Prediction of genomic breeding values for growth, carcass and meat quality traits in a multi-breed sheep population using a HD SNP chip

Table 2 Heritability estimates, expected accuracy, theoretical accuracy, effective number of progeny and observed accuracies of molecular breeding values in different scenarios for traits measured in the live animal (growth and carcass traits)

Trait¹	h² ± SE	AccE	AccT	ENP	GB0	GB2PC	GB4PC	GB6PC	GB10	GB20	GBRCV	GBKCV	GBC
BWT	0.10 ± 0.03	0.08	0.25	1	0.15	0.14	0.14	0.12	0.16	0.18	0.33 ± 0.24	0.14 ± 0.06	0.11 ± 0.02
WWT	0.19 ± 0.02	0.45	0.45	1	0.19	0.17	0.15	0.14	0.19	0.19	0.46 ± 0.01	0.24 ± 0.08	0.08 ± 0.06
LW6	0.30 ± 0.01	0.51	0.48	1	0.25	0.23	0.22	0.21	0.25	0.25	0.41 ± 0.03	0.22 ± 0.06	0.14 ± 0.09
EMD	0.35 ± 0.01	0.44	0.49	2	0.40	0.37	0.38	0.37	0.40	0.40	0.53 ± 0.03	0.28 ± 0.05	0.20 ± 0.08
EMDad	0.43 ± 0.01	0.48	0.46	3	0.48	0.43	0.44	0.44	0.48	0.48	0.56 ± 0.01	0.37 ± 0.06	0.24 ± 0.11
EMW	0.24 ± 0.01	0.38	0.45	2	0.31	0.31	0.32	0.30	0.31	0.31	0.52 ± 0.03	0.28 ± 0.05	0.23 ± 0.13
EMWad	0.31 ± 0.01	0.42	0.47	3	0.44	0.43	0.43	0.42	0.44	0.43	0.54 ± 0.02	0.33 ± 0.06	0.31 ± 0.12
FDM	0.28 ± 0.01	0.41	0.45	2	0.33	0.23	0.22	0.22	0.33	0.33	0.48 ± 0.04	0.24 ± 0.08	0.16 ± 0.02
FDMad	0.33 ± 0.01	0.43	0.47	2	0.37	0.23	0.22	0.20	0.37	0.38	0.49 ± 0.04	0.27 ± 0.10	0.15 ± 0.10
PRESLT	0.25 ± 0.02	0.49	0.44	3	0.35	0.28	0.25	0.25	0.35	0.35	0.47 ± 0.02	0.28 ± 0.09	0.16 ± 0.11
Average	0.28 ± 0.08	0.41 ± 0.11	0.44	2.00 ± 0.74	0.33 ± 0.10	0.28 ± 0.09	0.28 ± 0.10	0.27 ± 0.10	0.33 ± 0.09	0.33 ± 0.09	0.48 ± 0.06	0.26 ± 0.07	0.18 ± 0.07

¹Abbreviations are presented in Table 1; “ad”: traits that were adjusted for correlated variables; h²: heritability estimate; AccE: Expected accuracy; AccT: Theoretical accuracy from the MME; ENP: effective number of progeny calculated using the accuracies from GB0; GB0: GBLUP accuracies fitting only G matrix; GB10 and GB20: accuracies of GBLUP fitting G matrix and 10 or 20% of A matrix, respectively; GB2PC, GB4PC and GB6PC: GBLUP accuracies fitting for 2, 4 or 6 principal components, respectively; GBRCV: GBLUP accuracies for random cross-validation; GBKCV: GBLUP accuracies for k-means clustering; GBC: GBLUP accuracies for predictions performed within each cluster

ISSN: 2730-6844