Major advances in determining appropriate selection goals

Partitioning among-animal variance of energy utilization in lactating Jersey cows

Animals vary in the way in which they utilize energy due to diet, genetics, and management. Energy consumed by the animal supports milk production, but considerable variation among-animals in energy utilization is thought to exist. The study objective was to estimate the among-animal variance in energy utilization in data collected from Jersey cows using indirect calorimetry. Individual animal-period data from 15 studies (n = 560) were used. The data set included 115 animals from 44 to 410 DIM producing 11.5 to 39.1 kg/d of milk. On average, the 63 treatments in the data set ranged 14.8 to 19.5% CP, 21.4 to 43.0% NDF, 16.2 to 33.3% starch, and 2.21 to 6.44% crude fat. Data were analyzed with the Glimmix procedure of SAS (9.4) with random effects of cow, treatment nested within period, square, and experiment. The percentage of among-animal, dietary treatment, and experimental variance was calculated as the variance associated with each fraction divided by the sum of variance from animal, dietary treatment, experiment, and residual which was considered the total variance. The percentage of among-animal variance was characterized as high or low when the value was greater than or less than the mean value of 29.2%. Among-animal variance explained approximately 29.3 - 42.5% of the total variance in DM intake (DMI), gross energy (GE), digestible energy (DE), metabolizable energy (ME), and net energy of lactation (NEL) in Mcal/d. When energetic components of feces, urine, and heat in Mcal/d were expressed per unit of DMI the among-animal variance decreased by 20.4, 4.82, and 9.55% units, respectively. However, among-animal variance explained 4.80, 8.78, and 5.02% units more of the total variation for methane energy, lactation energy, and tissue energy in Mcal/d when expressed per unit of DMI. Variance in energetic efficiencies of DE/GE, ME/GE, and ME/DE were explained to a lesser extent by among-animal variance (averaging 17.8 ± 1.95%). The among-animal contribution to total variance in milk energy was 28.8%. Milk energy was a large proportion of the energy efficiency calculation which included milk energy plus corrected tissue energy over net energy intake which likely contributed to the 22.2% of total among-animal variance in energy efficiency. Results indicate that among-animal variance explains a large proportion of the total variation in DMI. This contributes to the variance observed for energy fractions as well as energy components when expressed in Mcal/d. Variation in energetic loss associated with methane was primarily explained by differences among-animals and was increased when expressed per unit of DMI highlighting the role of inherent animal differences in these losses.

Characteristics of restricted selection indices and geometrical interpretation of restricted breeding values

Restricted selection is used to control genetic changes in one or more characters. Three main selection indices are adopted for this purpose. First, Kempthorne's index is used to maximize aggregate breeding value (BV) with changes in some traits restricted to zero; second, Harville's index is used to maximize aggregate BV with proportional changes for some traits; and third, Yamada's index is mathematically used to achieve the relative desired changes for all traits. Kempthorne's index is equivalent to Harville's index. However, the relationship between Kempthorne's and Yamada's indices has not been clarified. In addition, the characteristics of restricted selection indices and the relationship between BV and restricted BV (RBV) are also unknown. The aim of this study was to clarify the characteristics of restricted selection indices and describe the relationship between BV and RBV by using linear algebra and geometric techniques, respectively. First, I proved that Yamada's index is part of Kempthorne's index. Second, I investigated the relationship between BVs that were estimated using an ordinary selection index (EBVs) and RBVs estimated using a restricted selection index (ERBVs) and proved that the ERBVs of the restricted traits are proportional to the relative desired changes. Third, I proved that RBV is represented by a linear function of BV and geometrically represented the relationship between BV and RBV. In this study, new findings on restricted selection indices and RBV were obtained. This useful clarification of the relationship between BV and RBV will make it possible to evaluate the response to selection using not only a restricted selection index, but also a restricted BLUP in computer simulation studies.

Body conformation traits in early-lactation associated with clinical mastitis and lameness in lactating Chinese holstein cows

BACKGROUND

Comprehending the correlation between body conformation traits of cows at the early stages of lactation and prevalent lactation diseases might facilitate the execution of selection and feeding strategies that prioritize cow health. This study aimed to evaluate the impact of body conformation traits on the incidence of clinical mastitis and lameness in Chinese Holstein cows. From a pasture herd of 1472 early lactating Chinese Holstein cows, we evaluated 20 body conformation traits. During lactation, this pasture herd was visited weekly to gather clinical mastitis and lameness data. A nine-point scale was used to determine the conformation traits of cows to clarify their linear characters, including frame capacity, rump (RU), feet and leg (FL), mammary system (MS), and dairy character. A longitudinal binary disease (0 = healthy; 1 = diseased) data structure was created by allocating disease records to adjacent official test dates. The impact of body conformation traits on the risk of developing diseases (clinical mastitis and lameness) was analyzed using the logistic regression models.

RESULTS

Compared to cows with low total scores (75-79 points), those with high total scores (80-85 points) of body conformation traits had a significantly lower risk of mastitis (P < 0.001). The disease status (0 or 1: binary variable) of clinical mastitis in lactating cows was significantly impacted negatively by age (P < 0.05). The fore udder attachment (FUA), angularity, rear attachment height (RAH), and rear teat placement (RTP) were all significantly associated with clinical mastitis during lactation (P < 0.05). The rear leg-rear view (RLRV) was significantly correlated with correlated considerably (P < 0.05) with lameness during lactation. An ideal score of four points on the lameness risk dimension of the RLRV may indicate a low risk of lameness. Since the risk of mastitis decreased as this trait score increased, the RTP may be an ideal marker for mastitis risk.

CONCLUSIONS

According to the study, clinical mastitis and lameness risks in cows can be estimated using their body conformation traits. Cows with more centrally located rear teats have a lower risk of mastitis. These results may help dairy farmers identify cows at high risk of disease early in lactation and aid in breeding for disease resistance in cows.

Defining valid breeding goals for animal breeds

BACKGROUND

The objective of any valid breeding program is to increase the suitability of a breed for its future purposes. The approach most often followed in animal breeding for optimizing breeding goals assumes that the sole desire of the owners is profit maximization. As this assumption is often violated, a generalized approach is needed that does not rely on this assumption.

RESULTS

The generalized approach is based on the niche concept. The niche of a breed is a set of environments in which a small population of the breed would have a positive population growth rate. Its growth rate depends on demand from prospective consumers and supply from producers. The approach involves defining the niche that is envisaged for the breed and identifying the trait optima that maximize the breed's adaptation to its envisaged niche within the set of permissible breeding goals. The set of permissible breeding goals is the set of all potential breeding goals that are compatible with animal welfare and could be reached within the planning horizon of the breeding program. In general, the breed's adaptation depends on the satisfaction of the producers with the animals and on the satisfaction of the consumers with the products produced by the animals. When consumers buy live animals, then the breed needs to adapt to both the environments provided by the producers, and the environments provided by the consumers. The profit function is replaced by a more general adaptedness function that measures the breed's adaptation to its envisaged niche.

