GWAS Of Meat Yield,Body Fat And Meat Quality Traits In Nonghua Ducks

Genome-wide association studies(GWAS)has advantages including higher accuracy and higher sensitivity,therefore,it has been widely used in studies focusing on human genetics and animal breeding.Meat yield,body fat and meat quality traits are important economic traits of ducks,and they are also typical quantitative traits.Screening of genetic variations and functional genes affecting these traits will be helpful for meat duck breeding.In addition,variants and genes related to these traits can provide a reference for the exploring of molecular mechanisms of traits formation.In this study,225 Nonghua ducks were used as experimental materials,high-density SNP markers of this population were obtained by simplified genome sequencing,and then the genotypes of above-mentioned SNPs were imputed based on a reference sequence set.After genotype imputation,GWAS analysis of meat yield,fat yield,and meat quality were carried out.The main results are as follows :1.Within the experimental population,the variation coefficients of traits were3.54%-27.61%,and there were negative phenotypic and genetic correlations among meat yield traits and body fat traits,while the genetic basis of meat quality traits may be relatively independent.Based on the simplified genome sequencing data,112,894high-quality and evenly distributed SNPs were discovered.By using a reference sequence set,genotype imputation improved the number of SNPs to 358,640.2.The population stratification of Nonghua ducks was relatively weak,in detail,the cumulative explanation rate of the first 10 principal components was less than 10%.The appropriate number of principal components used in GWAS model was 0 for all traits.Different GWAS models(GLM,MLM,CMLM and Farm CPU)were compared,and it was found that Farm CPU model has the best performance.3.Through GWAS analysis,associated SNPs and regions of traits related to meat yield were mapped to chromosomes 3,4,and 28.Among them,the mutant allele of SNP4＿57347099 could increase both leg muscle weight by 14.08 g and lean meat weight by33.06 g.IGF2BP1 and UBE2 Z were important candidate genes for meat yield.The significant SNP 28＿137217 located within the 3’UTR of UBE2 Z gene,thus may play a causal role by regulating gene expression level.4.Through GWAS analysis,associated SNPs and regions of traits related to fat yield were mapped to chromosomes 1,3,4,13,14 and 29.Among them,the mutant allele of SNP 29＿3072666 could increase both sebum weight by 128.87 g and fat weight by144.38 g,whereas the mutant allele of SNP 13＿10434859 could decrease sebum weight by 53.66 g and fat weight by 59.18 g.CARD10,QRFPR and SH3PXD2 B were candidate genes.The significant SNP 14＿11177480 located within the 3’UTR of SH3PXD2 B gene,thus may play a causal role by regulating gene expression level.5.Through GWAS analysis,associated SNPs and regions of meat to fat ratio were mapped to chromosomes 1,3,4,26 and 27.QRFPR,MEF2 D,and FOXN2 were candidate genes for this trait.Sequence analysis indicated that the CAG repeat sequence within MEF2 D gene was a potential causative mutation.Sanger sequencing verified that both the CAG repeat sequence and its flanking SNPs had significant impacts on meat to fat ratio,meat yield and body fat traits.6.GWAS analysis of meat quality traits found 14 and 7 associated SNPs for pectoral muscle shear force and leg muscle shear force,respectively.But there was no candidate gene and potential causal variation be found.In summary,this study has discovered and imputed high-density SNP markers suitable for Nonghua ducks,and then applied them to the GWAS analysis of meat yield,fat yield,and meat quality.The results showed significant associated SNPs and genomic regions for traits,and SNPs with relatively big genetic effects,important candidate genes and potential causal variants were obtained.These will be helpful for clarifying the genetic basis of above traits and lay the foundation for the further breeding and the establishment of genomic selection system of Nonghua duck.