Functional Mapping of Quantitative Trait Loci (QTLs) Associated With Plant Performance in a Wheat MAGIC Mapping Population.

Functional Mapping of Quantitative Trait Loci (QTLs) Associated With Plant Performance in a Wheat MAGIC Mapping Population.
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DOI:
10.3389/fpls.2018.00887
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发表时间:
2018
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;Mackay I;Mott R;Han J;Doonan JH;Askew K;Corke F;Williams K;Bentley AR

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在作物遗传研究中,描述农艺性状时空性质的纵向数据图谱可以阐明影响其形成和发展的因素。在这里,我们将MAGIC小麦群体的绘图能力和精度与强大的计算方法相结合,以跟踪与小麦生产性能相关的性状的时空动态。在智能住宅条件下,NIAB MAGIC系在其整个生命周期中表型化。生长模型拟合了描述生长轨迹的植物面积、高度、水分利用和衰老数据,并将拟合参数映射为数量性状。来自单个时间点的性状数据也被映射,以确定标记何时以及如何变得重要和不再重要。对时间动态的评估可以识别标记-性状关联,并根据关键标记的遗传贡献跟踪性状发育。我们建立了一个数据驱动的方法来理解复杂的农艺性状和加速植物育种的研究。
In crop genetic studies, the mapping of longitudinal data describing the spatio-temporal nature of agronomic traits can elucidate the factors influencing their formation and development. Here, we combine the mapping power and precision of a MAGIC wheat population with robust computational methods to track the spatio- temporal dynamics of traits associated with wheat performance. NIAB MAGIC lines were phenotyped throughout their lifecycle under smart house conditions. Growth models were fitted to the data describing growth trajectories of plant area, height, water use and senescence and fitted parameters were mapped as quantitative traits. Trait data from single time points were also mapped to determine when and how markers became and ceased to be significant. Assessment of temporal dynamics allowed the identification of marker-trait associations and tracking of trait development against the genetic contribution of key markers. We establish a data-driven approach for understanding complex agronomic traits and accelerate research in plant breeding.
DOI: 10.1534/g3.114.012963
发表时间: 2014-09-18
期刊: G3 (Bethesda, Md.)
影响因子: --
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Mackay IJ;Bansept-Basler P;Barber T;Bentley AR;Cockram J;Gosman N;Greenland AJ;Horsnell R;Howells R;O'Sullivan DM;Rose GA;Howell PJ
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