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Genome wide association study on feed conversion ratio using imputed sequence data in chickens.
Asian-Australasian Journal of Animal Sciences 2018 October 27
Objective: Feed consumption contributes a large percentage for total production costs in the poultry industry. Detecting genes associated with feeding traits will be of benefit to improve our understanding of the molecular determinants for feed efficiency. The objective of this study was to identify candidate genes associated with feed conversion ratio (FCR) via genome-wide association study (GWAS) using sequence data imputed from SNP panel in a Chinese indigenous chicken population.
Methods: A total of 435 Chinese indigenous chickens were phenotyped for FCR and were genotyped using a 600K single nucleotide polymorphism (SNP) genotyping array. Twenty-four birds were selected for sequencing, and the 600K SNP panel data were imputed to whole sequence data with the 24 birds as the reference. GWAS were performed with GEMMA software.
Results: After quality control, 8,626,020 SNPs were used for sequence based GWAS, in which ten significant genomic regions were detected to be associated with FCR. Ten candidate genes, USP44, LTA4H, ELK3, RSPO2, IAP3, SOWAHD, CAMSAP2, ZBTB41, KCNT2 and RAP1A were annotated. Several of them were within or near the reported FCR QTLs, and others were newly reported.
Conclusion: Results from this study provide valuable prior information on chicken genomic breeding program, and potentially improved our understanding of the molecular mechanism for feeding traits.
Methods: A total of 435 Chinese indigenous chickens were phenotyped for FCR and were genotyped using a 600K single nucleotide polymorphism (SNP) genotyping array. Twenty-four birds were selected for sequencing, and the 600K SNP panel data were imputed to whole sequence data with the 24 birds as the reference. GWAS were performed with GEMMA software.
Results: After quality control, 8,626,020 SNPs were used for sequence based GWAS, in which ten significant genomic regions were detected to be associated with FCR. Ten candidate genes, USP44, LTA4H, ELK3, RSPO2, IAP3, SOWAHD, CAMSAP2, ZBTB41, KCNT2 and RAP1A were annotated. Several of them were within or near the reported FCR QTLs, and others were newly reported.
Conclusion: Results from this study provide valuable prior information on chicken genomic breeding program, and potentially improved our understanding of the molecular mechanism for feeding traits.
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