Genome-wide association study for milk production and conformation traits in Canadian Alpine and Saanen dairy goats

Increasing the productivity of Canadian dairy goats is critical to the competitiveness of the sector; however, little is known about the underlying genetic architecture of economically important traits in these populations. Consequently, the objectives of this study were as follows: (1) to perform a single-step GWAS for milk production traits (milk, protein, and fat yields, and protein and fat percentages in first and later lactations) and conformation traits (body capacity, dairy character, feet and legs, fore udder, general appearance, rear udder, suspensory ligament, and teats) in the Canadian Alpine and Saanen breeds; and (2) to identify positional and functional candidate genes related to these traits. The data available for analysis included 305-d milk production records for 6,409 Alpine and 3,434 Saanen does in first lactation and 5,827 Alpine and 2,632 Saanen does in later lactations; as well as linear type conformation records for 5,158 Alpine and 2,342 Saanen does. Genotypes were available for 833 Alpine and 874 Saanen animals. Both single-breed and multiple-breed GWAS were performed using single-trait animal models. Positional and functional candidate genes were then identified in downstream analyses. The GWAS identified 189 unique SNP that were significant at the chromosomal level, corresponding to 271 unique positional candidate genes within 50 kb up- and downstream, across breeds and traits. This study provides evidence for the economic importance of several candidate genes (e.g., CSN1S1, CSN2, CSN1S2, CSN3, DGAT1, and ZNF16) in the Canadian Alpine and Saanen populations that have been previously reported in other dairy goat populations. Moreover, several novel positional and functional candidate genes (e.g., RPL8, DCK, and MOB1B) were also identified. Overall, the results of this study have provided greater insight into the genetic architecture of milk production and conformation traits in the Canadian Alpine and Saanen populations. Greater understanding of these traits will help to improve dairy goat breeding programs.     

Genome-wide association studies to identify quantitative trait loci affecting milk production traits in water buffalo

Water buffalo is the second largest resource of milk supply around the world, and it is well known for its distinctive milk quality in terms of fat, protein, lactose, vitamin, and mineral contents. Understanding the genetic architecture of milk production traits is important for future improvement by the buffalo breeding industry. The advance of genome-wide association studies (GWAS) provides an opportunity to identify potential genetic variants affecting important economical traits. In the present study, GWAS was performed for 489 buffaloes with 1,424 lactation records using the 90K Affymetrix Buffalo SNP Array (Affymetrix/Thermo Fisher Scientific, Santa Clara, CA). Collectively, 4 candidate single nucleotide polymorphisms (SNP) in 2 genomic regions were found to associate with buffalo milk production traits. One region affecting milk fat and protein percentage was located on the equivalent of Bos taurus autosome (BTA)3, spanning 43.3 to 43.8 Mb, which harbored the most likely candidate genes MFSD14A, SLC35A3, and PALMD. The other region on the equivalent of BTA14 at 66.5 to 67.0 Mb contained candidate genes RGS22 and VPS13B and influenced buffalo total milk yield, fat yield, and protein yield. Interestingly, both of the regions were reported to have quantitative trait loci affecting milk performance in dairy cattle. Furthermore, we suggest that buffaloes with the C allele at AX-85148558 and AX-85073877 loci and the G allele at AX-85106096 locus can be selected to improve milk fat yield in this buffalo-breeding program. Meanwhile, the G allele at AX-85063131 locus can be used as the favorable allele for improving milk protein percentage. Genomic prediction showed that the reliability of genomic estimated breeding values (GEBV) of 6 milk production traits ranged from 0.06 to 0.22, and the correlation between estimated breeding values and GEBV ranged from 0.23 to 0.35. These findings provide useful information to understand the genetic basis of buffalo milk properties and may play a role in accelerating buffalo breeding programs using genomic approaches.     

