Porcine circovirus type 3 (PCV3) is an emerging pathogen linked with reproductive failure, respiratory disease, dermatitis, nephropathy, and multisystemic inflammation, posing growing threats to the swine industry worldwide. Although molecular evidence of PCV3 circulation has been reported in India, there is no published information on its seroprevalence, leaving the extent of exposure and population immunity largely unknown. Serological tools are critical for epidemiological surveillance and monitoring vaccine responses; however, validated assays for PCV3 remain scarce. In the present study, we developed and evaluated an indirect enzyme-linked immunosorbent assay (ELISA) for the detection of PCV3-specific antibodies, based on a recombinant truncated Cap protein expressed in Escherichia coli. The antigenic fragment of the Cap gene, excluding the N-terminal nuclear localization signal, was used as coating antigen and assay parameters like optimal antigen concentration, serum dilution, and conjugate conditions, were standardized. The developed ELISA exhibited high specificity, with no cross-reactivity to antisera against other common porcine viruses, and the relative diagnostic sensitivity and specificity were estimated to be 97.0 % and 94.5 %, respectively. The assay also demonstrated strong repeatability and reproducibility and was validated at four different laboratories with κ- values indicating perfect agreement Application of the assay to field sera revealed widespread seropositivity (64.25 %), underscoring its utility for epidemiological surveillance and sero-monitoring of PCV3. This study provides the first indigenous ELISA with potential application in India, and is the first report indicating widespread seropositivity of PCV3 in India.

The present study aimed to characterize the immune response, differential gene expression, and functional alterations observed following an in vivo challenge of Classical Swine Fever Virus (CSFV) in crossbred pigs. RNA-sequencing was performed on whole blood samples collected from three pigs before and at 7 days post-infection. A total of 3428 differentially expressed genes (DEGs) were identified, including 970 significantly upregulated and 261 downregulated genes (|log2 fold change| ≥ 1.5, adjusted p < 0.05). The most prominent DEG was LAMB4, a gene associated with cellular attachment receptors facilitating CSFV binding to porcine cells. Several cytokine-cytokine receptor interaction genes, such as CXCL12, CCL2, CCR1, and IL10RA, were upregulated, indicating a strong activation of innate immune responses. Simultaneously, multiple adaptive immune genes, including CD28, CD83, SLA-DQB1, and IL1A, IL12A, IL26 were downregulated, suggesting viral-mediated suppression of antigen presentation and T-cell signaling. Pathway analysis highlighted the involvement of platelet activation and coagulation cascades during viral evasion. Protein-protein interaction (PPI) analysis revealed a core antiviral module comprising MX1, MX2, ISG15, IFIH1, OASL, IFIT1, and UBE2L6, which are central to interferon signaling and viral restriction. Transcription factors such as ETV7, TOX3, and MSC were upregulated, pointing to immune modulation and possible T-cell exhaustion. Conversely, downregulation of HES1, PRDM6, and MYOG indicated impaired lymphocyte differentiation and tissue repair. Overall, the findings suggest a dual host response to CSFV, with strong innate activation alongside adaptive immune suppression, providing valuable insights for vaccine and therapeutic development.

Subclinical mastitis (SCM) is a major constraint in dairy production and is driven by complex host–pathogen interactions. Although transcriptional responses associated with SCM have been widely investigated, the epigenetic mechanisms that stably regulate these programs remain less well characterized, particularly in crossbred cattle populations. This study aimed to characterize DNA methylation-based regulatory networks by integrating whole-genome methylation and transcriptome data from milk somatic cells of Vrindavani (Bos taurus × Bos indicus) cattle. Whole-genome methylation (n = 6) and corresponding transcriptome profiling (n = 6) were performed on milk somatic cells from SCM-affected and healthy control cows. Differential methylation analysis (q-value < 0.05) identified 62,940 differentially methylated cytosines (DMCs), 7,706 differentially methylated regions (DMRs), and 6,203 differentially methylated genes (DMGs), with a predominant bias toward hypomethylation in SCM. Integrative analysis using stringent thresholds for both methylation (≥ 10