CONCLUSIONS

The proposed approach coincides with the traditional approach if the producers have the sole desire to maximize their income, and if consumer preferences are well reflected by the product prices. If these assumptions are not met, then the traditional approach to breeding goal optimization is unlikely to result in a valid breeding goal. Using the example of companion breeds, this paper shows that the proposed approach has the potential to fill the gap.

Fertility and survival of Swedish Red and White × Holstein crossbred cows and purebred Holstein cows

Swedish Red and White × Holstein (S×H) cows were compared with pure Holstein (HOL) cows for fertility and survival traits in 2 commercial dairy farms in central-southern Córdoba province, Argentina, over 6 years (2008-2013). The following traits were evaluated: first service conception rate (FSCR), overall conception rate (CR), number of services per conception (SC), days open (DO), mortality rate, culling rate, survival to subsequent calvings, and length of productive life (LPL). The data set consisted of 506 lactations from 240 S×H crossbred cows and 1,331 lactations from 576 HOL cows. The FSCR and CR were analyzed using logistic regression, DO and LPL were analyzed using a Cox's proportional hazards regression model, and differences of proportions were calculated for mortality rate, culling rate, and survival to subsequent calvings. The S×H cows were superior to HOL cows in overall lactations for all the fertility traits (+10.5% FSCR, +7.7% CR, -0.5 SC, and 35 fewer DO). During the first lactation, S×H cows were superior to HOL cows for all fertility traits (+12.8% FSCR, +8.0% CR, -0.4 SC, and 34 fewer DO). In the second lactation, S×H cows exhibited lower SC (-0.5) and 21 fewer DO than HOL cows. In the third or greater lactations, S×H cows showed higher FSCR (+11.0%) and CR (+12.2%), lower SC (-0.8), and 44 fewer DO than pure HOL cows. In addition, S×H cows had a lower mortality rate (-4.7%) and a lower culling rate (-13.7%) than HOL cows. Due to the higher fertility and lower mortality and culling rates, the S×H cows had higher survival to the second (+9.2%), third (+16.9%), and fourth (+18.7%) calvings than HOL cows. Because of these results, S×H cows had longer LPL (+10.3 mo) than HOL cows. These results indicate that S×H cows had higher fertility and survival than HOL cows on commercial dairy farms in Argentina.

Feasibility of Supplying Ruminally Protected Lysine and Methionine to Periparturient Dairy Cows on the Efficiency of Subsequent Lactation

The objective of this study was to evaluate the effects of supplying ruminally protected Lys (RPL) and ruminally protected Met (RPM) to transition cows' diets on the efficiency of subsequent lactation. A total of 120 prepartum Holstein cows were assigned into four treatments blocked by the anticipated calving date, previous lactation milk yield, number of lactations, and body condition score and fed either RPL, RPM, or the combination (RPML) or control diet (CON) throughout the transition period (3 weeks before till 3 weeks after calving). From 22 to 150 days in milk (DIM), all animals (100 cows) were fed a combination of RPM and RPL (0.17% RPM and 0.41% RPL of DM; n = 25 cows/treatment) as follows; CON–RPML, RPM–RPML, RPL–RPML, and RPML–RPML. Milk production and dry matter intake (DMI) were measured daily; milk and blood samples were taken at 21, 30, 60, 90, 120, and 150 DIM. Supplemented amino acids (AA) were mixed with the premix and added to the total mixed ration during the experiment. DMI (p &lt; 0.001) and energy-corrected milk (ECM, p = 0.04) were higher for cows that were fed RPML–RPML than other cows. Compared with CON–RPML, yields of milk total protein, lactose, and nitrogen efficiency were increased (p &lt; 0.01), whereas milk urea nitrogen (MUN; p = 0.002) was decreased for other treatments. However, supplemental AA did not affect milk lactose percentage, fat yield, feed efficiency, or serum total protein concentration (p &gt; 0.10). Transition cows that consumed AA had a greater peak of milk yield (p &lt; 0.01), as well as quickly reached the peak of milk (p &lt; 0.004). There were differences in β-hydroxybutyrate concentration during the early lactation, with a lower level for AA groups (p &lt; 0.05), and the difference faded with the progression of lactation (p &gt; 0.10). Fertility efficiency as measured by pregnancy rate was improved by supplemental AA during the perinatal period (p &lt; 0.05). In conclusion, transition cows consumed RPM and RPL, increased post-calving DMI, milk production, milk protein yield, nitrogen efficiency, and improved fertility performance.

Review: Preference elicitation methods for appropriate breeding objectives

Breeding objectives of livestock and other agricultural species are usually profit maximising. The selection emphasis placed on specific traits to achieve a breeding objective is often informed by the financial value of a trait to a farm system. However, there are alternative, and complementary approaches to defining both the breeding objective and the selection emphasis placed on traits that are included in associated selection tools. These are based on the preferences of stakeholders, which are often heterogeneous and include broader values and motivations than profit. In this regard, stated preference methods are useful when considering traits that have either no discernible market value or whose value is not fully transferred via the market. Such approaches can guide more appropriate breeding decisions that are amenable to changing societal values, for example with reduced negative environmental externalities. However, while stated preference methods offer promising conceptualisations of value in genetic improvement programmes, there is still a substantial knowledge gap in terms of the current state of research and a catalogue of publications to date. This paper reviews publications of stated preference approaches in the field of livestock breeding (and some relevant crop breeding examples), providing a knowledge base of published applications and promoting their continued development and implementation towards the formulation of appropriate breeding objectives and selection indices. A systematic review of 84 peer-reviewed publications and an aggregate ranking of traits for the most commonly studied subject (cattle) reveals uncertainty in preference estimates which may be driven by (i) a diverse set of non-standardised methodologies, (ii) common oversights in the selection, inclusion and description of traits, and (iii) inaccurate representations of the respondent population. We discuss key considerations to help overcome these limitations, including avoiding methodological confinement to a disciplinary silo and reducing complexity so that the values of broader respondent groups may be accounted for.

