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Transcriptome and metabolome analysis of plant sulfate starvation and resupply provides novel information on transcriptional regulation of metabolism associated with sulfur, nitrogen and phosphorus nutritional responses in Arabidopsis.

Bielecka M, Watanabe M, Morcuende R, Scheible WR, Hawkesford MJ, Hesse H, Hoefgen R - Front Plant Sci (2015)

Bottom Line: Additionally, combinations of transcriptome and metabolome data allowed identification of relationships between TFs and downstream responses, namely, expression changes in biosynthetic genes and subsequent metabolic responses.Effect chains on glucosinolate and polyamine biosynthesis are discussed in detail.The knowledge gained from this study provides a blueprint for an integrated analysis of transcriptomics and metabolomics and application for the identification of uncharacterized genes.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmaceutical Biotechnology, Faculty of Pharmacy, Wroclaw Medical University Wroclaw, Poland ; Max-Planck Institute of Molecular Plant Physiology Potsdam-Golm, Germany.

ABSTRACT
Sulfur is an essential macronutrient for plant growth and development. Reaching a thorough understanding of the molecular basis for changes in plant metabolism depending on the sulfur-nutritional status at the systems level will advance our basic knowledge and help target future crop improvement. Although the transcriptional responses induced by sulfate starvation have been studied in the past, knowledge of the regulation of sulfur metabolism is still fragmentary. This work focuses on the discovery of candidates for regulatory genes such as transcription factors (TFs) using 'omics technologies. For this purpose a short term sulfate-starvation/re-supply approach was used. ATH1 microarray studies and metabolite determinations yielded 21 TFs which responded more than 2-fold at the transcriptional level to sulfate starvation. Categorization by response behaviors under sulfate-starvation/re-supply and other nutrient starvations such as nitrate and phosphate allowed determination of whether the TF genes are specific for or common between distinct mineral nutrient depletions. Extending this co-behavior analysis to the whole transcriptome data set enabled prediction of putative downstream genes. Additionally, combinations of transcriptome and metabolome data allowed identification of relationships between TFs and downstream responses, namely, expression changes in biosynthetic genes and subsequent metabolic responses. Effect chains on glucosinolate and polyamine biosynthesis are discussed in detail. The knowledge gained from this study provides a blueprint for an integrated analysis of transcriptomics and metabolomics and application for the identification of uncharacterized genes.

No MeSH data available.


Related in: MedlinePlus

Figure 7. Gene expression changes in known transcription factors and the downstream genes. (A) Methionine derived glucosinolates (Met-GLSs). (B) Tryptophan derived glucosinolates (Indole-GLSs). (C) Anthocyanin AGI IDs and full names of genes are in Supplemental Table SV. Values are in log2 scale.
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Figure 7: Figure 7. Gene expression changes in known transcription factors and the downstream genes. (A) Methionine derived glucosinolates (Met-GLSs). (B) Tryptophan derived glucosinolates (Indole-GLSs). (C) Anthocyanin AGI IDs and full names of genes are in Supplemental Table SV. Values are in log2 scale.

Mentions: MYB75/PAP1 expression was up-regulated (Figures 3, 5) and MYB29 down-regulated (Figure 6) under sulfate starvation. These genes were reported to be positive regulators of anthocyanin production and glucosinolate production, respectively (Borevitz et al., 2000; Hirai et al., 2007). Additional TFs were reported to be involved in regulating anthocyanin production (MYB90/PAP2, MYB113, and MYB114 for anthocyanin, TT8 (TRANSPARENT TESTA8); bHLH, TTG1 (TRANSPARENT TESTA GLABRA1); WD40 and TTG2 (TRANSPARENT TESTA GLABRA2); WRKY for flavonoids) (Tohge et al., 2013) and glucosinolate production [MYB28 and MYB76 for methionine derived glucosinolates (Met-GLSs), and MYB34, MYB51, and MYB122 for tryptophan derived glucosinolates (indole-GLSs)] (Celenza et al., 2005; Hirai et al., 2007; Sonderby et al., 2007; Gigolashvili et al., 2007a, b, 2008; Malitsky et al., 2008). We investigated whether these TFs were responding to sulfate starvation similarly to MYB75/PAP1 and MYB29, and we further screened whether the respective downstream target genes of the biosynthetic pathways showed any correlation in expression characteristics (Figure 7). For this, we additionally included values with “absent” calls. Biosynthetic genes, which are involved in production of both Met-GLSs and indole-GLSs were down regulated under –S conditions and re-induced under re-supply of sulfate (Figure 4). The gene expression patterns of the biosynthetic genes specifically followed that of MYB29 (Figure 7A). MYB34 also showed a similar pattern to the biosynthetic genes, but with smaller changes in expression (Figure 7B). These results suggest that MYB29 and MYB34 seem to be major regulators under sulfate starvation for Met-GLSs and indole-GLSs, respectively. MYB75/PAP1 was an up-regulated gene and clustered to class IV, which showed a slow tendency for being repressed with re-supply of sulfate (Figure 3). The gene expression patterns of anthocyanin biosynthetic genes and other TFs followed that of PAP1 in experiment 1, although other TFs, except for PAP2, showed changes lower than the previously applied threshold (Figure 7C). In experiment 2, biosynthetic genes showed smaller changes in expression compared to experiment 1 and mixed patterns, which might be caused by the mixed patterns of other TFs such as PAP2, TT8, and MYB114.


