Short communication: Validation of somatic cell score–associated loci identified in a genome-wide association study in German Holstein cattle

Recently, we identified 6 genomic loci affecting daughter yield deviations (DYD) for somatic cell score (SCS) in a genome-wide association study (GWAS) performed with German Holstein bulls. In the current study, we tested if these loci were associated with SCS in cows using their own performance data. The study was performed with 1,412 German Holstein cows, of which 483 were daughters of 71 bulls that had been used in the GWAS. We tested 10 single nucleotide polymorphisms (SNP) representing 6 genomic regions that were associated with DYD for SCS in bulls. All tested SNP were significant in cows. Seven of them, located on Bos taurus autosomes (BTA) 6, 13, and 19, had the same direction of effect as those previously reported in the bull population. The most significant associations were detected on BTA6 and BTA19, accounting for 1.8% of the total genetic variance. The major allele of the 2 SNP on BTA6 and the minor allele of the 2 SNP on BTA19 were favorable for lower SCS. The differences between the homozygous genotype classes were up to 15,000 cells/mL. The verification of SNP associated with SCS in this study provides further evidence for the functional role of the linked genomic regions for immune response and contributes to identification of causative mutations. In particular, SNP with minor frequency of the favorable allele possess high potential to reduce SCS in German Holstein cattle by selection.     

Genome-wide association study of normal and atypical progesterone profiles in Holstein-Friesian dairy cows

Female fertility has a major role in dairy production and affects the profitability of dairy cattle. The genetic progress obtained by traditional selection can be slow because of the low heritability of classical fertility traits. Endocrine fertility traits based on progesterone concentration in milk have higher heritability and more directly reflect the cow's own reproductive physiology. The aim of our study was to identify genomic regions for 7 endocrine fertility traits in dairy cows by performing a genome-wide association study with 54,000 SNP. The next step was to fine-map targeted genomic regions with significant SNP using imputed sequences to identify potential candidate genes associated with the normal and atypical progesterone profiles. The association between a SNP and a phenotype was assessed by a single SNP analysis, using a linear mixed model that included a random polygenic effect. Phenotypes and genotypes were available for 1,126 primiparous and multiparous Holstein-Friesian cows from research herds in Ireland, the Netherlands, Sweden, and the United Kingdom. In total, 44 significant SNP associated with 7 endocrine fertility traits were identified on Bos taurus autosome (BTA) 1–4, 6, 8–9, 11–12, 14–17, 19, 21–24, and 29. Three chromosomes, BTA8, BTA17, and BTA23, were imputed from 54,000 SNP genotypes to the whole-genome sequence level with Beagle version 4.1. The fine-mapping identified several significant associations with delayed cyclicity, cessation of cyclicity, commencement of luteal activity, and inter-ovulatory interval. These associations may contribute to an index of markers for genetic improvement of fertility. Several potential candidate genes reported to affect reproduction were also identified in the targeted genomic regions. However, due to high linkage disequilibrium, it was not possible to identify putative causal genes or polymorphisms for any of the regions.     

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.     

Genome-wide association study identifies loci influencing natural antibody titers in milk of Dutch Holstein-Friesian cattle

Natural antibodies (NAb) are produced without any antigenic stimulation as a part of the innate immune system and provide a first line of defense against pathogens. Hence, they may be a useful trait when estimating an animal's potential immune competence and in selection for disease resistance. The aim of this study was to identify genomic regions associated with different NAb traits in milk and potentially describe candidate genes. Milk samples from 1,695 first-lactation Holstein Friesian cows with titer measurements for keyhole limpet hemocyanin, lipopolysaccharide, lipoteichoic acid, and peptidoglycan-binding total NAb and isotypes IgG₁, IgM, and IgA were used. Genome-wide association study analyses were performed using imputed 777K SNP genotypes, accounting for relationships using pedigree information. Functional enrichment analysis was performed on the significantly associated genomic regions to look for candidate genes. For IgM NAb, significant associations (false discovery rate <0.05) were found on Bos taurus autosome (BTA) 17, 18, and 21 with candidate genes related to immunoglobulin structure and early B cell development. For IgG₁, associations were found on BTA3, and we confirmed a quantitative trait loci on BTA21 previously reported for IgG NAb in serum. Our results provide new insights into the regulation of milk NAb that will help unravel the complex relationship between milk immunoglobulins and disease resistance in dairy cattle.     

