The objective of this study was to identify genomic regions and candidate genes associated with feed efficiency in lactating Holstein cows. In total, 4,916 cows with actual or imputed genotypes for 60,671 single nucleotide polymorphisms having individual feed intake, milk yield, milk composition, and body weight records were used in this study. Cows were from research herds located in the United States, Canada, the Netherlands, and the United Kingdom. Feed efficiency, defined as residual feed intake (RFI), was calculated within location as the residual of the regression of dry matter intake (DMI) on milk energy (MilkE), metabolic body weight (MBW), change in body weight, and systematic effects. For RFI, DMI, MilkE, and MBW, bivariate analyses were performed considering each trait as a separate trait within parity group to estimate variance components and genetic correlations between them. Animal relationships were established using a genomic relationship matrix. Genome-wide association studies were performed separately by parity group for RFI, DMI, MilkE, and MBW using the Bayes B method with a prior assumption that 1% of single nucleotide polymorphisms have a nonzero effect. One-megabase windows with greatest percentage of the total genetic variation explained by the markers (TGVM) were identified, and adjacent windows with large proportion of the TGVM were combined and reanalyzed. Heritability estimates for RFI were 0.14 (±0.03; ±SE) in primiparous cows and 0.13 (±0.03) in multiparous cows. Genetic correlations between primiparous and multiparous cows were 0.76 for RFI, 0.78 for DMI, 0.92 for MBW, and 0.61 for MilkE. No single 1-Mb window explained a significant proportion of the TGVM for RFI; however, after combining windows, significance was met on Bos taurus autosome 27 in primiparous cows, and nearly reached on Bos taurus autosome 4 in multiparous cows. Among other genes, these regions contain β-3 adrenergic receptor and the physiological candidate gene, leptin, respectively. Between the 2 parity groups, 3 of the 10 windows with the largest effects on DMI neighbored windows affecting RFI, but were not in the top 10 regions for MilkE or MBW. This result suggests a genetic basis for feed intake that is unrelated to energy consumption required for milk production or expected maintenance as determined by MBW. In conclusion, feed efficiency measured as RFI is a polygenic trait exhibiting a dynamic genetic basis and genetic variation distinct from that underlying expected maintenance requirements and milk energy output.
Among other regulations, organic cows in the United States cannot receive antibiotics and preserve their organic status, emphasizing the importance of prevention of illness and benefit of high genetic merit for disease resistance. At the same time, data underlying national genetic evaluations primarily come from conventional cows, drawing concern to the possibility of a genotype by environment interaction whereby the value of a genotype varies depending on the environment, and potentially limits the relevance of these evaluations to organic cows. The objectives of this study were to characterize the genetics of and determine the presence of genotype by environment interaction for health traits in US organic dairy cows. Individual cow health data were obtained from 16 US Department of Agriculture certified organic dairy farms from across the United States that used artificial insemination and maintained detailed records. Data were obtained for the following traits: died, lameness, mastitis, metabolic diseases (displaced abomasum, ketosis, and milk fever), reproductive diseases (abortion, metritis, and retained placenta), transition health events (any health event occurring 21 d before or after parturition), and all health events. Binary phenotypes (1 = diseased, 0 = otherwise) for 38,949 lactations on 19,139 Holstein cows were used. Genotypes from 2,347 cows with 87.5% or greater Holstein breed-based representation were incorporated into single-step multitrait threshold animal models that included stayability (1 = completed lactation, 0 = otherwise). Gibbs sampling was used. Genomic predicted transmitting abilities (gPTA) from national genetic evaluations were obtained for sires for production, fitness, health, and conformation traits. We approximated genetic correlations for sires using these gPTA and our estimated breeding values. We also regressed health phenotypes on cow estimated breeding values and sire gPTA. Heritabilities (± standard error) ranged from 0.03 ± 0.01 (reproductive diseases) to 0.11 ± 0.03 (metabolic diseases). Most genetic correlations among health traits were positive, though the genetic correlation between metabolic disease and mastitis was −0.42 ± 0.17. Approximate genetic correlations between disease resistance for our health trait categories and disease resistance for the nationally-evaluated health traits generally carried the expected sign with the strongest correlation for mastitis (0.72 ± 0.084). Regression coefficients carried the expected sign and were mostly different from zero, indicating that evaluations from primarily conventional herd data predicted health on organic farms. In conclusion, use of national evaluations for health traits should afford genetic improvement for health in US organic herds.
