New mutation within a common haplotype is associated with calf muscle weakness in Holsteins.

A recessive haplotype resulting in elevated calf mortality but with apparent incomplete penetrance was previously linked to the end of chromosome 16 (78.7-80.7 Mbp). Genotype analysis of 5.6 million Holsteins indicated that the haplotype was common and traced back to 1952, with a key ancestor born in 1984 (HOUSA1964484, Southwind) identified from chip genotypes as homozygous for the suspect haplotype. Sequence data from Southwind (an affected calf) and the sire of the affected calf were scanned for candidate mutations. A missense mutation with a deleterious projected impact at 79,613,592 bp was homozygous in the affected calf and heterozygous in the calf's sire and Southwind. Sequence data available from the Cooperative Dairy DNA Repository for 299 other Holsteins indicated a 97% concordance with the haplotype and an 89% call rate. The exon amino acid sequence appears to be broadly conserved in the CACNA1S gene, and mutations in humans and mice can cause phenotypes of temporary or permanent paralysis analogous to those in calves with the haplotype causing muscle weakness (HMW). Improved methods for using pedigree to track new mutations within existing haplotypes were developed and applied to the haplotypes for both muscle weakness and Holstein cholesterol deficiency (HCD). For HCD, concordance of the gene test with its haplotype status was greatly improved. For both defects, haplotype status was matched to heifer livability records for 558,000 calves. For HMW, only 46 heifers with livability records were homozygous and traced only to Southwind on both sides. Of those, 52% died before 18 mo at an average age of 1.7 ± 1.6 mo, but that death rate may be underestimated if only healthier calves were genotyped. The death rate was 2.4% for noncarriers. Different reporting methods or dominance effects may be needed to include HMW and other partially lethal effects in selection and mating. Direct tests are needed for new mutations within existing common haplotypes because tracking can be difficult even with accurate pedigrees when the original haplotype has a high frequency.

Inheritance of a mutation causing neuropathy with splayed forelimbs in Jersey cattle.

A new undesirable genetic factor, neuropathy with splayed forelimbs (JNS), has been identified recently in the Jersey breed. Calves affected with JNS are unable to stand on splayed forelimbs that exhibit significant extensor rigidity and excessive lateral abduction at birth. Affected calves generally are alert at birth but exhibit neurologic symptoms, including spasticity of head and neck and convulsive behavior. Other symptoms reported include dislocated shoulders, congenital craniofacial anomalies, and degenerative myelopathy. Inheritance of an undesirable genetic factor was determined from a study of 16 affected calves reported by Jersey breeders across the United States. All of their pedigrees traced back on both paternal and maternal sides to a common ancestor born in 1995. Genotypes revealed that JNS is attributable to a specific haplotype on Bos taurus autosome 6. Currently 8.2% of the genotyped US Jersey population are carriers of the haplotype. Sequencing of the region of shared homozygosity revealed missense variant rs1116058914 at base 60,158,901 of the ARS-UCD1.2 reference map as the most concordant with the genetic condition and the most likely cause. The single-base G to A substitution is in the coding region of the last exon of UCHL1, which is conserved across species. Mutations in humans and gene knockouts in mice cause similar recessive symptoms and muscular degeneration. Since December 2020, carrier status has been tracked using the identified haplotype and reported for all 459,784 genotyped Jersey animals. With random mating, about 2,200 affected calves per year with losses of about $250,000 would result from the 1.3 million US Jersey cows in the national population. Selection and mating programs can reduce numbers of JNS-affected births using either the haplotype status or a direct gene test in the future. Breeders should report calf abnormalities to their breed association to help discover new defects such as JNS.

Development of polymorphic markers in the immune gene complex loci of cattle.