Genomic analyses and biological validation of candidate genes for rectal temperature as an indicator of heat stress in Holstein cattle

Heat stress is a major cause of welfare issues and economic losses to the worldwide dairy cattle industry. Genetic selection for heat tolerance has a great potential to positively affect the dairy industry, as the gains are permanent and cumulative over generations. Rectal temperature (RT) is hypothesized to be a good indicator trait of heat tolerance. Therefore, this study investigated the genetic architecture of RT by estimating genetic parameters, performing genome-wide association studies, and biologically validating potential candidate genes identified to be related to RT in Holstein cattle. A total of 33,013 RT records from 7,598 cows were used in this study. In addition, 1,114 cows were genotyped using the Illumina 150K Bovine BeadChip (Illumina, San Diego, CA). Rectal temperature measurements taken in the morning (AMRT) and in the afternoon (PMRT) are moderately heritable traits, with estimates of 0.09 ± 0.02 and 0.04 ± 0.01, respectively. These 2 traits are also highly genetically correlated (r = 0.90 ± 0.08). A total of 10 SNPs (located on BTA3, BTA4, BTA8, BTA13, BTA14, and BTA29) were found to be significantly associated with AMRT and PMRT. Subsequently, gene expression analyses were performed to validate the key functional genes identified (SPAG17, FAM107B, TSNARE1, RALYL, and PHRF1). This was done through in vitro exposure of peripheral blood mononuclear cells (PBMC) to different temperatures (37°C, 39°C, and 42°C). The relative mRNA expression of 2 genes, FAM107B and PHRF1, significantly changed between the control and heat stressed PBMC. In summary, RT is heritable, and enough genetic variability exists to enable genetic improvement of heat tolerance in Holstein cattle. Important genomic regions were identified and biologically validated; FAM107B and PHRF1 are the main candidate genes identified to influence heat stress response in dairy 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.     

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.     

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.     

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.     

Genome-wide association study for milk production traits in a Brazilian Holstein population

Advances in the molecular area of selection have expanded knowledge of the genetic architecture of complex traits through genome-wide association studies (GWAS). Several GWAS have been performed so far, but confirming these results is not always possible due to several factors, including environmental conditions. Thus, our objective was to identify genomic regions associated with traditional milk production traits, including milk yield, somatic cell score, fat, protein and lactose percentages, and fatty acid composition in a Holstein cattle population producing under tropical conditions. For this, 75,228 phenotypic records from 5,981 cows and genotypic data of 56,256 SNP from 1,067 cows were used in a weighted single-step GWAS. A total of 46 windows of 10 SNP explaining more than 1% of the genetic variance across 10 Bos taurus autosomes (BTA) harbored well-known and novel genes. The MGST1 (BTA5), ABCG2 (BTA6), DGAT1 (BTA14), and PAEP (BTA11) genes were confirmed within some of the regions identified in our study. Potential novel genes involved in tissue damage and repair of the mammary gland (COL18A1), immune response (LTTC19), glucose homeostasis (SLC37A1), synthesis of unsaturated fatty acids (LTBP1), and sugar transport (SLC37A1 and MFSD4A) were found for milk yield, somatic cell score, fat percentage, and fatty acid composition. Our findings may assist genomic selection by using these regions to design a customized SNP array to improve milk production traits on farms with similar environmental conditions.     

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.     

Association of lipid-related genes implicated in conceptus elongation with female fertility traits in dairy cattle

Elongation of the preimplantation conceptus is a requirement for pregnancy success in ruminants, and failures in this process are highly associated with subfertility in dairy cattle. Identifying genetic markers that are related to early conceptus development and survival and utilizing these markers in selective breeding can improve the reproductive efficiency of dairy herds. Here, we evaluated the association of 1,679 SNP markers within or close to 183 candidate genes involved in lipid metabolism of the elongating conceptus with different fertility traits in US Holstein cattle. A total of 27,371 bulls with predicted transmitting ability records for daughter pregnancy rate, cow conception rate, and heifer conception rate were used as the discovery population. The associations found in the discovery population were validated using 2 female populations (1,122 heifers and 2,138 lactating cows) each with 4 fertility traits, including success to first insemination, number of services per conception, age at first conception for heifers, or days open for cows. Marker effects were estimated using a linear mixed model with SNP genotype as a linear covariate and a random polygenic effect. After multiple testing correction, 39 SNP flagging 27 candidate genes were associated with at least one fertility trait in the discovery population. Of these 39 markers, 3 SNP were validated in the heifer population and 4 SNP were validated in the cow population. The 3 SNP validated in heifers are located within or near genes CAT, MYOF, and RBP4, and the 4 SNP validated in lactating cows are located within or close to genes CHKA, GNAI1, and HMOX2. These validated genes seem to be relevant for reducing pregnancy losses, and the SNP within these genes are excellent candidates for inclusion in genomic tests to improve reproductive performance in dairy cattle.     

