4.7 Article

Mapping quantitative trait loci for quality factors in an inter-class cross of US and Chinese wheat

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THEORETICAL AND APPLIED GENETICS
卷 120, 期 5, 页码 1041-1051

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SPRINGER
DOI: 10.1007/s00122-009-1232-x

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  1. NRI of the USDA CSREES [2006-55606-16629]
  2. U.S. Department of Agriculture
  3. Kansas Agricultural Experiment Station, Manhattan, Kansas, USA [09-254-J]

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Wheat quality factors are critical in determining the suitability of wheat (Triticum aestivum L.) for end-use product and economic value, and they are prime targets for marker-assisted selection. Objectives of this study were to identify quantitative trait loci (QTLs) that ultimately influence wheat market class and milling quality. A population of 132 F-12 recombinant inbred lines (RILs) was derived by single-seed descent from a cross between the Chinese hard wheat line Ning7840 and the soft wheat cultivar Clark and grown at three Oklahoma locations from 2001 to 2003. Milling factors such as test weight (volumetric grain weight, TW), kernel weight (KW), and kernel diameter (KD) and market class factors such as wheat grain protein content (GPC) and kernel hardness index (HI) were characterized on the basis of a genetic map constructed from 367 SSR and 241 AFLP markers covering all 21 chromosomes. Composite interval mapping identified eight QTLs for TW, seven for KW, six for KD, two each for GPC and HI measured by near-infrared reflectance (NIR) spectroscopy, and four for HI measured by single kernel characterization system. Positive phenotypic correlations were found among milling factors. Consistent co-localized QTLs were identified for TW, KW, and KD on the short arms of chromosomes 5A and 6A. A common QTL was identified for TW and KD on the long arm of chromosome 5A. A consistent major QTL for HI peaked at the Pinb-D1 locus on the short arm of chromosome 5D and explained up to 85% of the phenotypic variation for hardness. We identified QTLs for GPC on 4B and the short arm of 3A chromosomes. The consistency of quality factor QTLs across environments reveals their potential for marker-assisted selection.

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