Genome-wide association mapping for type and mammary health traits in French dairy goats identifies a pleiotropic region on chromosome 19 in the Saanen breed

Type traits and mammary health traits are important to dairy ruminant breeding because they influence animal health, milking ability, and longevity, as well as the economic sustainability of farms. The availability of the genomic sequence and a single nucleotide polymorphism chip in goats has opened up new fields of investigation to better understand the genes and mechanisms that underlie such complex traits and to be able to select them. Our objective was to perform a genome-wide association study in dairy goats for 11 type traits and somatic cell count (SCC) as proxies for mastitis resistance. A genome-wide association study was implemented using a daughter design composed of 1,941 Alpine and Saanen goats sired by 20 artificial insemination bucks, genotyped with the Illumina GoatSNP50 BeadChip (Illumina Inc., San Diego, CA). This association study was based on both linkage analyses and linkage disequilibrium using QTLmap software (http://dga7.jouy.inra.fr/qtlmap/) interval mapping was performed with the likelihood ratio test using linear regressions. Breeds were analyzed together and separately. The study highlighted 37 chromosome-wide significant quantitative trait loci (QTL) with linkage analyses and 222 genome-wide significant QTL for linkage disequilibrium, for type and SCC traits in dairy goats. Genomic control of those traits was mostly polygenic and breed-specific, suggesting that within-breed selection would be favored for those traits. Of note, Capra hircus autosome (CHI) 19 appeared to be highly enriched in single nucleotide polymorphisms associated with type and SCC, with 2 highly significant regions in the Saanen breed. One region (33–42 Mb) was significantly associated with SCC and includes candidate genes associated with response to intramammary infections (RARA, STAT3, STAT5A, and STAT5B). Another region of the CHI 19 (24.5–27 Mb) exhibited an adverse pleiotropic effect on milk production (milk, fat yield, and protein yield) and udder traits (udder floor position and rear udder attachment) that agreed with the negative genetic correlations that exist between those 2 groups of traits. These QTL were not found in the Alpine breed. In Alpine, the 2 most significant regions were associated with chest depth on CHI 6 (45.8–46.0 Mb) and CHI 8 (80.7–81.1 Mb). These results will be helpful for goat selection in the future and could lead to identification of causal mutations.     

Estimation of genetic parameters for milk yield across lactations in mixed-breed dairy goats

Currently, breeding values for dairy goats in the United Kingdom are not estimated and selection is based only on phenotypes. Several studies from other countries have applied various methodologies to estimate breeding values for milk yield in dairy goats. However, most of the previous analyses were based on relatively small data sets, which might have affected the accuracy of the parameter estimates. The objective of this study was to estimate genetic parameters for milk yield in crossbred dairy goats in lactations 1 to 4. The research was based on data provided by 2 commercial goat farms in the United Kingdom comprising 390,482 milk yield records on 13,591 dairy goats kidding between 1987 and 2012. The population was created by crossing 3 breeds: Alpine, Saanen, and Toggenburg. In each generation, the best-performing animals were selected for breeding and, as a result, a synthetic breed was created. The pedigree file contained 28,184 individuals, of which 2,414 were founders. The data set contained test-day records of milk yield, lactation number, farm, age at kidding, and year and season of kidding. Data on milk composition was unavailable. Covariance components were estimated with the average information REML algorithm in the ASReml package (VSN International Ltd., Hemel Hempstead, UK). A random regression animal model for milk yield with fixed effects of herd test day, year-season, and age at kidding was used. Heritability was the highest at 200 and 250 d in milk (DIM), reaching 0.45 in the first lactation and between 0.34 and 0.25 in subsequent lactations. After 300 DIM, the heritability started decreasing to 0.23 and 0.10 at 400 DIM in the first and subsequent lactations, respectively. Genetic correlation between milk yield in the first and subsequent lactations was between 0.16 and 0.88. This study found that milk yields in first and subsequent lactations are highly correlated, both at the genetic and phenotypic level. Estimates of heritability for milk yield were higher than most of the values reported in the literature, although they were in the range reported in this species. This should facilitate genetic improvement for the population studied as part of a broader multi-trait breeding program.     

Genome-wide association study for cheese yield and curd nutrient recovery in dairy cows