The addition of cattle health and immunity traits to genomic selection indices holds promise to increase individual animal longevity and productivity, and decrease economic losses from disease. However, highly variable genomic loci that contain multiple immune-related genes were poorly assembled in the first iterations of the cattle reference genome assembly and underrepresented during the development of most commercial genotyping platforms. As a consequence, there is a paucity of genetic markers within these loci that may track haplotypes related to disease susceptibility. By using hierarchical assembly of bacterial artificial chromosome inserts spanning 3 of these immune-related gene regions, we were able to assemble multiple full-length haplotypes of the major histocompatibility complex, the leukocyte receptor complex, and the natural killer cell complex. Using these new assemblies and the recently released ARS-UCD1.2 reference, we aligned whole-genome shotgun reads from 125 sequenced Holstein bulls to discover candidate variants for genetic marker development. We selected 124 SNPs, using heuristic and statistical models to develop a custom genotyping panel. In a proof-of-principle study, we used this custom panel to genotype 1,797 Holstein cows exposed to bovine tuberculosis (bTB) that were the subject of a previous GWAS study using the Illumina BovineHD array. Although we did not identify any significant association of bTB phenotypes with these new genetic markers, 2 markers exhibited substantial effects on bTB phenotypic prediction. The models and parameters trained in this study serve as a guide for future marker discovery surveys particularly in previously unassembled regions of the cattle genome.

Marker selection and genomic prediction of economically important traits using imputed high-density genotypes for 5 breeds of dairy cattle.

Marker sets used in US dairy genomic predictions were previously expanded by including high-density (HD) or sequence markers with the largest effects for Holstein breed only. Other non-Holstein breeds lacked enough HD genotyped animals to be used as a reference population at that time, and thus were not included in the genomic prediction. Recently, numbers of non-Holstein breeds genotyped using HD panels reached an acceptable level for imputation and marker selection, allowing HD genomic prediction and HD marker selection for Holstein plus 4 other breeds. Genotypes for 351,461 Holsteins, 347,570 Jerseys, 42,346 Brown Swiss, 9,364 Ayrshires (including Red dairy cattle), and 4,599 Guernseys were imputed to the HD marker list that included 643,059 SNP. The separate HD reference populations included Illumina BovineHD (San Diego, CA) genotypes for 4,012 Holsteins, 407 Jerseys, 181 Brown Swiss, 527 Ayrshires, and 147 Guernseys. The 643,059 variants included the HD SNP and all 79,254 (80K) genetic markers and QTL used in routine national genomic evaluations. Before imputation, approximately 91 to 97% of genotypes were unknown for each breed; after imputation, 1.1% of Holstein, 3.2% of Jersey, 6.7% of Brown Swiss, 4.8% of Ayrshire, and 4.2% of Guernsey alleles remained unknown due to lower density haplotypes that had no matching HD haplotype. The higher remaining missing rates in non-Holstein breeds are mainly due to fewer HD genotyped animals in the imputation reference populations. Allele effects for up to 39 traits were estimated separately within each breed using phenotypic reference populations that included up to 6,157 Jersey males and 110,130 Jersey females. Correlations of HD with 80K genomic predictions for young animals averaged 0.986, 0.989, 0.985, 0.992, and 0.978 for Jersey, Ayrshire, Brown Swiss, Guernsey, and Holstein breeds, respectively. Correlations were highest for yield traits (about 0.991) and lowest for foot angle and rear legs-side view (0.981and 0.982, respectively). Some HD effects were more than twice as large as the largest 80K SNP effect, and HD markers had larger effects than nearby 80K markers for many breed-trait combinations. Previous studies selected and included markers with large effects for Holstein traits; the newly selected HD markers should also improve non-Holstein and crossbred genomic predictions and were added to official US genomic predictions in April 2020.

Major quantitative trait loci influencing milk production and conformation traits in Guernsey dairy cattle detected on Bos taurus autosome 19.

The goal of this study was to identify potential quantitative trait loci (QTL) for 27 production, fitness, and conformation traits of Guernsey cattle through genome-wide association (GWA) analyses, with extra emphasis on BTA19, where major QTL were observed for several traits. Animals' de-regressed predicted transmitting abilities (PTA) from the December 2018 traditional US evaluation were used as phenotypes. All of the Guernsey cattle included in the QTL analyses were predictor animals in the reference population, ranging from 1,077 to 1,685 animals for different traits. Single-trait GWA analyses were carried out by a mixed-model approach for all 27 traits using imputed high-density genotypes. A major QTL was detected on BTA19, influencing several milk production traits, conformation traits, and livability of Guernsey cattle, and the most significant SNP lie in the region of 26.2 to 28.3 Mb. The myosin heavy chain 10 (MYH10) gene residing within this region was found to be highly associated with milk production and body conformation traits of dairy cattle. After the initial GWA analyses, which suggested that many significant SNP are in linkage with one another, conditional analyses were used for fine mapping. The top significant SNP on BTA19 were fixed as covariables in the model, one at a time, until no more significant SNP were detected on BTA19. After this fine-mapping approach was applied, only 1 significant SNP was detected on BTA19 for most traits, but multiple, independent significant SNP were found for protein yield, dairy form, and stature. In addition, the haplotype that hosts the major QTL on BTA19 was traced to a US Guernsey born in 1954. The haplotype is common in the breed, indicating a long-term influence of this QTL on the US Guernsey population.

