A Practical Application of Genomic Predictions for Mastitis Resistance in Italian Holstein Heifers.

Abstract

Simple SummarySelecting the best animals for farms has always been a fundamental aspect of animal breeding. To assist in the traditional selection performed on phenotypes and to further improve genetic selection as performed in recent years, genomic tools could be applied to select animals early in their productive careers. The aim of this study was to evaluate the application of a commercial genomic tool on animals selected from farms grouped by their average somatic cell count. The obtained results showed that farms with good animal management practices also rear animals with better genomic indexes, probably due to selection on other well-established indexes (e.g., productive traits). Selecting heifers based on their wellness genomic indexes would further improve both their economic value and their disease resistance and resilience.Heifers are a fundamental resource on farms, and their importance is reflected in both farm management and economy. Therefore, the selection of heifers to be reared on a farm should be carefully performed to select only the best animals. Genomic selection is available nowadays to evaluate animals in a fast and economic way. However, it is mainly used on the sire line and on performance traits. Ten farms were selected based on their 5-year records of average somatic cell count and evenly classified into high (>300,000 cells/mL) and low somatic cell count (<150,000 cells/mL). Genomic indexes (regarding both wellness and productive traits) were evaluated in 157 Italian Holstein heifers reared in the selected ten farms (90 from high-cells farms and 67 from low-cells ones). Linear mixed models were fitted to analyze the effects of the abovementioned genomic indexes on related phenotypes. Results have shown that farms classified into low somatic cell count had an overall better animal genomic pool compared to high somatic cell count ones. Additionally, the results shown in this study highlighted a difference in wellness genomic indexes in animals from farms with either a high or a low average somatic cell count. Applying genomic tools directly to heifer selection could improve economic aspects related to herd turnover.