Advanced backcross-QTL analysis in spring barley (H. vulgare ssp. spontaneum) comparing a REML versus a Bayesian model in multi-environmental field trials.
Advanced backcross-QTL analysis in spring barley (H. vulgare ssp. spontaneum) comparing a REML versus a Bayesian model in multi-environmental field trials.
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DOI：
10.1007/s00122-009-1021-6
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发表时间：
2009-06
影响因子：
5.4
通讯作者：
Sillanpaa, M. J.
中科院分区：
文献类型：
--
作者：
Bauer, Andrea Michaela;Hoti, F.;von Korff, M.;Pillen, K.;Leon, J.;Sillanpaa, M. J.
数量性状基因座（QTL）定位的一个常见困难是QTL效应可能表现出环境特异性，因此在不同环境中存在差异。此外，数量性状可能受到多个QTL或基因的影响，具有不同的效果大小。目前需要有效的作图策略来解释多个QTL和标记与环境的相互作用。因此，本研究的目的是建立一个贝叶斯多位点多环境QTL分析方法。该策略与（1）贝叶斯多位点映射，其中每个环境分别进行分析，（2）使用混合分层模型的限制最大似然（REML）单位点方法，以及（3）应用混合分层模型的REML前向选择进行比较。在这项研究中，我们使用了来自春大麦优良品种Scarlett和来自以色列的野生供体ISR 42 -8之间的杂交的301个BC 2DH系的多环境田间试验的数据。通过98个SSR标记对这些品系进行基因分型，并测量农艺性状“每平方米穗数”、“抽穗前天数”、“株高”、“千粒重”和“籽粒产量”。此外，进行了模拟研究，以验证在春大麦群体中获得的QTL结果。总体而言，贝叶斯QTL定位的结果与REML方法一致。在这项研究中，贝叶斯多位点多环境分析是一种有价值的方法，特别适合于在多环境田间试验中培养品系。本文的在线版本（doi：10.1007/s 00122 -009-1021-6）包含补充材料，可供授权用户使用。
A common difficulty in mapping quantitative trait loci (QTLs) is that QTL effects may show environment specificity and thus differ across environments. Furthermore, quantitative traits are likely to be influenced by multiple QTLs or genes having different effect sizes. There is currently a need for efficient mapping strategies to account for both multiple QTLs and marker-by-environment interactions. Thus, the objective of our study was to develop a Bayesian multi-locus multi-environmental method of QTL analysis. This strategy is compared to (1) Bayesian multi-locus mapping, where each environment is analysed separately, (2) Restricted Maximum Likelihood (REML) single-locus method using a mixed hierarchical model, and (3) REML forward selection applying a mixed hierarchical model. For this study, we used data on multi-environmental field trials of 301 BC2DH lines derived from a cross between the spring barley elite cultivar Scarlett and the wild donor ISR42-8 from Israel. The lines were genotyped by 98 SSR markers and measured for the agronomic traits “ears per m²,” “days until heading,” “plant height,” “thousand grain weight,” and “grain yield”. Additionally, a simulation study was performed to verify the QTL results obtained in the spring barley population. In general, the results of Bayesian QTL mapping are in accordance with REML methods. In this study, Bayesian multi-locus multi-environmental analysis is a valuable method that is particularly suitable if lines are cultivated in multi-environmental field trials. The online version of this article (doi:10.1007/s00122-009-1021-6) contains supplementary material, which is available to authorized users.
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影响因子：
3.8
作者：
HALEY, CS;KNOTT, SA
通讯作者：
KNOTT, SA
影响因子：
2.1
作者：
Kilpikari, R;Sillanpää, MJ
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Sillanpää, MJ
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作者：
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作者：
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