Genomic prediction of residual feed intake in US Holstein dairy cattle.

Genomic selection is an important tool to introduce feed efficiency into dairy cattle breeding. The goals of the current research are to estimate genomic breeding values of residual feed intake (RFI) and to assess the prediction reliability for RFI in the US Holstein population. The RFI data were collected from 4,823 lactations of 3,947 Holstein cows in 9 research herds in the United States, and were pre-adjusted to remove phenotypic correlations with milk energy, metabolic body weight, body weight change, and for several environmental effects. In the current analyses, genomic predicted transmitting abilities of milk energy and of body weight composite were included into the RFI model to further remove the genetic correlations that remained between RFI and these energy sinks. In the first part of the analyses, a national genomic evaluation for RFI was conducted for all the Holsteins in the national database using a standard multi-step genomic evaluation method and 60,671 SNP list. In the second part of the study, a single-step genomic prediction method was applied to estimate genomic breeding values of RFI for all cows with phenotypes, 5,252 elite young bulls, 4,029 young heifers, as well as their ancestors in the pedigree, using a high-density genotype chip. Theoretical prediction reliabilities were calculated for all the studied animals in the single-step genomic prediction by direct inversion of the mixed model equations. In the results, breeding values were estimated for 1.6 million genotyped Holsteins and 60 million ungenotyped Holsteins, The genomic predicted transmitting ability correlations between RFI and other traits in the index (e.g., fertility) are generally low, indicating minor correlated responses on other index traits when selecting for RFI. Genomic prediction reliabilities for RFI averaged 34% for all phenotyped animals and 13% for all 1.6 million genotyped animals. Including genomic information increased the prediction reliabilities for RFI compared with using only pedigree information. All bulls had low reliabilities, and averaged to only 16% for the top 100 net merit progeny-tested bulls. Analyses using single-step genomic prediction and high-density genotypes gave similar results to those obtained from the national evaluation. The average theoretical reliability for RFI was 18% among the elite young bulls under 5 yr old, being lower in the younger generations of elite bulls compared with older bulls. To conclude, the size of the reference population and its relationship to the predicted population remain as the limiting factors in the genomic prediction for RFI. Continued collection of feed intake data is necessary so that reliabilities can be maintained due to close relationships of phenotyped animals with breeding stock. Considering the currently low prediction reliability and high cost of data collection, focusing RFI data collection on relatives of elite bulls that will have the greatest genetic contribution to the next generation will give more gains and profit.

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.

Short communication: Phenotypic and genetic effects of the polled haplotype on yield, longevity, and fertility in US Brown Swiss, Holstein, and Jersey cattle.

Phenotypes from the December 2018 US national genetic evaluations were used to compute effects of the polled haplotype in US Brown Swiss (BS), Holstein (HO), and Jersey (JE) cattle on milk, fat, and protein yields, somatic cell score, single-trait productive life, daughter pregnancy rate, heifer conception rate, and cow conception rate. Lactation records pre-adjusted for nongenetic factors and direct genomic values were used to estimate phenotypic and genetic effects of the polled haplotype, respectively. No phenotypic or direct genomic values effects were different from zero for any trait in any breed. Genomic PTA (gPTA) for the lifetime net merit (NM$) selection index of bulls born since January 1, 2012, that received a marketing code from the National Association of Animal Breeders (Madison, WI), and cows born on or after January 1, 2015, were compared to determine whether there was a systematic benefit to polled or horned genetics. Horned bulls had the highest average gPTA for NM$ in all 3 breeds, but that difference was significant only in HO and JE (HO: 615.4 ± 1.9, JE: 402.3 ± 3.4). Homozygous polled BS cows had significantly higher average gPTA for NM$ than their heterozygous polled or horned contemporaries (PP = 261.4 ± 43.5, Pp = 166.1 ± 13.7, pp = 174.1 ± 1.8), but the sample size was very small (n = 9). In HO and JE, horned cows had higher gPTA for NM$ (HO = 378.3 ± 0.2, JE = 283.3 ± 0.3). Selection for polled cattle should not have a detrimental effect on yield, fertility, or longevity, but these differences show that, in the short term, selection for polled over horned cattle will result in lower rates of genetic gain.