Transcriptome and metabolome analysis of plant sulfate starvation and resupply provides novel information on transcriptional regulation of metabolism associated with sulfur, nitrogen and phosphorus nutritional responses in Arabidopsis.

Bielecka M, Watanabe M, Morcuende R, Scheible WR, Hawkesford MJ, Hesse H, Hoefgen R - Front Plant Sci (2015)

Figure 7. Gene expression changes in known transcription factors and the downstream genes. (A) Methionine derived glucosinolates (Met-GLSs). (B) Tryptophan derived glucosinolates (Indole-GLSs). (C) Anthocyanin AGI IDs and full names of genes are in Supplemental Table SV. Values are in log2 scale.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4309162&req=5

Figure 7: Figure 7. Gene expression changes in known transcription factors and the downstream genes. (A) Methionine derived glucosinolates (Met-GLSs). (B) Tryptophan derived glucosinolates (Indole-GLSs). (C) Anthocyanin AGI IDs and full names of genes are in Supplemental Table SV. Values are in log2 scale.
Mentions: MYB75/PAP1 expression was up-regulated (Figures 3, 5) and MYB29 down-regulated (Figure 6) under sulfate starvation. These genes were reported to be positive regulators of anthocyanin production and glucosinolate production, respectively (Borevitz et al., 2000; Hirai et al., 2007). Additional TFs were reported to be involved in regulating anthocyanin production (MYB90/PAP2, MYB113, and MYB114 for anthocyanin, TT8 (TRANSPARENT TESTA8); bHLH, TTG1 (TRANSPARENT TESTA GLABRA1); WD40 and TTG2 (TRANSPARENT TESTA GLABRA2); WRKY for flavonoids) (Tohge et al., 2013) and glucosinolate production [MYB28 and MYB76 for methionine derived glucosinolates (Met-GLSs), and MYB34, MYB51, and MYB122 for tryptophan derived glucosinolates (indole-GLSs)] (Celenza et al., 2005; Hirai et al., 2007; Sonderby et al., 2007; Gigolashvili et al., 2007a, b, 2008; Malitsky et al., 2008). We investigated whether these TFs were responding to sulfate starvation similarly to MYB75/PAP1 and MYB29, and we further screened whether the respective downstream target genes of the biosynthetic pathways showed any correlation in expression characteristics (Figure 7). For this, we additionally included values with “absent” calls. Biosynthetic genes, which are involved in production of both Met-GLSs and indole-GLSs were down regulated under –S conditions and re-induced under re-supply of sulfate (Figure 4). The gene expression patterns of the biosynthetic genes specifically followed that of MYB29 (Figure 7A). MYB34 also showed a similar pattern to the biosynthetic genes, but with smaller changes in expression (Figure 7B). These results suggest that MYB29 and MYB34 seem to be major regulators under sulfate starvation for Met-GLSs and indole-GLSs, respectively. MYB75/PAP1 was an up-regulated gene and clustered to class IV, which showed a slow tendency for being repressed with re-supply of sulfate (Figure 3). The gene expression patterns of anthocyanin biosynthetic genes and other TFs followed that of PAP1 in experiment 1, although other TFs, except for PAP2, showed changes lower than the previously applied threshold (Figure 7C). In experiment 2, biosynthetic genes showed smaller changes in expression compared to experiment 1 and mixed patterns, which might be caused by the mixed patterns of other TFs such as PAP2, TT8, and MYB114.

Bottom Line: Additionally, combinations of transcriptome and metabolome data allowed identification of relationships between TFs and downstream responses, namely, expression changes in biosynthetic genes and subsequent metabolic responses.Effect chains on glucosinolate and polyamine biosynthesis are discussed in detail.The knowledge gained from this study provides a blueprint for an integrated analysis of transcriptomics and metabolomics and application for the identification of uncharacterized genes.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmaceutical Biotechnology, Faculty of Pharmacy, Wroclaw Medical University Wroclaw, Poland ; Max-Planck Institute of Molecular Plant Physiology Potsdam-Golm, Germany.

ABSTRACT
Sulfur is an essential macronutrient for plant growth and development. Reaching a thorough understanding of the molecular basis for changes in plant metabolism depending on the sulfur-nutritional status at the systems level will advance our basic knowledge and help target future crop improvement. Although the transcriptional responses induced by sulfate starvation have been studied in the past, knowledge of the regulation of sulfur metabolism is still fragmentary. This work focuses on the discovery of candidates for regulatory genes such as transcription factors (TFs) using 'omics technologies. For this purpose a short term sulfate-starvation/re-supply approach was used. ATH1 microarray studies and metabolite determinations yielded 21 TFs which responded more than 2-fold at the transcriptional level to sulfate starvation. Categorization by response behaviors under sulfate-starvation/re-supply and other nutrient starvations such as nitrate and phosphate allowed determination of whether the TF genes are specific for or common between distinct mineral nutrient depletions. Extending this co-behavior analysis to the whole transcriptome data set enabled prediction of putative downstream genes. Additionally, combinations of transcriptome and metabolome data allowed identification of relationships between TFs and downstream responses, namely, expression changes in biosynthetic genes and subsequent metabolic responses. Effect chains on glucosinolate and polyamine biosynthesis are discussed in detail. The knowledge gained from this study provides a blueprint for an integrated analysis of transcriptomics and metabolomics and application for the identification of uncharacterized genes.

No MeSH data available.


Related in: MedlinePlus