The objectives of this study were to estimate genetic parameters for stayability in US organic Holstein dairy cows and estimate genetic correlations with nationally evaluated traits of interest. Stayability is the binary trait for success or failure to remain in the herd until a given time point. We used birth, calving, and cull dates from 16 USDA certified organic farms recommended by industry personnel as herds maintaining individual cow records and using artificial insemination. Stayability at 5 time points was assigned based on the presence of a calving date for each parity up to 5 (STAY1 to STAY5). We also considered livebirth (vs. stillbirth), stayability from a successful first calving to second calving (STAY12), stayability from a successful second calving to third calving (STAY23), and stayability as a repeated measure encompassing STAY1 to STAY5. In total, 44,995 females were used in this study. Ninety-six percent were born alive and of these, 64% reached first parity. Animals with Holstein sires and no other identified breed for 3 generations on the maternal side were included. Heritabilities for stayability to each parity on the underlying scale were estimated using a threshold model with the fixed effect of herd and the random effects of animal and herd-year-season of birth. Genetic correlations were estimated among livebirth, STAY1, STAY12, and STAY23 with a 4-trait linear model with fixed herd-year-season of birth and random effects of animal, dam of the calf (livebirth), and herd calving date (STAY12 and STAY23). Heritabilities for stayability ranged from 0.07 to 0.15 and was 0.08 for the direct effect of livebirth and 0.06 for the maternal effect of livebirth. The repeatability for stayability was 0.60. Genetic correlations ranged from 0.11 between livebirth and STAY1 to 0.83 between STAY12 and STAY23. Excluding livebirth, stayability to all time points was significantly correlated with productive life and with cow livability. In general, stayability was positively associated with milk yield and negatively associated with fat percent and stillbirth. In conclusion, stayability in organic herds is heritable and positively associated with nationally evaluated longevity traits suggesting that improvement for stayability in organic herds can be achieved with current national evaluations for longevity.
Prior to genomic selection on a trait, a reference population needs to be established to link marker genotypes with phenotypes. For costly and difficult-to-measure traits, international collaboration and sharing of data between disciplines may be necessary. Our aim was to characterize the combining of data from nutrition studies carried out under similar climate and management conditions to estimate genetic parameters for feed efficiency. Furthermore, we postulated that data from the experimental cohorts within these studies can be used to estimate the net energy of lactation (NE(L)) densities of diets, which can provide estimates of energy intakes for use in the calculation of the feed efficiency metric, residual feed intake (RFI), and potentially reduce the effect of variation in energy density of diets. Individual feed intakes and corresponding production and body measurements were obtained from 13 Midwestern nutrition experiments. Two measures of RFI were considered, RFI(Mcal) and RFI(kg), which involved the regression of NE(L )intake (Mcal/d) or dry matter intake (DMI; kg/d) on 3 expenditures: milk energy, energy gained or lost in body weight change, and energy for maintenance. In total, 677 records from 600 lactating cows between 50 and 275 d in milk were used. Cows were divided into 46 cohorts based on dietary or nondietary treatments as dictated by the nutrition experiments. The realized NE(L) densities of the diets (Mcal/kg of DMI) were estimated for each cohort by totaling the average daily energy used in the 3 expenditures for cohort members and dividing by the cohort's total average daily DMI. The NE(L) intake for each cow was then calculated by multiplying her DMI by her cohort's realized energy density. Mean energy density was 1.58 Mcal/kg. Heritability estimates for RFI(kg), and RFI(Mcal) in a single-trait animal model did not differ at 0.04 for both measures. Information about realized energy density could be useful in standardizing intake data from different climate conditions or management systems, as well as investigating potential genotype by diet interactions.
The objectives of this study were to estimate genetic parameters of calf health in organic US Holstein calves. Calves were born on farms across the United States from 2006 to 2019. Three calf health traits were evaluated in the study: calf respiratory disease until 365 d of age, calf scours until 60 d of age, and heifer stayability until 365 d of age. For respiratory disease and scours, animals were assigned a phenotype of 0 if they were healthy and a phenotype of 1 if they were diseased. For stayability, animals were assigned a phenotype of 0 if they were removed from the herd by 365 d of age and 1 if they remained in the herd at 365 d of age. Genetic parameters were estimated from threshold models that included the fixed effects of mean, year-season of birth, and dam age (respiratory disease and scours only) as well as the random effects of herd-year of birth and additive genetics. Heritability estimates were 0.100, 0.075, and 0.085 for respiratory disease, scours, and stayability, respectively. Solutions for estimated breeding values for respiratory disease and scours were transformed from disease risk to disease resistance by reversing the signs before calculating genetic correlations such that higher values of scours, respiratory disease, and stayability were favored. There was a moderate favorable genetic correlation estimate between respiratory disease resistance and stayability of 0.675. However, genetic correlation estimates between respiratory disease resistance and scours resistance (0.148) and between scours resistance and stayability (0.165) were low. Estimated breeding value correlations between calf health traits and other traits evaluated nationally were generally low in magnitude. The strongest correlation estimates were with longevity, particularly between stayability and heifer livability (0.217) and between stayability and cow livability (0.288); respiratory disease resistance was also favorably correlated with heifer (0.190) and cow (0.178) livability. Correlations with cow health traits were generally low and unfavorable. Linear models including the random effect of herd-by-sire indicated that herd-by-sire accounted for approximately 2% of phenotypic variance for scours and stayability, which may indicate a genotype by environment interaction effect for these traits. In conclusion, there is significant genetic variation in organic calf health, and there was evidence of genotype by environment interaction.
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