A genome wide association study for QTL affecting direct and maternal effects of stillbirth and dystocia in cattle

Dystocia and stillbirth are significant causes of female and neonatal death in many species and there is evidence for a genetic component to both traits. Identifying causal mutations affecting these traits through genome wide association studies could reveal the genetic pathways involved and will be a step towards targeted interventions. Norwegian Red cattle are an ideal model breed for such studies as very large numbers of records are available. We conducted a genome wide association study for direct and maternal effects of dystocia and stillbirth using almost 1 million records of these traits. Genotyping costs were minimized by genotyping the sires of the recorded cows, and using daughter averages as phenotypes. A dense marker map containing 17 343 single nucleotide polymorphisms covering all autosomal chromosomes was utilized. The genotyped sires were assigned to one of two groups in an attempt to ensure independence between the groups. Associations were only considered validated if they occurred in both groups. Strong associations were found and validated on chromosomes 4, 5, 6, 9, 12, 20, 22 and 28. The QTL region on chromosome 6 was refined using LDLA analysis. The results showed that this chromosome most probably contains two QTL for direct effect on dystocia and one for direct effect on stillbirth. Several candidate genes may be identified close to these QTL. Of these, a cluster of genes expected to affect bone and cartilage formation (i.e. SPP1, IBSP and MEPE) are of particular interest and we suggest that these genes are screened in candidate gene studies for dystocia and stillbirth in cattle as well as other species.     

Genetic parameters for producer-recorded health data in Canadian Holstein cattle

Health traits are of paramount importance for economic dairy production. Improvement in liability to diseases has been made with better management practices, but genetic aspects of health traits have received less attention. Dairy producers in Canada have been recording eight health traits (mastitis (MAST), lameness (LAME), cystic ovarian disease (COD), left displaced abomasum (LDA), ketosis (KET), metritis (MET), milk fever (MF) and retained placenta (RP)) since April 2007. Genetic analyses of these traits were carried out in this study for the Holstein breed. Edits on herd distributions of recorded diseases were applied to the data to ensure a sufficient quality of recording. Traits were analysed either individually (MAST, LAME, COD) or were grouped according to biological similarities (LDA and KET, and MET, MF and RP) and analysed with multiple-trait models. Data included 46 104 cases of any of the above diseases. Incidence ranged from 2.3% for MF to 9.7% for MAST. MET and KET also had an incidence below 4.0%. Variance components were estimated using four different sire threshold models. The differences between models resulted from the inclusion of days at risk (DAR) and a cow effect, in addition to herd, parity and sire effects. Models were compared using mean squared error statistic. Mean squared error favoured, in general, the sire and cow within sire model with regression on DAR included. Heritabilities on the liability scale were between 0.02 (MET) and 0.21 (LDA). There was a moderate, positive genetic correlation between LDA and KET (0.58), and between MET and RP (0.79).     

A genome map of divergent artificial selection between Bos taurus dairy cattle and Bos taurus beef cattle

A number of cattle breeds have become highly specialized for milk or beef production, following strong artificial selection for these traits. In this paper, we compare allele frequencies from 9323 single nucleotide polymorphism (SNP) markers genotyped in dairy and beef cattle breeds averaged in sliding windows across the genome, with the aim of identifying divergently selected regions of the genome between the production types. The value of the method for identifying selection signatures was validated by four sources of evidence. First, differences in allele frequencies between dairy and beef cattle at individual SNPs were correlated with the effects of those SNPs on production traits. Secondly, large differences in allele frequencies generally occurred in the same location for two independent data sets (correlation 0.45) between sliding window averages. Thirdly, the largest differences in sliding window average difference in allele frequencies were found on chromosome 20 in the region of the growth hormone receptor gene, which carries a mutation known to have an effect on milk production traits in a number of dairy populations. Finally, for the chromosome tested, the location of selection signatures between dairy and beef cattle was correlated with the location of selection signatures within dairy cattle.     

