Nordic Dairy Cattle Research Articles

A Post-GWAS Functional Analysis Confirming Effects of Three BTA13 Genes CACNB2, SLC39A12, and ZEB1 on Dairy Cattle Reproduction.

In our previous GWAS of Chinese and Nordic dairy cattle, genes CACNB2, SLC39A12, and ZEB1 locating on BTA 13 were suggested as candidate genes for reproduction. In this study, validation of these associations was performed in an independent population with records of nine reproductive traits. More importantly, functions of these genes in the reproductive process were verified by employing the expression data of ovarian follicles. The potential variants within the three genes were firstly detected in 68 Chinese Holstein bulls, and then screened in 1,588 Chinese Holstein cows using the KASP (Kompetitive allele-specific PCR) method. There were nine variants with polymorphisms in CACNB2, five in SLC39A12, and four in ZEB1, respectively, of which one SNP was in the upstream regulatory region, two in exon region, four in downstream regulatory region, and 11 SNPs in intronic regions. Amongst the 18 variants, g.33267056T/G in CACNB2 explained the largest phenotypic variance for age at first calving (0.011%), interval from first to last insemination (0.004%), and calving ease (0.002%), while g.32751518G/A in SLC39A12 contributed the most to stillbirth in heifers (0.038%). Two haplotype blocks were constructed for CACNB2 while one each for SLC39A12 and ZEB1, which were significantly associated with five reproductive traits, including age at the first service, age at the first calving, calving ease in heifers and cows, and the interval from calving to the first insemination. We then studied the profile of gene expression in granulosa cells isolated from four developmental stages of ovarian follicles from eight dairy cows. All three genes were differentially expressed between ovarian follicles with different sizes (p < 0.05), indicating their potential roles in the reproductive process of dairy cows. This study successfully demonstrated the associations of three BTA 13 genes CACNB2, SLC39A12, and ZEB1 with reproduction and further examined their expression levels in ovarian follicles directly. These findings can be beneficial for the ongoing genomic selection program for reproductive traits which have long been considered as traits that are difficult to achieve genetic improvement due to the lack of efficient genetic markers.

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.

Genetic analyses of metabolic body weight, carcass weight and body conformation traits in Nordic dairy cattle

Improving feed efficiency in dairy cattle by animal breeding has started in the Nordic countries. One of the two traits included in the applied Saved feed index is called maintenance and it is based on the breeding values for metabolic BW (MBW). However, BW recording based on heart girth measurements is decreasing and recording based on scales is increasing only slowly, which may weaken the maintenance index in future. Therefore, the benefit of including correlated traits, like carcass weight and conformation traits, is of interest. In this study, we estimated genetic variation and genetic correlations for eight traits describing the energy requirement for maintenance in dairy cattle including: first, second and third parity MBW based on heart girth measurements, carcass weight (CARW) and predicted MBW (pMBW) based on predicted slaughter weight, and first parity conformation traits stature (ST), chest width (CW) and body depth (BD). The data consisted of 21329 records from Finnish Ayrshire and 9780 records from Holstein cows. Heritability estimates were 0.44, 0.53, 0.56, 0.52, 0.54, 0.60, 0.17 and 0.26 for MBW1, MBW2, MBW3, CARW, pMBW, ST, CW and BD, respectively. Estimated genetic correlations among MBW traits were strong (>0.95). Genetic correlations between slaughter traits (CARW and pMBW) and MBW traits were higher (from 0.77 to 0.90) than between conformation and MBW traits (from 0.47 to 0.70). Our results suggest that including information on carcass weight and body conformation as correlated traits into the maintenance index is beneficial when direct BW measurements are not available or are difficult or expensive to obtain.

Genomic inbreeding and selection signatures in the local dairy breed Icelandic Cattle.

