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Contents The aim of this study was to evaluate the influence of two different concentrations of plasma progesterone at the time of FSH-P treatment on the superovulatory response in dairy heifers. Sixteen reproductively sound Holstein heifers (13-15 months of age) were used in this study. Superovulatory treatment was commenced at mid-dioestrus (Day 10 ± 2 of the oestrous cycle) of the synchronized (using two injections of PGF2α, 11 days apart) oestrous cycles. Blood samples were collected on the day and the day after commencing FSH-P treatment and at oestrus for plasma progesterone determination. Heifers were grouped based on two levels of plasma progesterone; Group low progesterone (LP; ranging from 2 to 4.5 ng /ml; n = 7) and Group high progesterone (HP; ≥4.6 ng /ml; n = 8) at the beginning of FSH-P treatment (one heifer was excluded from the statistical analysis because of the abnormal progesterone level at oestrus). The superovulatory response in terms of mean numbers of palpable corpora lutea (ovulation rate) was significantly higher (p < 0.05) in group LP than group HP. Ovulation rate was negatively correlated ( r = −0.51) with the progesterone concentration at the time of commencing FSH-P treatment (p < 0.05). Data suggest that varying concentrations of plasma progesterone at the time of FSH-P treatment may have a different effect on the outcome of superovulatory response in dairy heifers. [ABSTRACT FROM AUTHOR]

Contents The primary objective of this study was to investigate the impact of animal-level factors including energy balance and environmental/management stress, on the ovarian function of Bos indicus heifers treated to synchronize ovulation. Two-year-old Brahman (BN) (n = 30) and BN-cross (n = 34) heifers were randomly allocated to three intravaginal progesterone-releasing device (IPRD) treatment groups: (i) standard-dose IPRD [Cue-Mate® (CM) 1.56 g; n = 17]; (ii) half-dose IPRD [0.78 g progesterone (P4); CM 0.78 g; n = 15]; (iii) half-dose IPRD + 300 IU equine chorionic gonadotrophin at IPRD removal (CM 0.78 g + G; n = 14); (iv) and a control group, 2× PGF2α [500 μg prostaglandin F2α (PGF2α)] on Day −16 and −2 (n = 18). Intravaginal progesterone-releasing device-treated heifers received 250 μg PGF2α at IPRD insertion (Day −10) and IPRD removal (Day −2) and 1 mg oestradiol benzoate on Day −10 and −1. Heifers were managed in a small feedlot and fed a defined ration. Ovarian function was evaluated by ultrasonography and plasma P4 throughout the synchronized and return cycles. Energy balance was evaluated using plasma insulin-like growth factor 1 (IGF-I) and glucose concentrations. The impact of environmental stressors was evaluated using plasma cortisol concentration. Heifers that had normal ovarian function had significantly higher IGF-I concentrations at commencement of the experiment (p = 0.008) and significantly higher plasma glucose concentrations at Day −2 (p = 0.040) and Day 4 (p = 0.043), than heifers with abnormal ovarian function. There was no difference between the mean pre-ovulatory cortisol concentrations of heifers that ovulated or did not ovulate. However, heifers that ovulated had higher cortisol concentrations at Day 4 (p = 0.056) and 6 (p = 0.026) after ovulation than heifers that did not ovulate. [ABSTRACT FROM AUTHOR]

Contents [ABSTRACT FROM AUTHOR]

Contents [ABSTRACT FROM AUTHOR]

