Computational protocol: A whole genome association study to detect additive and dominant single nucleotide polymorphisms for growth and carcass traits in Korean native cattle, Hanwoo

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Protocol publication

[…] A mixed-inheritance animal model was used to detect SNP with additive or dominance effects for growth and carcass quality of Hanwoo. The ‘snp_a’, ‘snp_d’, and ‘snp_ad’ options of Qxpak software (Barcelona, Spain) were applied for each SNP. For each trait, appropriate fixed factors or covariates were fitted in the models (p<0.05) using a general linear model procedure in SAS (SAS 9.1, SAS Institute Inc., Cary, NC, USA).Firstly, the additive and dominance expression model (Add+Dom) was chosen as a base model:Where yi is the phenotypic record of animal i, μ is the average phenotypic performance, cji is the value of the jth covariate or fixed effect for the animal i, βj is an estimate of the jth fixed effect or covariate, SNPad_i is the additive and dominance effect of SNP for animal i (e.g. individuals with marker genotypes ‘11’, ‘12’, and ‘22’ are assumed to have genetic values μkAA, μkAB, and μkBB), ui is the infinitesimal genetic effect of animal i, which is distributed as N(0,A σu2) (the numerator relationship matrix A and the additive genetic variance σu2) and ei is a random residual for animal i, which is distributed as N(0,Iσe2)( identity matrix I and residual variance σe2). Two fixed effects were fitted in the models: year and season of birth (5 levels) for all the traits and region where the steers were born (41 levels) for WWT, YWT, and Marb, and a covariate was fitted; weaning age for WWT, yearling age for YWT, slaughter age for CWT, BFT, and LMA, was also fitted. Pedigrees of the base population animals were traced back for two generations to form the numerator relationship matrix, and 1,033 animals were included in the pedigree analysis.The next models are the additive (Add) and dominance (Dom) expression models, and the null model:Where yi, μ, cji, βj, ui as described above, SNPa_i is the additive(a) effect of the SNP genotype values for animal i (e.g. individuals with marker genotypes ‘11’, ‘12’, and ‘22’ are assumed to have genetic values μkAA, 0, and μkBB), and SNPd_i is the dominance effect of the SNP for animal i (e.g. individuals with marker genotypes ‘11’, ‘12’, and ‘22’ are assumed to have genetic values 0, μkAB and 0).A series of tests was applied to classify gene expression pattern; additive or dominant, following the decision trees ():If the Add+Dom Model vs the Null model was significant at the 5% chromosome-wise (ChW) level:If the Add+Dom model vs the Add model was significant and the Add+Dom model vs the Dom model was not significant at the 5% comparison wise level, then the SNP was defined to have dominance inheritance mode of gene action.If the Add+Dom model vs the Add model was not significant and the Add+Dom model vs the Dom model was significant at the 5% comparison wise level, then the SNP was defined to have additive inheritance mode of gene action.If the Add+Dom model vs the Add model and the Add+Dom model vs the Dom model were both significant or both not significant at the 5% comparison wise level, then the SNP was defined to have additive and dominance expressed.If the Add+Dom model vs the Null model was not significant at the 5% ChW level:If the Add model vs the Null model was significant at the 5% ChW level, then the SNP was classified as additive expressed SNP.If the Dom model vs the Null model was significant at the 5% ChW level, then the SNP was classified as dominance expressed SNP.All the models were fitted for each of the available SNPs. The log likelihood ratio tests (LRT) statistic was applied by comparing the log likelihoods between the full model and the reduced model:The LRT test statistics approximately followed chi-squared distributions with degree of freedom equal to the number of extra parameters (one or two) estimated in the full model compared with the reduced model.False discovery rate (FDR) was used to set significant thresholds to account for multiple testing, by calculating q-value based on nominal p-value from LRT test statistic for each trait using the R packages ‘qvalue’. The FDR threshold was set at 5% genome-wise (GW) or a 5% ChW level. […]

Pipeline specifications

Software tools QxPak, snpAD
Applications WGS analysis, GWAS
Organisms Bos taurus
Diseases Muscular Diseases
Chemicals Nitroprusside, Nucleotides