Multidimensional patterns of metabolic response in abiotic stress-induced growth of Arabidopsis thaliana
Key message Contextualization of specific transcriptional responses of Arabidopsis within the stress–tissue–time perspective provides a simplified representation of the cellular transcriptional response pathways to abiotic stress, while reducing the dimensions in gene-oriented response description....
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Yadav, Brijesh S. [verfasserIn] Lahav, Tamar [verfasserIn] Reuveni, Eli [verfasserIn] Chamovitz, Daniel A. [verfasserIn] Freilich, Shiri [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Plant molecular biology - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981, 92(2016), 6 vom: 15. Sept., Seite 689-699 |
|---|---|
| Übergeordnetes Werk: |
volume:92 ; year:2016 ; number:6 ; day:15 ; month:09 ; pages:689-699 |
| Links: |
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| DOI / URN: |
10.1007/s11103-016-0539-7 |
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| Katalog-ID: |
SPR016688406 |
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| 245 | 1 | 0 | |a Multidimensional patterns of metabolic response in abiotic stress-induced growth of Arabidopsis thaliana |
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| 520 | |a Key message Contextualization of specific transcriptional responses of Arabidopsis within the stress–tissue–time perspective provides a simplified representation of the cellular transcriptional response pathways to abiotic stress, while reducing the dimensions in gene-oriented response description. Abstract Crops resistant to abiotic stresses are a long-term goal of many research programs, thus understanding the progression of stress responses is of great interest. We reanalyzed the AtGenExpress transcription dataset to go beyond gene-level characterization, and to contextualize the discrete information into (1) a process-level signature of stress-specific, time-specific, and tissue-specific responses and (2) identify patterns of response progression across a time axis. To gain a functional perspective, ∼1000 pathways associated with the differentially-expressed genes were characterized across all experiments. We find that the global response of pathways to stress is multi-dimensional and does not obviously cluster according to stress, time or tissue. The early response to abiotic stress typically involves induction of genes involved in transcription, hormone synthesis and signaling modules; a later response typically involves metabolism of amino acids and secondary metabolites. By linking specific primary and secondary response pathways, we outline possible stress-associated routes of response progression. The contextualization of specific processes within stress–tissue–time perspective provides a simplified representation of cellular response while reducing the dimensions in gene-oriented response description. Such simplified representation allows finding stress-specific markers based on process-combinations pointing whether a stress-specific response was invoked as well as provide a reference point for the conductance of comparative inter-plant study of stress response, bypassing the need in detailed orthologous mapping. | ||
| 650 | 4 | |a Abiotic Stress |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Metabolic Response |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Expression data |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Pathway analysis |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Lahav, Tamar |e verfasserin |4 aut | |
| 700 | 1 | |a Reuveni, Eli |e verfasserin |4 aut | |
| 700 | 1 | |a Chamovitz, Daniel A. |e verfasserin |4 aut | |
| 700 | 1 | |a Freilich, Shiri |e verfasserin |4 aut | |
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10.1007/s11103-016-0539-7 doi (DE-627)SPR016688406 (SPR)s11103-016-0539-7-e DE-627 ger DE-627 rakwb eng 580 ASE 42.43 bkl 48.58 bkl Yadav, Brijesh S. verfasserin aut Multidimensional patterns of metabolic response in abiotic stress-induced growth of Arabidopsis thaliana 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Key message Contextualization of specific transcriptional responses of Arabidopsis within the stress–tissue–time perspective provides a simplified representation of the cellular transcriptional response pathways to abiotic stress, while reducing the dimensions in gene-oriented response description. Abstract Crops resistant to abiotic stresses are a long-term goal of many research programs, thus understanding the progression of stress responses is of great interest. We reanalyzed the AtGenExpress transcription dataset to go beyond gene-level characterization, and to contextualize the discrete information into (1) a process-level signature of stress-specific, time-specific, and tissue-specific responses and (2) identify patterns of response progression across a time axis. To gain a functional perspective, ∼1000 pathways associated with the differentially-expressed genes were characterized across all experiments. We find that the global response of pathways to stress is multi-dimensional and does not obviously cluster according to stress, time or tissue. The early response to abiotic stress typically involves induction of genes involved in transcription, hormone synthesis and signaling