| 000 | 02528nab|a22003377a|4500 | ||
|---|---|---|---|
| 999 |
_c64154 _d64146 |
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| 001 | 64154 | ||
| 003 | MX-TxCIM | ||
| 005 | 20211006075200.0 | ||
| 008 | 201209s2021||||xxk|||p|op||||00||0|eng|d | ||
| 022 | _a2045-2322 | ||
| 024 | 8 | _ahttps://doi.org/10.1038/s41598-021-86259-2 | |
| 040 | _aMX-TxCIM | ||
| 041 | _aeng | ||
| 100 | 1 |
_aKhahani, B. _922675 |
|
| 245 | 1 | 0 | _aMeta-QTL and ortho-MQTL analyses identified genomic regions controlling rice yield, yield-related traits and root architecture under water deficit conditions |
| 260 |
_aLondon (United Kingdom) : _bNature Publishing Group, _c2021. |
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| 500 | _aPeer review | ||
| 500 | _aOpen Access | ||
| 520 | _aMeta-QTL (MQTL) analysis is a robust approach for genetic dissection of complex quantitative traits. Rice varieties adapted to non-flooded cultivation are highly desirable in breeding programs due to the water deficit global problem. In order to identify stable QTLs for major agronomic traits under water deficit conditions, we performed a comprehensive MQTL analysis on 563 QTLs from 67 rice populations published from 2001 to 2019. Yield and yield-related traits including grain weight, heading date, plant height, tiller number as well as root architecture-related traits including root dry weight, root length, root number, root thickness, the ratio of deep rooting and plant water content under water deficit condition were investigated. A total of 61 stable MQTLs over different genetic backgrounds and environments were identified. The average confidence interval of MQTLs was considerably refined compared to the initial QTLs, resulted in the identification of some well-known functionally characterized genes and several putative novel CGs for investigated traits. Ortho-MQTL mining based on genomic collinearity between rice and maize allowed identification of five ortho-MQTLs between these two cereals. The results can help breeders to improve yield under water deficit conditions. | ||
| 546 | _aText in English | ||
| 650 | 7 |
_aGenomics _2AGROVOC _91132 |
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| 650 | 7 |
_aRice _gAGROVOC _2 _91243 |
|
| 650 | 7 |
_aQuantitative Trait Loci _2AGROVOC _91853 |
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| 650 | 7 |
_aWater depletion _2AGROVOC _912959 |
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| 700 | 1 |
_aTavakol, E. _922677 |
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| 700 | 1 |
_aShariati, V. _922676 |
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| 700 | 1 |
_aRossini, L. _922678 |
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| 773 | 0 |
_gv. 11, art. 6942 _dLondon (United Kingdom) : Nature Publishing Group, 2021. _x2045-2322 _tNature Scientific Reports _wa58025 |
|
| 856 | 4 |
_yClick here to access online _uhttps://doi.org/10.1038/s41598-021-86259-2 |
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| 942 |
_cJA _n0 _2ddc |
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