Deciphering the Molecular Mechanism Underlying African Animal Trypanosomiasis by Means of the 1000 Bull Genomes Project Genomic Dataset

Simple Summary

Climate change is increasing the risk of spreading vector-borne diseases such as African Animal Trypanosomiasis (AAT), which is causing major economic losses, especially in sub-Saharan African countries. Mainly considering this disease, we have investigated transcriptomic and genomic data from two cattle breeds, namely Boran and N‘Dama, where the former is known for its susceptibility and the latter one for its tolerance to the AAT. Despite the rich literature on this disease, there is still a need to investigate underlying genetic mechanisms to decipher the complex interplay of regulatory SNPs (rSNPs), their corresponding gene expression profiles and the downstream effectors associated with the AAT disease. The findings of this study complement our previous results, which mainly involve the upstream events, including transcription factors (TFs) and their co-operations as well as master regulators. Moreover, our investigation of significant rSNPs and effectors found in the liver, spleen and lymph node tissues of both cattle breeds could enhance the understanding of distinct mechanisms leading to either resistance or susceptibility of cattle breeds.

Abstract

African Animal Trypanosomiasis (AAT) is a neglected tropical disease and spreads by the vector tsetse fly, which carries the infectious Trypanosoma sp. in their saliva. Particularly, this parasitic disease affects the health of livestock, thereby imposing economic constraints on farmers, costing billions of dollars every year, especially in sub-Saharan African countries. Mainly considering the AAT disease as a multistage progression process, we previously performed upstream analysis to identify transcription factors (TFs), their co-operations, over-represented pathways and master regulators. However, downstream analysis, including effectors, corresponding gene expression profiles and their association with the regulatory SNPs (rSNPs), has not yet been established. Therefore, in this study, we aim to investigate the complex interplay of rSNPs, corresponding gene expression and downstream effectors with regard to the AAT disease progression based on two cattle breeds: trypanosusceptible Boran and trypanotolerant N’Dama. Our findings provide mechanistic insights into the effectors involved in the regulation of several signal transduction pathways, thereby differentiating the molecular mechanism with regard to the immune responses of the cattle breeds. The effectors and their associated genes (especially MAPKAPK5, CSK, DOK2, RAC1 and DNMT1) could be promising drug candidates as they orchestrate various downstream regulatory cascades in both cattle breeds.

Supplementing Ruminally Protected Lysine, Methionine, or Combination Improved Milk Production in Transition Dairy Cows

The objectives of this study were to evaluate the effects of dietary supplementation of ruminally protected lysine (RPL), or methionine (RPM), and their combination (RPML) on the production efficiency of transition cows. A total of 120 pre-partum multiparous Holstein cows were assigned to four treatments based on previous lactation milk production, days (d) of pregnancy, lactation, and body condition score (BCS). Cows were fed a basal diet [pre-calving: 1.53 Mcal/kg dry matter (DM) and post-calving: 1.70 Mcal/kg DM] with or without supplemental ruminally protected amino acids (RPAA). Treatments were the basal diets without supplemental amino acids (CONTROL, n = 30), with supplemental methionine (RPM, pre-calving at 0.16% of DM and post-calving at 0.12% of DM, n = 30), with supplemental lysine (RPL, pre-calving at 0.33% of DM and post-calving at 0.24% DM, n = 30), and the combination (RPML, pre-calving at 0.16% RPM + 0.33% RPL of DM and post-calving at 0.12% RPM + 0.24 % RPL DM, n = 30). The dietary content of lysine was balanced to be within 6.157.2% metabolizable protein (MP)-lysine and that of methionine was balanced within 2.1-2.35% MP-methionine. Dry matter intake (DMI) was measured daily. Milk samples were taken on d 7, 14, and 21 days relative to calving (DRC), and milk yields were measured daily. Blood samples were taken on d -21, -14, -7 before expected calving and d 0, 7, 14, and 21 DRC. Data were analyzed using SAS software. There were significant Trt × time interactions (P < 0.01) for DMI pre- and post-calving period. The CON cows had lower DMI than RPM, RPL, and RPML, both pre-calving (P < 0.01) and post-calving periods (P < 0.01). Energy-corrected milk (P < 0.01), milk fat (P < 0.01), protein (P = 0.02), and lactose (P < 0.01) percentage levels were greater for RPM, RPL, and RPML cows compared to CON. Supplementing RPAA assisted in maintaining BCS post-calving than CON (P < 0.01). Blood concentrations of β-hydroxybutyrate decreased with RPM or RPL or the combination pre-calving (P < 0.01) and tended to decrease post-calving (P = 0.10). These results demonstrated that feeding RPL and RPM improved DMI and milk production efficiency, maintained BCS, and reduced β-hydroxybutyrate concentrations of transition cows.

Milk selenium content and speciation in response to supranutritional selenium yeast supplementation in cows

The effects of selenium (Se) yeast supplementation on performance, blood biochemical and antioxidant parameters, and milk Se content and speciation were evaluated. Thirty-six mid-lactation Holstein dairy cows were randomly assigned to 1 of 3 treatments: 1) control (basal diet containing Se at 0.11 mg/kg DM), 2) basal diet + 0.5 mg supplemental Se/kg DM (SY-0.5), and 3) basal diet + 5 mg supplemental Se/kg DM (SY-5). Selenium was supplemented as Se yeast. The trial consisted of a 1-week pretrial period and an 8-week experimental period. Milk somatic cell score decreased with SY-5 supplementation (P < 0.05), but other performance parameters were not affected (P > 0.05). The serum Se concentration increased with the increasing levels of Se yeast supplementation (P < 0.05), however, blood biochemical parameters showed few treatment effects. The antioxidant capacity of dairy cows was improved with Se yeast supplementation reflected in increased serum glutathione peroxidase activity (P < 0.05) and total antioxidant capacity (P = 0.08), and decreased malondialdehyde concentration (P < 0.05). Milk total Se concentration increased with Se dose (P < 0.05). Also, the selenomethionine concentration increased with Se dose from 13.0 ± 0.7 μg/kg in control to 33.1 ± 2.1 μg/kg in SY-0.5 and 530.4 ± 17.5 μg/kg in SY-5 cows (P < 0.05). Similarly, selenocystine concentration increased from 15.6 ± 0.9 μg/kg in control and 18.9 ± 1.1 μg/kg in SY-0.5 to 22.2 ± 1.5 μg/kg in SY-5 cows (P < 0.05). In conclusion, Se yeast is a good organic Se source to produce Se-enriched cow milk with increased Se species including selenomethionine and selenocystine. The results can provide useful information on milk Se species when a high dose Se yeast was supplemented in the cow diet.

