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Genetic determinism of egg production and egg quality traits

Over the last decades, layer chicken lines have been selected and improved for egg production and egg quality performance. However, the genomic regions, i.e. the quantitative trait loci (QTL), which influence these traits, are still poorly known (Romé and Le Roy, 2016). On the other hand, even if environmental effects explain a part of the phenotypic variance in laying traits in chickens, to date, no study has tested the robustness of QTL across environments.

A high-density array to improve QTL detection

The high-density array for chicken recently developed by Affymetrix, i.e. the 600K Affymetrix® Axiom® HD genotyping array (Kranis et al., 2013), contributed to improve the location of previously detected QTL and to detect new QTL. Therefore, in this study, a genome-wide association study (GWAS) was conducted to detect QTL that influence egg production and egg quality traits in layer chickens using that high density array. In order to investigate whether the QTL detected differed between environmental conditions, animals were divided into two groups that were fed a different diet.

Different metabolic pathways to adapt to their environment

This study detected 131 QTL for egg production and egg quality traits. These QTL were distributed across 27 chromosomes, two linkage groups and a group of unassigned SNPs. Among the 131 QTL detected, 48 showed a significant interaction with diet although the average phenotypic performance varied only slightly with diet. This shows that laying hens have an in-built ability to adapt to their environment that probably involves different genetic pathways.

Impact to be clarified on genomic selection

These genome by environment interactions could have an effect on genetic selection, since the best candidates may differ depending on the environmental conditions in which the hens are reared. This study pinpoints also the existence of “unrobust” QTL, which raises the question which QTL are expressed in the commercial hybrids.

Bibliography

• Kranis A., Gheyas A.A., Boschiero C., Turner F., Yu L., Smith S., Talbot R., Pirani A., Brew F., Kaiser P., Hocking P.M., Fife M., Salmon N., Fulton J., Strom T.M., Haberer G., Weigand S., Preisinger R., Gholami M., Qanbari S., Simianer H., Watson K.A., Woolliams J.A., Burt D.W. (2013). Development of a high density 600K SNP genotyping array for chicken. BMC Genomics 14: 59. [DOI]
• Romé H., Varenne A., Hérault F., Chapuis H., Alleno C., Dehais P., Vignal A., Burlot T., Le Roy P. (2015). GWAS analyses reveal QTL in egg layers that differ in response to diet differences. Genetics Selection Evolution 47: 83. [DOI]
• Romé H, Le Roy P. (2016). Régions chromosomiques influençant les caractères de production et de qualité des œufs de poule. Inra Productions Animales 29(2): 117-128. [Lien]