Estimation of genetic parameters and single-step genome-wide association studies for milk urea nitrogen in Holstein cattle

The main objectives of this study were to estimate genetic parameters for milk urea nitrogen (MUN) in Holstein cattle and to conduct a single-step (ss)GWAS to identify candidate genes associated with MUN. Phenotypic measurements from 24,435 Holstein cows were collected from March 2013 to July 2019 in 9 dairy farms located in the Beijing area, China. A total of 2,029 cows were genotyped using the Illumina 150K Bovine Bead Chip, containing 121,188 SNP. A single-trait repeatability model was used to evaluate the genetic background of MUN. We found that MUN is a trait with low heritability (0.06 ± 0.004) and repeatability (0.12). Considering similar milk production levels, a lower MUN concentration indicates higher nitrogen digestibility. The genetic correlations between MUN and milk yield, net energy concentration, fat percentage, protein percentage, and lactose percentage were positive and ranged from 0.02 to 0.26. The genetic correlation between MUN and somatic cell score (SCS) was negative (?0.18), indicating that animals with higher MUN levels tend to have lower SCS. Both ssGWAS and pathway enrichment analyses were used to explore the genetic mechanisms underlying MUN. A total of 18 SNP (located on BTA11, BTA12, BTA14, BTA17, and BTA18) were found to be significantly associated with MUN. The genes CFAP77, CAMSAP1, CACNA1B, ADGRB1, FARP1, and INTU are considered to be candidate genes for MUN. These candidate genes are associated with important biological processes such as protein and lipid metabolism and binding to specific proteins. This set of candidate genes, metabolic pathways, and their functions provide a better understanding of the genomic architecture and physiological mechanisms underlying MUN in Holstein cattle.     

Association analysis for young stock survival index with imputed whole-genome sequence variants in Nordic Holstein cattle

Identification of the genetic variants associated with calf survival in dairy cattle will aid in the elimination of harmful mutations from the cattle population and the reduction of calf and young stock mortality rates. We used de-regressed estimated breeding values for the young stock survival (YSS) index as response variables in a genome-wide association study with imputed whole-genome sequence variants. A total of 4,610 bulls with estimated breeding values were genotyped with the Illumina BovineSNP50 (Illumina, San Diego, CA) single nucleotide polymorphism (SNP) genotyping array. Genotypes were imputed to whole-genome sequence variants. After quality control, 15,419,550 SNP on 29 Bos taurus autosomes (BTA) were used for association analysis. A modified mixed-model association analysis was used for a genome scan, followed by a linear mixed-model analysis for selected genetic variants. We identified 498 SNP on BTA5 and BTA18 that were associated with the YSS index in Nordic Holstein. The SNP rs440345507 (Chr5:94721790) on BTA5 was the putative causal mutation affecting YSS. Two haplotype-based models were used to identify haplotypes with the largest detrimental effects on YSS index. For each association signal, 1 haplotype region with harmful effects and the lead associated SNP were identified. Detected haplotypes on BTA5 and BTA18 explained 1.16 and 1.20%, respectively, of genetic variance for the YSS index. We examined whether YSS quantitative trait loci (QTL) on BTA5 and BTA18 were associated with stillbirth. YSS QTL on BTA18 overlapped a QTL region for stillbirth, but most likely 2 different causal variants were responsible for these 2 QTL. Four component traits of the YSS index, defined by sex and age, were analyzed separately by the modified mixed-model approach. The same genomic regions were associated with both bull and heifer calf mortality. Several genes (EPS8, LOC100138951, and KLK family genes) contained a lead associated SNP or were included in haplotypes with large detrimental effects on YSS in Nordic Holstein cattle.     

Genetic parameters for rectal temperature,respiration rate,and drooling score in Holstein cattle and their relationships with various fertility,production, body conformation,and health traits