New phenotypes for new breeding goals in dairy cattle

Cattle production faces new challenges regarding sustainability with its three pillars - economic, societal and environmental. The following three main factors will drive dairy cattle selection in the future: (1) During a long period, intensive selection for enhanced productivity has deteriorated most functional traits, some reaching a critical point and needing to be restored. This is especially the case for the Holstein breed and for female fertility, mastitis resistance, longevity and metabolic diseases. (2) Genomic selection offers two new opportunities: as the potential genetic gain can be almost doubled, more traits can be efficiently selected; phenotype recording can be decoupled from selection and limited to several thousand animals. (3) Additional information from other traits can be used, either from existing traditional recording systems at the farm level or from the recent and rapid development of new technologies and precision farming. Milk composition (i.e. mainly fatty acids) should be adapted to better meet human nutritional requirements. Fatty acids can be measured through a new interpretation of the usual medium infrared spectra. Milk composition can also provide additional information about reproduction and health. Modern milk recorders also provide new information, that is, on milking speed or on the shape of milking curves. Electronic devices measuring physiological or activity parameters can predict physiological status like estrus or diseases, and can record behavioral traits. Slaughterhouse data may permit effective selection on carcass traits. Efficient observatories should be set up for early detection of new emerging genetic defects. In the near future, social acceptance of cattle production could depend on its capacity to decrease its ecological footprint. The first solution consists in increasing survival and longevity to reduce replacement needs and the number of nonproductive animals. At the individual level, selection on rumen activity may lead to decreased methane production and concomitantly to improved feed efficiency. A major effort should be dedicated to this new field of research and particularly to rumen flora metagenomics. Low input in cattle production is very important and tomorrow's cow will need to adapt to a less intensive production environment, particularly lower feed quality and limited care. Finally, global climate change will increase pathogen pressure, thus more accurate predictors for disease resistance will be required.     

Genetic association between body energy measured throughout lactation and fertility in dairy cattle

The objective of this study was to quantify the genetic association of body energy assessed throughout lactation with a cow's fertility. Nine direct and indirect body energy traits were defined at different stages of lactation. Four were daily records of energy balance, energy content, cumulative effective energy (CEE) and body condition score (BCS) calculated between lactation days 4 and 311. The other five traits included duration of negative energy balance (DNEB), rate of recovery during DNEB (RNEB), sum of negative energy balance (SNEB), nadir of energy content (NEC) and number of days from calving to NEC. Of these traits, energy balance, DNEB, RNEB and SNEB were primarily based on individual cow feed intake and milk yield, and considered direct measures of body energy. The other traits were calculated from body lipid and protein changes, predicted from BCS and live weight profiles, and were considered indirect measures of body energy. Fertility was defined by number of days between calving and commencement of luteal activity (DLA), first observed oestrus (DH) and conception (DC), and number of services per conception. A total of 957 cows in their first four lactations were considered in the study. Genetic models fitted cubic splines to define longitudinal traits (energy balance, energy content, CEE and BCS) and calculate heritability and genetic correlation with fertility. Daily heritability estimate ranges were 0.10 to 0.34, 0.35 to 0.61, 0.32 to 0.53 and 0.24 to 0.56 for energy balance, energy content, CEE and BCS, respectively, and, in most cases, tended to increase towards the middle of lactation and remain relatively stable thereafter. Of the other body energy traits, heritability of NEC (0.44) was the most notable. Statistically significant (P < 0.05) genetic correlations of DH with daily energy balance, energy content, CEE and BCS ranged from -0.16 to -0.28, -0.35 to -0.48, -0.16 to -0.26 and -0.37 to -0.44, respectively. For DC, respective estimates were -0.28 to -0.64, -0.37 to -0.60, -0.30 to -0.48 and -0.29 to -0.53. For DLA, they ranged from -0.47 to -0.56 with energy content and from -0.50 to -0.74 with BCS. Of special interest was the genetic correlation of NEC with DH (-0.54) and DC (-0.48). Results suggest that indirect measures of body energy have the strongest genetic association with cow fertility. NEC and early lactation (circa day 50) BCS and energy content are the most useful traits for selection in terms of the correlated improvement in a cow's capacity to resume her reproductive activity post partum.     

