Abstract
A within-breed genome-wide association study (GWAS) is useful when identifying the QTL that segregates in a breed. However, an across-breed meta-analysis can be used to increase the power of identification and precise localization of QTL that segregate in multiple breeds. Precise localization will allow including QTL information from other breeds in genomic prediction due to the persistence of the linkage phase between the causal variant and the marker. This study aimed to identify and confirm QTL detected in within-breed GWAS through a meta-analysis in three French dairy cattle breeds. A set of sequence variants selected based on their functional annotations were imputed into 50 k genotypes for 46,732 Holstein, 20,096 Montbeliarde, and 11,944 Normande cows to identify QTL for milk production, the success rate at insemination of cows (fertility) and stature. We conducted within-breed GWAS followed by across-breed meta-analysis using a weighted Z-scores model on the GWAS summary data (i.e., P-values, effect direction, and sample size). After Bonferroni correction, the GWAS result identified 21,956 significantly associated SNP (PFWER < 0.05), while meta-analysis result identified 9,604 significant SNP (PFWER < 0.05) associated with the phenotypes. The meta-analysis identified 36 QTL for milk yield, 48 QTL for fat yield and percentage, 29 QTL for protein yield and percentage, 13 QTL for fertility, and 16 QTL for stature. Some of these QTL were not significant in the within-breed GWAS. Some previously identified causal variants were confirmed, e.g., BTA14:1802265 (fat percentage, P = 1.5 × 10−760; protein percentage, P = 7.61 × 10−348) both mapping the DGAT1-K232A mutation and BTA14:25006125 (P = 8.58 × 10−140) mapping PLAG1 gene was confirmed for stature in Montbeliarde. New QTL lead SNP shared between breeds included the intronic variant rs109205829 (NFIB gene), and the intergenic variant rs41592357 (1.38 Mb upstream of the CNTN6 gene and 0.65 Mb downstream of the CNTN4 gene). Rs110425867 (ZFAT gene) was the top variant associated with fertility, and new QTL lead SNP included rs109483390 (0.1 Mb upstream of the TNFAIP3 gene and 0.07 Mb downstream of PERP gene), and rs42412333 (0.45 Mb downstream of the RPL10L gene). An across-breed meta-analysis had greater power to detect QTL as opposed to a within breed GWAS. The QTL detected here can be incorporated in routine genomic predictions.
Highlights
The magnitude of estimated effects on the quantitative trait of interest could be used to rank single nucleotide polymorphisms (SNP) for a functional genomic study to identify causal variants
Our meta-analysis of association summary statistics for seven traits across three French dairy cattle breeds discovered 120 quantitative trait loci (QTL) including 13 QTL that had not been detected at P < 1.03 × 10−6 in the within-breed analyses
In agreement with previous studies (Pausch et al, 2017) our results show that combining genome-wide association study (GWAS) summary data from several breeds increases the power of association studies
Summary
The magnitude of estimated effects on the quantitative trait of interest could be used to rank single nucleotide polymorphisms (SNP) for a functional genomic study to identify causal variants. Causal variants reported for QTL in previous dairy cattle studies include polymorphisms causing variation in milk production, fertility, and embryo mortality (Grisart et al, 2002; Hoff et al, 2017; Michot et al, 2017; Bouwman et al, 2018). A meta-analysis can be used to improve the resolution of QTL detection and identify causal variants provided that LD is conserved at short distances across breeds (van den Berg et al, 2016). The main advantage of a meta-analysis is that it allows simultaneous analysis of many breeds by combining GWAS summary statistics across populations, thereby increasing power to detect QTL (van den Berg et al, 2016; Bouwman et al, 2018)
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