Depending on the disorder type, non-rodent animals have been described as better animal models of human disease. The pig (Sus scrofa), for example, in relation with dimensions, physiology and genetics is considered an interesting model for human complex disorders, such as obesity and related diseases. To apply a targeted genetic investigation in the pig as model for human obesity we developed a comparative and systemic approach that makes use of the human interactome to select and recruit candidate genes and of an in silico database mining to identify single nucleotide polymorphisms (SNPs) for a customized large scale genotyping. Our implementation includes two modules. The first is a gene selector implemented combining gene-disease curated information and projecting these relationships in a systemic vision of the disease within the human interactome. The second is a SNP mining pipeline using expressed sequence tags (ESTs) of the model species to identify DNA markers in a core and candidate gene datasets. Starting with an initial set of 249 obesityrelated human genes, other 2,117 genes were recruited from the human interactome. With the expanded gene set, the platform detected and filtered some 12,159 SNPs in a collection of 3,259,972 porcine ESTs. 5,455 SNPs were fully annotated in 690 pig genes. Validation by resequencing on a selected set of the animal predicted SNPs gave a 65% rate of success. This tool can be applied to other animal species and human diseases and can be adapted to mine data obtained from new sequencing platforms.

A systemic approach for SNP detection in animal models of human genetic diseases: the case of the pig as a model for human obesity

FRONZA, RAFFAELE;MARTELLI, PIER LUIGI;FONTANESI, LUCA;RUSSO, VINCENZO;CASADIO, RITA
2009

Abstract

Depending on the disorder type, non-rodent animals have been described as better animal models of human disease. The pig (Sus scrofa), for example, in relation with dimensions, physiology and genetics is considered an interesting model for human complex disorders, such as obesity and related diseases. To apply a targeted genetic investigation in the pig as model for human obesity we developed a comparative and systemic approach that makes use of the human interactome to select and recruit candidate genes and of an in silico database mining to identify single nucleotide polymorphisms (SNPs) for a customized large scale genotyping. Our implementation includes two modules. The first is a gene selector implemented combining gene-disease curated information and projecting these relationships in a systemic vision of the disease within the human interactome. The second is a SNP mining pipeline using expressed sequence tags (ESTs) of the model species to identify DNA markers in a core and candidate gene datasets. Starting with an initial set of 249 obesityrelated human genes, other 2,117 genes were recruited from the human interactome. With the expanded gene set, the platform detected and filtered some 12,159 SNPs in a collection of 3,259,972 porcine ESTs. 5,455 SNPs were fully annotated in 690 pig genes. Validation by resequencing on a selected set of the animal predicted SNPs gave a 65% rate of success. This tool can be applied to other animal species and human diseases and can be adapted to mine data obtained from new sequencing platforms.
Procedings of Pig Genome III conference
32
33
Fronza R.; Martelli P.L.; Fontanesi L.; Russo V.; Casadio R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/79508
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