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Genetic architecture of bone quality variation in layer chickens revealed by a genome-wide association study

View Article: PubMed Central - PubMed

ABSTRACT

Skeletal problems in layer chickens are gaining attention due to animal welfare and economic losses in the egg industry. The genetic improvement of bone traits has been proposed as a potential solution to these issues; however, genetic architecture is not well understood. We conducted a genome-wide association study (GWAS) on bone quality using a sample of 1534 hens genotyped with a 600 K Chicken Genotyping Array. Using a linear mixed model approach, a novel locus close to GSG1L, associated with femur bone mineral density (BMD), was uncovered in this study. In addition, nine SNPs in genes were associated with bone quality. Three of these genes, RANKL, ADAMTS and SOST, were known to be associated with osteoporosis in humans, which makes them good candidate genes for osteoporosis in chickens. Genomic partitioning analysis supports the fact that common variants contribute to the variations of bone quality. We have identified several strong candidate genes and genomic regions associated with bone traits measured in end-of-lay cage layers, which accounted for 1.3–7.7% of the phenotypic variance. These SNPs could provide the relevant information to help elucidate which genes affect bone quality in chicken.

No MeSH data available.


Manhattan and quantile-quantile (QQ) plot on tibia traits.The single-trait analyses on femur breaking strength (A) and breaking work (B); the horizontal black and green lines indicate the whole-genome significance (P = 8.43 × 10−7) and suggestive thresholds (P = 1.69 × 10−5), respectively.
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f2: Manhattan and quantile-quantile (QQ) plot on tibia traits.The single-trait analyses on femur breaking strength (A) and breaking work (B); the horizontal black and green lines indicate the whole-genome significance (P = 8.43 × 10−7) and suggestive thresholds (P = 1.69 × 10−5), respectively.

Mentions: The quantile–quantile (QQ) plot revealed that SNPs deviated from the distribution under the hypothesis, which indicated a strong association between SNPs and BMD (Fig. 1A). Significant genome-wide associations (P = 8.43 × 10−7) were examined for four SNPs, of which three were mapped on chromosome 14. The most significant was rs313699988 (P = 4.18 × 10−7), which was located at 11.88 Mb. The two significant SNPs on GGA14 were rs314036389 (P = 4.36 × 10−7) at 11.87 Mb, and rs313517665 (P = 6.86 × 10−7) at 11.57 Mb. Support for the significant association was apparent in a Manhattan plot illustrating that the univariate analysis generated several p-values that exceeded the Bonferroni cutoff (Fig. 1A1). Apart from the region on GGA14 associated with BMD, 13 SNPs were detected for this trait, which were located at the region close to 169 Mb on GGA 1 and 11 Mb on GGA7. The GWAS identified three regions that were significantly associated with femur BMC, and the QQ plot for BMC supported the results shown in the Manhattan plot (Fig. 1B). Three regions were located on GGA 1, 4 and 27. For femur weight, a peak of genome-wide significant SNP effects was found on GGA 1 (P = 4.75 × 10–21). Almost all significant associated loci located in this region spanning from 164.80 Mb to 173.85 Mb on GGA 1. Out of this region, 28 SNPs on GGA 4 built up an associated block ranged from 73.48 Mb to 76.94 Mb, and a region located between 3.03 Mb and 3.63 Mb on GGA 27 showed significant at the genome-wide level. The distribution of significant SNPs related to tibia traits was shown in Fig. 2.


Genetic architecture of bone quality variation in layer chickens revealed by a genome-wide association study
Manhattan and quantile-quantile (QQ) plot on tibia traits.The single-trait analyses on femur breaking strength (A) and breaking work (B); the horizontal black and green lines indicate the whole-genome significance (P = 8.43 × 10−7) and suggestive thresholds (P = 1.69 × 10−5), respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5382839&req=5

f2: Manhattan and quantile-quantile (QQ) plot on tibia traits.The single-trait analyses on femur breaking strength (A) and breaking work (B); the horizontal black and green lines indicate the whole-genome significance (P = 8.43 × 10−7) and suggestive thresholds (P = 1.69 × 10−5), respectively.
Mentions: The quantile–quantile (QQ) plot revealed that SNPs deviated from the distribution under the hypothesis, which indicated a strong association between SNPs and BMD (Fig. 1A). Significant genome-wide associations (P = 8.43 × 10−7) were examined for four SNPs, of which three were mapped on chromosome 14. The most significant was rs313699988 (P = 4.18 × 10−7), which was located at 11.88 Mb. The two significant SNPs on GGA14 were rs314036389 (P = 4.36 × 10−7) at 11.87 Mb, and rs313517665 (P = 6.86 × 10−7) at 11.57 Mb. Support for the significant association was apparent in a Manhattan plot illustrating that the univariate analysis generated several p-values that exceeded the Bonferroni cutoff (Fig. 1A1). Apart from the region on GGA14 associated with BMD, 13 SNPs were detected for this trait, which were located at the region close to 169 Mb on GGA 1 and 11 Mb on GGA7. The GWAS identified three regions that were significantly associated with femur BMC, and the QQ plot for BMC supported the results shown in the Manhattan plot (Fig. 1B). Three regions were located on GGA 1, 4 and 27. For femur weight, a peak of genome-wide significant SNP effects was found on GGA 1 (P = 4.75 × 10–21). Almost all significant associated loci located in this region spanning from 164.80 Mb to 173.85 Mb on GGA 1. Out of this region, 28 SNPs on GGA 4 built up an associated block ranged from 73.48 Mb to 76.94 Mb, and a region located between 3.03 Mb and 3.63 Mb on GGA 27 showed significant at the genome-wide level. The distribution of significant SNPs related to tibia traits was shown in Fig. 2.

View Article: PubMed Central - PubMed

ABSTRACT

Skeletal problems in layer chickens are gaining attention due to animal welfare and economic losses in the egg industry. The genetic improvement of bone traits has been proposed as a potential solution to these issues; however, genetic architecture is not well understood. We conducted a genome-wide association study (GWAS) on bone quality using a sample of 1534 hens genotyped with a 600 K Chicken Genotyping Array. Using a linear mixed model approach, a novel locus close to GSG1L, associated with femur bone mineral density (BMD), was uncovered in this study. In addition, nine SNPs in genes were associated with bone quality. Three of these genes, RANKL, ADAMTS and SOST, were known to be associated with osteoporosis in humans, which makes them good candidate genes for osteoporosis in chickens. Genomic partitioning analysis supports the fact that common variants contribute to the variations of bone quality. We have identified several strong candidate genes and genomic regions associated with bone traits measured in end-of-lay cage layers, which accounted for 1.3–7.7% of the phenotypic variance. These SNPs could provide the relevant information to help elucidate which genes affect bone quality in chicken.

No MeSH data available.