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Genomewide association for a dominant pigmentation gene in sheep
J W Kijas1, M Serrano, R McCulloch
1CSIRO Animal, Food and Health Sciences, Brisbane, QLD, Australia.
Summary
Genomewide association studies (GWAS) can identify dominant traits in sheep, even with small sample sizes. Combining GWAS with random forest analysis improves accuracy by correcting for population structure and identifying false positives.
Area of Science:
- Animal Genetics
- Genomics
- Quantitative Genetics
Background:
- Most sheep genomewide association studies (GWAS) focus on recessive traits.
- The genetic basis of dominant traits is less explored using GWAS.
- Coat pigmentation in sheep is a known trait with a genetic basis.
Purpose of the Study:
- To evaluate the feasibility of performing GWAS for a dominant trait in sheep.
- To assess the effectiveness of combined analytical approaches for GWAS in sheep.
- To investigate population substructure and its impact on GWAS results.
Main Methods:
- Genotyping of 42 sheep (Manchega and Rasa Aragonesa) with coat pigmentation using the SNP50 BeadChip.
- Population substructure analysis using multiple methods.
- Allelic association testing for 49,034 SNPs, followed by correction for substructure.
- Permutation tree-based random forest (RF) analysis for validation and false positive identification.
Main Results:
- GWAS identified a significant association between SNP s26449 and coat pigmentation, located near the MC1R gene.
- RF analysis supported the primary GWAS findings and identified potential false positives.
- A combined analytical approach proved beneficial in managing population stratification and identifying true associations.
Conclusions:
- GWAS is feasible for dominant traits in sheep, particularly when the genetic basis is known.
- Combined GWAS and RF analysis enhance the reliability of results, especially with limited sample sizes and population stratification.
- This study demonstrates a successful strategy for genetic studies in sheep populations with complex structures.
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