patterning, density and predictability, Ann. Bot. (Lond.), 97, 903, 10.1093/aob/mcj604 · doi:10.1093/aob/mcj604
  71. Bengough, 2004, Gel observation chamber for rapid screening of root traits in cereal seedlings, Plant Soil, 262, 63, 10.1023/B:PLSO.0000037029.82618.27 · DOI
  72. Gregory, 2003, Non-invasive imaging of roots with high resolution X-ray micro-tomography, Plant Soil, 255, 351, 10.1023/A:1026179919689 · DOI
  73. Van As, 2007, Intact plant MRI for the study of cell water relations, membrane permeability, cell-to-cell and long distance water transport, J. Exp. Bot., 58, 743, 10.1093/jxb/erl157 · DOI
  74. Pierret, 2003, Simultaneous X-ray imaging of plant root growth and water uptake in thin-slab systems, Plant Soil, 255, 361, 10.1023/A:1026130532683 · DOI
  75. Garrigues, 2006, Water uptake by plant roots: I - Formation and propagation of a water extraction front in mature root systems as evidenced by 2D light transmission imaging, Plant Soil, 283, 83, 10.1007/s11104-004-7903-0 · doi:10.1007/s11104-004-7903-0
  76. Sharp, 2004, Root growth maintenance during water deficits: physiology to functional genomics, J. Exp. Bot., 55, 2343, 10.1093/jxb/erh276 · DOI · Paper page
  77. Eshed, 1995, An introgression line population of Lycopersicon pennellii in the cultivated tomato enables the identification and fine mapping of yield-associated QTL, Genetics, 141, 1147, 10.1093/genetics/141.3.1147 · DOI · Paper page
  78. Koumproglou, 2002, STAIRS: a new genetic resource for functional genomic studies of Arabidopsis, Plant J., 31, 355, 10.1046/j.1365-313X.2002.01353.x · DOI
  79. Li, 2005, Genome-wide introgression lines and their use in genetic and molecular dissection of complex phenotypes in rice (Oryza sativa L.), Plant Mol. Biol., 59, 33, 10.1007/s11103-005-8519-3 · DOI
  80. Tanksley, 1996, Advanced backcross QTL analysis in a cross between an elite processing line of tomato and its wild relative L. pimpinellifolium, Theor. Appl. Genet., 92, 213, 10.1007/BF00223378 · DOI · Paper page
  81. Mccallum, 2000, Targeting induced local lesions in genomes (TILLING) for plant functional genomics, Plant Physiol., 123, 439, 10.1104/pp.123.2.439 · DOI · Paper page
  82. Peleman, 2003, Breeding by design, Trends Plant Sci., 8, 330, 10.1016/S1360-1385(03)00134-1 · DOI · Paper page
  83. Hinsinger, 2005, Rhizosphere geometry and heterogeneity arising from root-mediated physical and chemical processes, New Phytol., 168, 293, 10.1111/j.1469-8137.2005.01512.x · DOI · Paper page

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Metadata

Authors
de Dorlodot, S., Forster, B., Pagès, L., Price, A., Tuberosa, R., & Draye, X.
Venue
Trends in Plant Science
Publisher
Elsevier BV
Published
2007-10
Volume
12
Issue
10
Pages
474-481
ISSN
1360-1385 (ISSN-L)
OpenAlex
W2051040054
Cited by
739
References
1
FWCI
1.53
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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CoChat. (2026). Citation check: Root system architecture: opportunities and constraints for genetic improvement of crops. https://app.cochat.ai/papers/10.1016/j.tplants.2007.08.012
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de Dorlodot, S., Forster, B., Pagès, L., Price, A., Tuberosa, R., & Draye, X. (2007). Root system architecture: opportunities and constraints for genetic improvement of crops. Trends in Plant Science. https://doi.org/10.1016/j.tplants.2007.08.012

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