modules; a later response typically involves metabolism of amino acids and secondary metabolites. By linking specific primary and secondary response pathways, we outline possible stress-associated routes of response progression. The contextualization of specific processes within stress–tissue–time perspective provides a simplified representation of cellular response while reducing the dimensions in gene-oriented response description. Such simplified representation allows finding stress-specific markers based on process-combinations pointing whether a stress-specific response was invoked as well as provide a reference point for the conductance of comparative inter-plant study of stress response, bypassing the need in detailed orthologous mapping. Abiotic Stress (dpeaa)DE-He213 Metabolic Response (dpeaa)DE-He213 Expression data (dpeaa)DE-He213 Pathway analysis (dpeaa)DE-He213 Lahav, Tamar verfasserin aut Reuveni, Eli verfasserin aut Chamovitz, Daniel A. verfasserin aut Freilich, Shiri verfasserin aut Enthalten in Plant molecular biology Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 92(2016), 6 vom: 15. Sept., Seite 689-699 (DE-627)269758658 (DE-600)1475712-6 1573-5028 nnns volume:92 year:2016 number:6 day:15 month:09 pages:689-699 https://dx.doi.org/10.1007/s11103-016-0539-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.43 ASE 48.58 ASE AR 92 2016 6 15 09 689-699 |
| spelling |
10.1007/s11103-016-0539-7 doi (DE-627)SPR016688406 (SPR)s11103-016-0539-7-e DE-627 ger DE-627 rakwb eng 580 ASE 42.43 bkl 48.58 bkl Yadav, Brijesh S. verfasserin aut Multidimensional patterns of metabolic response in abiotic stress-induced growth of Arabidopsis thaliana 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Key message Contextualization of specific transcriptional responses of Arabidopsis within the stress–tissue–time perspective provides a simplified representation of the cellular transcriptional response pathways to abiotic stress, while reducing the dimensions in gene-oriented response description. Abstract Crops resistant to abiotic stresses are a long-term goal of many research programs, thus understanding the progression of stress responses is of great interest. We reanalyzed the AtGenExpress transcription dataset to go beyond gene-level characterization, and to contextualize the discrete information into (1) a process-level signature of stress-specific, time-specific, and tissue-specific responses and (2) identify patterns of response progression across a time axis. To gain a functional perspective, ∼1000 pathways associated with the differentially-expressed genes were characterized across all experiments. We find that the global response of pathways to stress is multi-dimensional and does not obviously cluster according to stress, time or tissue. The early response to abiotic stress typically involves induction of genes involved in transcription, hormone synthesis and signaling modules; a later response typically involves metabolism of amino acids and secondary metabolites. By linking specific primary and secondary response pathways, we outline possible stress-associated routes of response progression. The contextualization of specific processes within stress–tissue–time perspective provides a simplified representation of cellular response while reducing the dimensions in gene-oriented response description. Such simplified representation allows finding stress-specific markers based on process-combinations pointing whether a stress-specific response was invoked as well as provide a reference point for the conductance of comparative inter-plant study of stress response, bypassing the need in detailed orthologous mapping. Abiotic Stress (dpeaa)DE-He213 Metabolic Response (dpeaa)DE-He213 Expression data (dpeaa)DE-He213 Pathway analysis (dpeaa)DE-He213 Lahav, Tamar verfasserin aut Reuveni, Eli verfasserin aut Chamovitz, Daniel A. verfasserin aut Freilich, Shiri verfasserin aut Enthalten in Plant molecular biology Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 92(2016), 6 vom: 15. Sept., Seite 689-699 (DE-627)269758658 (DE-600)1475712-6 1573-5028 nnns volume:92 year:2016 number:6 day:15 month:09 pages:689-699 https://dx.doi.org/10.1007/s11103-016-0539-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.43 ASE 48.58 ASE AR 92 2016 6 15 09 689-699 |
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10.1007/s11103-016-0539-7 doi (DE-627)SPR016688406 (SPR)s11103-016-0539-7-e DE-627 ger DE-627 rakwb eng 580 ASE 42.43 bkl 48.58 bkl Yadav, Brijesh S. verfasserin aut Multidimensional patterns of metabolic response in abiotic stress-induced growth of Arabidopsis thaliana 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Key message Contextualization of specific transcriptional responses of Arabidopsis within the stress–tissue–time perspective provides a simplified representation of the cellular transcriptional response pathways to abiotic stress, while reducing the dimensions in gene-oriented response description. Abstract Crops resistant to abiotic stresses are a long-term goal of many research programs, thus understanding the progression of stress responses is of great interest. We reanalyzed the AtGenExpress transcription dataset to go beyond gene-level characterization, and to contextualize the discrete information into (1) a process-level signature of