A multi-trait Bayesian method for mapping QTL and genomic prediction

Table 6 Accuracy and bias of genomic predictions for milk production^a traits using different reference populations and different analysis methods and when validated in Holstein, Jersey or Australian Red animals

Analysis method^b	Reference dataset	Validation dataset	Accuracy^c			Bias
Analysis method^b	Reference dataset	Validation dataset	FY	MY	PY	FY	MY	PY
BayesR^d	Holstein	Holstein	0.63	0.62	0.58	1.22	0.89	1.02
BayesR_LC	Holstein	Holstein	0.65	0.62	0.57	1.17	0.91	0.99
BayesMV	Holstein	Holstein	0.65	0.63	0.59	1.21	0.89	1.03
BayesR^d	Hol_Jer	Holstein	0.65	0.63	0.58	1.25	0.89	0.99
BayesR_LC	Hol_Jer	Holstein	0.65	0.62	0.58	1.14	0.90	0.97
BayesMV	Hol_Jer	Holstein	0.66	0.63	0.58	1.17	0.87	0.97
BayesR^d	Jersey	Jersey	0.56	0.70	0.72	0.89	0.98	1.24
BayesR_LC	Jersey	Jersey	0.57	0.70	0.72	0.70	1.05	1.17
BayesMV	Jersey	Jersey	0.55	0.70	0.71	0.81	1.00	1.11
BayesR^d	Hol_Jer	Jersey	0.56	0.69	0.71	0.93	0.95	1.18
BayesR_LC	Hol_Jer	Jersey	0.58	0.69	0.73	0.92	1.00	1.20
BayesMV	Hol_Jer	Jersey	0.55	0.66	0.69	0.92	0.96	1.15
BayesR^d	Hol_Jer	Aust Red	0.26	0.22	0.10	0.89	0.56	0.38
BayesR_LC	Hol_Jer	Aust Red	0.28	0.20	0.12	0.87	0.53	0.41
BayesMV	Hol_Jer	Aust Red	0.26	0.14	0.07	0.75	0.34	0.25

^aMilk production traits were fat yield (FY), milk yield (MY) and protein yield (PY)
^bMethods were either BayesR on raw phenotypes (BayesR), linear combinations of traits analyzed with univariate BayesR (BayesR_LC) or the multivariate BayesMV method
^cStandard errors are approximately 0.062 for Holstein, 0.098 for Jersey and 0.074 for Australian Red predictions
^dUnivariate results from Kemper et al. [1]

ISSN: 1297-9686