Multi-omics-data-assisted genomic feature markers preselection improves the accuracy of genomic prediction

Table 2 Prediction accuracies using SNPs preselection based on GWAS results (S_GWAS)

Model	P-value cutoffs^a	Prediction accuracy (Mean ± SE^b)
		Startle response		Starvation resistance
		Female	Male	Female	Male
GBLUP^d	All^c	0.208 ± 0.020	0.181 ± 0.022	0.272 ± 0.017	0.307 ± 0.015
	< 0.05	0.186 ± 0.021	0.158 ± 0.022	0.207 ± 0.020	0.268 ± 0.020
	< 0.001	0.097 ± 0.025	0.087 ± 0.022	0.135 ± 0.025	0.140 ± 0.019
	< 0.0001	0.065 ± 0.018	0.053 ± 0.020	0.100 ± 0.019	0.032 ± 0.021
	< 0.00001	0.066 ± 0.019	0.060 ± 0.025	0.004 ± 0.021	−0.056 ± 0.019
GFBLUP^e	< 0.05	0.054 ± 0.026	0.049 ± 0.024	0.115 ± 0.025	0.121 ± 0.024
	< 0.001	0.083 ± 0.026	0.034 ± 0.023	0.036 ± 0.025	0.047 ± 0.019
	< 0.0001	0.041 ± 0.020	0.045 ± 0.021	0.130 ± 0.021	0.084 ± 0.020
	< 0.00001	0.068 ± 0.019	0.061 ± 0.025	0.101 ± 0.024	0.045 ± 0.017

^aP-value cutoffs: using different P-value cutoffs to preselect SNPs from whole genome sequencing (WGS) data based on the results of genome-wide association study (GWAS); ^bSE: Standard error; ^cAll: All SNPs of WGS data; ^dGBLUP Genomic best linear unbiased prediction; ^eGFBLUP: Genomic feature best linear unbiased prediction

ISSN: 2049-1891