Investigating the impact of non-additive genetic effects in the estimation of variance components and genomic predictions for heat tolerance and performance traits in crossbred and purebred pig populations

de Oliveira, Letícia Fernanda; Brito, Luiz F.; Marques, Daniele Botelho Diniz; da Silva, Delvan Alves; Lopes, Paulo Sávio; dos Santos, Cassiane Gomes; Johnson, Jay S.; Veroneze, Renata

doi:10.1186/s12863-023-01174-x

Table 5 Variance components for traits related to heat tolerance based on models fitting non-additive genetic effects

From: Investigating the impact of non-additive genetic effects in the estimation of variance components and genomic predictions for heat tolerance and performance traits in crossbred and purebred pig populations

Trait^a	Model^b	\(\widehat{{\sigma }_{a}^{2}}\)	\(\widehat{{\sigma }_{d}^{2}}\)	\(\widehat{{\sigma }_{aa}^{2}}\)	\(\widehat{{\sigma }_{pe}^{2}}\)	\(\widehat{{\sigma }_{e}^{2}}\)
T_Vall	MAIpe	0.0626 ± 0.0107	-	-	0.1274 ± 0.0081	0.3047 ± 0.0005
	MAIDpe	0.0618 ± 0.0111	0.0050 ± 0.0140	-	0.1237 ± 0.0128	0.3047 ± 0.0005
	MAIDEpe	0.0616 ± 0.0121	0.0047 ± 0.0144	0.0031 ± 0.0340	0.1213 ± 0.0294	0.3047 ± 0.0005
	MAIEpe	0.0618 ± 0.0120		0.0050 ± 0.0336	0.1231 ± 0.0290	0.3047 ± 0.0005
T_V4days	MAIpe	0.0653 ± 0.0113	-	-	0.1266 ± 0.0086	0.1378 ± 0.0014
	MAIDpe	0.0642 ± 0.0116	0.0068 ± 0.0145	-	0.1216 ± 0.0132	0.1378 ± 0.0014
	MAIDEpe	0.0642 ± 0.0116	0.0068 ± 0.0145	3.48 × 10⁻⁹ ± 0.00000	0.1216 ± 0.0132	0.1378 ± 0.0014
	MAIEpe	0.0653 ± 0.0113	-	3.48 × 10⁻⁹ ± 0.00000	0.1266 ± 0.0086	0.1378 ± 0.0014
T_ES	MAIpe	0.0316 ± 0.0069	-	-	0.0507 ± 0.0059	0.7287 ± 0.0074
	MAIDpe	0.0316 ± 0.0069	1.84 × 10⁻⁸ ± 0.00000	-	0.0507 ± 0.0059	0.7287 ± 0.0074
	MAIDEpe	0.0316 ± 0.0069	1.84 × 10⁻⁸ ± 0.00000	1.84 × 10⁻⁸ ± 0.00000	0.0507 ± 0.00589	0.7287 ± 0.0074
	MAIEpe	0.0316 ± 0.0069	-	1.84 × 10⁻⁸ ± 0.00000	0.0507 ± 0.00589	0.7287 ± 0.0074
T_SS	MAIpe	0.0445 ± 0.0100	-	-	0.1176 ± 0.0090	0.6119 ± 0.0062
	MAIDpe	0.0437 ± 0.0104	0.0045 ± 0.0165	-	0.1145 ± 0.0145	0.6119 ± 0.0062
	MAIDEpe	0.0437 ± 0.0104	0.0045 ± 0.0165	1.54 × 10⁻⁷ ± 0.00000	0.1145 ± 0.0145	0.6119 ± 0.0062
	MAIEpe	0.0445 ± 0.0100	-	1.54 × 10⁻⁷ ± 0.00000	0.1176 ± 0.0090	0.6119 ± 0.0062
T_RS	MAIpe	0.0276 ± 0.0063	-	-	0.0739 ± 0.0056	0.3577 ± 0.0036
	MAIDpe	0.0276 ± 0.0063	9.05 × 10⁻⁹ ± 0.00000	-	0.0739 ± 0.0056	0.3577 ± 0.0036
	MAIDEpe	0.0276 ± 0.0063	9.05 × 10⁻⁹ ± 0.00000	9.05 × 10⁻⁹ ± 0.00000	0.0739 ± 0.0056	0.3577 ± 0.0036
	MAIEpe	0.0276 ± 0.0063	-	9.05 × 10⁻⁹ ± 0.00000	0.0739 ± 0.0056	0.3577 ± 0.0036
T_TS	MAIpe	0.0283 ± 0.0067	-	-	0.0730 ± 0.0060	0.4525 ± 0.0046
	MAIDpe	0.0278 ± 0.0070	0.0021 ± 0.0096	-	0.0716 ± 0.0089	0.4525 ± 0.0046
	MAIDEpe	0.0278 ± 0.0070	0.0021 ± 0.0096	1.14 × 10⁻⁸ ± 0.00000	0.0716 ± 0.00889	0.4525 ± 0.0046
	MAIEpe	0.0283 ± 0.0067	-	1.14 × 10⁻⁸ ± 0.00000	0.0730 ± 0.0060	0.4525 ± 0.0046
RR	MAIpe	34.7580 ± 7.0790	-	-	70.3639 ± 5.9429	442.7150 ± 4.4814
	MAIDpe	34.7580 ± 7.0790	1.11 × 10⁻⁵ ± 0.00000	-	70.3639 ± 5.9429	442.7150 ± 4.4814
	MAIDEpe	34.7580 ± 7.0790	1.11 × 10⁻⁵ ± 0.00000	1.11 × 10⁻⁵ ± 0.00000	70.3639 ± 5.9429	442.7150 ± 4.4814
	MAIEpe	34.7580 ± 7.0790	-	1.11 × 10⁻⁵ ± 0.00000	70.3639 ± 5.9429	442.7150 ± 4.4814
PS	MAIpe	0.0551 ± 0.0185	-	-	0.1297 ± 0.0195	0.8463 ± 0.0191
	MAIDpe	0.0542 ± 0.0194	0.0044 ± 0.0291	-	0.1267 ± 0.0282	0.8463 ± 0.0191
	MAIDEpe	0.0298 ± 0.0204	2.14 × 10⁻⁸ ± 0.00000	0.1379 ± 0.0711	0.0137 ± 0.0623	0.8463 ± 0.0191
	MAIEpe	0.0298 ± 0.0204	-	0.1379 ± 0.0711	0.0137 ± 0.0623	0.8463 ± 0.0191
HD	MAI	0.1088 ± 0.0247	-	-	-	0.3052 ± 0.0206
	MAID	0.1040 ± 0.0256	0.0289 ± 0.0366	-	-	0.2854 ± 0.0324
	MAIDE1	0.0795 ± 0.0278	0.0147 ± 0.0367	0.1745 ± 0.1015	-	0.1437 ± 0.0876
	MAIE	0.0806 ± 0.0275	-	0.1845 ± 0.0997	-	0.1455 ± 0.0876