Genetic and nongenetic profiling of milk pregnancy-associated glycoproteins in Holstein cattle.

Pregnancy-associated glycoproteins (PAG) are secreted by the trophoblast and are detectable in maternal circulation around the time of attachment of the fetal placenta, as well as in blood and milk throughout gestation. The understanding of the genetic mechanisms controlling PAG levels can confer advantages for livestock breeding programs given the precocity and the ease of obtaining this phenotype from routine pregnancy diagnosis. The aim of this study was to characterize PAG levels by estimating genetic parameters and correlations with other dairy traits, and to identify genomic regions and candidate genes associated with PAG levels in milk. The PAG data consisted of pregnancy diagnoses using commercial assays from 2012 to 2017, and genotype data consisted of 54,123 SNP markers for 2,352 individuals (embryos and dams). The model included contemporary group (herd, year, and season) and embryo age as fixed effects, and random embryonic (direct) and maternal (indirect) genetic effects. Using genomic data, the estimated heritability for direct and maternal genetic effects (± standard deviations) were 0.23 ± 0.05 and 0.11 ± 0.05, respectively. The genetic correlation between these effects was almost zero (0.001 ± 0.06). A preliminary analysis revealed low correlations between milk PAG levels and other dairy traits. The genome-wide association analysis was performed using 2 approaches: single-marker and single-step using all markers. Four genomic regions with direct genetic effects were detected on Bos taurus autosome (BTA) 6, BTA7, BTA19, and BTA29 of the embryonic genome. The BTA29 locus was within the bovine PAG gene cluster, suggesting a cis-regulatory quantitative trait locus on the PAG expression. However, other associations, without an obvious link to PAG expression, could be related to the transportation of PAG and their concentration in milk. Only 1 region from the maternal genome, on BTA4, had a significant indirect effect, where WNT2 is a candidate gene related to placenta vascularization and gestation health. Collectively, our results suggest a moderate genetic control of milk PAG levels from both maternal and fetal genomes, but larger studies are needed to fully evaluate the usefulness of milk PAG in the genetic evaluation of fetal growth and cow fertility.

Genomic evaluation of age at first calving.

From their time of birth until their first lactation, dairy heifers incur management, health, and feed expenses while not producing milk. Much effort has been made to estimate optimal ages of first calving (AFC) for cows to reduce these costs, which can be as high as $2.50 per day, and ensure that animals are productive earlier in life. To identify AFC for 3 dairy cattle breeds (Holstein, Jersey, and Brown Swiss) that maximizes production, we retrieved phenotypic records for more than 14 million cows calving between 1997 and 2015 from the US national dairy database. The mean AFC for Holstein and Jersey has decreased by 2.4 and 2.7 mo, respectively, since 2006. When comparing the association of AFC with production and fertility traits, we found that decreased AFC was correlated with greater fertility and higher milk yield for all but the earliest group (18 to 20 mo). We also identified an unfavorable correlation of lower AFC with increasing stillbirth rates in Holstein (0.047 least squares means compared with a baseline of 24 mo) and Brown Swiss (0.062 least squares means). Finally, we identified favorable genetic correlations of lower AFC with lifetime net merit, heifer conception rate, cow conception rate, and daughter pregnancy rate in Holstein and Jersey cattle, and favorable correlations for net merit and heifer conception rate in Brown Swiss. To maximize lifetime production and reduce the effects of AFC on stillbirth, the AFC that maximizes production for Holstein and Brown Swiss is 21 to 22 mo, and for Jersey it is 20 to 21 mo. However, the effect of AFC on stillbirth reduces the benefits of calving at very young ages. Calculated genomic predicted transmitting ability for AFC showed an improvement in reliability of 20 percentage points in genomic young bulls compared with parent averages in Holstein, suggesting that genomic testing can improve selection for this trait.