We offer a perspective on the major challenges that are confronting the management of reproduction in sheep and cattle in Australia and New Zealand, over the next two decades. An important context is the dominance of grazing systems in which large flocks or herds are managed over large areas where it is challenging to manage reproduction with precision. Consequently, the variable forage supply usually dominates reproductive outcomes, a problem that will be exacerbated by global heating. Thus, in extensive grazing systems, there is a great need for technological solutions to improve the management of nutrition. Global heating will also exert direct effects on reproductive function. Therefore, for the foreseeable future, reproduction will remain a focus for industry. In addition, as the industries develop, we foresee continued societal pressure to reduce medication, mitigate environmental damage, and improve animal well-being. Management solutions for extensive grazing systems must involve minimal interventions with the animals and be applicable to diverse genotypes and environments. Clearly, genetics and breeding will be at the heart of solutions and elegant strategies will be needed that focus on developing animals that are robust, if perhaps a little less productive. A high rate of genetic gain is the main reason for pursuing reproductive technologies, but highly advanced reproductive technology is not likely to be the best fit in extensive management systems. Even for AI, the simplest technology, uptake is limited and lateral thinking is needed to find ways to improve the rates of genetic gain. We conclude that there are many opportunities for improving reproductive performance in sheep and cattle in Australia and New Zealand. As we gain deeper understanding of the processes involved, we should be able to make progress in fertility and fecundity, embryo survival, and postnatal survival. Improvements in reproductive performance will increase productivity, and should also be associated with significantly improved animal well-being and a reduction in methane emissions intensity. To capture these benefits, the development of new management options will require lateral thinking about reproductive technology for extensive grazing systems, and a transdisciplinary approach that brings together the systems biology of grazing animals with an understanding of the barriers to adoption by farmers., Competing Interests: Declaration of competing interest The authors declare that the research described herein was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024. Published by Elsevier Inc.)

This study aimed to identify the pathogens isolated from the milk of cows with clinical mastitis in the subtropical region of Australia and to determine the antimicrobial susceptibility of these bacteria. Thirty dairy herds in the subtropical dairy region were asked to submit milk samples for the first 5 cases of clinical mastitis each month for 12 mo. Samples underwent aerobic culture, and isolates were identified via MALDI-TOF mass spectrometry. Antimicrobial susceptibility was determined for Escherichia coli, Enterococcus spp., Streptococcus agalactiae, Streptococcus uberis, Streptococcus dysgalactiae, Staphylococcus aureus, and non-aureus staphylococci and mammaliicocci (NASM). Between March 2021 and July 2022, 1,230 milk samples were collected. A positive culture result was recorded for 812 (66%) of the milk samples; from these samples, 909 isolates were obtained, including 49 isolates where no identification was possible. The remaining samples were classified as having no growth (16.8%) or as being contaminated (17.2%). The most common isolates with a MALDI-TOF diagnosis (n = 909) were Strep. uberis (23.6%), followed by the NASM group (15.0%). Farms enrolled in the study were in 3 distinct locations within the subtropical dairy region: North Queensland, Southeast Queensland, and Northern New South Wales. Some variation in isolate prevalence occurred between these 3 locations. We found lower odds of a sample being positive for E. coli in North Queensland (odds ratio [OR]: 0.25; 95% confidence interval [CI]: 0.07-0.87) and higher odds in Southeast Queensland (OR: 4.01; 95% CI: 1.96-8.20) compared with the reference, Northern New South Wales. We further found higher odds of Strep. dysgalactiae in North Queensland (OR: 5.69; 95% CI: 1.85-17.54) and Southeast Queensland compared with Northern New South Wales (OR: 3.99; 95% CI: 1.73-9.22). Although some seasonal patterns were observed, season was not significant for any of the analyzed isolates. Farm-level differences in pathogen profiles were obvious. Overall, clinical mastitis pathogens had low levels of resistance to the antimicrobials tested. This research demonstrates that Strep. uberis and the NASM bacterial group are the most common pathogens causing clinical mastitis in the subtropical dairy region. It highlights the importance of understanding pathogenic causes of mastitis at the farm and regional level for targeted control and therapy., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Many of the world's agriculturally important plant and animal populations consist of hybrids of subspecies. Cattle in tropical and sub-tropical regions for example, originate from two subspecies, Bos taurus indicus (Bos indicus) and Bos taurus taurus (Bos taurus). Methods to derive the underlying genetic architecture for these two subspecies are essential to develop accurate genomic predictions in these hybrid populations. We propose a novel method to achieve this. First, we use haplotypes to assign SNP alleles to ancestral subspecies of origin in a multi-breed and multi-subspecies population. Then we use a BayesR framework to allow SNP alleles originating from the different subspecies differing effects. Applying this method in a composite population of B. indicus and B. taurus hybrids, our results show that there are underlying genomic differences between the two subspecies, and these effects are not identified in multi-breed genomic evaluations that do not account for subspecies of origin effects. The method slightly improved the accuracy of genomic prediction. More significantly, by allocating SNP alleles to ancestral subspecies of origin, we were able to identify four SNP with high posterior probabilities of inclusion that have not been previously associated with cattle fertility and were close to genes associated with fertility in other species. These results show that haplotypes can be used to trace subspecies of origin through the genome of this hybrid population and, in conjunction with our novel Bayesian analysis, subspecies SNP allele allocation can be used to increase the accuracy of QTL association mapping in genetically diverse populations., (© 2023. The Author(s).)

