Heat stress impacts ruminant livestock production on varied levels in this alarming climate breakdown scenario. The drastic effects of the global climate change-associated heat stress in ruminant livestock demands constructive evaluation of animal performance bordering on effective monitoring systems. In this climate-smart digital age, adoption of advanced and developing Artificial Intelligence (AI) technologies is gaining traction for efficient heat stress management. AI has widely penetrated the climate sensitive ruminant livestock sector due to its promising and plausible scope in assessing production risks and the climate resilience of ruminant livestock. Significant improvement has been achieved alongside the adoption of novel AI algorithms to evaluate the performance of ruminant livestock. These AI-powered tools have the robustness and competence to expand the evaluation of animal performance and help in minimising the production losses associated with heat stress in ruminant livestock. Advanced heat stress management through automated monitoring of heat stress in ruminant livestock based on behaviour, physiology and animal health responses have been widely accepted due to the evolution of technologies like machine learning (ML), neural networks and deep learning (DL). The AI-enabled tools involving automated data collection, pre-processing, data wrangling, development of appropriate algorithms, and deployment of models assist the livestock producers in decision-making based on real-time monitoring and act as early-stage warning systems to forecast disease dynamics based on prediction models. Due to the convincing performance, precision, and accuracy of AI models, the climate-smart livestock production imbibes AI technologies for scaled use in the successful reducing of heat stress in ruminant livestock, thereby ensuring sustainable livestock production and safeguarding the global economy.

The livestock sector, a crucial source of revenue and global food security, is facing serious challenges due to climate change driven by global warming. This leads to serious effects on animal health and productivity, making it difficult for the livestock industry to meet the global demand and sustain the livelihoods of farmers. The main factor affecting livestock’s productivity is heat stress. However, animals develop various adaptive mechanisms to cope with the effects of heat stress. Cellular and molecular responses act as key defense mechanisms, enabling animals adapt to environmental changes. The recent advancements in molecular biology have opened up opportunities for extensive research on epigenetics, which has a key role in regulating gene expression in animals in response to environmental stimuli. Such studies have gained considerable attention regarding heat acclimation in animals due to the fact that epigenetic mechanisms have been recognized as key players in long-term adaptation to high temperatures in farm animals. This review summarizes the different mechanisms and methodologies used to assess heat stress-associated epigenetic changes, including DNA methylation, which is an extensively studied epigenetic regulatory mechanism in relation to gene expression. The review also highlights the mechanisms and regulation of adaptation to heat stress in animals and collates information related to various epigenetic markers to assess the heat stress response, thereby aiding in improving thermal resilience in animals.

The livestock sector, essential for maintaining food supply and security, encounters numerous obstacles as a result of climate change. Rising global populations exacerbate competition for natural resources, affecting feed quality and availability, heightening livestock disease risks, increasing heat stress, and contributing to biodiversity loss. Although various management and dietary interventions exist to alleviate these impacts, they often offer only short-lived solutions. We must take a more comprehensive approach to understanding how animals adapt to and endure their environments. One such approach is quantifying transcriptomes under different environments, which can uncover underlying pathways essential for livestock adaptation. This review explores the progress and techniques in studies that apply gene expression analysis to livestock production systems, focusing on their adaptation to climate change. We also attempt to identify various biomarkers and transcriptomic differences between species and pure/crossbred animals. Looking ahead, integrating emerging technologies such as spatialomics could further accelerate genetic improvements, enabling more thermoresilient and productive livestock in response to future climate fluctuations. Ultimately, insights from these studies will help optimize livestock production systems by identifying thermoresilient/desired animals for use in precise breeding programs to counter climate change.

The climate change-associated abnormal weather patterns negatively influences the productivity and performance of farm animals. Heat stress is the major detrimental factor hampering production, causing substantial economic loss to the livestock industry. Therefore, it is important to identify heat-tolerant breeds that can survive and produce optimally in any given environment. To achieve this goal, a clearer understanding of the genetic differences and the underlying molecular mechanisms associated with climate change impacts and heat tolerance are a prerequisite. Adopting next-generation biotechnological and statistical tools like whole transcriptome analysis, whole metagenome sequencing, bisulphite sequencing, genome-wide association studies (GWAS), and selection signatures provides an opportunity to achieve this goal. Through these techniques, it is possible to identify permanent genetic markers for heat tolerance, and by incorporating those markers in marker-assisted breeding selection, it is possible to achieve the target of breeding for heat tolerance in livestock. This review gives an overview of the recent advancements in assessing heat tolerance in livestock using such ‘omics’ approaches and statistical models. The salient findings from this research highlighted several candidate biomarkers that have the potential to be incorporated into future heat-tolerance studies. Such approaches could revolutionise livestock production in the changing climate scenario and support the food demands of the growing human population.

Given livestock’s crucial role in global food security and economic stability, the alarming threat of climate change calls for the implementation of effective mitigation strategies for climate-resilient livestock production. Management and nutritional strategies offer temporary relief, whereas genetic approaches represent a permanent solution. The role of genetic tools in enabling the development of climate-resilient livestock breeds is widely recognized. Genetic tools like microarrays, RNA-seq, omics, and GWAS can improve the understanding of livestock’s climate adaptability at a molecular level. These tools facilitate the identification of biomarkers for thermo-tolerance, bordering on climate-resilient livestock breeding. Among them, studies employing genome-wide association studies (GWAS) have increased in recent years. GWAS have the potential to improve the genetic basis of thermo-tolerance in heat-stressed livestock populations. GWAS have been used to identify candidate genes for complex and economically important traits in livestock. These include growth, reproduction, disease resistance, milk, meat, and wool production traits under heat stress conditions. This makes GWAS a useful tool for identifying biomarkers that can be incorporated in breeding programs through marker-assisted selection (MAS). The integration of these potential biomarkers into selection and breeding programs would allow GWAS to substantially refine breeding strategies, thereby advancing the climate-resilient potential and sustainability of the livestock sector. Furthermore, GWAS, when utilized along with emerging technologies like Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) for genomic prediction, can predict genetic aspects of livestock adaptation more efficiently and precisely. Thus, future studies should focus on integrated modeling approaches for improving the climate resilience of livestock without jeopardizing their production potential. Such an effort will contribute to sustainable livestock production as well as ensure food security for the growing human population amid changing climate conditions.

An eight-year-old, non-descriptive female dog that had not whelped before was presented to the Department of Veterinary Gynaecology and Obstetrics, Veterinary Clinical Complex, Rajiv Gandhi Institute of Veterinary Education and Research, Puducherry with a history of protrusion of a large mass through the vulva since ten days. Clinical examination revealed a hyperemic and oedematous mass in the vagina protruding through the vulval lips. Macroscopically, it was relatively well-circumscribed and measured 13×11×9 cm. Based on the history and clinical examination, the growth was tentatively diagnosed as a vaginal tumour and was excised by following the standard operative procedure. The cut surface of the mass was white, hard, and sticky with mucinous exudate. Histopathology revealed spindle and stellate cells within a myxoid stroma, diagnosed as fibromyxoma. The animal made an uneventful recovery after the surgical treatment.