The Larson Blue coat color phenotype in Holsteins: Characteristics and effects on body temperature regulation and production in lactating cows in a hot climate.

Here we report a previously undescribed coat color phenotype in Holstein cattle. Larson Blue Holsteins, located on a dairy in south Florida, exhibit a coloration pattern that is similar to that of black and white or red and white Holsteins except that, instead of being black or red, darker regions of the body vary in color from gray to taupe. The Larson Blue phenotype was readily apparent in young calves. The phenotype is not due to inheritance of known mutations causing coat color variation in cattle, including dominant red, Telstar, silver color dilutor, or Dun color. Three variants with moderate effects on the () gene were identified in 2 Larson blue cows. Despite being lighter in color, there was no difference in daily variation in vaginal temperature between Larson Blue and other Holsteins when recorded during the summer for cows housed in free-stall barns with shade, fans, and sprinklers. Similarly, there was no effect of the Larson Blue phenotype on seasonal variation in milk yield. Therefore, the phenotype confers no advantage in terms of response to heat stress when cattle are housed in facilities with extensive cooling.

Evaluation of genetic components in traits related to superovulation, in vitro fertilization, and embryo transfer in Holstein cattle.

The objectives of this study were to estimate variance components and identify regions of the genome associated with traits related to embryo transfer in Holsteins. Reproductive technologies are used in the dairy industry to increase the reproductive rate of superior females. A drawback of these methods remains the variability of animal responses to the procedures. If some variability can be explained genetically, selection can be used to improve animal response. Data collected from a Holstein dairy farm in Florida from 2008 to 2015 included 926 superovulation records (number of structures recovered and number of good embryos), 628 in vitro fertilization records (number of oocytes collected, number of cleaved embryos, number of high- and low-quality embryos, and number of transferrable embryos), and 12,089 embryo transfer records (pregnancy success). Two methods of transformation (logarithmic and Anscombe) were applied to count variables and results were compared. Univariate animal models were fitted for each trait with the exception of pregnancy success after embryo transfer. Due to the binary nature of the latter trait, a threshold liability model was fitted that accounted for the genetic effect of both the recipient and the embryo. Both transformation methods produced similar results. Single-step genomic BLUP analyses were performed and SNP effects estimated for traits with a significant genetic component. Heritability of number of structures recovered and number of good embryos when log-transformed were 0.27 ± 0.08 and 0.15 ± 0.07, respectively. Heritability estimates from the in vitro fertilization data ranged from 0.01 ± 0.08 to 0.21 ± 0.15, but were not significantly different from zero. Recipient and embryo heritability (standard deviation) of pregnancy success after embryo transfer was 0.03 (0.01) and 0.02 (0.01), respectively. The 10-SNP window explaining the largest proportion of variance (0.37%) for total structures collected was located on chromosome 8 beginning at 55,663,248 bp. Similar regions were identified for number of good embryos, with the largest proportion of variance (0.43%) explained by a 10-SNP window on chromosome 14 beginning at 26,713,734 bp. Results indicate that there is a genetic component for some traits related to superovulation and that selection should be possible. Moreover, the genetic component for superovulation traits involves some genomic regions that are similar to those for other fertility traits currently evaluated.

Phenotypic and genetic effects of recessive haplotypes on yield, longevity, and fertility.