Genome-wide scan reveals genetic divergence in Italian Holstein cows bred within PDO cheese production chains

Dairy cattle breeds have been exposed to intense artificial selection for milk production traits over the last fifty years. In Italy, where over 80% of milk is processed into cheese, selection has also focused on cheese-making traits. Due to a deep-rooted tradition in cheese-making, currently fifty Italian cheeses are marked with the Protected Designation of Origin (PDO) label as they proved traditional land of origin and procedures for milk transformation. This study aimed to explore from a genetic point of view if the presence of such diverse productive contexts in Italy have shaped in a different manner the genome of animals originally belonging to a same breed. We analyzed high density genotype data from 1000 Italian Holstein cows born between 2014 and 2018. Those animals were either farmed in one of four Italian PDO consortia or used for drinkable milk production only. Runs of Homozygosity, Bayesian Information Criterion and Discriminant Analysis of Principal Components were used to evaluate potential signs of genetic divergence within the breed. We showed that the analyzed Italian Holstein cows have genomic inbreeding level above 5% in all subgroups, reflecting the presence of ongoing artificial selection in the breed. Our study provided a comprehensive representation of the genetic structure of the Italian Holstein breed, highlighting the presence of potential genetic subgroups due to divergent dairy farming systems. This study can be used to further investigate genetic variants underlying adaptation traits in these subgroups, which in turn might be used to design more specialized breeding programs.

Keeping Dairy Cows for Longer: A Critical Literature Review on Dairy Cow Longevity in High Milk-Producing Countries

Simple Summary

The ability of farms to produce milk sustainably is closely related to dairy cow longevity, i.e., the length of productive life. However, longevity is a very complex feature that depends on all the aspects of the lifespan of a cow and there is no standard definition nor metric to measure it. Measuring longevity is important because it influences the profitability and the environmental impact of farms as well as the welfare of the animals. The objectives of this paper were to review metrics used to measure longevity and describe its status among high milk-producing countries. Increasing dairy cow longevity would imply that an animal has an early age at first calving and a long and profitable productive life. Combining age at first calving, length of productive life, and margin over all (available) costs provides a complete evaluation of longevity. This paper also shows that dairy cow longevity has decreased in most high milk-producing countries over time, which confirm the concerns voiced by the dairy industry and other stakeholders. Increasing cow longevity would reduce health costs and increase cow profitability while improving both animal welfare and quality of life, contributing to a more sustainable dairy industry.

Abstract

The ability of dairy farmers to keep their cows for longer could positively enhance the economic performance of the farms, reduce the environmental footprint of the milk industry, and overall help in justifying a sustainable use of animals for food production. However, there is little published on the current status of cow longevity and we hypothesized that a reason may be a lack of standardization and an over narrow focus of the longevity measure itself. The objectives of this critical literature review were: (1) to review metrics used to measure dairy cow longevity; (2) to describe the status of longevity in high milk-producing countries. Current metrics are limited to either the length of time the animal remains in the herd or if it is alive at a given time. To overcome such a limitation, dairy cow longevity should be defined as an animal having an early age at first calving and a long productive life spent in profitable milk production. Combining age at first calving, length of productive life, and margin over all costs would provide a more comprehensive evaluation of longevity by covering both early life conditions and the length of time the animal remains in the herd once it starts to contribute to the farm revenues, as well as the overall animal health and quality of life. This review confirms that dairy cow longevity has decreased in most high milk-producing countries over time and its relationship with milk yield is not straight forward. Increasing cow longevity by reducing involuntary culling would cut health costs, increase cow lifetime profitability, improve animal welfare, and could contribute towards a more sustainable dairy industry while optimizing dairy farmers’ efficiency in the overall use of resources available.

Invited review: The future of selection decisions and breeding programs: What are we breeding for, and who decides?

Genetic selection has been a very successful tool for the long-term improvement of livestock populations, and the rapid adoption of genomic selection over the last decade has doubled the rate of gain in some populations. Breeding programs seek to identify genetically superior parents of the next generation, typically as a function of an index that combines information about many economically important traits into a single number. In the United States, the data that drive this system are collected through the national dairy herd improvement program that began more than a century ago. The resulting information about animal performance, pedigree, and genotype is used to compute genomic evaluations for comparing and ranking animals for selection. However, the full expression of genetic potential requires that animals are placed in environments that can support such performance. The Agricultural Research Service of the US Department of Agriculture and the Council on Dairy Cattle Breeding collaborate to deliver state-of-the-art genomic evaluations to the dairy industry. Today, most breeding stock are selected and marketed using the net merit dollars (NM$) selection index, which evolved from 2 traits in 1926 (milk and fat yield) to a combination of 36 individual traits following the last NM$ update in 2018. Updates to NM$ require the estimation of many different values, and it can be difficult to achieve consensus from stakeholders on what should be added to, or removed from, the index at each review, and how those traits should be weighted. Over time, the majority of the emphasis in the index has shifted from yield traits to fertility, health, and fitness traits. Phenotypes for some of these new traits are difficult or expensive to measure, or require changes to on-farm habits that have not been widely adopted. This is driving interest in sensor-based systems that provide continuous measurements of the farm environment, individual animal performance, and detailed milk composition. There is also a need to capture more detailed data about the environment in which animals perform, including information about feeding, housing, milking systems, and infectious and parasitic load. However, many challenges accompany these new technologies, including a lack of standardization or validation, need for high-speed internet connections, increased computational requirements, and interpretations that are often not backed by direct observations of biological phenomena. This work will describe how US selection objectives are developed, as well as discuss opportunities and challenges associated with new technologies for measuring and recording animal performance.

Follicular Fluid Metabolite Changes in Dairy Cows with Inactive Ovary Identified Using Untargeted Metabolomics

The metabolism of dairy cows with inactive ovaries differs from that of healthy dairy cows. However, the molecular mechanisms underpinning these physiological and metabolic changes remain unclear. The purpose of this study was to investigate follicular fluid metabolite changes in dairy cows with inactive ovaries. Untargeted metabolomics technology and multivariate statistical analysis were used to screen differential metabolites in follicular fluid samples between inactive ovaries and estrus cows at 45-60 d postpartum. Fourteen differential metabolites were identified, consisting of amino acids, lipids, sugars, and nucleotides. When compared with healthy animal samples, eight follicular fluid metabolites were significantly increased, and six metabolites were significantly decreased in dairy cows with inactive ovaries. Metabolic pathway analyses indicated that differential metabolites were primarily involved in glycerol phospholipid metabolism, arachidonic acid metabolism, valine, leucine and isoleucine biosynthesis, and phenylalanine metabolism. These metabolites and their enrichment pathways indicate that the enhancement of lipid metabolism and the weakening of carbohydrate production of amino acids in dairy cows with impaired follicular development. Overall, these data provide a better understanding of the changes that could affect follicular development during the postpartum period and lay the ground for further investigations.

