Document Type : Research Paper

Authors

• Zeinab Asgari ¹
• Alireza Ehsani ¹
• Ali Akbar Masoudi ¹
• Rasoul Vaez Torshizi ²

¹ Department of Animal Sciences, Agricultural Faculty, Tarbiat Modares University, Tehran, Iran

² Department of Animal Science, Agricultural Faculty, Tarbiat Modares University, Tehran, Iran

Abstract

Keywords

• Bayesian method
• Body weight
• Candidate gene
• Genome-wide association study
• Single nucleotide polymorphism

Main Subjects

• Animal Breeding and Genetics

Extended Abstract

Introduction

Body weight as one of the most important carcass traits in chickens is of critical importance in meat production. This trait is regulated by different genetic factors (including genetic polymorphism, genetic background, and gene expression). Therefore, genetic studies focused on this trait are of great importance. In this regard, the identification of genome polymorphisms and genes affecting body weight (by genome wide association studies) provide the necessary information to select and improve this trait based on markers.  Different methods have been used to identify the genetic factors affecting polygenic traits. Among them bayes methodology due to the simultaneous use of all SNPs in a regression model is a suitable alternative to overcome excess of false positives and the overestimation of SNPs effects which is created when using common methods such as least squares. For this reason, Bayesian methods based on Gibbs sampling technique have been considered as a new method. Therefore, the present study was conducted with the aim of identifying genes affecting the body weight trait using the BayesCpi method. The population under study was an F2 population of crossbred chickens, which are more beneficial than random populations in reducing errors and improving mapping accuracy.

Background and objectives

The aim of the present study is to identify SNPs associated with body weight in late growth stages in a population of mixed chickens. For this purpose, Bayesian methods based on Gibbs sampling technique are used as a new method and an F2 population of mixed chickens. Because in most breeding studies, the importance of statistical methods is considered, and the F2 population leads to a reduction in errors and improvement of mapping accuracy.

Materials and method

The required phenotypic data were collected from an F2 generation created in the Poultry Breeding Research Center, Faculty of Agriculture, Tarbiat Modares University. To create this population, a cross was made between a commercial broiler line (Arian (AA)) and a native Iranian chicken (NN) (Urmia). The choice of Arian chicken was due to its body weight and meat quality characteristics. Urmia chicken was also chosen due to its greater resistance to diseases and pathogens. After 23 generations of selection, finally 450 F2. All weightings were done after 8 hours of fasting and weekly using a digital scale with a capacity of 50 kg and a measurement accuracy of 1 gram. Genotypic data were also obtained from 312 birds of the F2 generation using Illumina 60k SNP chips. ّFinaly, crossbred regression model and GS3 software were used for data analysis. After identifying the markers using the ncbi website and considering 0.5 Mbp around each SNP, genes close to them were identified.

Result

Using the Bayes factor of 150 as significant thresholds, 10 SNP markers and eaight candidate genes were identifed for body weight at ages 9–12 weeks. These markers and genes were distributed on six chromosomes of which 6 were protein-encoding genes and the rest were noncoding regions (MIR135A2 and LOC112531721). The identified genes included AKR1D1, XPO7, CSMD2, SEPT8, LMO7 and SHISA6, and had different metabolic functions. Results can be used in genomic selection and marker or gene assisted selection to improve growth rate in chicken.

Conclusion

Our results have provided 10 SNP markers for body weight at ages 9, 10, 11 and 12 weeks which provide appropriate information to help identify the genes affecting the body weight trait in the end ages of chickens. The results of the present study, confirming the previous studies, prove the role of macro-chromosomes in controlling growth traits.

Author Contributions

Zeinab Asgari: Conceptualization, methodology, software, validation, formal analysis, investigation, resources, data curation, writing—original draft preparation and writing—review and editing.

Alireza Ehsani2: methodology, software, validation visualization, supervision, project administration, writing—review and editing and funding acquisition.

Ali Akbar Masoudi: supervision and project administration.

Rasoul Vaez Torshizi: supervision and project administration.

All authors contributed equally to the conceptualization of the article and writing of the original and subsequent drafts.

Data Availability Statement

phenotypes: https://figshare.com/articles/Phenotypes_rar/11369358/1

genotypes: https://figshare.com/articles/f2_chicken_data/11369352/2

Acknowledgements

The authors gratefully acknowledge to Dr. Just Jensen from Aarhus University for scientific assistance and supporting genotyping the birds. Thanks to Staff of Arian Line Breeding Center and West Azarbayjan NativeFowls Breeding Center for providing parents of F1 chickens. The main financial support came from Tarbiat Modares University and the genotyping of the birds was supported by Aarhus University, Denmark by GenSAP Grant no 0603-00519B from the Danish Innovation.

Ethical considerations

All experimental procedures have been approved by the Animal Care Committee of Tarbiat Modares University with a letter number 1229734.

Conflict of interest

The author declares no conflict of interest.