Phenotypes from the August 2015 US national genetic evaluation were used to compute phenotypic effects of 18 recessive haplotypes in Ayrshire (n=1), Brown Swiss (n=5), Holstein (n=10), and Jersey (n=2) cattle on milk, fat, and protein yields, somatic cell score (SCS), single-trait productive life (PL), daughter pregnancy rate (DPR), heifer conception rate (HCR), and cow conception rate (CCR). The haplotypes evaluated were Ayrshire haplotype 1, Brown Swiss haplotypes 1 and 2, spinal dysmyelination, spinal muscular atrophy, Weaver Syndrome, brachyspina, Holstein cholesterol deficiency, Holstein haplotypes 1 to 5, bovine leukocyte adhesion deficiency, complex vertebral malformation, mulefoot (syndactyly), and Jersey haplotypes 1 and 2. When causal variants are unknown and tests are based only on single nucleotide polymorphism haplotypes, it can sometimes be difficult to accurately determine carrier status. For example, 2 Holstein haplotypes for cholesterol deficiency have the same single nucleotide polymorphism genotype, but only one of them carries the causative mutation. Genotyped daughters of carrier bulls included in the analysis ranged from 8 for Weaver Syndrome to 17,869 for Holstein haplotype 3. Lactation records preadjusted for nongenetic factors and direct genomic values (DGV) were used to estimate phenotypic and genetic effects of recessive haplotypes, respectively. We found no phenotypic or genetic differences between carriers and noncarriers of Ayrshire or Brown Swiss defects. Several associations were noted for Holstein haplotypes, including fat and HCR for Holstein haplotype 0 carriers; milk, protein, SCS, PL, and fertility for Holstein haplotype 1; protein, PL, CCR, and HCR for Holstein haplotype 2; milk, protein, and fertility for Holstein haplotype 4; and protein yield and DPR for Holstein haplotype 5. There were no differences among bovine leukocyte adhesion deficiency carriers, but complex vertebral malformation affected fat yield and mulefoot carriers had higher SCS and lower PL DGV. Jersey haplotype 1 was not associated with any phenotypic effects, but we noted significant differences among DGV for fat, protein, PL, DPR, CCR, and HCR. Jersey haplotype 2 was associated only with lower phenotypic CCR. Effects of the recessive haplotypes on other traits studied generally were small even when significant. Almost $11 million of economic losses per year due to reduced fertility and perinatal calf death in the US population can be avoided by selecting mate pairs that will not produce affected embryos. Carrier animals may continue to be selected if the merit of their favorable alleles exceeds the loss from their recessive alleles, but carrier bulls can be generally avoided without reducing the average genetic merit of the sires available for mating.

Explorations in genome-wide association studies and network analyses with dairy cattle fertility traits.

The objective of this study was to identify single nucleotide polymorphisms and gene networks associated with 3 fertility traits in dairy cattle-daughter pregnancy rate, heifer conception rate, and cow conception rate-using different approaches. Deregressed predicted transmitting abilities were available for approximately 24,000 Holstein bulls and 36,000 Holstein cows sampled from the National Dairy Database with high-density genotypes. Of those, 1,732 bulls and 375 cows had been genotyped with the Illumina BovineHD Genotyping BeadChip (Illumina Inc., San Diego, CA). The remaining animals were genotyped with various chips of lower density that were imputed to high density. Univariate and trivariate genome-wide association studies (GWAS) with both medium- (60,671 markers) and high-density (312,614 markers) panels were performed for daughter pregnancy rate, heifer conception rate, and cow conception rate using GEMMA (version 0.94; http://www.xzlab.org/software.html). Analyses were conducted using bulls only, cows only, and a sample of both bulls and cows. The partial correlation and information theory algorithm was used to develop gene interaction networks. The most significant markers were further investigated to identify putatively associated genes. Little overlap in associated genes could be found between GWAS using different reference populations of bulls only, cows only, and combined bulls and cows. The partial correlation and information theory algorithm was able to identify several genes that were not identified by ordinary GWAS. The results obtained herein will aid in further dissecting the complex biology underlying fertility traits in dairy cattle, while also providing insight into the nuances of GWAS.

Reducing animal sequencing redundancy by preferentially selecting animals with low-frequency haplotypes.

Many studies leverage targeted whole-genome sequencing (WGS) experiments to identify rare and causal variants within populations. As a natural consequence of their experimental design, many of these surveys tend to sequence redundant haplotype segments due to their high frequency in the base population, and the variants discovered within sequencing data are difficult to phase. We propose a new algorithm, called inverse weight selection (IWS), that preferentially selects individuals based on the cumulative presence of rare frequency haplotypes to maximize the efficiency of WGS surveys. To test the efficacy of this method, we used genotype data from 112,113 registered Holstein bulls derived from the US national dairy database. We demonstrate that IWS is at least 6.8% more efficient than previously published methods in selecting the least number of individuals required to sequence all haplotype segments ≥4% frequency in the US Holstein population. We also suggest that future surveys focus on sequencing homozygous haplotype segments as a first pass to achieve a 50% reduction in cost with an added benefit of phasing variant calls efficiently. Together, this new selection algorithm and experimental design suggestion significantly reduce the overall cost of variant discovery through WGS experiments, making surveys for causal variants influencing disease and production even more efficient.

