Literature DB >> 12920521

Identification of QTL for growth- and grain yield-related traits in rice across nine locations of Asia.

Shailaja Hittalmani1, N Huang, B Courtois, R Venuprasad, H E Shashidhar, J-Y Zhuang, K-L Zheng, G-F Liu, G-C Wang, J S Sidhu, S Srivantaneeyakul, V P Singh, P G Bagali, H C Prasanna, G McLaren, G S Khush.   

Abstract

Rice double-haploid (DH) lines of an indica and japonica cross were grown at nine different locations across four countries in Asia. Genotype-by-environment (G x E) interaction analysis for 11 growth- and grain yield-related traits in nine locations was estimated by AMMI analysis. Maximum G x E interaction was exhibited for fertility percentage number of spikelets and grain yield. Plant height was least affected by environment, and the AMMI model explained a total of 76.2% of the interaction effect. Mean environment was computed by averaging the nine environments and subsequently analyzed with other environments to map quantitative trait loci (QTL). QTL controlling the 11 traits were detected by interval analysis using mapmaker/qtl. A threshold LOD of >/=3.20 was used to identify significant QTL. A total of 126 QTL were identified for the 11 traits across nine locations. Thirty-four QTL common in more than one environment were identified on ten chromosomes. A maximum of 44 QTL were detected for panicle length, and the maximum number of common QTL were detected for days to heading detected. A single locus for plant height (RZ730-RG810) had QTL common in all ten environments, confirming AMMI results that QTL for plant height were affected the least by environment, indicating the stability of the trait. Two QTL were detected for grain yield and 19 for thousand-grain weight in all DH lines. The number of QTL per trait per location ranged from zero to four. Clustering of the QTL for different traits at the same marker intervals was observed for plant height, panicle number, panicle length and spikelet number suggesting that pleiotropism and or tight linkage of different traits could be the possible reason for the congruence of several QTL. The many QTL detected by the same marker interval across environments indicate that QTL for most traits are stable and not essentially affected by environmental factors.

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Year:  2003        PMID: 12920521     DOI: 10.1007/s00122-003-1269-1

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


  12 in total

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Authors:  H X Lin; H R Qian; J Y Zhuang; J Lu; S K Min; Z M Xiong; N Huang; K L Zheng
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  64 in total

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Authors:  G F Liu; M Li; J Wen; Y Du; Y-M Zhang
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3.  Using probe genotypes to dissect QTL × environment interactions for grain yield components in winter wheat.

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Journal:  Theor Appl Genet       Date:  2010-08-10       Impact factor: 5.699

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Authors:  D-B Yoon; K-H Kang; H-J Kim; H-G Ju; S-J Kwon; J-P Suh; O-Y Jeong; S-N Ahn
Journal:  Theor Appl Genet       Date:  2006-01-24       Impact factor: 5.699

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

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9.  QTL analysis for yield components and kernel-related traits in maize across multi-environments.

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10.  Genetic analysis and major QTL detection for maize kernel size and weight in multi-environments.

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Journal:  Theor Appl Genet       Date:  2014-02-20       Impact factor: 5.699

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