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

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Title: Using a physiological framework for improving the detection of quantitative trait loci related to nitrogen nutrition in Medicago truncatula.
Authors: Moreau, Delphine delphine.moreau@dijon.inra.fr, Burstin, Judith1, Aubert, Grégoire1, Huguet, Thierry2, Ben, Cécile, Prosperi, Jean-Marie3, Salon, Christophe1, Munier-Jolain, Nathalie1
Source: Theoretical & Applied Genetics. Mar2012, Vol. 124 Issue 4, p755-768. 14p.
Subjects: Quantitative research, Legumes, Plant nutrition, Effect of nitrogen on plants, Crop physiology, Plant growth, Plant biomass, Plant genetics
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 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 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. [ABSTRACT FROM AUTHOR]
Copyright of Theoretical & Applied Genetics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="AR" term="%22Moreau%2C+Delphine%22">Moreau, Delphine</searchLink><i> delphine.moreau@dijon.inra.fr</i><br /><searchLink fieldCode="AR" term="%22Burstin%2C+Judith%22">Burstin, Judith</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Aubert%2C+Grégoire%22">Aubert, Grégoire</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Huguet%2C+Thierry%22">Huguet, Thierry</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Ben%2C+Cécile%22">Ben, Cécile</searchLink><br /><searchLink fieldCode="AR" term="%22Prosperi%2C+Jean-Marie%22">Prosperi, Jean-Marie</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Salon%2C+Christophe%22">Salon, Christophe</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Munier-Jolain%2C+Nathalie%22">Munier-Jolain, Nathalie</searchLink><relatesTo>1</relatesTo>
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  Data: 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 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 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. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Theoretical & Applied Genetics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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