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. 2025 May 15;16(5):583.
doi: 10.3390/genes16050583.

Genome-Wide Association Studies and Candidate Genes for Egg Production Traits in Layers from an F2 Crossbred Population Produced Using Two Divergently Selected Chicken Breeds, Russian White and Cornish White

Natalia A Volkova  1 , Michael N Romanov  1   2   3 , Alan Yu Dzhagaev  1 , Polina V Larionova  1 , Ludmila A Volkova  1 , Alexandra S Abdelmanova  1 , Anastasia N Vetokh  1 , Darren K Griffin  2   3   4 , Natalia A Zinovieva  1
Affiliations

Genome-Wide Association Studies and Candidate Genes for Egg Production Traits in Layers from an F2 Crossbred Population Produced Using Two Divergently Selected Chicken Breeds, Russian White and Cornish White

Natalia A Volkova et al. Genes (Basel). .

Abstract

Background/Objectives: Finding single nucleotide polymorphisms (SNPs) and candidate genes that influence the expression of key traits is essential for genomic selection and helps improve the efficiency of poultry production. Here, we aimed to conduct a genome-wide association study (GWAS) for egg production traits in an F2 resource population of chickens (Gallus gallus). Methods: The examined F2 population was produced by crossing two divergently selected breeds with contrasting phenotypes for egg performance traits, namely Russian White (of higher egg production) and Cornish White (of lower egg production). Sampled birds (n = 142) were genotyped using the Illumina Chicken 60K SNP iSelect BeadChip. Results: In the course of the GWAS analysis, we were able to clarify significant associations with phenotypic traits of interest and economic value by using 47,432 SNPs after the genotype dataset was filtered. At the threshold p < 1.06 × 10-6, we found 23 prioritized candidate genes (PCGs) associated with egg weight at the age of 42-52 weeks (FGF14, GCK), duration of egg laying (CNTN4), egg laying cycle (SAMD12) and egg laying interval (PHF5A, AKR1B1, CALD1, ATP7B, PIK3R4, PTK2, PRKCE, FAT1, PCM1, CC2D2A, BMS1, SEMA6D, CDH13, SLIT3, ATP10B, ISCU, LRRC75A, LETM2, ANKRD24). Moreover, two SNPs were co-localized within the FGF14 gene. Conclusions: Based on our GWAS findings, the revealed SNPs and candidate genes can be used as genetic markers for egg weight and other performance characteristics in chickens to attain genetic enhancement in production and for further genomic selection.

Keywords: candidate genes; chicken (Gallus gallus); egg performance; genome-wide association study (GWAS); single nucleotide polymorphisms (SNPs).

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Conflict of interest statement

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Initial parent breeds and F1 hybrids used to obtain the F2 model resource chicken population.
Figure 2
Figure 2
Principal component analysis (PCA) for the F2 resource chicken population. (a) PCA performed in the projection of the first (PC1) and second (PC2) components. X-axis, PC1; Y-axis, PC2. (b) PCA performed in the projection of the PC1 and third (PC3) components. X-axis, PC1; Y-axis, PC3. Different colors are used to represent members of certain groups.
Figure 2
Figure 2
Principal component analysis (PCA) for the F2 resource chicken population. (a) PCA performed in the projection of the first (PC1) and second (PC2) components. X-axis, PC1; Y-axis, PC2. (b) PCA performed in the projection of the PC1 and third (PC3) components. X-axis, PC1; Y-axis, PC3. Different colors are used to represent members of certain groups.
Figure 3
Figure 3
Manhattan plots resulting from GWAS for the studied egg production traits in the F2 resource chicken population. (a) Duration of egg laying from age at first egg to 52 weeks of age; (b) egg laying cycle; (c) egg laying interval; (d) mean egg weight at 18–28 weeks of age; and (e) mean egg weight at 42–52 weeks of age. Manhattan plots: distribution of single nucleotide changes across 28 chicken chromosomes (autosomes) at the significance level (−log10(p)) based on the traits’ predicted probability values. The only purpose of color-coding dots is to show chromosomal segregation.
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