stress-specific, time-specific, and tissue-specific responses and (2) identify patterns of response progression across a time axis. To gain a functional perspective, ∼1000 pathways associated with the differentially-expressed genes were characterized across all experiments. We find that the global response of pathways to stress is multi-dimensional and does not obviously cluster according to stress, time or tissue. The early response to abiotic stress typically involves induction of genes involved in transcription, hormone synthesis and signaling modules; a later response typically involves metabolism of amino acids and secondary metabolites. By linking specific primary and secondary response pathways, we outline possible stress-associated routes of response progression. The contextualization of specific processes within stress–tissue–time perspective provides a simplified representation of cellular response while reducing the dimensions in gene-oriented response description. Such simplified representation allows finding stress-specific markers based on process-combinations pointing whether a stress-specific response was invoked as well as provide a reference point for the conductance of comparative inter-plant study of stress response, bypassing the need in detailed orthologous mapping. Abiotic Stress (dpeaa)DE-He213 Metabolic Response (dpeaa)DE-He213 Expression data (dpeaa)DE-He213 Pathway analysis (dpeaa)DE-He213 Lahav, Tamar verfasserin aut Reuveni, Eli verfasserin aut Chamovitz, Daniel A. verfasserin aut Freilich, Shiri verfasserin aut Enthalten in Plant molecular biology Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 92(2016), 6 vom: 15. Sept., Seite 689-699 (DE-627)269758658 (DE-600)1475712-6 1573-5028 nnns volume:92 year:2016 number:6 day:15 month:09 pages:689-699 https://dx.doi.org/10.1007/s11103-016-0539-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.43 ASE 48.58 ASE AR 92 2016 6 15 09 689-699 |
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10.1007/s11103-016-0539-7 doi (DE-627)SPR016688406 (SPR)s11103-016-0539-7-e DE-627 ger DE-627 rakwb eng 580 ASE 42.43 bkl 48.58 bkl Yadav, Brijesh S. verfasserin aut Multidimensional patterns of metabolic response in abiotic stress-induced growth of Arabidopsis thaliana 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Key message Contextualization of specific transcriptional responses of Arabidopsis within the stress–tissue–time perspective provides a simplified representation of the cellular transcriptional response pathways to abiotic stress, while reducing the dimensions in gene-oriented response description. Abstract Crops resistant to abiotic stresses are a long-term goal of many research programs, thus understanding the progression of stress responses is of great interest. We reanalyzed the AtGenExpress transcription dataset to go beyond gene-level characterization, and to contextualize the discrete information into (1) a process-level signature of stress-specific, time-specific, and tissue-specific responses and (2) identify patterns of response progression across a time axis. To gain a functional perspective, ∼1000 pathways associated with the differentially-expressed genes were characterized across all experiments. We find that the global response of pathways to stress is multi-dimensional and does not obviously cluster according to stress, time or tissue. The early response to abiotic stress typically involves induction of genes involved in transcription, hormone synthesis and signaling modules; a later response typically involves metabolism of amino acids and secondary metabolites. By linking specific primary and secondary response pathways, we outline possible stress-associated routes of response progression. The contextualization of specific processes within stress–tissue–time perspective provides a simplified representation of cellular response while reducing the dimensions in gene-oriented response description. Such simplified representation allows finding stress-specific markers based on process-combinations pointing whether a stress-specific response was invoked as well as provide a reference point for the conductance of comparative inter-plant study of stress response, bypassing the need in detailed orthologous mapping. Abiotic Stress (dpeaa)DE-He213 Metabolic Response (dpeaa)DE-He213 Expression data (dpeaa)DE-He213 Pathway analysis (dpeaa)DE-He213 Lahav, Tamar verfasserin aut Reuveni, Eli verfasserin aut Chamovitz, Daniel A. verfasserin aut Freilich, Shiri verfasserin aut Enthalten in Plant molecular biology Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 92(2016), 6 vom: 15. Sept., Seite 689-699 (DE-627)269758658 (DE-600)1475712-6 1573-5028 nnns volume:92 year:2016 number:6 day:15 month:09 pages:689-699 https://dx.doi.org/10.1007/s11103-016-0539-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.43 ASE 48.58 ASE AR 92 2016 6 15 09 689-699 |