A 5-year retrospective study was conducted to describe the mastitis-causing organisms isolated from bovine milk samples submitted to four veterinary diagnostic laboratories in Australia. The aim of this study was to identify temporal, geographical, and seasonal patterns of occurrence for the organisms and report the in vitro susceptibility of the most common mastitis-causing pathogens. In total, 22,102 milk samples were submitted between 2015 and 2019. The results were reported as positive growth for at least one significant organism ( n = 11,407; 51.6%), no growth ( n = 5,782; 26.2%), and mixed/contaminated growth ( n = 4,913; 22.2%). Culture results for no growth, gram-negative bacteria, and eukaryotic organisms were combined for each region, and they were accounted for between 23 and 46% of submissions. These results represent a subset of mastitis cases for which the antibiotic treatment may not be warranted. A total of 11,907 isolates were cultured from 11,407 milk samples. The most common isolated organisms were Streptococcus uberis [41.3%; 95% confidence interval (CI): 40.4-42.1%] and Staphylococcus aureus (23.6%; 95% CI: 22.8-24.3%). For S. uberis and S. aureus , there was an association between a positive culture result and the dairy region. All regions except for the Sub-tropical Dairy region were more likely to culture S. uberis compared to the reference, Dairy NSW ( P < 0.001). Similarly, for S. aureus , a positive culture result was more likely in all other dairy regions compared to Dairy NSW ( P < 0.001). The LISA cluster analysis identified differences between High-High (hotspot) postcodes for S . aureus and S . uberis throughout all the analyzed dairy regions. These results highlight the need for further investigations into specific risk factors, such as environmental factors and herd-level predictors, which may have influenced the observed regional variations. Common mastitis-causing pathogens showed overall good susceptibility to a range of antimicrobials used in the treatment of mastitis. On-going surveillance of mastitis-causing pathogens and their antimicrobial susceptibilities will facilitate targeted mastitis control and treatment programs., Competing Interests: MH is employed by The Milk Road. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Langhorne, Gupta, Horsman, Wood, Wood, Barker, Deutscher, Price, McGowan, Humphris, Ranjbar, Henning and Gibson.)

