Selection for Favorable Health Traits: A Potential Approach to Cope with Diseases in Farm Animals

Identification of AGO2 and PLEC genes polymorphisms in Hu sheep and their relationship with body size traits

The body size traits are major traits in livestock, which intuitively displays the development of the animal's bones and muscles. This study used PCR amplification, Sanger sequencing, KASPar genotyping, and quantitative real-time reverse transcription PCR (qRT-PCR) to analyze the Single-nucleotide polymorphism and expression characteristics of Argonaute RISC catalytic component 2 (AGO2) and Plectin (PLEC) genes in Hu sheep. Two intron mutations were found in Hu sheep, which were AGO2 g.51700 A > C and PLEC g.23157 C > T, respectively. Through association analysis of two mutation sites and body size traits, it was found that AGO2 g.51700 A > C mainly affects the chest and cannon circumference of Hu sheep of while PLEC g.23157 C mainly affects body height and body length. The combined genotypes of AGO2 and PLEC genes with body size traits showed SNPs at the AGO2 g.51700 A > C and PLEC g.23157 C > T loci significantly improved the body size traits of Hu sheep. In addition, the AGO2 gene has the highest expression levels in the heart, rumen, and tail fat, and the PLEC gene is highly expressed in the heart. These two loci can provide new research ideas for improving the body size traits of Hu sheep.

MicroRNAs: exploring their role in farm animal disease and mycotoxin challenges

MicroRNAs (miRNAs) serve as key regulators in gene expression and play a crucial role in immune responses, holding a significant promise for diagnosing and managing diseases in farm animals. This review article summarizes current research on the role of miRNAs in various farm animal diseases and mycotoxicosis, highlighting their potential as biomarkers and using them for mitigation strategies. Through an extensive literature review, we focused on the impact of miRNAs in the pathogenesis of several farm animal diseases, including viral and bacterial infections and mycotoxicosis. They regulate gene expression by inducing mRNA deadenylation, decay, or translational inhibition, significantly impacting cellular processes and protein synthesis. The research revealed specific miRNAs associated with the diseases; for instance, gga-miR-M4 is crucial in Marek's disease, and gga-miR-375 tumor-suppressing function in Avian Leukosis. In swine disease such as Porcine Respiratory and Reproductive Syndrome (PRRS) and swine influenza, miRNAs like miR-155 and miR-21-3p emerged as key regulatory factors. Additionally, our review highlighted the interaction between miRNAs and mycotoxins, suggesting miRNAs can be used as a biomarker for mycotoxin exposure. For example, alterations in miRNA expression, such as the dysregulation observed in response to Aflatoxin B1 (AFB1) in chickens, may indicate potential mechanisms for toxin-induced changes in lipid metabolism leading to liver damage. Our findings highlight miRNAs potential for early disease detection and intervention in farm animal disease management, potentially reducing significant economic losses in agriculture. With only a fraction of miRNAs functionally characterized in farm animals, this review underlines more focused research on specific miRNAs altered in distinct diseases, using advanced technologies like CRISPR-Cas9 screening, single-cell sequencing, and integrated multi-omics approaches. Identifying specific miRNA targets offers a novel pathway for early disease detection and the development of mitigation strategies against mycotoxin exposure in farm animals.

ranchSATdb: A Genome-Wide Simple Sequence Repeat (SSR) Markers Database of Livestock Species for Mutant Germplasm Characterization and Improving Farm Animal Health

