Identification of potential genomic regions for egg weight by a haplotype-based genome-wide association study using Bayesian methods

ABSTRACT

1. Theoretically, haplotype blocks might be a more suitable alternative to SNP genotypes as they are usually better at capturing multi-allelic QTL effects, compared to individual SNP genotypes in genome-wide association studies. The objectives of this study were to identify genomic regions related to egg weight traits by Bayesian methods (BayesA, BayesB, and BayesN) that fit fixed-length haplotypes using GenSel software.

2. Genotypes at 294,705 SNPs, that were common on a 600K Affymetrix chip, were phased for an egg-laying hen population of 1,063 birds. Recorded traits included first egg weight (FEW) and average egg weight at 28, 36, 56, 66, 72 and 80 weeks of age.

2. Fitting 1Mb haplotypes from BayesB resulted in the highest proportion of genetic variance explained for the egg weight traits. Based on the trait, the genetic variance explained by each marker ranged from 27% to 76%.

3. Different haplotype windows associated with egg weight traits only explained a small percentage of the genetic variance.

4. The top one 1-Mb window on GGA1 explained approximately 4.05% of total genetic variance for the FEW. Candidate genes, including PRKAR2B, HMGA2, LEMD3, GRIP1, EHBP1, MAP3K7, and MYH were identified for egg weight traits.

5. Several genomic regions, potentially associated with egg weight traits, were identified, some of which overlapped with known genes and previously reported QTL regions for egg production traits.

KEYWORDS:

• Egg production
• genome wide association study
• SNP
• Bayesian approach
• laying hens

Disclosure Statement

No potential conflict of interest was reported by the authors.

Data Availability

The data described in this article are openly available in the Open Science Framework at DOI:10.17605/OSF.IO/TPA6U.