| 000 | 03251nab|a22004697a|4500 | ||
|---|---|---|---|
| 001 | 65283 | ||
| 003 | MX-TxCIM | ||
| 005 | 20230217221756.0 | ||
| 008 | 202212s2022||||mx |||p|op||||00||0|eng|d | ||
| 022 | _a2045-2322 (Online) | ||
| 024 | 8 | _ahttps://doi.org/10.1038/s41598-022-10618-w | |
| 040 | _aMX-TxCIM | ||
| 041 | _aeng | ||
| 100 | 1 |
_aRathan, N.D. _917206 |
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| 245 | 1 | 1 | _aGenome-wide association study identifies loci and candidate genes for grain micronutrients and quality traits in wheat (Triticum aestivum L.) |
| 260 |
_bNature Publishing Group, _c2022. _aLondon (United Kingdom) : |
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| 500 | _aPeer review | ||
| 500 | _aOpen Access | ||
| 520 | _aMalnutrition due to micronutrients and protein deficiency is recognized among the major global health issues. Genetic biofortification of wheat is a cost-effective and sustainable strategy to mitigate the global micronutrient and protein malnutrition. Genomic regions governing grain zinc concentration (GZnC), grain iron concentration (GFeC), grain protein content (GPC), test weight (TW), and thousand kernel weight (TKW) were investigated in a set of 184 diverse bread wheat genotypes through genome-wide association study (GWAS). The GWAS panel was genotyped using Breeders' 35 K Axiom Array and phenotyped in three different environments during 2019–2020. A total of 55 marker-trait associations (MTAs) were identified representing all three sub-genomes of wheat. The highest number of MTAs were identified for GPC (23), followed by TKW (15), TW (11), GFeC (4), and GZnC (2). Further, a stable SNP was identified for TKW, and also pleiotropic regions were identified for GPC and TKW. In silico analysis revealed important putative candidate genes underlying the identified genomic regions such as F-box-like domain superfamily, Zinc finger CCCH-type proteins, Serine-threonine/tyrosine-protein kinase, Histone deacetylase domain superfamily, and SANT/Myb domain superfamily proteins, etc. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection. | ||
| 546 | _aText in English | ||
| 650 | 7 |
_2AGROVOC _96463 _aMalnutrition |
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| 650 | 7 |
_2AGROVOC _91731 _aBiofortification |
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| 650 | 7 |
_2AGROVOC _91310 _aWheat |
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| 650 | 7 |
_2AGROVOC _91231 _aQuality |
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| 700 | 1 |
_aKrishna, H. _925014 |
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| 700 | 1 |
_aEllur, R.K. _927424 |
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| 700 | 1 |
_aSehgal, D. _8INT3332 _9922 _gGlobal Wheat Program |
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| 700 | 1 |
_aVelu, G. _8INT2983 _9880 _gGlobal Wheat Program |
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| 700 | 1 |
_aAhlawat, A.K. _917899 |
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| 700 | 1 |
_aKrishnappa, G. _927425 |
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| 700 | 1 |
_aJaiswal, J.P. _94174 |
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| 700 | 1 |
_aSingh, J.B. _927426 |
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| 700 | 1 |
_aSV, S. _927427 |
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| 700 | 1 |
_aAmbati, D. _927428 |
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| 700 | 1 |
_aSingh, S.K. _927429 |
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| 700 | 1 |
_aBajpai, K. _927430 |
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| 700 | 1 |
_aMahendru-Singh, A. _917207 |
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| 773 | 0 |
_tScientific Reports _gv. 12, no. 1, art. 7037 _dLondon (United Kingdom) : Nature Publishing Group, 2022 _w58025 _x2045-2322 |
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| 856 |
_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/22071 |
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| 942 |
_cJA _n0 _2ddc |
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| 999 |
_c65283 _d65275 |
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