Microsatellites, also known as simple sequence repeats (SSRs), are polymorphic loci that play an important role in genome research, animal breeding, and disease control. Ranch animals are important components of agricultural landscape. The ranch animal SSR database, ranchSATdb, is a web resource which contains 15,520,263 putative SSR markers. This database provides a comprehensive tool for performing end-to-end marker selection, from SSRs prediction to generating marker primers and their cross-species feasibility, visualization of the resulting markers, and finding similarities between the genomic repeat sequences all in one place without the need to switch between other resources. The user-friendly online interface allows users to browse SSRs by genomic coordinates, repeat motif sequence, chromosome, motif type, motif frequency, and functional annotation. Users may enter their preferred flanking area around the repeat to retrieve the nucleotide sequence, they can investigate SSRs present in the genic or the genes between SSRs, they can generate custom primers, and they can also execute in silico validation of primers using electronic PCR. For customized sequences, an SSR prediction pipeline called miSATminer is also built. New species will be added to this website's database on a regular basis throughout time. To improve animal health via genomic selection, we hope that ranchSATdb will be a useful tool for mapping quantitative trait loci (QTLs) and marker-assisted selection. The web-resource is freely accessible at https://bioinfo.usu.edu/ranchSATdb/.

Comparative Characterization of Immune Response in Sheep with Caseous Lymphadenitis through Analysis of the Whole Blood Transcriptome

Caseous lymphadenitis (CL) is a chronic contagious disease that affects small ruminants and is characterized by the formation of pyogranulomas in lymph nodes and other organs. However, the pathogenesis of this disease and the response of the host genome to infection are not yet fully understood. This study aimed to investigate the whole blood transcriptome and evaluate differential gene expression during the later stages of CL in naturally infected ewes. The study included diseased, serologically positive (EP), exposed, serologically negative (EN) ewes from the same infected flock and healthy ewes (CN) from a different flock. RNA sequencing was performed using the Illumina NextSeq system, and differential gene expression was estimated using DESeq2 and Edge R approaches. The analysis identified 191 annotated differentially expressed genes (DEGs) in the EP group (102 upregulated and 89 downregulated) and 256 DEGs in the EN group (106 upregulated and 150 downregulated) compared to the CN group. Numerous immunoregulatory interactions between lymphoid and nonlymphoid cells were influenced in both EP and EN ewes. Immune DEGs were preferentially assigned to antigen presentation through the MHC complex, T lymphocyte-mediated immunity, and extracellular matrix interactions. Furthermore, the EP group showed altered regulation of cytokine and chemokine signaling and activation and recombination of B-cell receptors. Conversely, NF-kappa B signaling, apoptosis, and stress response were the main processes influenced in the EN group. In addition, statistically significant enrichment of the essential immune pathways of binding and uptake of ligands by scavenger receptors in EP and p53 signaling in the EN group was found. In conclusion, this study provides new insights into the disease course and host-pathogen interaction in naturally CL-infected sheep by investigating the blood transcriptome.

Genetic and phenotypic correlations between Aleutian disease tests with body weight, growth, and feed efficiency traits in mink

The ineffectiveness of vaccination, medicine, and culling strategy leads mink farmers to control Aleutian disease (AD) by selecting AD-resilient mink based on AD tests. However, the genetic background of AD tests and their correlations with economically important or AD-resilient traits are limited. This study estimated the genetic and phenotypic correlations between four AD tests and seven body weight (BW) traits, six growth parameters from the Richards growth model, and eight feed-related traits. Univariate models were used to test the significance (P < 0.05) of fixed effects (sex, color type, AD test year, birth year, and row-by-year), random effects (additive genetic, maternal genetic, and permanent environmental), and a covariate of age using ASReml 4.1. Likewise, pairwise bivariate analyses were conducted to estimate the phenotypic and genetic correlations among the studied traits. Both antigen- and virus capsid protein-based enzyme-linked immunosorbent assay tests (ELISA-G and ELISA-P) showed significant (P < 0.05) moderate positive genetic correlations (±SE) with maturation rate (from 0.36 ± 0.18 to 0.38 ± 0.19). ELISA-G showed a significant negative genetic correlation (±SE) with average daily gain (ADG, -0.37 ± 0.16). ELISA-P showed a significant positive moderate genetic correlation (±SE) with off-feed days (DOF, 0.42 ± 0.17). These findings indicated that selection for low ELISA scores would reduce the maturation rate, increase ADG (by ELISA-G), and minimize DOF (by ELISA-P). The iodine agglutination test (IAT) showed significant genetic correlations with DOF (0.73 ± 0.16), BW at 16 weeks of age (BW16, 0.45 ± 0.23), and BW at harvest (HW, -0.47 ± 0.20), indicating that selection for lower IAT scores would lead to lower DOF and BW16, and higher HW. These estimated genetic correlations suggested that the selection of AD tests would not cause adverse effects on the growth, feed efficiency, and feed intake of mink. The estimates from this study might strengthen the previous finding that ELISA-G could be applied as a reliable and practical indicator trait in the genetic selection of AD-resilient mink in AD-positive farms.

