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Vertebrate reproductive science and technology
RESEARCH ARTICLE

163 Genome-wide association study to identify candidate genomic regions for cow fertility in Retinta cattle breed

N. Laseca A , R. Morales A , A. Molina A , G. Anaya A , C. Medina A and S. Demyda-Peyrás B C
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A Department of Genetics, University of Cordoba, Córdoba, Spain

B Department of Animal Production, Veterinary School, University of La Plata, La Plata, Argentina

C National Research Council (CONICET), La Plata, Argentina

Reproduction, Fertility and Development 35(2) 209-209 https://doi.org/10.1071/RDv35n2Ab163
Published: 5 December 2022

© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of the IETS

In cows, fertility traits are difficult to estimate phenotypically from a populational point of view, despite its influence on the profitability of herds. However, indirect traits such as reproductive efficiency (RE), determined as the deviation in percentage of the number of calvings that an animal has at each age from the number of calving that it could have had in optimal conditions, are showing promising results to obtain large-scale phenotypic datasets. Additionally, detection of genomic regions associated with fertility could help to select fertile cows more accurately and to identify candidate genes for marker-assisted or gene-based genomic selection. In this study, we performed a genome-wide association study (GWAS) for RE in a population of 252 Retinta cows genotyped using the Axiom Bovine Genotyping v3 Array (Applied Biosystems). Raw data was first filtered, excluding SNP markers with call-rate ≤ 0.95 and with a minor allele frequency < 0.01. The final genomic dataset included 29,037 SNPs from the autosomal and X chromosomes. The GWAS was performed using GEMMA software (National Institutes of Health, the Wellcome Trust) with a linear mixed model association test, taking into account the relatedness genomic matrix and 10 principal components from a PCA analysis as covariates for correcting populational structure. Results showed five SNPs significantly associated with reproductive efficiency located in two genomic regions on BTA4 and BTA28. The in silico functional analysis revealed the presence of five candidate genes (NRF1, ZC3HC1, SSMEM1, RYR2, and ZP4) located within these regions, which were previously involved in different aspects related to fertility in cattle and mice models. Overall, we demonstrated the existence of specific genomic regions possibly influencing the fertility of Retinta breed cows. This new information could help facilitate a better understanding of the genetic architecture of reproductive traits in the species as well as allow for a more accurate selection of fertile cows. However, further analysis, including large populations and different breeds, are necessary to validate our findings.

The authors thank the CEAG (Experimental Agriculture and Livestock Centre of Jerez de la Frontera, Rural Council of Cadiz) and the National Retinta Breeders Association for their collaboration in this study and for providing the biological samples and genealogical data used in this study.