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High throughput analyses of epistasis for swine body dimensions and organ weights.

机译:高通量分析猪体大小和器官重量。

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High throughput analyses were performed to detect epistatic QTL in 17 body dimension and organ weight traits from a large F2 pig population derived from a White Duroc and Erhualian intercross. The analyses used a nested test framework to handle multiple tests and a combined search algorithm to map epistatic QTL with empirical genome-wide thresholds derived via prior permutation. Alternative statistical models (e.g. including vs. excluding carcass weight as a covariate) were tested to develop an in-depth understanding of the role of epistasis in these kinds of traits. Epistasis signals were detected in only two or three traits under each statistical model studied. The interaction component of each pair of epistatic QTL explained a small proportion (0.7 to 2.1%) of the phenotypic variance in general. About half of the detected epistatic QTL pairs involved one of the two major QTL on porcine chromosomes 7 and 4. In those traits, the Erhualian allele consistently increased the phenotypes for the chromosome 7 QTL but decreased them for the chromosome 4 QTL. Models including carcass weight as covariate detected epistasis in body dimension traits whereas those excluding carcass weight found epistasis in organ weight traits. In addition, the epistasis results suggested that a QTL on chromosome 14 could be important for a number of organ weight traits. Using the high-throughput analysis tool to examine different statistical models was essential for the generation of a complete picture of epistasis in a whole category of traits.Digital Object Identifier http://dx.doi.org/10.1111/j.1365-2052.2010.02082.x
机译:进行了高通量分析,以检测来自白色杜洛克和二华联交配的大量F 2 猪群的17个体形和体重特征的上位QTL。分析使用嵌套的测试框架来处理多个测试,并使用组合的搜索算法来映射上位QTL与通过事先排列获得的经验性全基因组阈值。测试了其他统计模型(例如,包括或不包括including体重量作为协变量)来深入了解上位性在这些类型性状中的作用。在每个研究的统计模型下,仅在两个或三个特征中检测到上位信号。通常,每对上位QTL的相互作用成分解释了表型差异的一小部分(0.7至2.1%)。大约一半的检测到的上位QTL对涉及猪7号和4号染色体上的两个主要QTL之一。在这些性状中,二化all等位基因持续增加7号染色体QTL的表型,但减少4号染色体QTL的表型。包括car体重量作为协变量的模型可检测到人体尺度特征的上位性,而不包括car体重量的模型则可发现器官重量性状的上位性。此外,上位性结果表明第14号染色体上的QTL对于许多器官重量性状可能很重要。使用高通量分析工具检查不同的统计模型对于在整个特征类别中生成完整的上位性图谱至关重要。数字对象标识符http://dx.doi.org/10.1111/j.1365-2052.2010 .02082.x

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