Validation of genomic predictions for a lifetime merit selection index for the US dairy industry

Selection indices are a critical component of many breeding programs. A common purpose of a selection index is to predict an animal's genetic potential for total economic merit. The objective of this study was to evaluate retrospectively whether a specific selection index comprising genomically-enhanced predicted transmitting abilities had the ability to predict observed lifetime profit in US Holstein animals. The selection index evaluated was dairy wellness profit (DWP$). In total, 2,185 animals were included in this study. Index values were used to rank and assign animals to quartiles (genetic groups: worst 25%, 26-50%, 51-75%, and best 25%). Generalized linear mixed effects models were applied to estimate the associations between index quartile and defined economic outcomes. Similar analyses were conducted to estimate associations between index quartile and observed phenotype to characterize the extent to which profitability outcomes were driven by economically relevant production and health traits. Differences in lifetime profit and annuity value between the best and worst genetic groups for DWP$ were $811 (±297) and $232 (±88), respectively. Significant differences were also observed between top and bottom quartiles for milk production (8,077 kg), fat production (336 kg), protein production (264 kg), live calves (0.5), time spent in the lactating herd (6.6 mo), and cow mortality (8.4%). Additionally, differences in disease incidence were significant between the best and worst DWP$ quartiles for metritis (5.2%), mastitis (14.9%), and lameness (15.9%). The observed results of this study demonstrated the ability of DWP$ predictions to predict lifetime profitability of Holstein animals and its potential utility as a tool to guide selection and breeding programs. Improving DWP$ through genetic selection, when combined with good management practices, provides an opportunity for dairy producers to improve overall herd profitability.

Genome-Wide Association Study and Pathway Analysis for Female Fertility Traits in Iranian Holstein Cattle

Female fertility is an important trait that contributes to cow’s profitability and it can be improved by genomic information. The objective of this study was to detect genomic regions and variants affecting fertility traits in Iranian Holstein cattle. A data set comprised of female fertility records and 3,452,730 pedigree information from Iranian Holstein cattle were used to predict the breeding values, which were then employed to estimate the de-regressed proofs (DRP) of genotyped animals. A total of 878 animals with DRP records and 54k SNP markers were utilized in the genome-wide association study (GWAS). The GWAS was performed using a linear regression model with SNP genotype as a linear covariate. The results showed that an SNP on BTA19, ARS-BFGL-NGS-33473, was the most significant SNP associated with days from calving to first service. In total, [69] significant SNPs were located within 27 candidate genes. Novel potential candidate genes include OSTN, DPP6, EphA5, CADPS2, Rfc1, ADGRB3, Myo3a, C10H14orf93, KIAA1217, RBPJL, SLC18A2, GARNL3, NCALD, ASPH, ASIC2, OR3A1, CHRNB4, CACNA2D2, DLGAP1, GRIN2A and ME3. These genes are involved in different pathways relevant to female fertility and other characteristics in mammals. Gene set enrichment analysis showed that thirteen GO terms had significant overrepresentation of genes statistically associated with female fertility traits. The results of network analysis identified CCNB1 gene as a hub gene in the progesterone-mediated oocyte maturation pathway, significantly associated with age at first calving. The candidate genes identified in this study can be utilized in genomic tests to improve reproductive performance in Holstein cattle.

Driving Sustainability in Dairy Farming from a TBL Perspective: Insights from a Case Study in the West Region of Santa Catarina, Brazil

All companies in agribusiness supply chains need to be aware of the best use of available resources, which demands an integrated assessment of environmental, economic and social aspects, i.e., the Triple Bottom Line (TBL). Such analysis allows us to get a more balanced and complete understanding of the real performance of companies, supply chains and industries. Companies in the upstream of agribusinesses supply chains present some limitations, but can contribute significantly to the overall sustainability of the entire value chain. The objective of this research was to understand the role of the drivers of sustainability in dairy farming from a TBL perspective, such as assistance to producers and the value chain, and the use of better technology and management practices. A sample of 54 rural farms in the dairy supply chain of the western region of Santa Catarina, Brazil, was used to test four hypotheses about what can drive sustainability. Furthermore, first- and second-order structural equation models using SMART PLS software were used for the analysis of the data. The results obtained show that social sustainability is positively influenced by the use of good management practices, and the latter, as well as public policies, positively influence economic sustainability. Furthermore, it was found that improvements in production techniques positively influence environmental sustainability, and this is mostly influenced by the use of good management practices, and less so by policies directed at the supply chain. Finally, from the analysis of the second-order variable for sustainability, it was highlighted that the economic dimension prevails in the eyes of the farmers, as the main dimension of sustainability, and that environmental aspects are still neglected.

The effects of improved performance in the U.S. dairy cattle industry on environmental impacts between 2007 and 2017

The U.S. dairy industry considerably reduced environmental impacts between 1944 and 2007, primarily through improved dairy cow productivity. However, although milk yield per cow has increased over the past decade, whole-system environmental impact analyses have not been conducted over this time period, during which environmental modeling science has improved considerably. The objective of this study was to compare the environmental impact of U.S. dairy cattle production in 2007–2017. A deterministic model based on population demographics, metabolism, and nutrient requirements of dairy cattle was used to estimate resource inputs, nutrient excretion, and greenhouse gas (GHG) emissions per 1.0 × 10⁶ t (one million metric t or MMT) of energy-corrected milk (ECM) produced in 2007 and 2017. System boundaries extended from the manufacture and transport of cropping inputs to milk at the farm gate. Milk transport, processing, and retail were not included. Dairy systems were modeled using typical management practices, herd population dynamics, and production data from U.S. dairy farms. Cropping data were sourced from national databases. The resources required to produce 1.0 MMT ECM in 2017 were considerably reduced relative to those required in 2007, with 2017 production systems using 74.8% of the cattle, 82.7% of the feedstuffs, 79.2% of the land, and 69.5% of the water as compared to 2007. Waste outputs were similarly reduced, with the 2017 U.S. dairy industry producing 79.4%, 82.5%, and 85.7% of the manure, N, and P excretion, respectively. Dairy production in 2017 emitted 80.9% of the CH₄ and 81.5% of the N₂O per 1.0 MMT ECM compared to 2007. Enteric and manure emissions contributed the major proportion (80%) of GHG emissions per unit of milk, with lesser contributions from cropping (7.6%) and fertilizer application (5.3%). The GHG emissions per 1.0 MMT ECM produced in 2017 were 80.8% of equivalent milk production in 2007. Consequently, although total U.S. ECM production increased by 24.9% between 2007 and 2017, total GHG emissions from this milk production increased by only 1.0%. In line with previous historical analyses, the U.S. dairy industry has made remarkable productivity gains and environmental progress over time. To maintain this culture of continuous improvement, the dairy industry must build on gains made to date and demonstrate its commitment to reducing environmental impacts while improving both economic viability and social acceptability.