Genome-wide association analysis for susceptibility to infection by Mycobacterium avium ssp. paratuberculosis in US Holsteins

Paratuberculosis, or Johne's disease, is a chronic, granulomatous, gastrointestinal tract disease of cattle and other ruminants caused by the bacterium Mycobacterium avium subspecies paratuberculosis (MAP). Control of Johne's disease is based on programs of testing and culling animals positive for infection with MAP and concurrently modifying management to reduce the likelihood of infection. The current study was motivated by the hypothesis that genetic variation in host susceptibility to MAP infection can be dissected and quantifiable associations with genetic markers identified. Two separate GWAS analyses were conducted, the first using 897 genotyped Holstein artificial insemination sires with phenotypes derived from incidence of MAP infection among daughters based on milk ELISA testing records. The second GWAS analysis was a case-control design using US Holstein cows phenotyped for MAP infection by serum ELISA or fecal culture tests. Cases included cows positive for either serum ELISA, fecal culture, or both. Controls consisted of animals negative for all tests conducted. A total of 376 samples (70 cases and 306 controls) from a University of Minnesota Johne's management demonstration project and 184 samples (76 cases and 108 controls) from a Michigan State University study were used. Medium-density (sires) and high-density (cows) genotype data were imputed to full genome sequence for the analyses. Marker-trait associations were analyzed using the single-step (ss)GWAS procedure implemented in the BLUPF90 suite of programs. Evidence of significant genomic contributions for susceptibility to MAP infection were observed on multiple chromosomes. Results were combined across studies in a meta-analysis, and increased support for genomic regions on BTA7 and BTA21 were observed. Gene set enrichment analysis suggested pathways for antigen processing and presentation, antimicrobial peptides and natural killer cell–mediated cytotoxicity are relevant to variation in host susceptibility to MAP infection, among others. Genomic prediction was evaluated using a 5-fold cross-validation, and moderate correlations were observed between genomic breeding value predictions and daughter averages (～0.43 to 0.53) for MAP infection in testing data sets. These results suggest that genomic selection against susceptibility to MAP infection is feasible in Holstein cattle.     

On the genomic regions associated with milk lactose in Fleckvieh cattle

Lactose is a sugar uniquely found in mammals' milk and it is the major milk solid in bovines. Lactose yield (LY, kg/d) is responsible for milk volume, whereas lactose percentage (LP) is thought to be more related to epithelial integrity and thus to udder health. There is a paucity of studies that have investigated lactose at the genomic level in dairy cows. This paper aimed to improve our knowledge on LP and LY, providing new insights into the significant genomic regions affecting these traits. A genome-wide association study for LP and LY was carried out in Fleckvieh cattle by using bulls' deregressed estimated breeding values of first lactation as pseudo-phenotypes. Heritabilities of first-lactation test-day LP and LY estimated using linear animal models were 0.38 and 0.25, respectively. A total of 2,854 bulls genotyped with a 54K SNP chip were available for the genome-wide association study; a linear mixed model approach was adopted for the analysis. The significant SNP of LP were scattered across the whole genome, with signals on chromosomes 1, 2, 3, 7, 12, 16, 18, 19, 20, 28, and 29; the top 4 significant SNP explained 4.90% of the LP genetic variance. The signals were mostly in regions or genes with involvement in molecular intra- or extracellular transport; for example, CDH5, RASGEF1C, ABCA6, and SLC35F3. A significant region within chromosome 20 was previously shown to affect mastitis or somatic cell score in cattle. As regards LY, the significant SNP were concentrated in fewer regions (chromosomes 6 and 14), related to mastitis/somatic cell score, immune response, and transport mechanisms. The 5 most significant SNP for LY explained 8.45% of genetic variance and more than one-quarter of this value has to be attributed to the variant within ADGRB1. Significant peaks in target regions remained even after adjustment for the 2 most significant variants previously detected on BTA6 and BTA14. The present study is a prelude for deeper investigations into the biological role of lactose for milk secretion and volume determination, stressing the connection with genes regulating intra- or extracellular trafficking and immune and inflammatory responses in dairy cows. Also, these results improve the knowledge on the relationship between lactose and udder health; they support the idea that LP and its derived traits are potential candidates as indicators of udder health in breeding programs aimed to enhance cows' resistance to mastitis.     

