Computational selection and prioritization of candidate genes for Fetal Alcohol Syndrome

 

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dc.contributor.author Lombard, Zane en_ZA
dc.contributor.author Tiffin, Nicki en_ZA
dc.contributor.author Hofmann, Oliver en_ZA
dc.contributor.author Bajic, Vladimir en_ZA
dc.contributor.author Hide, Winston en_ZA
dc.contributor.author Ramsay, Michele en_ZA
dc.date.accessioned 2015-10-12T10:58:32Z
dc.date.available 2015-10-12T10:58:32Z
dc.date.issued 2007 en_ZA
dc.identifier.citation Lombard, Z., Tiffin, N., Hofmann, O., Bajic, V. B., Hide, W., & Ramsay, M. (2007). Computational selection and prioritization of candidate genes for fetal alcohol syndrome. BMC genomics, 8(1), 389. en_ZA
dc.identifier.uri 10.1186/1471-2164-8-389 en_ZA
dc.identifier.uri http://hdl.handle.net/11427/14198
dc.description.abstract BACKGROUND:Fetal alcohol syndrome (FAS) is a serious global health problem and is observed at high frequencies in certain South African communities. Although in utero alcohol exposure is the primary trigger, there is evidence for genetic- and other susceptibility factors in FAS development. No genome-wide association or linkage studies have been performed for FAS, making computational selection and -prioritization of candidate disease genes an attractive approach. RESULTS: 10174 Candidate genes were initially selected from the whole genome using a previously described method, which selects candidate genes according to their expression in disease-affected tissues. Hereafter candidates were prioritized for experimental investigation by investigating criteria pertinent to FAS and binary filtering. 29 Criteria were assessed by mining various database sources to populate criteria-specific gene lists. Candidate genes were then prioritized for experimental investigation using a binary system that assessed the criteria gene lists against the candidate list, and candidate genes were scored accordingly. A group of 87 genes was prioritized as candidates and for future experimental validation. The validity of the binary prioritization method was assessed by investigating the protein-protein interactions, functional enrichment and common promoter element binding sites of the top-ranked genes. CONCLUSION: This analysis highlighted a list of strong candidate genes from the TGF-beta, MAPK and Hedgehog signalling pathways, which are all integral to fetal development and potential targets for alcohol's teratogenic effect. We conclude that this novel bioinformatics approach effectively prioritizes credible candidate genes for further experimental analysis. en_ZA
dc.language.iso eng en_ZA
dc.publisher BioMed Central Ltd en_ZA
dc.rights This is an Open Access article distributed under the terms of the Creative Commons Attribution License en_ZA
dc.rights.uri http://creativecommons.org/licenses/by/2.0 en_ZA
dc.source BMC Genomics en_ZA
dc.source.uri http://www.biomedcentral.com/bmcgenomics/ en_ZA
dc.subject.other Fetal alcohol syndrome en_ZA
dc.subject.other Human Genetics en_ZA
dc.title Computational selection and prioritization of candidate genes for Fetal Alcohol Syndrome en_ZA
dc.type Journal Article en_ZA
uct.type.publication Research en_ZA
uct.type.resource Article en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Health Sciences en_ZA
dc.publisher.department Division of Human Genetics en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Lombard, Z., Tiffin, N., Hofmann, O., Bajic, V., Hide, W., & Ramsay, M. (2007). Computational selection and prioritization of candidate genes for Fetal Alcohol Syndrome. <i>BMC Genomics</i>, http://hdl.handle.net/11427/14198 en_ZA
dc.identifier.chicagocitation Lombard, Zane, Nicki Tiffin, Oliver Hofmann, Vladimir Bajic, Winston Hide, and Michele Ramsay "Computational selection and prioritization of candidate genes for Fetal Alcohol Syndrome." <i>BMC Genomics</i> (2007) http://hdl.handle.net/11427/14198 en_ZA
dc.identifier.vancouvercitation Lombard Z, Tiffin N, Hofmann O, Bajic V, Hide W, Ramsay M. Computational selection and prioritization of candidate genes for Fetal Alcohol Syndrome. BMC Genomics. 2007; http://hdl.handle.net/11427/14198. en_ZA
dc.identifier.ris TY - Journal Article AU - Lombard, Zane AU - Tiffin, Nicki AU - Hofmann, Oliver AU - Bajic, Vladimir AU - Hide, Winston AU - Ramsay, Michele AB - BACKGROUND:Fetal alcohol syndrome (FAS) is a serious global health problem and is observed at high frequencies in certain South African communities. Although in utero alcohol exposure is the primary trigger, there is evidence for genetic- and other susceptibility factors in FAS development. No genome-wide association or linkage studies have been performed for FAS, making computational selection and -prioritization of candidate disease genes an attractive approach. RESULTS: 10174 Candidate genes were initially selected from the whole genome using a previously described method, which selects candidate genes according to their expression in disease-affected tissues. Hereafter candidates were prioritized for experimental investigation by investigating criteria pertinent to FAS and binary filtering. 29 Criteria were assessed by mining various database sources to populate criteria-specific gene lists. Candidate genes were then prioritized for experimental investigation using a binary system that assessed the criteria gene lists against the candidate list, and candidate genes were scored accordingly. A group of 87 genes was prioritized as candidates and for future experimental validation. The validity of the binary prioritization method was assessed by investigating the protein-protein interactions, functional enrichment and common promoter element binding sites of the top-ranked genes. CONCLUSION: This analysis highlighted a list of strong candidate genes from the TGF-beta, MAPK and Hedgehog signalling pathways, which are all integral to fetal development and potential targets for alcohol's teratogenic effect. We conclude that this novel bioinformatics approach effectively prioritizes credible candidate genes for further experimental analysis. DA - 2007 DB - OpenUCT DP - University of Cape Town J1 - BMC Genomics LK - https://open.uct.ac.za PB - University of Cape Town PY - 2007 T1 - Computational selection and prioritization of candidate genes for Fetal Alcohol Syndrome TI - Computational selection and prioritization of candidate genes for Fetal Alcohol Syndrome UR - http://hdl.handle.net/11427/14198 ER - en_ZA


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