| 000 | 02519nab|a22003617a|4500 | ||
|---|---|---|---|
| 999 |
_c62732 _d62724 |
||
| 001 | 62732 | ||
| 003 | MX-TxCIM | ||
| 005 | 20211006072310.0 | ||
| 008 | 200423s2020||||xxk|||p|op||||00||0|eng|d | ||
| 022 | _a2045-2322 | ||
| 024 | 8 | _ahttps://doi.org/10.1038/s41598-020-64660-7 | |
| 040 | _aMX-TxCIM | ||
| 041 | _aeng | ||
| 100 | 0 |
_aHongying Duan _916497 |
|
| 245 | 1 | 0 | _aResponsive changes of DNA methylation in wheat (Triticum aestivum) under water deficit |
| 260 |
_aLondon (United Kingdom) : _bNature Publishing Group, _c2020. |
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| 500 | _aPeer review | ||
| 500 | _aOpen Access | ||
| 520 | _aDNA methylation plays an important role in the growth and development of plant, and would change under different environments. In this study, 5-methyl cytosine (5mC) content and methylation level exhibited tissue specificity in genomic DNA of wheat seedling, and increased significantly in leaf along with the increase of water deficit, which was especially significant in leaf of wheat AK58. Full-methylation might dominate in genomic DNA of wheat seedling, the increase of full-methylation level under water deficit was significantly higher than that of hemi-methylation level. Under water deficit, DNA methylation of wheat seedling showed significant polymorphism, this polymorphism was always higher in root, especially was higher in root of wheat AK58. Further analysis appeared that changes of DNA methylation in wheat seedling took methylation as principle and demethylation as supplement under water deficit. Therefore, under water deficit, the degree, level and polymorphism of DNA methylation in wheat seedling showed tissue specificity and species specificity, and were higher in wheat AK58 compared with those of wheat XM13, perhaps wheat AK58 could more rapidly respond to water deficit by changes of DNA methylation, which would contribute to reveal molecular mechanism of wheat adapting to water deficit. | ||
| 546 | _aText in English | ||
| 650 | 7 |
_2AGROVOC _91080 _aDrought |
|
| 650 | 7 |
_aWheat _gAGROVOC _2 _91310 |
|
| 650 | 7 |
_2AGROVOC _913434 _aDNA |
|
| 700 | 0 |
_aJingyun Li _916498 |
|
| 700 | 0 |
_aYanqiu Zhu _916499 |
|
| 700 | 0 |
_aWenjing Jia _916500 |
|
| 700 | 0 |
_aHuihui Wang _916501 |
|
| 700 | 0 |
_aLina Jiang _916502 |
|
| 700 | 0 |
_aYanqing Zhou _916503 |
|
| 773 | 0 |
_tNature Scientific Reports _gv. 10, art. 7938 _dLondon (United Kingdom) : Nature Publishing Group, 2020. _x2045-2322 _wa58025 |
|
| 856 | 4 |
_yClick here to access online _uhttps://doi.org/10.1038/s41598-020-64660-7 |
|
| 942 |
_cJA _n0 _2ddc |
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