We compared the performance of the multi-trait predictors \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left( {\widehat {\bf{g}}_{{\mathrm{wMT}} - {\mathrm{SBLUP}}}} \right)$$\end{document}g^wMT-SBLUP not only to the performance of the single-trait predictor \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left( {\widehat {\bf{g}}_{{\mathrm{SBLUP}}}} \right)$$\end{document}g^SBLUP for the same trait but also to the performance of all other (cross-trait) single-trait predictors for the traits that exhibited significant rG with the focal trait (Fig. 4). This is appropriate because in some traits the single-trait predictor from the same trait is not the most accurate single-trait predictor.