Weighted single-step genomic best linear unbiased prediction integrating variants selected from sequencing data by association and bioinformatics analyses

Aoxing Liu; Mogens Sandø Lund; Didier Boichard; Emre Karaman; Bernt Guldbrandtsen; Sebastien Fritz; Gert Pedersen Aamand; Ulrik Sander Nielsen; Goutam Sahana; Yachun Wang; Guosheng Su

doi:10.1186/s12711-020-00568-0

Genetics Selection Evolution

Table 6 Regression coefficients of yield deviation (YD) on prediction from a pedigree-based BLUP (PBLUP) model and different ssGBLUP models using different SNP sets for female fertility traits

From: Weighted single-step genomic best linear unbiased prediction integrating variants selected from sequencing data by association and bioinformatics analyses

Trait	Population	Model	Pedigree	SNP
Trait	Population	Model	Pedigree	54K	54K + DFS	54K + FRA	54K + DFS + FRA
IFLh	Genotyped	PBLUP	1.64	–	–	–	–
		ssGBLUP	–	_a1.56^a	_a1.54^a	_a1.55^a	_a1.53^a
		ssFGBLUP	–	–	_a1.55^a	_a1.49^a	_a1.46^a
		ssWGBLUP_bin1	–	_a1.55^a	_a1.54^a	_a1.55^a	_a1.53^a
		ssWGBLUP_bin30	–	_a1.55^a	_a1.53^a	_a1.53^a	_a1.51^a
		ssWGBLUP_bin100	–	_a1.54^a	_a1.53^a	_a1.52^a	_a1.53^a
	Non-genotyped	PBLUP	1.08	–	–	–	–
		ssGBLUP	–	_a1.10^a	_a1.10^a	_a1.10^a	_a1.10^a
		ssFGBLUP	–	–	_a1.02^a	_a1.09^a	_a1.05^a
		ssWGBLUP_bin1	–	_a1.10^a	_a1.09^a	_a1.10^a	_a1.10^a
		ssWGBLUP_bin30	–	_a1.10^a	_a1.09^a	_a1.10^a	_a1.10^a
		ssWGBLUP_bin100	–	_a1.10^a	_a1.09^a	_a1.10^a	_a1.11^a
IFLc	Genotyped	PBLUP	1.17	–	–	–	–
		ssGBLUP	–	_a1.18^a	_a1.17^a	_a1.20^a	_a1.18^a
		ssFGBLUP	–	–	_a1.11^a	_a1.20^a	_a1.14^a
		ssWGBLUP_bin1	–	_a1.18^a	_a1.16^a	_a1.19^a	_a1.17^a
		ssWGBLUP_bin30	–	_a1.18^a	_a1.16^a	_a1.19^a	_a1.16^a
		ssWGBLUP_bin100	–	_a1.17^a	_a1.15^a	_a1.18^a	_a1.17^a
	Non-genotyped	PBLUP	1.32	–	–	–	–
		ssGBLUP	–	_a1.03^bc	_a1.02^c	_a1.05^a	_a1.04^ab
		ssFGBLUP	–	–	_b0.99^c	_a1.07^a	_ab1.04^b
		ssWGBLUP_bin1	–	_b1.02^b	_ab1.01^b	_b1.04^a	_b1.02^ab
		ssWGBLUP_bin30	–	_b1.00^a	_b0.99^a	_c1.01^a	_c1.00^a
		ssWGBLUP_bin100	–	_b1.00^a	_b0.99^a	_bc1.00^a	_bc0.99^a
ICF	Genotyped	PBLUP	0.57	–	–	–	–
		ssGBLUP	–	_a0.66^a	_a0.67^a	_a0.67^a	_a0.67^a
		ssFGBLUP	–	–	_a0.67^a	_a0.67^a	_a0.68^a
		ssWGBLUP_bin1	–	_a0.66^a	_a0.67^a	_a0.66^a	_a0.67^a
		ssWGBLUP_bin30	–	_a0.65^a	_a0.66^a	_a0.66^a	_a0.67^a
		ssWGBLUP_bin100	–	_a0.65^a	_a0.66^a	_a0.66^a	_a0.66^a
	Non-genotyped	PBLUP	0.89	–	–	–	–
		ssGBLUP	–	_a0.71^b	_a0.72^ab	_a0.73^a	_a0.73^a
		ssFGBLUP	–	–	_a0.74^a	_a0.75^a	_a0.76^a
		ssWGBLUP_bin1	–	_a0.71^b	_a0.72^ab	_a0.73^ab	_a0.73^a
		ssWGBLUP_bin30	–	_a0.71^b	_a0.72^ab	_a0.73^ab	_a0.73^a
		ssWGBLUP_bin100	–	_a0.71^b	_a0.72^ab	_a0.73^a	_a0.73^a

ssGBLUP models = a single-step genomic BLUP (ssGBLUP) model, a featured ssGBLUP (ssFGBLUP) model, and weighted ssGBLUP models with a region size of 1 (ssWGBLUP_bin1), 30 (ssWGBLUP_bin30), or 100 SNPs (ssWGBLUP_bin100)
SNP sets = SNPs in the 54K-SNP chip (54K), SNPs in the 54K-SNP chip together with sequencing SNPs selected by Denmark–Finland–Sweden (54K + DFS), SNPs in the 54K-SNP chip together with sequencing SNPs selected by France (54K + FRA), and SNPs in the 54K-SNP chip together with both sets of selected sequencing SNPs (54K + DFS + FRA)
IFLh the interval from first to last insemination in heifers, IFLc the interval from first to last insemination in cows, ICF the interval from calving to first insemination
_a,b,csubscript letters to the left are for comparisons among models using the same SNP set, and superscript letters to the right are for comparisons among SNP sets using the same model. Regression coefficients with no common letter differ significantly (P < 0.05)

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ISSN: 1297-9686

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Genetics Selection Evolution

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