Prevalence and antimicrobial resistance of Campylobacter in US dairy cattle

AIMS: To obtain an overview of the prevalence and antimicrobial resistance of Campylobacter in faeces of US dairy cows in 2002. METHODS AND RESULTS: Faeces from 1435 cows, representing 96 dairy operations in 21 US states, were collected for the culture of Campylobacter. A total of 735 Campylobacter strains were isolated (51.2% positive samples) with 94 operations positive (97.9%) for Campylobacter. From this collection, 532 isolates (473 Campylobacter jejuni and 59 Campylobacter coli) were randomly selected for susceptibility testing to eight antimicrobials: azithromycin, chloramphenicol, ciprofloxacin, clindamycin, erythromycin, gentamicin, nalidixic acid and tetracycline. The C. jejuni isolates exhibited resistance to tetracycline (47.4%), nalidixic acid (4.0%) and ciprofloxacin (2.5%), while the C. coli strains exhibited some resistance to all antimicrobials except chloramphenicol and ciprofloxacin. Only 3.6% of the C. jejuni isolates were resistant to two or more antimicrobials but 20.3% of the C. coli strains were multiresistant. CONCLUSIONS: On most operations, at least one cow was positive for Campylobacter and more than half of the cows sampled were shedding Campylobacter. The C. coli isolates had significantly higher levels of resistance to macrolides and to tetracycline compared with the C. jejuni strains, but were susceptible to ciprofloxacin. SIGNIFICANCE AND IMPACT OF THE STUDY: This study demonstrated a high prevalence of Campylobacter on US dairy operations; however, US dairy cattle have not been recognized as a major source of human infection compared with poultry. Campylobacter coli appears to develop antimicrobial resistance more readily than C. jejuni from the same environment.     

Shedding of Campylobacter spp. in Finnish cattle on dairy farms

Aims:  The aim of this study was to determine variation of prevalence throughout a year, colonization levels and genotypes of Campylobacter jejuni in Finnish dairy cattle herds.
Methods and Results:  Faecal samples and tank milk samples from three dairy cattle herds were taken five times, and swab samples from drinking troughs once during a 1-year sampling period. The samples were enriched in Bolton broth and subsequently spread on mCCDA. Isolates were then subtyped by pulsed-field gel electrophoresis using SmaI. Campylobacter jejuni was detected in 169 of the 340 faecal samples and in one drinking trough sample. Prevalences between herds and sampling times varied widely. The faecal levels of C. jejuni were mainly low. Between one and four SmaI subtypes were identified from each herd per sampling. Two SmaI subtypes persisted in two of the herds throughout the study.
Conclusions:  Dairy cattle can be a long-term reservoir of C. jejuni subtypes similar to clinical isolates. Differences in the colonization potential among C. jejuni strains as well as in the resistance to campylobacter colonization among animals are possible.
Significance and Impact of the Study:  The study provides data on contamination dynamics, colonization levels and the persistence of C. jejuni in dairy cattle.     

Quantitative trait loci mapping in dairy cattle: review and meta-analysis

From an extensive review of public domain information on dairy cattle quantitative trait loci (QTL), we have prepared a draft online QTL map for dairy production traits. Most publications (45 out of 55 reviewed) reported QTL for the major milk production traits (milk, fat and protein yield, and fat and protein concentration (%)) and somatic cell score. Relatively few QTL studies have been reported for more complex traits such as mastitis, fertility and health. The collated QTL map shows some chromosomal regions with a high density of QTL, as well as a substantial number of QTL at single chromosomal locations. To extract the most information from these published records, a meta-analysis was conducted to obtain consensus on QTL location and allelic substitution effect of these QTL. This required modification and development of statistical methodologies. The meta-analysis indicated a number of consensus regions, the most striking being two distinct regions affecting milk yield on chromosome 6 at 49 cM and 87 cM explaining 4.2 and 3.6 percent of the genetic variance of milk yield, respectively. The first of these regions (near marker BM143) affects five separate milk production traits (protein yield, protein percent, fat yield, fat percent, as well as milk yield).     

