Prioritising candidate genes causing QTL using hierarchical orthologous groups.

Christophe Dessimoz,Alex Warwick Vesztrocy,Henning Redestig

doi:10.1093/bioinformatics/bty615

Christophe Dessimoz, Alex Warwick Vesztrocy + Show 1 more

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https://doi.org/10.1093/bioinformatics/bty615

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Abstract

MotivationA key goal in plant biotechnology applications is the identification of genes associated to particular phenotypic traits (for example: yield, fruit size, root length). Quantitative Trait Loci (QTL) studies identify genomic regions associated with a trait of interest. However, to infer potential causal genes in these regions, each of which can contain hundreds of genes, these data are usually intersected with prior functional knowledge of the genes. This process is however laborious, particularly if the experiment is performed in a non-model species, and the statistical significance of the inferred candidates is typically unknown.ResultsThis paper introduces QTLSearch, a method and software tool to search for candidate causal genes in QTL studies by combining Gene Ontology annotations across many species, leveraging hierarchical orthologous groups. The usefulness of this approach is demonstrated by re-analysing two metabolic QTL studies: one in Arabidopsis thaliana, the other in Oryza sativa subsp. indica. Even after controlling for statistical significance, QTLSearch inferred potential causal genes for more QTL than BLAST-based functional propagation against UniProtKB/Swiss-Prot, and for more QTL than in the original studies.Availability and implementationQTLSearch is distributed under the LGPLv3 license. It is available to install from the Python Package Index (as qtlsearch), with the source available from https://bitbucket.org/alex-warwickvesztrocy/qtlsearch.Supplementary information Supplementary data are available at Bioinformatics online.

Highlights

Identification of variants of genes that are linked to differences in phenotypic traits is a first step in many plant biotechnology applications
To illustrate the usefulness of QTLSearch, data from two previous metabolic Quantitative Trait Loci (QTL) studies was re-analysed—one in A. thaliana (Lisec et al, 2009), the other in O. sativa subsp. indica (Gong et al, 2013)—in which candidate causal genes were identified for a subset of the QTL using ad hoc methods
The limiting factor for QTLSearch was the number of metabolites which could be associated to Galactose bio-synthetic process’ (GO) or ChEBI terms

Summary

Introduction

Identification of variants of genes that are linked to differences in phenotypic traits is a first step in many plant biotechnology applications. A faster complementary approach is to annotate the genes in the target species with known associations to the trait of interest (for example, involvement in relevant pathways or biological processes), and searching for overlap with the genes inside a given QTL (Bargsten et al, 2014; Chen et al, 2012; Gong et al, 2013; Lisec et al, 2009). This approach has aided the identification of several verified causal genes—for example, the AT5G50950 fumarase (Brotman et al, 2011; Lisec et al, 2008)— demonstrating its merit

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