Plastic expression of heterochrony quantitative trait loci (<scp><i>h</i>QTL</scp>s) for leaf growth in the common bean (<i><scp>P</scp>haseolus vulgaris</i>)

Jiang, Libo; Clavijo, José; Sun, Lidan; Zhu, Xuli; Bhakta, Mehul; Gezan, Salvador A.; Carvalho, Marcelo; Vallejos, C. Eduardo; Wu, Rongling

doi:10.1111/nph.13386

Cited by 19 publications

(20 citation statements)

References 44 publications

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“…The bottom‐up model has successfully identified important QTLs for the growth trajectories of leaf area and leaf mass in the common bean ( Phaseolus vulgaris L.) given in two contrasting environments. Some of these QTLs were confirmed by the top‐down approach (Jiang et al ., ).…”

Section: Discussionmentioning

confidence: 99%

An ecophysiologically based mapping model identifies a major pleiotropic QTL for leaf growth trajectories of Phaseolus vulgaris

et al. 2018

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Crop modeling, a widely used tool to predict plant growth and development in heterogeneous environments, has been increasingly integrated with genetic information to improve its predictability. This integration can also shed light on the mechanistic path that connects the genotype to a particular phenotype under specific environments. We implemented a bivariate statistical procedure to map and identify quantitative trait loci (QTLs) that can predict the form of plant growth by estimating cultivar-specific growth parameters and incorporating these parameters into a mapping framework. The procedure enables the characterization of how QTLs act differently in response to developmental and environmental cues. We used this procedure to map growth parameters of leaf area and mass in a mapping population of the common bean (Phaseolus vulgaris L.). Different sets of QTLs are responsible for various aspects of growth, including the initiation time of growth, growth rate, inflection point and asymptotic growth. A major QTL of a large effect was identified to pleiotropically affect trait expression in distinct environments and different traits expressed on the same organism. The integration of crop models and QTL mapping through our statistical procedure provides a powerful means of building a more precise predictive model of genotype-phenotype relationships for crops.

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Section: Discussionmentioning

confidence: 99%

An ecophysiologically based mapping model identifies a major pleiotropic QTL for leaf growth trajectories of Phaseolus vulgaris

et al. 2018

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“…Because of tremendous efforts by geneticists worldwide, a vast amount of mapping materials used to map complex traits for a wide range of species have been established (Cheverud et al ., ; Peiffer et al ., ; Rebetzke et al ., ; Jiang et al ., ). Consider such a mapping population available to map phase change.…”

Section: Modelmentioning

confidence: 97%

A computational framework for mapping the timing of vegetative phase change

Jiang

Zhu

et al. 2016

New Phytologist

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SummaryPhase change plays a prominent role in determining the form of growth and development. Although considerable attention has been focused on identifying the regulatory control mechanisms of phase change, a detailed understanding of the genetic architecture of this phenomenon is still lacking.We address this issue by deriving a computational model. The model is founded on the framework of functional mapping aimed at characterizing the interplay between quantitative trait loci (QTLs) and development through biologically meaningful mathematical equations.A multiphasic growth equation was implemented into functional mapping, which, via a series of hypothesis tests, allows the quantification of how QTLs regulate the timing and pattern of vegetative phase transition between independently regulated, temporally coordinated processes.The model was applied to analyze stem radial growth data of an interspecific hybrid family derived from two Populus species during the first 24 yr of ontogeny. Several key QTLs related to phase change have been characterized, most of which were observed to be in the adjacent regions of candidate genes.The identification of phase transition QTLs, whose expression is regulated by endogenous and environmental signals, may enhance our understanding of the evolution of development in changing environments.

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“…Zhao et al [78,79] developed a bivariate SAD(1) [biSAD (1)] model to simultaneously model the longitudinal variance matrix for each variable and the longitudinal covariance matrix between two variables using a parsimonious set of parameters. The biSAD(1) has well been used to model longitudinal data in forest trees [80] and crop plants [81].…”

Section: Mapping Dynamic Phenotypes Through Evolutionary Game Theorymentioning

confidence: 99%

Integrating Evolutionary Game Theory into Mechanistic Genotype–Phenotype Mapping

Zhu

Jiang

et al. 2016

Trends in Genetics

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Plastic expression of heterochrony quantitative trait loci (hQTLs) for leaf growth in the common bean (Phaseolus vulgaris)

Cited by 19 publications

References 44 publications

An ecophysiologically based mapping model identifies a major pleiotropic QTL for leaf growth trajectories of Phaseolus vulgaris

An ecophysiologically based mapping model identifies a major pleiotropic QTL for leaf growth trajectories of Phaseolus vulgaris

A computational framework for mapping the timing of vegetative phase change

Integrating Evolutionary Game Theory into Mechanistic Genotype–Phenotype Mapping

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