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10.1007/s11103-016-0539-7 doi (DE-627)SPR016688406 (SPR)s11103-016-0539-7-e DE-627 ger DE-627 rakwb eng 580 ASE 42.43 bkl 48.58 bkl Yadav, Brijesh S. verfasserin aut Multidimensional patterns of metabolic response in abiotic stress-induced growth of Arabidopsis thaliana 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Key message Contextualization of specific transcriptional responses of Arabidopsis within the stress–tissue–time perspective provides a simplified representation of the cellular transcriptional response pathways to abiotic stress, while reducing the dimensions in gene-oriented response description. Abstract Crops resistant to abiotic stresses are a long-term goal of many research programs, thus understanding the progression of stress responses is of great interest. We reanalyzed the AtGenExpress transcription dataset to go beyond gene-level characterization, and to contextualize the discrete information into (1) a process-level signature of stress-specific, time-specific, and tissue-specific responses and (2) identify patterns of response progression across a time axis. To gain a functional perspective, ∼1000 pathways associated with the differentially-expressed genes were characterized across all experiments. We find that the global response of pathways to stress is multi-dimensional and does not obviously cluster according to stress, time or tissue. The early response to abiotic stress typically involves induction of genes involved in transcription, hormone synthesis and signaling modules; a later response typically involves metabolism of amino acids and secondary metabolites. By linking specific primary and secondary response pathways, we outline possible stress-associated routes of response progression. The contextualization of specific processes within stress–tissue–time perspective provides a simplified representation of cellular response while reducing the dimensions in gene-oriented response description. Such simplified representation allows finding stress-specific markers based on process-combinations pointing whether a stress-specific response was invoked as well as provide a reference point for the conductance of comparative inter-plant study of stress response, bypassing the need in detailed orthologous mapping. Abiotic Stress (dpeaa)DE-He213 Metabolic Response (dpeaa)DE-He213 Expression data (dpeaa)DE-He213 Pathway analysis (dpeaa)DE-He213 Lahav, Tamar verfasserin aut Reuveni, Eli verfasserin aut Chamovitz, Daniel A. verfasserin aut Freilich, Shiri verfasserin aut Enthalten in Plant molecular biology Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 92(2016), 6 vom: 15. Sept., Seite 689-699 (DE-627)269758658 (DE-600)1475712-6 1573-5028 nnns volume:92 year:2016 number:6 day:15 month:09 pages:689-699 https://dx.doi.org/10.1007/s11103-016-0539-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.43 ASE 48.58 ASE AR 92 2016 6 15 09 689-699 |
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Enthalten in Plant molecular biology 92(2016), 6 vom: 15. Sept., Seite 689-699 volume:92 year:2016 number:6 day:15 month:09 pages:689-699 |
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Enthalten in Plant molecular biology 92(2016), 6 vom: 15. Sept., Seite 689-699 volume:92 year:2016 number:6 day:15 month:09 pages:689-699 |
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Abiotic Stress Metabolic Response Expression data Pathway analysis |
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Plant molecular biology |
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Yadav, Brijesh S. @@aut@@ Lahav, Tamar @@aut@@ Reuveni, Eli @@aut@@ Chamovitz, Daniel A. @@aut@@ Freilich, Shiri @@aut@@ |
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Yadav, Brijesh S. |
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Yadav, Brijesh S. ddc 580 bkl 42.43 bkl 48.58 misc Abiotic Stress misc Metabolic Response misc Expression data misc Pathway analysis Multidimensional patterns of metabolic response in abiotic stress-induced growth of Arabidopsis thaliana |
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580 ASE 42.43 bkl 48.58 bkl Multidimensional patterns of metabolic response in abiotic stress-induced growth of Arabidopsis thaliana Abiotic Stress (dpeaa)DE-He213 Metabolic Response (dpeaa)DE-He213 Expression data (dpeaa)DE-He213 Pathway analysis (dpeaa)DE-He213 |
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multidimensional patterns of metabolic response in abiotic stress-induced growth of arabidopsis thaliana |
| title_auth |
Multidimensional patterns of metabolic response in abiotic stress-induced growth of Arabidopsis thaliana |
| abstract |
Key message Contextualization of specific transcriptional responses of Arabidopsis within the stress–tissue–time perspective provides a simplified representation of the cellular transcriptional response pathways to abiotic stress, while reducing the dimensions in gene-oriented response description. Abstract Crops resistant to abiotic stresses are a long-term goal of many research programs, thus understanding the progression of stress responses is of great interest. We reanalyzed the AtGenExpress transcription dataset to go beyond gene-level characterization, and to contextualize the discrete information into (1) a process-level signature of stress-specific, time-specific, and tissue-specific responses and (2) identify patterns of response progression across a time axis. To gain a functional perspective, ∼1000 pathways associated with the differentially-expressed genes were characterized across all experiments. We find that the global response of pathways to stress is multi-dimensional and does not obviously cluster according to stress, time or tissue. The early response