Fig. 3: The estimation of the indictive number of pleiotropic QTL across 34 traits (tr01–tr34) for each chromosome segments.
a An asymmetric matrix of the variance and covariance of local gEBV of 34 traits for a chromosome segment. The asymmetry (the colour difference between elements above and below the diagonal) of the matrix is due to the use of two sets of local gEBV to calculate the covariance from different training populations (bulls or cows). The yellow colour indicates positive values and the dark colour indicates negative values. The diagonal elements are labelled as red ‘V’ (variance) and the off-diagonal elements are labelled as grey ‘C’ (covariance). b Equation (2) uses the inverse of the weighted correlation (rweighted) of the asymmetric variance and covariance matrix (panel a) to estimate the number of QTL within each segment (n(QTL)segment). c boxplot for the estimation of the number of QTL across 39,635 chromosome segments in bull data. d Boxplot for the estimation of the number of pleiotropic QTL across 40,763 chromosome segments in cow data. Each dot on c and d indicate the estimated number of causal QTL per segment. For each box, the minimum is the lowest point, the maximum is the highest point, whiskers are maxima 1.5 times of interquartile range, the bottom bound, middle line and top bound of the box are the 25th percentile, median and the 75th percentile, respectively.