Genetic selection for improved climatic resilience is paramount to increase the long-term sustainability of high-producing dairy cattle, especially in face of climate change. Various physiological indicators, such as rectal temperature (RT), respiration rate score (RR), and drooling score (DS), can be used to genetically identify animals with more effective coping mechanisms in response to heat stress events. In this study, we investigated genetic parameters for RT, RR (score from 1–3), and DS (score from 1–3). Furthermore, we assessed the genetic relationship among these indicators and other economically important traits for the dairy cattle industry. After data editing, 59,265 (RT), 30,290 (RR), and 30,421 (DS) records from 13,592 lactating Holstein cows were used for the analyses. Variance components were estimated based on a multiple-trait repeatability animal model. The heritability ± standard error estimate for RT, RR, and DS was 0.06 ± 0.01, 0.04 ± 0.01, and 0.02 ± 0.01, respectively, whereas their repeatability was 0.19, 0.14, and 0.14, respectively. Moderate genetic correlations of RR with RT and DS (0.26 ± 0.11 and 0.25 ± 0.16) and nonsignificant correlation between RT and DS (?0.11 ± 0.14) were observed. Furthermore, the approximate genetic correlations between RT, RR, and DS with 12 production, 29 conformation, 5 fertility and reproduction, 5 health, and 9 longevity-indicator traits were assessed. In general, the approximate genetic correlations calculated were low to moderate. In summary, 3 physiological indicators of heat stress response were measured in a large number of animals and shown to be lowly heritable. There is a value in developing a selection index including all the 3 indicators to improve heat tolerance in dairy cattle. All the unfavorable genetic relationships observed between heat tolerance and other economically important traits can be accounted for in a selection index to enable improved climatic resilience while also maintaining or increasing productivity in Holstein cattle.     

Genome-wide association study using high-density single nucleotide polymorphism arrays and whole-genome sequences for clinical mastitis traits in dairy cattle

Mastitis is a mammary disease that frequently affects dairy cattle. Despite considerable research on the development of effective prevention and treatment strategies, mastitis continues to be a significant issue in bovine veterinary medicine. To identify major genes that affect mastitis in dairy cattle, 6 chromosomal regions on Bos taurus autosome (BTA) 6, 13, 16, 19, and 20 were selected from a genome scan for 9 mastitis phenotypes using imputed high-density single nucleotide polymorphism arrays. Association analyses using sequence-level variants for the 6 targeted regions were carried out to map causal variants using whole-genome sequence data from 3 breeds. The quantitative trait loci (QTL) discovery population comprised 4,992 progeny-tested Holstein bulls, and QTL were confirmed in 4,442 Nordic Red and 1,126 Jersey cattle. The targeted regions were imputed to the sequence level. The highest association signal for clinical mastitis was observed on BTA 6 at 88.97 Mb in Holstein cattle and was confirmed in Nordic Red cattle. The peak association region on BTA 6 contained 2 genes: vitamin D-binding protein precursor (GC) and neuropeptide FF receptor 2 (NPFFR2), which, based on known biological functions, are good candidates for affecting mastitis. However, strong linkage disequilibrium in this region prevented conclusive determination of the causal gene. A different QTL on BTA 6 located at 88.32 Mb in Holstein cattle affected mastitis. In addition, QTL on BTA 13 and 19 were confirmed to segregate in Nordic Red cattle and QTL on BTA 16 and 20 were confirmed in Jersey cattle. Although several candidate genes were identified in these targeted regions, it was not possible to identify a gene or polymorphism as the causal factor for any of these regions.     

High-density genome-wide association study for residual feed intake in Holstein dairy cattle

Improving feed efficiency (FE) of dairy cattle may boost farm profitability and reduce the environmental footprint of the dairy industry. Residual feed intake (RFI), a candidate FE trait in dairy cattle, can be defined to be genetically uncorrelated with major energy sink traits (e.g., milk production, body weight) by including genomic predicted transmitting ability of such traits in genetic analyses for RFI. We examined the genetic basis of RFI through genome-wide association (GWA) analyses and post-GWA enrichment analyses and identified candidate genes and biological pathways associated with RFI in dairy cattle. Data were collected from 4,823 lactations of 3,947 Holstein cows in 9 research herds in the United States. Of these cows, 3,555 were genotyped and were imputed to a high-density list of 312,614 SNP. We used a single-step GWA method to combine information from genotyped and nongenotyped animals with phenotypes as well as their ancestors' information. The estimated genomic breeding values from a single-step genomic BLUP were back-solved to obtain the individual SNP effects for RFI. The proportion of genetic variance explained by each 5-SNP sliding window was also calculated for RFI. Our GWA analyses suggested that RFI is a highly polygenic trait regulated by many genes with small effects. The closest genes to the top SNP and sliding windows were associated with dry matter intake (DMI), RFI, energy homeostasis and energy balance regulation, digestion and metabolism of carbohydrates and proteins, immune regulation, leptin signaling, mitochondrial ATP activities, rumen development, skeletal muscle development, and spermatogenesis. The region of 40.7 to 41.5 Mb on BTA25 (UMD3.1 reference genome) was the top associated region for RFI. The closest genes to this region, CARD11 and EIF3B, were previously shown to be related to RFI of dairy cattle and FE of broilers, respectively. Another candidate region, 57.7 to 58.2 Mb on BTA18, which is associated with DMI and leptin signaling, was also associated with RFI in this study. Post-GWA enrichment analyses used a sum-based marker-set test based on 4 public annotation databases: Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, Reactome pathways, and medical subject heading (MeSH) terms. Results of these analyses were consistent with those from the top GWA signals. Across the 4 databases, GWA signals for RFI were highly enriched in the biosynthesis and metabolism of amino acids and proteins, digestion and metabolism of carbohydrates, skeletal development, mitochondrial electron transport, immunity, rumen bacteria activities, and sperm motility. Our findings offer novel insight into the genetic basis of RFI and identify candidate regions and biological pathways associated with RFI in dairy cattle.     