Cheese production and consumption are increasing in many countries worldwide. As a result, interest has increased in strategies for genetic selection of individuals for technological traits of milk related to cheese yield (CY) in dairy cattle breeding. However, little is known about the genetic background of a cow's ability to produce cheese. Recently, a relatively large panel (1,264 cows) of different measures of individual cow CY and milk nutrient and energy recoveries in the cheese (REC) became available. Genetic analyses showed considerable variation for CY and for aptitude to retain high proportions of fat, protein, and water in the coagulum. For the dairy industry, these characteristics are of major economic importance. Nevertheless, use of this knowledge in dairy breeding is hampered by high costs, intense labor requirement, and lack of appropriate technology. However, in the era of genomics, new possibilities are available for animal breeding and genetic improvement. For example, identification of genomic regions involved in cow CY might provide potential for marker-assisted selection. The objective of this study was to perform genome-wide association studies on different CY and REC measures. Milk and DNA samples from 1,152 Italian Brown Swiss cows were used. Three CY traits expressing the weight (wt) of fresh curd (%CY_CURD), curd solids (%CY_SOLIDS), and curd moisture (%CY_WATER) as a percentage of weight of milk processed, and 4 REC (REC_FAT, REC_PROTEIN, REC_SOLIDS, and REC_ENERGY, calculated as the % ratio between the nutrient in curd and the corresponding nutrient in processed milk) were analyzed. Animals were genotyped with the Illumina BovineSNP50 Bead Chip v.2. Single marker regressions were fitted using the GenABEL R package (genome-wide association using mixed model and regression–genomic control). In total, 103 significant associations (88 single nucleotide polymorphisms) were identified in 10 chromosomes (2, 6, 9, 11, 12, 14, 18, 19, 27, 28). For REC_FAT and REC_PROTEIN, high significance peaks were identified in Bos taurus autosome (BTA) 6 and BTA11, respectively. Marker ARS-BFGL-NGS-104610 (～104.3 Mbp) was highly associated with REC_PROTEIN and Hapmap52348-rs29024684 (～87.4 Mbp), closely located to the casein genes on BTA6, with REC_FAT. Genomic regions identified may enhance marker-assisted selection in bovine cheese breeding beyond the use of protein (casein) and fat contents, whereas new knowledge will help to unravel the genomic background of a cow's ability for cheese production.     

Mapping quantitative trait loci affecting dairy conformation to chromosome 27 in two Holstein grandsire families

Preliminary marker association results for quantitative trait loci affecting conformation traits using the granddaughter design and 8 large US Holstein grandsire families revealed strong associations in two families between the predicted transmitting abilities for dairy conformation and marker genotypes on bovine chromosome 27. Those results were based on single marker-trait associations in a genome-scan to identify broad chromosomal regions potentially containing genes affecting traits of interest. Results presented here describe continued study of quantitative trait loci on chromosome 27 for eventual incorporation into a marker-assisted selection program. Tests of marker associations for family 8 (91 sons) indicated an association with a microsatellite marker located near the telomere of chromosome 27. Interval analysis performed using additional marker genotypes generated for family 8 yielded further evidence for a quantitative trait locus in this region. No evidence was found for associations with milk production traits in this family in this region. An association was also detected in family 2 (240 sons) with a microsatellite marker located approximately 21 cM from the centromere of chromosome 27. Interval analysis performed for family 2 yielded evidence for a quantitative trait locus for dairy conformation near BMS689 with evidence of associations with fat percentage in the same region. Identification of quantitative trait loci affecting dairy conformation and fat components supports results reported by other groups, providing additional evidence that genes affecting fat metabolism are located on bovine chromosome 27.     

Short communication: Replication of genome-wide association studies for milk production traits in Chinese Holstein by an efficient rotated linear mixed model

Milk is regarded as an important nutrient for humans, and Chinese Holstein cows provide high-quality milk for billions of Chinese people. Therefore, detecting quantitative trait nucleotides (QTN) or candidate genes for milk production traits in Chinese Holstein is important. In this study, we performed genome-wide association studies (GWAS) in a Chinese Holstein population of 6,675 cows and 71,633 SNP using deregressed proofs (DRP) as phenotypes to replicate our previous study in a population of 1,815 cows and 39,163 SNP using estimated breeding values (EBV) as phenotypes. The associations between 3 milk production traits—milk yield (MY), fat percentage (FP), and protein percentage (PP)—and the SNP were determined by using an efficient rotated linear mixed model, which benefits from linear transformations of genomic estimated values and Eigen decomposition of the genomic relationship matrix algorithm. In total, we detected 94 SNP that were significantly associated with one or more milk production traits, including 7 SNP for MY, 76 for FP, and 36 for PP; 87% of these SNP were distributed across Bos taurus autosomes 14 and 20. In total, 83 SNP were found to be located within the reported quantitative trait loci (QTL) regions, and one novel segment (between 1.41 and 1.49 Mb) on chromosome 14 was significantly associated with FP, which could be an important candidate QTL region. In addition, the detected intervals were narrowed down from the reported regions harboring causal variants. The top significant SNP for the 3 traits was ARS-BFGL-NGS-4939, which is located within the DGAT1 gene. Five detected genes (CYHR1, FOXH1, OPLAH, PLEC, VPS28) have effects on all 3 traits. Our study provides a suite of QTN, candidate genes, and a novel QTL associated with milk production traits, and thus forms a solid basis for genomic selection and molecular breeding for milk production traits in Chinese Holstein.     

