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Enhancing genomic selection for reproductive traits in turkeys through SNP prioritization using the fixation index
Evan Hartono1, Owen W Willems2, Xuechun Bai2
1Department of Poultry Science, University of Georgia, Athens, GA 30602, USA.
Poultry Science
|December 23, 2025
Summary
Genomic selection accuracy for turkey reproductive traits improved by prioritizing informative SNPs using FST and applying Box-Cox transformation. This enhances breeding value prediction for lowly heritable traits.
Area of Science:
- Animal Breeding and Genetics
- Quantitative Genetics
- Poultry Science
Background:
- Genomic selection (GS) improves breeding value accuracy but shows modest gains for lowly heritable traits like turkey reproduction.
- Reproductive traits in turkeys often exhibit non-normal phenotypic distributions, complicating accurate genetic evaluation.
Purpose of the Study:
- To enhance the accuracy of genomic selection for turkey reproductive traits.
- To improve the genomic relationship matrix quality and normalize phenotypic distributions.
Main Methods:
- Utilized the fixation index (FST) to select informative single nucleotide polymorphisms (SNPs) differentiating extreme phenotypic groups.
- Applied Box-Cox transformation to normalize phenotypic distributions of reproductive traits.
- Analyzed egg production percent (PEP), fertility (FERT), and hatchability (HOF) using BLUP, GBLUP, and ssGBLUP models.
Main Results:
- FST-prioritized SNPs significantly improved heritability estimates, especially for fertility (FERT).
- Prioritizing top 10% FST markers increased FERT heritability by 93% in GBLUP (0.15 to 0.29).
- Box-Cox transformation consistently increased heritability across all methods, with combined FST90 and transformation yielding highest estimates.
Conclusions:
- FST-based SNP prioritization and Box-Cox transformation effectively enhance genomic selection accuracy for turkey reproductive traits.
- These methods improve the identification of superior turkeys, crucial for genetic improvement programs.
- The study demonstrates a powerful strategy for optimizing GS in poultry for challenging traits.