Antimicrobial peptides (AMPs), produced constitutively by all living organisms serve as critical components of the innate immune system. Owing to their broad-spectrum antimicrobial activity and low propensity for resistance development, AMPs represent promising alternatives to conventional antibiotics. Mesenchymal stem cells (MSCs), beyond their regenerative capabilities; have gained attention for their innate antimicrobial properties. In this study, we performed de novo transcriptome analysis for the expression of AMPs in canine MSCs following bacterial priming and assessed the in vitro antimicrobial activity of the conditioned media. MSCs were isolated and characterized from canine umbilical cord tissue. The cells were primed with Staphylococcus aureus by transwell culture method for 6 h. The RNA was extracted from these primed cells and whole transcriptome profile was generated through next-generation RNA sequencing. The antimicrobial activity of primed-cell culture supernatant was assessed in vitro. Using Illumina Novaseq sequencer, we obtained 26.23 million high quality clean reads and subsequently de novo assembled into 59,214 contigs which were annotated using Trinity, TransDecoder, UniProt database and validated with CAMPR4 database. The database could identify a total 30 potential AMPs; among them 8 were found which matched with the existing database and the remaining 22 were predicted to be AMPs. The conditioned media exhibited strong antibacterial effects against S. aureus, likely attributable to the secreted AMPs. These findings highlight the capacity of canine MSCs to serve as a source of both known and novel AMPs that could be screened for prospective biotherapeutic strategies. Workflow of transcriptome analysis for AMP detection of cUC-MSC

This study evaluated the dietary effect of complete substitution (32%) of maize grain with a self-fermented agro-waste mix (SFAWM) composed of apple pomace, spent mushroom residue, and wheat straw in male Gaddi goats. The study included two treatments viz. Control and SFAWM32 with six animals (3-4 months) per treatment (n = 6). After feeding for 150 days, goats were slaughtered for the determination of carcass yield, meat physico-chemical traits and fatty acid composition. Replacing maize with SFAWM32 reduced daily dry matter intake by 17.8% with comparable average daily gain, resulting in an improved feed conversion ratio by 22.4% compared with the Control group (P < 0.05). Linear body measurements and carcass characteristics were not significantly affected by the treatment. Meat from animals fed SFAWM32 exhibited improved tenderness (P < 0.001), greater redness value (a*) (P < 0.001), and lower thiobarbituric acid-reactive substance values (P = 0.023) compared with the Control group. The fatty acid profile showed a significant reduction in total and selected saturated fatty acids, accompanied by significantly greater levels of n-3 PUFA, resulting in a more favourable n-6/n-3 ratio. Meat from the SFAWM32 group also showed increased (P < 0.001) moisture content compared with the Control group. Results demonstrate that self-fermented agro-waste mix at 32% maize grain replacement level in goat diet improved FCR, tenderness, a*, oxidative stability, and n-3 PUFA content of meat. The approach offered an effective and sustainable strategy to address food-feed competition with improvement in meat nutritional value and oxidative stability.

Foot-and-Mouth Disease (FMD) continues to pose a major threat to global livestock health and food security, particularly in endemic regions like India. A primary challenge in FMD control is the inability of conventional vaccines to differentiate infected from vaccinated animals (DIVA), a limitation that complicates surveillance and restricts international trade. To address this, we evaluated a trivalent negative-marker FMD vaccine targeting serotypes O, A, and Asia 1, with immunogenicity and protective efficacy assessed in cattle, the target host species. The vaccine elicited robust humoral and cellular immune responses. Virus-neutralizing antibody titers peaked at 2-4 weeks and remained significant for six months. Cellular profiling revealed a dynamic Th1/Th2 response, characterized by an early IL-4 peak at 7 days post-vaccination (DPV), followed by peak IFN-γ secretion at 14 DPV, correlating with antibody isotype switching from IgG1 to IgG2, indicating a balanced immune response. Importantly, the vaccine conferred protection of cattle against homologous serotype O virus challenge for up to six months. Furthermore, DIVA compliance was unequivocally demonstrated by the absence of antibodies to the deleted 3A segment in repeated booster vaccination studies in guinea pigs. Collectively, these findings show that the trivalent marker vaccine provides protective efficacy equivalent to conventional vaccine while enabling the immunological monitoring essential for strategic FMD control programs.

Rathi cattle, an indigenous Bos indicus breed of north-western India, represent a valuable genetic resource due to their adaptation to arid environments, heat tolerance and dairy potential. However, genomic information on this breed remains limited. This study provides the first double-digest restriction-site associated DNA sequencing (ddRAD) based genome-wide assessment of Rathi cattle using a large sample size. A total of 96 animals were genotyped, generating 78,193 high-quality SNPs with 96.52

The recurring Fibonacci sequence in various biological systems proves that mathematical ideas are frequently mirrored in natural patterns. This work assumes the compelling theory that cattle genomes may exhibit similar periodic and recursive patterns, particularly in regions associated with reproductive fitness. Unregulated crossbreeding can jeopardize indigenous germplasm and disturb natural genomic configurations, endangering genetic diversity and the structural integrity of the genome. We suggest that animal genomes may follow observable mathematical patterns by looking at haplotype and single-nucleotide polymorphism (SNP) distributions. Finding these hidden patterns through whole genome sequencing (WGS) is crucial for rethinking genetic improvement strategies in livestock breeding programs and providing insights into optimising reproductive traits.