Genetic and genomic analysis of long insemination interval in Israeli dairy cattle as an indicator of early abortions

One of the causes of observed low fertility is embryo loss after fertilization. Previous findings suggested that more than half of fertilizations result in embryo loss before pregnancy is detected. We proposed reinsemination between 49 and 100 d after the first insemination as an indicator trait for early abortion (EA) in dairy cattle based on the mean estrus interval of 21 d. This trait was compared with conception rate from first insemination and conception status, computed as the inverse of the number of inseminations to conception. Animal model variance components were estimated by REML, including parents and grandparents of cows with records. First-parity heritability for first insemination conception rate was 3%. In the multitrait analysis of parities 1 to 3 for putative EA, heritabilities ranged from 8.9% for first parity to 10.4% for second parity. All genetic correlations were >0.9, whereas all environmental correlations were <0.12. The variance component for the service sire effect for putative EA rate was less than half the variance component for conception rate. Thus, genetic control of the 2 traits is clearly different, and analysis of EA rate by a single-trait animal model is justified. Genetic evaluation for putative EA was computed using this model, including all first- through third-parity cows with freshening dates from January 1, 1985, through December 31, 2016, that either became pregnant on first insemination or were reinseminated between 49 and 100 d after the first insemination. All known parents and grandparents of cows with records were included in the analysis. The regression of the breeding value for non-abortion rate on the cows' birth year was 0.083%/yr. The genetic correlation between first-parity EA and conception status was 0.995. The genetic correlations between first-parity EA and milk, fat, and protein production were all negative, whereas the genetic correlation between EA and herd life was 0.33. Inclusion of putative EA in the selection index instead of conception status resulted in 10 to 20% greater genetic gain for both fertility traits. In a genome-wide association study based on 1,200 dairy bulls with reliabilities >50% for abortion rate genotyped for 41,000 markers, 6 markers were found with nominal probabilities of <10^-12 to reject the null hypothesis of no effect on EA rate. The markers with the lowest probabilities for EA rate were also included among the markers with the lowest probabilities for female fertility, but not vice versa. The marker explaining the most variance for abortion rate is located within the ABCA9 gene, which is found within an ATP-binding cassette (ABC) genes cluster. The ABC family is the major class of primary active transporters in the placenta.

Causes, types, etiological agents, prevalence, diagnosis, treatment, prevention, effects on human health and future aspects of bovine mastitis

Mastitis is among the most common and challenging diseases of dairy animals. It is an inflammation of udder tissues due to physical damage, chemical irritation, or infection caused by certain pathogens. Bovine mastitis has been known for ages, but its complex etiology and multi-factorial nature make it difficult to control. Mastitis may have a negative impact on human health by inducing antibiotic-resistant pathogens that may spread, which is threatening. Researchers are continuously struggling to devise suitable methods for mastitis control. Management strategies are mainly focused on disease prevention by farm management which includes proper hygiene, trained staff to monitor minor changes in the udder or milk, and better diagnostic and treatment methods. New technologies which have the potential to unravel this complicated disease include improved diagnostic tools, based on advanced genomics or proteomics, prevention, based on vaccines and immune modulators, and metabolic products of probiotics such as bacteriocins and gene therapy.

Managing the transition from purebred to rotational crossbred dairy cattle herds: three technical pathways from a retrospective case-study analysis

The growing interest in rotational crossbreeding in Western countries is due to its potential to improve reproductive and health performances of cows. Although a large amount of research focuses on assessing crossbred cows' performances, how to manage the transition from purebred to rotational crossbred herds is under-explored. Based on a retrospective analysis of French dairy herd case studies, we aimed to identify and characterise technical pathways to make such a transition. In 2018, we performed semi-directive interviews on 26 commercial dairy farms. Data were collected to describe changes in breeding, replacement and culling management practices from the first crossbred mating with purebred cows to the management of a mainly crossbred herd in 2018. Based on a multivariate analysis, we identified two main guidelines structuring technical pathways to move towards rotational crossbred herds: (i) the depth and scale of change (i.e. farm v. herd) associated with the introduction of rotational crossbreeding in the whole-farm dynamics and (ii) the changes in herd replacement and breeding practices to adapt to the evolution of herd demographics induced by the evolution of the dairy crossbred mating rate over time (high from the beginning v. distributed over time). Hierarchical clustering discriminated three groups of farmers differing in their technical pathway to move towards a rotational crossbred herd. In pathway 1, farmers customised one or several rotational crossbreeding schemes to support whole-farm transition towards an organic or grass-based system. Once the scheme stabilised, they quickly implemented it and had to readjust replacement and culling practices to regulate imbalance in herd demographics induced by the improvement in cow fertility. In pathway 2, farmers also customised one or several rotational crossbreeding schemes to support whole-farm redesign but they implemented it more gradually in the herd, which induced no major imbalance in herd demographics. In pathway 3, farmers predefined a relatively well-known rotational crossbreeding scheme to correct fertility issues of purebred cows without any changes at the farm level. They implemented it quickly from the beginning and had to adapt herd replacement and culling to regulate imbalance in herd demographics induced by the improvement in cow fertility. These first empirical evidences on how dairy farmers manage the transition from a purebred to rotational crossbred herd provide original scientific and operational contributions.

Identification of loci associated with conception rate in primiparous Holstein cows

Background

Subfertility is a major issue facing the dairy industry as the average US Holstein cow conception rate (CCR) is approximately 35%. The genetics underlying the physiological processes responsible for CCR, the proportion of cows able to conceive and maintain a pregnancy at each breeding, are not well characterized. The objectives of this study were to identify loci, positional candidate genes, and transcription factor binding sites (TFBS) associated with CCR and determine if there was a genetic correlation between CCR and milk production in primiparous Holstein cows. Cows were bred via artificial insemination (AI) at either observed estrus or timed AI and pregnancy status was determined at day 35 post-insemination. Additive, dominant, and recessive efficient mixed model association expedited (EMMAX) models were used in two genome-wide association analyses (GWAA). One GWAA focused on CCR at first service (CCR1) comparing cows that conceived and maintained pregnancy to day 35 after the first AI (n = 494) to those that were open after the first AI (n = 538). The second GWAA investigated loci associated with the number of times bred (TBRD) required for conception in cows that either conceived after the first AI (n = 494) or repeated services (n = 472).

Results

The CCR1 GWAA identified 123, 198, and 76 loci associated (P < 5 × 10^− 08) in additive, dominant, and recessive models, respectively. The TBRD GWAA identified 66, 95, and 33 loci associated (P < 5 × 10^− 08) in additive, dominant, and recessive models, respectively. Four of the top five loci were shared in CCR1 and TBRD for each GWAA model. Many of the associated loci harbored positional candidate genes and TFBS with putative functional relevance to fertility. Thirty-six of the loci were validated in previous GWAA studies across multiple breeds. None of the CCR1 or TBRD associated loci were associated with milk production, nor was their significance with phenotypic and genetic correlations to 305-day milk production.

