Accuracy of breeding values for production traits in turkeys (Meleagris gallopavo) using recursive models with or without genomics.

Abdalla, Emhimad A.; Wood, Benjamin J.; Baes, Christine F. (2021). Accuracy of breeding values for production traits in turkeys (Meleagris gallopavo) using recursive models with or without genomics. Genetics, selection, evolution, 53(1), p. 16. BioMed Central 10.1186/s12711-021-00611-8

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BACKGROUND

Knowledge about potential functional relationships among traits of interest offers a unique opportunity to understand causal mechanisms and to optimize breeding goals, management practices, and prediction accuracy. In this study, we inferred the phenotypic causal networks among five traits in a turkey population and assessed the effect of the use of such causal structures on the accuracy of predictions of breeding values.

METHODS

Phenotypic data on feed conversion ratio, residual feed intake, body weight, breast meat yield, and walking score in addition to genotype data from a commercial breeding population were used. Causal links between the traits were detected using the inductive causation algorithm based on the joint distribution of genetic effects obtained from a standard Bayesian multiple trait model. Then, a structural equation model was implemented to infer the magnitude of causal structure coefficients among the phenotypes. Accuracies of predictions of breeding values derived using pedigree- and blending-based multiple trait models were compared to those obtained with the pedigree- and blending-based structural equation models.

RESULTS

In contrast to the two unconditioned traits (i.e., feed conversion ratio and breast meat yield) in the causal structures, the three conditioned traits (i.e., residual feed intake, body weight, and walking score) showed noticeable changes in estimates of genetic and residual variances between the structural equation model and the multiple trait model. The analysis revealed interesting functional associations and indirect genetic effects. For example, the structural coefficient for the path from body weight to walking score indicated that a 1-unit genetic improvement in body weight is expected to result in a 0.27-unit decline in walking score. Both structural equation models outperformed their counterpart multiple trait models for the conditioned traits. Applying the causal structures led to an increase in accuracy of estimated breeding values of approximately 7, 6, and 20% for residual feed intake, body weight, and walking score, respectively, and different rankings of selection candidates for the conditioned traits.

CONCLUSIONS

Our results suggest that structural equation models can improve genetic selection decisions and increase the prediction accuracy of breeding values of selection candidates. The identified causal relationships between the studied traits should be carefully considered in future turkey breeding programs.

Item Type:

Journal Article (Original Article)

Division/Institute:

05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH) > Institute of Genetics
05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH)

UniBE Contributor:

Baes, Christine Francoise

Subjects:

500 Science > 590 Animals (Zoology)
600 Technology > 630 Agriculture

ISSN:

1297-9686

Publisher:

BioMed Central

Language:

English

Submitter:

Christine Francoise Baes

Date Deposited:

13 Sep 2021 10:17

Last Modified:

19 Sep 2021 03:09

Publisher DOI:

10.1186/s12711-021-00611-8

PubMed ID:

33593272

BORIS DOI:

10.48350/159189

URI:

https://boris.unibe.ch/id/eprint/159189

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