Icelandic Cattle is the only dairy cattle breed native to Iceland. It currently numbers ca. 26000 breeding females. We used 50k genotypes of over 8000 Icelandic Cattle to estimate genomic and pedigree-based inbreeding and to detect selection signatures using the integrated haplotype score. We used 47 Icelandic bulls genotyped with a 770k SNP chip to estimate LD decay for comparison with other Nordic dairy cattle breeds. We detected ROHs on the autosomes and computed ROH-based autosomal inbreeding coefficients. Average inbreeding coefficients according to pedigree and ROHs were 0.0621 and 0.101. Effective population sizes for the years 2009-2017 according to pedigree, ROHs, genomic relationship matrix, excess of homozygosity and individual increase in inbreeding were 81, 65, 60, 58 and 92 respectively. We identified three regions and six candidate genes that showed a signature of selection according to the integrated haplotype score (P<0.05) on chromosomes 1, 16 and 23. The LD structure of Icelandic Cattle is shaped by a long period of isolation and a small founder population. The estimate of LD at distances closer than 0.3Mb is lower in Icelandic Cattle than in Danish Jersey, but is higher than in Danish Holstein and Red Nordic Dairy Cattle breeds. Our findings show that inbreeding rates in Icelandic Cattle currently are sustainable according to FAO guidelines, and our results do not indicate severe historical inbreeding.

Association of genomically enhanced and parent average breeding values with cow performance in Nordic dairy cattle

This study compared the abilities of virgin heifer genomically enhanced breeding values (GEBV) and parent average breeding values (PA) to predict future cow performance. To increase confidence in genomic technology among farmers, a clear demonstration of the relationship between genomic predictions and future phenotypes is needed. We analyzed 12 different traits in first parity, including production, conformation, fertility, and other functional traits. Phenotype data were obtained from national milk recording schemes and breeding values from the Nordic Cattle Genetic Evaluation. Direct genomic breeding values were calculated using genomic BLUP and combined with traditional breeding values, using bivariate blending. The data covered 14,862 Red Dairy Cattle, 17,145 Holstein, and 7,330 Jersey genotyped virgin heifers born between 2013 and 2015 in Denmark, Finland, and Sweden. Phenotypes adjusted for systematic environmental effects were used as measures of cow performance. Two methods were used to compared virgin heifer GEBV and PA regarding their ability to predict future cow performance: (1) correlations between breeding values and adjusted phenotypes, (2) ranking cows into 4 quartiles for their virgin heifer GEBV or PA, and calculating actual cow performance for each quartile. We showed that virgin heifer GEBV predicted cow performance significantly better than PA for the vast majority of analyzed traits. The correlations with adjusted phenotypes were 38 to 136% higher for GEBV than for PA in Red Dairy Cattle, 42 to 194% higher for GEBV in Holstein, and 11 to 78% higher for GEBV in Jersey. The relative change between GEBV bottom and top quartiles compared with that between PA bottom and top quartiles ranged from 9 to 261% for RDC, 42 to 138% for Holstein, and 4 to 90% for Jersey. Hence, farmers in Denmark, Finland, and Sweden can have confidence in using genomic technology on their herds.

Different beef breed sires used for crossbreeding with Swedish dairy cows - effects on calving performance and carcass traits

Improved potential for weight gain and carcass classification traits in calves aimed at slaughter from dairy herds would increase the calves’ economic value, and enable an increased beef production. At present, relatively low economic weights are placed on beef traits in the comprehensive Nordic dairy cattle breeding goal. An effective way to improve beef production from dairy herds is therefore to inseminate a larger proportion of dairy heifers and cows with beef bull semen. In the choice of beef bull breed, both effects on calving traits, carcass weight gain and carcass traits need to be considered. The aim of this study was therefore to compare different beef x dairy crosses regarding calving performance and carcass traits. Field data comprising in total close to 1.6 million calving records from Swedish herds, and more than 1.1 million carcass records from commercial slaughter houses, were analyzed using linear models. Differences in least-square means between different breed combinations were estimated for percentage of calving difficulty, stillbirth, daily carcass gain, carcass weight, EUROP conformation and fat classification. The dams were purebred Swedish Red (SR) or Swedish Holstein (SH), and the sires were either of purebred dairy (SR or SH) or of the beef breeds Angus, Hereford, Limousin, Simmental or Charolais. The results showed that crossbreeding dairy cows with beef bulls, especially of late maturing breeds, has potential to considerably improve beef production from dairy herds. Improvement of carcass characteristics and carcass gain were most noticeable in young crossbred bulls, where the highest increase for single breed combinations was 67% for conformation and 17% for carcass gain. Offspring of different beef x dairy combinations displayed varying average carcass gain and characteristics in terms of fatness and conformation in heifers, steers and young bulls, and would fit different types of production systems. Whereas crossbreeding had small or favorable effects on stillbirth, the use of late maturing beef breed sires negatively influenced the calving performance, especially in primiparous dairy cows. By choosing individual beef bulls with high estimated breeding values for calving ease, the percentage of calving difficulty could be reduced, even when using late maturing beef breed sires for crossbreeding.

