| 000 | 02625nab a22004457a 4500 | ||
|---|---|---|---|
| 999 |
_c62496 _d62488 |
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| 001 | 62496 | ||
| 003 | MX-TxCIM | ||
| 005 | 20211006082419.0 | ||
| 008 | 200212s2020 xxk|||p|op||| 00| 0 eng d | ||
| 022 | _a1467-7644 | ||
| 022 | _a1467-7652 (Online) | ||
| 024 | 8 | _ahttps://doi.org/10.1111/pbi.13335 | |
| 040 | _aMX-TxCIM | ||
| 041 | _aeng | ||
| 100 | 0 |
_98340 _aJie Chen |
|
| 245 | 1 | 0 | _aMetabolite‐based genome‐wide association study enables dissection of the flavonoid decoration pathway of wheat kernels |
| 260 |
_aOxford (United Kingdom) : _bWiley, _c2020. |
||
| 500 | _aPeer review | ||
| 500 | _aOpen Access | ||
| 520 | _aThe marriage of metabolomic approaches with genetic design has proven a powerful tool in dissecting diversity in the metabolome and has additionally enhanced our understanding of complex traits. That said, such studies have rarely been carried out in wheat. In this study, we detected 805 metabolites from wheat kernels and profiled their relative contents among 182 wheat accessions, conducting a metabolite‐based genome‐wide association study (mGWAS) utilizing 14 646 previously described polymorphic SNP markers. A total of 1098 mGWAS associations were detected with large effects, within which 26 candidate genes were tentatively designated for 42 loci. Enzymatic assay of two candidates indicated they could catalyse glucosylation and subsequent malonylation of various flavonoids and thereby the major flavonoid decoration pathway of wheat kernel was dissected. Moreover, numerous high‐confidence genes associated with metabolite contents have been provided, as well as more subdivided metabolite networks which are yet to be explored within our data. These combined efforts presented the first step towards realizing metabolomics‐associated breeding of wheat. | ||
| 526 | _aWC | ||
| 546 | _aText in English | ||
| 650 | 7 |
_2AGROVOC _912884 _aFlavonoids |
|
| 650 | 7 |
_2AGROVOC _98948 _aMetabolites |
|
| 650 | 7 |
_aWheat _gAGROVOC _2 _91310 |
|
| 650 | 7 |
_2AGROVOC _91168 _aKernels |
|
| 700 | 0 |
_915512 _aXin Hu |
|
| 700 | 0 |
_98341 _aTaotao Shi |
|
| 700 | 0 |
_915513 _aHuanran Yin |
|
| 700 | 0 |
_98343 _aDongfa Sun |
|
| 700 | 1 |
_9919 _aYuanfeng Hao |
|
| 700 | 0 |
_9377 _aXianchun Xia |
|
| 700 | 0 |
_915514 _aJie Luo |
|
| 700 | 1 |
_92019 _aFernie, A.R. |
|
| 700 | 1 |
_aHe Zhonghu _gGlobal Wheat Program _8INT2411 _9838 |
|
| 700 | 0 |
_92613 _aWei Chen |
|
| 773 | 0 |
_dOxford (United Kingdom) : Wiley, 2020. _gv. 18, no. 8, p. 1722-1735 _tPlant Biotechnology Journal _x1467-7652 _wu57523 |
|
| 856 | 4 |
_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/20943 |
|
| 942 |
_2ddc _cJA _n0 |
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