کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5908067 1160974 2007 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Heritability and segregation analysis of osteosarcoma in the Scottish deerhound
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی ژنتیک
پیش نمایش صفحه اول مقاله
Heritability and segregation analysis of osteosarcoma in the Scottish deerhound
چکیده انگلیسی
Osteosarcoma is the most common malignant bone tumor in dogs and, like its human orthologue, is characterized by aggressive local behavior and high metastatic rates. The Scottish deerhound is a breed of dog with a > 15% incidence of osteosarcoma and represents an excellent spontaneously occurring large-animal model of the human disease. We modeled the transmission of the osteosarcoma phenotype in a population of over 1000 related deerhounds ascertained as part of a prospective health study. Variance component analysis, segregation analysis, and linear modeling were performed to evaluate heritability, to infer the presumptive transmission model, and to identify covariate effects for this phenotype within the breed, respectively. Based on variance component analysis, heritability (h2) was estimated to be 0.69. Six transmission models were analyzed by segregation analysis; based on Akaike's information criteria, the most parsimonious model was the Mendelian major gene model with dominant expression. Linear modeling identified gender and genotype as significant predictors of disease outcome. Importantly, duration of gonadal hormone exposure, weight, and height at maturity were not significant predictors of outcome. Inheritance of the putative high-risk allele was thus associated with > 75% risk of disease occurrence compared to the <5% baseline risk. These results support the hypothesis that a major gene with a dominant effect explains most of the osteosarcoma phenotype within the Scottish deerhound.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Genomics - Volume 90, Issue 3, September 2007, Pages 354-363
نویسندگان
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