to abiotic stress typically involves induction of genes involved in transcription, hormone synthesis and signaling modules; a later response typically involves metabolism of amino acids and secondary metabolites. By linking specific primary and secondary response pathways, we outline possible stress-associated routes of response progression. The contextualization of specific processes within stress–tissue–time perspective provides a simplified representation of cellular response while reducing the dimensions in gene-oriented response description. Such simplified representation allows finding stress-specific markers based on process-combinations pointing whether a stress-specific response was invoked as well as provide a reference point for the conductance of comparative inter-plant study of stress response, bypassing the need in detailed orthologous mapping. |
| abstractGer |
Key message Contextualization of specific transcriptional responses of Arabidopsis within the stress–tissue–time perspective provides a simplified representation of the cellular transcriptional response pathways to abiotic stress, while reducing the dimensions in gene-oriented response description. Abstract Crops resistant to abiotic stresses are a long-term goal of many research programs, thus understanding the progression of stress responses is of great interest. We reanalyzed the AtGenExpress transcription dataset to go beyond gene-level characterization, and to contextualize the discrete information into (1) a process-level signature of stress-specific, time-specific, and tissue-specific responses and (2) identify patterns of response progression across a time axis. To gain a functional perspective, ∼1000 pathways associated with the differentially-expressed genes were characterized across all experiments. We find that the global response of pathways to stress is multi-dimensional and does not obviously cluster according to stress, time or tissue. The early response to abiotic stress typically involves induction of genes involved in transcription, hormone synthesis and signaling modules; a later response typically involves metabolism of amino acids and secondary metabolites. By linking specific primary and secondary response pathways, we outline possible stress-associated routes of response progression. The contextualization of specific processes within stress–tissue–time perspective provides a simplified representation of cellular response while reducing the dimensions in gene-oriented response description. Such simplified representation allows finding stress-specific markers based on process-combinations pointing whether a stress-specific response was invoked as well as provide a reference point for the conductance of comparative inter-plant study of stress response, bypassing the need in detailed orthologous mapping. |
| abstract_unstemmed |
Key message Contextualization of specific transcriptional responses of Arabidopsis within the stress–tissue–time perspective provides a simplified representation of the cellular transcriptional response pathways to abiotic stress, while reducing the dimensions in gene-oriented response description. Abstract Crops resistant to abiotic stresses are a long-term goal of many research programs, thus understanding the progression of stress responses is of great interest. We reanalyzed the AtGenExpress transcription dataset to go beyond gene-level characterization, and to contextualize the discrete information into (1) a process-level signature of stress-specific, time-specific, and tissue-specific responses and (2) identify patterns of response progression across a time axis. To gain a functional perspective, ∼1000 pathways associated with the differentially-expressed genes were characterized across all experiments. We find that the global response of pathways to stress is multi-dimensional and does not obviously cluster according to stress, time or tissue. The early response to abiotic stress typically involves induction of genes involved in transcription, hormone synthesis and signaling modules; a later response typically involves metabolism of amino acids and secondary metabolites. By linking specific primary and secondary response pathways, we outline possible stress-associated routes of response progression. The contextualization of specific processes within stress–tissue–time perspective provides a simplified representation of cellular response while reducing the dimensions in gene-oriented response description. Such simplified representation allows finding stress-specific markers based on process-combinations pointing whether a stress-specific response was invoked as well as provide a reference point for the conductance of comparative inter-plant study of stress response, bypassing the need in detailed orthologous mapping. |
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Multidimensional patterns of metabolic response in abiotic stress-induced growth of Arabidopsis thaliana |
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https://dx.doi.org/10.1007/s11103-016-0539-7 |
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Lahav, Tamar Reuveni, Eli Chamovitz, Daniel A. Freilich, Shiri |
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2024-07-04T00:23:03.363Z |
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| score |
7.4011183 |