Animal Molecular Breeding 2024, Vol.14, No.3, 196-206 http://animalscipublisher.com/index.php/amb 198 the abundance of specific microbial populations, such as an increase in lactate-producing bacteria and a decrease in acetate-producing bacteria. Additionally, key metabolic markers like isoleucine, methionine, and tryptophan are reduced under heat stress conditions, impacting feed consumption and milk production efficiency. 3.4 Influence on immune response Heat stress also influences the immune response in dairy cattle. HSPs, particularly HSP70 and HSP90, are involved in modulating immune functions (Guzmán et al., 2023). In channel catfish, HSP90 genes showed pathogen-specific expression patterns, indicating their role in immune responses (Xie et al., 2015). Similarly, in dairy cattle, the expression of immune-related genes such as bovine lymphocyte antigen and histocompatibility complex class II (DRB3) is downregulated during heat stress, while HSP70 and HSP90 are upregulated. These changes suggest that HSPs not only protect against thermal stress but also play a role in enhancing immune resilience. 4 Techniques for Analyzing Gene Expression in Heat-Stressed Cattle 4.1 RNA sequencing and transcriptomics RNA sequencing (RNA-seq) is a powerful technique used to analyze the complete transcriptome of an organism, providing insights into gene expression changes under various conditions, including heat stress. In dairy cattle, RNA-seq has been employed to identify differentially expressed (DE) genes and non-coding RNAs, such as microRNAs (miRNAs) and circular RNAs (circRNAs), in response to heat stress. For instance, a study on the hypothalamic-pituitary-mammary gland axis of dairy cows under heat stress identified numerous DE circRNAs, miRNAs, and mRNAs, highlighting the MAPK signaling pathway as a key player in the heat stress response (Zeng et al., 2023). Another study focused on the differential expression of miRNAs in buffalo heifers under heat stress, revealing significant changes in the expression of miRNAs and their target genes, which are involved in heat tolerance mechanisms (Yadav et al., 2021). 4.2 Quantitative PCR (qPCR) Quantitative PCR (qPCR) is a widely used method for quantifying gene expression due to its specificity, sensitivity, and reproducibility. It is particularly useful for validating RNA-seq results and for studying the expression of specific genes under heat stress conditions. For example, qPCR was used to validate the expression of DE miRNAs identified through RNA sequencing in dairy cows, confirming the downregulation of several miRNAs post-calving (Figure 1) (Webb et al., 2020). Additionally, qPCR has been employed to study the expression of heat shock proteins (HSPs) in different cattle breeds, revealing higher expression levels of Hsp90 in the Sahiwal breed compared to the Frieswal breed under heat stress, which may contribute to better heat tolerance in Sahiwal cattle (Deb et al., 2014). The research of Webb et al. (2020) illustrates the relative expression of different microRNAs (miRNAs) in dairy cows with high and normal body conditions at various time points relative to calving. It shows distinct patterns of miRNA expression, with significant differences between time points within each group and between the groups at specific time points. These variations suggest that miRNA levels are dynamically regulated in response to physiological changes around parturition, potentially influencing the health and metabolic status of the cows during this critical period. The trends indicate potential biomarkers for monitoring dairy cow health in relation to body condition and calving. 4.3 Bioinformatics tools for data analysis Bioinformatics tools are essential for analyzing the large datasets generated by RNA-seq and qPCR. These tools facilitate the identification of DE genes, pathway enrichment analysis, and the construction of gene regulatory networks. For instance, bioinformatics analysis was used to identify putative target genes and enriched biological pathways for DE miRNAs in dairy cows, revealing associations with cell cycle, insulin signaling, and lipid metabolism (Webb et al., 2020). Similarly, competitive endogenous RNA (ceRNA) networks were established to understand the molecular basis of heat stress response and lactation regulation in dairy cows. Tools such as geNorm and NormFinder are also used to evaluate the stability of reference genes for qPCR, ensuring accurate normalization of gene expression data (Lozano-Villegas et al., 2021).
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