Use of single nucleotide polymorphisms in candidate genes associated with daughter pregnancy rate for prediction of genetic merit for reproduction in Holstein cows.

We evaluated 69 SNPs in genes previously related to fertility and production traits for their relationship to daughter pregnancy rate (DPR), cow conception rate (CCR) and heifer conception rate (HCR) in a separate population of Holstein cows grouped according to their predicted transmitting ability (PTA) [≤-1 (n = 1287) and ≥1.5 (n = 1036)] for DPR. Genotyping was performed using Sequenom MassARRAY(®) . There were a total of 39 SNPs associated with the three fertility traits. The SNPs that explained the greater proportion of the genetic variation for DPR were COQ9 (3.2%), EPAS1 (1.0%), CAST (1.0%), C7H19orf60 (1.0%) and MRPL48 (1.0%); for CCR were GOLGA4 (2.4%), COQ9 (1.8%), EPAS1 (1.1%) and MRPL48 (0.8%); and for HCR were HSD17B7 (1.0%), AP3B1 (0.8%), HSD17B12 (0.7%) and CACNA1D (0.6%). Inclusion of 39 SNPs previously associated with DPR in the genetic evaluation system increased the reliability of PTA for DPR by 0.20%. Many of the genes represented by SNPs associated with fertility are involved in steroidogenesis or are regulated by steroids. A large proportion of SNPs previously associated with genetic merit for fertility in Holstein bulls maintained their association in a separate population of cows. The inclusion of these genes in genetic evaluation can improve reliabilities of genomic estimates for fertility.

Single nucleotide polymorphisms associated with thermoregulation in lactating dairy cows exposed to heat stress.

Dairy cows with increased rectal temperature experience lower milk yield and fertility. Rectal temperature during heat stress is heritable, so genetic selection for body temperature regulation could reduce effects of heat stress on production. One aim of the study was to validate the relationship between genotype and heat tolerance for single nucleotide polymorphisms (SNPs) previously associated with resistance to heat stress. A second aim was to identify new SNPs associated with heat stress resistance. Thermotolerance was assessed in lactating Holsteins during the summer by measuring rectal temperature (a direct measurement of body temperature regulation; n = 435), respiration rate (an indirect measurement of body temperature regulation, n = 450) and sweating rate (the major evaporative cooling mechanism in cattle, n = 455). The association between genotype and thermotolerance was evaluated for 19 SNPs previously associated with rectal temperature from a genomewide analysis study (GWAS), four SNPs previously associated with change in milk yield during heat stress from GWAS, 2 candidate gene SNPs previously associated with rectal temperature and respiration rate during heat stress (ATPA1A and HSP70A) and 66 SNPs in genes previously shown to be associated with reproduction, production or health traits in Holsteins. For SNPs previously associated with heat tolerance, regions of BTA4, BTA6 and BTA24 were associated with rectal temperature; regions of BTA6 and BTA24 were associated with respiration rate; and regions of BTA5, BTA26 and BTA29 were associated with sweating rate. New SNPs were identified for rectal temperature (n = 12), respiration rate (n = 8) and sweating rate (n = 3) from among those previously associated with production, reproduction or health traits. The SNP that explained the most variation were PGR and ASL for rectal temperature, ACAT2 and HSD17B7 for respiration rate, and ARL6IP1 and SERPINE2 for sweating rate. ARL6IP1 was associated with all three thermotolerance traits. In conclusion, specific genetic markers responsible for genetic variation in thermoregulation during heat stress in Holsteins were identified. These markers may prove useful in genetic selection for heat tolerance in Holstein cattle.

Dissection of genomic correlation matrices of US Holsteins using multivariate factor analysis.

