Residual energy intake, energy balance, and liability to diseases: Genetic parameters and relationships in German Holstein dairy cows

Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows

BACKGROUND

Over the last decades, it was subject of many studies to investigate the genomic connection of milk production and health traits in dairy cattle. Thereby, incorporating functional information in genomic analyses has been shown to improve the understanding of biological and molecular mechanisms shaping complex traits and the accuracies of genomic prediction, especially in small populations and across-breed settings. Still, little is known about the contribution of different functional and evolutionary genome partitioning subsets to milk production and dairy health. Thus, we performed a uni- and a bivariate analysis of milk yield (MY) and eight health traits using a set of ~34,497 German Holstein cows with 50K chip genotypes and ~17 million imputed sequence variants divided into 27 subsets depending on their functional and evolutionary annotation. In the bivariate analysis, eight trait-combinations were observed that contrasted MY with each health trait. Two genomic relationship matrices (GRM) were included, one consisting of the 50K chip variants and one consisting of each set of subset variants, to obtain subset heritabilities and genetic correlations. In addition, 50K chip heritabilities and genetic correlations were estimated applying merely the 50K GRM.

RESULTS

In general, 50K chip heritabilities were larger than the subset heritabilities. The largest heritabilities were found for MY, which was 0.4358 for the 50K and 0.2757 for the subset heritabilities. Whereas all 50K genetic correlations were negative, subset genetic correlations were both, positive and negative (ranging from -0.9324 between MY and mastitis to 0.6662 between MY and digital dermatitis). The subsets containing variants which were annotated as noncoding related, splice sites, untranslated regions, metabolic quantitative trait loci, and young variants ranked highest in terms of their contribution to the traits` genetic variance. We were able to show that linkage disequilibrium between subset variants and adjacent variants did not cause these subsets` high effect.

CONCLUSION

Our results confirm the connection of milk production and health traits in dairy cattle via the animals` metabolic state. In addition, they highlight the potential of including functional information in genomic analyses, which helps to dissect the extent and direction of the observed traits` connection in more detail.

Unveiling the Genetic Landscape of Feed Efficiency in Holstein Dairy Cows: Insights into Heritability, Genetic Markers, and Pathways via Meta-Analysis

Improving the feeding efficiency of dairy cows is a key component to improve the utilization of land resources and meet the demand for high-quality protein. Advances in genomic methods and omics techniques have made it possible to breed more efficient dairy cows through genomic selection. The aim of this review is to obtain a comprehensive understanding of the biological background of feed efficiency (FE) complex traits in purebred Holstein dairy cows including heritability estimate, and genetic markers, genes, and pathways participating in FE regulation mechanism. Through a literature search, we systematically reviewed the heritability estimation, molecular genetic markers, genes, biomarkers, and pathways of traits related to feeding efficiency in Holstein dairy cows. A meta-analysis based on a random-effects model was performed to combine reported heritability estimates of FE complex. The heritability of residual feed intake, dry matter intake, and energy balance was 0.20, 0.34, and 0.22, respectively, which proved that it was reasonable to include the related traits in the selection breeding program. For molecular genetic markers, a total of 13 single-nucleotide polymorphisms and copy number variance loci, associated genes, and functions were reported to be significant across populations. A total of 169 reported candidate genes were summarized on a large scale, using a higher threshold (adjusted P value < 0.05). Then, the subsequent pathway enrichment of these genes was performed. The important genes reported in the articles were included in a gene list and the gene list was enriched by gene ontology (GO):biological process (BP), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis. Three GO:BP terms and four KEGG terms were statistically significant, which mainly focused on adenosine triphosphate (ATP) synthesis, electron transport chain, and OXPHOS pathway. Among these pathways, involved genes such as ATP5MC2, NDUFA, COX7A2, UQCR, and MMP are particularly important as they were previously reported. Twenty-nine reported biological mechanisms along with involved genes were explained mainly by four biological pathways (insulin-like growth factor axis, lipid metabolism, oxidative phosphorylation pathways, tryptophan metabolism). The information from this study will be useful for future studies of genomic selection breeding and genetic structures influencing animal FE. A better understanding of the underlying biological mechanisms would be beneficial, particularly as it might address genetic antagonism.

