High density marker panels, SNPs prioritizing and accuracy of genomic selection

BMC Genomic Data

Table 3 Number of selected SNPs, number of tagged QTLs, percentage of genetic variance explained, and accuracies of genomic and phenotype prediction under different quantile of the distribution of FST scores, sampling distribution for the QTL effects and density of the marker panel using the proposed method. Standard errors of accuracies are listed between parentheses

	All SNPs		97.5 quantile¹		99.0 quantile		99.5 quantile
	Gamma²	Predefined³	Gamma	Predefined	Gamma	Predefined	Gamma	Predefined
200 K SNP marker panel
Selected SNP	200 K	200 K	4932	5620	1956	2171	935	1076
Tagged QTL⁴	95	97	33	69	18	47	13	31
% GV⁵	91.29	98.60	83.70	71.27	73.57	49.69	64.08	35.10
Acc_P⁶	0.462	0.445	0.503	0.490	0.472	0.415	0.434	0.359
	(0.018)	(0.012)	(0.017)	(0.014)	(0.015)	(0.018)	(0.028)	(0.032)
Acc_G⁷	0.777	0.741	0.853	0.830	0.797	0.704	0.725	0.617
	(0.017)	(0.012)	(0.019)	(0.023)	(0.017)	(0.031)	(0.037)	(0.026)
400 K SNP marker panel
Selected SNP	400 K	400 K	10,173	10,651	3586	4646	2078	2037
Tagged QTL	95	99	38	74	20	53	13	34
% GV	96.73	99.01	84.03	75.09	73.83	56.66	66.12	43.79
Acc_P	0.456	0.438	0.506	0.485	0.473	0.433	0.448	0.350
	(0.015)	(0.017)	(0.014)	(0.017)	(0.029)	(0.021)	(0.039)	(0.028)
Acc_G	0.775	0.735	0.860	0.813	0.807	0.722	0.765	0.685
	(0.020)	(0.012)	(0.015)	(0.012)	(0.041)	(0.025)	(0.059)	(0.052)

¹quantile of the distribution of the F_ST scores, ²QTL effects sampled from a Gamma distribution, ³QTL effects pre-defined to explain at least 0.5% of genetic variance (GV), ⁴QTL with r² > 0.7 with at least one selected SNP, ⁵GV = Genetic Variance, ⁶accuracy of phenotype prediction, ⁷accuracy of genomic prediction

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