Bull-bull mounts in Holstein bulls: a survey of its incidence,possible causes,and consequences in Uruguayan bull’ breeders

Bulls frequently display male-male mounts, with consequences in the incidence of injuries, and possibly affecting the reproductive performance of the bulls. This behavior is known as the “buller syndrome” when appears in steers, with several individuals mounting one or a few penmates. The study aimed to collect information on the incidence of bull-bull mounts, the possible associated factors, the productive consequences, and management applied by distributing a survey to Holstein bull breeders in Uruguay. A survey was applied and responded by most Holstein breeders in Uruguay (30/33). Nineteen of the 30 breeders observed mounting behavior among bulls, and 15 of them considered it as a relevant problem. The breeders that observed the behavior had a greater number of bulls than those that did not observe it (P = 0.002). All of them observed that mounts were persistently directed towards the same individual (considering a specific period, while it remained in the group). Of these, 11 (58%) considered that this stopped only when the “buller” bull was removed from the group, mentioning that the behavior was frequently redirected to another individual. The mounts between bulls are a major problem in the breeding of Holstein bulls, with important consequences on weight gain and animal health, reproductive problems such as low libido and seminal quality, and even provoking the death of animals. Although not all breeders reported the existence of the problem, those with the bigger herds did. While some management and/or environmental conditions seem to influence (higher density, regrouping, managements that involve movement of animals, and spring) the incidence of bull-bull mounts, there are no standardized managements to avoid this behavior. Considering that most breeders were interested in including practices to minimize this problem if available, it would be essential to understand better the causes and predisposing factors to decrease its negative impacts.     

Comparison of artificial insemination and natural service cost effectiveness in dairy cattle

Reproductive efficiency in the dairy herd is the most important factor for its economic success and a major concern for dairy farmers when using artificial insemination (AI) or natural service (NS). Our objectives were to estimate, compare and analyse the costs associated with breeding cattle by do-it-yourself (DIY) AI and NS and identify the factors that influence them, under typical dairy farming conditions in Greece. A simulation study was designed based on data from 120 dairy cattle farms that differed in size (range 40 to 285 cows) and milk production level (4000 to 9300 kg per cow per year). Different scenarios were employed to estimate costs associated directly with AI and NS as well as potentially extended calving intervals (ECI) due to AI. Results showed that bull maintenance costs for NS were €1440 to €1670 per year ($1,820 to $2,111). Direct AI costs were higher than those for NS for farms with more than 30 cows and ECI constituted a considerable additional burden. In fact, amongst the factors that affected the amount of milk needed to cover total extra AI costs, number of days open was the dominant one. Semen, feed and heifer prices had a very small effect. When, hypothetically, use of NS bulls results in a calving interval of 12 months, AI daughters with a calving interval of 13.5 months have to produce about 705 kg of additional milk in order to cover the extra cost. Their actual milk production, however, exceeds this limit by more than 25%. When real calving intervals are considered (13.0 v. 13.7 months for NS and AI, respectively) AI daughters turn out to produce more than twice the additional amount of milk needed. It was concluded that even under less than average management conditions, AI is more profitable than the best NS scenario. The efficient communication of this message should be a primary concern of the AI industry.     

Review: How to improve genomic predictions in small dairy cattle populations

This paper reviews strategies and methods to improve accuracies of genomic predictions from the perspective of a numerically small population. Improvements are realized by influencing one or both of the main factors: (1) improve or increase genomic connections to phenotypic records in training data. (2) Models and strategies to focus genomic predictions on markers closer to the causative variants. Combining populations into a joint reference population results in high improvements when combining populations of the same breed and diminishes as the genetic distance between populations increases. For distantly related breeds sophisticated Bayesian variable selection models in combination with denser markers sets or functional subsets of markers is needed. This is expected to be further improved by the efficient use of sequence information. In addition predictions can be improved by the use of phenotypes of genotyped and non-genotyped cows directly. For a small population the optimal approach will combine the above components.     

