Literature DB >> 17092764

Models for navigating biological complexity in breeding improved crop plants.

Graeme Hammer1, Mark Cooper, François Tardieu, Stephen Welch, Bruce Walsh, Fred van Eeuwijk, Scott Chapman, Dean Podlich.   

Abstract

Progress in breeding higher-yielding crop plants would be greatly accelerated if the phenotypic consequences of making changes to the genetic makeup of an organism could be reliably predicted. Developing a predictive capacity that scales from genotype to phenotype is impeded by biological complexities associated with genetic controls, environmental effects and interactions among plant growth and development processes. Plant modelling can help navigate a path through this complexity. Here we profile modelling approaches for complex traits at gene network, organ and whole plant levels. Each provides a means to link phenotypic consequence to changes in genomic regions via stable associations with model coefficients. A unifying feature of the models is the relatively coarse level of granularity they use to capture system dynamics. Much of the fine detail is not directly required. Robust coarse-grained models might be the tool needed to integrate phenotypic and molecular approaches to plant breeding.

Mesh:

Year:  2006        PMID: 17092764     DOI: 10.1016/j.tplants.2006.10.006

Source DB:  PubMed          Journal:  Trends Plant Sci        ISSN: 1360-1385            Impact factor:   18.313


  70 in total

Review 1.  Genetic and physiological bases for phenological responses to current and predicted climates.

Authors:  A M Wilczek; L T Burghardt; A R Cobb; M D Cooper; S M Welch; J Schmitt
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-10-12       Impact factor: 6.237

2.  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

3.  Using a model-based framework for analysing genetic diversity during germination and heterotrophic growth of Medicago truncatula.

Authors:  S Brunel; B Teulat-Merah; M-H Wagner; T Huguet; J M Prosperi; C Dürr
Journal:  Ann Bot       Date:  2009-02-27       Impact factor: 4.357

4.  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

5.  Estimation of Plant and Canopy Architectural Traits Using the Digital Plant Phenotyping Platform.

Authors:  Shouyang Liu; Pierre Martre; Samuel Buis; Mariem Abichou; Bruno Andrieu; Frédéric Baret
Journal:  Plant Physiol       Date:  2019-08-16       Impact factor: 8.340

Review 6.  Gene expression analysis, proteomics, and network discovery.

Authors:  Sacha Baginsky; Lars Hennig; Philip Zimmermann; Wilhelm Gruissem
Journal:  Plant Physiol       Date:  2009-12-11       Impact factor: 8.340

7.  Quantitative genetics, version 3.0: where have we gone since 1987 and where are we headed?

Authors:  Bruce Walsh
Journal:  Genetica       Date:  2008-09-15       Impact factor: 1.082

8.  Simulating the yield impacts of organ-level quantitative trait loci associated with drought response in maize: a "gene-to-phenotype" modeling approach.

Authors:  Karine Chenu; Scott C Chapman; François Tardieu; Greg McLean; Claude Welcker; Graeme L Hammer
Journal:  Genetics       Date:  2009-09-28       Impact factor: 4.562

9.  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

10.  Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress.

Authors:  Junfei Gu; Xinyou Yin; Chengwei Zhang; Huaqi Wang; Paul C Struik
Journal:  Ann Bot       Date:  2014-07-01       Impact factor: 4.357

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