Carcass weight (CW) is one of the most important economic traits in pigs, directly affecting the income of farmers. In this study, a genome wide association study was performed to detect significant single nucleotide polymorphisms (SNPs) affecting CW in pigs derived from a $F_2$ intercros...
Carcass weight (CW) is one of the most important economic traits in pigs, directly affecting the income of farmers. In this study, a genome wide association study was performed to detect significant single nucleotide polymorphisms (SNPs) affecting CW in pigs derived from a $F_2$ intercross between Landrace and Korean native pig (KNP). Using high-density porcine SNP chips, highly significant SNPs were identified on SSC12. Two candidate genes, LOC100523510 and LOC100621652, were subsequently selected within this region and further investigated. Within these candidate genes, five SNPs were identified and genotyped using the VeraCode GoldenGate assay. The results revealed that one SNP in the LOC100621652 gene and four SNPs in the LOC100523510 gene are highly associated with CW. These SNP markers can thus have significant applications for improving CW in KNP. However, the functions of these candidate genes are not fully understood and require further study.
Carcass weight (CW) is one of the most important economic traits in pigs, directly affecting the income of farmers. In this study, a genome wide association study was performed to detect significant single nucleotide polymorphisms (SNPs) affecting CW in pigs derived from a $F_2$ intercross between Landrace and Korean native pig (KNP). Using high-density porcine SNP chips, highly significant SNPs were identified on SSC12. Two candidate genes, LOC100523510 and LOC100621652, were subsequently selected within this region and further investigated. Within these candidate genes, five SNPs were identified and genotyped using the VeraCode GoldenGate assay. The results revealed that one SNP in the LOC100621652 gene and four SNPs in the LOC100523510 gene are highly associated with CW. These SNP markers can thus have significant applications for improving CW in KNP. However, the functions of these candidate genes are not fully understood and require further study.
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제안 방법
Association tests were performed between carcass weight (CW) and 60K SNPs (for pigs from the F2 intercross population between Landrace and KNP), then visualized with the Manhattan plot. The results revealed two chromosomes, SSC5 and SSC12, with chromosomal regions with a genomewide significance level of 5.
In this study, a GWAS was performed for CW in pigs derived from a F2 intercross between Landrace and KNP using high-density SNP chips to identify significant SNPs in candidate genes affecting the CW trait. These results will ultimately aid the design of breeding strategies for improving CW in pigs.
대상 데이터
Until recently, thirty-five QTLs affecting CW were identified over nearly the whole genome in pigs. Six QTLs were identified in SSC1, eight in SSC4, three each in SSC7 and SSC8, and two each in SSC10 and SSC14. In addition, one QTL was identified in six chromosomes (SSC 2, 3, 5, 6, 12, 13).
The positional candidate genes in the SSC12 CW QTL region were searched using the NCBI database (http://www. ncbi.nih.gov). The SNPs in the candidate genes were searched using previous results from the Hiseq 2000 (Illumina Inc.
(2011), which was the crossbred population between Landrace and KNP. This population was composed of 1,233 pigs from 79 full-sib F2 families. The male animals in the F2 population were not castrated.
데이터처리
The phenotype was processed with the Minitab program (Minitab, PA, USA). The mixed-effects model (including sire and dam as the random effects as well as SNP genotype and sex as the fixed effects) was used to calculate the least squares mean and standard error of the SNP genotypes with the SAS program (SAS ver 9.1, SAS Institute Inc., NC, USA). The Plink program was used for the association analyses between SNP genotypes and CW.
이론/모형
, USA) database. Additional SNP genotyping was performed using the VeraCode GoldenGate assay (Illumina Inc., USA).
The genome-wide threshold was applied using a Bonferroni correction (i.e., 0.05/number of SNP markers; P = 1.61×10-6).
The SNPs in the two positional candidate genes were investigated using previous genome sequencing information and five SNPs were identified. To validate the five SNPs from the two genes on SSC12, the VeraCode GoldenGate assay tool was applied. One SNP in the LOC100621652 gene and four SNPs in LOC100523510 gene were highly associated with the CW trait (Fig.
성능/효과
A total of nine candidate genes associated with CW were selected in the significant QTL region on SSC12 (LOC100523510, LOC100621652, LOC100521749, LOC100736982, MYHC, LOC100621981, DNAH2, MYOCD, WSB1). Among these, two significant candidate genes (LOC100523510, LOC 100621652) were further investigated because of their locations in the regions with the highest test statistics.
In conclusion, a GWAS was performed for the CW trait in a F2 intercross population between Landrace and KNP. The results indicated that two genes, LOC100621652 and LOC100523510, on SSC12 show significant associations with the CW trait.
8 cM region in Berkshire and Yorkshire crosses. Our results also demonstrated a significant association of CW with a region between the 88.5 and 113.1 cM interval (SW1962-SWR1021). Therefore, significant SNPs in this region were further investigated to identify causative SNPs that directly affect CW in pigs.
, USA). The filtered SNPs for the analysis had a minor allele frequency less than 5%, more than 10% of genotyping errors, less than or equal 0.001 for the Hardy Weinberg equilibrium error. At the end of filtration, 30,930 SNP markers remained for the GWAS.
intercross population between Landrace and KNP. The results indicated that two genes, LOC100621652 and LOC100523510, on SSC12 show significant associations with the CW trait. The identification and further validation of five SNPs can potentially be applied to improve CW in Korean native pigs.
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