Genome-wide association study for calving traits in Danish and Swedish Holstein cattle

A total of 22 quantitative trait loci (QTL) were detected on 19 chromosomes for direct and maternal calving traits in cattle using a genome-wide association study. Calving performance is affected by the genotypes of both the calf (direct effect) and dam (maternal effect). To identify the QTL contributing these effects to calving characteristics, we performed a genome-wide association study using a mixed-model analysis in Danish and Swedish Holstein cattle. The analysis incorporated 2,062 progeny-tested bulls, and 36,387 single nucleotide polymorphism markers on 29 bovine autosomes were analyzed for association with 14 calving traits. Strong evidence for the presence of QTL that affect calving traits was observed on chromosomes 4, 6, 12, 18, 20, and 25. The QTL intervals were generally smaller than those described in earlier linkage studies. The identification of calving trait-associated single nucleotide polymorphisms and mapping of the corresponding QTL in small chromosomal regions will facilitate the search for candidate calving performance genes and polymorphisms.     

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.     

A genome scan for quantitative trait loci affecting body conformation traits in Spanish Churra dairy sheep

A genome scan for chromosomal regions influencing body conformation traits was conducted for a population of Spanish Churra dairy sheep following a daughter design. A total of 739 ewes from 11 half-sib sire families were included in the study. The ewes were scored for the 5 linear traits used in the breeding scheme of the Churra breed to assess body conformation: stature, rear legs-rear view, foot angle, rump width, and general appearance. All the animals, including the 11 sires, were genotyped for 181 microsatellite markers evenly distributed across the 26 sheep autosomes. Using the yield deviations of the raw scores adjusted for fixed factors as phenotypic measurements, a quantitative trait loci (QTL) analysis was performed on the basis of a multi-marker regression method. Seven suggestive QTL were identified on chromosomes Ovis aries (OAR)2, OAR5, OAR16, OAR23, and OAR26, but none reached a genome-wise significance level. Putative QTL were identified for all of the traits analyzed, except for general appearance score. The suggestive QTL showing the highest test statistic influenced rear legs-rear view and was localized on OAR16, close to the growth hormone receptor coding gene, GHR. Some of the putative linkage associations reported here are consistent with previously reported QTL in cattle for similar traits. To the best of our knowledge, this study provides the first report of QTL for body conformation traits in dairy sheep; further studies will be needed to confirm and redefine the linkage associations reported herein. It is expected that future genome-wide association analyses of larger families will help identify genes underlying these putative genetic effects and provide useful markers for marker-assisted selection of such functional traits.     

Genome-wide association study for milk infrared wavenumbers

Individual wavenumbers of the infrared (IR) spectra of bovine milk have been shown to be moderately to highly heritable. The objective of this study was to identify genomic regions associated with individual milk IR wavenumbers. This is expected to provide information about the genetic background of milk composition and give insight in the relation between IR wavenumbers and milk components. For this purpose, a genome-wide association study was performed for a selected set of 50 individual IR wavenumbers measured on 1,748 Dutch Holstein cows. Significant associations were detected for 28 of the 50 wavenumbers. In total, 24 genomic regions distributed over 16 bovine chromosomes were identified. Major genomic regions associated with milk IR wavenumbers were identified on chromosomes 1, 5, 6, 14, 19, and 20. Most of these regions also showed significant associations with fat, protein, or lactose percentage. However, we also identified some new regions that were not associated with any one of these routinely collected milk composition traits. On chromosome 1, we identified 2 new genomic regions and hypothesized that they are related to variation in milk phosphorus content and orotic acid, respectively. On chromosome 20, we identified a new genomic region that seems to be related to citric acid. Identification of genomic regions associated with milk phosphorus content, orotic acid, and citric acid suggest that the milk IR spectra contain direct information on these milk components. Consequently milk IR analyses probably can be used to predict these milk components, which have low concentrations in milk; this can lead to novel applications of milk IR spectroscopy for dairy cattle breeding and herd management.     

