Genetic Control of Plasticity in Root Morphology and Anatomy of Rice in Response to Water Deficit

Kadam, Niteen N.; Tamilselvan, Anandhan; Lawas, Lovely Mae F; Quiñones, Cherryl; Bahuguna, Rajeev Nayan; Thomson, Michael J.; Dingkuhn, Michaël; Raveendran, M.; Struik, P.C.; Yin, Xinyou; Jagadish, S. V. Krishna

doi:10.1104/pp.17.00500

Cited by 137 publications

(150 citation statements)

References 54 publications

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“…Next we analyze 25 traits measured on 274 indica genotypes of rice ( Oryza sativa ) under water-deficit, reported by Kadam et al (2017). Three replicates of each genotype were phenotyped in a randomized complete block design, and block was included as a covariate in all conditional independence tests.…”

Section: Resultsmentioning

confidence: 99%

“…PCgen-reconstruction for the rice-data from Kadam et al (2017), with α = 0.01. Five traits (MRL, ART, RL2530, RL3035 and RL35) are not shown, as they were completely isolated in the graph, without any connections to other traits or G .…”

Section: Resultsmentioning

confidence: 99%

“…PCgen-reconstruction for the rice-data from Kadam et al (2017), with α = 0.01: p-values. For each pair of nodes, the figure displays the highest p-value observed across all conditional independence tests performed for that pair.…”

Section: Supplementary File 7 Miscelleneousmentioning

confidence: 99%

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Reconstruction of networks with direct and indirect genetic effects

Kruijer

Behrouzi

Korts

et al. 2019

Preprint

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1Genetic variance of a phenotypic trait can originate from direct genetic effects, or from indirect effects, i.e. through genetic effects on other traits, affecting the trait of interest. This distinction is often of great importance, for example when trying to improve crop yield and simultaneously controlling plant height. As suggested by Sewall Wright, assessing contributions of direct and indirect effects requires knowledge of (1) the presence or absence of direct genetic effects on each trait, and (2) the functional relationships between the traits. Because experimental validation of such relationships is often unfeasible, it is increasingly common to reconstruct them using causal inference methods. However, current methods require all genetic variance to be explained by a small number of QTLs with fixed effects. Only few authors considered the 'missing heritability' case, where contributions of many undetectable QTLs are modelled with random effects. Usually, these are treated as nuisance terms, that need to be eliminated by taking residuals from a multi-trait mixed model (MTM). But fitting such MTM is challenging, and it is impossible to infer the presence of direct genetic effects. Here we propose an alternative strategy, where genetic effects are formally included in the graph. This has important advantages: (1) genetic effects can be directly incorporated in causal inference, leading to the PCgen algorithm, which can analyze many more traits (2) we can test the existence of direct genetic effects, and improve the orientation of edges between traits. Finally, we show that reconstruction is much more accurate if individual plant or plot data are used. We have implemented the PCgen-algorithm in the R-package pcgen. 2 3 4 5 6 7 8 9 10 11 12 13 14 15KEYWORDS Structural Equation Models, multivariate mixed models, causal inference 16 17 18 22 the genomic prediction applications are based on linear mixed-23 or Bayesian models that predict the phenotype for the target 24 trait (yield) as a function of a multivariate distribution for SNP 25 effects. In these models, the physiological mechanisms and traits 26 that modulate the genotypic response to the environment over 27 time are modeled implicitly via the SNP effects on the target 28 trait (Zhou and Stephens 2014; Calus and Veerkamp 2011). The 29 availability of high throughput phenotyping technologies has 30 enabled breeders to characterize additional traits and monitor 31 growth and development during the season. This opens new 32 opportunities in breeding strategies, in which better-adapted 33 genotypes result from combining loci that regulate complemen-34 tary physiological mechanisms. This kind of breeding strategy 35 is called physiological breeding (Reynolds and Langridge 2016). 36In physiological breeding, prediction accuracy for the target 37 trait benefits from modeling the target trait and its underly-38 ing traits simultaneously (van Eeuwijk et al. 2018) because of a 39 larger power to estimate its underlying effects (Stephens 2013).40The challenge of...

