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Scholarly Communication

A systematic strategy for large-scale analysis of genotype-phenotype correlations: identification of candidate genes involved in African trypanosomiasis

Fisher, Paul; Hedeler, Cornelia; Wolstencroft, Katherine; Hulme, Helen; Noyes, Harry; Kemp, Stephen; Stevens, Robert and Brass, Andrew (2007) A systematic strategy for large-scale analysis of genotype-phenotype correlations: identification of candidate genes involved in African trypanosomiasis. Nucleic Acids Research, 35 (16). pp. 1-9. ISSN 1362-4962 (Online); 0305-1048 (Print)

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One of the major goals of biology, and consequently bioinformatics, is to successfully bridge the gap between genotype and phenotype. Microarray and Quantitative Trait Loci data are increasingly used to aid in the discovery of candidate genes responsible for phenotypic variation. With the development of workflows, these large scale datasets can be processed systematically, and provide a framework for the re-use and the explicit declaration of experimental methods. In this paper we highlight the issues facing the manual analysis of microarray and QTL data, and show how automated approaches provide a systematic means to investigate genotype-phenotype correlations. This methodology was applied to a use case of resistance to African trypanosomiasis in the mouse. Pathways represented in the results identified Daxx as one of the candidate genes within the Tir1 QTL region. A deletion of an amino acid in Daxx was identified in susceptible mouse strains in the Daxx-p53 protein binding region, implicating the role of Daxx in the control of apoptosis as part of the trypanosomiasis resistance phenotype.

Item Type:Article
Additional Information:Published online on August 20, 2007.
Uncontrolled Keywords:bioinformatics; genotype; phenotype; Microarray; Quantitative Trait Loci; QTL data; Daxx; genes; Tir1; QTL; amino acid
Subjects:Q Science > QH Natural history > QH301 Biology
Q Science > QA Mathematics > QA76 Computer software
Departments, Research Centres and Related Units:Academic Faculties, Institutes and Research Centres > Faculty of Science > Department of Biological Sciences
Publisher's Statement:© 2007 The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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ID Code:236
Deposited On:05 Oct 2007 15:40
Last Modified:19 May 2011 10:04

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