Literature DB >> 12961067

QTL x environment interactions in rice. I. heading date and plant height.

Z K Li1, S B Yu, H R Lafitte, N Huang, B Courtois, S Hittalmani, C H M Vijayakumar, G F Liu, G C Wang, H E Shashidhar, J Y Zhuang, K L Zheng, V P Singh, J S Sidhu, S Srivantaneeyakul, G S Khush.   

Abstract

One hundred twenty six doubled-haploid (DH) rice lines were evaluated in nine diverse Asian environments to reveal the genetic basis of genotype x environment interactions (GEI) for plant height (PH) and heading date (HD). A subset of lines was also evaluated in four water-limited environments, where the environmental basis of G x E could be more precisely defined. Responses to the environments were resolved into individual QTL x environment interactions using replicated phenotyping and the mixed linear-model approach. A total of 37 main-effect QTLs and 29 epistatic QTLs were identified. On average, these QTLs were detectable in 56% of the environments. When detected in multiple environments, the main effects of most QTLs were consistent in direction but varied considerably in magnitude across environments. Some QTLs had opposite effects in different environments, particularly in water-limited environments, indicating that they responded to the environments differently. Inconsistent QTL detection across environments was due primarily to non- or weak-expression of the QTL, and in part to significant QTL x environment interaction effects in the opposite direction to QTL main effects, and to pronounced epistasis. QTL x environment interactions were trait- and gene-specific. The greater GEI for HD than for PH in rice were reflected by more environment-specific QTLs, greater frequency and magnitude of QTL x environment interaction effects, and more pronounced epistasis for HD than for PH. Our results demonstrated that QTL x environment interaction is an important property of many QTLs, even for highly heritable traits such as height and maturity. Information about QTL x environment interaction is essential if marker-assisted selection is to be applied to the manipulation of quantitative traits.

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Year:  2003        PMID: 12961067     DOI: 10.1007/s00122-003-1401-2

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


  17 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  1997-08-19       Impact factor: 11.205

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Authors:  J Crossa; M Vargas; F A van Eeuwijk; C Jiang; G O Edmeades; D Hoisington
Journal:  Theor Appl Genet       Date:  1999-08       Impact factor: 5.699

3.  Comparative mapping of QTLs for agronomic traits of rice across environments using a doubled haploid population.

Authors:  C Lu; L Shen; Z Tan; Y Xu; P He; Y Chen; L Zhu
Journal:  Theor Appl Genet       Date:  1996-12       Impact factor: 5.699

4.  Mixed model approaches for diallel analysis based on a bio-model.

Authors:  J Zhu; B S Weir
Journal:  Genet Res       Date:  1996-12       Impact factor: 1.588

5.  Mendelian factors underlying quantitative traits in tomato: comparison across species, generations, and environments.

Authors:  A H Paterson; S Damon; J D Hewitt; D Zamir; H D Rabinowitch; S E Lincoln; E S Lander; S D Tanksley
Journal:  Genetics       Date:  1991-01       Impact factor: 4.562

6.  Interactions between quantitative trait loci in soybean in which trait variation at one locus is conditional upon a specific allele at another.

Authors:  K G Lark; K Chase; F Adler; L M Mansur; J H Orf
Journal:  Proc Natl Acad Sci U S A       Date:  1995-05-09       Impact factor: 11.205

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8.  Epistasis for three grain yield components in rice (Oryza sativa L.).

Authors:  Z Li; S R Pinson; W D Park; A H Paterson; J W Stansel
Journal:  Genetics       Date:  1997-02       Impact factor: 4.562

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Authors:  P M Hayes; B H Liu; S J Knapp; F Chen; B Jones; T Blake; J Franckowiak; D Rasmusson; M Sorrells; S E Ullrich; D Wesenberg; A Kleinhofs
Journal:  Theor Appl Genet       Date:  1993-11       Impact factor: 5.699

10.  Identification of QTLs affecting traits of agronomic importance in a recombinant inbred population derived from a subspecific rice cross.

Authors:  J Xiao; J Li; L Yuan; S D Tanksley
Journal:  Theor Appl Genet       Date:  1996-02       Impact factor: 5.699

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  71 in total

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Journal:  Mol Cells       Date:  2011-11-09       Impact factor: 5.034

2.  QTL analysis of soybean seed weight across multi-genetic backgrounds and environments.

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Journal:  Theor Appl Genet       Date:  2012-04-06       Impact factor: 5.699

3.  A unified statistical model for functional mapping of environment-dependent genetic expression and genotype x environment interactions for ontogenetic development.

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Journal:  Genetics       Date:  2004-11       Impact factor: 4.562

4.  Gene networks in hexaploid wheat: interacting quantitative trait loci for grain protein content.

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5.  QTLs for drought escape and tolerance identified in a set of random introgression lines of rice.

Authors:  J L Xu; H R Lafitte; Y M Gao; B Y Fu; R Torres; Z K Li
Journal:  Theor Appl Genet       Date:  2005-11-10       Impact factor: 5.699

6.  Identification of quantitative trait loci across recombinant inbred lines and testcross populations for traits of agronomic importance in rice.

Authors:  Aiqing You; Xinggui Lu; Huajun Jin; Xiang Ren; Kai Liu; Guocai Yang; Haiyuan Yang; Lili Zhu; Guangcun He
Journal:  Genetics       Date:  2005-12-01       Impact factor: 4.562

7.  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

8.  Mapping QTLs of root morphological traits at different growth stages in rice.

Authors:  Yanying Qu; Ping Mu; Hongliang Zhang; Charles Y Chen; Yongming Gao; Yuxiu Tian; Feng Wen; Zichao Li
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9.  Comparison of QTL controlling seedling vigour under different temperature conditions using recombinant inbred lines in rice (Oryza sativa).

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10.  Quantitative trait loci for grain yield and adaptation of durum wheat (Triticum durum Desf.) across a wide range of water availability.

Authors:  Marco Maccaferri; Maria Corinna Sanguineti; Simona Corneti; José Luis Araus Ortega; Moncef Ben Salem; Jordi Bort; Enzo DeAmbrogio; Luis Fernando Garcia del Moral; Andrea Demontis; Ahmed El-Ahmed; Fouad Maalouf; Hassan Machlab; Vanessa Martos; Marc Moragues; Jihan Motawaj; Miloudi Nachit; Nasserlehaq Nserallah; Hassan Ouabbou; Conxita Royo; Amor Slama; Roberto Tuberosa
Journal:  Genetics       Date:  2008-01       Impact factor: 4.562

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