Gene mapping,gene-set analysis,and genomic prediction of postpartum blood calcium in Holstein cows

The onset of lactation results in a sudden irreversible loss of Ca for colostrum and milk synthesis. Some cows are unable to quickly adapt to this demand and succumb to clinical hypocalcemia, whereas a larger proportion of cows develop subclinical hypocalcemia that predisposes them to other peripartum diseases. The objective of this study was to perform a comprehensive genomic analysis of blood total Ca concentration in periparturient Holstein cows. We first performed a genomic scan and a subsequent gene-set analysis to identify candidate genes, biological pathways, and molecular mechanisms affecting postpartum Ca concentration. Then, we assessed the prediction of postpartum Ca concentration using genomic information. Data consisted of 7,691 records of plasma or serum concentrations of Ca measured in the first, second, and third day after parturition of 959 primiparous and 1,615 multiparous cows that calved between December 2015 and June 2020 in 2 dairy herds. All cows were genotyped with 80k SNPs. The statistical model included lactation (1 to 5+), calf category (male, females, twins), and day as fixed effects, and season-treatment-experiment, animal, and permanent environmental as random effects. Model predictive ability was evaluated using 10-fold cross-validation. Heritability and repeatability estimates were 0.083 (standard error = 0.017) and 0.444 (standard error = 0.028). The association mapping identified 2 major regions located on Bos taurus autosome (BTA)6 and BTA16 that explained 1.2% and 0.7% of additive genetic variance of Ca concentration, respectively. Interestingly, the region on BTA6 harbors the GC gene, which encodes the vitamin D binding protein, and the region on BTA16 harbors LRRC38, which is actively involved in K transport. Other sizable peaks were identified on BTA5, BTA2, BTA7, BTA14, and BTA9. These regions harbor genes associated with Ca channels (CACNA1S, CRACR2A), K channels (KCNK9), bone remodeling (LRP6), and milk production (SOCS2). The gene-set analysis revealed terms related to vitamin transport, calcium ion transport, calcium ion binding, and calcium signaling. Genomic predictions of phenotypic and genomic estimated breeding values of Ca concentration yielded predictive correlations up to 0.50 and 0.15, respectively. Overall, the present study contributes to a better understanding of the genetic basis of postpartum blood Ca concentration in Holstein cows. In addition, the findings may contribute to the development of novel selection and management strategies for reducing periparturient hypocalcemia in dairy cattle.     

The genetic architecture of milk ELISA scores as an indicator of Johne's disease (paratuberculosis) in dairy cattle

Johne's disease (or paratuberculosis), caused by Mycobacterium avium ssp. paratuberculosis (MAP) infection, is a globally prevalent disease with severe economic and welfare implications. With no effective treatment available, understanding the role of genetics influencing host infection status is essential to develop selection strategies to breed for increased resistance to MAP infection. The main objectives of this study were to estimate genetic parameters for the MAP-specific antibody response using milk ELISA scores in Canadian Holstein cattle as an indicator of resistance to Johne's disease, and to unravel genomic regions and candidate genes significantly associated with MAP infection. After data editing, 168,987 milk ELISA records from 2,306 herds, obtained from CanWest Dairy Herd Improvement, were used for further analyses. Variance and heritability estimates for MAP infection status were determined using univariate linear animal models under 3 scenarios: (a) SCEN1: the complete data set (all herds); (b) SCEN2: herds with at least one suspect or test-positive animal (ELISA optical density ≥0.07); and (c) SCEN3: herds with at least one test-positive animal (ELISA optical density ≥0.11). Heritability estimates were calculated as 0.066, 0.064, and 0.063 for SCEN1, SCEN2, and SCEN3, respectively. The correlations between estimated breeding values for resistance to MAP infection and other economically important traits, when significant, were favorable and of low magnitude. Genome-wide association analyses identified important genomic regions on Bos taurus autosome (BTA)1, BTA7, BTA9, BTA14, BTA15, BTA17, BTA19, and BTA25 showing significant association with MAP infection status. These regions included 2 single nucleotide polymorphisms located 2 kb upstream of positional candidate genes CD86 and WNT9B, which play key roles in host immune response and tissue homeostasis. This study revealed the genetic architecture of MAP infection in Canadian Holstein cattle as measured by milk ELISA scores by estimating genetic parameters along with the identification of genomic regions potentially influencing MAP infection status. These findings will be of significant value toward implementing genetic and genomic evaluations for resistance to MAP infection in Holstein cattle.     