Variation in the actual preferences for AI bull traits among Finnish dairy herds.

Changing production circumstances, a wide range of traits and the international bull market enable dairy farmers to make increasingly specific choices concerning artificial insemination (AI) bulls. Finland is part of the joint Nordic dairy cattle breeding programme where in addition to yield, high emphasis is given to health, fertility, conformation and longevity. The aims of our study were (a) to investigate whether Finnish dairy farmers differ in their selection preferences for AI bull traits and can be clustered into herd groups, (b) to determine whether AI bull selection in different herd groups is in line with the Nordic Total Merit index (NTM) and (c) to analyse how the herd groups are related to herd characteristics. We used a statistical cluster analysis to analyse AI bull usage and to group herds according to each herd's bull selection profile determined by the traits' estimated breeding value (EBV) mean weighted by the number of inseminations for the various traits. We identified four herd groups in both Ayrshire (AY) and Holstein (HOL) breeds: Production, Fertility, All-rounders, and Conformation. The herds' bull selection profiles were mostly close to the NTM except in the Conformation herd groups where traits other than conformation were nearly neglected. This led to poorer expected genetic and economic outcomes than with the NTM selection. Conformation herds were a minority, but they were larger in herd size and investments had recently been made. The data suggest that either fine-tuning the weights in the NTM, forming alternative indices or developing a herd-specific total merit index (TMI) could fulfil the needs of very diverse herds.

Short communication: Multivariate outlier detection for routine Nordic dairy cattle genetic evaluation in the Nordic Holstein and Red population

It is of practical importance to ensure the data quality from a milk-recording system before use for genetic evaluation. A procedure was developed for detection of multivariate outliers based on an approximation for Mahalanobis distance and was implemented in the Nordic Holstein and Red population. The general target of this procedure is based on the Nordic Cattle Genetic Evaluation yield model, which is a 9-trait model for milk, protein, and fat in the first 3 lactations. The procedure is based on the phenotypic correlation structure as a function of days in milk (DIM) and on computation of trait means and standard deviations within a production year, lactation, and DIM. For each record in the data, a Mahalanobis distance value was computed based on the trait mean and the covariance matrix for the actual production year, lactation, and DIM. A set of cutoff values, ranging from 10 to 100 with steps of 10, for discarding multivariate outliers was investigated. Prediction accuracy was calculated as the Pearson correlations between estimated breeding values predicted by full data set and estimated breeding values predicted by reduced data set for cows without records in the reduced data set and with 1 or more records deleted due to the editing rules on Mahalanobis distance. The results showed that, averaged over all scenarios, gains of 0.005 to 0.048 on prediction accuracy have been obtained by deleting the multivariate outliers. The improvements were more profound for progeny of young bulls compared with progeny of proven bulls. It is easy to implement this multivariate outlier-detection procedure in the routine genetic evaluation for different dairy cattle breeds; however, an optimal cutoff value for Mahalanobis distance needs to be defined to achieve an acceptable compromise between genetic evaluation accuracy and data deletion.

