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Fine-mapping quantitative trait loci with a medium density marker panel: efficiency of population structures and comparison of linkage disequilibrium linkage analysis models

机译:具有中等密度标记面板的精细映射数量性状基因座:种群结构的效率和连锁不平衡连锁分析模型的比较

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Recently, a Haley–Knott-type regression method using combined linkage disequilibrium and linkage analyses (LDLA) was proposed to map quantitative trait loci (QTLs). Chromosome of 5 and 25 cM with 0·25 and 0·05 cM, respectively, between markers were simulated. The differences between the LDLA approaches with regard to QTL position accuracy were very limited, with a significantly better mean square error (MSE) with the LDLA regression (LDLA_reg) in sparse map cases; the contrary was observed, but not significantly, in dense map situations. The computing time required for the LDLA variance components (LDLA_vc) model was much higher than the LDLA_reg model. The precision of QTL position estimation was compared for four numbers of half-sib families, four different family sizes and two experimental designs (half-sibs, and full- and half-sibs). Regarding the number of families, MSE values were lowest for 15 or 50 half-sib families, differences not being significant. We observed that the greater the number of progenies per sire, the more accurate the QTL position. However, for a fixed population size, reducing the number of families (e.g. using a small number of large full-sib families) could lead to less accuracy of estimated QTL position.
机译:最近,提出了一种使用联合连锁不平衡和连锁分析(LDLA)的Haley-Knott型回归方法来绘制数量性状基因座(QTL)的图。模拟标记之间的5和25 cM的染色体,分别为0·25和0·05 cM。 LDLA方法之间在QTL位置准确性方面的差异非常有限,在稀疏地图情况下,采用LDLA回归(LDLA_reg)的均方差(MSE)明显更好。在密集的地图情况下,观察到相反但不是很大。 LDLA方差分量(LDLA_vc)模型所需的计算时间比LDLA_reg模型要长得多。比较了QTL位置估计的精度,包括四个半同胞家族,四个不同的家族大小和两个实验设计(半同胞,全同胞和半同胞)。关于家庭数量,MSE值在15个或50个同胞家庭中最低,差异不显着。我们观察到,每个父系的后代数量越多,QTL位置越准确。但是,对于固定的人口规模,减少家庭数量(例如,使用少量的全同胞大家庭)可能导致估计的QTL位置准确性降低。

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