Using Gene Data to Pinpoint Fertility Traits in Dairy Cows

Jenn Hoskins
7th June, 2024

Using Gene Data to Pinpoint Fertility Traits in Dairy Cows

Image Source: Frank Van Esch (photographer)

Key Findings

  • The study focused on dairy cattle fertility in Australia and New Zealand
  • Researchers identified genetic variants linked to fertility by combining various types of expression data
  • These findings can improve the accuracy of genomic predictions and enhance breeding programs for better reproductive performance
Female fertility is a crucial trait in dairy cattle, impacting the efficiency and profitability of dairy production. Identifying genetic variants associated with fertility can enhance the accuracy of genomic predictions, ultimately improving reproductive performance. A recent study by Agriculture Victoria aimed to fine-map quantitative trait loci (QTL) associated with fertility by integrating multiple types of expression data and allele frequency information in high- and low-fertility cows from New Zealand and Australia[1]. Reproductive performance in dairy cattle has historically faced challenges due to the low heritability of fertility traits. Previous studies have shown that female reproductive traits in dairy cattle tend to be lowly heritable, with estimates ranging from 0.02 to 0.04[2]. Despite this, genetic selection can still alter phenotypic performance, as evidenced by the decline in dairy cow reproductive performance due to aggressive selection for increased milk production[2]. The establishment of pregnancy, which involves a series of heritable events, is a key indicator of fertility in dairy systems[3]. Genetic selection for fertility has traditionally focused on reducing the number of days from calving to pregnancy, known as "days open"[3]. Recent advancements in genomic technologies have shown promise in improving fertility traits. Genomic selection has stabilized and even reversed the declining trend in dairy cattle fertility, demonstrating its effectiveness[4]. However, genome-wide association studies (GWAS) on dairy fertility traits have often been underpowered due to the polygenic nature of these traits, with only one major QTL identified across multiple studies[4]. The study by Agriculture Victoria sought to address these challenges by combining multiple types of expression data, including expression quantitative trait loci (eQTL), exon-level expression, gene splicing, and allele-specific expression, to fine-map QTL associated with fertility. This approach aimed to get closer to identifying causal mutations. Additionally, the study leveraged a selection experiment in New Zealand that created a resource of cows selected for high (POS) and low (NEG) fertility, providing valuable allele frequency data. By integrating expression data and allele frequency information with a GWAS on calving interval in Australian cows, the study aimed to identify genomic differences between high- and low-fertility cows. This comprehensive approach allowed for a more precise identification of QTL associated with fertility in both Australian and New Zealand dairy cattle populations. The findings of this study have significant implications for the dairy industry. By identifying putative causal variants associated with fertility, the accuracy of genomic predictions for fertility traits can be improved. This, in turn, can enhance the effectiveness of breeding programs aimed at improving reproductive performance. The study also highlights the importance of combining multiple types of data to achieve more accurate and reliable genetic insights. In summary, the study by Agriculture Victoria represents a significant advancement in the field of dairy cattle genetics. By integrating multiple types of expression data with allele frequency information and GWAS, the study provides a more detailed understanding of the genetic architecture of fertility traits. This approach not only enhances the accuracy of genomic predictions but also offers valuable insights for future breeding programs aimed at improving reproductive performance in dairy cattle.

AgricultureGeneticsAnimal Science

References

Main Study

1) Using expression data to fine map QTL associated with fertility in dairy cattle

Published 6th June, 2024

https://doi.org/10.1186/s12711-024-00912-8

Related Studies

2) Genetics and genomics of reproductive performance in dairy and beef cattle.

https://doi.org/10.1017/S1751731114000743

3) Symposium review: Selection for fertility in the modern dairy cow-Current status and future direction for genetic selection.

https://doi.org/10.3168/jds.2018-15544

4) Symposium review: Genetics, genome-wide association study, and genetic improvement of dairy fertility traits.

https://doi.org/10.3168/jds.2018-15269


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