RNA-Seq transcriptomics and pathway analyses reveal potential regulatory genes and molecular mechanisms in high- and low-residual feed intake in Nordic dairy cattle

BackgroundThe selective breeding of cattle with high-feed efficiencies (FE) is an important goal of beef and dairy cattle producers. Global gene expression patterns in relevant tissues can be used to study the functions of genes that are potentially involved in regulating FE. In the present study, high-throughput RNA sequencing data of liver biopsies from 19 dairy cows were used to identify differentially expressed genes (DEGs) between high- and low-FE groups of cows (based on Residual Feed Intake or RFI). Subsequently, a profile of the pathways connecting the DEGs to FE was generated, and a list of candidate genes and biomarkers was derived for their potential inclusion in breeding programmes to improve FE.ResultsThe bovine RNA-Seq gene expression data from the liver was analysed to identify DEGs and, subsequently, identify the molecular mechanisms, pathways and possible candidate biomarkers of feed efficiency. On average, 57 million reads (short reads or short mRNA sequences < ~200 bases) were sequenced, 52 million reads were mapped, and 24,616 known transcripts were quantified according to the bovine reference genome. A comparison of the high- and low-RFI groups revealed 70 and 19 significantly DEGs in Holstein and Jersey cows, respectively. The interaction analysis (high vs. low RFI x control vs. high concentrate diet) showed no interaction effects in the Holstein cows, while two genes showed interaction effects in the Jersey cows. The analyses showed that DEGs act through certain pathways to affect or regulate FE, including steroid hormone biosynthesis, retinol metabolism, starch and sucrose metabolism, ether lipid metabolism, arachidonic acid metabolism and drug metabolism cytochrome P450.ConclusionWe used RNA-Seq-based liver transcriptomic profiling of high- and low-RFI dairy cows in two breeds and identified significantly DEGs, their molecular mechanisms, their interactions with other genes and functional enrichments of different molecular pathways. The DEGs that were identified were the CYP’s and GIMAP genes for the Holstein and Jersey cows, respectively, which are related to the primary immunodeficiency pathway and play a major role in feed utilization and the metabolism of lipids, sugars and proteins.

Validation of Nordic dairy cattle disease recording databases—Completeness for locomotor disorders

The Nordic countries Denmark (DK), Finland (FIN), Norway (NO) and Sweden (SE) all have unique national databases holding the disease records of dairy cows. The objective of this study was to estimate and compare completeness for locomotor disorders in the four Nordic national databases. Completeness figures for farmer-recorded disease events were calculated on two different levels: the first refers to disease events that were observed on the farm regardless of whether a veterinarian had been involved (FARMER); the second refers to farmer records of cases attended by a veterinarian, i.e. to veterinarian-treated disease events (VET). A sample of herds with 15 or more cows was obtained from a simple random sample of dairy farms in FIN, NO and SE, and from a systematic random sample in DK. There were 105, 167, 179 and 129 participating farmers in DK, FIN, NO and SE, respectively, and during two 2-month periods in 2008 these farmers recorded the disease events they observed on the farm. Data from the four national databases were extracted in May 2009. The two data sources, farmer recordings and national databases, were managed in a comparable way in all four countries, and common diagnostic codes were created and added to match recordings appearing in both datasets. In all 555 farmers completed data records in the first data-recording period, and 515 farmers did so in the second period. In DK, FIN, NO and SE, 55%, 77%, 82% and 75%, participating farmers completed the recordings during the first recording period, respectively; the corresponding figures for the second recording period were 71%, 82%, 83% and 91%.To calculate completeness, disease cases recorded in the national databases were compared with the farmer recordings using an exact match for the locomotor complex defined as same country, herd identification number (id), cow id, and event date at the levels of FARMER and VET. Completeness at FARMER level were 0.22, 0.21, 0.23 and 0.12 in DK, FIN, NO and SE, respectively. At VET level they were 0.37, 0.27, 0.34 and 0.17. To compare differences in completeness between countries exact 95% confidence intervals were calculated. There were significant differences in completeness between DK and SE at both FARMER and VET level. The completeness indicate that the ability to estimate true disease occurrences in the four national databases varies and is in general poor. Completeness should be taken into account when disease occurrences in different countries are compared.