Genome-wide associations for heat stress response suggest potential candidate genes underlying milk fatty acid composition in dairy cattle

Contents of milk fatty acids (FA) display remarkable alterations along climatic gradients. Detecting candidate genes underlying such alterations might be beneficial for the exploration of climate sensitivity in dairy cattle. Consequently, we aimed on the definition of FA heat stress indicators, considering FA breeding values in response to temperature-humidity index (THI) alterations. Indicators were used in GWAS, in ongoing gene annotations and for the estimation of chromosome-wide variance components. The phenotypic data set consisted of 39,600 test-day milk FA records from 5,757 first-lactation Holstein dairy cows kept in 16 large-scale German cooperator herds. The FA traits were C18:0, polyunsaturated fatty acids (PUFA), saturated fatty acids (SFA), and unsaturated fatty acids (UFA). After genotype quality control, 40,523 SNP markers from 3,266 cows and 930 sires were considered. Meteorological data from the weather station in closest herd distance were used for the calculation of maximum hourly daily THI, which were allocated to 10 different THI classes. The same FA from 3 stages of lactation were considered as different, but genetically correlated traits. Consequently, a 3-trait reaction norm model was used to estimate genetic parameters and breeding values for FA along THI classes, considering either pedigree (A) or genomic (G) relationship matrices. De-regressed proofs and genomic estimated breeding values at the intermediate THI class 5 and at the extreme THI class 10 were used as pseudophenotypes in ongoing genomic analyses for thermoneutral (TNC) and heat stress conditions (HSC), respectively. The differences in de-regressed proofs and in genomic estimated breeding values from both THI classes were pseudophenotypes for heat stress response (HSR). Genetic correlations between the same FA under TNC and HSC were smallest in the first lactation stage and ranged from 0.20 for PUFA to 0.87 for SFA when modeling with the A matrix, and from 0.35 for UFA to 0.86 for SFA when modeling with the G matrix. In the first lactation stage, larger additive genetic variances under HSC compared with TNC indicate climate sensitivity for C18:0, PUFA, and UFA. Climate sensitivity was also reflected by pronounced chromosome-wide genetic variances for HSR of PUFA and UFA in the first stage of lactation. For all FA under TNC, HSC, and HSR, quite large genetic variance proportions were explained by BTA14. In GWAS, 30 SNP (within or close to 38 potential candidate genes) overlapped for HSR of the different FA. One unique potential candidate gene (AMFR) was detected for HSR of PUFA, 15 for HSR of SFA (ADGRB1, DENND3, DUSP16, EFR3A, EMP1, ENSBTAG00000003838, EPS8, MGP, PIK3C2G, STYK1, TMEM71, GSG1, SMARCE1, CCDC57, and FASN) and 3 for HSR of UFA (ENSBTAG00000048091, PAEP, and EPPK1). The identified unique genes play key roles in milk FA synthesis and are associated with disease resistance in dairy cattle. The results suggest consideration of FA in combination with climatic responses when inferring genetic mechanisms of heat stress in dairy cows.     

Short communication: Validation of in vitro fertility genes in a Holstein bull population

Previously, we constructed an in vitro fertilization system for the identification of genes affecting fertility traits in dairy cattle. The efficiency of this system has been demonstrated by the identification of several genes affecting fertilization rate and early embryonic survival. However, to employ these genetic markers in marker- and gene-assisted selection programs, there is a need to validate in vitro results in phenotypic data sets collected in vivo. Thus, the objective of this study was to validate, in a population of Holstein bulls, the fertility trait genes we previously identified in an in vitro system. Estimated relative conception rate (ERCR) data from 222 Holstein bulls were obtained from 5 different artificial insemination companies in the United States. Bulls were genotyped for the genes FGF2, POU1F1, PRL, PRLR, GH, GHR, STAT5A, OPN, and UTMP, and the data were analyzed for association with ERCR using a mixed effects sire model. A stepwise model selection procedure revealed evidence of association with ERCR for FGF2 and STAT5A polymorphisms. The in vivo validation suggests that these genes can be used in gene-assisted selection programs for reproductive performance in dairy cattle. The genotypes found to be associated with low bull fertility in this study have been reported to be associated with high milk composition in previous studies. These findings provide molecular evidence for the antagonistic relationship between milk production and fertility observed for many years in different breeds of dairy cattle.