A candidate gene association study for nine economically important traits in Italian Holstein cattle

We genotyped 58 single nucleotide polymorphisms (SNPs) in 25 candidate genes in about 800 Italian Holstein sires. Fifty‐six (minor allele frequency >0.02) were used to evaluate their association with single traits: milk yield (MY), milk fat yield (FY), milk protein yield (PY), milk fat percentage (FP), milk protein percentage (PP), milk somatic cell count (MSCC); and complex indexes: longevity, fertility and productivity–functionality type (PFT), using deregressed proofs, after adjustment for familial relatedness. Thirty‐two SNPs were significantly associated (proportion of false positives <0.05) with different traits: 16 with MSCC, 15 with PY, 14 with MY, 12 with PFT, eight with longevity, eight with FY, eight with PP, five with FP and two with fertility. In particular, a SNP in the promoter region of the PRLR gene was associated with eight of nine traits. DGAT1 polymorphisms were highly associated with FP and FY. Casein gene markers were associated with several traits, confirming the role of the casein gene cluster in affecting milk yield, milk quality and health traits. Other SNPs in genes located on chromosome 6 were associated with PY, PP, PFT, MY (PPARGC1A) and MSCC (KIT). This latter association may suggest a biological link between the degree of piebaldism in Holstein and immunological functions affecting somatic cell count and mastitis resistance. Other significant SNPs were in the ACACA, CRH, CXCR1, FASN, GH1, LEP, LGB (also known as PAEP), MFGE8, SRC, TG, THRSP and TPH1 genes. These results provide information that can complement QTL mapping and genome‐wide association studies in Holstein.     

Evaluation of the impact of a Herd Health and Production Management programme in organic dairy cattle farms: a process evaluation approach

Animal health planning activities are not always providing a satisfactory positive impact on herd health and welfare. Moreover, evaluating the impact of advisory programmes is complex due to multiple interacting elements that influence its outcome. Therefore, measuring solely health outcomes is not sufficient: the whole process of the implementation and use of such programmes should be evaluated. In order to evaluate the impact of an intervention with a Herd Health and Production Management (HHPM) programme a process evaluation framework was designed and used. The intervention involved 20 organic dairy cattle farmers and their advisors, in both France and Sweden. In both countries 20 organic dairy farms were selected as control herds. The evaluation of the HHPM programme was based on: (a) the compliance to the programme; (b) the programme’s functions influencing herd health management practices and stimulating dialogue between farmers and advisors; (c) its effectiveness in terms of improving herd health compared with control farms. Complete compliance to the programme was fulfilled by 21 out of 40 farmers–advisors. Results from a questionnaire showed that the programme functioned as intended (e.g. by allowing early identification of herd health problems), stimulated change in farmers’ herd health management practices and farmer–advisor dialogue. Even though the majority of the users perceived that the programme contributed to herd health improvements, no significant differences in health outcomes were found when compared with control farms 12 months after the start of the intervention. The programme allowed creating an environment promoting the exchange of information between farmers and advisors, necessary to define pertinent advice in a farm-specific situation. Future research should aim at improving methods for the evaluation of the effect of advisory programmes, by identifying early indicators for effective advice and developing methods to evaluate the quality of advisory situations without interfering with them.     

Non-additive genetic effects for fertility traits in Canadian Holstein cattle (Open Access publication )

The effects of additive, dominance, additive by dominance, additive by additive and dominance by dominance genetic effects on age at first service, non-return rates and interval from calving to first service were estimated. Practical considerations of computing additive and dominance relationships using the genomic relationship matrix are discussed. The final strategy utilized several groups of 1000 animals (heifers or cows) in which all animals had a non-zero dominance relationship with at least one other animal in the group. Direct inversion of relationship matrices was possible within the 1000 animal subsets. Estimates of variances were obtained using Bayesian methodology via Gibbs sampling. Estimated non-additive genetic variances were generally as large as or larger than the additive genetic variance in most cases, except for non-return rates and interval from calving to first service for cows. Non-additive genetic effects appear to be of sizeable magnitude for fertility traits and should be included in models intended for estimating additive genetic merit. However, computing additive and dominance relationships for all possible pairs of individuals is very time consuming in populations of more than 200 000 animals.     

