Recent research on the transition period (TP) of dairy cows has highlighted the pivotal role of immune function in affecting the severity of metabolic challenges the animals face when approaching calving. This suggests that the immune system may play a role in the etiology of metabolic diseases occurring in early lactation. Several studies have indicated that the roots of immune dysfunctions could sink way before the “classical” TP (e.g., 3 weeks before and 3 weeks after calving), extending the time frame deemed as “risky” for the development of early lactation disorders at the period around the dry-off. Several distressing events occurring during the TP (i.e., dietary changes, heat stress) can boost the severity of pre-existing immune dysfunctions and metabolic changes that physiologically affect this phase of the lactation cycle, further increasing the likelihood of developing diseases. Based on this background, several operational and nutritional strategies could be adopted to minimize the detrimental effects of immune dysfunctions on the adaptation of dairy cows to the new lactation. A suitable environment (i.e., optimal welfare) and a balanced diet (which guarantees optimal nutrient partitioning to improve immune functions in cow and calf) are key aspects to consider when aiming to minimize TP challenges at the herd level. Furthermore, several prognostic behavioral and physiological indicators could help in identifying subjects that are more likely to undergo a “bad transition”, allowing prompt intervention through specific modulatory treatments. Recent genomic advances in understanding the linkage between metabolic disorders and the genotype of dairy cows suggest that genetic breeding programs aimed at improving dairy cows’ adaptation to the new lactation challenges (i.e., through increasing immune system efficiency or resilience against metabolic disorders) could be expected in the future. Despite these encouraging steps forward in understanding the physiological mechanisms driving metabolic responses of dairy cows during their transition to calving, it is evident that these processes still require further investigation, and that the TP—likely extended from dry-off—continues to be “the final frontier” for research in dairy sciences.

Livestock radiated out from domestication centres to most regions of the world, gradually adapting to diverse environments, from very hot to sub-zero temperatures and from wet and humid conditions to deserts. The climate is changing; generally global temperature is increasing, although there are also more extreme cold periods, storms, and higher solar radiation. These changes impact livestock welfare and productivity. This review describes advances in the methodology for studying livestock genomes and the impact of the environment on animal production, giving examples of discoveries made. Sequencing livestock genomes has facilitated genome-wide association studies to localize genes controlling many traits, and population genetics has identified genomic regions under selection or introgressed from one breed into another to improve production or facilitate adaptation. Landscape genomics, which combines global positioning and genomics, has identified genomic features that enable animals to adapt to local environments. Combining the advances in genomics and methods for predicting changes in climate is generating an explosion of data which calls for innovations in the way big data sets are treated. Artificial intelligence and machine learning are now being used to study the interactions between the genome and the environment to identify historic effects on the genome and to model future scenarios.

Milk has become a staple food product globally. Traditionally, milk quality assessment has been primarily focused on hygiene and composition to ensure its safety for consumption and processing. However, in recent years, the concept of milk quality has expanded to encompass a broader range of factors. Consumers now also consider animal welfare, environmental impact, and the presence of additional beneficial components in milk when assessing its quality. This shifting consumer demand has led to increased attention on the overall production and sourcing practices of milk. Reflecting on this trend, this review critically explores such novel quality parameters, offering insights into how such practices meet the modern consumer’s holistic expectations. The multifaceted aspects of milk quality are examined, revealing the intertwined relationship between milk safety, compositional integrity, and the additional health benefits provided by milk’s bioactive properties. By embracing sustainable farming practices, dairy farmers and processors are encouraged not only to fulfill but to anticipate consumer standards for premium milk quality. This comprehensive approach to milk quality underscores the necessity of adapting dairy production to address the evolving nutritional landscape and consumption patterns.

Stress in livestock reduces productivity and is a welfare concern. At a physiological level, stress is associated with the activation of inflammatory responses and increased levels of harmful reactive oxygen species. Biomarkers that are indicative of stress could facilitate the identification of more stress-resilient animals. We examined twenty-one metabolic, immune response, and liver function biomarkers that have been associated with stress in 416 Italian Simmental and 436 Italian Holstein cows which were genotyped for 150K SNPs. Single-SNP and haplotype-based genome-wide association studies were carried out to assess whether the variation in the levels in these biomarkers is under genetic control and to identify the genomic loci involved. Significant associations were found for the plasma levels of ceruloplasmin (Bos taurus chromosome 1—BTA1), paraoxonase (BTA4) and γ-glutamyl transferase (BTA17) in the individual breed analysis that coincided with the position of the genes coding for these proteins, suggesting that their expression is under cis-regulation. A meta-analysis of both breeds identified additional significant associations with paraoxonase on BTA 16 and 26. Finding genetic associations with variations in the levels of these biomarkers suggests that the selection for high or low levels of expression could be achieved rapidly. Whether the level of expression of the biomarkers correlates with the response to stressful situations has yet to be determined.