Genetic relationship of energy balance predicted from milk traits with fertility in Japanese Holsteins

We predicted the energy balance of cows from milk traits and estimated the genetic correlations of predicted energy balance (PEB) with fertility traits for the first three lactations. Data included 9,646,606 test-day records of 576,555 Holstein cows in Japan from 2015 to 2019. Genetic parameters were estimated with a multiple-trait model in which the records among lactation stages and parities were treated as separate traits. Fertility traits were conception rate at first insemination (CR), number of inseminations (NI), and days open (DO). Heritability estimates of PEB were 0.28-0.35 (first lactation), 0.15-0.29 (second), and 0.09-0.23 (third). Estimated genetic correlations among lactation stages were 0.85-1.00 (first lactation), 0.73-1.00 (second), and 0.64-1.00 (third). Estimated genetic correlations among parities were 0.82-0.96 (between first and second), 0.97-0.99 (second and third), and 0.69-0.92 (first and third). Estimated genetic correlations of PEB in early lactation with fertility were 0.04 to 0.19 for CR, -0.03 to -0.19 for NI, and -0.01 to -0.24 for DO. Genetic improvement of PEB is possible. Lower PEB in early lactation was associated with worse fertility, suggesting that improving PEB in early lactation may improve reproductive performance.

An evaluation of detailed animal characteristics influencing the lactation production efficiency of spring-calving, pasture-based dairy cattle

Selection for feed efficiency, the ratio of output (e.g., milk yield) to feed intake, has traditionally been limited on commercial dairy farms by the necessity for detailed individual animal intake and performance data within large animal populations. The objective of the experiment was to evaluate the effects of individual animal characteristics (animal breed, genetic potential, milk production, body weight (BW), daily total dry matter intake (TDMI), and energy balance) on a cost-effective production efficiency parameter calculated as the annual fat and protein (milk solids) production per unit of mid-lactation BW (MSperBW_lact). A total of 1,788 individual animal intake records measured at various stages of lactation (early, mid, and late lactation) from 207 Holstein-Friesian and 200 Jersey × Holstein-Friesian cows were used. The derived efficiency traits included daily kilograms of milk solids produced per 100 kg of BW (dMSperBW_int) and daily kilograms of milk solids produced per kilogram of TDMI (dMSperTDMI). The TDMI per 100 kg of BW was also calculated (TDMI/BW_int) at each stage of lactation. Animals were subsequently either ranked as the top 25% (Heff) or bottom 25% (Leff) based on their lactation production efficiency (MSperBW_lact). Dairy cow breed significantly affected animal characteristics over the entire lactation and during specific periods of intake measurements. Jersey crossbred animals produced more milk, based on a lower TDMI, and achieved an increased intake per kilogram of BW. Similarly, Heff produced more milk over longer lactations, weighed less, were older, and achieved a higher TDMI compared with the Leff animals. Both Jersey × Holstein-Friesian and Heff cows achieved superior production efficiency due to lower maintenance energy requirements, and consequentially increased milk solids production per kilogram of BW and per kilogram of TDMI at all stages of lactation. Indeed, within breed, Heff animals weighed 20 kg less and produced 15% more milk solids over the total lactation than Leff. In addition, Heff achieved increased daily milk solids yield (+0.16 kg) and milk solids yield per kilogram of TDMI (+ 0.23 kg/kg DM) during intake measurement periods. Moreover, the strong and consistently positive correlations between MSperBW_lact and detailed production efficiency traits (dMSperBW_int, dMSperTDMI) reported here demonstrate that MSperBW_lact is a robust measure that can be applied within commercial grazing dairy systems to increase the selection intensity for highly efficient animals.

