Medical record, seizure survey, and telephone interview information was obtained for 29 Vizslas with idiopathic epilepsy (IE), 74 unaffected siblings, and 41 parents to determine the common clinical characteristics and most likely mode of inheritance. IE was diagnosed on the basis of the age of seizure onset, laboratory results, and neurologic examination findings. Computerized tomography (CT) or magnetic resonance imaging (MRI) scan with cerebrospinal fluid (CSF) analysis was required for the inclusion of dogs with an age of seizure onset of < 6 months or > 5 years. Simple segregation analysis was performed with an ascertainment correction and chi-square analysis. IE appeared to be familial in these pedigrees, with 79% of affected Vizslas exhibiting partial onset seizures. Partial seizure signs included a combination of limb tremors, staring, pupillary dilatation, or salivation without loss of consciousness in > 50% of the dogs with partial signs. The estimated segregation frequency of P = .22 (95% CI, P = .08 to .36) was consistent with autosomal recessive inheritance; however, polygenic inheritance could not be excluded as a possibility. Simulated linkage with FASTSLINK estimated that the average logarithm of odds (LOD) score would be 3.23 with a 10-centimorgan (cM) whole-genome scan for these families, indicating that these families would be useful for a whole-genome scan to potentially find the chromosomal segment(s) containing the epilepsy gene or genes. We conclude that IE in Vizslas appears to be primarily a partial onset seizure disorder that may be inherited as an autosomal recessive trait.
A strategy of multi-step minimal conditional regression analysis has been developed to determine the existence of statistical testing and parameter estimation for a quantitative trait locus (QTL) that are unaffected by linked QTLs. The estimation of marker-QTL recombination frequency needs to consider only three cases: 1) the chromosome has only one QTL, 2) one side of the target QTL has one or more QTLs, and 3) either side of the target QTL has one or more QTLs. Analytical formula was derived to estimate marker-QTL recombination frequency for each of the three cases. The formula involves two flanking markers for case 1), two flanking markers plus a conditional marker for case 2), and two flanking markers plus two conditional markers for case 3). Each QTL variance and effect, and the total QTL variance were also estimated using analytical formulae. Simulation data show that the formulae for estimating marker-QTL recombination frequency could be a useful statistical tool for fine QTL mapping. With 1 000 observations, a QTL could be mapped to a narrow chromosome region of 1.5 cM if no linked QTL is present, and to a 2.8 cM chromosome region if either side of the target QTL has at least one linked QTL.
-Epistasis refers to gene interaction effect involving two or more genes. Statistical methods for mapping quantitative trait loci (QTL) with epistasis effects have become available recently. However, little is known about the statistical power and sample size requirements for mapping epistatic QTL using genetic markers. In this study, we developed analytical formulae to calculate the statistical power and sample requirement for detecting each epistasis effect under the F-2 design based on crossing inbred lines. Assuming two unlinked interactive QTL and the same absolute value for all epistasis effects, the heritability of additive × additive (a × a) effect is twice as large as that of additive × dominance (a × d) or dominance × additive (d × a) effect, and is four times as large as that of dominance × dominance (d × d) effect. Consequently, among the four types of epistasis effects involving two loci, 'a × a' effect is the easiest to detect whereas 'd × d' effect is the most difficult to detect. The statistical power for detecting 'a × a' effect is similar to that for detecting dominance effect of a single QTL. The sample size requirements for detecting 'a × d', 'd × a' and 'd × d' are highly sensitive to increased distance between the markers and the interacting QTLs. Therefore, using dense marker coverage is critical to detecting those effects. epistasis / QTL / statistical power / sample size / F-2
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