Department of Genetics, Evolution and Environment, University College London, London, UK.
SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Bioinformatics. 2018 Sep 1;34(17):i612-i619. doi: 10.1093/bioinformatics/bty615.
A 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.
This 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.
QTLSearch 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 data are available at Bioinformatics online.
植物生物技术应用的一个关键目标是鉴定与特定表型特征（例如产量、果实大小、根长）相关的基因。数量性状位点（QTL）研究确定与感兴趣性状相关的基因组区域。然而，为了推断这些区域中的潜在因果基因（每个区域都可能包含数百个基因），通常需要将这些数据与这些基因的先前功能知识相交集。然而，这个过程很繁琐，特别是如果实验是在非模式物种中进行的，并且推断候选基因的统计显著性通常是未知的。
本文介绍了 QTLSearch，这是一种通过跨多个物种组合使用基因本体论注释、利用层次同源群来搜索 QTL 研究中候选因果基因的方法和软件工具。通过重新分析两个代谢 QTL 研究，证明了这种方法的有效性：一个在拟南芥中，另一个在籼稻亚种中。即使在控制了统计显著性之后，QTLSearch 推断的潜在因果基因比基于 BLAST 的功能传播针对 UniProtKB/Swiss-Prot 的更多 QTL，并且比原始研究中的更多 QTL。
QTLSearch 根据 LGPLv3 许可证分发。它可以从 Python 包索引（作为 qtlsearch）安装，其源代码可从 https://bitbucket.org/alex-warwickvesztrocy/qtlsearch 获得。
补充数据可在生物信息学在线获得。
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