Literature DB >> 22113590

Using a physiological framework for improving the detection of quantitative trait loci related to nitrogen nutrition in Medicago truncatula.

Delphine Moreau1, Judith Burstin, Grégoire Aubert, Thierry Huguet, Cécile Ben, Jean-Marie Prosperi, Christophe Salon, Nathalie Munier-Jolain.   

Abstract

Medicago truncatula is used as a model plant for exploring the genetic and molecular determinants of nitrogen (N) nutrition in legumes. In this study, our aim was to detect quantitative trait loci (QTL) controlling plant N nutrition using a simple framework of carbon/N plant functioning stemming from crop physiology. This framework was based on efficiency variables which delineated the plant's efficiency to take up and process carbon and N resources. A recombinant inbred line population (LR4) was grown in a glasshouse experiment under two contrasting nitrate concentrations. At low nitrate, symbiotic N(2) fixation was the main N source for plant growth and a QTL with a large effect located on linkage group (LG) 8 affected all the traits. Significantly, efficiency variables were necessary both to precisely localize a second QTL on LG5 and to detect a third QTL involved in epistatic interactions on LG2. At high nitrate, nitrate assimilation was the main N source and a larger number of QTL with weaker effects were identified compared to low nitrate. Only two QTL were common to both nitrate treatments: a QTL of belowground biomass located at the bottom of LG3 and another one on LG6 related to three different variables (leaf area, specific N uptake and aboveground:belowground biomass ratio). Possible functions of several candidate genes underlying QTL of efficiency variables could be proposed. Altogether, our results provided new insights into the genetic control of N nutrition in M. truncatula. For instance, a novel result for M. truncatula was identification of two epistatic interactions in controlling plant N(2) fixation. As such this study showed the value of a simple conceptual framework based on efficiency variables for studying genetic determinants of complex traits and particularly epistatic interactions.

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Year:  2011        PMID: 22113590     DOI: 10.1007/s00122-011-1744-z

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  44 in total

1.  QTL analysis and QTL-based prediction of flowering phenology in recombinant inbred lines of barley.

Authors:  Xinyou Yin; Paul C Struik; Fred A van Eeuwijk; Piet Stam; Jianjun Tang
Journal:  J Exp Bot       Date:  2005-02-14       Impact factor: 6.992

2.  A novel RNA-binding peptide regulates the establishment of the Medicago truncatula-Sinorhizobium meliloti nitrogen-fixing symbiosis.

Authors:  Philippe Laporte; Béatrice Satiat-Jeunemaître; Isabel Velasco; Tibor Csorba; Willem Van de Velde; Anna Campalans; Joszef Burgyan; Miguel Arevalo-Rodriguez; Martin Crespi
Journal:  Plant J       Date:  2009-12-23       Impact factor: 6.417

3.  Adaptation of Medicago truncatula to nitrogen limitation is modulated via local and systemic nodule developmental responses.

Authors:  Christian Jeudy; Sandrine Ruffel; Sandra Freixes; Pascal Tillard; Anne Lise Santoni; Sylvain Morel; Etienne-Pascal Journet; Gérard Duc; Alain Gojon; Marc Lepetit; Christophe Salon
Journal:  New Phytol       Date:  2009-12-15       Impact factor: 10.151

4.  Quantitative trait loci analysis reveals a correlation between the ratio of sucrose/raffinose family oligosaccharides and seed vigour in Medicago truncatula.

Authors:  Céline Vandecasteele; Béatrice Teulat-Merah; Marie-Christine Morère-Le Paven; Olivier Leprince; Benoit Ly Vu; Laure Viau; Lydie Ledroit; Sandra Pelletier; Nicole Payet; Pascale Satour; Camille Lebras; Karine Gallardo; Thierry Huguet; Anis M Limami; Jean-Marie Prosperi; Julia Buitink
Journal:  Plant Cell Environ       Date:  2011-06-28       Impact factor: 7.228

5.  Using a standard framework for the phenotypic analysis of Medicago truncatula: an effective method for characterizing the plant material used for functional genomics approaches.

Authors:  Delphine Moreau; Christophe Salon; Nathalie Munier-Jolain
Journal:  Plant Cell Environ       Date:  2006-06       Impact factor: 7.228

6.  Can differences of nitrogen nutrition level among Medicago truncatula genotypes be assessed non-destructively?: Probing with a recombinant inbred lines population.

