Lactation performance, feed efficiency, and blood metabolites of dairy cows treated with recombinant bovine somatotropin: A systematic review and meta-analysis

A systematic review and meta-analysis were conducted to assess the impact of recombinant bovine somatotropin (rbST) on lactation performance, feed efficiency, and blood metabolites in dairy cows. In the systematic review, articles were selected based on the following criteria: (1) Data focusing on the influence of bovine somatotropin doses on milk production; (2) Submission of original data; (3) Articles published in journals; and (4) Articles in English or Portuguese. The analysis of variance was used with a completely randomized design and mixed models methodology. Polynomial regression was applied to significant fixed effects (rbST dose). The use of rbST resulted in increased milk yield and 4% fat-corrected milk yield, while fat, protein, and lactose contents remained unaffected. Dry matter and metabolizable energy intakes, as well as milk/feed efficiency, exhibited a linear increase, but body condition score (BCS) was negatively impacted. The administration of rbST led to higher blood concentrations of triglycerides and insulin. Cows treated with rbST showed a 23% increase in non-esterified fatty acid (NEFA) concentrations compared to non-treated cows. Additionally, growth factors IGF-1 and IGF-2 displayed a linear increase with rbST treatment. In summary, rbST administration increased milk yield and fat-corrected milk yield without affecting milk components. However, despite increasing intake, it resulted in BCS losses and alterations in blood parameters such as NEFA, IGF-1, and IGF-2.

Unlocking growth potential: Synergistic potassium fertilization for enhanced yield, nutrient uptake, and energy fractions in Chinese cabbage

The implementation of integrated potassium management presents a viable approach for augmenting plant growth, yield, and nutrient uptake while enhancing soil nutrient availability. A field experiment was executed during the rabi season of 2020, employing a randomized complete block design encompassing eight treatments involving standard (100%) and reduced (75% and 50%) rates of the recommended dose of potassium (RDK) administered through muriate of potash (MOP). Treatments included variations in the incorporation/exclusion of plant growth-promoting rhizobacteria (PGPR), farmyard manure (FYM) at 25% of potassium recommendation, and foliar application of nano potash. The use of 100% RDK +25% K augmentation through FYM + PGPR and nano K fertilizer spray at 25 and 40 DAS (T8) exhibited significant enhancements in green fodder yield (64.0 ± 2.2 t ha-1) over control with no potassium application (47.3 ± 3.7 t ha-1) and found at par with and 75% RDK + 25% K augmentation through FYM + PGPR and nano K fertilizer spray at 25 and 40 DAS (T7). These treatments yielded maximum percent increase for plant height (34.9%), leaf count (38.5%), leaf dimensions (28.8-31.5%), stem girth (25.84%), root volume (27.0%), and root length (37.64%), observed at the harvest stage compared to control (T1-no potassium application). The treatment T8 was on par with T7 and recorded highest uptake of macro (N, P, and K) and micro (Zn, Fe, Cu, and Mn) nutrients. While soil parameters such as available nitrogen and potassium levels were notably increased through the application of treatment T7 across various treatment combinations and found significantly superiority over treatment T8. Multivariate analysis also highlighted treatment T7 is more efficient in maintaining sustainability. Hence, based on the present findings it can be concluded that application of 75% RDK +25% K augmentation through FYM + PGPR and nano K fertilizer spray at 25 and 40 DAS (T7) can be recommended for achieving enhanced productivity and soil fertility improvement within agricultural systems.

Developmental programming of production and reproduction in dairy cows: III. Association of level of maternal milk production with offspring's birth weight, survival, productive and reproductive performance and AMH concentration from birth to the first lactation period