Genome-wide association study with imputed whole-genome sequence variants including large deletions for female fertility in 3 Nordic dairy cattle breeds

Fertility is an economically important trait in livestock. Poor fertility in dairy cattle can be due to loss-of-function variants affecting any essential gene that causes early embryonic mortality in homozygotes. To identify fertility-associated quantitative trait loci, we performed single-marker association analyses for 8 fertility traits in Holstein, Jersey, and Nordic Red Dairy cattle using imputed whole-genome sequence variants including SNPs, indels, and large deletion. We then performed stepwise selection of independent markers from GWAS loci using conditional and joint association analyses. From single-marker analyses for fertility traits, we reported genome-wide significant associations of 30,384 SNPs, 178 indels, and 3 deletions in Holstein; 23,481 SNPs, 189 indels, and 13 deletions in Nordic Red; and 17 SNPs in Jersey cattle. Conditional and joint association analyses identified 37 and 23 independent associations in Holstein and Nordic Red Dairy cattle, respectively. Fertility-associated GWAS loci were enriched for developmental and cellular processes (Gene Ontology enrichment, false discovery rate < 0.05). For these quantitative trait loci regions (top marker and 500 kb of surrounding regions), we proposed several candidate genes with functional annotations corresponding to embryonic lethality and various fertility-related phenotypes in mouse and cattle. The inclusion of these top markers in future releases of the custom SNP chip used for genomic evaluations will enable their validation in independent populations and improve the accuracy of genomic predictions.     

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.     

Short communication: quantitative trait loci affecting the somatic cell score on chromosomes 4 and 26 in Italian Holstein cattle

This work aimed to confirm previously reported quantitative trait loci (QTL) affecting the somatic cell score (SCS) in dairy cattle on Bos taurus autosomes (BTA) 4 and 26. A granddaughter design with selective genotyping was implemented that included half-sib families from 12 male lines of Italian Holstein cattle. The animals were genotyped for 5 microsatellite markers each on regions of BTA 4 (average marker spacing 9.42 cM) and BTA 26 (average marker spacing 5.26 cM), previously reported by other authors as carrying QTL for somatic cell count. Quantitative trait loci analyses were performed using interval mapping by regressing sire breeding values for SCS onto genotype probabilities at 1-cM intervals along the 2 chromosome regions. Breeding values for SCS were estimated for the whole population using a test-day repeatability animal model. Results were not significant on a chromosome basis, but a possible QTL was found at BM4505 on BTA 26, confirming this region for further studies of QTL affecting SCS in the Italian Holstein population.     

Random Forests approach for identifying additive and epistatic single nucleotide polymorphisms associated with residual feed intake in dairy cattle

Feed efficiency is an economically important trait in the beef and dairy cattle industries. Residual feed intake (RFI) is a measure of partial efficiency that is independent of production level per unit of body weight. The objective of this study was to identify significant associations between single nucleotide polymorphism (SNP) markers and RFI in dairy cattle using the Random Forests (RF) algorithm. Genomic data included 42,275 SNP genotypes for 395 Holstein cows, whereas phenotypic measurements were daily RFI from 50 to 150 d postpartum. Residual feed intake was defined as the difference between an animal’s feed intake and the average intake of its cohort, after adjustment for year and season of calving, year and season of measurement, age at calving nested within parity, days in milk, milk yield, body weight, and body weight change. Random Forests is a widely used machine-learning algorithm that has been applied to classification and regression problems. By analyzing the tree structures produced within RF, the 25 most frequent pairwise SNP interactions were reported as possible epistatic interactions. The importance scores that are generated by RF take into account both main effects of variables and interactions between variables, and the most negative value of all importance scores can be used as the cutoff level for declaring SNP effects as significant. Ranking by importance scores, 188 SNP surpassed the threshold, among which 38 SNP were mapped to RFI quantitative trait loci (QTL) regions reported in a previous study in beef cattle, and 2 SNP were also detected by a genome-wide association study in beef cattle. The ratio of number of SNP located in RFI QTL to the total number of SNP in the top 188 SNP chosen by RF was significantly higher than in all 42,275 whole-genome markers. Pathway analysis indicated that many of the top 188 SNP are in genomic regions that contain annotated genes with biological functions that may influence RFI. Frequently occurring ancestor-descendant SNP pairs can be explored as possible epistatic effects for further study. The importance scores generated by RF can be used effectively to identify large additive or epistatic SNP and informative QTL. The consistency in results of our study and previous studies in beef cattle indicates that the genetic architecture of RFI in dairy cattle might be similar to that of beef cattle.     