The aim of this study was to compare correlation matrices between direct genomic predictions for 31 traits at the genomic and chromosomal levels in US Holstein bulls. Multivariate factor analysis carried out at the genome level identified seven factors associated with conformation, longevity, yield, feet and legs, fat and protein content traits. Some differences were found at the chromosome level; variations in covariance structure on BTA 6, 14, 18 and 20 were interpreted as evidence of segregating QTL for different groups of traits. For example, milk yield and composition tended to join in a single factor on BTA 14, which is known to harbour the DGAT1 locus that affects these traits. Another example was on BTA 18, where a factor strongly correlated with sire calving ease and conformation traits was identified. It is known that in US Holstein, there is a segregating QTL on BTA18 influencing these traits. Moreover, a possible candidate gene for daughter pregnancy rate was suggested for BTA28. The methodology proposed in this study could be used to identify individual chromosomes, which have covariance structures that differ from the overall (whole genome) covariance structure. Such differences can be difficult to detect when a large number of traits are evaluated, and covariances may be affected by QTL that do not have large allele substitution effects.

Genomic evaluation, breed identification, and discovery of a haplotype affecting fertility for Ayrshire dairy cattle.

Genomic evaluations of dairy cattle in the United States have been available for Brown Swiss, Holsteins, and Jerseys since 2009. As of January 2013, 1,023 Ayrshires had genotypes in the North American database. Evaluation accuracy was assessed using genomic evaluations based on 646 bulls with 2008 traditional evaluations to predict daughter performance of up to 180 bulls in 2012. Mean gain in reliability over parent average for all traits was 8.2 percentage points. The highest gains were for protein yield (16.9 percentage points), milk yield (16.6 percentage points), and stature (16.2 percentage points). Twelve single nucleotide polymorphisms were useful for Ayrshire breed determination. Fewer breed-determining SNP were available for Ayrshires than for Holsteins, Jerseys, and Brown Swiss because of the similarity of Ayrshires and Holsteins. A haplotype that affects fertility was identified on chromosome 17 and traces back in the genotyped population to the bull Selwood Betty's Commander (born in 1953). The haplotype carrier frequency for genotyped Ayrshires was 26.1%. Sire conception rate was decreased by 4.3 ± 2.5 percentage points for carriers of the haplotype as determined by 618 matings of carrier sire by carrier maternal grandsire. Genomic evaluations for Ayrshires were officially implemented in the United States in April 2013.

Visualization of the transmission of direct genomic values for paternal and maternal chromosomes for 15 traits in US Brown Swiss, Holstein, and Jersey cattle.

Haplotypes are available for 220,671 Brown Swiss, Holstein, and Jersey bulls and cows that received genomic evaluations in August 2012. Differences in least squares means of direct genomic values (DGV) for paternal and maternal haplotypes of Bos taurus autosomes 1, 6, 14, and 18 for lifetime net merit were significant in all but one case. Those chromosomes were chosen to represent cases with and without known quantitative trait loci, and other chromosomes may differ as well. Paternal haplotypes had higher DGV than maternal haplotypes in most cases, and differences were larger when quantitative trait loci were present. Longer chromosomes generally accounted for more variance than shorter chromosomes, and differences among breeds were consistent with known mutations of large effect. For example, Bos taurus autosome 18 accounted for 2.5, 7, and 2.6% of the variance in lifetime net merit for Brown Swiss (BS), Holsteins, and Jerseys, respectively. Distributions of the number of positive DGV inherited from sires and dams were negatively skewed in all breeds, and modes were slightly higher for paternally than maternally derived haplotypes in Holsteins and BS (22 vs. 20 and 22 vs. 21, respectively) and slightly lower in BS (17 vs. 19). Graphical representations of DGV are available to all users through a query on the Animal Improvement Programs Laboratory (ARS, USDA, Beltsville, MD) web site. Query results were also used to illustrate several quantitative genetic principles using genotype information from real animals. For example, offspring DGV can be compared with parental DGV to demonstrate that a parent transmits the average value of its 2 chromosomes to its progeny. The frequency of DGV with positive and negative values in animals of different ages can be used to show how selection affects allele frequencies. The effect of selection for alleles with large effects versus those with small effects is demonstrated using an animal with undesirable alleles for a marker with a large effect but many desirable alleles for markers with small effects. Strategies for the use of those data in selection programs are being studied, and work is underway to add data on conformation traits to the system.