Although some studies investigated the relationship of dam milk production (DMP) with offspring birth weight and productive performance, limited information is available on the association of level of DMP with reproductive performance in dairy cows. Therefore, the present study was conducted to understand whether dams with various levels of milk production produce offspring with different fertility. In study I, offspring were classified based on the level of DMP into five categories, including DMP1 (dams with <10.00 × 103 kg of 305-day milk production), DMP2 (dams with ≥10.00 × 103 kg and <12.00 × 103 kg of 305-day milk production), DMP3 (dams with ≥12.00 × 103 kg and <14.00 × 103 kg of 305-day milk production), DMP4 (dams with ≥14.00 × 103 kg and <16.00 × 103 kg of 305-day milk production) and DMP5 (dams with ≥16.00 × 103 kg of 305-day milk production). In study I, data of birth weight, milk yield and reproductive variables of 14,536 offspring born to lactating dams and corresponding data of DMP were retrieved. In study II, blood samples (n = 339) were collected from offspring in various categories of DMP for measurement of serum AMH. Offspring were heavier at birth in DMP4 and DMP5 categories than DMP1 and DMP2 categories (P < 0.05). Milk yield of offspring increased as DMP elevated (P < 0.05); however, offspring in DMP1 and DMP2 categories produced higher milk as compared with their dams during primiparity (P < 0.05) whereas offspring in DMP3, DMP4 and DMP5 categories produced less milk as compared with their dams during primiparity (P < 0.05). Milk fat to protein ratio during the first month of lactation was greater in DMP4 and DMP5 categories than DMP1 category (P < 0.05). Offspring of DMP4 and DMP5 categories were inseminated and conceived at younger ages than offspring of DMP1 category during nulliparity (P < 0.05). Calving to conception interval was longer in DMP5 than DMP1 category in primiparous offspring (P < 0.05), but concentration of AMH did not differ among various categories of DMP (P > 0.05). In conclusion, dams with greater level of milk production produced heavier offspring with higher milk yield but worse transgenerational improvement in milk production and diminished reproductive performance, which were seemingly under higher pressure of negative energy balance during the first month of lactation.

Sperm-borne tsRNAs and miRNAs analysis in relation to dairy cattle fertility

Sperm small non-coding RNAs (sncRNAs), such as microRNAs (miRNAs) and tRNA-derived small RNAs (tsRNAs), have been found to have implications for male fertility and play a role in the intergenerational transmission of specific phenotypes by influencing the early embryo's physiological processes in various animal species. This study postulates that there exists a correlation between sperm small non-coding RNAs (sncRNAs) and bull fertility, which in turn can influence the fertility of offspring through the modulation of early embryo development. To investigate this hypothesis, we generated comparative libraries of sperm sncRNAs from sires exhibiting high (n = 3) versus low bull fertility (n = 3), as well as high (n = 3) versus low daughter fertility (n = 3), as determined by the industry-standard Bull fertility index and Daughter fertility index. In total, 12 tsRNAs carried by sperm (11 down-regulated and 1 up-regulated) were found to be associated with bull fertility, while 19 tsRNAs (11 down-regulated and 8 up-regulated) were found to be associated with daughter fertility (q < 0.05, Log2foldchange>±1.5, base mean > 50). Notably, tRX-Glu-NNN-3811 exhibited potential as a biomarker for predicting fertility in both male and female dairy cattle. Moreover, a total of six miRNAs sperm-borne (two up-regulated and four down-regulated) and 35 miRNAs (27 up-regulated and eight down-regulated) exhibited a significant correlation with both bull fertility and daughter fertility individually (p < 0.05, base mean > 50, log2foldchange>±1.5), two microRNAs, namely miR-2385-5p (down-regulated) and miR-98 (up-regulated), exhibit a significant association (p < 0.05, base mean > 50, log2foldchange>±1.5) with the fertility of both bulls and daughter. The targets of these two microRNAs were subsequently identified and integrated with the transcriptomic database of the embryonic cells at the two-cell stage, which is known to be indicative of embryonic competence. The KEGG analysis revealed a potential correlation between these targets and choline metabolism, a crucial factor in embryonic epigenetic programming. In summary, the findings of this study indicate that sperm-borne small non-coding RNAs (sncRNAs) hold promise as biomarkers for predicting and enhancing fertility in dairy cattle. Furthermore, it is plausible that these sncRNAs may exert their effects on daughter fertility by targeting genes in the early embryo.

Impact of postpartum time period associated body condition score on reproductive performance in dairy cows

This study was designed to identify the time period at which the body condition score (BCS) most critically affects the reproductive performance after calving in dairy cows. Data were collected from 4865 lactation records (1821 from primiparous and 3044 from multiparous cows) on 28 dairy farms, including the BCS (at calving, and month 1 and the first artificial insemination [AI] after calving), the presence of peri- or postpartum disorders, reproductive data, and the weather. The data on the extent of BCS loss from calving to the first AI was divided into two periods, namely, between calving and month 1 after calving (period 1), and between month 1 and the first AI after calving (period 2). Cows with BCS of 3.0, 3.25 and ≥ 3.5 at the first AI after calving were more likely (P < 0.05-0.01) to be pregnant at 30 (odds ratio [OR]: 1.36, 1.64, and 1.90) and 45 (OR: 1.39, 1.75, and 1.99) days post-AI and more likely (P < 0.05-0.01) to be pregnant within 180 days after calving (hazard ratio [HR]: 1.18, 1.43, and 1.58) than cows with BCS of ≤2.75. In addition, cows who suffered a BCS loss of ≥0.5 units during period 1 tended to be less likely (HR: 0.79, P < 0.1) to be pregnant within 180 days after calving than cows without a BCS loss. Cows with BCS of 3.0, 3.25, and ≥3.5 at calving were less likely (P < 0.1-0.05) to lose their pregnancy (OR: 0.37, 0.33, and 0.16) than cows with BCS of ≤2.75. These results indicate that the linearly higher BCS (3.0, 3.25, and ≥3.5) at the first AI is positively associated with the probability of pregnancy per AI after the first AI and the likelihood of pregnancy within 180 days after calving, whereas a higher BCS loss of ≥0.5 units during period 1 was adversely associated with the likelihood of pregnancy within 180 days after calving.

