Publications by authors named "H Ben Zaabza"
Genomic selection and extensive use of a few elite bulls through artificial insemination are leading to reduced genetic diversity in Jersey cattle. Conservation of genetic diversity through gene banks can protect a breed's genetic diversity and genetic gain, ensuring continued genetic advancement in the future. The availability of genomic information in the US National Animal Germplasm Program (NAGP) facilitates characterization of Jersey bulls in the germplasm collection.
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- The productive life of a cow is the time it spends in the milking herd, and researchers studied how genetics affects it using data from a lot of cows.
- They analyzed over a million Holstein cows with genetic information to find out what genes are linked to how long they can produce milk.
- The study found many important gene areas that influence not only milk production but also fertility and health, helping to identify which cows should be kept or removed from the herd.
A genome-wide association study of resistance to retained placenta (RETP) using 632,212 Holstein cows and 74,747 SNPs identified 200 additive effects with -values < 10 on thirteen chromosomes but no dominance effect was statistically significant. The regions of 87.61-88.
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- A genome-wide association study (GWAS) analyzed fat percentage in over 1.2 million first lactation cows and confirmed significant inter-chromosome effects in a specific region on Chromosome 14.
- The study identified two sub-regions within this area, Chr14a and Chr14b, with Chr14a showing the majority of additive × additive interactions.
- Notably, the research highlights interactions between specific SNPs (genetic markers) linked to traits like milk production and fertility, enhancing the understanding of genetic influences on fat percentage in Holstein cows.
The calculation of exact reliabilities involving the inversion of mixed model equations poses a heavy computational challenge when the system of equations is large. This has prompted the development of different approximation methods. We give an overview of the various methods and computational approaches in calculating reliability from the era before the animal model to the era of single-step genomic models.
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