Applying Machine Learning Algorithms for the Classification of Mink Infected with Aleutian Disease Using Different Data Sources

Simple Summary

Aleutian disease (AD) is a major infectious disease found in mink farms, and it causes financial losses to the mink industry. Controlling AD often requires a counterimmunoelectrophoresis (CIEP) method, which is relatively expensive for mink farmers. Therefore, predicting AD infected mink without using CIEP records will be important for controlling AD in mink farms. In the current study, we applied nine machine learning algorithms to classify AD-infected mink. We indicated that the random forest could be used to classify AD-infected mink (accuracy of 0.962) accurately. This result could be used for implementing machine learning in controlling AD in the mink farms.

Abstract

American mink (Neogale vison) is one of the major sources of fur for the fur industries worldwide, whereas Aleutian disease (AD) is causing severe financial losses to the mink industry. A counterimmunoelectrophoresis (CIEP) method is commonly employed in a test-and-remove strategy and has been considered a gold standard for AD tests. Although machine learning is widely used in livestock species, little has been implemented in the mink industry. Therefore, predicting AD without using CIEP records will be important for controlling AD in mink farms. This research presented the assessments of the CIEP classification using machine learning algorithms. The Aleutian disease was tested on 1157 individuals using CIEP in an AD-positive mink farm (Nova Scotia, Canada). The comprehensive data collection of 33 different features was used for the classification of AD-infected mink. The specificity, sensitivity, accuracy, and F1 measure of nine machine learning algorithms were evaluated for the classification of AD-infected mink. The nine models were artificial neural networks, decision tree, extreme gradient boosting, gradient boosting method, K-nearest neighbors, linear discriminant analysis, support vector machines, naive bayes, and random forest. Among the 33 tested features, the Aleutian mink disease virus capsid protein-based enzyme-linked immunosorbent assay was found to be the most important feature for classifying AD-infected mink. Overall, random forest was the best-performing algorithm for the current dataset with a mean sensitivity of 0.938 ± 0.003, specificity of 0.986 ± 0.005, accuracy of 0.962 ± 0.002, and F1 value of 0.961 ± 0.088, and across tenfold of the cross-validation. Our work demonstrated that it is possible to use the random forest algorithm to classify AD-infected mink accurately. It is recommended that further model tests in other farms need to be performed and the genomic information needs to be used to optimize the model for implementing machine learning methods for AD detection.

Emerging Roles of Noncoding RNAs in Bovine Mastitis Diseases

Non-coding RNAs (ncRNAs) are an abundant class of RNA with varying nucleotide lengths. They have been shown to have great potential in eutherians/human disease diagnosis and treatments and are now gaining more importance for the improvement of diseases in livestock. To date, thousands of ncRNAs have been discovered in the bovine genome and the continuous advancement in deep sequencing technologies and various bioinformatics tools has enabled the elucidation of their roles in bovine health. Among farm animals' diseases, mastitis, a common inflammatory disease in cattle, has caused devastating economic losses to dairy farmers over the last few decades. Here, we summarize the biology of bovine mastitis and comprehensively discuss the roles of ncRNAs in different types of mastitis infection. Based on our findings and relevant literature, we highlighted various evidence of ncRNA roles in mastitis. Different approaches (in vivo versus in vitro) for exploring ncRNA roles in mastitis are emphasized. More particularly, the potential applications of emerging genome editing technologies, as well as integrated omics platforms for ncRNA studies and implications for mastitis are presented.

