Transcriptomic and Co-Expression Network Profiling of Shoot Apical Meristem Reveal Contrasting Response to Nitrogen Rate between Indica and Japonica Rice Subspecies
Reducing nitrogen (N) input is a key measure to achieve a sustainable rice production in China, especially in Jiangsu Province. Tiller is the basis for achieving panicle number that plays as a major factor in the yield determination. In actual production, excessive N is often applied in order to produce enough tillers in the early stages. Understanding how N regulates tillering in rice plants is critical to generate an integrative management to reduce N use and reaching tiller number target. Aiming at this objective, we utilized RNA sequencing and weighted gene co-expression network analysis (WGCNA) to compare the transcriptomes surrounding the shoot apical meristem of indica (Yangdao6, YD6) and japonica (Nipponbare, NPB) rice subspecies. Our results showed that N rate influenced tiller number in a different pattern between the two varieties, with NPB being more sensitive to N enrichment, and YD6 being more tolerant to high N rate. Tiller number was positively related to N content in leaf, culm and root tissue, but negatively related to the soluble carbohydrate content, regardless of variety. Transcriptomic comparisons revealed that for YD6 when N rate enrichment from low (LN) to medium (MN), it caused 115 DEGs (LN vs. MN), from MN to high level (HN) triggered 162 DEGs (MN vs. HN), but direct comparison of low with high N rate showed a 511 DEGs (LN vs. HN). These numbers of DEG in NPB were 87 (LN vs. MN), 40 (MN vs. HN), and 148 (LN vs. HN). These differences indicate that continual N enrichment led to a bumpy change at the transcription level. For the reported sixty-five genes which affect tillering, thirty-six showed decent expression in SAM at tiller starting phase, among them only nineteen being significantly influenced by N level, and two genes showed significant interaction between N rate and variety. Gene ontology analysis revealed that the majority of the common DEGs are involved in general stress responses, stimulus responses, and hormonal signaling process. WGCNA network identified twenty-two co-expressing gene modules and ten candidate hubgenes for each module. Several genes associated with tillering and N rate fall on the related modules. These indicate that there are more genes participating in tillering regulation in response to N enrichment.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2019 |
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| Erschienen: |
2019 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:20 |
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| Enthalten in: |
International journal of molecular sciences - 20(2019), 23 vom: 25. Nov. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Zhang, Xiaoxiang [VerfasserIn] |
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| Links: |
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| Themen: |
Co-expression network |
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| Anmerkungen: |
Date Completed 04.05.2020 Date Revised 05.05.2020 published: Electronic Citation Status MEDLINE |
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| doi: |
10.3390/ijms20235922 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM303775807 |
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| 100 | 1 | |a Zhang, Xiaoxiang |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Transcriptomic and Co-Expression Network Profiling of Shoot Apical Meristem Reveal Contrasting Response to Nitrogen Rate between Indica and Japonica Rice Subspecies |
| 264 | 1 | |c 2019 | |
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| 500 | |a Date Revised 05.05.2020 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Reducing nitrogen (N) input is a key measure to achieve a sustainable rice production in China, especially in Jiangsu Province. Tiller is the basis for achieving panicle number that plays as a major factor in the yield determination. In actual production, excessive N is often applied in order to produce enough tillers in the early stages. Understanding how N regulates tillering in rice plants is critical to generate an integrative management to reduce N use and reaching tiller number target. Aiming at this objective, we utilized RNA sequencing and weighted gene co-expression network analysis (WGCNA) to compare the transcriptomes surrounding the shoot apical meristem of indica (Yangdao6, YD6) and japonica (Nipponbare, NPB) rice subspecies. Our results showed that N rate influenced tiller number in a different pattern between the two varieties, with NPB being more sensitive to N enrichment, and YD6 being more tolerant to high N rate. Tiller number was positively related to N content in leaf, culm and root tissue, but negatively related to the soluble carbohydrate content, regardless of variety. Transcriptomic comparisons revealed that for YD6 when N rate enrichment from low (LN) to medium (MN), it caused 115 DEGs (LN vs. MN), from MN to high level (HN) triggered 162 DEGs (MN vs. HN), but direct comparison of low with high N rate showed a 511 DEGs (LN vs. HN). These numbers of DEG in NPB were 87 (LN vs. MN), 40 (MN vs. HN), and 148 (LN vs. HN). These differences indicate that continual N enrichment led to a bumpy change at the transcription level. For the reported sixty-five genes which affect tillering, thirty-six showed decent expression in SAM at tiller starting phase, among them only nineteen being significantly influenced by N level, and two genes showed significant interaction between N rate and variety. Gene ontology analysis revealed that the majority of the common DEGs are involved in general stress responses, stimulus responses, and hormonal signaling process. WGCNA network identified twenty-two co-expressing gene modules and ten candidate hubgenes for each module. Several genes associated with tillering and N rate fall on the related modules. These indicate that there are more genes participating in tillering regulation in response to N enrichment | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a co-expression network | |
| 650 | 4 | |a nitrogen rate | |
| 650 | 4 | |a rice (Oryza sativa L.) | |
| 650 | 4 | |a shoot apical meristem | |
| 650 | 4 | |a tiller | |
| 650 | 4 | |a transcriptomic analysis | |
| 650 | 7 | |a Plant Proteins |2 NLM | |
| 650 | 7 | |a Nitrogen |2 NLM | |
| 650 | 7 | |a N762921K75 |2 NLM | |
| 700 | 1 | |a Zhou, Juan |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Niansheng |e verfasserin |4 aut | |
| 700 | 1 | |a Mo, Lanjing |e verfasserin |4 aut | |
| 700 | 1 | |a Lv, Minjia |e verfasserin |4 aut | |
| 700 | 1 | |a Gao, Yingbo |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Chen |e verfasserin |4 aut | |
| 700 | 1 | |a Yin, Shuangyi |e verfasserin |4 aut | |
| 700 | 1 | |a Ju, Jing |e verfasserin |4 aut | |
| 700 | 1 | |a Dong, Guichun |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Yong |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Zefeng |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Aihong |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Yulong |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Jianye |e verfasserin |4 aut | |
| 700 | 1 | |a Yao, Youli |e verfasserin |4 aut | |
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| 856 | 4 | 0 | |u http://dx.doi.org/10.3390/ijms20235922 |3 Volltext |
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