Determining Phenological Patterns Associated with the Onset of Senescence in a Wheat MAGIC Mapping Population.

Determining Phenological Patterns Associated with the Onset of Senescence in a Wheat MAGIC Mapping Population.
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DOI:
10.3389/fpls.2016.01540
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发表时间:
2016
影响因子:
5.6
通讯作者:
Bentley AR
Bentley AR
中科院分区:
生物学2区
文献类型:
--
作者:
Camargo AV;Mott R;Gardner KA;Mackay IJ;Corke F;Doonan JH;Kim JT;Bentley AR

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The appropriate timing of developmental transitions is critical for adapting many crops to their local climatic conditions. Therefore, understanding the genetic basis of different aspects of phenology could be useful in highlighting mechanisms underpinning adaptation, with implications in breeding for climate change. For bread wheat (Triticum aestivum), the transition from vegetative to reproductive growth, the start and rate of leaf senescence and the relative timing of different stages of flowering and grain filling all contribute to plant performance. In this study we screened under Smart house conditions a large, multi-founder “NIAB elite MAGIC” wheat population, to evaluate the genetic elements that influence the timing of developmental stages in European elite varieties. This panel of recombinant inbred lines was derived from eight parents that are or recently have been grown commercially in the UK and Northern Europe. We undertook a detailed temporal phenotypic analysis under Smart house conditions of the population and its parents, to try to identify known or novel Quantitative Trait Loci associated with variation in the timing of key phenological stages in senescence. This analysis resulted in the detection of QTL interactions with novel traits such the time between “half of ear emergence above flag leaf ligule” and the onset of senescence at the flag leaf as well as traits associated with plant morphology such as stem height. In addition, strong correlations between several traits and the onset of senescence of the flag leaf were identified. This work establishes the value of systematically phenotyping genetically unstructured populations to reveal the genetic architecture underlying morphological variation in commercial wheat.
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