Estimation of genetic parameters and breeding values for feed intake and energy balance using pedigree relationships or single-step genomic evaluation in Holstein Friesian cows

Abstract

At the beginning of lactation, high-performing dairy cows often experience a severe energy deficit, which in turn is associated with metabolic stress. Increasing feed intake (FI) or reducing the energy deficit during this period could improve the metabolic stability and thus the health of the animals. Genomic selection for the first time enables the inclusion of this hard-to-measure trait in breeding programs. The objective of the current study was the estimation of genetic parameters and genomic breeding values for FI and energy balance (EB). For this purpose, 1,374 Holstein Friesian (HF) dairy cows from 8 German research farms were phenotyped with standardized FI data protocols. After data editing, phenotypic data of HF comprised a total of 40,012 average weekly FI records with a mean of 21.8 ± 4.3 kg/d. For EB 33,376 average weekly records were available with a mean of 3.20 ± 29.4 MJ of NE L /d. With the Illumina Bovine SNP50 BeadChip (Illumina Inc., San Diego, CA) 1,128 of phenotyped cows were genotyped. Thirty-five female candidates of the HF population were genotyped but not phenotyped. Pedigree information contained sires and dams 4 generations back. The random regression animal model included the fixed effects of herd test week (alternatively, herd group test week), parity, and stage of lactation, modeled by the function according to Ali and Schaeffer (1987). For both the random permanent environmental effect across lactations and the random additive genetic effect, third-order Legendre polynomials were chosen. Additionally, a random permanent environmental cow effect within lactation was included. Analyses for heritabilities, genetic correlations between different lactation stages, and breeding values were estimated using, respectively, pedigree relationships and single-step genomic evaluation, carried out with the DMU software package (Madsen et al., 2013). This allowed for comparison of conventional reliabilities with genomic-assisted reliabilities based on real data, to evaluate the gain of genotyping. Heritability estimates ranged between 0.12 and 0.50 for FI, and 0.15 and 0.48 for EB, and increased toward the end of lactation. Genetic correlations were weak between early and late lactation, with a value of 0.05 for FI and negative with a value of −0.05 for EB. Reliabilities for genomic values of cows for FI and EB ranged between 0.33 and 0.61, and 0.27 and 0.47, respectively. For the genotyped cows without phenotypes, the inclusion of genomic relationship leads to an increase of the average reliability of the breeding value for FI by nearly 9% and for EB by 4%. The results show the possibility of combining pedigree, genotypes, and phenotypes for increasing FI or EB to reduce health and reproductive problems, especially at the beginning of lactation. Nevertheless, the reference population needs to be extended to reach higher breeding value reliabilities.

Genetic analysis of resilience indicators based on milk yield records in different lactations and at different lactation stages

“…These correlations suggest that the resilience indicators are partly determined by different genes in early lactation than in the rest of the lactation. It is commonly observed that traits in early lactation are different than the rest of lactation, such as fat and protein yield (Jamrozik and Schaeffer, 1997), liability to clinical mastitis Heringstad et al, 2004;Negussie et al, 2008), SCC and SCS (Haile-Mariam et al, 2001;Mrode and Swanson, 2003;Elsaid et al, 2011), liability to hoof problems (Alkhoder et al, 2010;Gernand et al, 2013), and traits related to energy balance (Koenen and Veerkamp, 1998;Manzanilla Pech et al, 2014;Harder et al, 2020).…”

Liability to diseases and their relation to dry matter intake and energy balance in German Holstein and Fleckvieh dairy cows

“…In terms of efficiency, we want to note that DMI in early lactation is genetically low correlated with DMI in late lactation. Different genes affect DMI at different lactation stages (Berry et al, 2007;Tetens et al, 2014;Harder et al, 2020). Spurlock et al (2012) concluded this for EB as well.…”

Identification of Genomic Instability in Cows Infected with BVD Virus

“…Any deviations from these standards can negatively affect milk production [7][8][9]. Dairy cattle breeding has long been aimed at a high milk yield, often at the expense of functional traits, the loss of which may entail health disorders and affect longevity [10][11][12][13][14][15]. Animals with high genetic resistance maintain a good production level despite the frequently negative impact of exogenous factors [16,17].…”