Genome-wide association study and functional analyses for clinical and subclinical ketosis in Holstein cattle

Ketosis is one of the most frequent metabolic diseases in high-yielding dairy cows and is characterized by high concentrations of ketone bodies in blood, urine, and milk, causing high economic losses. The search for polymorphic genes, whose alleles have different effects on resistance to developing the disease, is of extreme importance to help select less susceptible animals. The aims of this study were to identify genomic regions associated with clinical and subclinical ketosis (β-hydroxybutyrate concentration) in North American Holstein dairy cattle and to investigate these regions to identify candidate genes and metabolic pathways associated with these traits. To achieve this, a GWAS was performed for 4 traits: clinical ketosis lactation 1, clinical ketosis lactation 2 to 5, subclinical ketosis lactation 1, and subclinical ketosis lactation 2 to 5. The estimated breeding values from 77,277 cows and 7,704 bulls were deregressed and used as pseudophenotypes in the GWAS. The top-20 genomic regions explaining the largest proportion of the genetic variance were investigated for putative genes associated with the traits through functional analyses. Regions of interest were identified on chromosomes 2, 5, and 6 for clinical ketosis lactation 1; 3, 6, and 7 for clinical ketosis lactation 2 to 5; 1, 2, and 12 for subclinical ketosis lactation 1; and 20, 11, and 25 for subclinical ketosis lactation 2 to 5. The highlighted genes potentially related to clinical and subclinical ketosis included ACAT2 and IGF1. Enrichment analysis of the list of candidate genes for clinical and subclinical ketosis showed molecular functions and biological processes involved in fatty acid metabolism, lipid metabolism, and inflammatory response in dairy cattle. Several genomic regions and SNPs related to susceptibility to ketosis in dairy cattle that were previously described in other studies were confirmed. The novel genomic regions identified in this study aid to characterize the most important genes and pathways that explain the susceptibility to clinical and subclinical ketosis in dairy cattle.     

Whole-genome association study for milk protein composition in dairy cattle

Our objective was to perform a genome-wide association study for content in bovine milk of α_S1-casein (α_S1-CN), α_S2-casein (α_S2-CN), β-casein (β-CN), κ-casein (κ-CN), α-lactalbumin (α-LA), β-lactoglobulin (β-LG), casein index, protein percentage, and protein yield using a 50K single nucleotide polymorphism (SNP) chip. In total, 1,713 Dutch Holstein-Friesian cows were genotyped for 50,228 SNP and a 2-step association study was performed. The first step involved a general linear model and the second step used a mixed model accounting for all family relationships. Associations with milk protein content and composition were detected on 20 bovine autosomes. The main genomic regions associated with milk protein composition or protein percentage were found on chromosomes 5, 6, 11, and 14. The number of chromosomal regions showing significant (false discovery rate <0.01) effects ranged from 3 for β-CN and 3 for β-LG to 12 for α_S2-CN. A genomic region on Bos taurus autosome (BTA) 6 was significantly associated with all 6 major milk proteins, and a genomic region on BTA 11 was significantly associated with the 4 caseins and β-LG. In addition, regions were detected that only showed a significant effect on one of the milk protein fractions: regions on BTA 13 and 22 with effects on α_S1-CN; regions on BTA 1, 9, 10, 17, 19, and 28 with effects on α_S2-CN; a region on BTA 6 with an effect on β-CN; regions on BTA 13 and 21 with effects on κ-CN; regions on BTA 1, 5, 9, 16, 17, and 26 with effects on α-LA; and a region on BTA 24 with an effect on β-LG. The proportion of genetic variance explained by the SNP showing the strongest association in each of these genomic regions ranged from <1% for α_S1-CN on BTA 22 to almost 100% for casein index on BTA 11. Variation associated with regions on BTA 6, 11, and 14 could in large part but not completely be explained by known protein variants of β-CN (BTA 6), κ-CN (BTA 6), and β-LG (BTA 11) or DGAT1 variants (BTA 14). Our results indicate 3 regions with major effects on milk protein composition, in addition to several regions with smaller effects involved in the regulation of milk protein composition.