Assisted reproductive technologies (ARTs) in Mithun (Bos frontalis): What progress has been made so far? An overview

Urinary metabolomics reveals potential biomarkers for early detection of pregnancy in Mithun (Bos frontalis) cows

The present study investigated the urinary metabolic profiles of early pregnant and non-pregnant Mithun to identify potential pregnancy detection biomarkers. Urine samples were collected on days 0, 10, 18, 35 and 45 of gestation from pregnant (n = 6) and on days 0, 10 and 18 from non-pregnant (n = 6) Mithun. Urinary metabolites were assessed using proton nuclear magnetic resonance (1H NMR) spectroscopy and identified 270 metabolites. Statistical analyses demonstrated pronounced distinctions in metabolite profiles between pregnant and non-pregnant samples. Twenty-five metabolites that could discriminate between pregnant and non-pregnant Mithun based on Variable Importance in Projection (VIP) scores >1 were identified. Upon further examination of six metabolites (kynurenine, kynurenate, 3-hydroxykynurenine, quinolinate, tyrosine and leucine) identified with high VIP scores, ROC curve analyses demonstrated their significant predictive potential, with AUC values ranging between 0.50 and 0.85. Additionally, a combined panel of top 25 metabolites yielded an AUC value of 0.85. Pathway analysis identified seven potential metabolic pathway modulations during early gestation, with particular emphasis on phenylalanine, tyrosine and tryptophan biosynthesis, tryptophan pathway and pathways involved in the metabolism of various amino acids. In conclusion, kynurenine, kynurenate, 3-hydroxykynurenine, quinolinate, tyrosine, and leucine show promise as non-invasive urinary biomarkers for early pregnancy detection in Mithun. SIGNIFICANCE: This study presents the first report on the metabolic profile of urine from early pregnant and non-pregnant Mithun (Bos frontalis). The metabolites like kynurenine and its derivatives (kynurenate, 3-hydroxykynurenine and quinolinate), tyrosine and leucine were documented signature urinary metabolites associated with early pregnancy in Mithun. The identified combination of metabolites holds promise as predictive biomarkers for non-invasive urinary-based early pregnancy diagnostics in Mithun. In addition, this study identified changes in metabolic pathways that involve phenylalanine, tyrosine, tryptophan and related amino acids and biomarkers identified were either precursors or products within these metabolic pathways.

Genetic parameters of body weight traits in Mithun (Bos frontalis) using animal model

Mithun (Bos frontalis), a domestically raised herbivore, holds significant economic importance for the farming community of Northeast India. This study aimed to elucidate the genetic parameters governing Mithun body weight traits across different ages using data from the sole organized semi-intensive Mithun farm in India. Information was gathered from 110 Mithuns born over a period spanning from 2011 to 2022. Body weight taken at week 1 (W1), 1-month (M1), 3-months (M3), 6-months (M6), 9-months (M9), 12-months (M12), 30-months (M30) and 45-months (M45) were considered for the study. The genetic parameters estimation employed the BLUPF90 suite of programs, incorporating univariate Gibbs sampler animal model with fixed effects; season and period of birth, and sex of the animal. Variance and covariance components, including direct additive genetic effects, were estimated. Heritability estimates for the eight body weight traits ranged from 0.47 ± 0.0050 to 0.50 ± 0.0043, indicating varying genetic influence across growth stages. Results revealed that Mithun herd has a substantial genetic variability for growth traits and therefore there is ample scope to select for a better growth rate. Here, we conclude that Month 12 (M12) and Month 9 (M9) body weights exhibit higher heritability, indicating potential for genetic improvement through selective breeding.

Assessment of Constraints of Artificial Insemination Service in Smallholder Dairy Cattle Keepers in Kacha Bira District of Southern Ethiopia

Artificial insemination (AI) is among the most effective reproductive biotechnologies that afford widespread propagation of genes carried by superior males. A cross-sectional study followed by a simple random sampling technique was conducted from December 2021 to May 2022 to assess the constraints of artificial insemination (AI) provision in and around Kacha Bira district, Southern Ethiopia, using a structured questionnaire. A total of 200 respondents were surveyed accordingly. In this study, the education level of farmers revealed no statistically significant difference $\left(P>0.05\right)$ with the identification of time of insemination. Conception failure (62.5%), unavailability of artificial insemination technicians (7.5%), dystocia (3.5%), and both conception failure and unavailability of artificial insemination technicians (4.5%) were found to be the major constraints of AI service in the study area according to dairy cattle owners’ response and revealed a statistically significant difference $\left(P<0.05\right)$ with AI service. Although statistically significant $\left(P<0.05\right)$ , differences in AI service interruptions during both regular working hours and weekends and holidays were also observed. Among total respondents, 20.5% of dairy cattle owners got AI service at right time, but 79.5% of them used it at the wrong time. Regarding inbreeding problems, 77.5% of dairy cattle owners responded that there was no inbreeding problem and the remaining 22.5% of farmers indicated presence of inbreeding problem of which 10.5% and 10% had a perception that local breeds had low milk production and low genetic improvement than exotic breeds, respectively. On the other hand, 11.5% of dairy cattle owners responded that local breeds have a similar level of disease resistance to that of exotic breeds (11%). 48.5% of dairy farmers reported that bellowing is the most frequent sign that they used to detect heat followed by vulval discharge (23%) and mounting on other cows (10%). Majority (78.5%) of the dairy cattle owners interviewed were found to be not satisfied with the artificial insemination services. In general, different AI technicians and cattle and dairy cattle keeper-related factors constrain the AI service and its result in survey site. Therefore, smallholder dairy cattle owners should be trained sufficiently about the AI service strategies, usage, and proper management of dairy farms and the technical constraints should be avoided in order to provide AI service sufficiently.