The aim of this study was to assess effects on milk yield (MY), rumen temperature, and panting score when lactating dairy cows were cooled during the day only or during the day and night. The study was conducted over 106 d during using 120 multiparous Holstein-Friesian cows assigned to 2 treatments (60 cows/treatment; 2 pens/treatment): (1) day cooling (DC): overhead sprinklers (large droplet) and fans while in the dairy holding yard only, shade and fans at the feedpad, and a shaded loafing area; and (2) enhanced day+night cooling (EDN): overhead sprinklers (large droplet) and fans in dairy holding yard, ducted air blowing onto cows during milking, plus thorough wetting (shower array) on exit from dairy; shade and fans at feedpad (turned off at night); and shaded loafing area + ducted fan-forced air blowing onto cows at night. The ducted air at night was manually activated at 2030 h when the maximum daily temperature-humidity index exceeded 75 and remained on until 0430 h the next day. The cows were fed a total mixed ration ad libitum, and feed intake was determined on a pen basis. Rumen temperature and cow activity were obtained from each cow at 10-min intervals via rumen boluses. Panting scores were obtained by direct observation 4 times a day at approximately 0430, 0930, 1530, and 2030 h. Cows were milked twice daily: 0500 to 0600 h and 1600 to 1700 h. Individual MY were obtained at each milking and combined to give individual daily totals. The EDN cows had greater daily MY (+2.05 kg/cow per day) over the duration of the study compared with DC cows. Rumen temperature during the third heat wave was lower for EDN (39.51 ± 0.01°C) than for DC (39.66 ± 0.01°C) cows. During the most severe heat wave (heat wave 3), MY for the 2 groups was similar, but over the 6 d following the heat wave, EDN cows had greater daily MY (+3.61 kg/cow per day). Rumen temperature was lower for EDN (39.58 ± 0.01°C) than for DC (40.10 ± 0.01°C) cows., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Worldwide, most beef breeding herds are naturally mated. As such, the ability to identify and select fertile bulls is critically important for both productivity and genetic improvement. Here, we collected ten fertility-related phenotypes for 6,063 bulls from six tropically adapted breeds. Phenotypes were comprised of four bull conformation traits and six traits directly related to the quality of the bull's semen. We also generated high-density DNA genotypes for all the animals. In total, 680,758 single nucleotide polymorphism (SNP) genotypes were analyzed. The genomic correlation of the same trait observed in different breeds was positive for scrotal circumference and sheath score on most breed comparisons, but close to zero for the percentage of normal sperm, suggesting a divergent genetic background for this trait. We confirmed the importance of a breed being present in the reference population to the generation of accurate genomic estimated breeding values (GEBV) in an across-breed validation scenario. Average GEBV accuracies varied from 0.19 to 0.44 when the breed was not included in the reference population. The range improved to 0.28 to 0.59 when the breed was in the reference population. Variants associated with the gene HDAC4, six genes from the spermatogenesis-associated (SPATA) family of proteins, and 29 transcription factors were identified as candidate genes. Collectively these results enable very early in-life selection for bull fertility traits, supporting genetic improvement strategies currently taking place within tropical beef production systems. This study also improves our understanding of the molecular basis of male fertility in mammals., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Porto-Neto et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Pregnancy in cattle is the outcome of the complex process of initiation of cycling, fertilization, maternal recognition of pregnancy and foeto-placental development. Though much is known about initiation of cycling and associated risk factors, there are virtually no data on pregnancy rate per cycle for naturally mated cattle, especially for extensively managed, tropically adapted genotypes, which this study aimed to determine. Tropical composite (Bos indicus and African Sanga crosses with Bos taurus) and Brahman cattle (n = 2,181) of known pedigree in four-year groups at four sites were mated annually for 84 days. Body condition, ovarian function, pregnancies, calving and lactation were monitored through six full reproductive cycles using 4-8 weekly ultrasound of the reproductive tract outside the calving period and daily monitoring during calving. From this, dates of commencement of cycling and conception in each year were estimated for each animal, enabling calculation of established pregnancy for consecutive 21-day periods while cycling and of pregnancies within four months of calving while lactating (P4M). Pregnancy per 21-day period (cycle) during mating for cycling animals averaged 63%, 71%, 41% and 28% in four consecutive cycles. Pregnant per cycle was 2%-11% higher in tropical composites than in Brahmans. The only other consistently significant risk to becoming pregnant was if cycling commenced later than three weeks before mating commenced. P4M averaged 62% and was lower for cows in sub-optimal body condition and in first-parity and later-calving cows. Pregnant per cycle was moderately heritable (~20%), while heritability was moderate to high (33%) for P4M. Selection for pregnant per cycle could be achieved indirectly by selection for P4M, a trait that is readily measured., (© 2021 Wiley-VCH GmbH.)