Cattle are integral to agriculture and rural livelihoods in India, where diverse indigenous breeds have adapted to varied environments. The diversity of Indian breeds has shaped genetic traits linked to toxin processing, disease resistance, and metabolic efficiency. The genomic study of cattle reveals significant insights into the evolutionary pressures shaping drug-metabolizing genes (DMGs) across breeds. This study analyzed genome-wide selection signatures in seven cattle breeds, including Indigenous such as Red Sindhi (n = 96), Tharparkar (n = 72), Gir (n = 96), crossbred such as Frieswal (n = 14), Vrindavani (n = 72), and exotic cattle populations such as Holstein Friesian (n = 63), Jersey (n = 28). We utilized 50K and ddRAD SNP genotyping data to perform intra-population analyses (iHS, CLR, ROH) and inter-population analyses (FST, XP-EHH) for detecting genomic regions under selection. Key findings include the identification of cytochrome P450 genes (e.g., CYP7A1, CYP4A11, CYP19A1) and other DMGs exhibiting selection signatures linked to metabolic and biosynthetic processes. Red Sindhi cattle exhibited selection in genes like CYP7A1 and CYP2W1, which were involved in steroid biosynthesis and chemical stimulus response. Tharparkar cattle demonstrated positive selection in CYP4A11 and related genes involved in the functionalization of compounds. Crossbreeds of Vrindavani and Frieswal displayed intermediate signatures, reflecting mixed genetic contributions. Our research shows that Indigenous purebred cattle possess a superior selection signature of drug-metabolizing ability, enhanced disease resistance, and greater adaptability than crossbred and exotic breeds. This research contributes to understanding breed-specific adaptations, informing pharmacological interventions and conservation efforts.

Litter size in mice is an important fitness and economic feature that is controlled by several genes and influenced by non-genetic factors too. High positive selection pressure in each generation for Litter size at birth (LSB), resulted in the development of high and low prolific lines of inbred Swiss albino mice (SAM). Despite uniform management conditions, these lines showed variability in LSB across the generation. Variation in estrous-phased ovarian gene expression between high (LSB ≥ 12) and low prolific lines (LSB ≤ 3) of F4 inbred SAM, was explored using RNA-Seq. Estrous phase assessment was done using vaginal cytology. A total of 870 differentially expressed genes (DEGs) were identified; among which, 287 genes were significantly up-regulated while 583 genes were down-regulated in HLS as compared to the LLS group. DEGs were assigned to 166 Gene Ontology (GO) terms and KEGG pathways. In HLS, the significantly up-regulated DEGs were involved in ovarian cell-cell signaling, regulation of biological activity and ovarian metabolic-associated pathways. Most down-regulated DEGs were expressed in immune-related pathways, indicating that immunological dampening is associated with a high ovulation rate and higher level of progesterone concentration leading to physiological changes responsible for higher fecundity. The present study, based on bulk RNA-seq analysis reflects the aggregate gene expression of the whole ovarian tissue, and reveals 24 DEGs that could be used as candidates for litter size attributes in future polymorphism and functional studies to gain further insights into the mechanisms underlying litter size variations in animals.

Pigs are highly susceptible to heat stress and their performance affects sustainability of the pig farming sector. It is therefore, essential to understand their behavior in different climatic conditions. In this work, 24 Landlly crossbred pigs in grower stage with uniform body weight were selected and randomly divided into two groups (heat stress [HS] and heat stress alleviated [HSA]). The HSA group was supplemented with a sensor-based cooling system to minimize heat stress. Major micro-climatic variables viz., ambient temperature (AT), relative humidity (RH %) and temperature humidity index (THI) were recorded twice daily in both pens. Mean AT, RH and THI around the micro-climate were 29.6 ± 0.15 °C, 72.4 ± 0.19 % and 80 ± 0.24, respectively. The lying, sitting, standing, feeding, drinking, and agonistic behavior were recorded daily for 90 days (June, July, August 2023) using 2 fixed Axis M1065 IP cameras. Ethogram was prepared for each behavior individually after segregating the recording from 0900 to 1700 h where maximum AT, RH and THI variations were experienced. Significant increase in the duration of lateral lying, water trough access, walking and standing posture (p < 0.01) were observed in heat stressed pigs. Average feed intake time per animal increased by ∼15 % than normal. During extreme periods of heat, time spend for sternal lying and sitting was significantly lower by 55 % and 25 %, respectively (p < 0.01). Additionally, high incidence of tail biting and agonistic behaviors (p < 0.01) were observed in the HS group. Variation within groups revealed that harsh effects of heat stress in pigs were more evident during the hot-dry period.