A practical approach for minimising inbreeding and maximising genetic gain in dairy cattle

A method that predicts the genetic composition and inbreeding (F) of the future dairy cow population using information on the current cow population, semen use and progeny test bulls is described. This is combined with information on genetic merit of bulls to compare bull selection methods that minimise F and maximise breeding value for profit (called APR in Australia). The genetic composition of the future cow population of Australian Holstein-Friesian (HF) and Jersey up to 6 years into the future was predicted. F in Australian HF and Jersey breeds is likely to increase by about 0.002 and 0.003 per year between 2002 and 2008, respectively. A comparison of bull selection methods showed that a method that selects the best bull from all available bulls for each current or future cow, based on its calf''s APR minus F depression, is better than bull selection methods based on APR alone, APR adjusted for mean F of prospective progeny after random mating and mean APR adjusted for the relationship between the selected bulls. This method reduced F of prospective progeny by about a third to a half compared to the other methods when bulls are mated to current and future cows that will be available 5 to 6 years from now. The method also reduced the relationship between the bulls selected to nearly the same extent as the method that is aimed at maximising genetic gain adjusted for the relationship between bulls. The method achieves this because cows with different pedigree exist in the population and the method selects relatively unrelated bulls to mate to these different cows. Selecting the best bull for each current or future cow so that the calf''s genetic merit minus F depression is maximised can slow the rate of increase in F in the population.     

Detection of genes influencing economic traits in three French dairy cattle breeds

A project of QTL detection was carried out in the French Holstein, Normande, and Montbéliarde dairy cattle breeds. This granddaughter design included 1 548 artificial insemination bulls distributed in 14 sire families and evaluated after a progeny-test for 24 traits (production, milk composition, persistency, type, fertility, mastitis resistance, and milking ease). These bulls were also genotyped for 169 genetic markers, mostly microsatellites. The QTL were analysed by within-sire linear regression of daughter yield deviations or deregressed proofs on the probability that the son receives one or the other paternal QTL allele, given the marker information. QTL were detected for all traits, including those with a low heritability. One hundred and twenty QTL with a chromosome-wise significance lower than 3% were tabulated. This threshold corresponded to a 15% false discovery rate. Amongst them, 32 were genome-wise significant. Estimates of their contribution to genetic variance ranged from 6 to 40%. Most substitution effects ranged from 0.6 to 1.0 genetic standard deviation. For a given QTL, only 1 to 5 families out of 14 were informative. The confidence intervals of the QTL locations were large and always greater than 20 cM. This experiment confirmed several already published QTL but most of them were original, particularly for non-production traits.     

Mapping economic trait loci for somatic cell score in Holstein cattle using microsatellite markers and selective genotyping

Marker-assisted selection (MAS) uses genetic marker genotypes to predict an animal's production potential and will provide additional selection information for progeny testing. With the discovery of highly polymorphic microsatellite markers, the tools now exist to begin the search for economic trait loci (ETL), which is the first step toward MAS. The objective of this study was to identify ETL for somatic cell score in an existing Holstein population. Using the granddaughter design, sons from seven grandsire families were genotyped with 20 autosomal microsatellites from five chromosomes (4, 8, 13, 17, 23), with an emphasis on chromosome 23, which is the location of the bovine major histocompatibility complex (BoLA). Selective genotyping was used to reduce the number of genotypes required, in which the 10 highest and 10 lowest sons from the phenotypic distribution curve were tested (140 sons in seven families). One marker (513), located near BoLA, showed evidence of an ETL in three of five polymorphic families. Additional sons were genotyped from the five families to estimate the effect and to compare selective and ‘complete’ genotyping. Both methods detected an ETL at marker 513, but in different families. This study provides evidence of the usefulness of microsatellite markers and the granddaughter design in the detection of ETL; however, additional markers need to be evaluated to determine the usefulness of selective genotyping. Based on the results from the 20 studied markers, the most likely position of a somatic cell score ETL lies near marker 513, located on chromosome 23.