Conclusions

The identification and validation of loci, positional candidate genes, and TFBS associated with CCR1 and TBRD can be utilized to improve, and further characterize the processes involved in cattle fertility.

Genetic and environmental analysis of diseases with major economic impact in Israeli Holsteins

Incidences of ketosis, metritis, mastitis, and retained placenta were studied in Israeli Holstein cows calving between 2008 and 2017. These diseases were selected based on their economic impact. Ketosis, metritis, and retained placenta were scored dichotomously. Mastitis was scored as absent, a single occurrence during the lactation, or more than 1 occurrence. Ketosis and metritis were recorded during the first 21 d after calving, retained placenta during the first 5 d after calving, and mastitis up to 305 d in milk. The effects of herd-year-season, calving age, month of calving, gestation length, and occurrence of dystocia were included in the first-parity analysis models. All effects were significant for metritis and retained placenta. For ketosis, all effects were significant, except for gestation length. For mastitis, only the effects of herd-year-season and calving age were significant. Variance components were computed by the multitrait animal model. The 4 diseases were analyzed jointly based on first-parity records, and each disease was analyzed separately for parities 1 to 3 with the different parities considered separate traits. The 4 disease traits in first parity were also analyzed jointly with the 6 major traits included in the Israeli breeding index: milk, fat, and protein production; somatic cell score; female fertility; and longevity. Heritability was highest for metritis and lowest for mastitis, but all heritabilities were <0.07, similar to previous studies. For all 4 diseases, genetic correlations among the first 3 parities were >0.65, and all residual correlations were <0.07. Selection of herd-years assumed to have more accurate recording of mastitis did not result in higher heritability estimates. Genetic correlations between the disease traits and milk, fat, and protein production were economically unfavorable, while correlations between the disease traits and somatic cell score, female fertility, and longevity were economically favorable. Expected genetic changes in the disease traits after 10 yr of selection with the current Israeli breeding index were all <1%, except for ketosis, which was predicted to increase by 1.5%. Inclusion of these traits in a proposed index with the disease traits constituting 7% of the index would result in only marginal improvements for the disease traits and adversely affect genetic gain for fat and protein production. Thus, inclusion of these traits in the breeding index cannot be justified economically.

Genetic parameter estimates for body conformation traits using composite index, principal component, and factor analysis

Information about genetic parameters is population specific and it is crucial for designing animal breeding programs and predicting response to selection. This study was carried out to estimate the genetic parameters for 23 body conformation traits of 45,517 Chinese Holstein reared in Eastern China from 1995 to 2017 with the Bayesian inference method using a linear animal mixed model. The methods to integrate these traits included (1) using the composite index from the Dairy Association of China and (2) applying principal component analysis and factor analysis to explore the relationship between the conformation traits. Estimates of heritability using the composite index were low (0.04; feet and legs) to moderate (0.23; body capacity). Strong genetic correlations were observed between the individual body conformation traits. Both principal components (1 to 7; eigenvalues ≥ 1) and latent factors (1 to 7; eigenvalues ≥ 1) explained 60.37% of total variability. Principal component 1 and factor 1 accounted for the traits that are usually associated with milk production. Moderate to low heritability were estimated through multi-trait analysis for principal components (from 0.07 to 0.21) and latent factors (from 0.07 to 0.23). Genetic correlations among the 2 multivariate techniques are typically lower compared with the one existing among the measured traits. Results from these analyses suggest the possibility of using both principal component analysis and factor analysis in morphological evaluation, simplifying the information given by the body conformation traits into new variables that could be useful for the genetic improvement of the Chinese Holstein population. This information could also be used to avoid analyzing large number of correlated traits, thereby improving precision and reducing computation burdens to analyze large and complex data.

A 100-Year Review: Identification and genetic selection of economically important traits in dairy cattle

Over the past 100 yr, the range of traits considered for genetic selection in dairy cattle populations has progressed to meet the demands of both industry and society. At the turn of the 20th century, dairy farmers were interested in increasing milk production; however, a systematic strategy for selection was not available. Organized milk performance recording took shape, followed quickly by conformation scoring. Methodological advances in both genetic theory and statistics around the middle of the century, together with technological innovations in computing, paved the way for powerful multitrait analyses. As more sophisticated analytical techniques for traits were developed and incorporated into selection programs, production began to increase rapidly, and the wheels of genetic progress began to turn. By the end of the century, the focus of selection had moved away from being purely production oriented toward a more balanced breeding goal. This shift occurred partly due to increasing health and fertility issues and partly due to societal pressure and welfare concerns. Traits encompassing longevity, fertility, calving, health, and workability have now been integrated into selection indices. Current research focuses on fitness, health, welfare, milk quality, and environmental sustainability, underlying the concentrated emphasis on a more comprehensive breeding goal. In the future, on-farm sensors, data loggers, precision measurement techniques, and other technological aids will provide even more data for use in selection, and the difficulty will lie not in measuring phenotypes but rather in choosing which traits to select for.

Derivation of economic values for production traits in aquaculture species

BACKGROUND

In breeding programs for aquaculture species, breeding goal traits are often weighted based on the desired gains but economic gain would be higher if economic values were used instead. The objectives of this study were: (1) to develop a bio-economic model to derive economic values for aquaculture species, (2) to apply the model to determine the economic importance and economic values of traits in a case-study on gilthead seabream, and (3) to validate the model by comparison with a profit equation for a simplified production system.

METHODS

A bio-economic model was developed to simulate a grow-out farm for gilthead seabream, and then used to simulate gross margin at the current levels of the traits and after one genetic standard deviation change in each trait with the other traits remaining unchanged. Economic values were derived for the traits included in the breeding goal: thermal growth coefficient (TGC), thermal feed intake coefficient (TFC), mortality rate (M), and standard deviation of harvest weight ([Formula: see text]). For a simplified production system, improvement in TGC was assumed to affect harvest weight instead of growing period. Using the bio-economic model and a profit equation, economic values were derived for harvest weight, cumulative feed intake at harvest, and overall survival.

RESULTS

Changes in gross margin showed that the order of economic importance of the traits was: TGC, TFC, M, and [Formula: see text]. Economic values in € (kg production)^-1 (trait unit)^-1 were: 0.40 for TGC, -0.45 for TFC, -7.7 for M, and -0.0011 to -0.0010 for [Formula: see text]. For the simplified production system, similar economic values were obtained with the bio-economic model and the profit equation. The advantage of the profit equation is its simplicity, while that of the bio-economic model is that it can be applied to any aquaculture species, because it can include any limiting factor and/or environmental condition that affects production.

