A computational framework for evaluating the efficiency of Arabidopsis accessions in response to nitrogen stress reveals important metabolic mechanisms
High-throughput phenotyping technologies in combination with genetic variability for the plant model species Arabidopsis thaliana (Arabidopsis) offer an excellent experimental platform to reveal the effects of different gene combinations on phenotypes. These developments have been coupled with compu...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2012-09-01
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| Series: | Frontiers in Plant Science |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fpls.2012.00217/full |
| _version_ | 1811276059042119680 |
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| author | Sabrina eKleessen Alisdair R Fernie Zoran eNikoloski |
| author_facet | Sabrina eKleessen Alisdair R Fernie Zoran eNikoloski |
| author_sort | Sabrina eKleessen |
| collection | DOAJ |
| description | High-throughput phenotyping technologies in combination with genetic variability for the plant model species Arabidopsis thaliana (Arabidopsis) offer an excellent experimental platform to reveal the effects of different gene combinations on phenotypes. These developments have been coupled with computational approaches to extract information not only from the multidimensional data, capturing various levels of biochemical organization, but also from various morphological and growth-related traits. Nevertheless, the existing methods usually focus on data aggregation which may neglect accession-specific effects. Here we argue that revealing the molecular mechanisms governing a desired set of output traits can be performed by ranking of accessions based on their efficiencies relative to all other analyzed accessions. To this end, we propose a framework for evaluating accessions via their relative efficiencies which relate multidimensional system's inputs and outputs from different environmental conditions. The framework combines data envelopment analysis (DEA) with a novel valency index characterizing the difference in congruence between the efficiency rankings of accessions under various conditions. We illustrate the advantages of the proposed approach for analyzing genetic variability on a publicly available data set comprising quantitative data on metabolic and morphological traits for 23 Arabidopsis accessions under three conditions of nitrogen availability. In addition, we extend the proposed framework to identify the set of traits displaying the highest influence on ranking based on the relative efficiencies of the considered accessions. As an outlook, we discuss how the proposed framework can be combined with well-established statistical techniques to further dissect the relationship between natural variability and metabolism. |
| first_indexed | 2024-04-12T23:48:38Z |
| format | Article |
| id | doaj.art-f226e876002c4f6a929bd1a0aabf1527 |
| institution | Directory Open Access Journal |
| issn | 1664-462X |
| language | English |
| last_indexed | 2024-04-12T23:48:38Z |
| publishDate | 2012-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj.art-f226e876002c4f6a929bd1a0aabf15272022-12-22T03:11:46ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2012-09-01310.3389/fpls.2012.0021730553A computational framework for evaluating the efficiency of Arabidopsis accessions in response to nitrogen stress reveals important metabolic mechanismsSabrina eKleessen0Alisdair R Fernie1Zoran eNikoloski2Max-Planck Institute of Molecular Plant PhysiologyMax-Planck Institute of Molecular Plant PhysiologyMax-Planck Institute of Molecular Plant PhysiologyHigh-throughput phenotyping technologies in combination with genetic variability for the plant model species Arabidopsis thaliana (Arabidopsis) offer an excellent experimental platform to reveal the effects of different gene combinations on phenotypes. These developments have been coupled with computational approaches to extract information not only from the multidimensional data, capturing various levels of biochemical organization, but also from various morphological and growth-related traits. Nevertheless, the existing methods usually focus on data aggregation which may neglect accession-specific effects. Here we argue that revealing the molecular mechanisms governing a desired set of output traits can be performed by ranking of accessions based on their efficiencies relative to all other analyzed accessions. To this end, we propose a framework for evaluating accessions via their relative efficiencies which relate multidimensional system's inputs and outputs from different environmental conditions. The framework combines data envelopment analysis (DEA) with a novel valency index characterizing the difference in congruence between the efficiency rankings of accessions under various conditions. We illustrate the advantages of the proposed approach for analyzing genetic variability on a publicly available data set comprising quantitative data on metabolic and morphological traits for 23 Arabidopsis accessions under three conditions of nitrogen availability. In addition, we extend the proposed framework to identify the set of traits displaying the highest influence on ranking based on the relative efficiencies of the considered accessions. As an outlook, we discuss how the proposed framework can be combined with well-established statistical techniques to further dissect the relationship between natural variability and metabolism.http://journal.frontiersin.org/Journal/10.3389/fpls.2012.00217/fullEfficiencyMetabolomicsMultivariate data analysisdata envelopment analysisgenotypes |
| spellingShingle | Sabrina eKleessen Alisdair R Fernie Zoran eNikoloski A computational framework for evaluating the efficiency of Arabidopsis accessions in response to nitrogen stress reveals important metabolic mechanisms Frontiers in Plant Science Efficiency Metabolomics Multivariate data analysis data envelopment analysis genotypes |
| title | A computational framework for evaluating the efficiency of Arabidopsis accessions in response to nitrogen stress reveals important metabolic mechanisms |
| title_full | A computational framework for evaluating the efficiency of Arabidopsis accessions in response to nitrogen stress reveals important metabolic mechanisms |
| title_fullStr | A computational framework for evaluating the efficiency of Arabidopsis accessions in response to nitrogen stress reveals important metabolic mechanisms |
| title_full_unstemmed | A computational framework for evaluating the efficiency of Arabidopsis accessions in response to nitrogen stress reveals important metabolic mechanisms |
| title_short | A computational framework for evaluating the efficiency of Arabidopsis accessions in response to nitrogen stress reveals important metabolic mechanisms |
| title_sort | computational framework for evaluating the efficiency of arabidopsis accessions in response to nitrogen stress reveals important metabolic mechanisms |
| topic | Efficiency Metabolomics Multivariate data analysis data envelopment analysis genotypes |
| url | http://journal.frontiersin.org/Journal/10.3389/fpls.2012.00217/full |
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