Veterinary dairy herd fertility service provision in seasonal and non-seasonal dairy industries - a comparison

The decline in dairy herd fertility internationally has highlighted the limited impact of traditional veterinary approaches to bovine fertility management. Three questionnaire surveys were conducted at buiatrics conferences attended by veterinary practitioners on veterinary dairy herd fertility services (HFS) in countries with a seasonal (Ireland, 47 respondents) and non-seasonal breeding model (The Netherlands, 44 respondents and Portugal, 31 respondents). Of the 122 respondents, 73 (60%) provided a HFS and 49 (40%) did not. The majority (76%) of all practitioners who responded stated that bovine fertility had declined in their practice clients' herds with inadequate cow management, inadequate nutrition and increased milk yield as the most important putative causes. The type of clients who adopted a herd fertility service were deemed more educated than average (70% of respondents), and/or had fertility problems (58%) and/or large herds (53%). The main components of this service were routine postpartum examinations (95% of respondents), fertility records analysis (75%) and ultrasound pregnancy examinations (69%). The number of planned visits per annum varied between an average of four in Ireland, where breeding is seasonal, and 23 in Portugal, where breeding is year-round. The benefits to both the practitioner and their clients from running a HFS were cited as better fertility, financial rewards and job satisfaction. For practitioners who did not run a HFS the main reasons given were no client demand (55%) and lack of fertility records (33%). Better economic evidence to convince clients of the cost-benefit of such a service was seen as a major constraint to adoption of this service by 67% of practitioners

Monoallelic maternal expression of STAT5A affects embryonic survival in cattle

<p>Abstract</p> <p>Background</p> <p>Reproductive disorders and infertility are surprisingly common in the human population as well as in other species. The decrease in fertility is a major cause of cow culling and economic loss in the dairy herd. The conception rate has been declining for the past 30–50 years. Conception rate is the product of fertilization and embryonic survival rates. In a previous study, we have identified associations of several single nucleotide polymorphisms (SNPs) in the signal transducer and activator 5A (<it>STAT5A</it>) with fertilization and survival rates in an <it>in </it>vitro experimental system. The objectives of this study are to fine map the <it>STAT5A </it>region in a search for causative mutations and to investigate the parent of origin expression of this gene.</p> <p>Results</p> <p>We have performed a total of 5,222 fertilizations and produced a total of 3,696 in vitro fertilized embryos using gametes from 440 cows and eight bulls. A total of 37 SNPs were developed in a 63.4-kb region of genomic sequence that includes <it>STAT5A</it>, <it>STAT3</it>, and upstream and downstream sequences of these genes. SNP153137 (G/C) in exon 8 of <it>STAT5A </it>was associated with a significant variability in embryonic survival and fertilization rate compared to all other examined SNPs. Expression analysis revealed that <it>STAT5A </it>is primarily monoallelically expressed in early embryonic stages but biallelically expressed in later fetal stages. Furthermore, the occurrence of monoallelic maternal expression of <it>STAT5A </it>was significantly higher in blastocysts, while paternal expression was more frequent in degenerative embryos.</p> <p>Conclusion</p> <p>Our results imply that <it>STAT5A </it>affects embryonic survival in a manner influenced by developmental stage and allele parent of origin.</p

Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models

Genotype by environment interactions (GEI) have attracted increasing attention in tropical breeding programs because of the variety of production systems involved. In this work, we assessed GEI in 450-day adjusted weight (W450) Nelore cattle from 366 Brazilian herds by comparing traditional univariate single-environment model analysis (UM) and random regression first order reaction norm models for six environmental variables: standard deviations of herd-year (RRMw) and herd-year-season-management (RRMw-m) groups for mean W450, standard deviations of herd-year (RRMg) and herd-year-season-management (RRMg-m) groups adjusted for 365-450 days weight gain (G450) averages, and two iterative algorithms using herd-year-season-management group solution estimates from a first RRMw-m and RRMg-m analysis (RRMITw-m and RRMITg-m, respectively). The RRM results showed similar tendencies in the variance components and heritability estimates along environmental gradient. Some of the variation among RRM estimates may have been related to the precision of the predictor and to correlations between environmental variables and the likely components of the weight trait. GEI, which was assessed by estimating the genetic correlation surfaces, had values < 0.5 between extreme environments in all models. Regression analyses showed that the correlation between the expected progeny differences for UM and the corresponding differences estimated by RRM was higher in intermediate and favorable environments than in unfavorable environments (p < 0.0001)

Gene expression patterns in four brain areas associate with quantitative measure of estrous behavior in dairy cows