Association of Lactoferrin and Toll-like Receptor 2 Genotypes with Mastitis and Milk Components in Vietnamese Holstein Cattle

Mastitis is one of the most widespread diseases in dairy cows and causes huge losses for the dairy industry. Molecular markers can be used for the quick diagnosis of mastitis infection, consequently reducing the loss caused by this disease. Lactoferrin (LTF) and Toll-like receptor 2 (TLR2) have been suggested as candidate genes for mastitis; however, their associations with the mastitis incidence and milk components have not been reported in Vietnamese Holstein cows. This study examined the association of TLR2 and LTF polymorphisms with subclinical mastitis and milk components in the Holstein breed raised in Vietnam. Among 192 samples, we identified 44 mastitis-positive samples (22.92%). The mastitis significantly reduced the fat and lactose components in milk (p < 0.001) but increased the protein concentration in milk. A total of 94 (49%) and 98 (51%) cows had AA and AB genotypes for the LTF gene, respectively. No significant association was found between the LTF genotypes and the milk component traits or mastitis incidence (p > 0.05). The interaction between LTF and mastitis incidence was significantly associated with the protein percentage (p = 0.01). A total of 78, 76, and 38 cows had genotypes GG, GT, and TT for the TLR2 gene, respectively. TLR2 genotypes were not significantly associated with mastitis incidence (p > 0.05) but were significantly associated with pH value (p = 0.03). The interaction between TLR2 and mastitis incidence was significantly associated with the fat (p = 0.02) and protein percentage (p = 0.04). Further studies are required to confirm the roles of LTF and TFL2 in mastitis in the Holstein breed in Vietnam.

Designing prototype rapid test device at qualitative performance to detect residue of tetracycline in chicken carcass

Background and Aim:

Human health problems due as a microbial resistance or tumors and cancers because consumption of the carcasses containing residues of tetracycline are main global problems in the context of fight against antimicrobial resistance phenomena. Explanation of the sustainable development goals, particularly point 3, is well recognized that all animal products for human consumption must be safe to live a healthy life. This study aimed to design a prototype of rapid test devices (RTD) based on principles of precipitate to obtain a specific color change after the process of reactions as an indicator to determine tetracycline residues in the carcass.

Materials and Methods:

Five samples of tetracycline-containing poultry carcasses using artificial add the tetracycline at pharmaceutics grade were examined using a prototype of a strong reaction solution for tetracycline fixation based on the concept bonded by ion Fe(III) at atom O in position atom C-1 at the ring of tetracycline and ion N⁺ as the functional branch of tetracycline. RTD detection was evaluated using a yellow color presentation and an absorbance spectrometric technique at a wavelength of 273 nm.

Results:

The following chemicals were used to create the best-fixed tetracycline residue: HCl and H₂SO₄ dissolved in H₂O, chromatographic grade of 0.1 N and 0.5 N of HNO₃, and 1% Fe (III) Cl. The RTD had a higher limit of detection (LOD) than the ultraviolet-visible spectrophotometer.

Conclusion:

The results of this study revealed that RTD, as constructed in this study, can be used to detect residue at LOD 44.764 mg/mL during 120 min of exposure through a light-emitting diode at 980 nm wavelength (p<0.05). The necessity for using RTD was because of the apparent limitations of conventional devices.

Direct and indirect contributions of molecular genetics to farm animal welfare: a review

Since domestication, farm animals have played a key role to increase the prosperity of humankind, while animal welfare (AW) is debated even today. This paper aims to comprehensively review the contributions of developing molecular genetics to farm animal welfare (FAW) and to raise awareness among both scientists and farmers about AW. Welfare is a complex trait affected by genetic structure and environmental factors. Therefore, the best welfare status can be achieved not only to enhance environmental factors such as management and feeding practices, but also the genetic structure of animals must be improved. In this regard, advances in molecular genetics have made great contributions to improve the genetic structure of farm animals, which has increased AW. Today, by sequencing and/or molecular markers, genetic diseases may be detected and eliminated in local herds. Additionally, genes related to diseases or adaptations are investigated by molecular techniques, and the frequencies of desired genotypes are increased in farm animals to keep welfare at an optimized level. Furthermore, stress on animals can be reduced with DNA extraction from stool and feather samples which reduces physical contact between animals and veterinarians. Together with molecular genetics, advances in genome editing tools and biotechnology are promising to improve FAW in the future.