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.     

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.     

Associations among the genome,rumen metabolome,ruminal bacteria,and milk production in early-lactation Holsteins

A multicenter observational study to evaluate genome-wide association was conducted in early-lactation Holstein cows (n = 293) from 36 herds in Canada, the USA, and Australia. Phenotypic observations included rumen metabolome, acidosis risk, ruminal bacterial taxa, and milk composition and yield measures. Diets ranged from pasture supplemented with concentrates to total mixed rations (nonfiber carbohydrates = 17 to 47, and neutral detergent fiber = 27 to 58% of dry matter). Rumen samples were collected <3 h after feeding and analyzed for pH, ammonia, d- and l-lactate, volatile fatty acid (VFA) concentrations, and abundance of bacterial phyla and families. Eigenvectors were produced using cluster and discriminant analyses from a combination of pH and ammonia, d-lactate, and VFA concentrations, and were used to estimate the probability of the risk of ruminal acidosis based on proximity to the centroid of 3 clusters, termed high (24.0% of cows), medium (24.2%), and low risk (51.8%) for acidosis. DNA of sufficient quality was successfully extracted from whole blood (218 cows) or hair (65 cows) collected simultaneously with the rumen samples and sequenced using the Geneseek Genomic Profiler Bovine 150K Illumina SNPchip. Genome-wide association used an additive model and linear regression with principal component analysis (PCA) population stratification and a Bonferroni correction for multiple comparisons. Population structure was visualized using PCA plots. Single genomic markers were associated with milk protein percent and the center logged ratio abundance of the phyla Chloroflexi, SR1, and Spirochaetes, and tended to be associated with milk fat yield, rumen acetate, butyrate, and isovalerate concentrations and with the probability of being in the low-risk acidosis group. More than one genomic marker was associated or tended to be associated with rumen isobutyrate and caproate concentrations, and the center log ratio of the phyla Bacteroidetes and Firmicutes and center log ratio of the families Prevotellaceae, BS11, S24-7, Acidaminococcaceae, Carnobacteriaceae, Lactobacillaceae, Leuconostocaceae, and Streptococcaceae. The provisional NTN4 gene, involved in several functions, had pleiotropy with 10 bacterial families, the phyla Bacteroidetes and Firmicutes, and butyrate. The ATP2CA1 gene, involved in the ATPase secretory pathway for Ca²⁺ transport, overlapped for the families Prevotellaceae, S24-7, and Streptococcaceae, the phylum Bacteroidetes, and isobutyrate. No genomic markers were associated with milk yield, fat percentage, protein yield, total solids, energy-corrected milk, somatic cell count, rumen pH, ammonia, propionate, valerate, total VFA, and d-, l-, or total lactate concentrations, or probability of being in the high- or medium-risk acidosis groups. Genome-wide associations with the rumen metabolome, microbial taxa, and milk composition were present across a wide geographical and management range of herds, suggesting the existence of markers for the rumen environment but not for acidosis susceptibility. The variation in pathogenesis of ruminal acidosis in the small population of cattle in the high risk for acidosis group and the dynamic nature of the rumen as cows cycle through a bout of acidosis may have precluded the identification of markers for acidosis susceptibility. Despite a limited sample size, this study provides evidence of interactions between the mammalian genome, the rumen metabolome, ruminal bacteria, and milk protein percentage.     

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.     

Detection of quantitative trait loci influencing conformation traits and calving ease in Holstein-Friesian cattle

An extension of our previous genome scan of a North American Holstein-Friesian population was conducted to identify quantitative trait loci (QTL) affecting conformation traits. Resource families consisted of 1404 sons of 10 elite sires. Genome coverage was estimated to be 2713.5 cM (90%) for 406 markers using a granddaughter design. Regression interval mapping was used to detect QTL affecting 22 conformation traits, including body, udder, feet and legs, and dairy conformation as well as calving ease. Analysis of the families jointly identified 41 chromosome-wise significant QTL influencing conformation traits and 3 significant QTL influencing calving ease on 20 chromosomes. The false discovery rate method was used to account for multiple testing and 3/4 of the suggestive and 5/6 of significant QTL should be real effects. Fourteen of the 44 QTL were significant at the genome-wise level. Comparison of these results with other published reports identifies common QTL affecting conformation traits. Regions on 10 chromosomes appear to affect multiple traits, including conformation, milk production, and somatic cell score, within these particular US Holstein families. Additional work is needed to determine the precise locations of the QTL and select positional candidate genes influencing these traits.     

