Combined Use of Univariate and Multivariate Approaches to Detect Selection Signatures Associated with Milk or Meat Production in Cattle
2024

Genomic Study of Cattle Breeds for Milk and Meat Production

Sample size: 391 publication 10 minutes Evidence: high

Author Information

Author(s): Congiu Michele, Cesarani Alberto, Falchi Laura, Macciotta Nicolò Pietro Paolo, Dimauro Corrado

Primary Institution: Dipartimento di Agraria, Università degli Studi di Sassari, Italy

Hypothesis

The study aims to investigate the genomic structure of cattle breeds selected for meat and milk production and identify selection signatures between them.

Conclusion

The combined use of univariate and multivariate approaches can help to better identify selection signatures due to directional selection.

Supporting Evidence

  • 10 SNPs located on seven different chromosomes were identified.
  • 165 QTL and 51 genes were found close to the identified SNPs.
  • Three significant QTL terms were identified: milk fat content, tenderness score, and length of productive life.

Takeaway

Scientists looked at the DNA of different cattle breeds to see how they were changed by breeding for milk or meat. They found specific genetic markers that help tell the two groups apart.

Methodology

The study used both univariate (FST) and multivariate (CDA) approaches to analyze genomic data from 391 cattle genotyped at 41,258 SNPs.

Limitations

The study relied on preexisting datasets and did not involve new animal care and use committee approval.

Participant Demographics

The study included nine cattle breeds: Angus, Charolais, Hereford, Limousin, Piedmontese, Brown Swiss, Holstein, Jersey, and Montbéliarde.

Statistical Information

P-Value

p<0.001

Statistical Significance

p<0.001

Digital Object Identifier (DOI)

10.3390/genes15121516

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