Breeding for polled animals is deemed the most practical solution to eradicate horns naturally and circumvent management costs and risks on health and welfare. However, there has been a historical reluctance by some farmers to select polled animals due to perceived lower productivity of their calves. This study has compared estimated breeding values (EBVs) between horned and polled animals (N = 2,466,785) for 12 production and carcass traits to assess historical (before 2000) and recent (2000-2018) genetic implications of poll breeding. Older generations of the polled animals in most breeds had significantly lower (Bonferroni-corrected p = 0.05) genetic merits for live (birth to maturity) and carcass weights, milk, meat quality, and fat content traits. Substantial gains of genetic potential were achieved during 2000 to 2018 in each breed, such that polled animals have significantly improved for the majority of traits studied. Generally, polled cohorts showed advantageous EBVs for live and carcass weights irrespective of the lower birth weights in some breeds. While Polled Brahman showed inferior production parameters, the poll genetics' effect size ( d ) and correlation ( r ) were very small on recent birth weight ( d = -0.30, r = -0.08), 200 days (-0.19, -0.05), 400 days (-0.06, -0.02), 600 days (-0.05, -0.01), mature cow live weight (-0.08, -0.02), and carcass weight (-0.19, -0.05). In conclusion, although there is some evidence that historical selection for polled breeding animals may have reduced productivity, there is strong evidence that more recent selection for polled genotypes in the breeds studied has not resulted in any adverse effects on genetic merit.

Background: In tropically-adapted beef heifers, application of genomic prediction for age at puberty has been limited due to low prediction accuracies. Our aim was to investigate novel methods of pre-selecting whole-genome sequence (WGS) variants and alternative analysis methodologies; including genomic best linear unbiased prediction (GBLUP) with multiple genomic relationship matrices (MGRM) and Bayesian (BayesR) analyses, to determine if prediction accuracy for age at puberty can be improved., Methods: Genotypes and phenotypes were obtained from two research herds. In total, 868 Brahman and 960 Tropical Composite heifers were recorded in the first population and 3695 Brahman, Santa Gertrudis and Droughtmaster heifers were recorded in the second population. Genotypes were imputed to 23 million whole-genome sequence variants. Eight strategies were used to pre-select variants from genome-wide association study (GWAS) results using conditional or joint (COJO) analyses. Pre-selected variants were included in three models, GBLUP with a single genomic relationship matrix (SGRM), GBLUP MGRM and BayesR. Five-way cross-validation was used to test the effect of marker panel density (6 K, 50 K and 800 K), analysis model, and inclusion of pre-selected WGS variants on prediction accuracy., Results: In all tested scenarios, prediction accuracies for age at puberty were highest in BayesR analyses. The addition of pre-selected WGS variants had little effect on the accuracy of prediction when BayesR was used. The inclusion of WGS variants that were pre-selected using a meta-analysis with COJO analyses by chromosome, fitted in a MGRM model, had the highest prediction accuracies in the GBLUP analyses, regardless of marker density. When the low-density (6 K) panel was used, the prediction accuracy of GBLUP was equal (0.42) to that with the high-density panel when only six additional sequence variants (identified using meta-analysis COJO by chromosome) were included., Conclusions: While BayesR consistently outperforms other methods in terms of prediction accuracies, reasonable improvements in accuracy can be achieved when using GBLUP and low-density panels with the inclusion of a relatively small number of highly relevant WGS variants.

Many breeds of modern cattle are naturally horned, and for sound husbandry management reasons the calves frequently undergo procedures to physically remove the horns by disbudding or dehorning. These procedures are however a welfare concern. Selective breeding for polledness - absence of horns - has been effective in some cattle breeds but not in others ( Bos indicus genotypes) due in part to the complex genetics of horn phenotype. To address this problem different approaches to genetic testing which provide accurate early-in-life prediction of horn phenotype have been evaluated, initially using microsatellites (MSAT) and more recently single nucleotide polymorphism (SNP). A direct gene test is not effective given the genetic heterogeneity and large-sized sequence variants associated with polledness in different breeds. The current study investigated 39,943 animals of multiple breeds to assess the accuracy of available poll testing assays. While the standard SNP-based test was an improvement on the earlier MSAT haplotyping method, 1999 (9.69%) out of 20,636 animals tested with this SNP-based assay did not predict a genotype, most commonly associated with the Indicus-influenced breeds. The current study has developed an optimized poll gene test that resolved the vast majority of these 1999 unresolved animals, while the predicted genotypes of those previously resolved remained unchanged. Hence the optimized poll test successfully predicted a genotype in 99.96% of samples assessed. We demonstrated that a robust set of 5 SNPs can effectively determine P C and P F alleles and eliminate the ambiguous and undetermined results of poll gene testing previously identified as an issue in cattle., (Copyright © 2020 Randhawa et al.)