Genetic monitoring of inbred laboratory animal populations, developed at any laboratory, is one of the key elements of quality control and their colony management. The present study aimed to mine microsatellite (or SSR) markers from double digest restriction-site associated DNA (ddRAD) sequencing data of outbred foundation stock and F9 inbred generation of Swiss albino mice. Genomic DNA (12 F0 outbred and 12 F9 inbred) was isolated from tail tissue samples of F0 outbred and F9 inbred Swiss albino mice and processed for genotyping by sequencing using ddRAD platform. Double digestion of DNA was done using EcoR1 and Mse1 enzymes, and ddRAD data was subsequently analysed to identify and characterize microsatellite markers at genome-wide level. The analysis involved three key steps: pre-processing of reads, single sequence repeat (SSR) mining, and primer designing using different software i.e., PEAR, stacks and QDD. A total of 508 and 353 SSR motifs were identified in the outbred and inbred groups, respectively. Additionally, 828 and 551 primer sets were designed for the outbred and inbred groups, respectively. Furthermore, SSR loci specific to the outbred and inbred groups were also identified. Among these, eight SSR motifs (three each specific to the outbred and inbred groups, and two common) were validated using PCR amplification and gel electrophoresis. The designed primer sets successfully amplified respective SSR loci and produced reproducible bands on gel electrophoresis. The validated microsatellites were mapped to specific chromosomal locations using NCBI BLASTN with Mus musculus as the reference genome. In conclusion, the present study reports mining of SSR loci in outbred and inbred mice population. SSR loci were found to be more abundant and diverse in outbred population as compared to the inbred population. The unique SSRs identified for outbred and inbred groups will be helpful in checking the strain purity, marker assisted selection, and breeding programs without need for repeating the ddRAD sequencing in other laboratory animal population.

Red Sindhi cattle, a distinguished dairy breed from India, are famous for their resilience in tropical climates and exceptional milk yield. This study utilized double digest restriction site-associated DNA sequencing (ddRADseq) across 96 individuals to explore genome-wide diversity and uncover signatures of selection. The analysis revealed a high proportion of polymorphic SNPs (0.956), moderate nucleotide diversity (π = 0.215 ± 0.114), and a low minor allele frequency (MAF = 0.149 ± 0.128). The analysis of Red Sindhi data showed a steep decline in effective population size (Ne) from 2387 to 125.9 over 13 generations, implying potential bottlenecks and underscoring the urgency of conservation efforts. Employing Tajima’s D, composite likelihood ratio (CLR), integrated haplotype score (iHS), and runs of homozygosity (ROH) methods, we identified 490 genomic regions under positive selection, encompassing 1282 genes and aligning with 574 quantitative trait loci (QTLs). Functional annotations highlighted several genes linked to reproduction (RHOU, MND1), production (DOK6, NPFFR2), immune response (BOLA-DYA and BOLA-DMB), and environmental adaptation (HSPA14, NOD2, GCLC, and RPS19BP1). Several MHC class II genes under selection pressure indicate robust immune competence, while stress-response genes supported Red Sindhi’s remarkable tolerance to extreme heat. These findings show the breed’s strong adaptability and disease resilience, underlining its importance as a valuable genetic resource for improving livestock in challenging environments.

Animal breeding has undergone profound transformations from its origins in phenotypic observation to the integration of genomic and machine learning techniques. This review paper explores the progression of livestock breeding, tracing its roots to the domestication of animals during the Neolithic Revolution. Gregor Mendel's foundational work with pea plants established key principles of Mendelian genetics, which initially focused on discrete qualitative traits. However, the advancement of quantitative genetics has shifted the focus to continuous traits, such as body weight and milk yield, which are influenced by multiple genes. QTL mapping revolutionized breeding by shifting from phenotype- to genotype-based selection, enhancing accuracy through genomic predictions like GEBV under GBLUP. The strongest QTL associations on chromosome 18 linked local GEBV with FUK and DDX19B expression. In recent years, machine learning and artificial intelligence have transformed genomic prediction into livestock breeding by efficiently handling high-dimensional data and capturing complex genetic relationships. Notably, a deployed deep learning model achieved an average correlation of up to 0.643 between actual and predicted values. This review highlights the integration of machine learning approaches in animal breeding, showcasing advancements in milk and meat production, and the improvement of disease management through multi-omics strategies. The paper underscores the shift towards innovative methods and their impact on advancing animal breeding practices, offering insights into prospects for enhancing productivity, health, and welfare in livestock.