High-Fat Diet and Female Fertility across Lifespan: A Comparative Lesson from Mammal Models

Female reproduction focuses mainly on achieving fully grown follicles and competent oocytes to be successfully fertilized, as well as on nourishing the developing offspring once pregnancy occurs. Current evidence demonstrates that obesity and/or high-fat diet regimes can perturbate these processes, leading to female infertility and transgenerational disorders. Since the mechanisms and reproductive processes involved are not yet fully clarified, the present review is designed as a systematic and comparative survey of the available literature. The available data demonstrate the adverse influences of obesity on diverse reproductive processes, such as folliculogenesis, oogenesis, and embryo development/implant. The negative reproductive impact may be attributed to a direct action on reproductive somatic and germinal compartments and/or to an indirect influence mediated by the endocrine, metabolic, and immune axis control systems. Overall, the present review highlights the fragmentation of the current information limiting the comprehension of the reproductive impact of a high-fat diet. Based on the incidence and prevalence of obesity in the Western countries, this topic becomes a research challenge to increase self-awareness of dietary reproductive risk to propose solid and rigorous preventive dietary regimes, as well as to develop targeted pharmacological interventions.

Machine Learning-Based Co-Expression Network Analysis Unravels Potential Fertility-Related Genes in Beef Cows

Simple Summary

Female reproductive failure is still a challenge for the beef industry. Several biological processes that underlie fertility-related traits, such as the establishment of pregnancy and embryo survival, are still unclear. Increased availability of transcriptomic data has allowed a deep investigation of the potential mechanisms involved in fertility. This study investigated candidate gene biomarkers predictive of pregnancy status and underlying fertility-related networks. To this end, we integrated gene expression profiles through supervised machine learning and gene network modeling. We identified nine biologically relevant endometrial gene biomarkers that could discriminate against pregnancy status in cows. These biomarkers were co-expressed with genes critical for uterine receptivity, including endometrial tissue remodeling, focal adhesion, and embryo development. This study outlined key pathways involved with pregnancy success and provided predictive candidate biomarkers for pregnancy outcome in cows.

Abstract

Reproductive failure is still a challenge for beef producers and a significant cause of economic loss. The increased availability of transcriptomic data has shed light on the mechanisms modulating pregnancy success. Furthermore, new analytical tools, such as machine learning (ML), provide opportunities for data mining and uncovering new biological events that explain or predict reproductive outcomes. Herein, we identified potential biomarkers underlying pregnancy status and fertility-related networks by integrating gene expression profiles through ML and gene network modeling. We used public transcriptomic data from uterine luminal epithelial cells of cows retrospectively classified as pregnant (P, n = 25) and non-pregnant (NP, n = 18). First, we used a feature selection function from BioDiscML and identified SERPINE3, PDCD1, FNDC1, MRTFA, ARHGEF7, MEF2B, NAA16, ENSBTAG00000019474, and ENSBTAG00000054585 as candidate biomarker predictors of pregnancy status. Then, based on co-expression networks, we identified seven genes significantly rewired (gaining or losing connections) between the P and NP networks. These biomarkers were co-expressed with genes critical for uterine receptivity, including endometrial tissue remodeling, focal adhesion, and embryo development. We provided insights into the regulatory networks of fertility-related processes and demonstrated the potential of combining different analytical tools to prioritize candidate genes.

