Literature DB >> 16874488

Assessing the importance of genotype x environment interaction for root traits in rice using a mapping population. I: a soil-filled box screen.

K MacMillan1, K Emrich, H-P Piepho, C E Mullins, A H Price.   

Abstract

Altering root system architecture is considered a method of improving crop water and soil nutrient capture. The analysis of quantitative trait loci (QTLs) for root traits has revealed inconsistency in the same population evaluated in different environments. It must be clarified if this is due to genotype x environment interaction or considerations of statistics if the value of QTLs for marker-assisted breeding is to be estimated. A modified split-plot design was used where a main plot corresponded to a separate experiment. The main plot factor had four treatments (environments), which were completely randomized among eight trials, so that each treatment was replicated twice. The sub-plot factor consisted of 168 recombinant inbreed lines of the Bala x Azucena rice mapping population, randomly allocated to the seven soil-filled boxes. The aim of the trial was to quantify QTL x environment interaction. The treatments were chosen to alter partitioning to roots; consisting of a control treatment (high-soil nitrogen, high light and high-water content) and further treatments where light, soil nitrogen or soil water was reduced singly. After 4 weeks growth, maximum root length (MRL), maximum root thickness, root mass below 50 cm, total plant dry mass (%), root mass and shoot length were measured. The treatments affected plant growth as predicted; low nitrogen and drought increased relative root partitioning, low-light decreased it. The parental varieties Bala and Azucena differed significantly for all traits. Broad-sense heritability of most traits was high (57-86%). Variation due to treatment was the most important influence on the variance, while genotype was next. Genotype x environment interaction was detected for all traits except MRL, although the proportion of variation due to this interaction was generally small. It is concluded that genotype x environment interaction is present but less important than genotypic variation. A companion paper presents QTL x environment analysis of data.

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Year:  2006        PMID: 16874488     DOI: 10.1007/s00122-006-0356-5

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  4 in total

Review 1.  The role of nutrient availability in regulating root architecture.

Authors:  José López-Bucio; Alfredo Cruz-Ramírez; Luis Herrera-Estrella
Journal:  Curr Opin Plant Biol       Date:  2003-06       Impact factor: 7.834

Review 2.  Intrinsic and environmental response pathways that regulate root system architecture.

Authors:  J E Malamy
Journal:  Plant Cell Environ       Date:  2005-01       Impact factor: 7.228

3.  Effects of Phenotyping Environment on Identification of Quantitative Trait Loci for Rice Root Morphology under Anaerobic Conditions.

Authors:  A. Kamoshita; Jingxian Zhang; J. Siopongco; S. Sarkarung; H. T. Nguyen; L. J. Wade
Journal:  Crop Sci       Date:  2002-01       Impact factor: 2.319

4.  An Arabidopsis MADS box gene that controls nutrient-induced changes in root architecture.

Authors:  H Zhang; B G Forde
Journal:  Science       Date:  1998-01-16       Impact factor: 47.728

  4 in total
  7 in total

1.  Assessing the importance of genotype x environment interaction for root traits in rice using a mapping population II: conventional QTL analysis.

Authors:  K MacMillan; K Emrich; H-P Piepho; C E Mullins; A H Price
Journal:  Theor Appl Genet       Date:  2006-07-29       Impact factor: 5.699

2.  Quantitative trait loci and crop performance under abiotic stress: where do we stand?

Authors:  Nicholas C Collins; François Tardieu; Roberto Tuberosa
Journal:  Plant Physiol       Date:  2008-06       Impact factor: 8.340

3.  3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture.

Authors:  Christopher N Topp; Anjali S Iyer-Pascuzzi; Jill T Anderson; Cheng-Ruei Lee; Paul R Zurek; Olga Symonova; Ying Zheng; Alexander Bucksch; Yuriy Mileyko; Taras Galkovskyi; Brad T Moore; John Harer; Herbert Edelsbrunner; Thomas Mitchell-Olds; Joshua S Weitz; Philip N Benfey
Journal:  Proc Natl Acad Sci U S A       Date:  2013-04-11       Impact factor: 11.205

4.  Dissection of QTL effects for root traits using a chromosome arm-specific mapping population in bread wheat.

Authors:  Sundrish Sharma; Shizhong Xu; Bahman Ehdaie; Aaron Hoops; Timothy J Close; Adam J Lukaszewski; J Giles Waines
Journal:  Theor Appl Genet       Date:  2010-12-11       Impact factor: 5.699

5.  Disentangling the intertwined genetic bases of root and shoot growth in Arabidopsis.

Authors:  Marie Bouteillé; Gaëlle Rolland; Crispulo Balsera; Olivier Loudet; Bertrand Muller
Journal:  PLoS One       Date:  2012-02-24       Impact factor: 3.240

6.  Genome-wide analyses of rice root development QTLs and development of an online resource, Rootbrowse.

Authors:  Pala Suryapriya; Allada Snehalatha; Ulaganathan Kayalvili; Radha Krishna; Sukpal Singh; Kandasamy Ulaganathan
Journal:  Bioinformation       Date:  2009-01-12

7.  Genome-wide association mapping of root traits in a japonica rice panel.

Authors:  Brigitte Courtois; Alain Audebert; Audrey Dardou; Sandrine Roques; Thaura Ghneim-Herrera; Gaëtan Droc; Julien Frouin; Lauriane Rouan; Eric Gozé; Andrzej Kilian; Nourollah Ahmadi; Michael Dingkuhn
Journal:  PLoS One       Date:  2013-11-05       Impact factor: 3.240

  7 in total

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