Literature DB >> 10383660

The role of ecophysiological models in QTL analysis: the example of specific leaf area in barley

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Abstract

Crop modelling has so far contributed little to the genetic analysis of a quantitative trait. This study illustrates how a simple model for crop phenological development, which assumes that crop development rate is affected by daily effective temperature, can assist the identification of Quantitative Trait Loci (QTLs), using specific leaf area (SLA) in barley as an example. The SLA was measured in a field experiment six times during the growing season of 94 recombinant inbred lines (RILs) derived from a cross between cultivars Prisma and Apex. Of the six measurements, one was conducted at the same physiological age for all RILs (at flowering), four were undertaken at specific chronological days prior to flowering, and the last one was taken at 14 days after flowering. When the measured SLA was directly used as the quantitative trait, one to three QTLs were detected for SLA at each measurement time. The major dwarfing gene denso segregating in the population was found to affect SLA strongly at all measurement times except at flowering. If SLA of the different RILs was corrected for differences in physiological age at the time of measurement, by the use of the crop development model, QTLs were detected for SLA at only three stages. Furthermore, the effect of the denso gene was no longer significant during the preflowering stages. The effect of the denso gene detected in the first instance was therefore the consequence of its direct effect on the duration of the preflowering period. This demonstrates the important role that crop development models can play in QTL analysis of a trait that varies with developmental stage. Potential uses of ecophysiological crop growth models in QTL analysis are briefly discussed.

Entities:  

Year:  1999        PMID: 10383660     DOI: 10.1038/sj.hdy.6885030

Source DB:  PubMed          Journal:  Heredity (Edinb)        ISSN: 0018-067X            Impact factor:   3.821


  24 in total

1.  Quantitative genetics and functional-structural plant growth models: simulation of quantitative trait loci detection for model parameters and application to potential yield optimization.

Authors:  Véronique Letort; Paul Mahe; Paul-Henry Cournède; Philippe de Reffye; Brigitte Courtois
Journal:  Ann Bot       Date:  2007-08-31       Impact factor: 4.357

2.  A functional-structural model of rice linking quantitative genetic information with morphological development and physiological processes.

Authors:  Lifeng Xu; Michael Henke; Jun Zhu; Winfried Kurth; Gerhard Buck-Sorlin
Journal:  Ann Bot       Date:  2011-01-18       Impact factor: 4.357

3.  A genetic analysis of relative growth rate and underlying components in Hordeum spontaneum.

Authors:  Hendrik Poorter; Cynthia P E van Rijn; Tytti K Vanhala; Koen J F Verhoeven; Yvonne E M de Jong; Piet Stam; Hans Lambers
Journal:  Oecologia       Date:  2004-11-20       Impact factor: 3.225

4.  A simplified conceptual model of carbon/nitrogen functioning for QTL analysis of winter wheat adaptation to nitrogen deficiency.

Authors:  A Laperche; F Devienne-Barret; O Maury; J Le Gouis; B Ney
Journal:  Theor Appl Genet       Date:  2006-08-15       Impact factor: 5.699

5.  Combining quantitative trait Loci analysis and an ecophysiological model to analyze the genetic variability of the responses of maize leaf growth to temperature and water deficit.

Authors:  Matthieu Reymond; Bertrand Muller; Agnès Leonardi; Alain Charcosset; François Tardieu
Journal:  Plant Physiol       Date:  2003-02       Impact factor: 8.340

6.  Simulating the impact of genetic diversity of Medicago truncatula on germination and emergence using a crop emergence model for ideotype breeding.

Authors:  S Brunel-Muguet; J-N Aubertot; C Dürr
Journal:  Ann Bot       Date:  2011-04-18       Impact factor: 4.357

7.  Leaf thickness of barley: genetic dissection, candidate genes prediction and its relationship with yield-related traits.

Authors:  Zhi Zheng; Haiyan Hu; Shang Gao; Hong Zhou; Wei Luo; Udaykumar Kage; Chunji Liu; Jizeng Jia
Journal:  Theor Appl Genet       Date:  2022-03-29       Impact factor: 5.699

8.  Analysis of genotypic variation in fruit flesh total sugar content via an ecophysiological model applied to peach.

Authors:  B Quilot; M Génard; J Kervella; F Lescourret
Journal:  Theor Appl Genet       Date:  2004-04-17       Impact factor: 5.699

9.  Detection of a quantitative trait locus controlling carbon isotope discrimination and its contribution to stomatal conductance in japonica rice.

Authors:  Toshiyuki Takai; Akihiro Ohsumi; Yumiko San-oh; Ma Rebecca C Laza; Motohiko Kondo; Toshio Yamamoto; Masahiro Yano
Journal:  Theor Appl Genet       Date:  2009-02-26       Impact factor: 5.699

10.  QTL Mapping and Phenotypic Variation for Seedling Vigour Traits in Barley (Hordeum vulgare L.).

Authors:  Ludovic J A Capo-Chichi; Sharla Eldridge; Ammar Elakhdar; Takahiko Kubo; Robert Brueggeman; Anthony O Anyia
Journal:  Plants (Basel)       Date:  2021-06-04
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