The discovery of QTL for mastitis resistance in Nordic dairy cattle

The discovery of QTL for mastitis resistance in Nordic dairy cattle

Joint Analysis of Quantitative Trait Loci for Clinical Mastitis and Somatic Cell Score on Five Chromosomes in Three Nordic Dairy Cattle Breeds

Five chromosomes were selected for joint quantitative trait loci (QTL) analyses for clinical mastitis (CM) and somatic cell score (SCS) in 3 breeds: Finnish Ayrshire (FA), Swedish Red and White (SRB), and Danish Red (DR). In total, 19 grandsires and 672 sons in FA, 19 grandsires and 499 sons in SRB, and 8 grandsires and 258 sons in DR were used in the study. These individuals were genotyped with the 61 microsatellite markers used in any of the previous QTL scans on the selected chromosomes. Within-family QTL analyses based on linear regression models were carried out for CM and SCS to identify the segregating sires for each region. On the segregating families, joint single-trait and 2-trait analyses were performed using variance components models. The analyses confirmed that QTL affecting CM or SCS, or both, segregate on Bos taurus autosomes (BTA) 9, 11, 14, and 18, whereas a QTL on BTA29 could not be confirmed. Our results indicate that there may be at least 2 linked QTL on BTA9, one that primarily affects CM and a second that primarily affects SCS. On chromosomes BTA11, 14, and 18, the joint analyses were only significant for SCS.

Economic values for production and non-production traits in nordic dairy cattle populations calculated by stochastic simulation

The objective of this paper was to calculate and compare economic values for dairy cattle traits across the Nordic countries. The stochastic model used was dynamic, and it simulated production, reproduction and health in a dairy herd. Finland and Norway had the highest economic values for milk production, whereas Denmark and Sweden had lower values, assuming a fixed number of cows. Norway had the highest absolute economic values for stillbirth, retained placenta, laminitis, feed intake capacity, milking speed and daily gain. Denmark had the highest absolute economic value for milk fever and calving ease. Finland had the highest economic value for conception rate. Sweden had the lowest economic value for body weight but the highest for temperament. In most cases the differences in economic values were less than two-fold, with greater than two-fold differences for stillbirth (Sweden vs. Finland and Norway), retained placenta (Sweden vs. Norway), laminitis (Sweden vs. Denmark and Norway) and days from calving to first heat (Sweden vs. Finland). The consideration of milk quota, for most traits, caused minor (less than two-fold) changes in economic values. The differences in economic values, for most of the traits, were slight and do not seem to be a hindrance towards a closer cooperation within a joint breeding programme for the Nordic countries.

Genotype by Environment Interaction in Nordic Dairy Cattle Studied Using Reaction Norms

Genotype by environment interaction for production and fertility was studied by use of a reaction norm model. Milk recording data, comprising 927 929 records, were analysed to predict reaction norms for young bulls of the Nordic Red dairy breeds. Random regressions were estimated for each bull, regressing phenotypic values of daughters on herd environment. The phenotypic measures were 305 days kg protein production and days open in first lactation. The herd environment was defined as the herd-year average of protein production and days open, respectively. Heritability of protein production and days open and genetic correlation between the two traits were estimated as functions of the herd environment. The results showed that the genetic parameters change over environments, which are measured on a continuous scale across countries. Grouping of observations is avoided and thereby the problem of genetic connectedness between groups or countries may be avoided. Although significant genetic variation for the slope of the reaction norm was found, there was little reranking of sires, except between extreme environments. More appropriate models and methods need to be developed for further studies of genetic variation in reaction norms.

Nordic dairy cattle comparison for milk production by using a mixed linear model approach

The exchange of genetic material between the dairy cattle populations in the Nordic countries is well established. Initially the following Nordic dairy cattle populations were used to perform a comparison of their genetic levels for milk production: the Norwegian Cattle (NRF), the Swedish Red and White Cattle (SRB), and the Finnish Ayrshire Cattle (FAY). A linear model, including genetic base of sire proofs and genetic group made up by breed composition and date of birth of sire as fixed effects and sire as a random effect, was applied to standardize and deregress official sire proofs. The result was expressed as Nordic transmitting ability in kg of fat- and protein-corrected milk (FPM). The overall average of Nordic proofs of sires used in the NRF population was, respectively, 72 and 151 kg FPM higher than those of sires proven in the SRB and FAY populations. A genetic comparison of the breeds gave the same general result. The annual genetic trends were 25.5, 16.7 and 30.4 kg FPM in the NRF, SRB and FAY populations. Actually, the highest selection differentials were measured for bull sires in the FAY population. Sons of foreign bull sires had an overall negative impact in the NRF population, but a positive impact in both the SRB and FAY populations.