The present study was undertaken to elucidate the population structure and differentiation of Indian yak from Chinese and wild cohorts on genome-wide scale by identifying the selection sweeps and genomic basis of their adaptation across different comparisons while analyzing whole genome sequencing (WGS) data using latest bioinformatics tools. The study included 105 individuals from three distinct yak populations i.e., Indian yak (n = 29); Chinese yak (n = 61) and wild yak (n = 15), hypothesized to be related along the evolutionary timescale. Efficient variant calling and quality control in GATK and PLINK programs resulted in around 1 million (1,002,970) high-quality (LD-independent) SNPs with an average genotyping rate of 96.55

This study aims to comprehensively explore genome-wide selective processes influencing reproductive traits across six cattle breeds by employing different statistical methods. Reproductive efficiency is crucial for livestock productivity, as it directly influences the number of offspring and, consequently, the availability of animals for production. Early reproductive development and high fertility in herds boost selection intensity, driving faster genetic gains. This efficiency underpins the sustainability and profitability of livestock systems. To identify genomic signatures related to these traits, this study utilises genotyping technologies, including the Illumina BovineSNP50 Bead Chip and GGP Bos indicus 70k array. For this work, we used four summary statistics, including two intra-population statistics (Tajima's D and iHS), and two inter-population statistics (Rsb and XP-EHH). After identifying the key locations for selection, the NCBI database and the Cattle QTL database were utilised for annotation. The genes CACNA1H, KCNIP4, GDF9, SLC4A4, DHX57, EIF2AK3 and ME3 have been demonstrated to be under positive selection in Gir cattle. These are associated with characteristics such as udder cleft, age at puberty, sperm counts, sperm motility, sperm acrosome integrity rate, sperm motility per conception, sperm counts, conception rate, etc. Two genes, ENTHD1 and PRDM16 found on chromosomes 5 and 16, respectively, have been shared by Tharparkar and Gir which were undergoing positive selection. The ENTHD1 gene is linked to reproductive traits such as calving ease and stillbirth. Meanwhile, the PRDM16 gene is associated with characteristics like udder cleft, udder attachment, udder depth and udder height. The genes RXFP2, FRY, ENTHD1, SREBF2, RNF10, NYAP2, VWF, PPP1R8, EYA3, BBX, and TRPM3 were consistently identified across multiple selection signature methods, highlighting them as strong candidates under intense selection pressure. This approach offers valuable insights into the genetic basis of variations in reproductive traits, facilitating informed selection processes and enhancing our understanding of evolutionary and domestication in diverse cattle breeds.

Goats are vital to the rural economy of India, contributing significantly to livelihoods, nutrition, and agricultural sustainability. With a population of 148.88 million, India holds the world’s largest goat population, comprising 41 recognized indigenous breeds. These goats provide milk, meat, and fiber, particularly in marginal environments. The genomic advancements in goat research have revolutionized the understanding of genetic diversity, adaptation, and trait improvement. Whole-genome sequencing (WGS), single nucleotide polymorphism (SNP) arrays and transcriptomics have unveiled genetic markers associated with production, disease resistance, and reproductive traits. Genomic tools such as the Illumina Goat SNP50K BeadChip and high-throughput sequencing technologies have facilitated the identification of selection signatures and quantitative trait loci (QTL), influencing economically important traits like milk yield, meat quality, and prolificacy. Notably, genes such as DGAT1, GHR, BMPR1B, and HSP70 have been linked to production efficiency, reproductive performance, and climate resilience. Genome-wide association studies (GWAS) and genomic selection (GS) have enabled precision breeding, enhancing genetic gains and reducing inbreeding risks. The application of RNA sequencing has provided insights into gene expression patterns governing lactation, growth, and reproductive efficiency. Epigenomic studies, focusing on DNA methylation and histone modifications, have highlighted regulatory mechanisms underpinning prolificacy and muscle development. Conservation genomics has played a pivotal role in safeguarding native breeds by assessing genetic diversity and mitigating inbreeding depression. Indicine goat breeds, such as Jamunapari, Beetal, Barbari, and Black Bengal, exhibit unique genetic adaptations to diverse agro-climatic conditions, emphasizing the need for their conservation. Emerging technologies, including CRISPR-Cas9 gene editing, hold promise for precision breeding to enhance productivity and disease resistance. Integrating genomics with artificial intelligence (AI) and big data analytics is poised to revolutionize goat breeding and management. Future efforts should focus on expanding genomic databases, developing breed-specific reference genomes, and promoting genomic literacy among farmers to ensure sustainable goat production and improve rural livelihoods in India.