Heifers that have an earlier age at puberty often have greater lifetime productivity. Age at puberty is moderately heritable so selection should effectively reduce the number of days to puberty, and improve heifer productivity and profitability as a result. However, recording age at puberty is intensive, requiring repeat ovarian scanning to determine age at first corpus luteum (AGECL). Genomic selection has been proposed as a strategy to select for earlier age at puberty; however, large reference populations of cows with AGECL records and genotypes would be required to generate accurate GEBV for this trait. Reproductive maturity score (RMS) is a proxy trait for age at puberty for implementation in northern Australia beef herds, where large scale recording of AGECL is not feasible. RMS assigns a score of 0 to 5 from a single ovarian scan to describe ovarian maturity at ~600 d. Here we use multivariate genomic prediction to evaluate the value of a large RMS data set to improve accuracy of GEBV for age at puberty (AGECL). There were 882 Brahman and 990 Tropical Composite heifers with AGECL phenotypes, and an independent set of 974 Brahman, 1,798 Santa Gertrudis, and 910 Droughtmaster heifers with RMS phenotypes. All animals had 728,785 real or imputed SNP genotypes. The correlation of AGECL and RMS (h2 = 0.23) was estimated as -0.83 using the genomic information. This result also demonstrates that using genomic information it is possible to estimate genetic correlations between traits collected on different animals in different herds, with minimal or unknown pedigree linkage between them. Inclusion of heifers with RMS in the multi-trait model improved the accuracy of genomic evaluations for AGECL. Accuracy of RMS GEBV generally did not improve by adding heifers with AGECL phenotypes into the reference population. These results suggest that RMS and AGECL may be used together in a multi-trait prediction model to increase the accuracy of prediction for age at puberty in tropically adapted beef cattle.

Developing accurate genomic evaluations of fertility for tropical beef cattle must deal with at least two major challenges (i) recording cow fertility traits in extensive production systems on large numbers of cows and (ii) the genomic evaluations should work across the breeds, crossbreds, and composites used in tropical beef production. Here, we assess accuracy of genomic evaluations for a trait which can be collected on a large scale in extensive conditions, corpus luteum score (CLscore), which is 1 if ovarian scanning indicates a heifer has cycled by 600 d and 0 if not, in a multi-breed population. A total of 3,696 heifers, including 979 Brahmans, 914 Droughtmasters, and 1,803 Santa Gertrudis in seven herds across 3-yr cohorts with CLscores, were genotyped for 24,211 SNPs. Genotypes were imputed to 728,785 SNPs. GBLUP and BayesR were used to predict GEBV. Accuracy of GEBV was evaluated with two validation strategies. In the first strategy, the last year cohort of heifers from each herd was used for validation, such that every herd had heifers in both reference and validation populations. In the second validation strategy, each herd in turn was removed in its entirety from the reference population, and was used for validation. For both validation strategies, accuracy of GEBV for single breed and multi-breed reference populations was assessed. For the first validation strategy, accuracy of GEBV ranged from 0.2 for Brahmans to 0.4 for Droughtmasters. Increasing marker density from 24K SNPs to 728K SNPs resulted in a small increase in accuracy, and including multiple-breeds in the reference did not help improve accuracy. These results suggest that provided a herd has animals in the reference population, the accuracy of the GEBV is largely determined by within herd (linkage) information. The situation was very different when entire herds were predicted in the second validation. In this case accuracy of GEBV using only 24K SNPs and only a within breed reference was close to zero for all breeds. Accuracy increased substantially when 728K SNPs, BayesR, and a multi-breed reference were used, from 0.15 for Brahmans to 0.35 for Santa Gertrudis. Given the second validation strategy is more likely to reflect the situation for many herds in tropical beef production (no animals in the reference), genomic evaluations for fertility in tropical beef cattle should be based on high-density markers (728K SNPs) and should be multi-breed.