Authors:  Delphine Moreau; Charles Schneider; Thierry Huguet; Christophe Salon; Nathalie Munier-Jolain
Journal:  Plant Signal Behav       Date:  2009-01

7.  Identification of QTL affecting seed mineral concentrations and content in the model legume Medicago truncatula.

Authors:  Renuka P Sankaran; Thierry Huguet; Michael A Grusak
Journal:  Theor Appl Genet       Date:  2009-04-25       Impact factor: 5.699

8.  Partial resistance of Medicago truncatula to Aphanomyces euteiches is associated with protection of the root stele and is controlled by a major QTL rich in proteasome-related genes.

Authors:  Naceur Djébali; Alain Jauneau; Carine Ameline-Torregrosa; Fabien Chardon; Valérie Jaulneau; Catherine Mathé; Arnaud Bottin; Marc Cazaux; Marie-Laure Pilet-Nayel; Alain Baranger; Mohamed Elarbi Aouani; Marie-Thérèse Esquerré-Tugayé; Bernard Dumas; Thierry Huguet; Christophe Jacquet
Journal:  Mol Plant Microbe Interact       Date:  2009-09       Impact factor: 4.171

9.  AER1, a major gene conferring resistance to Aphanomyces euteiches in Medicago truncatula.

Authors:  M-L Pilet-Nayel; J-M Prospéri; C Hamon; A Lesné; R Lecointe; I Le Goff; M Hervé; G Deniot; M Delalande; T Huguet; C Jacquet; A Baranger
Journal:  Phytopathology       Date:  2009-02       Impact factor: 4.025

10.  Translational Genomics in Legumes Allowed Placing In Silico 5460 Unigenes on the Pea Functional Map and Identified Candidate Genes in Pisum sativum L.

Authors:  Amandine Bordat; Vincent Savois; Marie Nicolas; Jérome Salse; Aurélie Chauveau; Michael Bourgeois; Jean Potier; Hervé Houtin; Céline Rond; Florent Murat; Pascal Marget; Grégoire Aubert; Judith Burstin
Journal:  G3 (Bethesda)       Date:  2011-07-01       Impact factor: 3.154

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  6 in total

1.  How to hierarchize the main physiological processes responsible for phenotypic differences in large-scale screening studies?

Authors:  Delphine Moreau; Christophe Salon; Nathalie Munier-Jolain
Journal:  Plant Signal Behav       Date:  2012-03-01

2.  QTL detection for forage quality and stem histology in four connected mapping populations of the model legume Medicago truncatula.

Authors:  Luz Del Carmen Lagunes Espinoza; Bernadette Julier
Journal:  Theor Appl Genet       Date:  2012-10-26       Impact factor: 5.699

3.  Nitrogen Uptake Efficiency, Mediated by Fine Root Growth, Early Determines Temporal and Genotypic Variations in Nitrogen Use Efficiency of Winter Oilseed Rape.

Authors:  Victor Vazquez-Carrasquer; Anne Laperche; Christine Bissuel-Bélaygue; Michaël Chelle; Céline Richard-Molard
Journal:  Front Plant Sci       Date:  2021-05-13       Impact factor: 5.753

4.  Clusthaplo: a plug-in for MCQTL to enhance QTL detection using ancestral alleles in multi-cross design.

Authors:  Damien Leroux; Abdelaziz Rahmani; Sylvain Jasson; Marjolaine Ventelon; Florence Louis; Laurence Moreau; Brigitte Mangin
Journal:  Theor Appl Genet       Date:  2014-01-31       Impact factor: 5.699

5.  Soil nitrogen availability and plant genotype modify the nutrition strategies of M. truncatula and the associated rhizosphere microbial communities.

Authors:  Anouk Zancarini; Christophe Mougel; Anne-Sophie Voisin; Marion Prudent; Christophe Salon; Nathalie Munier-Jolain
Journal:  PLoS One       Date:  2012-10-15       Impact factor: 3.240

6.  Unexpectedly low nitrogen acquisition and absence of root architecture adaptation to nitrate supply in a Medicago truncatula highly branched root mutant.

Authors:  Virginie Bourion; Chantal Martin; Henri de Larambergue; Françoise Jacquin; Grégoire Aubert; Marie-Laure Martin-Magniette; Sandrine Balzergue; Geoffroy Lescure; Sylvie Citerne; Marc Lepetit; Nathalie Munier-Jolain; Christophe Salon; Gérard Duc
Journal:  J Exp Bot       Date:  2014-04-04       Impact factor: 6.992

  6 in total

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