Johne's Disease in Dairy Cattle: An Immunogenetic Perspective

Johne's disease (JD), also known as paratuberculosis, is a severe production-limiting disease with significant economic and welfare implications for the global cattle industry. Caused by infection with Mycobacterium avium subspecies paratuberculosis (MAP), JD manifests as chronic enteritis in infected cattle. In addition to the economic losses and animal welfare issues associated with JD, MAP has attracted public health concerns with potential association with Crohn's disease, a human inflammatory bowel disease. The lack of effective treatment options, such as a vaccine, has hampered JD control resulting in its increasing global prevalence. The disease was first reported in 1895, but in recognition of its growing economic impact, extensive recent research facilitated by a revolution in technological approaches has led to significantly enhanced understanding of the immunological, genetic, and pathogen factors influencing disease pathogenesis. This knowledge has been derived from a variety of diverse models to elucidate host-pathogen interactions including in vivo and in vitro experimental infection models, studies measuring immune parameters in naturally-infected animals, and by studies conducted at the population level to enable the estimation of genetic parameters, and the identification of genetic markers and quantitative trait loci (QTL) putatively associated with susceptibility or resistance to JD. The main objectives of this review are to summarize these recent developments from an immunogenetics perspective and attempt to extract the principal and common findings emerging from this wealth of recent information. Based on these analyses, and in light of emerging technologies such as gene-editing, we conclude by discussing potential future avenues for effectively mitigating JD in cattle.

miRNA Regulatory Functions in Farm Animal Diseases, and Biomarker Potentials for Effective Therapies

MicroRNAs (miRNAs) are small endogenous RNAs that regulate gene expression post-transcriptionally by targeting either the 3′ untranslated or coding regions of genes. They have been reported to play key roles in a wide range of biological processes. The recent remarkable developments of transcriptomics technologies, especially next-generation sequencing technologies and advanced bioinformatics tools, allow more in-depth exploration of messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs), including miRNAs. These technologies have offered great opportunities for a deeper exploration of miRNA involvement in farm animal diseases, as well as livestock productivity and welfare. In this review, we provide an overview of the current knowledge of miRNA roles in major farm animal diseases with a particular focus on diseases of economic importance. In addition, we discuss the steps and future perspectives of using miRNAs as biomarkers and molecular therapy for livestock disease management as well as the challenges and opportunities for understanding the regulatory mechanisms of miRNAs related to disease pathogenesis.

Population Genomics of American Mink Using Whole Genome Sequencing Data

Characterizing the genetic structure and population history can facilitate the development of genomic breeding strategies for the American mink. In this study, we used the whole genome sequences of 100 mink from the Canadian Centre for Fur Animal Research (CCFAR) at the Dalhousie Faculty of Agriculture (Truro, NS, Canada) and Millbank Fur Farm (Rockwood, ON, Canada) to investigate their population structure, genetic diversity and linkage disequilibrium (LD) patterns. Analysis of molecular variance (AMOVA) indicated that the variation among color-types was significant (p < 0.001) and accounted for 18% of the total variation. The admixture analysis revealed that assuming three ancestral populations (K = 3) provided the lowest cross-validation error (0.49). The effective population size (Ne) at five generations ago was estimated to be 99 and 50 for CCFAR and Millbank Fur Farm, respectively. The LD patterns revealed that the average r² reduced to <0.2 at genomic distances of >20 kb and >100 kb in CCFAR and Millbank Fur Farm suggesting that the density of 120,000 and 24,000 single nucleotide polymorphisms (SNP) would provide the adequate accuracy of genomic evaluation in these populations, respectively. These results indicated that accounting for admixture is critical for designing the SNP panels for genotype-phenotype association studies of American mink.