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Table 3 Summary of the number of independent SNPs/number of SNPs associated with the seven traits

From: Leveraging breeding programs and genomic data in Norway spruce (Picea abies L. Karst) for GWAS analysis

Method Genetic cluster Trait
BB Height DBH FD WD MFA WS
CMLM Whole pop. 10/16 (0.68–6.70) 0 2/3 (1.15–1.51) 3/6 (2.22–5.19) 3/3 (0.68–0.82) 0 0
ALP 7/12 0 0 NA 0 0 0
CEU 2/5 0 0 NA 0 0 1/2
CSE 2/4 0 0 NA 0 0 0
NPL 2/4 0 0 NA 0 0 0
Rus_Bal 0 0 0 NA 0 0 2/2
ROM NA NA NA NA NA NA NA
NFE 0 0 NA NA 0 0 0
BLINK Whole pop. 24/24 (0.13–6.70) 3/3 (0.33–0.48) 2/2 (0.57–0.62) 1/1 (5.19) 3/3 (0.07–0.82) 0 0
ALP 1/1 0 0 NA 2/2 0 0
CEU 2/2 0 0 NA 0 0 1/2
CSE 2/2 0 0 NA 0 0 0
NPL 1/1 0 0 NA 0 0 0
Rus_Bal 0 0 0 NA 0 0 3/3
ROM NA NA NA NA NA NA NA
NFE 6/6 0 NA NA 0 1/2 0
Total SNPs 40/47 (0.13–6.70) 3/3 (0.330.48) 4/5 (0.57–1.51) 3/6 (2.22–5.19) 6/6 (0.07–0.82) 1/2 (0.14) 4/5 (0.06–0.21)
R2* 15.7 1.5 2.6 4.9 2.4 0.1 0.5
R2** 4.7 1.7 NA NA 0 0 0
  1. In this study, we performed GWAS in the whole elite tree population and seven genetic clusters by two methods (CMLM and BLINK), phenotypic variance explained (PVE2) by a single SNP shown in parenthesis, and cumulative phenotypic variance explained by all associated SNPs (R2*) for each trait in the whole elite tree population and the validation population (R2**) in the two full-sib progeny field plantations in Northern Sweden. BB budburst stage, DBH diameter at breast height, FD frost damage, WD wood density, MFA microfibril angle, WS wood stiffness. NA: represents that we did not perform CMLM for each genetic cluster because of small cluster size in several clusters, such as NFE and ROM in Table 2