A genomic assessment of the correlation between milk production traits and claw and udder health traits in Holstein dairy cattle

Claw diseases and mastitis represent the most important disease traits in dairy cattle with increasing incidences and a frequently mentioned connection to milk yield. Yet, many studies aimed to detect the genetic background of both trait complexes via fine-mapping of quantitative trait loci. However, little is known about genomic regions that simultaneously affect milk production and disease traits. For this purpose, several tools to detect local genetic correlations have been developed. In this study, we attempted a detailed analysis of milk production and disease traits as well as their interrelationship using a sample of 34,497 50K genotyped German Holstein cows with milk production and claw and udder disease traits records. We performed a pedigree-based quantitative genetic analysis to estimate heritabilities and genetic correlations. Additionally, we generated GWAS summary statistics, paying special attention to genomic inflation, and used these data to identify shared genomic regions, which affect various trait combinations. The heritability on the liability scale of the disease traits was low, between 0.02 for laminitis and 0.19 for interdigital hyperplasia. The heritabilities for milk production traits were higher (between 0.27 for milk energy yield and 0.48 for fat-protein ratio). Global genetic correlations indicate the shared genetic effect between milk production and disease traits on a whole genome level. Most of these estimates were not significantly different from zero, only mastitis showed a positive one to milk (0.18) and milk energy yield (0.13), as well as a negative one to fat-protein ratio (-0.07). The genomic analysis revealed significant SNPs for milk production traits that were enriched on Bos taurus autosome 5, 6, and 14. For digital dermatitis, we found significant hits, predominantly on Bos taurus autosome 5, 10, 22, and 23, whereas we did not find significantly trait-associated SNPs for the other disease traits. Our results confirm the known genetic background of disease and milk production traits. We further detected 13 regions that harbor strong concordant effects on a trait combination of milk production and disease traits. This detailed investigation of genetic correlations reveals additional knowledge about the localization of regions with shared genetic effects on these trait complexes, which in turn enables a better understanding of the underlying biological pathways and putatively the utilization for a more precise design of breeding schemes.

Long-term effects of early-life rumen microbiota modulation on dairy cow production performance and methane emissions

Rumen microbiota modulation during the pre-weaning period has been suggested as means to affect animal performance later in life. In this follow-up study, we examined the post-weaning rumen microbiota development differences in monozygotic twin-heifers that were inoculated (T-group) or not inoculated (C-group) (n = 4 each) with fresh adult rumen liquid during their pre-weaning period. We also assessed the treatment effect on production parameters and methane emissions of cows during their 1st lactation period. The rumen microbiota was determined by the 16S rRNA gene, 18S rRNA gene, and ITS1 amplicon sequencing. Animal weight gain and rumen fermentation parameters were monitored from 2 to 12 months of age. The weight gain was not affected by treatment, but butyrate proportion was higher in T-group in month 3 (p = 0.04). Apart from archaea (p = 0.084), the richness of bacteria (p < 0.0001) and ciliate protozoa increased until month 7 (p = 0.004) and anaerobic fungi until month 11 (p = 0.005). The microbiota structure, measured as Bray-Curtis distances, continued to develop until months 3, 6, 7, and 10, in archaea, ciliate protozoa, bacteria, and anaerobic fungi, respectively (for all: p = 0.001). Treatment or age × treatment interaction had a significant (p < 0.05) effect on 18 bacterial, 2 archaeal, and 6 ciliate protozoan taxonomic groups, with differences occurring mostly before month 4 in bacteria, and month 3 in archaea and ciliate protozoa. Treatment stimulated earlier maturation of prokaryote community in T-group before month 4 and earlier maturation of ciliate protozoa at month 2 (Random Forest: 0.75 month for bacteria and 1.5 month for protozoa). No treatment effect on the maturity of anaerobic fungi was observed. The milk production and quality, feed efficiency, and methane emissions were monitored during cow's 1st lactation. The T-group had lower variation in energy-corrected milk yield (p < 0.001), tended to differ in pattern of residual energy intake over time (p = 0.069), and had numerically lower somatic cell count throughout their 1st lactation period (p = 0.081), but no differences between the groups in methane emissions (g/d, g/kg DMI, or g/kg milk) were observed. Our results demonstrated that the orally administered microbial inoculant induced transient changes in early rumen microbiome maturation. In addition, the treatment may influence the later production performance, although the mechanisms that mediate these effects need to be further explored.