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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.


Regional association plot of the primary signal (rs13975174) associated with femur weight at GGA1.For each plot, the −log10 (observed P-values) of SNPs (y-axis) are presented according to their chromosomal positions (x-axis). The blue line indicates the genome-wide significance level (8.43 × 10−7), and the red line the predicted level. The primary SNP are denoted by large blue circles. SNPs are represented by colored circles according to the target SNP with which they were in strongest LD (r2 > 0.4). The upper part of the figure shows the association results for BMC before conditional analysis on rs13975174. In the lower part of the figure, the P-value of corresponding SNPs fell below the predicted threshold.
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f3: Regional association plot of the primary signal (rs13975174) associated with femur weight at GGA1.For each plot, the −log10 (observed P-values) of SNPs (y-axis) are presented according to their chromosomal positions (x-axis). The blue line indicates the genome-wide significance level (8.43 × 10−7), and the red line the predicted level. The primary SNP are denoted by large blue circles. SNPs are represented by colored circles according to the target SNP with which they were in strongest LD (r2 > 0.4). The upper part of the figure shows the association results for BMC before conditional analysis on rs13975174. In the lower part of the figure, the P-value of corresponding SNPs fell below the predicted threshold.

Mentions: Stepwise conditional analysis was conducted to examine whether there are cryptic, independently associated SNPs that might act as potential causal variants. We performed conditional single-marker association analyses on rs315077363 to uncover the signals potentially masked by the strong signals in GGA1. The P-values of previous significant SNPs for BMC on GGA1 were lower than the suggestive level, whereas an SNP at 169.4 Mb on GGA1 was identified as the significant marker, which were located in the intron of the INTS6 gene. For femur weight, a SNP located in the intron of POSTN gene on GGA1 was also identified as a significantly associated marker. Moreover, no significant association was found on GGA1 after conditional analysis of two additional variants. In our conditional analyses, only SNPs on GGA1 were selected, and no additional signals were detected except for this region. The results on region-specific and conditional analysis for the BMC are presented in Fig. 3 and Figure S1.


Genetic architecture of bone quality variation in layer chickens revealed by a genome-wide association study
Regional association plot of the primary signal (rs13975174) associated with femur weight at GGA1.For each plot, the −log10 (observed P-values) of SNPs (y-axis) are presented according to their chromosomal positions (x-axis). The blue line indicates the genome-wide significance level (8.43 × 10−7), and the red line the predicted level. The primary SNP are denoted by large blue circles. SNPs are represented by colored circles according to the target SNP with which they were in strongest LD (r2 > 0.4). The upper part of the figure shows the association results for BMC before conditional analysis on rs13975174. In the lower part of the figure, the P-value of corresponding SNPs fell below the predicted threshold.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f3: Regional association plot of the primary signal (rs13975174) associated with femur weight at GGA1.For each plot, the −log10 (observed P-values) of SNPs (y-axis) are presented according to their chromosomal positions (x-axis). The blue line indicates the genome-wide significance level (8.43 × 10−7), and the red line the predicted level. The primary SNP are denoted by large blue circles. SNPs are represented by colored circles according to the target SNP with which they were in strongest LD (r2 > 0.4). The upper part of the figure shows the association results for BMC before conditional analysis on rs13975174. In the lower part of the figure, the P-value of corresponding SNPs fell below the predicted threshold.
Mentions: Stepwise conditional analysis was conducted to examine whether there are cryptic, independently associated SNPs that might act as potential causal variants. We performed conditional single-marker association analyses on rs315077363 to uncover the signals potentially masked by the strong signals in GGA1. The P-values of previous significant SNPs for BMC on GGA1 were lower than the suggestive level, whereas an SNP at 169.4 Mb on GGA1 was identified as the significant marker, which were located in the intron of the INTS6 gene. For femur weight, a SNP located in the intron of POSTN gene on GGA1 was also identified as a significantly associated marker. Moreover, no significant association was found on GGA1 after conditional analysis of two additional variants. In our conditional analyses, only SNPs on GGA1 were selected, and no additional signals were detected except for this region. The results on region-specific and conditional analysis for the BMC are presented in Fig. 3 and Figure S1.

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.