CONCLUSIONS

We confirmed the validity of the bio-economic model. TGC is the most important trait to improve, followed by TFC and M, and the effect of [Formula: see text] on gross margin is small.

Unravelling the genomic architecture of bull fertility in Holstein cattle

BACKGROUND

Fertility is considered an important economic trait in dairy cattle. Most studies have investigated cow fertility while bull fertility has received much less consideration. The main objective of this study was to perform a comprehensive genomic analysis in order to unravel the genomic architecture underlying sire fertility in Holstein dairy cattle. The analysis included the application of alternative genome-wide association mapping approaches and the subsequent use of diverse gene set enrichment tools.

RESULTS

The association analyses identified at least eight genomic regions strongly associated with bull fertility. Most of these regions harbor genes, such as KAT8, CKB, TDRD9 and IGF1R, with functions related to sperm biology, including sperm development, motility and sperm-egg interaction. Moreover, the gene set analyses revealed many significant functional terms, including fertilization, sperm motility, calcium channel regulation, and SNARE proteins. Most of these terms are directly implicated in sperm physiology and male fertility.

CONCLUSIONS

This study contributes to the identification of genetic variants and biological processes underlying sire fertility. These findings can provide opportunities for improving bull fertility via marker-assisted selection.

The Effect of Sperm Morphology and Sire Fertility on Calving Rate of Finnish Ayrshire AI Bulls

Good-quality semen is a prerequisite for successful and profitable artificial insemination (AI) of modern dairy cattle. Fertility of the bulls is evaluated with andrological examinations and semen analyses, such as morphology. However, little attention has been paid to the inheritance of bull fertility. In this study, we correlated sperm morphology, birth year and station of 695 AI bulls with calving rate (CR). Sperm morphology was clearly associated with CR underlining the usefulness of morphological examination in the assessment of fertility. The correlation between the proportion of normal spermatozoa and CR was significant (p < 0.001). No significant differences were detected between stations or birth years. We also compared the CR of 695 AI bulls with the CR of their 27 sires to study the inheritance of fertility. Sire's CR did not correlate with the CR of the sons (p = 0.218). This result indicates that at least when sires of acceptable CR are used to produce sons for use in AI the inheritance of CR is not significantly correlated.

Polymorphisms in the promoter region of the bovine lactoferrin gene influence milk somatic cell score and milk production traits in Chinese Holstein cows

Lactoferrin is an iron-binding protein found in cow's milk that plays an important role in preventing mastitis caused by intramammary infection. In this study, 20 Chinese Holstein cows were selected randomly for PCR amplification and sequencing of the bovine lactoferrin gene promoter region and used for SNP discovery in the region between nucleotide positions -461 to -132. Three SNPs (-270T>C, -190G>A and -156A>G) were identified in bovine lactoferrin, then Chinese Holstein cows (n=866) were genotyped using Sequenom MassARRAY (Sequenom Inc., San Diego, CA) based on the previous SNP information in this study, and the associations between SNPs or haplotype and milk somatic cell score (SCS) and production traits were analyzed by the least squares method in the GLM procedure of SAS. SNPs -270T>C and -156A>G showed close linkage disequilibrium (r(2)=0.76). The SNP -190G>A showed a significant association with SCS, and individuals with genotype GG had higher SCS than genotypes AG and AA. Associations were found between the SNPs -270T>C and -190G>A with SCS and the milk composition. The software MatInspector revealed that these SNPs were located within several potential transcription factor binding sites, including NF-κB p50, KLF7 and SP1, and may alter gene expression, but further investigation will be required to elucidate the biological and practical relevance of these SNPs.

Overlap in genomic variation associated with milk fat composition in Holstein Friesian and Dutch native dual-purpose breeds

The aim of this study was to identify if genomic variations associated with fatty acid (FA) composition are similar between the Holstein-Friesian (HF) and native dual-purpose breeds used in the Dutch dairy industry. Phenotypic and genotypic information were available for the breeds Meuse-Rhine-Yssel (MRY), Dutch Friesian (DF), Groningen White Headed (GWH), and HF. First, the reliability of genomic breeding values of the native Dutch dual-purpose cattle breeds MRY, DF, and GWH was evaluated using single nucleotide polymorphism (SNP) effects estimated in HF, including all SNP or subsets with stronger associations in HF. Second, the genomic variation of the regions associated with FA composition in HF (regions on Bos taurus autosome 5, 14, and 26), were studied in the different breeds. Finally, similarities in genotype and allele frequencies between MRY, DF, GWH, and HF breeds were assessed for specific regions associated with FA composition. On average across the traits, the highest reliabilities of genomic prediction were estimated for GWH (0.158) and DF (0.116) when the 8 to 22 SNP with the strongest association in HF were included. With the same set of SNP, GEBV for MRY were the least reliable (0.022). This indicates that on average only 2 (MRY) to 16% (GWH) of the genomic variation in HF is shared with the native Dutch dual-purpose breeds. The comparison of predicted variances of different regions associated with milk and milk fat composition showed that breeds clearly differed in genomic variation within these regions. Finally, the correlations of allele frequencies between breeds across the 8 to 22 SNP with the strongest association in HF were around 0.8 between the Dutch native dual-purpose breeds, whereas the correlations between the native breeds and HF were clearly lower and around 0.5. There was no consistent relationship between the reliabilities of genomic prediction for a specific breed and the correlation between the allele frequencies of this breed and HF. In conclusion, most of the genomic variation associated with FA composition in the Dutch dual-purpose breeds appears to be breed-specific. Furthermore, the minor allele frequencies of genes having an effect on the milk FA composition in HF were shown to be much smaller in the breeds MRY, DF, and GWH, especially for the MRY breed.

Association of IL8 -105G/A with mastitis somatic cell score in Chinese Holstein dairy cows

The single nucleotide polymorphisms (SNPs) in the 5' upstream of bovine IL8 gene were investigated in 810 Chinese Holstein cows from 35 bull families in a dairy farm in Shanghai using polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) technique. The Real-time PCR and Western blot were used to detect the mRNA and protein levels of genotype Chinese Holstein dairy cows. The results showed that one SNP -105G>A was detected, designating three genotypes (GG, GA and AA) with respective frequencies of 0.38, 0.46, and 0.16. The significant association of the SNP -105G>A with somatic cell score (SCS) was identified. Genotype GG had a significantly lower SCS than genotype GA or AA (P < 0.01), and the relative mRNA expression and protein level of GG was found to be the highest. These results suggest that the genotype GG may be a useful genetic marker for mastitis resistance selection and breeding in Chinese Holstein dairy cows.