Exhausted model selection for multitrait mapping QTL: application to barley ( Hordeum vulgare L.) dataset
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RESEARCH ARTICLE
Exhausted model selection for multitrait mapping QTL: application to barley (Hordeum vulgare L.) dataset Jinhua Ye . Hao Yang . Yingbo Yuan . Zenglong An . Ming Fang . Zhiyong Wang . Dan Jiang
Received: 20 June 2019 / Accepted: 2 May 2020 Springer Nature B.V. 2020
Abstract In this study, a QTL mapping method combining multiple traits is proposed. The key feature of the new method is that it tests all possible traits and chooses those affected traits in the model for a specific QTL, whereas these ‘‘working’’ traits may be different for different QTL. The BIC model selection criteria was used to choose the best model and to ascertain the ‘‘working’’ traits; then the ‘‘working’’ traits were combined together to detect QTL affecting these traits, by which it can boost QTL signals and increase statistical power. The new method has been applied to Barley dataset, which contains eight traits. The results showed that sometimes a QTL might affect more than one trait but not always affected all traits; the QTL detection power with new method was increased and 4 more QTLs were detected compared with single-trait method; generally, - logP values were much higher
Jinhua Ye and Hao Yang have equally contributed to this work.
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10722-020-00952-1) contains supplementary material, which is available to authorized users. J. Ye College of Science, Heilongjiang Bayi Agricultural University, Daqing 163319, China J. Ye College of Life Science, Heilongjiang Bayi Agricultural University, Daqing 163319, China
than those by single-trait analysis, but they were highly correlated, confirmed the unbiaseness of the new multitrait method. These results suggest that the developed multitrait method is effective for QTL mapping. The computational program is written in Fortran language for convenience to use, which is available on request. Keywords Multitrait Barley Qtlmapping Traitspecific QTL
Introduction Association study is an effective way to map QTL. When designing the experiment for association study, researchers usually study on multiple traits, which is an economic way to get more additional findings without additional genotyping charge. In most of H. Yang Y. Yuan M. Fang Z. Wang D. Jiang (&) Key Laboratory of Healthy Mariculture for the East China Sea, Ministry of Agriculture and Rural Affairs, Fisheries College, Jimei University, Xiamen 361021, Fujian province, China e-mail: [email protected] Z. An (&) College of Economics and Management, Heilongjiang Bayi Agricultural University, Daqing 163319, China e-mail: [email protected]
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Genet Resour Crop Evol
cases, the traits are genetically correlated, meaning that these traits maybe controlled by the same QTL or close linked QTL. Wang et al. (2016) studied on the published GWAS variants from the National Human Genome Research Institute (NHGRI) Catalogue and defined cross-phenotype (CP) loci as a region within w
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