Co-Expression Network and Integrative Analysis of Metabolome and Transcriptome Uncovers Biological Pathways for Fertility in Beef Heifers

Reproductive failure remains a significant challenge to the beef industry. The omics technologies have provided opportunities to improve reproductive efficiency. We used a multistaged analysis from blood profiles to integrate metabolome (plasma) and transcriptome (peripheral white blood cells) in beef heifers. We used untargeted metabolomics and RNA-Seq paired data from six AI-pregnant (AI-P) and six nonpregnant (NP) Angus-Simmental crossbred heifers at artificial insemination (AI). Based on network co-expression analysis, we identified 17 and 37 hub genes in the AI-P and NP groups, respectively. Further, we identified TGM2, TMEM51, TAC3, NDRG4, and PDGFB as more connected in the NP heifers’ network. The NP gene network showed a connectivity gain due to the rewiring of major regulators. The metabolomic analysis identified 18 and 15 hub metabolites in the AI-P and NP networks. Tryptophan and allantoic acid exhibited a connectivity gain in the NP and AI-P networks, respectively. The gene–metabolite integration identified tocopherol-a as positively correlated with ENSBTAG00000009943 in the AI-P group. Conversely, tocopherol-a was negatively correlated in the NP group with EXOSC2, TRNAUIAP, and SNX12. In the NP group, α-ketoglutarate-SMG8 and putrescine-HSD17B13 were positively correlated, whereas a-ketoglutarate-ALAS2 and tryptophan-MTMR1 were negatively correlated. These multiple interactions identified novel targets and pathways underlying fertility in bovines.

Historical Evolution of Cattle Management and Herd Health of Dairy Farms in OECD Countries

This work aimed to review the important aspects of the dairy industry evolution at herd level, interrelating production with health management systems. Since the beginning of the industrialization of the dairy cattle sector (1950s), driven by the need to feed the rapidly growing urban areas, this industry has experienced several improvements, evolving in management and technology. These changes have been felt above all in the terms of milking, rearing, nutrition, reproductive management, and design of facilities. Shortage of labor, emphasis on increasing farm efficiency, and quality of life of the farmers were the driving factors for these changes. To achieve it, in many areas of the world, pasture production has been abandoned, moving to indoor production, which allows for greater nutritional and reproductive control of the animals. To keep pace with this paradigm in milk production, animal health management has also been improved. Prevention and biosecurity have become essential to control and prevent pathologies that cause great economic losses. As such, veterinary herd health management programs were created, allowing the management of health of the herd as a whole, through the common work of veterinarians and farmers. These programs address the farms holistically, from breeding to nutrition, from prevention to consultancy. In addition, farmers are now faced with a consumer more concerned on animal production, valuing certified products that respect animal health and welfare, as well as environmental sustainability.

Major Nutritional Metabolic Alterations Influencing the Reproductive System of Postpartum Dairy Cows

Early successful conception of postpartum dairy cows is crucial in determining the optimum reproductive efficiency and profitability in modern dairy farming. Due to the inherent high production potential of modern dairy cows, the extra stress burden of peri-parturient events, and associated endocrine and metabolic changes causes negative energy balance (NEBAL) in postpartum cows. The occurrence of NEBAL is associated with excessive fat mobilization in the form of non-esterified fatty acids (NEFAs). The phenomenon of NEFA mobilization furthers with occurrence of ketosis and fatty liver in postpartum dairy cows. High NEFAs and ketones are negatively associated with health and reproductive processes. An additional burden of hypocalcemia, ruminal acidosis, and high protein metabolism in postpartum cows presents further consequences for health and reproductive performance of postpartum dairy cows. This review intends to comprehend these major nutritional metabolic alterations, their mechanisms of influence on the reproduction process, and relevant mitigation strategies.

Production and Health Management from Grazing to Confinement Systems of Largest Dairy Bovine Farms in Azores: A Farmers' Perspective

Simple Summary

This study aimed to evaluate differences and critical factors in production and health management between dairy cattle farms with fixed milk parlours (FMP), and mobile milk systems (MMS) from Azorean grasslands. According to the farmers’ perspective, calf diarrhea, calf pneumonia, infertility/poor reproductive management, and mastitis were the main problems that farms faced in 2020. FMP was associated with more advanced and mechanized production systems, with a higher adherence to preventive and biosecurity control programs, than traditional MMS farms. MMS farms also showed a greater vocation for dual-purpose farming (beef and milk), smaller herd sizes and more grazing time for cows. In conclusion, inherent and non-inherent differences in production and health management between FMP and MMS were quantified by authors. These results indicate that a greater adoption of preventive veterinary medicine and biosecurity measures should be taken, especially among MMS farms. The education of farmers should also be improved and stimulated.

