Literature DB >> 15490102

Yield response to water deficit in an upland rice mapping population: associations among traits and genetic markers.

H R Lafitte1, A H Price, B Courtois.   

Abstract

A population of recombinant inbred rice lines from a cross between the upland japonica cultivar Azucena and the upland indica cultivar Bala was evaluated in a series of upland field experiments. Water stress was imposed during the reproductive stage by managed irrigation during the dry season, while control treatments were maintained in aerobic, well-irrigated conditions. Water deficit resulted in a yield reduction of 17 to 50%. The genetic correlation between stress and control yields was quite high when stress was mild, and the heritability of yield was similar in stress and control treatments across both years of this study. Genetic correlations between secondary traits such as leaf rolling and drying and yield under stress varied from high (leaf drying) to insignificant (leaf rolling). Lines with superior yield tended to have fewer panicles and larger grain size than the high-yielding parent, Bala, even though the panicle number was positively correlated with yield and the thousand-grain weight was not associated with yield for the population as a whole. Analysis of quantitative trait loci (QTLs) for yield and yield components allowed the identification of 31 regions associated with growth or yield components. Superior alleles came from either parent. Several of the regions identified had also been reported for root mass at depth or maximum root length in this population in other studies made under controlled environments, and for leaf drying (LD) in field studies. However, the direction of the effect of QTLs was not consistent, which indicates that there was not necessarily a causal relationship between these secondary traits and performance. We conclude that mapping populations can provide novel insights on the actual relationships between yield components and secondary traits in stress and control environments and can allow identification of significant QTLs for yield components under drought stress.

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Year:  2004        PMID: 15490102     DOI: 10.1007/s00122-004-1731-8

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


  3 in total

Review 1.  Linking drought-resistance mechanisms to drought avoidance in upland rice using a QTL approach: progress and new opportunities to integrate stomatal and mesophyll responses.

Authors:  Adam H Price; Jill E Cairns; Peter Horton; Hamlyn G Jones; Howard Griffiths
Journal:  J Exp Bot       Date:  2002-05       Impact factor: 6.992

2.  Mapping QTLs associated with drought avoidance in upland rice grown in the Philippines and West Africa.

Authors:  Adam H Price; John Townend; Monty P Jones; Alain Audebert; Brigitte Courtois
Journal:  Plant Mol Biol       Date:  2002 Mar-Apr       Impact factor: 4.076

3.  Bias and Sampling Error of the Estimated Proportion of Genotypic Variance Explained by Quantitative Trait Loci Determined From Experimental Data in Maize Using Cross Validation and Validation With Independent Samples.

Authors: 
Journal:  Genetics       Date:  2000-04       Impact factor: 4.562

  3 in total
  28 in total

1.  Fine mapping of QTLs for rice grain yield under drought reveals sub-QTLs conferring a response to variable drought severities.

Authors:  Shalabh Dixit; B P Mallikarjuna Swamy; Prashant Vikram; H U Ahmed; M T Sta Cruz; Modesto Amante; Dinesh Atri; Hei Leung; Arvind Kumar
Journal:  Theor Appl Genet       Date:  2012-02-24       Impact factor: 5.699

2.  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

3.  Overexpressing a NAM, ATAF, and CUC (NAC) transcription factor enhances drought resistance and salt tolerance in rice.

Authors:  Honghong Hu; Mingqiu Dai; Jialing Yao; Benze Xiao; Xianghua Li; Qifa Zhang; Lizhong Xiong
Journal:  Proc Natl Acad Sci U S A       Date:  2006-08-21       Impact factor: 11.205

4.  Mapping QTLs for plant phenology and production traits using indica rice (Oryza sativa L.) lines adapted to rainfed environment.

Authors:  K K Suji; K R Biji; R Poornima; K Silvas Jebakumar Prince; K Amudha; S Kavitha; Sumeet Mankar; R Chandra Babu
Journal:  Mol Biotechnol       Date:  2012-10       Impact factor: 2.695

5.  Identification of major candidate genes for multiple abiotic stress tolerance at seedling stage by network analysis and their validation by expression profiling in rice (Oryza sativa L.).

Authors:  M K Ramkumar; Ekta Mulani; Vasudha Jadon; V Sureshkumar; S Gopala Krishnan; S Senthil Kumar; M Raveendran; A K Singh; Amolkumar U Solanke; N K Singh; Amitha Mithra Sevanthi
Journal:  3 Biotech       Date:  2022-05-12       Impact factor: 2.893

Review 6.  Breeding for abiotic stresses for sustainable agriculture.

Authors:  J R Witcombe; P A Hollington; C J Howarth; S Reader; K A Steele
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2008-02-27       Impact factor: 6.237

7.  Using chromosome introgression lines to map quantitative trait loci for photosynthesis parameters in rice (Oryza sativa L.) leaves under drought and well-watered field conditions.

Authors:  Junfei Gu; Xinyou Yin; Paul C Struik; Tjeerd Jan Stomph; Huaqi Wang
Journal:  J Exp Bot       Date:  2011-10-06       Impact factor: 6.992

8.  Improved resolution in the position of drought-related QTLs in a single mapping population of rice by meta-analysis.

Authors:  Farkhanda S Khowaja; Gareth J Norton; Brigitte Courtois; Adam H Price
Journal:  BMC Genomics       Date:  2009-06-22       Impact factor: 3.969

9.  Dissecting rice polyamine metabolism under controlled long-term drought stress.

Authors:  Phuc Thi Do; Thomas Degenkolbe; Alexander Erban; Arnd G Heyer; Joachim Kopka; Karin I Köhl; Dirk K Hincha; Ellen Zuther
Journal:  PLoS One       Date:  2013-04-08       Impact factor: 3.240

10.  Genetic, physiological, and gene expression analyses reveal that multiple QTL enhance yield of rice mega-variety IR64 under drought.

Authors:  B P Mallikarjuna Swamy; Helal Uddin Ahmed; Amelia Henry; Ramil Mauleon; Shalabh Dixit; Prashant Vikram; Ram Tilatto; Satish B Verulkar; Puvvada Perraju; Nimai P Mandal; Mukund Variar; S Robin; Ranganath Chandrababu; Onkar N Singh; Jawaharlal L Dwivedi; Sankar Prasad Das; Krishna K Mishra; Ram B Yadaw; Tamal Lata Aditya; Biswajit Karmakar; Kouji Satoh; Ali Moumeni; Shoshi Kikuchi; Hei Leung; Arvind Kumar
Journal:  PLoS One       Date:  2013-05-08       Impact factor: 3.240

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