<p>Abstract</p> <p>Background</p> <p>The decline noticed in several fertility traits of dairy cattle over the past few decades is of major concern. Understanding of the genomic factors underlying fertility, which could have potential applications to improve fertility, is very limited. Here, we aimed to identify and study those genes that associated with a key fertility trait namely estrous behavior, among genes expressed in four bovine brain areas (hippocampus, amygdala, dorsal hypothalamus and ventral hypothalamus), either at the start of estrous cycle, or at mid cycle, or regardless of the phase of cycle.</p> <p>Results</p> <p>An average heat score was calculated for each of 28 primiparous cows in which estrous behavior was recorded for at least two consecutive estrous cycles starting from 30 days post-partum. Gene expression was then measured in brain tissue samples collected from these cows, 14 of which were sacrificed at the start of estrus and 14 around mid cycle. For each brain area, gene expression was modeled as a function of the orthogonally transformed average heat score values using a Bayesian hierarchical mixed model. Genes whose expression patterns showed significant linear or quadratic relationships with heat scores were identified. These included genes expected to be related to estrous behavior as they influence states like socio-sexual behavior, anxiety, stress and feeding motivation (<it>OXT, AVP, POMC, MCHR1</it>), but also genes whose association with estrous behavior is novel and warrants further investigation.</p> <p>Conclusions</p> <p>Several genes were identified whose expression levels in the bovine brain associated with the level of expression of estrous behavior. The genes <it>OXT </it>and <it>AVP </it>play major roles in regulating estrous behavior in dairy cows. Genes related to neurotransmission and neuronal plasticity are also involved in estrous regulation, with several genes and processes expressed in mid-cycle probably contributing to proper expression of estrous behavior in the next estrus. Studying these genes and the processes they control improves our understanding of the genomic regulation of estrous behavior expression.</p

Utility of whole-genome sequence data for across-breed genomic prediction

Background: Genomic prediction (GP) across breeds has so far resulted in low accuracies of the predicted genomic breeding values. Our objective was to evaluate whether using whole-genome sequence (WGS) instead of low-density markers can improve GP across breeds, especially when markers are pre-selected from a genome-wide association study (GWAS), and to test our hypothesis that many non-causal markers in WGS data have a diluting effect on accuracy of across-breed prediction. Methods: Estimated breeding values for stature and bovine high-density (HD) genotypes were available for 595 Jersey bulls from New Zealand, 957 Holstein bulls from New Zealand and 5553 Holstein bulls from the Netherlands. BovineHD genotypes for all bulls were imputed to WGS using Beagle4 and Minimac2. Genomic prediction across the three populations was performed with ASReml4, with each population used as single reference and as single validation sets. In addition to the 50k, HD and WGS, markers that were significantly associated with stature in a large meta-GWAS analysis were selected and used for prediction, resulting in 10 prediction scenarios. Furthermore, we estimated the proportion of genetic variance captured by markers in each scenario. Results: Across breeds, 50k, HD and WGS markers resulted in very low accuracies of prediction ranging from − 0.04 to 0.13. Accuracies were higher in scenarios with pre-selected markers from a meta-GWAS. For example, using only the 133 most significant markers in 133 QTL regions from the meta-GWAS yielded accuracies ranging from 0.08 to 0.23, while 23,125 markers with a − log10(p) higher than 7 resulted in accuracies of up 0.35. Using WGS data did not significantly improve the proportion of genetic variance captured across breeds compared to scenarios with few but pre-selected markers. Conclusions: Our results demonstrated that the accuracy of across-breed GP can be improved by using markers that are pre-selected from WGS based on their potential causal effect. We also showed that simply increasing the number of markers up to the WGS level does not increase the accuracy of across-breed prediction, even when markers that are expected to have a causal effect are included

Suboptimal herd performance amplifies the spread of infectious disease in the cattle industry

Farms that purchase replacement breeding cattle are at increased risk of introducing many economically important diseases. The objectives of this analysis were to determine whether the total number of replacement breeding cattle purchased by individual farms could be reduced by improving herd performance and to quantify the effects of such reductions on the industry-level transmission dynamics of infectious cattle diseases. Detailed information on the performance and contact patterns of British cattle herds was extracted from the national cattle movement database as a case example. Approximately 69% of beef herds and 59% of dairy herds with an average of at least 20 recorded calvings per year purchased at least one replacement breeding animal. Results from zero-inflated negative binomial regression models revealed that herds with high average ages at first calving, prolonged calving intervals, abnormally high or low culling rates, and high calf mortality rates were generally more likely to be open herds and to purchase greater numbers of replacement breeding cattle. If all herds achieved the same level of performance as the top 20% of herds, the total number of replacement beef and dairy cattle purchased could be reduced by an estimated 34% and 51%, respectively. Although these purchases accounted for only 13% of between-herd contacts in the industry trade network, they were found to have a disproportionately strong influence on disease transmission dynamics. These findings suggest that targeting extension services at herds with suboptimal performance may be an effective strategy for controlling endemic cattle diseases while simultaneously improving industry productivity