QTL meta-analysis in Arabidopsis reveals an interaction between leaf senescence and resource allocation to seeds

Chardon, Fabien; Jasinski, Sophie; Durandet, Monique; Lécureuil, Alain; Soulay, Fabienne; Bedu, Magali; Guerche, Philippe; Masclaux-Daubresse, Céline

doi:10.1093/jxb/eru125

Cited by 36 publications

(35 citation statements)

References 63 publications

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“…Grami et al [44] also established that seed oil content is negatively correlated with protein content; therefore, increasing the oil fraction of the seed would naturally enhance the oil:protein ratio and, according to our model, potentially help increase yields independently of changing architectural traits, although the mechanism by which this conversion occurs is presently not clear. A recent study using Arabidopsis populations established that seed carbon and N content were antagonistic and that % N was negatively correlated with yield [45], as it is in the present study. In Arabidopsis, the number of seeds and pods per plant were closely related to the concentration of seed oil and protein within the seeds [19].…”

Section: Increasing Seed Oil:protein Ratiosupporting

confidence: 78%

Development of a Statistical Crop Model to Explain the Relationship between Seed Yield and Phenotypic Diversity within the Brassica napus Genepool

et al. 2017

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Plants are extremely versatile organisms that respond to the environment in which they find themselves, but a large part of their development is under genetic regulation. The links between developmental parameters and yield are poorly understood in oilseed rape; understanding this relationship will help growers to predict their yields more accurately and breeders to focus on traits that may lead to yield improvements. To determine the relationship between seed yield and other agronomic traits, we investigated the natural variation that already exists with regards to resource allocation in 37 lines of the crop species Brassica napus. Over 130 different traits were assessed; they included seed yield parameters, seed composition, leaf mineral analysis, rates of pod and leaf senescence and plant architecture traits. A stepwise regression analysis was used to model statistically the measured traits with seed yield per plant. Above-ground biomass and protein content together accounted for 94.36% of the recorded variation. The primary raceme area, which was highly correlated with yield parameters (0.65), provides an early indicator of potential yield. The pod and leaf photosynthetic and senescence parameters measured had only a limited influence on seed yield and were not correlated with each other, indicating that reproductive development is not necessarily driving the senescence process within field-grown B. napus. Assessing the diversity that exists within the B. napus gene pool has highlighted architectural, seed and mineral composition traits that should be targeted in breeding programmes through the development of linked markers to improve crop yields.

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Section: Increasing Seed Oil:protein Ratiosupporting

confidence: 78%

Development of a Statistical Crop Model to Explain the Relationship between Seed Yield and Phenotypic Diversity within the Brassica napus Genepool

et al. 2017

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“…Unlike cereals, which have a long history of domestication, oilseed rape (Brassica napus) and Arabidopsis still show considerable variation in N remobilization efficiency across related populations (Chardon et al, 2014;Girondé et al, 2015). Moreover, in many Brassica spp.…”

Section: Carbon-nitrogen Resource Allocationmentioning

confidence: 99%

“…In many Brassica spp. crops, there is a negative correlation between seed N concentration and yield (Chardon et al, 2014). Also, in cereals, a negative correlation exists between protein concentration in the grain and plant yield, along with a delayed onset of senescence (Oury and Godin, 2007;Bogard et al, 2010;Blanco et al, 2012).…”

Section: Senescence and Grain Qualitymentioning

confidence: 99%

Living to Die and Dying to Live: The Survival Strategy behind Leaf Senescence

et al. 2015

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ORCID ID: 0000-0001-7934-126X (J.H.M.S.).Senescence represents the final developmental act of the leaf, during which the leaf cell is dismantled in a coordinated manner to remobilize nutrients and to secure reproductive success. The process of senescence provides the plant with phenotypic plasticity to help it adapt to adverse environmental conditions. Here, we provide a comprehensive overview of the factors and mechanisms that control the onset of senescence. We explain how the competence to senesce is established during leaf development, as depicted by the senescence window model. We also discuss the mechanisms by which phytohormones and environmental stresses control senescence as well as the impact of source-sink relationships on plant yield and stress tolerance. In addition, we discuss the role of senescence as a strategy for stress adaptation and how crop production and food quality could benefit from engineering or breeding crops with altered onset of senescence.

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“…In the model species Arabidopsis , using natural variation resources, QTL involved in seed oil content and/or quality have also been detected (Hobbs et al, 2004; Jasinski et al, 2012; O’Neill et al, 2012; Sanyal and Linder, 2012) as well as “regions of interest” by GWAS (Branham et al, 2015), but only the study published by Jasinski et al (2012) identified the gene involved. Since QTL cloning is often easier in model species for which substantial genetic resources exist, we implemented a QTL approach to study storage compound metabolisms in Arabidopsis seed (Jasinski et al, 2012; Chardon et al, 2014). Seed metabolism is very similar between Arabidopsis and Brassica species and the close relationship between them allows the use of comparative genetics to predict orthologous genes and alleles within the Brassica genome (Parkin et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…Finally, a search for genetic factors governing the accumulation of these four components in Arabidopsis seed was carried out by a QTL analysis (this work and Chardon et al, 2014), allowing the mapping of new QTL involved in seed oil and protein content.…”

Section: Introductionmentioning

confidence: 99%

Arabidopsis Seed Content QTL Mapping Using High-Throughput Phenotyping: The Assets of Near Infrared Spectroscopy

Jasinski¹,

Lécureuil²,

Durandet³

et al. 2016

Front. Plant Sci.

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Seed storage compounds are of crucial importance for human diet, feed and industrial uses. In oleo-proteaginous species like rapeseed, seed oil and protein are the qualitative determinants that conferred economic value to the harvested seed. To date, although the biosynthesis pathways of oil and storage protein are rather well-known, the factors that determine how these types of reserves are partitioned in seeds have to be identified. With the aim of implementing a quantitative genetics approach, requiring phenotyping of 100s of plants, our first objective was to establish near-infrared reflectance spectroscopic (NIRS) predictive equations in order to estimate oil, protein, carbon, and nitrogen content in Arabidopsis seed with high-throughput level. Our results demonstrated that NIRS is a powerful non-destructive, high-throughput method to assess the content of these four major components studied in Arabidopsis seed. With this tool in hand, we analyzed Arabidopsis natural variation for these four components and illustrated that they all displayed a wide range of variation. Finally, NIRS was used in order to map QTL for these four traits using seeds from the Arabidopsis thaliana Ct-1 × Col-0 recombinant inbred line population. Some QTL co-localized with QTL previously identified, but others mapped to chromosomal regions never identified so far for such traits. This paper illustrates the usefulness of NIRS predictive equations to perform accurate high-throughput phenotyping of Arabidopsis seed content, opening new perspectives in gene identification following QTL mapping and genome wide association studies.

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QTL meta-analysis in Arabidopsis reveals an interaction between leaf senescence and resource allocation to seeds

Abstract: SummaryMapping of metaQTL controlling leaf senescence and seed resource allocation in Arabidopsis reveals that leaf senescence might disrupt the general negative correlation observed between yield and seed nitrogen concentration.

Cited by 36 publications

References 63 publications

Development of a Statistical Crop Model to Explain the Relationship between Seed Yield and Phenotypic Diversity within the Brassica napus Genepool

Development of a Statistical Crop Model to Explain the Relationship between Seed Yield and Phenotypic Diversity within the Brassica napus Genepool

Living to Die and Dying to Live: The Survival Strategy behind Leaf Senescence

Arabidopsis Seed Content QTL Mapping Using High-Throughput Phenotyping: The Assets of Near Infrared Spectroscopy

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