Abstract
BackgroundElucidation of genotype-to-phenotype relationships is a major challenge in biology. In plants, it is the basis for molecular breeding. Quantitative Trait Locus (QTL) mapping enables to link variation at the trait level to variation at the genomic level. However, QTL regions typically contain tens to hundreds of genes. In order to prioritize such candidate genes, we show that we can identify potentially causal genes for a trait based on overrepresentation of biological processes (gene functions) for the candidate genes in the QTL regions of that trait.ResultsThe prioritization method was applied to rice QTL data, using gene functions predicted on the basis of sequence- and expression-information. The average reduction of the number of genes was over ten-fold. Comparison with various types of experimental datasets (including QTL fine-mapping and Genome Wide Association Study results) indicated both statistical significance and biological relevance of the obtained connections between genes and traits. A detailed analysis of flowering time QTLs illustrates that genes with completely unknown function are likely to play a role in this important trait.ConclusionsOur approach can guide further experimentation and validation of causal genes for quantitative traits. This way it capitalizes on QTL data to uncover how individual genes influence trait variation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-014-0330-3) contains supplementary material, which is available to authorized users.
Highlights
Elucidation of genotype-to-phenotype relationships is a major challenge in biology
Quantitative Trait Locus (QTL) candidate gene prioritization Our prioritization approach is based on the assumption that multiple QTL regions for a trait reflect variation in genes involved in the same biological process
To have a closer look at the genes prioritized for the trait days to heading based on the biological process (BP) ? regulation of flower development? we focused on the genes that in the QTL region in which they occur were the only gene associated with this BP
Summary
Elucidation of genotype-to-phenotype relationships is a major challenge in biology. In plants, it is the basis for molecular breeding. Quantitative Trait Locus (QTL) mapping is an attractive approach to link genetic determinants to methods that help prioritizing QTL candidate genes using a computational approach would be very helpful in unraveling genotype-to-phenotype relationships. Such prioritization is well developed in human disease genetics, where several criteria, such as the putative deleteriousness of a variant, evolutionary conservation, and known biological pathways, are taken into account [11,12,13,14,15,16,17,18,19,20,21,22,23].
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