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. 2009 Jun;119(1):105-23.
doi: 10.1007/s00122-009-1021-6. Epub 2009 Apr 11.

Advanced backcross-QTL analysis in spring barley (H. vulgare ssp. spontaneum) comparing a REML versus a Bayesian model in multi-environmental field trials

Andrea Michaela Bauer  1 , F Hoti, M von Korff, K Pillen, J Léon, M J Sillanpää
Affiliations

Advanced backcross-QTL analysis in spring barley (H. vulgare ssp. spontaneum) comparing a REML versus a Bayesian model in multi-environmental field trials

Andrea Michaela Bauer et al. Theor Appl Genet. 2009 Jun.

Abstract

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 BC(2)DH 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 m(2)," "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.

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Figures

Fig. 1
Fig. 1
Locus-specific point-estimates (posterior medians) of effect sizes of Bayesian multi-locus single-environmental QTL mapping for the trait “grain yield” in the spring barley population. The posterior medians are displayed for all environments separately. The significance threshold was obtained from permutation tests. The markers were coded according to their chromosomal location
Fig. 2
Fig. 2
Locus-specific point-estimates (posterior medians) of standardized effects of Bayesian multi-locus multi-environmental QTL mapping for the trait “grain yield” in the spring barley population. The posterior medians of all environments are displayed jointly in the graph. The markers were coded according to their chromosomal location
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