Genome-wide scan to detect quantitative trait loci for milk urea nitrogen in Dutch Holstein-Friesian cows

Studies have reported genetic variation in milk urea nitrogen (MUN) between cows, suggesting genetic differences in nitrogen efficiency between cows. In this paper, the results of a genome-wide scan to identify quantitative trait loci (QTL) that contribute to genetic variation in MUN and MUN yield are presented. Two to 3 morning milk samples were taken from 1,926 cows, resulting in 5,502 test-day records. Test-day records were corrected for systematic environmental effects using a repeatability animal model. Averages of corrected phenotypes of 849 cows, belonging to 7 sire families, were used in an across-family multimarker regression approach to detect QTL. Animals were successfully genotyped for 1,341 single nucleotide polymorphisms. The QTL analysis resulted in 4 chromosomal regions with suggestive QTL: Bos taurus autosomes (BTA) 1, 6, 21, and 23. On BTA 1, 2 suggestive QTL affecting MUN were detected at 60 and 140 cM. On BTA 6, 1 suggestive QTL affecting both MUN and MUN yield was detected at 103 cM. On BTA 21, 1 suggestive QTL affecting MUN yield was detected at 83 cM. On BTA 23, 1 suggestive QTL affecting MUN was detected at 54 cM. Quantitative trait loci for MUN and MUN yield were suggestive and each explained between 2 and 3% of the phenotypic variance.     

Detection of quantitative trait loci affecting lameness and leg conformation traits in Danish Holstein cattle

Lameness is an important factor for culling animals. Strong legs and feet improve herd life of dairy cows. Therefore, many countries include leg and feet conformation traits in their breeding programs, often as early predictors of longevity. However, few countries directly measure lameness related traits to include these in a breeding program. Lameness indices in 3 different lactations and 5 leg conformation traits (rear legs side view, rear legs rear view, hock quality, bone quality, and foot angle) were measured on granddaughters of 19 Danish Holstein grandsires with 33 to 105 sons. A genome scan was performed to detect quantitative trait loci (QTL) based on the 29 autosomes using microsatellite markers. Data were analyzed across and within families for QTL affecting lameness and leg conformation traits. A regression method and a variance component method were used for QTL detection. Two QTL each for lameness in the first [Bos taurus autosome (BTA); BTA5, BTA26] and second (BTA19, BTA22) lactations were detected. For the 5 different leg conformation traits, 7 chromosome-wise significant QTL were detected across families for rear legs side view, 5 for rear legs rear view, 4 for hock quality, 4 for bone quality, and 1 for foot angle. For those chromosomes where a QTL associated with 2 different traits was detected (BTA1, BTA11, BTA15, BTA26, and BTA27), a multitrait-1-QTL model and a multitrait-2-QTL model were performed to characterize these QTL as single QTL with pleiotropic effects or distinct QTL.     

Phenotypic and genetic effects of season on milk production traits in dairy cattle in the Netherlands

Milk production systems in several countries show considerable differences between seasons. For example, in the Netherlands, cows are kept inside and fed silage in winter, whereas they are on pasture in summer. The differences between seasons affect milk yield and composition and might influence the genetic background of milk production traits. The objective of this study was to estimate phenotypic and genetic effects of season on milk production traits. For this purpose, 19,286 test-day milk production records of 1,800 first-parity Dutch Holstein-Frisian cows were available, and these cows were genotyped using a 50K SNP panel. Phenotypic effects of season were significant for all milk production traits. Effects of season were large for milk fat yield, fat content, and protein content. Genetic correlations between milk production traits in different seasons showed that genotype by season interaction effects were relatively small for most milk production traits. The genetic background of protein content and lactose content seems to be sensitive to seasonal effects. Furthermore, the genetic correlations between spring and autumn differed significantly from unity for almost all milk production traits. A genome-wide association study for genotype by season interaction identified chromosomal regions on BTA3, BTA14, BTA20, and BTA25 that showed genotype by season interaction effects, including a region containing DGAT1, which showed interaction effects for fat content and protein content.