Abstract

The intensification of bovine milk production in the Azores has led farmers to increase farm size and specialization in grasslands, implementing confined and semi-confined production systems. Fixed milking parlours (FMP) have progressively gained more popularity, at the expense of conventional mobile milking systems (MMS). The present study aimed to evaluate the associations between production and health management in dairy cattle farms, with FMP or MMS, in grasslands (São Miguel, Azores), according to the farmers’ perspective. A total of 102 questions about production and health management were surveyed in 105 farms with >30 dairy cows each. Farms with FMP were associated (p ≤ 0.05) with larger herd size, better facilities, and specialized management, however, the adoption of preventive and biosecurity measures should be improved by these farmers. MMS farms implemented a lower level of disease prevention or control programs, less frequent transhumance, and showed a wider vocation to dual-purpose (milk and cross beef) than FMP farms. In conclusion, MMS and FMP farms tried to optimize yield and economic viability in different ways using grasslands. Several biosecurity and health prevention constraints were identified for improvement.

Review: Perspective on high-performing dairy cows and herds

Milk and dairy products provide highly sustainable concentrations of essential amino acids and other required nutrients for humans; however, amount of milk currently produced per dairy cow globally is inadequate to meet future needs. Higher performing dairy cows and herds produce more milk with less environmental impact per kg than lower performing cows and herds. In 2018, 15.4% of the world's dairy cows produced 45.4% of the world's dairy cow milk, reflecting the global contribution of high-performing cows and herds. In high-performing herds, genomic evaluations are utilized for multiple trait selection, welfare is monitored by remote sensing, rations are formulated at micronutrient levels, health care is focused on prevention and reproduction is managed with precision. Higher performing herds require more inputs and generate more waste products per cow, thus innovations in environmental management on such farms are essential for lowering environmental impacts. Our focus is to provide perspectives on technologies and practices that contribute most to sustainable production of milk from high-performing dairy cows and herds.

Mapping the past, present and future research landscape of paternal effects

BACKGROUND

Although in all sexually reproducing organisms an individual has a mother and a father, non-genetic inheritance has been predominantly studied in mothers. Paternal effects have been far less frequently studied, until recently. In the last 5 years, research on environmentally induced paternal effects has grown rapidly in the number of publications and diversity of topics. Here, we provide an overview of this field using synthesis of evidence (systematic map) and influence (bibliometric analyses).

RESULTS

We find that motivations for studies into paternal effects are diverse. For example, from the ecological and evolutionary perspective, paternal effects are of interest as facilitators of response to environmental change and mediators of extended heredity. Medical researchers track how paternal pre-fertilization exposures to factors, such as diet or trauma, influence offspring health. Toxicologists look at the effects of toxins. We compare how these three research guilds design experiments in relation to objects of their studies: fathers, mothers and offspring. We highlight examples of research gaps, which, in turn, lead to future avenues of research.

CONCLUSIONS

The literature on paternal effects is large and disparate. Our study helps in fostering connections between areas of knowledge that develop in parallel, but which could benefit from the lateral transfer of concepts and methods.

Symposium review: Decomposing efficiency of milk production and maximizing profit

The dairy industry has focused on maximizing milk yield, as it is believed that this maximizes profit mainly through dilution of maintenance costs. Efficiency of milk production has received, until recently, considerably less attention. The most common method to determine biological efficiency of milk production is feed efficiency (FE), which is defined as the amount of milk produced relative to the amount of nutrients consumed. Economic efficiency is best measured as income over feed cost or gross margin obtained from feed investments. Feed efficiency is affected by a myriad of factors, but overall they could be clustered as follows: (1) physiological status of the cow (e.g., age, state of lactation, health, level of production, environmental conditions), (2) digestive function (e.g., feeding behavior, passage rate, rumen fermentation, rumen and hindgut microbiome), (3) metabolic partitioning (e.g., homeorhesis, insulin sensitivity, hormonal profile), (4) genetics (ultimately dictating the 2 previous aspects), and (5) nutrition (e.g., ration formulation, nutrient balance). Over the years, energy requirements for maintenance seem to have progressively increased, but efficiency of overall nutrient use for milk production has also increased due to dilution of nutrient requirements for maintenance. However, empirical evidence from the literature suggests that marginal increases in milk require progressively greater marginal increases in nutrient supply. Thus, the dilution of maintenance requirements associated with increases in production is partially overcome by a progressive diminishing marginal biological response to incremental energy and protein supplies. Because FE follows the law of diminishing returns, and because marginal feed costs increase progressively with milk production, profits associated with improving milk yield might, in some cases, be considerably lower than expected.