\(\widehat{{\sigma }_{a}^{2}}\): additive genetic variance estimate
\(\widehat{{\sigma }_{d}^{2}}\): dominance variance estimate
\(\widehat{{\sigma }_{aa}^{2}}\): additive-by-additive epistatic variance estimate
\(\widehat{{\sigma }_{pe}^{2}}\): permanent environmental variance estimate
\(\widehat{{\sigma }_{e}^{2}}\): residual variance estimate
^aT_Vall: all measures (every 10 min) of vaginal temperatures during four days (°C); T_V4days: four-time measures of vaginal temperatures during four days (°C); T_ES: ear skin temperature; T_SS: shoulder skin temperature; T_RS: rump skin temperature; T_TS: tail skin temperature; RR: respiration rate; PS: panting score; HD: hair density.
^bMAIpe: \(\textbf{y}=\textbf{X}\varvec{\upbeta }+\textbf{fb}+\textbf{Za}+\textbf{Zpe}+\varvec{\upepsilon }\); MAIEpe: \(\textbf{y}=\textbf{X}\varvec{\upbeta }+\textbf{fb}+\textbf{Za}+\textbf{Zpe}+\textbf{Z}{\varvec{e}}_{\textbf{aa}}+\varvec{\upepsilon }\); MAIDpe: \(\textbf{y}=\textbf{X}\varvec{\upbeta }+\textbf{fb}+\textbf{Za}+\textbf{Zpe}+\textbf{Zd}+\varvec{\upepsilon }\); MAIDEpe: \(\textbf{y}=\textbf{X}\varvec{\upbeta }+\textbf{fb}+\textbf{Za}+\textbf{Zd}+\textbf{Z}{\varvec{e}}_{\textbf{aa}}+\textbf{Zpe}+\varvec{\upepsilon }\); MAI: \(\textbf{y}=\textbf{X}\varvec{\upbeta }+\textbf{fb}+\textbf{Za}+\varvec{\upepsilon }\); MAIE: \(\textbf{y}=\textbf{X}\varvec{\upbeta }+\textbf{fb}+\textbf{Za}+\textbf{Z}{\varvec{e}}_{\textbf{aa}}+\varvec{\upepsilon }\); MAID: \(\textbf{y}=\textbf{X}\varvec{\upbeta }+\textbf{fb}+\textbf{Za}+\textbf{Zd}+\varvec{\upepsilon }\); MAIDE1:\(\textbf{y}=\textbf{X}\varvec{\upbeta }+\textbf{fb}+\textbf{Za}+\textbf{Zd}+\textbf{Z}{\varvec{e}}_{\textbf{aa}}+\varvec{\upepsilon }\)

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