A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes.
Hum Mol Genet
; 27(17): 3099-3112, 2018 09 01.
Article
en En
| MEDLINE
| ID: mdl-29893858
To explore the genetic determinants of obesity and Type 2 diabetes (T2D), the German Center for Diabetes Research (DZD) conducted crossbreedings of the obese and diabetes-prone New Zealand Obese mouse strain with four different lean strains (B6, DBA, C3H, 129P2) that vary in their susceptibility to develop T2D. Genome-wide linkage analyses localized more than 290 quantitative trait loci (QTL) for obesity, 190 QTL for diabetes-related traits and 100 QTL for plasma metabolites in the outcross populations. A computational framework was developed that allowed to refine critical regions and to nominate a small number of candidate genes by integrating reciprocal haplotype mapping and transcriptome data. The efficiency of the complex procedure was demonstrated for one obesity QTL. The genomic interval of 35 Mb with 502 annotated candidate genes was narrowed down to six candidates. Accordingly, congenic mice retained the obesity phenotype owing to an interval that contains three of the six candidate genes. Among these the phospholipase PLA2G4A exhibited an elevated expression in adipose tissue of obese human subjects and is therefore a critical regulator of the obesity locus. Together, our broad and complex approach demonstrates that combined- and comparative-cross analysis exhibits improved mapping resolution and represents a valid tool for the identification of disease genes.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Biomarcadores
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Biología Computacional
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Polimorfismo de Nucleótido Simple
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Sitios de Carácter Cuantitativo
/
Diabetes Mellitus Tipo 2
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Fosfolipasas A2 Grupo IV
/
Obesidad
Tipo de estudio:
Prognostic_studies
Límite:
Adolescent
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Adult
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Aged
/
Aged80
/
Animals
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Hum Mol Genet
Asunto de la revista:
BIOLOGIA MOLECULAR
/
GENETICA MEDICA
Año:
2018
Tipo del documento:
Article
País de afiliación:
Alemania
Pais de publicación:
Reino Unido