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Reconstruction of networks with direct and indirect genetic effects

Kruijer

Behrouzi

Korts

et al. 2019

Preprint

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“…Genetic mapping approaches now go beyond bi-parental populations with broadening genetic background, for example, by creating the multi-parent advanced generation inter-cross lines using multiple genetically diverse genotypes (Huang et al 2011). In addition, there is a growing number of studies pursuing GWAS (genome-wide association study) based on a high-density molecular marker set in a broad range of genotypes (e.g., McCouch et al 2016;Kadam et al 2017). This will provide unprecedented opportunities, not only to improve breeding efficiency via genomic selection based on genome-wide markers (Spindel et al 2015) or even via direct genome editing (Bortesi & Fischer 2015), but also to practise QTLor gene-based crop modelling (Dingkuhn et al 2017a,b).…”

Section: Role Of Genetics In Crop Modellingmentioning

confidence: 99%

Bringing genetics and biochemistry to crop modelling, and vice versa

Yin

Linden

Struik

2018

European Journal of Agronomy

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“…Recently, the FAO pictured how livestock species and breeds could contribute to ecosystem services and biodiversity (Hoffmann et al 2014) but even plant breeders have not internalized ecosystem services yet to a large extent (see Section 3.2). Some of these characteristics related to ecosystem services, such as plasticity of root systems for resource capture, will contribute also to climate mitigation and climate robustness (e.g., Kadam et al 2017). Climate robustness requires adaptation to variable, unpredictable, and extreme weather conditions tailor-made to local contexts (Shi et al 2017).…”

Section: From Action To Achievementmentioning

confidence: 99%

Towards resilience through systems-based plant breeding. A review

Bueren

Struik

Eekeren

et al. 2018

Agron. Sustain. Dev.

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How the growing world population can feed itself is a crucial, multi-dimensional problem that goes beyond sustainable development. Crop production will be affected by many changes in its climatic, agronomic, economic, and societal contexts. Therefore, breeders are challenged to produce cultivars that strengthen both ecological and societal resilience by striving for six international sustainability targets: food security, safety and quality; food and seed sovereignty; social justice; agrobiodiversity; ecosystem services; and climate robustness. Against this background, we review the state of the art in plant breeding by distinguishing four paradigmatic orientations that currently co-exist: community-based breeding, ecosystem-based breeding, trait-based breeding, and corporate-based breeding, analyzing differences among these orientations. Our main findings are: (1) all four orientations have significant value but none alone will achieve all six sustainability targets; (2) therefore, an overarching approach is needed: "systems-based breeding," an orientation with the potential to synergize the strengths of the ways of thinking in the current paradigmatic orientations; (3) achieving that requires specific knowledge development and integration, a multitude of suitable breeding strategies and tools, and entrepreneurship, but also a change in attitude based on corporate responsibility, circular economy and true-cost accounting, and fair and green policies. We conclude that systems-based breeding can create strong interactions between all system components. While seeds are part of the common good and the basis of agrobiodiversity, a diversity in breeding approaches, based on different entrepreneurial approaches, can also be considered part of the required agrobiodiversity. To enable systems-based breeding to play a major role in creating sustainable agriculture, a shared sense of urgency is needed to realize the required changes in breeding approaches, institutions, regulations and protocols. Based on this concept of systems-based breeding, there are opportunities for breeders to play an active role in the development of an ecologically and societally resilient, sustainable agriculture.

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Genetic Control of Plasticity in Root Morphology and Anatomy of Rice in Response to Water Deficit

Cited by 137 publications

References 54 publications

Reconstruction of networks with direct and indirect genetic effects

Reconstruction of networks with direct and indirect genetic effects

Bringing genetics and biochemistry to crop modelling, and vice versa

Towards resilience through systems-based plant breeding. A review

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